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• Landsat bands alone may not give adequate quality of LULC mapping in a heterogeneous landscape. • Remote sensing-derived indices and auxiliary data improve the accuracy of LULC mapping. • LULC maps classified under different classification algorithms have shown a significant discrepancy. Land use/land cover (LULC) information is regarded as one of the most important variables in global change studies. Several LULC classification algorithms are available with different levels of accuracy in LULC mapping under different geographical setups. Furthermore, different remote sensing (RS) based indices and auxiliary data have been reported to have contributed to the accuracy of LULC mapping. Hence, the main aim of this study was to compare the different ML algorithms for the LULC mapping and explicitly assess the potential contribution of different RS-derived indices and auxiliary data on classification accuracy in the Upper Tekeze-Atbarah (UTA) river basin in Ethiopia. The overall classifiers evaluation result revealed that random forest (RF) performed best and followed by K-Nearest Neighbour (KNN), Support Vector Machine (SVM), Artificial Neural Network (ANN), Maximum Likelihood Classification (MLC), and Classification and Regression Tree (CART). Compared to RF, the MLC method showed less accuracy by 16.2% (19.7%) in OA (kappa coefficient) respectively, which showed that the currently emerging ML classifiers contributed to an improvement in LULC mapping. The use of RS-derived indices and DEM as predictors together with the Landsat bands improved the overall accuracy and kappa coefficient by 5.5% and 7% respectively. Furthermore, the discrepancy in the classified LULC map from RF and other classifiers was compared at pixel-level and the result showed a considerable disagreement between the LULC maps. For instance, when the LULC map from RF and KNN are compared, only 80.6% of the area has the same LULC condition. This result reflects the potential discrepancy that could exist in LULC maps from different classifiers. The hydrological simulation under each of the classified map also resulted in a considerable difference in the major water balance components. In a conclusion, given the considerable difference in classifier performance and the potential propagation of errors in LULC maps to further applications such as water resources assessment, it is highly recommended to explicitly evaluate the available classifiers. Users should also harness the power of RS indices and auxiliary datasets for improved LULC mapping. [ABSTRACT FROM AUTHOR]

Humans have occupied the Alps over most of the Holocene. Yet, continuous records on the impact of using montane resources and landscapes are scarce or confined to segregated areas or periods. We present a high-resolution geochemical record of the last 4800 years from the ombrotrophic peatland Piller Moor in the Central Alps (Tyrolean Oberland, western Austria), using inductively coupled mass plasma spectrometry (ICP-MS) and highly efficient inter-calibrated portable X-ray fluorescence analysis (pXRF). Fluctuations of metal enrichment factors (EF) for lead (Pb), copper (Cu), zinc (Zn) and antimony (Sb), accumulation rates of anthropogenic lead (Pb anth AR) and mineral matter (MAR), based on titanium (Ti), are in line with archaeological and pollen evidence for human presence and environmental change. Periods of intensified, erosive land use are indicated by MAR around 4400 cal BP, 3400 cal BP and, very prominently, at 2400 cal BP. After low MAR in the early Middle Ages, soil disturbances reappear around 1200 cal BP (750 AD), after 200 cal BP (1750 AD) and during the 20th century AD. We found evidence that metallurgy was practised in the area as early as 4450 cal BP, again from 3500 to 2900 cal BP and episodically between 2400 and 1400 cal BP. The Central Alps were presumably a source of increased Pb-emissions in the post-Roman period from 1500 to 1400 cal BP (450–550 AD). Generally, our findings suggest that mining predates archaeological and historical evidence. Following a continuous increase since the Middle Ages, atmospheric Pb EF and Pb anth AR peak around 1980 AD. The record of mineral atmospheric input illustrates the notable impact of human activities on soil erosion and dust entrainment in the Central Alps. Furthermore, links between Little Ice Age cold phases and reduced human impact and mining are established. Our high-resolution peat-geochemistry data quantifies atmospheric deposition of mineral matter and Pb, which act as proxies for landscape evolution and metallurgy on a local and regional scale. It provides new insights and a deeper understanding of the interaction of climate, environment and humans in mountainous landscapes like the Central Alps. [ABSTRACT FROM AUTHOR]

Unbundled residential off-street car parking, where spaces are purchased or rented separately to housing, has been shown to reduce car ownership and use, and improve housing affordability. However, there is little understanding of the potential for unbundling parking in the context of residential apartment buildings, including the characteristics of apartment residents who are receptive to unbundling. This research explores the potential for unbundling off-street car parking based on a survey of apartment residents (n = 424) in Melbourne, Australia. The data was analysed using descriptive statistics and binary logistic regression modelling, supplemented by qualitative comments from survey respondents. Over one-third (35%) of apartment households were found to experience a mismatch between the supply and demand of their allocated off-street car parking, either having too much or too little parking relative to the number of cars they owned. Around 42% of apartment residents indicated receptiveness to unbundling off-street car parking. Living in a household with 2+ cars was found to increase the odds of being receptive to unbundling by over 3 times. Given the misallocation of off-street car parking relative to household car ownership in apartment buildings, the results imply that efforts could be directed towards unbundling off-street car parking from apartment housing, while carefully managing any associated risks. Future research could seek to explore the potential for unbundling car parking for other land uses and in other jurisdictions. • Draws on a survey of apartment residents (n = 424) in Melbourne, Australia. • 35% of respondents experienced a mismatch in their allocation of off-street car parking. • 42% of respondents indicated receptiveness to unbundling off-street car parking. • Living in a household with 2+ cars increased the odds of being receptive to unbundling by >3 times. [ABSTRACT FROM AUTHOR]

This study aimed to set up a life cycle assessment (LCA) approach at the level of individual animals to assess the effects of a 3-breed crossbreeding program on the environmental impact of cows. The study involved 564 cows, 279 purebred Holstein Friesian (HO) and 285 crossbred cows (CR), that originated from a 3-breed crossbreeding program based on the rotational use of Viking Red, Montebèliarde, and HO sires and kept in 2 dairy herds of northern Italy (224 and 340 cows/herd, respectively). The reference unit of the LCA model was the lifetime of cows, from the birth to culling or death. Data were collected at different levels: individual animal-based data referred to the whole life (birth, calving, dry, cull or death dates, and milk production); individual test-date collection of body measures and BCS, used to predict BW and to estimate energy requirements; common farm-based data concerning herd management (diets composition, and materials used). Data were used to compute DMI, milk and milk components production, gross income (GI), and income over feed costs (IOFC) pertaining to the lifespan of cows. An individual LCA-derived approach was set up to compute global warming potential (GWP), acidification and eutrophication potential (AP and EP, respectively), and land occupation (LO), which have been associated with different functional units (cow in her whole life or per day of life; kilograms of milk fat plus protein, and GI and IOFC [in euros] produced in the herd life). Data were analyzed using a generalized linear model including the fixed effects of genetic group (CR vs. HO), farm, and their interaction (genetic group × farm). Compared with HO, CR cows completed more lactations (+12%), had earlier first calving (−2 wk), yielded more fat plus protein in milk both in the lifespan (+8%) and per day of life (+4%). Concerning the environmental impact, when compared with HO herd mates, CR cows had nominal greater emissions per cow in the whole life, similar emissions per day of life and ∼3% lower GWP, AP, and EP per kilogram of fat plus protein yielded in lifespan. Income over feed costs per unit of emission tended to be ∼4% greater in CR compared with HO cows. Also, the use of land tended to be lower in CR compared with HO in most indicators considered. In conclusion, LCA could be adapted to represent individual animals. Moreover, managing dairy cows according to a 3-breed rotational crossbreeding scheme may be regarded as a strategy that can contribute to mitigate the emissions and to improve the environmental impact of dairy operations. [ABSTRACT FROM AUTHOR]

• LULC changes of three decades from 1991 to 2021 were examined and predicted. • Multi-spectral remote sensing data and RFT were utilized to generate LULC maps. • ACR were considered to analyze the categorical land use change detection. • Impervious land has expanded 10 times within 30 years and will increase in the future. The integration of multi-spectral remote sensing and GIS-based analysis is significant for studying land cover changes, providing valuable insights for informed land management and sustainable development. The present study aims to examine land use land cover (LULC) changes of three decades from 1991 to 2021 and predict the future LULC change in Binh Duong province, Vietnam to explore a future research direction on land use change and associated challenges in the study region. Multi-spectral remote sensing data and random forest tree (RFT) were utilized to generate LULC maps. Areal statistics and annual change rate were considered to analyze the categorical land use change detection. Statistical measures such as user's accuracy, producer's accuracy, kappa coefficient, and confusion matrix were employed to assess the accuracy of LULC classification. To predict future LULC and simulate the spatio-temporal change, we considered previous year LULC maps, independent spatial variables and a combined artificial neural network (ANN) multi-layer perceptron approach. The analysis revealed that there was a huge transition from agricultural lands to residential land with industry and commerce which resulting an expansion of impervious lands and a rapid decline of agricultural land as well as of scrub land and barren lands, and a changeability of forest and plantation, croplands, and waterbodies. Our study revealed that the impervious land has expanded 10 times within 30 years and will increase in the future. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of guiding a rocket-powered vehicle to land using aerodynamic and thrust controls. The vehicle initially glides towards the landing site, flying at an unprecedentedly high angle-of-attack to decelerate, thereby reducing the propellant needed for a later retro-thrust landing. The high angle-of-attack pure aerodynamic flight leads to highly nonlinear dynamics that have not been addressed by existing powered descent guidance methods. In particular, real-time optimization of the vehicle's landing trajectory has been very challenging. In this paper, a closed-loop guidance method is proposed that optimizes a restricted 6-degrees-of-freedom (6-DoF) trajectory in real-time. To remedy the difficulty caused by the highly nonlinear dynamics, the general propellant-optimal problem is regularized with two modifications. The first is to augment the angular velocity to the performance index, removing possible singularity arcs that cause numerical difficulties. The second is to parameterize the thrust magnitude with a piecewise-constant form, reducing the number of control variables to be optimized. The regularized problem is then solved with successive convexification to update the restricted 6-DoF landing trajectory in each guidance cycle. Monte Carlo experiments with aerodynamic and thrust dispersions are conducted to examine the proposed guidance method. • A new guidance method is proposed that uses both aerodynamic and thrust controls. • The guided vehicle can fly at unprecedentedly high angle-of-attack to decelerate. • The guidance method optimizes a restricted 6-degree-of-freedom trajectory in real-time. • The guidance problem is regularized twice to address the highly nonlinear dynamics. [ABSTRACT FROM AUTHOR]

[Display omitted] • Land use change profoundly impacts the migration of heavy metals (HMs) in the soil. • The comprehensive pollution index was in VGF>CVL>WSL>WDL. • Soil microbial and enzymatic activities did not directly affect HMs concentration. The accumulation of heavy metals (HMs) in soil has become a pressing global concern due to their persistent and non-degradable nature, resulting in the accumulation of toxic levels in the environment. In recent years, human activities have significantly altered land use patterns, leading to a marked increase in soil HM levels and subsequent land degradation. This research focused on four distinct land use patterns (vegetable fields (VGF), woodland (WDL), cultivated land (CVL), and wasteland (WSL)) commonly found in the Taojia River Basin, Hunan, China, which is facing severe HM pollution. Soil samples were collected from three different depths (0–10 cm, 10–20 cm, and 20–30 cm) to investigate HM distribution and intensity (cadmium (Cd), lead (Pb), copper (Cu), nickel (Ni), and zinc (Zn)), comprehensive soil pollution index, and their relationship with soil microbial and enzymatic activities. The results revealed that the Cd content exceeded the national standard for soil environmental quality, whereas concentrations of other HMs did not exceed the national standard across the four land use patterns. Most soil HMs were concentrated in the surface layer, with Cu, Pb, and Zn concentrations gradually decreasing with increasing soil depth. Conversely, Ni and Cd concentrations tended to increase with greater soil depth. There were significant positive correlations among HMs, indicating homogeneity among them. The pollution index across the HMs ranked as Cd > Ni > Zn > Cu and Pb, with land uses following the order of VGF (2.70) > CVL (2.12) > WSL (1.72) > WDL (1.63). Soil microbial and enzymatic activity was not the primary factor influencing HM concentration. The specific impacts of land use changes on soil HMs depend on management practices, local conditions, and the distribution characteristics of the HMs involved. [ABSTRACT FROM AUTHOR]

[Display omitted] • Introducing new combined models of MC-MCE-CA, MC-MLP-CA, MC-SW-CA and MC-LR-CA for the development of land use methodology, with emphasizing the nature and principles of them for modeling of land use changes studies. • Comparing the capabilities of the new models with the traditional CA-Markov model in terms of the overall accuracy of the models and the basis of their implementation in land use change studies. • Monitoring and modeling of land use changes from the areas of industrial and agricultural activities in a long time range of about half a century (1989-2037). Land use change is one of the most significant environmental issues in many countries and is the main reason for ecosystem changes. This issue is one of the most important environmental crises in Iran due to the lack of planning and inappropriate human use of the natural environment. Many parts of Iran, especially the Urmia Lake basin, are involved in challenging land use changes. The trend of land use changes extracted from Landsat images in the Urmia lake basin with overall accuracy and Kappa coefficient of more than 85 % and 80 % respectively shows that during the 32-year period (1989–2021) agricultural lands, built-up lands and barren lands respectively 3330.83 km2, 466.86 km2 and 5325.8 km2 have increased in area. On the other hand, the areas of vegetation and water bodies decreased by 6625.79 km2 and 2497.7 km2, respectively. The current trend of land use changes in Urmia basin based on all models of Markov chain-Multi Criteria Evolution-Cellular Automata (MC-MCE-CA), Markov Chain-Multilayer Perceptron-Cellular Automata (MC-MLP-CA), Markov Chain-Sim Weight-Cellular Automata (MC-SW-CA), Markov Chain–Logistic Regression-Cellular Automata (MC-LR-CA) indicate the continuation of changes until 2037. Meanwhile, based on the most accurate models such as MC-MLP-CA and MC-LR-CA models, agricultural lands will increase by 1436.60 km2 and 1258.33 km2, built-up lands by 75.23 km2 and 65.52 km2, and barren lands by 808.94 km2 and 856.90 km2 respectively. Also, the vegetation lands will be reduced by 1890.64 km2 and 1755.31 km2 and water bodies by 430.13 km2 and 425.44 km2. In general, the results showed that MC-MLP-CA, MC-LR-CA, MC-SW-CA, MC-MCE-CA models with Overall Kappa 89.89, 87.09, 84.52 % and 84.84 and Percent of Correctness 93.65, 93.09, 91.52 and 91.77 respectively, with higher accuracy than the CA-Markov model (Overall Kappa = 81.49 % and Percent of Correctness = 87.49 %) are more effective for land use changes modeling. [ABSTRACT FROM AUTHOR]

• Lake Edku, Egypt, sequester carbon which worth of $1.7 million. • NDVI and SAVI indicated that carbon stocks were best predicted during year of 2022. • Land use classification showed that many coastal areas were lost since 1994. As a case study to assess changes of blue carbon stocks among different land use classes; lake Edku, Egypt, was selected at the north Mediterranean coast of Egypt. Landsat 5 and 8 satellites imageries (1994, 2008, and 2022) were downloaded and upon classification, there were five land use classes identified: artificial surfaces (including barren and urban areas), crops, flooded vegetation, sabkha, and water. Using InVEST model, the quantity and economic value of the coastal blue carbon sequestration (CBCS) service offered by lake Edku were modelled. Based on land use classification of lake Edku, those area that were classified as surface water and croplands were decreased from 1994 to 2022. On the other hand, aerial coverage of the artificial surface increased. Analyses for Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegeation Index (SAVI) indicated that the amount of carbon stocks estimated by ground inventory was best predicted during year of 2022 (R2= 0.449, P value < 0.01). Our economic analyses of CBCS provided by lake Edku between 1994 and 2022 was 0.6507 (106 Mg C ha−1), which has a value of about $49 millions. Per year, lake Edku sequester carbon that worth about $1.7 million. Our study concluded that CBCS service can hasten the adoption of wetland rehabilitation measures, which have a favourable effect on climate regulation. [ABSTRACT FROM AUTHOR]

In developing countries, household credit constraints are determining factors affecting the efficient allocation of land resources. Digital financial inclusion is a new type of digital financial business by providing financial services through Internet technology. It broadens the information dissemination channels, provides more nonagricultural employment opportunities, and lowers the household credit constraint. By using data from Chinese farm households, we find that digital inclusive finance affects income of renting out households and expenditure of renting in households through credit mechanisms. Developing digital inclusive finance is a method to promote market-oriented land transfer and the effective utilization of land resources. [ABSTRACT FROM AUTHOR]

This study observes and records land cover changes in Al-Baha to track urban growth. The study develops a schematic vision of urban mass's current and future shape and distribution and its growth to achieve sustainable urban development, reduce service and social differences between city areas, and integrate urban and rural areas. The study uses inductive methods to monitor urban developments, population growth, and land use through Al-Baha's structural schemes by extracting digital data from satellite imagery to survey historical land cover changes. The mapping software ArcGIS v10.8 processed these digital data and the final map compositions. Through this urban mass study, the research predicted city growth and development. Capabilities and functions must shape urban and rural-urban communities. The development must also consider the National Urban Development Strategy, the relative importance of rural-urban communities, and their expected functional role in influencing the development of small rural communities adjacent to them to reduce migration from rural areas near the city. The study highlighted changes in city land coverage. Al-Baha expanded from 1982 to 1995. Al-Baha's transformation from village to city accelerated, increasing its area from 31 km2 to 44 km2. Many villages beyond 40 were included in the decisions. From 2006–2021, the city's area grew 221%. It increased from 60 km2 to 133 km2 in an urban area, indicating false urban growth. The study stressed the importance of geographic information systems (GIS) and remote sensing (RS). The study recommends urban development in suitable areas because agricultural development is not feasible, especially in the northeast. Land use changes should be prevented by planning regulations because these agricultural areas are essential. Helping urban development move away from agricultural areas, especially on the eastern axis, is crucial. Create new urban centers along Al-Baha's western cliff to attract residents and relieve pressure. Limited linear expansion, especially in the northeast, and more expansive urbanization are also significant. Maps should also show when the Al-Baha region's expansionary scope changed and the urban boundaries that had to be reached by a specific time while development plans were efficiently monitored. [ABSTRACT FROM AUTHOR]

[Display omitted] • Of 414.5 million livers analyzed; 224,872 cattle were infected with F. hepatica. • Infected livers were registered in 194 Brazilian municipalities in 2002, and 747 in 2020. • There was a reduction in forest areas and an increase in cattle livers infected with F. hepatica. • Fasciola hepatica was introduced to the Cerrado, Pantanal, and Amazon Forest biomes. • Significant territorial dispersion of infected cattle with F. hepatica was observed. Fasciolosis is caused by parasites of the genus Fasciola, affecting animals and humans worldwide. In South America, the disease is a result of infection with Fasciola hepatica and although animal infections are more frequently reported, the full extent of the impact on human health due to underdiagnosis remains uncertain. This study analyzed changes in land use and the distribution of F. hepatica in bovine livers in Brazil over 18 years. Data on land use and land cover were collected from the Mapbiomas Project. Data on 414,481,963 slaughtered cattle and condemned livers due to F. hepatica infection were obtained from 4,433 municipalities. Joinpoint analysis was used to study the time series, and the Susceptible-Infected-Recovered (SIR) model was utilized to explore the behavior of F. hepatica infection. In the North, pasture areas significantly increased (P = 0.000001), while forested areas decreased (P = 0.000001). The midwestern and northern regions concentrated the highest number (>290 million) of cattle slaughtered in Brazil. More than 2 million bovine livers were infected by F. hepatica. The infected cattle originated from 194 municipalities in 2002, increasing to 747 in 2020. We consider that the changes in land use and intense cattle transportation may have caused the expansion of F. hepatica. The SIR model analyzed the spread of the disease looking at all six biomes: Caatinga, Amazon Forest, Cerrado, Pantanal, Atlantic Forest, and Pampa. Moreover, this infection not only threatens the health of animals but is also a major concern to biodiversity and vulnerable human communities in South America. Emblematic biomes such as the Amazon basin already face challenges with logging, desertification, and loss of biodiversity. Therefore, strategies for mitigating infection should include controlling illegal pasture areas, establishing health inspections of animal transport, quarantine of newly arrived animals, and livestock zoning, as well as clear One Health policies. [ABSTRACT FROM AUTHOR]

Leveraging a reform that assigns central inspectorates to local units in China to oversee industrial land transactions, this study examines the effects of unleashing the local government's influence on land prices using a difference-in-differences design. Our research provides compelling evidence that the reform leads to an additional 50% increase in industrial land prices and significantly enhances the productivity of local industrial firms. The rise in land prices can be attributed to an increase in market-oriented transactions. Additionally, we discover an improvement in the quality of new entrants and a reduction in resource misallocation following the reform. By demonstrating the positive externalities of central supervision on local government intervention in the industrial land market, our findings suggest that, in certain cases, central inspection can mitigate distorting behaviors of the local government in input markets. This, in turn, facilitates the screening of productive entrants and hinders investments by unproductive incumbents, thereby improving the overall productivity of economic entities. [ABSTRACT FROM AUTHOR]

The mining industry plays a pivotal role in the global transition towards clean energy, driven by the escalating demand for critical elements like lithium. However, this growth raises profound environmental concerns, particularly regarding land use, global warming potential, water consumption, acidification, eutrophication, and toxicity. Life Cycle Assessment (LCA) has historically relied on approximations and theoretical methods, resulting in systematic underestimations of these impacts. This study begins to address part of this discrepancy by leveraging remote sensing technologies to gather empirical evidence. Focusing on the Greenbushes mining site in Australia, a comprehensive investigation was conducted to quantitatively evaluate the direct land use impact from satellite imagery over the life of the project. Comparative analyses were performed against various mid-point Life Cycle Impact Assessment (LCIA) methods. The findings unequivocally reveal a substantial under-reporting of the land use impact, highlighting the critical need for more accurate assessments in the context of mining activities. This research underscores the importance of empirical data in refining our understanding of the environmental footprint associated with mining operations, particularly in the critical context of clean energy transition. The study emphasises the imperative to reevaluate and adjust existing approaches to accurately account for the full scope of environmental impacts associated with mining operations. [ABSTRACT FROM AUTHOR]

In recent years, GPS data on truck movements have become much more available, leading researchers and practitioners to leverage these sources to generate a wealth of data and information related to truck OD flows. In this study large amount of truck GPS data used to investigate characteristics of freight transportation in particularly OD land uses and freight vehicle classes. Aiming to realize the freight flows characteristics of the Chicago Metropolitan Agency Planning (CMAP) region. The data are used primarily to gain insight into the nature of urban goods movement and the distribution of retail goods. The main objective in this respect is analyzing urban freight flows and retail goods movement. The data-driven analysis generates a number of interesting findings regarding the nature and volume of trips by light-duty, medium-duty, and heavy-duty truck that serve various types of retail and industrial functions are generated. The design of this study especially its land use data fusion aspect is expected to benefit both practitioners and researchers as they plan future data collection, model calibration and urban freight studies. [ABSTRACT FROM AUTHOR]

Substantial loss of biodiversity and the proliferation of invasive alien species can occur due to land cover anthropogenic transformations on islands. However, the effect of anthropogenic habitat modifications on the distribution of insular freshwater microcrustaceans is unknown. In the present paper, we examine the consequences of human activity on the insular diversity of microcrustaceans in the context of the theories of island biogeography and intermediate disturbances. The samples were collected in Madeira Island at 38 freshwater sampling sites with different anthropopressure. Morphology-based species identification of the copepods and cladocerans was supplemented with genetic analysis (COI) in some species. To estimate the species richness of the island, rarefaction, and extrapolation methods were used. Canonical Correspondence Analysis (CCA) was applied to assess the influence of geospatial and environmental variables on the species distribution. A total of 20 species belonging to six families were identified, of which 16 species are new to Madeira. There was low similarity between the fauna recorded and known previously on the island. The observed species richness was higher than the predictions by the island biogeography models for Madeira. CCA revealed a strong influence of anthropogenic land use on crustaceans. Anthropogenic transformations locally led to the depletion of fauna, but on the island scale they contributed to the increase of species richness including seven putative alien species. An increase in the artificial land cover and a decrease in the forest areas could lead to a further shift in the domination of non-indigenous microcrustaceans. [ABSTRACT FROM AUTHOR]

Catchment land use/land cover (LU/LC) is one of the crucial determinants of the water quality and condition of biota in aquatic environments. The aim of this study was to investigate how LU/LC in lake catchments influences the physicochemical and biological indicators used to assess the ecological status of lakes in Poland and whether these relationships vary depending on the spatial range. We analysed the catchment LU/LC forms of 114 flow-through lakes in three spatial ranges, i.e., a 100 m-wide buffer strip (BUF100), the direct catchment (DIR), and the total catchment (TOT). The water quality and biological variables were derived from the state monitoring conducted in the period 2012–2013. The redundancy analyses (RDA) and the Monte Carlo permutation tests depicted that the strength in explaining the parameter followed the order: TOT > DIR > BUF100 for physicochemical parameters, DIR = TOT > BUF100 for phytoplankton indicators and BUF100 > DIR > TOT for macrophyte indicators. In the direct and total catchment, the proportion of arable lands was decisive in shaping the macrophyte and physicochemical status, while the proportion of artificial surfaces affected phytoplankton status. It was also found that forested buffer zones promoted good macrophyte ecological status. The other types of LU/LC, i.e., meadows and pastures, wetlands, and surface waters exhibited little to no or marginal impact on the physicochemical and biological indicators, regardless of the spatial scale considered. Our results contribute to the rational planning of land development in lake surroundings, including the design of protected areas for inland waters. [ABSTRACT FROM AUTHOR]

This study investigated potential relationships between land-use structure in the catchments of six southern Baltic coastal lakes that differ in the level of hydrological connection with the sea and the lakes' trophic states. Our results indicate that three types of catchments can be distinguished, each of which has a high contribution of agricultural areas, plus: (i) considerable contributions of wetlands and water bodies (C1); (ii) a large contribution of wooded and seminatural habitats (C2); or (iii) a considerable contribution of artificial surfaces (C3). Correlations were analysed between land-use types and single-parameter Carlson's trophic state indices of lakes (TSI Chl , TSI TP , TSI SD , TSI TOC). Type C2 clearly differed from the others and was linked with the lowest trophic state index values. The other two catchment types were similarly related to the fertility of the coastal lakes. The results show that the analysed lakes' levels of connection with the sea do not affect the trophic state of their waters. Catchment structure, analysed using CORINE Land Cover data, is significantly linked with TP and TOC values, but it does not relate to Secchi depth or chlorophyll content of water in the lakes. Wetlands (especially peat bogs) in the catchment area most strongly reduced the phosphorus and organic carbon content of lake water. Furthermore, comparable contributions of natural vs. anthropogenic components (∼1:1) are associated with a lower trophic state of water. The presented results may be important for shaping the proper management of various catchment types in the future, especially when implementing climate change mitigation strategies. [ABSTRACT FROM AUTHOR]

Transit-oriented development (TOD), characterized by a high and mix development around public transport stations, is gaining traction as a sustainable way to support the use of public transport for regional trips and active transport for local trips. To support integrated land use and transport planning, several TOD typologies have been developed, with a focus on land use and transport characteristics, and more recently walkability. While TOD aims to motivate the use of active modes, including cycling, assessments of bikeability have been left out of TOD typologies. To fill this gap, this study seeks to develop a bicycle-oriented TOD typology that combines indicators related to the cycling environment with traditional land use and transport indicators. Using Montreal, Canada as a case study, 14 indicators are generated to develop a TOD typology oriented on bikeability and the 114 public station areas are grouped into seven distinct clusters. The results demonstrate that the addition of bikeability criteria to the TOD typology helps discriminate the different types of stations based on their current bikeability and bikeability potential. The proposed framework enables identifying and prioritizing targeted interventions to station development. This study is of relevance to planners and researchers aiming to integrate cycling in the development of TOD. • Development of a TOD typology oriented on bikeability applied to Montreal, Canada. • Addition of a bikeability criteria to the node-place model. • Generation of seven clusters with distinct cycling environment and bikeability potential. • Recommendations of strategic prioritization of targeted interventions to station development. • Framework relevant to support integrated public transport and cycling planning. [ABSTRACT FROM AUTHOR]

[Display omitted] • A novel approach to track emissions using nonparametric analysis. • Population growth has a significant impact on GHG emissions. • The increase in population size significantly corresponds to higher GHG emissions. • A significant and negative impact of economic growth on GHG emissions is observed. • Forest density has a positive and significant effect on GHG emissions. The rising levels of global GHG emissions underpin climate change, hence, taking an appropriate inventory of the drivers and patterns of anthropogenic emissions remains crucial to mitigating global climate effects. However, there are conflicting views in the literature on the relationship between respective drivers and GHG emissions due to the lack of robust analysis that accommodates the interaction of all significant drivers. We use novel estimation techniques to decipher the 26-year inventory of GHG occurrences and simultaneous assessment of interactions in 50 countries stratified based on socioeconomic developments over the period 1990–2018. This study highlights different drivers of GHG emissions under broader categories such as population, economic development, forest density, and agricultural practices. Non-parametric estimations roughly confirm the magnitude of the influence of forests, agriculture, and land-use intensity on GHG emissions, ultimately tracking the most significant emission sinks. [ABSTRACT FROM AUTHOR]

The process of urbanization is inevitable and its higher rates have been observed in the less developed nations. It has impacted the socio-economic as well as environmental condition of the urban system. The present study intends to demonstrate a methodological framework to utilize the computer applications, like GIS and remote sensing, for analyzing the pattern of urbanization and its impact on the environmental and climatic condition of the study region. The geospatial data has been collected from the satellite imagery and the data pertaining to social and environmental conditions has been collected from the reports obtained from the government agencies. The overlay analysis using GIS has been performed to understand the interactive pattern of the land use and land cover change. Further, the interdependence among variables has been established using regression analysis method. The results of the analysis have been presented using tabulation and graphical methods. [ABSTRACT FROM AUTHOR]

Caprine herding in the hyper-arid zone of the Southern Levant emerged in the early Holocene during a brief moist episode (∼9500 years ago) within semi-permanent Middle PPNB settlements that depended on herding, farming, and hunting/foraging, organized within a transhumant land use strategy. With the onset of much drier conditions (∼9200 years ago) these Desert Neolithic settlements were abandoned in Late PPNB times giving way to Timnian groups that followed a more mobile settlement strategy with an emphasis on herding accompanied by range expansion. Through introducing a case study of the Desert Neolithic site of Ayn Abū Nukhayla and a deep sounding in a nearby dry lake bed, climatic-environmental fluctuations, human demographics, resource availability and land use strategies are evaluated as interwoven effects relative to the progressive shifts seen between prehistoric human populations and caprine herds. And these changes are viewed in the context of cultural macroevolutionary theory, specifically in the framework of Niche Construction Theory (NCT), in weighing the differential influences of human agency and natural selection on the process. [ABSTRACT FROM AUTHOR]

The present study seeks to better understand the coupling of social and biophysical systems during the late Pleistocene and Holocene, a period characterized by changing interglacial conditions as well as human population expansion and intensified ecosystem management. The approach consists of a combination of patch-based archaeological survey methods, sediment column sampling for paleoenvironmental data, geospatial analysis, and machine learning for chronological unmixing, allowing the systematic evaluation of the distribution and intensity of prehistoric land use in the study area of eastern Mediterranean Iberia. Occupational and Land Use Intensity maps developed from continuous distributions of surface artifacts as well as a summed probability density curve developed from 14C dates indicate low but steady human presence in the study area during the Middle Paleolithic and Upper Paleolithic with a marked decrease of human presence across the Pleistocene/Holocene boundary. The Early (and Middle) Neolithic saw the most ubiquitous and intensive occupation of the study area followed by a significant decline during the Late Neolithic/Chalcolithic. The charcoal analysis also supports this pattern. Early Neolithic farming strategies may not have been damaging initially during the climatic regime of the Early Holocene but exacerbated the impacts of higher temperatures and summer droughts, with a loss of the most productive farmland, seen at the onset of the Late Neolithic. Similar boom-bust population trends have been documented throughout Europe during these same time spans and may indicate a recursive interaction or "coupling" between global and regional climate events and human land use strategies. [ABSTRACT FROM AUTHOR]

Critical to the survival of island-based human societies is their resilience and adaptation to volcanic hazards. We here evaluate pre-Hispanic (before 15th century AD) land use patterns on the volcanic island of Tenerife, Canary Islands, Spain using obsidian hydration dating (OHD). The samples studied include archaeological artifacts and natural rock chips from multiple sites of different elevation and micro-climate settings. We systematically collected samples from the southern dry area around Barranco de las Monjas in the Bandas del Sur. These include a total of 28 isolated artifact scatters (here, a scatter is defined as a minimum spatial unit of artifacts distributed spatially limited range on the surveyed surface), one dwelling, and several pyroclastic deposits containing obsidian clasts. We also collected several artifacts adjacent to a large obsidian flow of Tabonal Negro in the Las Cañadas Caldera. Unsystematic surveys in north of Mt. Teide identified large obsidian outcrops located at Tabonal de los Guanches and Charco del Viento. Size differences among surface-derived obsidian artifacts (i.e., Bandas del Sur, Las Cañadas Caldera, Icod Valley) suggest that pre-Hispanic groups utilized obsidian from multiple outcrops over wide areas. Hydration analysis on 136 obsidian flakes collected from both surface and buried contexts showed only minor obsidian hydration rims (5% of total samples) and varied mean rim thicknesses (0.6–3.5μ). The low percentage of hydration rim formation may be caused by environmental factors such as wind erosion, thermal effects from volcanic or natural ground fires, or due to obsidian geochemistry (low SiO 2 and water content of phonolitic obsidian). Surface-collected obsidian flakes from the southern dry area do contain hydration rims along internal fissure. The estimated hydration rates from these samples can provide an approximate age when compared to buried obsidian artifacts with associated radiocarbon dates. [ABSTRACT FROM AUTHOR]

The subterranean estuary (STE) is a recognized reactive biogeochemical zone at the groundwater–seawater interface in coastal regions. However, few studies have explored dissolved organic matter (DOM) and nutrient processes in buried organic-rich STEs (with up to 20 % of organic matter content), despite their potential contributions to coastal water hypoxia and greenhouse gas emissions. This study conducted controlled laboratory experiments to investigate the physicochemical controls on DOM and nutrient processing in organic-rich STEs, considering variations in groundwater nitrate (NO 3 –) concentrations, salt concentration, seawater ions, and incubation times. Results showed elevated levels of dissolved organic carbon (DOC) and dissolved organic nitrogen (DON) in pore water, primarily from particulate organic matter (POM) degradation that originated from decayed vascular plants. POM-to-DOM degradations further resulted in the accumulation of ammonium (NH 4 +) and highly unsaturated compounds in all treatments. The addition of high-ionic-strength treatments (e.g., seawater and sodium chloride [NaCl] solution) reduced DOC solubility and selectively removed dissolved aromatic compounds in porewater. The cation-rich seawater shifted the porewater NH 4 + generation pathway from predominantly biological (re)mineralization in freshwater to abiotic (desorption via ion exchange) pathways in the saline water setup. Orthophosphate (PO 4 3−) dynamics were likely to be influenced by the iron-rich sediment surface in both freshwater and saline water scenarios. Our experiments further indicated that the long-term incubation enriched DOM concentration with a high degradation state. This work demonstrated that organic-rich STEs are significant sources of less labile DOM and NH 4 + to coastal waters. In the context of global climate change, our results illustrate the sensitivity of DOM and nutrient biogeochemical cycling in STEs to salinization and altered residence time, consequently affecting the quantity and quality of DOM and nutrients transported to coastal waters. [ABSTRACT FROM AUTHOR]

Land Use and Land Cover (LULC) mapping products are essential for various environmental studies, including ecological environmental assessments, resource management, urban planning, and climate change. Satellite remote sensing allows for the efficient acquisition of large-scale land use/land cover change information, enabling the creation of accurate LULC mapping products. The article summarizes the basic information, classification systems, application fields, challenges, and trends of 107 satellite LULC products (59 general and 48 thematic products). In terms of spatial scale, there are 56 global, 16 continental and 35 national products, with the spatial resolution ranging from 1 m to 100 km. China's SinoLC-1 is the only product with 1 m spatial resolution. Meanwhile, the temporal frequency of the 54 products is from 1 to 10 years, with 52 single-date products also available. Dynamic World provides a near real-time global LULC mapping service. Significant differences exist between the various LULC products, and the differences in classification schemes are one of the primary factors leading to inconsistency and uncertainty. Most LULC products based on remote sensing use the Land Cover Classification Systems (LCCS) developed by the Food and Agriculture Organization of the United Nations (FAO), but the detailed classification is often absent for categories other than forests. And distinct LULC products find applications across various study domains that span different scales. Currently, the classification system, temporal and spatial resolution, product accuracy, and validation datasets remain constraints to applying LULC products. However, LULC products have been gradually advancing towards finer classification and higher spatial and temporal resolution, with the use of deep learning, cloud computing, and multiple data sources becoming a major trend. This article can assist users in choosing the most suitable LULC mapping product for specific applications and requirements by providing comprehensive information and guidance. [ABSTRACT FROM AUTHOR]

• Demonstrates the method and merit of multi-sensor image fusion for LULC classification. • Generates new databases for LULC classifications of mining region using deep learning algorithms. • Comparative evaluations of an DCNN and DNN-based LULC classification are conducted. • Performances of the DCNN algorithm with the fused and unfused datasets are compared. Accurate land use/land cover (LULC) classifications using satellite data is a challenging task due to the limited spatial and spectral resolutions of different satellite data. Moreover, the challenge is more severe for LULC classification of mining regions as no standardized spectral signature is available for the detection of coal mining regions. Thus, the current study aims to design deep learning algorithms using fused data of three satellite sensors (LISS-IV, Landsat-8, and Sentinel-2A) for LULC classification of mining regions. The fused image was derived from three satellite sensors using a discrete cosine transform (DCT) with a spatial correlation approach. A comparative evaluation of deep convolutional neural network (DCNN) and deep neural network (DNN) models in LULC classification of mining regions is conducted. Moreover, the performances of the models with fused data are compared with the performance of the same model with individual sensor data. The study area chosen to execute the work is Jharia Coalfield, which comprises five key LULC types, viz. barren land, coal mining region, built-up area, water body, and vegetation. A total of 6000 image samples of 6 × 6 sizes and 216,000 pixels were used to train and validate the DCNN and DNN models, respectively. That is, the DCNN model uses the object dataset and DNN uses the pixel dataset for model training and validation. The DCNN model achieved high training and validation accuracies (99.8% and 99.2%), while the DNN model achieved relatively lower accuracies (85.3% and 81.8%). The study evaluates the performance of both models further by employing confusion matrix parameters to measure accuracy, error, precision, and recall for each class. The results reveal that the DCNN model consistently outperforms the DNN model, showcasing accuracy, error rates, precision, and recall ranging from 99.83% to 99.99%, 0.01% to 0.17%, 99.52% to 99.99%, and 99.40% to 99.99% on the training dataset, and 99.50% to 99.99%, 0.01% to 0.50%, 98.35% to 99.99%, and 98.33% to 99.99% on the validation dataset, respectively. In comparison, the DNN model demonstrates values ranging from 90.36% to 99.90%, 0.01% to 9.64%, 75.10% to 99.53%, and 66.99% to 99.99% on the training dataset, and 88.50% to 99.94%, 0.06% to 11.50%, 72.25% to 99.66%, and 62.50% to 99.99% on the validation dataset. These findings showed that the DCNN classification algorithm outperforms the DNN classification algorithm. Moreover, the comparative performances of the DCNN model with different datasets indicate that the model with fused images outperformed the model with individual sensor images. [ABSTRACT FROM AUTHOR]

This research aims at determining and analysing the causes and consequences of desertification in the middle zone of Wadi Fatimah using satellite images, climatic data, and topographic maps. The climatic parameters such as temperature, rainfall, and global reference evapotranspiration (ET0) indicated common severe arid conditions in the study area. The CORONA images acquired in 1967 and 1979 along with the topographic map of 1971 helped define the initial morphologic features and anthropogenic regimes. Analysing the various spatial datasets implied that the inappropriate management of water resources has resulted in changes in the anthropogenic regimes in the middle zone of Wadi Fatimah. These changes have triggered a chain of desertification processes such as degradation of the vegetation biomass and wind activities. These processes have transformed 15.3 km2 of agricultural farms into abandoned lands. Nineteen km2 of bushes have disappeared as well. The degradation of both agricultural and natural vegetation has exposed soils to intense wind erosion that detaches, transports and deposits sand in areas of low elevations. Accordingly, sand accumulations have massively expanded from 16.4 km2, as monitored by 1967 CORONA images, to 40.8 km2, as monitored by SPOT in 2013. This research emphasises that the middle zone of Wadi Fatimah has been experiencing remarkable changes in its morphologic and environmental characteristics in response to serious desertification processes. These processes are strongly linked to many anthropogenic interventions. It became a necessity, then, to redefine, study and assess the various anthropogenic parameters and their relative roles in desertification processes to combat desertification hazards and enhance sustainable environmental context in the middle zone of Wadi Fatimah. [ABSTRACT FROM AUTHOR]

This study investigates the impact of Payments for Watershed Ecosystem Services (PWS) on the sustainable utilisation of cropland and crop security in Huangshan City, which is the primary implementation area for the Payments for Xin'an River Watershed Ecosystem Services pilot in China. Using a two-stage analytical framework along with a quasi-natural experiment, the research examines the policy's effectiveness in Huangshan City. In the initial stage, the directional distance function and global Malmquist-Luenberger index (DDF-GML) model are employed to calculate the agricultural green total factor productivity (AGTFP), representing sustainable management of cultivated land. Concurrently, the study constructs unobservable counterfactual paths using the synthetic control method (SCM) to evaluate impacts on land use practices. The findings show an increase in Huangshan City's AGTFP from 1.118 in 2010 to 1.823 in 2020. Quantitative assessments indicate that the policy contributed to a 15.3% rise in AGTFP in the PWS cohort compared to the control group. Though initial decreases were detected during three pilot intervals, a consistent upward trajectory in AGTFP was identified, suggesting that PWS encourages crop stability and the sustainable development of arable land. Further support from permutation, regional, and temporal placebo examinations affirm these conclusions. This work implies that PWS may be extended to other agriculturally vulnerable regions to foster a balanced alignment between sustainable growth and the enhancement of crop security The assessment focuses on policy lessons that could inform broader sustainability strategies. [ABSTRACT FROM AUTHOR]

Transport planning has recently gained increased attention due to its potential alignment with human-centered justice theories, particularly the Capability Approach. However, the existing literature lacks quantitative measurements of the interaction between effective factors that contribute to the development of individuals' capabilities, specifically for those living in urban areas. This study aims to address this gap by proposing a bottom-up model within the general framework of the capability approach and sufficientarianism. Through a survey of 1096 individuals in Tehran, Iran, this research examines the impact of individual characteristics, the living environment, and transport and mobility options on residents' capabilities using the Structural Equation Modeling (SEM) technique. Therefore, the study evaluates one model for the entire population and two sub-groups defined by high and low capability levels. The findings indicate that individual characteristics significantly predict the level of capabilities, with a stronger effect observed in the low-capability group. Also, individual characteristics positively affect the environmental constructs, with a stronger effect observed among the low-capability group. Importantly, the low-capability group experiences a mismatch between their level of education, job status, and income level. Regarding environmental factors, the road network, public transport performance, land use-transport system integration, land use diversity, and land use spatial distribution exhibit a considerable relationship with residents' capabilities. Additionally, it has been demonstrated that active transport modes have a greater impact on the capabilities of low-capability groups. These findings provide valuable insights for policymakers to develop a just prioritization process for urban transport planning. • The study provides a model within the capability approach and sufficientarianism to measure the capability of urban residents. • The model measures the impact of individual characteristics, living environment, and mobility options on capability level. • Effects of factors on capability and their interactions were investigated using Structural Equation Modeling (SEM). • High-capability group composed of 18-45-year-olds in higher income deciles with better employment and education level. • Low-capability group experiences a mismatch between education, job status, and income level. [ABSTRACT FROM AUTHOR]

Landing on small-bodies is a very challenging problem that requires high degrees of robustness and autonomy. Being able to perform simulations with great flexibility and accuracy is paramount for the development and design of landing systems. To this end, contact dynamics plays a fundamental role and is often handled by complex tools that require large amount of development and validation efforts and very specific expertise. In the last decade, the Visual Effects (VFX) industry has developed numerous suites that deal with contact dynamics frameworks. In this work, the possibility of leveraging on the work of the VFX industry by using Blender, one of these tools, as the source for the contact dynamics modelling is investigated. This research focuses on the description of the methodology used for the landing simulations and the validation of the tool developed. A step-by-step guide through the simulation setup is given, discussing how the wrapping GNC simulator and Blender interact. Validation tests for the different parameters and dynamic models involved in the simulations are also presented. The results refer to the landing of a CubeSat in the crater region of an asteroid. In particular, the artificial crater that will be generated on Dimorphos by NASA's DART impact in late September 2022, is considered in the simulations presented in this work. Safety maps are generated by post-processing these results, and are used to assess different landing strategies or site-selection criteria on the Dimorphos crater study case. Finally, the role of the developed tool in optimising the use of space resources and its contribution to landing design strategies is discussed. [ABSTRACT FROM AUTHOR]

This work addresses the challenge of classifying watersheds to support land use policy-making in rapidly developing, wet tropical regions, using a case study of the Brantas River Basin, Java, Indonesia. Hierarchical Clustering on Principal Components of the watershed descriptors resulted in three optimal clusters. Differentiation among these three clusters is mainly related to climatic regimes, topographic features, and land uses. Stepwise regression was used to identify the watershed descriptors that explain the spatial variability of four flow indices (95% non-exceedance percentile Q95; 5% non-exceedance percentile Q5; the slope of the flow duration curve SFDC; and the runoff coefficient RC). This gave, for these four indices in turn, R2 values of 0.77, 0.76, 0.84 and 0.45. The results show that built-up areas and dryland forest are primary land-use controls on flow indices. Clustering results suggest that existing regional development trends will have major hydrological impacts, especially related to runoff generation and groundwater. The results support the view that failure to implement land-use policy – failure that is expected to increase built-up areas across the watershed and increase forest loss in the upper watershed - will jeopardize watershed hydrological functions. The findings of this research support the need for frequent and updated land-use monitoring to control urban development and conserve dryland forest, as well as land-use policies that control increases in built-up areas and that minimize forest loss. [ABSTRACT FROM AUTHOR]

Public transportation (PT) studies often neglect non-routine trips focusing predominantly on commuting. However, recent research revealed that occasional trips make up a substantial portion of public transport journeys, and traveler preferences for non-routine trips diverge from their preferences for regular commuting. We study non-routine trips based on a database of 63 million smartcard (SC) records of PT boardings made in Israel during June 2019. The characteristics of these trips are revealed by clustering PT users' boarding records based on the location of the boarding stops and time of day, applying an extended DBSCAN algorithm. Our major findings are that (1) conventional home-work-home commuters are a minority in Israel and constitute less than 15% of the riders; (2) at least 30% of the PT trips do not belong to any cluster and can be classified as occasional; (3) The vast majority of users make both recurrent and occasional trips. A linear regression model provides a good estimate (R2 = 0.85) of the number of occasional boardings at a stop as a function of the total number of boardings, time of day, and land use composition around the location of trip origin. We discuss the potential applications of our approach in the landscape of diverse flexible PT. • Characteristics of non-routine public transport trips are revealed using an extended DBSCAN clustering algorithm. • The share of non-routine trips is not lower than 30%. • The number of occasional boarding at a stop can be predicted with a linear regression model. • Non-routine trips exhibit specific spatio-temporal patterns. • The patterns of non-routine demand provide the basis for establishing urban transportation policy. [ABSTRACT FROM AUTHOR]

Rise in length of haul (LOH) of business establishments and the associated greenhouse gas (GHG) emissions are a major concern for planners and policymakers, require extensive investigation. This paper quantifies various factors like business age, gross floor area, employment, the build environment variable on LOH, and associated GHG emission using EBFS data. Survival analysis has been utilized for the analysis. The aggregated LOH model provides a comparative analysis of LOH across different industry sectors and demonstrate that gross floor area, business age, and employment are positively associated with LOH. Subsequently, disaggregated LOH models are reveal the influencing parameter of LOH of a particular industry category. Lastly, GHG models show the influence of fleet ownership level on GHG emissions across different industry sectors. The outcomes will be beneficial for planners and policymakers to develop industry-specific regulations on land use, employment restructuring, and subsidies for owning different types of commercial vehicles. • Effect of various establishment characteristics on length of haul (LOH), and associated GHG emission have been quantified. • Survival analysis has been utilized to determine the influencing factors of LOH and associated GHG emission. • Three different models: Aggregated industry sector model, Disaggregated industry sector model and GHG emission model have been developed. • The understanding of this research on LOH and associated emissions provides clear insights for urban planners about the factors resulting in enhanced LOH and emission. [ABSTRACT FROM AUTHOR]

Semantic Segmentation is an important problem in many vision related tasks. Land use and land cover classification involves semantic segmentation of satellite imagery and plays a vital role in many applications. In this paper, we propose an extended U-Net architecture with dense decoder connections and attention mechanism for pixel wise classification of satellite imagery named Attention Dense U-Net (ADU-Net). We further evaluate the effect of different upsampling strategies in the decoder part of the U-Net architecture. We evaluate our models on the Gaofen Image Dataset (GID) for landcover classification consisting of five classes: built-up, forest, farmland, meadow and water. The experiments on the GID dataset show better performance than the previous approaches. Our proposed architecture delivers more than 4% higher mIoU and F1-score than the baseline U-Net. Moreover, our proposed architecture achieves an F1-score of 87.21% and mIoU of 77.66% on the GID dataset. Our evaluations shows that data-dependent upsampling layer achieves higher accuracy than the Transposed Convolution, Pixel Shuffle and Bilinear upsampling layers. [ABSTRACT FROM AUTHOR]

Changes in land use and cover (LULC) are now considered as a significant concern because they have a great impact on biodiversity loss and climate changes. Therefore, the present study was applied to assess the effect of land use dynamic on land surface temperature (LST). LULC maps of years; 1991, 2001, 2014, and 2022 were applied using Maximum likelihood classification MLC) while the LST was developed using thermal bands of Landsat images. LULC maps showed a considerable development and improvement in vegetation cover and urbanization. Results showed a negative and positive correlation between LST with NDVI and NDBI respectively. It was revealed that the estimated and predicted LST confirm the reliability of the present model with R2 = 0.95. The study calculated that the maximum LST in 2022 to simulate current state of Riyadh, Saudi Arabia and the results were 32.1, 45.5, 38.7 and 41.3 in winter, summer, autumn and spring respectively. We are now sounding the alarm because the state must act quickly and decisively to stop intensive forestation if it is to avoid very high temperatures by 2030. Our findings point to the need for environmental protection in response to the study area's quick conversion of LULC and increasing trend of LST. [ABSTRACT FROM AUTHOR]

Pressure is increasing globally to deliver integrated land use at large spatial scales (10–100 s km2) to address the climate and biodiversity emergencies through delivery of nature-based solutions. There is also pressure to decentralise land use decision-making to sub-national levels of government and multi-stakeholder partnerships, with the aim of improving policy targeting, coordination and participation. Whilst there has been significant research on these issues at smaller spatial and administrative scales, it is limited at larger scales. This paper addresses this gap, investigating whether the introduction of additional regional institutions can help address these challenges. It draws insights from Scotland's decade old Land Use Strategy (LUS) and evolving Regional Land Use Partnerships (RLUPs) that aim to mitigate climate change through encouraging improved and integrated land use and land management. We find that despite considerable stakeholder support, such approaches may not deliver on their ambitions. An overarching finding relates to the importance of political commitment to implementation at these larger scales, which is crucial for establishing clear objectives, giving regions authority to respond to regional priorities, and ensuring adequate resourcing. This affects buy-in from stakeholders and the resolution of policy coordination challenges that the partnerships are meant to address. It has wider implications for the delivery of national climate policies, given the importance of land management in most climate change strategies. The insights, and the analytical framework used, are relevant for any country grappling with the challenge of implementing nature-based solutions at ever larger scales whilst bridging local and national land use priorities. • Regional integrated land use planning in Scotland evaluated and wider lessons drawn. • Clear objectives, transfer of powers, and resourcing key to regional land use planning. • Political commitment is crucial in overcoming delivery challenges at this scale. • Approaches to scaling up integrated land use need to account for politics. • These lessons are important in global efforts to scale up nature-based solutions. [ABSTRACT FROM AUTHOR]

Integrated landscape approaches (ILA) aim to reconcile multiple, often competing, interests across agriculture, nature conservation, and other land uses. Recognized ILA design principles provide guidance for implementation, yet application remains challenging, and a strong performance evidence-base is yet to be formed. Through a critical literature review and focus group discussions with practitioners, we identified considerable diversity of ILA in actors, temporal, and spatial scales, inter alia. This diversity hampers learning from and steering ILA because of the intractable nature of the concept. Therefore, we developed a tool—an 'ILA mixing board'—to structure the complexity of ILA into selectable and scalable attributes in a replicable way to allow planning, diagnosing, and comparing ILA. The ILA mixing board tool presents seven qualifiers, each representing a key attribute of ILA design and performance (for example, project flexibility, inclusiveness of the dialogue, and the centrality of the power distribution). Each qualifier has five (non-normative) outcome indicators that can be registered as present or absent. This process in turn guides planners, evaluators and other participating stakeholders involved in landscape management to diagnose the ILA type, or its performance. We apply the ILA mixing board to three ILA cases in Nicaragua, Madagascar, and the Congo Basin to show some of the many possible configurations of qualifiers on the mixing board. Further application of the tool would allow comparative analysis of the complexity of ILA in a structured and manageable way thereby enhancing the understanding of ILA performance and informing the development of evidence-based land use policy. • Landscape approaches aim to reconcile multiple land use and conservation objectives and stakeholder interests. • How to break down the complexity of landscape approaches into selectable, scalable, and measurable indicators?. • We present a "mixing board" for landscape approaches consisting of 35 indicators across seven planning dimensions. • Planners, evaluators and stakeholders can classify landscape approaches based on their complexity and performance. • We show that the tool allows to compare even very different types of approaches in a replicable and transparent way. [ABSTRACT FROM AUTHOR]

Soil salinization and/or alkalization is a major constraint to crop production worldwide. Approximately 60% of the cultivated land is affected by salt, over half of which is alkalized. Alkaline soils are characterized by high alkalinity and typically high salinity, which creates a complex saline-alkaline (SA) stress that affects plant growth. Rice cultivation has been accepted as an important strategy for effective utilization of SA land if water is available for irrigation. Nevertheless, as a salt-sensitive plant, rice plants suffer severe SA-induced damage, which results in poor plant growth and grain yield. Various approaches have been employed to improve rice productivity in SA land. Among them, the priming technique has emerged as a powerful method for enhancing SA tolerance in rice plants. In this review, we summarized how SA stress damages rice plants, and then presented how priming treatment can mitigate such damage. [ABSTRACT FROM AUTHOR]

A 'planetary park' system has been suggested as a way for Mars to 'preserve' land for a multitude of purposes. These parks would represent a diverse portion of martian terrain and would be regulated to minimize human contamination and prevent excess human intervention. One suggestion is a two-part land-use policy for Mars, i.e. planetary parks and Lockean land for the use of non-park areas, in which non-park areas could be opened up for development and settlement. Others have proposed that this planetary parks concept could be extended to appeal to corporate interests as a compromise between protecting environmental interests and allowing private use of resources on Mars. This empirical study aims to help advance the core discussion of the interplay between future space activities and future preservation plans on Mars. Specifically, this work uses a particular strategic foresight method, the Policy Delphi, as a means to reveal positions on that issue and to explore alternative policy options in advance, through the collective judgment of a panel of experts. It should be noted that the goal was not strictly to promote consensus regarding the topic of interest, but to encourage structured dialogue. Consequently, the stable consensus achieved in specific areas indicated that the panel of experts foresees international cooperation on matters related to preservation plans for Mars, which, in turn, will enhance the overall international space governance. Furthermore, the panel foresees the inclusion of varying actors, both state and non-state ones, in the development of a preservation framework for Mars, especially on a national level. To this end, the panel endorses the inclusion of a diversity of values to be protected via the aforementioned framework, and suggests the advancement of broad global dialogue on this matter including academic, industrial, governmental, and public actors. The preliminary insights revealed in this work may inform relevant international discussions towards the formulation of proactive policies that will contribute to the environmental governance of future activities on Mars. [ABSTRACT FROM AUTHOR]

Lagos is Africa's most populous megacity and one of the world's fastest-growing urban areas. Lagos city's land use and land cover (LU/LC) classes have changed dramatically in recent decades as a result of its continuing population growth and other human and anthropogenic activities. The UN 2030 Agenda for Sustainable Development must be adopted in order to preserve the available land cover classes in Lagos. Goal 11 of the Sustainable Development Goals aims to make cities and human settlements more inclusive, safe, resilient, and long-term. The use of remote sensing and geographic information systems (GIS) to track the progress of SDG 11 is an essential strategy. Remote sensing and geographic information systems were used to model and analyze the data in this study. To achieve this aim, remotely sensed data, such as Landsat 7 ETM + and 8 OLI, was used to determine the rate of changes in Lagos from 2010 to 2020 by adopting the Maximum Likelihood Classifier (MLC) and then project the likely changes that may occur by 2025 and 2030. Observed ground truthing information was adopted for validation and for checking the accuracy of the classification. The result shows that from 2010 to 2015 and to 2020, built-up area had increased from 11.73 % to 12.81 % and finally to 29.51 %, while agricultural land declined by 11.84 % to 3.37 % and then to 2.99 %. Water bodies and wetland percentages decreased from 19.00 % and 19.50 % in 2010 to 17.39 % and 8.48 % in 2015, and to 18.37 % and 16.92 % in 2020. Forest land and bare land classes have also changed from 25.4 % and 12.52 % in 2010, to 33.37 % and 24.58 % in 2015, and to 18.10 % and 14.11 % in 2020. The study shows that remote sensing and GIS are excellent tools for monitoring the environment and for the development of a sustainable city. [ABSTRACT FROM AUTHOR]

Understanding the main drivers of biodiversity loss in Europe's agricultural landscapes has been a research priority in the last decades. One of the most important factors promoting biodiversity in farmed landscapes is habitat heterogeneity, which has often proved crucial for avian species and communities. Birds are highly sensitive to environmental changes and make use of a broad range of ecological niches, thus being exceptionally sensitive to the loss of habitat heterogeneity. Remote sensing data are particularly suited to quantify habitat heterogeneity at fine scales over relatively large extents, allowing to consider how different measures of heterogeneity may affect biotic communities at a regional scale. Here, we used airborne LiDAR (Light Detection And Ranging) and satellite multispectral data to derive vegetation canopy height and primary productivity for 118 sites in complex agricultural landscapes in a region in the Central Alps. We computed different bird diversity indices and classified bird species into guilds according to specific traits to analyse the relationship between avian communities and different facets of habitat heterogeneity. Results confirmed that habitat heterogeneity is essential in shaping rich and diverse bird communities, and it is particularly important for several farmland birds. By comparing the effects of canopy height, primary productivity, and specific vegetation features (e.g., cover of grassland, shrub, and tree layers), we showed how different habitat characteristics as well as landscape heterogeneity affected bird richness, diversity, functional entropy, and trait patterns. Landscape and height heterogeneity, estimated by NDVI and LiDAR Rao's Q indices, strongly influenced all response variables, for example, high NDVI values promoted species diversity and ground-understory nesters, and shrub layer was important for ground-understory nesters and forest specialists. Finally, we provide recommendations for conservation practices and mitigation measures to improve bird diversity in agricultural landscapes. [ABSTRACT FROM AUTHOR]

Understanding spatio-temporal suspended sediment dynamics is more important in large watersheds due to the decisive role of local source apportionment in sediment transport and yield. The Talar River with a large mountainous watershed in northern Iran, which plays a vital role in water supply for agriculture and drinking, recently has faced quality degradation. The current study explores the relative contribution of suspended sediment sources using geochemical tracers and fingerprinting techniques in high and low flow periods along this river. Soil samples were collected from four major land uses including rangeland, forest, rainfed agriculture, and irrigated agriculture, as well as riverbanks and riparian zones along the main river. Furthermore, suspended sediment was sampled at four sampling points along the main river in two seasons. Land use apportionment in suspended sediment yield was calculated using an unmixing model included in a newly developed package (FingerPro) in high flow and low flow, separately. The fingerprinting results showed a highly spatio-temporal dynamic for sediment source contribution along the main river in high and low flow periods. Natural land uses (forest and rangeland) in upstream reaches and agricultural land uses and riverbank sources in downstream reaches showed higher contributions to suspended sediment yield. The mean contribution of various land uses for both high and low flow periods indicated substantial contributions from forest (34%–41%) and riverbanks (31%–33%). The significant difference in sediment geochemical properties for the two flow seasons highlights the important role of the prevailing climatic-hydrologic condition on river sediment. Moreover, this issue indicates that sediment source contributions and transfer mechanisms are highly dynamic in Talar River watershed. The current study outcomes provide essential knowledge to create a robust strategy for mitigation of river sediment pollution. [Display omitted] • Geochemical properties of suspended sediments changed in high and low flow period. • Forest and river bank were the main sources of suspended sediment in both periods. • Contribution of irrigated and rainfed agriculture increased in downstream. • Spatio-temporal dynamic of suspended sediment sources evaluated using fingerPro. [ABSTRACT FROM AUTHOR]

Conserving natural resources and halting biodiversity loss are key environmental objectives of the European Union. High Nature Value farmland and forest (HNVFF) areas are associated with high biodiversity and other public goods. Currently, there are few dedicated HNV farmland and no HNV forest quality and quantity monitoring systems implemented in Europe, and none are in use in the Republic of Ireland. This study presents a conceptual framework to monitor quality, quantity, and change of HNVFF areas in the Republic of Ireland. The methods were tested using a set of monad sampling cells distributed across a range of representative landscapes. High resolution sampling cell habitat cover maps were developed using a national spatial database and recent orthoimagery, and a subsequent revision of the cell maps was performed using historical orthoimagery. This enabled a simulation of a 13-year monitoring cycle to compare trends in HNV farmland and forest quality, quantity, connectivity, and habitat categorical change. A contrasting trend of decreasing HNV farmland and increasing HNV forest quantity was observed over the monitoring period.Categorical habitat change detection identified a range of HNV habitat loss and gain, driven predominantly by land use intensification, but also by ecological succession and technogenic pressures. To upscale the monitoring to national scale, a sampling strategy using a recent landscape classification is proposed. The national monitoring approach aims to meet the needs of evolving policy requirements. This provides a useful example for countries seeking to establish their HNVFF and other land cover monitoring systems. [Display omitted] • We present a novel framework to monitor High Nature Value farmland and forests. • A temporal monitoring cycle was simulated to compare trends in HNV habitats. • Contrasting trends in HNV farmland and forest quantity and quality were observed. • Categorical change detection identified a range of HNV habitat loss and gain. • The study provides a useful example for other similar landcover monitoring systems. [ABSTRACT FROM AUTHOR]

Small body exploration has seen a renewed interest in recent years. Landing a spacecraft on the body's surface enhances the mission's scientific return, yet it is a high-risk operation. CubeSats offer a cheaper alternative to bigger spacecraft, and when used in tandem with a mothercraft, they may perform risky operations without exposing the mission to a complete loss. Nonetheless, their small size as well as their limited operational and computational capabilities pose hard limitations to their efficient exploitation. Historically, powered and controlled landing has often been key to soft landing success. In an asteroid complex dynamical environment, manoeuvre execution benefits from a dedicated Guidance and Control (G&C) scheme that is robust to dynamical uncertainty, autonomous and reliable. To robustly and reliably soft-land a CubeSat on a small body, we propose a novel Guidance & Control strategy. It alternates closed-loop control segments using the existing Multiple Surface Sliding Guidance algorithm with intervals of ballistic trajectory. We show that very good landing performance in terms of landing ellipse, collision velocity and fuel consumption can be achieved. The method has been tested for Hera's Milani CubeSat landing attempt on Dimorphos, the moon of (65803) Didymos binary asteroid, using Monte Carlo analysis. The Guidance & Control strategy is shown to comply with stringent requirements for targeted soft landing. [ABSTRACT FROM AUTHOR]

Urban development and effective land use planning are critical factors in creating sustainable and functional cities. Identifying vacant areas with development potential plays a crucial role in optimizing urban resources and contributes to making informed decisions for new projects and urban transformations. This paper presents a method for identifying vacant territories in the current urban environment to accommodate different infrastructures. The method uses modern technology and open-source data to identify vacant area that can become the object of urban planning and new construction projects. Taking into account such factors as accessibility, zoning rules and urban planning restrictions, the method offers a systematic approach to the assessment of urban development potential. The article describes the main steps of the method, including site selection, extracting sites and functional zones from public data sources, checking for compliance with urban planning regulations and restrictions, and cleaning up the data to eliminate geometric inconsistencies and shallow areas. Through detailed explanations, examples, and recommendations, this paper aims to provide a comprehensive understanding of the method and its application in urban planning practice. The results of this study have important implications for sustainable urban development by enabling informed decision-making that meets the needs and aspirations of communities, contributing to economic growth and improving the overall quality of life. Ultimately, the method developed to identify vacant spaces offers a valuable tool for urban planners and decision-makers seeking to optimize land use and create dynamic and sustainable cities. [ABSTRACT FROM AUTHOR]

This paper presents a method for generating urban blocks. Urban blocks are the basis from which urban processes are modelled and assessments of the current situation are made. The proposed method allows with the additional land use data, clustering algorithms and computational operations to obtain a more complete representation of urban blocks. The resulting refined blocks are more suitable for modelling and assessing processes of urban environmental change. Huge blocks (most often encountered outside the city) are divided by the cluster of buildings into smaller blocks that are connected to the road network, which allows them to be considered as full-fledged blocks and not only as a group of buildings. [ABSTRACT FROM AUTHOR]

• We investigate driving forces of different land-use types to BSD. • Diversified machine learnings are proposed for spatial interpolation fusion. • Hotspot detection establishes sampling points for reducing the MAUP effect. • Fusion models improve the interpolation performance: accuracy and stability. • Word clouds identifies predominant facility names in each land-use type. Land use plays a crucial role in promoting the bike-sharing demand. Traditionally, studies on bike-sharing demand (BSD) are mainly focused on its prediction through regression methods, but the influence of MAUP (modifiable areal unit problem) in modeling is ignored. This paper aims to model spatial BSD distribution and prove the driving forces of different land use types to BSD through a machine-learning-based multiple interpolation fusion method. The hotspot detection model is employed to establish sample points covering different land use types in urban areas. In order to capture the differences in adaptations among different urban regions and for different data sizes, six machine learning methods are applied and evaluated to improve BSD estimation by fusing five spatial interpolation algorithms, including Inverse Distance Weight, Spline, Kriging, Natural Neighborhood and Trend. The methodological verification of Beijing City shows that the fusion models improve the estimation performance compared with individual interpolation algorithms, and that GRNN (generalized regression neural network) method is superior to all the others. According to fitting results of all POIs based on the GRNN fusion model, we identify which types of facilities correspond to customers that will have a stronger preference for bike-sharing and demonstrate which facility names are more prominent in each land use type. The conclusions presented here enrich our understanding relationships between land-use and BSD, which provide a valuable foundation for the bike-sharing development. Compared with implementing regression in an analysis zone or a square grid, troubles caused by the MAUP are effectively solved through this method. [ABSTRACT FROM AUTHOR]

• Highly-unsaturated and aliphatic compounds accounted a large proportion of DOP. • Phosphate mining in forest land was responsible for the increasing sulfur-containing DOP compounds. • Intense anthropogenic activities increased inputs of aliphatic compounds in different reaches. • DOP compounds differed between agricultural runoff and urban runoff under similar precipitation. • Aliphatic DOP compounds in the upper reaches were preferentially used to further promote microbial degradation of biomass. Land use and precipitation are two major factors affecting phosphorus (P) pollution of watershed runoff. However, molecular characterization of dissolved organic phosphorus (DOP) in runoff under the joint influences of land use and precipitation remains limited. This study used Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) to study the molecular characteristics of DOP in a typical P-polluted watershed with spatially variable land use and precipitation. The results showed that low precipitation and intense human activity, including phosphate mining and associated industries, resulted in the accumulation of aliphatic DOP compounds in the upper reaches, characterized by low aromaticity and low biological stability. Higher precipitation and widespread agriculture in the middle and lower reaches resulted in highly unsaturated DOP compounds with high biological stability constituting a higher proportion, compared to in the upper reaches. While, under similar precipitation, more aliphatic DOP compounds characterized by lower aromaticity and higher saturation were enriched in the lower reaches due to more influence from urban runoff relative to the middle reaches. Photochemical and/or microbial processes did result in changes in the characteristics of DOP compounds during runoff processes due to the prevalence of low molecular weight and low O/C bioavailable aliphatic DOP molecules in the upper reaches, which were increasingly transformed into refractory compounds from the upper to middle reaches. The results of this study can increase the understanding of the joint impacts of land use and precipitation on DOP compounds in watershed runoff. [Display omitted] [ABSTRACT FROM AUTHOR]

Archaeological sites in wetlands or under waterlogged conditions provide excellent preservation conditions for organic material, particularly wood, and therefore constitute one of the most important prehistoric sources for dendroarchaeological studies available. The site of Bouchain in the North of France, is located on the bank of a palaeochannel close to the Scheldt River, a North Sea tributaty. Regular floods of varying intensity led to formation of peat and waterlogged site conditions, providing vast amounts of wooden artefacts sampled for dendroarchaeological analyses within an interdisciplinary research effort, further involving palynological, malacological and anthracological studies. Here we present a study on a total of 1858 individual wood objects, including architectural elements (posts, stakes and planks), tools and hunting weapons (axe handles, arrow shafts and bows, throwing sticks, slingshot balls), tableware, production waste from woodworking (chips) and finally two log boats. In addition, natural wood residues from peat and alluvial layers have been collected and analysed to obtain a more comprehensive picture of the Neolithic forest vegetation on-site. After an early occupation of the site during the Mesolithic period, the archaeological sequence is placed between the Middle Neolithic and the end of the Late Neolithic (∼4200–2700 BCE). However, the main occupation is in the Late Neolithic, broadly between 3400 BCE and 2950 BCE. The interdisciplinary approach allows to specify the nature of the forest stands on the periphery of the site as riparian forest of alder type, associated with a mixed forest and heliophilous vegetation. The dendroarchaeological investigations enabled precise tree-ring dating and provides important insights into the selection and processing of wood in Neolithic times in the context of weaponry production, shipbuilding and food consumption. [ABSTRACT FROM AUTHOR]