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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 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]

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]

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]

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]

• 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]

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]

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]

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]

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]

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]

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]

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]

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]

Dynamic monitoring and prediction of ecosystem service value (ESV) under land utilization change is of great significance to maintaining regional ecological security. In order to enrich the study of ESV changes in plateau region by using the improved equivalent factor method of unit area value, the western Sichuan Plateau was taken as the research object. In this paper, given the land use data of the western Sichuan Plateau in 2000, 2010 and 2020, efforts have been made to construct the suitability image collection of the study area and to amend the CA-Markov model as to predict the land use pattern in 2030. In addition, the improved ESV evaluation model was constructed to study the spatial and temporal dynamic variation features of ESV. The results showed that: Woodland and grassland are the main types of land utilization in the study area. There are frequent interchanges between various land utilization types. The overall reduction of ESV, decrease of 3.4917 × 109 yuan/a, mainly due to the conversion of woodland to other land types. The high-value areas of ESV in the study area are closely tied to rivers. Two areas with high ESV value were formed in the study area. The findings of the study enriched the research system of land use and ecosystem service value in the plateau region, provided basic data for the construction of regional ecological security pattern, and enhanced regional sustainable development. [ABSTRACT FROM AUTHOR]

The federal government of Ethiopia set a national target to restore 15 million hectares of degraded and deforested lands by 2030. While forest and landscape restoration governance is intended to be a multi-actor process through which various land uses are coordinated, in practice it turns out to be difficult to bring specialised government agencies together to achieve restoration targets. We conducted a policy document review, 56 semi-structured interviews and 14 focus group discussions to understand the different challenges that exist in the governance of forest and landscape restoration in Ethiopia. We found three cross-sector challenges that influence the way in which national restoration targets are implemented at the local level in Ethiopia: 1) food security dominates the restoration policy frame and budgetary allocation at the expense of alternative restoration pathways that foster forestry livelihoods and biodiversity benefits, 2) agricultural and environmental policy objectives and targets, and restoration mandates at the sub-national level are incoherent, and 3) a siloed land use planning instrument makes it difficult to negotiate trade-offs and find synergies between sectoral policy objectives. Our results point out the need for an integrated land use planning instrument to achieve a wider range of restoration benefits. Given existing power imbalances between land-based sectors, we posit that an independent integrated land use planning authority that can draw on hierarchical authority is required to better balance different sector interests and different forms of conservation and restoration. • The different ways in which sectoral interests can be misaligned are conceptualised. • Three cross-sector challenges in Ethiopian restoration governance are analysed. • To better balance sectoral interests, a dedicated land use planning agency is needed. [ABSTRACT FROM AUTHOR]

The introduction of new mobility technologies and systems have historically shaped the patterns of settlements. With the advent of autonomous vehicles (AVs) and the implementation of ubiquitous mobility-as-a-service (MaaS) systems, it can be argued that there may be another fundamental change in terms of people's travel. Given the interaction of land use and transport, a stronger reliance of travel on AVs has the potential to change the layout of cities. In this study, we use accessibility measures to quantify and compare the utility that such services offer for citizens in an exemplaric case study using the transport simulation model MATSim. MATSim allows both (1) to model demand-response transit services and (2) to compute dynamic accessibilities based on various modes of transport. This study brings these functionalities together for the first time to assess such services by a measure that resembles the perspective of the individual citizen. We find that the changes in the operational model of the SAV (shared autonomous vehicle) fleet has significant effect on accessibilities provided by SAVs. Especially in a setup were a fleet is expected to fulfill a basic needs supply, the results are of high relevance under equity aspects. [ABSTRACT FROM AUTHOR]

This paper develops a scenario analysis and visualization tool for an Integrated Transport, Land-Use and Energy (iTLE) model to spatially analyze and predict changes in transport and land-use environment. The decision support tool operates by taking the iTLE model output data as input which includes residential location of households, individuals' characteristics, and vehicle fleet information. Use of the tool is showcased through a scenario analysis of a 'business as usual (BAU)' projection versus a 'COVID-19 pandemic scenario' for Halifax, Canada. Agent-based microsimulation explores the possible future changes in households' socio-demographic characteristics and travel behaviour in the post-pandemic time. Forecasting up to the year 2025 and comparing between BAU and pandemic scenario shows that, many of the lower median income areas in the BAU projection are estimated to have a much lower median income under the COVID-19 scenario. Furthermore, the COVID-19 scenario only slightly decreases the proportion of the overall population with a transit pass. Under the pandemic scenario, the percentage of households with three or more cars experiences significant growth in urban and suburban areas. Outcomes of this study will offer policymakers a greater understanding of the transformation pattern of urban and suburban neighborhoods in the post-pandemic period. The developed iTLE VIZ tool will allow planners to formulate complex transport and land-use scenarios and simulate them for examining urban systems transformation. [ABSTRACT FROM AUTHOR]

• It summarized research progress and prospects of LUCC impacts on eco-environments. • LUCC affects Earth's eco-environment by altering the surface-atmospheric interaction. • Mechanisms of LUCC impacts are surface radiation budget and matter conservation. • Challenges remain because of uncertainties in data, methodologies and evolution. • Future studies on data assimilation, contribution, physical and full-process are required. Land use and cover change (LUCC) is one of the key variables dominating land–atmosphere interactions and strongly affects the Earth's eco-environments by altering surface properties. Numerous studies have been carried out to assess the impact of LUCC. However, the Earth is a large, open and complex system characterized by complex interactions between its eco-environments and drivers. This study aimed to summarize previous studies of the impact of LUCC on the Earth's eco-environments and discuss the progress and limitations in suggesting future directions. Previous studies have confirmed that LUCC has a wide range of impacts on the Earth's eco-environments, which are represented by the alternation of climate (temperature, precipitation, wind, and humidity), hydrology (soil moisture, runoff, and evapotranspiration), ecology and environmental (air, water, and soil) pollution. Physically, the impacts were mainly attributed to the disturbance of the surface radiation budget and matter conservation caused by LUCC. Although great achievements have been made, several challenges remain because of the unavoidable uncertainties in data sources and methodologies and the complexity of eco-environmental evolution. Therefore, data assimilation, physical-based investigations, contribution isolation, and full-process analysis are required to overcome these challenges in future research. The results of this study helped to capture the impact of LUCC and its physical mechanisms, which provide useful clues for future research and support the relative land use management for sustainable development. [ABSTRACT FROM AUTHOR]

Al Ahsa Metropolitan Area (AMA), located in the Eastern Region of Saudi Arabia, has witnessed rapid population growth with remarkable urban expansion during the past few decades due to the discovery of oil. Because of this rapid growth, AMA is currently exposed to many short and long-term social, economic, and environmental challenges that need to be studied and assessed to provide solutions for the betterment of the population. This study examines the historical growth of AMA by using Geographical Information System data and satellite image classification techniques for the last 30 years. The results show that the total urban area of AMA has significantly increased from 199 sq. km. to 276 sq. km. during the past 30 years from 1992 to 2022 with a sharp increase of 25.5 % in the last 10 years only. Statistical analysis of the historical data predicted an increase of 26.8 % in the area of settlements during the next decade up to the Year 2032. After a study of land use maps it was also observed that the increase in settlements caused a decrease in vegetation to 18 % in the last decade. The research presents beneficial statistics which shall help the decision-makers and related authorities in managing the development process in the area in a better and more sustainable manner. [ABSTRACT FROM AUTHOR]

Land use faces a double challenge: to provide biomass to a growing population while contributing to climate-change mitigation. We here scrutinize this challenge by exploring the domestic option space for meeting the food demand of Austria in 2050 under the condition of no deforestation. To that end, we bring together a quantitative assessment based on biogeochemical models with a socio-political analysis based on the conceptual framework of (dis-) embeddedness derived from Polanyian thinking. We consider viable options by modifying four levers: (i) human diet and food waste; (ii) trade patterns; (iii) agricultural practices; (iv) technical climate change mitigation. Past and present policies in Austria have fostered an agricultural system rich in animal products, land-use specialization and the integration of biomass products within international markets, ultimately resulting in a loss of embeddedness in the sense of Polanyi. The biophysical analysis, however, highlights that a shift towards diets with less animal products would allow increasing self-sufficiency or a generalization of organic farming while turning the agricultural and forestry sector into a net GHG sink. Following a Polanyian perspective, we show that feasible scenarios require different types of re-embedding of the agricultural system: ecological, spatial and social, implying that land products should rather be common goods than mere commodities. • We explore the biophysical option space of the agricultural system in Austria. • We combine a modelling approach with a Polanyian interpretation framework. • We show that diet is a key lever to meet food demand while reducing GHG budget. • We show that organic farming or self-sufficiency are feasible option. • Reducing GHG budget will require social, ecological and spatial re-embedding. [ABSTRACT FROM AUTHOR]

Perceived travel time plays an important role in the subjective wellbeing of the commuters. Recent studies have focused on the relationship between spatial characteristics and wellbeing, and the relationship between transportation and mobility with subjective wellbeing of the people. However, few studies tackled the influence of the urban form and the elements of built environment on wellbeing during commuting in the city. This manuscript discusses the concept of urban form, and perceptual qualities of urban design. Afterwards, it proceeds with delineating the research variables (i.e., Spatial and Perceptual). The case study selected is South 90 Street, New Cairo, Egypt, which serves as an urban corridor that accommodates various transit modes, diverse land uses, and variety of urban facades. The analysis is carried out utilizing the built environment dataset and collected responses about users' experience via a questionnaire. This manuscript attempts to answer two main questions: (1) What is the influence of urban form on commuters' travel time perception? (2) How do the elements of the built environment impact the subjective wellbeing of commuters? Descriptive analysis is conducted to understand the relationship and influence of the built environment on the perceived travel time during mobility and individuals' wellbeing. The manuscript further discusses the results, depicting which built environment elements are associated with either positive or negative effect on commuters' subjective wellbeing. The manuscript concludes with highlighting the potentials for maintaining the overall wellbeing of individuals and their perception during urban mobility. Thus, facilitating the design of functional, efficient, and reliable cities. [ABSTRACT FROM AUTHOR]

Subterranean habitats around the world can shelter diversified and threatened faunal communities. However, issues related to alterations in the landscape and structure of subterranean habitats still need to be better understood. Therefore, we used a multi-spatial scale analysis of land cover, land use, and cave habitats to predict the diversity of communities of subterranean invertebrates. We hypothesized that changes in land cover promote alterations in both faunal richness and composition and microhabitat diversity and that microhabitat features determined subterranean biodiversity. Sixteen limestone caves were sampled in Brazil at micro, meso, and macro scales using quadrats (1m²), transects (100 meters) as sample units inside caves and buffers with the radius of 100 and 250 meters in the surroundings of the cave entrances. Models performed showed that land cover and land use influenced cave environments, regarding both microhabitats traits and terrestrial invertebrate richness and composition. We also observed a relationship between microhabitat structure and terrestrial invertebrate richness and composition. Our results showed that deforested areas had negative effects on species richness and changed their composition, while natural areas had positive effects on microhabitat diversity. The same effects were observed for both 100 and 250 meters buffers. Invertebrate richness was negatively predicted by deforested areas while positively predicted by natural areas. Richness was also positively predicted by the combination of all microhabitat traits, and dissimilarity of fauna was influenced by microhabitat diversity in mesoscale and microscale by all microhabitat elements. The results highlight the importance of the landscape surrounding the caves to conserve the subterranean habitats and their fauna. Due to the spatial and temporal changes in the global environmental scenario, we argue the urgency of further detailed studies in fragmented landscapes to define minimum areas of protection for cave environments. [ABSTRACT FROM AUTHOR]

Because of the process of rapid urbanization in China, the urban waterlogging problems are becoming more prominent. Reasonable construction of rainstorm security pattern is an important means to realize urban sustainable rainstorm management. Using SCS-CN hydrological model, GIS hydrological analysis module and GIS spatial coupling method, we evaluated the safety space of the watershed, determined the spatial positioning of the inundated area, and finally constructed the rainstorm security pattern network of "runoff corridor + inundation area". Selecting Zhengzhou City as the research object, the study extracts an evaluation index and the numerical stimulation of the Rainstorm Security Pattern. According to the level of flood risk, all spatial areas of Zhengzhou City are divided into safety areas, low-risk areas, medium risk areas, high-risk areas and extremely high-risk areas. From the perspective of land use strategy, we determined the development intensity and prevention and control measures corresponding to the land space with different flood risk levels. [ABSTRACT FROM AUTHOR]

Climatic changes and land usage and cover (LULC) can significantly impact the availability of water resources in a region. On the other hand, water resources are intrinsically linked to economic production. Thus, managing water resources and their know-how on how they are affected by the climate and LULC are essential in regional development. The Global Climatic Model evaluated water resource management on its effects of climatic changes (2019–2099) based on four R epresentative Concentration Pathways (RCP 2.6, 4.5, 6.0, and 8.5) and the impact of changes in LULC in the Hydrographic Basin of the Cubatão River (HBCR), in Brazil. The fragilities of water resource management were observed. The scarcity of precipitation data made a direct impact on the estimated monthly average flow, as the estimated reduction was 45.4 % (RCP 2.6), 41.9 % (RCP 4.5), 43.2 % (RCP 6.0), and 41.7 % (RCP 8.5) by the end of the century. The forecast change in LULC reduces the impact on the decreased average monthly flow to 2.9 % by 2099 (RCP 2.6), 2.5 % (RCP 4.5), and 2.7 % (RCP 6.0 and 8.5). The actual evapotranspiration will be less than 2.4 % (RCP 2.6 and 6.0) and 2.3 % (RCP 4.5 and 8.5) with changes in the LULC in future scenarios. The HBCR already uses the entire status of authorized flow that will further aggravate as population growth continues. The results display faulty water resource maintenance of the basin that indeed will interfere in local economic development. • Climate change models estimate higher precipitation, but it is still insufficient. • Without the management of water resources, economic development is threatened. • The lack of instrument prevents the management of water resources. [ABSTRACT FROM AUTHOR]

Background In Latin America and the Caribbean (LAC), historical shifts away from traditional, plant-sourced food production and consumption patterns may undermine both nutritional status and environmental sustainability. Although agricultural intensification and increasingly animal-centric dietary preferences in the region are well-documented, their influence on environmental degradation remains unknown. Objectives This study aimed to 1) characterize the environmental impacts of current food consumption patterns in South America, Central America, and the Caribbean; and 2) identify food groups that minimize impact while maintaining adequate nutrient availability. Methods Apparent regional food consumption was derived using data from the FAO's Food Balance Sheets on per capita food availability and levels of imported and local food production. Region-specific life cycle assessment data on greenhouse gas emissions (GHGEs), land use, and freshwater consumption were leveraged to estimate total, food group–level, and nutrient-specific environmental impacts. Results Annual overall GHGEs were highest in Caribbean food consumption patterns (2521.2 kg/capita), largely derived from meat (26.7%) and fruit (23.8%) production. Land use (1941.0 m2/capita) and water consumption (2060.8 m3/capita), in contrast, were highest for the South American pattern, owing to high consumption of meat and dairy. Across the regions, meat constituted 7.5%–12.7% of food consumption yet accounted for as much as 73.1% of GHGEs, 56.6% of land use, and 54.2% of water consumption. In contrast, legumes and seeds, cereals, roots, and vegetables demonstrated overall low environmental impacts, particularly relative to their contributions to dietary protein, iron, and zinc availability. Conclusions Findings point to the capacity of plant-sourced food consumption to minimize environmental harm without necessarily jeopardizing nutrient availability in LAC. Local agriculture can contribute to food system sustainability by producing diversified plant-sourced foods, cornerstones of many traditional food customs, and mitigating the impacts of industrialized livestock operations and imported, animal-centric dietary habits. [ABSTRACT FROM AUTHOR]

• The thruster performance and glide-slope constraint are considered. • A novel time-varying feedback guidance and its incremental form are proposed. • The guidance laws are near-fuel-optimal and can avoid subsurface flight. • The trajectory can be set as a straight line. • An optimal problem is constructed to satisfy the glide-slope constraint. Taking into account the thruster performance (total thrust magnitude constraint and control acceleration deviation) and glide-slope constraint, this paper presents two types of new feedback guidance strategies for Mars pinpoint soft landing, which are near-fuel-optimal and robust to disturbance. A novel and simple time-varying feedback guidance law is proposed at first. Next, this guidance law is extended to the incremental guidance to improve the robustness and ability to deal with the thruster performance and disturbance. An advantage of these two guidance schemes is that they can avoid subsurface flight owing to the monotonic convergence of position and velocity. Moreover, an exciting feature of these two guidance laws is that the trajectory of the vehicle can be set as a straight line by choosing the guidance laws parameters. Finally, an optimal problem is constructed and solved based on this feature to obtain the guidance laws parameters to satisfy the glide-slope constraint. Its robustness, fuel efficiency, and performance in dealing with acceleration deviation and thruster constraint are demonstrated for different simulation scenarios, especially in comparison with zero-effort-miss/zero-effort-velocity feedback guidance law. [ABSTRACT FROM AUTHOR]

In the landing mission on low-gravity asteroids, the probe may have a large position error when touching the surface or hop away from the desired target after a collision. To achieve a precision landing, a guidance method using an active hopping trajectory is proposed. In contrast to passive hopping, the active hopping strategy can reduce the landing errors by controlling the collision attitude sequence of the probe. The collision attitude sequence is determined by dynamically planning the hopping trajectory which consists of an active hopping phase and a braking phase. The active hopping phase achieves an expected range with a small number of hops, and the braking phase eliminates the probe's horizontal velocity and provides feedback for the range adjustment of the active hopping phase. The guidance method based on the hopping trajectory planning is then verified in a simulated asteroid landing scenario. The results show that the method is effective in reducing the landing errors, robust to the environmental parameter perturbations, and applicable to landings on inclined surfaces. • A guidance method using active hopping trajectory is developed for the precision landing on the surface of asteroids. • The guidance method is effective in reducing the landing errors by controlling the collision attitude sequence of the probe. • The guidance method can reduce the effect of environment parameter perturbations by dynamically planning the hopping trajectory. • The guidance method is applicable to landing on asteroids with inclined surfaces. [ABSTRACT FROM AUTHOR]

Rain gardens, a type of green infrastructure (GI), have been recognized for mitigating flooding and improving water quality from minor storms by trapping stormwater pollutants. Yet, the capability of these systems to retain microplastics (MPs) from stormwater, especially in size <125 μ m , remains inadequately understood. This study investigated the spatial and temporal distributions of MPs in three rain gardens located in Newark, New Jersey, USA. The rain gardens have been in operation for ∼7 years and located in different land uses: low-density residential (Site 1), commercial (Site 2), and high-density residential (Site 3). The sediment samples were collected during May 2022, August 2022, and February 2023 at various soil depths and horizontal distances of rain gardens. The MPs were quantified and characterized using Fourier transform infrared (FTIR) spectrometer and a Raman microscope. The overall mean concentration varied between sampling sites, with 469 ± 89.8 pkg − 1 in Site 1, 604 ± 91.4 pkg − 1 in Site 2, and 997 ± 64.3 pkg − 1 in Site 3, with Polypropylene as the dominant polymer, followed by nylon and polyethylene. In the vertical direction, larger MPs (250 μ m –5 mm) were effectively retained within the top 5 cm and their concentration declined exponentially with the increasing depths. Small-sized MPs (1–250 μ m) were prevalent at deeper depths (≥ 10 cm), and no MPs were found below 15 cm. In the horizontal direction, the highest MP concentration was observed near the stormwater inlet, and the concentration decreased away from the inlet. Over the nine-month period, a notable increase in concentration was observed at all sites. These findings contribute valuable knowledge towards developing effective measures for retaining MPs from stormwater and monitoring GIs in urban environments. [Display omitted] • The MP accumulation decreases with depth in the bioretention media. • The larger-sized MPs (250 μ m –5 mm) are primarily retained in the top 5 cm. • The MPs in rain gardens reached down to 15 cm. • In the horizontal direction, MPs are highest near the inlet of rain gardens. [ABSTRACT FROM AUTHOR]

The high land surface temperature (LST) and fine particulate matter (PM 2.5) pose significant threats to urban ecological environment. LST and PM 2.5 are closely related, and land use/cover change (LUCC) has a significant influence on them. However, there is a lack of multi-scale analysis of their relationship under the background of LUCC. Therefore, this study designed a multi-scale analysis framework, adopted the Pearson correlation analysis, bivariate Moran's I and coupling coordination degree (D) to examine the relationship between LST and PM 2.5 in different land use types based on remote sensing data, and analyzed the influencing factors by Geodetector. The results showed that LST and PM 2.5 have a positive correlation, and their correlation would decrease with the research scale expansion, with the absolute values of Moran's I ranging from 0.229 to 0.577, 0.415–0.754 and 0.551–0.852 at national, urban agglomeration and city scales, respectively. LST, PM 2.5 and their correlation were lower in forest and water at the three scales, while they were the highest in construction land, and the difference in D values was about 0.3. Furthermore, the normalized difference vegetation index (NDVI) and construction land area played the most important role in spatial patterns of this relationship, followed by population and GDP. At last, the cost analysis of environmental pollution reduction was performed, and this study could provide support for proper public health policy-making and environmental protection in different regions. • The relationship between LST and PM 2.5 in different land use types at multi-scale was discussed. • There is a positive correlation between LST and PM 2.5 , and the interaction would decrease with the research scale expansion. • The interaction between LST and PM 2.5 was the highest in construction land, and the lowest in forest. • The influence degree of NDVI and night-time lights was higher than that of GDP and population. [ABSTRACT FROM AUTHOR]

Exploring the impact factors associated with biodiversity and the relationship between them has always been a concerned issue in recent years. However, the previous research mostly focus on theoretical layer. Accordingly, the relationship between landscape pattern and biodiversity is to be analyzed in this research. The landscape pattern determines the function and ecological process of the landscape, and affects the species flow, information flow and energy flow in the landscape. Land use patterns has inevitably left an impact on the landscape pattern. Landscape pattern determines the function and ecological process of landscape and thus plays a significant role in biodiversity. East Dongting Lake National Nature Reserve is taken as the research object of the paper, and the remote sensing image data of three different time periods are collected, including 2000, 2010 and 2020. With an interpretation of the vegetation landscape pattern changes inside the protected area to collect and analyze the vegetation coverage. By comparing landscape patterns and the dynamic changes of land use in different periods of time, the correlation between landscape pattern characteristics and regional biodiversity is to be analyzed. Research shows: (1) From 2000 to 2020, the vegetation coverage of East Dongting Lake increased, but the landscape shape, scale, diversity and uniformity index decreased to varying degrees. (2) At the class level of landscape type, the relationship between landscape index and biodiversity is different. A complex relationship between farmland landscape and biodiversity. There is a significant positive correlation between the index of grassland landscape type and the index of regional biodiversity. (3) The correlation analysis results at the landscape level show that the landscape characteristic index is positively correlated with the regional biodiversity index. The grassland landscape in the area is the main habitat of biological species. At the same time, as the main grain producing area, the impact of farmland landscape cannot be ignored. This study has certain theoretical guiding significance for the protection and management of biodiversity in the region in terms of maintaining landscape pattern in particular the grassland landscape area and increasing vegetation coverage in the process of land use. [Display omitted] • Land use change trend shows the increase of woodland and decrease of unused land. (81 characters). • High vegetation coverage area of East Dongting Lake increased 15.13 km2 in 2000–2020. (85 characters). • Grassland landscape index has positive correlation with regional biodiversity index. (84 characters). • Landscape shape index is strongly positive correlated with Gleason index, R is 0.607. (85 characters). [ABSTRACT FROM AUTHOR]

Non-Grain Production (NGP) on cropland emerges from complex interactions of human activities and environmental changes, posing an important threat to China's national food security. Exploring the driving forces of NGP and impact patterns is crucial to improve existing cropland protection policies. This study analyzes the relationship between the change of industrial structure and NGP in the Yangtze River Economic Belt (YREB)from 2000 to 2019 by using a spatial econometric model and a threshold effect model. Through the exploration of spatiotemporal evolution, the complex relationship between the change of industrial structure and the non-grain conversion of cultivated land is revealed. The results show that the change of industrial structure in the YREB affects the transformation of cultivated land use to a certain extent, and there is an obvious spatial spillover effect. At the same time, through the application of the threshold effect model, the threshold points affecting the relationship between industrial structure change and NGP conversion are found, which guides the formulation of relevant policies. Based on the research results, policy recommendations with regional differences are put forward to promote the coordinated development of land use protection and food security. Our study has important theoretical and practical significance for in-depth understanding of sustainable development and food security in the YREB and similar regions. • The impact of industrial structure changes on the non-grain production (NGP) of cropland are explored though evidence. • There is a spatial spillover effect of industrial structure changes on NGP. • Thresholds for the impact of industrial structure on NGP at different stages of economic development are existed. • Adjustment of industrial structure is an effective means to prevent further expansion of NGP. [ABSTRACT FROM AUTHOR]

Cultivating Suaeda salsa (S. salsa) is a promising strategy for the improvement and development of saline wastelands. However, the absence of a scientifically reasonable water and fertilizer management system has long hindered the large-scale improvement and utilization of saline wastelands. Therefore, we performed field experiments for two consecutive years to investigate the effects of water-nitrogen coupling on biomass, forage quality, salt absorption capacity, soil improvement effect, and economic benefits of S. salsa. The optimal water and nitrogen dosages for multi-objective optimization were determined using multiple regression and spatial analysis methods. Three irrigation levels were established for the experiment based on 0.35 (W1), 0.50 (W2), and 0.65 (W3) of the local ETo (Where ET o denotes the reference evapotranspiration calculated based on the FAO-56 recommended by the Food and Agriculture Organization). The three nitrogen application levels were 150 (F1), 250 (F2), and 350 (F3) kg ha−1 in the complete combination design. At the same nitrogen application level, the biomass and economic benefits of the W3 irrigation level were the highest. However, the forage quality, salt absorption capacity, salt reduction, and water productivity at the W3 irrigation level were lower than those at the W2 irrigation level, and the water productivity at the W1 irrigation level was the highest. At the same irrigation level, when the nitrogen application level was F2, the biomass, forage quality, salt absorption, salt reduction, and net profit, all reached their maximum values, and water productivity was the highest at the F3 level. The optimal amount of water and nitrogen applied for each parameter was different, so it was impossible to obtain the highest biomass, forage quality, salt absorption, salt reduction, water productivity, and net profit at the same time. Therefore, multi-objective optimization was needed, the optimal irrigation volume range was 3350.11–3485.97 m3 ha−1, and the nitrogen application rate range was 273.49–326.66 kg ha−1. These findings provide a scientific basis for the large-scale cultivation of S. salsa in extreme arid region, which is helpful for the improvement and utilization of saline-alkali land. • Planting Suaeda salsa improved saline wasteland and generated high income. • The optimal water and nitrogen rate was 0.5 ET o and 273.49–326.66 kg ha−1. • Planting Suaeda salsa reduced the salt content in the 0–1 m saline wasteland • Excessive water and nitrogen application had negative impact [ABSTRACT FROM AUTHOR]

Farm-scale decisions are key determinants of water quality and water use on a regional scale. This paper evaluates farm-scale economic–environmental tradeoffs associated with row crop land management decisions as well as land use decisions in a 15-county area of the Suwannee River Basin in North Florida. Discussions with stakeholders through a participatory modeling process identified the farm-scale land management and land use choices relevant for the study region. Land management choices included three fertilizer and irrigation management systems, and land use choices included a combination of corn, carrot, and peanut crop rotations. Farm-scale nitrate leaching and crop yield outcomes were simulated using the Soil & Water Assessment Tool (SWAT), and annualized net returns were simulated using Simetar Excel Add-In based on Extension production budgets and USDA crop and input price history. We show that the impacts from farmers' crop rotation choices outweigh the impacts from the irrigation and fertilizer management system choices. This difference in impacts can lead to a rebound in nutrient leaching if water policy regulates land management but not the land use. Nitrate leaching abatement cost were found to be comparable with the costs for other, non-agricultural pollution reduction projects in the region. • Conservation practices can reduce nitrate leaching in a corn–peanut rotation. • Adoption of conservation practices can impact net returns. • Adding carrots to the traditional corn–peanut rotation increases profits. • However, adding carrots almost doubles farm-scale nitrate leaching. • Changing crop rotations require flexible policies and evolving conservation practices. [ABSTRACT FROM AUTHOR]

The Full of Economic-Environment Linkages and Integration dX/dt (FeliX) model is a System Dynamics-based Integrated Assessment Model (IAM), explicitly incorporating human behaviors and their dynamic interactions among global systems. This paper presents FeliX 2.0, describing the detailed framework and key interactions among nine integrated modules. FeliX 2.0 refined its original version in population dynamics, food and land use systems, and socioeconomic settings for poverty analysis. Robust calibration is applied to key variables against their historical data since 1950. Future projections of multiple variables up to 2100 demonstrate coherences between FeliX 2.0 and the IAMs used in IPCC assessments. Both outputs (the robust calibration results and future projections) underscore the efficacy of FeliX 2.0 in capturing complex interdependencies within global systems. FeliX 2.0 stands as an informative tool and offers insights into interactions within the human-Earth system and the analysis of complex economic-environmental-social challenges in short- and long-term future. • A SD-based IAM model—FeliX 2.0—integrating human behavior for the human-Earth system simulation. • FeliX 2.0 refines FeliX 1.0 in population dynamics, food and land use, and poverty modeling. • Coherent projections up to 2100 for key variables in human-Earth systems by FeliX 2.0 • FeliX 2.0 stands as a pioneering tool for analyzing economic, environmental and social challenges. [ABSTRACT FROM AUTHOR]

Various approaches are available to assist stakeholders in identifying and resolving ecosystem service tradeoffs. However, existing tools fall short in simulating land use configuration effects on ecosystem services and subsequently making these effects accessible to users with varying levels of expertise. To address this gap, we introduce PLACES, a tool that estimates land use impacts on multiple ecosystem services by incorporating landscape-level processes. Tool results are provided in real-time and visualized to support a dialogue between different stakeholders. This study presents the tool development and application during a mixed stakeholder workshop, after which mental models, questionnaires, and videos were analyzed to evaluate PLACES. The tool increased the participants' understanding of insights of spatial processes and sparked discussions on the societal goals for sustainable landscapes. For future applications of PLACES, we encourage careful tailoring of the landscape representation and land use impact simulations to match the knowledge of the respective users. [Display omitted] • A new tool to elucidate ecosystem service tradeoffs in user-designed scenarios. • It models land use impacts on ecosystem services accounting for landscape-scale processes. • Outputs are calculated instantly and accessible to users with various backgrounds. • The tool supports interactive discussion and scenario design by diverse stakeholders. [ABSTRACT FROM AUTHOR]

• Collision-free low-thrust trajectories for asteroid landing is investigated. • A double homotopy method is developed for generating trajectory database. • Two DNN models are constructed for predicting features of optimal trajectories. • The developed DNN-based predictor can rapidly generate low-thrust trajectories. This study presents a fast generation method of time-optimal low-thrust trajectories based on deep neural networks (DNN) for the collision-free asteroid landings. An equivalent unconstrained differentiable problem is transformed via the introduction of smooth penalty function, so that it can be addressed with the optimal control framework. To efficiently solve the equivalent problem to generate sufficient dataset for training DNNs, a double homotopy method is developed. Specifically, the equivalent problem is connected to the time-optimal control problem without anti-collision through two consecutive simplifications, and a solving process with double backward continuation is also formulated. Besides, two DNN models are constructed to provide high-quality predictions for the minimum glide-slope constraint angle of an initial state, and the initial costates and landing time for time-optimal low-thrust trajectories with anti-collision constraints, respectively. As such, the efficiency of collision-free low-thrust landing trajectory generation is improved significantly. For the cases within the range of training dataset or within a certain extension, the low-thrust landing trajectories with a very small terminal landing error can be generated using the predicted initial costates. Meanwhile, with the high-quality initial costates, the high-precision landing trajectories can be obtained by the double homotopy method in only a few iterative steps. Finally, the promising results in a Bennu collision-free asteroid landing scenario validate the efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

• The VORSB farmwork can displayed the actual EH status than traditional method. • Land use change had significant spatiotemporal differences under a multi-scenario perspective. • The land development scenarios with target ecological protection increased EH. • The conversion of farmland to forest land had the greatest positive contribution to EH. • Future attention should be paid to the deterioration of EH caused by urban sprawl in metropolitan developed circle. Land-use changes dominated by high-intensity human activities have seriously threatened regional ecosystem health (EH) and will continue to increase in the future, especially in mountainous cities. Therefore, there is a need to systematically assess the contribution and spatial effects of future land use conversion on EH from a multi-scenario simulation perspective, which is essential for ecological conservation and management. For this purpose, taking Chongqing as an example, this study assessed the static distribution and dynamic evolution of EH over historical periods (2000–2020) and future multi-scenarios in 2030 using the vigor-organization-resilience-ecosystem services balance (VORSB) framework and patch-level land use simulation (PLUS) model, then analyzed the influence of land use conversion on EH and identified sensitive areas under multiple scenarios based on the contribution index and ecological sensitivity index. The results showed that Chongqing ecosystems were generally at a moderate healthy level during 2000–2020, with an increasing trend in EH level, with high-EH located in the eastern mountainous areas, while low-EH clustered in the western urban core and its peripheral areas. From 2020 to 2030, the EH level was improved by about 0.21% under the ecological protection scenario due to the transformation from farmland to forestland, which has the largest positive contribution of 0.111. In contrast, the EH level under the natural development and economic development scenarios declined by 1.95% and 3.07%, especially in the metropolitan developed circle, which was significantly related to the occupation of farmland resources by urban land, with negative contribution of −0.103 and −0.189, respectively. In the future, these regions should strictly control the urban expansion scale and strengthen high-quality farmland protection to achieve the balance of ecological protection and economic development. The findings will provide scientific guidance for the regional ecosystem conservation, land use planning, and urban sustainable development of mountainous cities. [ABSTRACT FROM AUTHOR]

• The potential conflict identification of production-living-ecological space uses POI to extract human-oriented factors. • Construct a multi-scale evaluation system integrating suitability and carrying capacity. • The result of incorporating human-oriented factors into the evaluation can more accurately reflect the actual situation. • The urban center area with large proportion of green space also has high ecological suitability. • Spatial conflicts mostly gather at the edge of urban expansion. The rapid urbanization in China has exacerbated the conflicts among production space, living space, and ecological space (PLES). Balancing economic development with ecological protection on limited land resources presents a pivotal challenge in the urbanization process. Mountainous urban agglomerations, with their complex terrain and limited development space, intensify PLES conflicts. Exploring potential PLES conflicts in these areas is crucial for optimizing spatial layout, coordinating human-land relationships, and promoting high-quality regional development. It is also a significant and challenging area in current research. Using the Central Yunnan Urban Agglomeration (CYUA) as a case study, this study integrated grid and administrative scales, incorporating human-oriented factors. A comprehensive evaluation system for mountain urban agglomerations, including suitability evaluation and spatial carrying capacity assessment, had been established. The conflict recognition matrix was used to identify potential PLES conflicts within the urban agglomeration. The results indicated that the PLES in the CYUA predominantly exhibited moderate levels of suitability. Production space suitability was higher in the southeast and lower in the northwest, living space suitability displayed a distinct strip-like distribution. Ecological space suitability was concentrated in the northeast and northwest, with lower suitability observed in the south. Apart from lake areas, approximately 71.92% of land in the CYUA faced potential conflicts regarding land use, primarily general spatial conflicts accounting for 49.79% of the total area. Intense conflict zones covered the smallest area, representing only 0.04% of the study area. The occurrence of potential spatial conflicts in this region was heavily influenced by both natural environmental factors and human activities. Suitable land areas were notably concentrated in regions with high human activity levels, favorable natural environments, and single land use functions. Conflicts were particularly concentrated in transition zones between human production and living spaces and ecological areas. The findings of this study offer valuable insights for guiding urban planning and management strategies not only for the CYUA but also for other mountainous urban agglomerations facing similar challenges. [ABSTRACT FROM AUTHOR]

[Display omitted] • A discrete DOEI is proposed, which is more suitable for dryland oasis analysis. • The response of ecological environment quality to land use transition was explored. • Expanding farmland may harm basin ecology, especially downstream. Oasis ecosystems in dryland regions take on crucial significance in human survival and development since the quality of these regions that are characterized by ecological environments directly affects the well-being and socio-economic progress of their residents. Accordingly, it is of utmost importance to evaluate changes in ecological environment quality (EEQ) and gain insights into how land use transformation affects the local ecological condition, thus guiding the sustainable development of the dryland oasis. In this study, we evaluated the EEQ of the Middle Heihe River (MHR) from 1985 to 2020 by constructing the dryland oasis ecological index (DOEI) through the Google Earth Engine (GEE) platform. Moreover, we investigated how land use transformation influenced the EEQ of the MHR. Results suggested that (1) the DOEI can effectively capture the comprehensive dynamics of long-term EEQ changes in MHR, providing a more accurate representation of land type characteristics. (2) The EEQ in MHR generally exhibited a trend of initial improvement, followed by deterioration. The desert-oasis transition zone acts as the most significant area of EEQ changes in the MHR. The mutual transformation among cropland, grassland and desert is the primary factor for EEQ in the MHR. (3) The expansion of cropland in the MHR pronouncedly affected the EEQ. However, this continuous expansion may impose greater stress on water resources while potentially threatening ecological degradation in the lower reaches of the river basin. The DOEI built through the GEE platform is capable of indicating the spatiotemporal status of the EEQ in the dryland oasis, which holds significant implications for studying the interaction between human activities and EEQ in the dryland oasis. [ABSTRACT FROM AUTHOR]

[Display omitted] • Framework to quantitatively assess CSS supply–demand and spatial flow. • Spatial heterogeneity and imbalance in CSS supply–demand exist. • CSS demand is rising, while supply is falling. • Forests are the main carbon sinks, with humans as the primary CSS consumers. • A reference for analyzing CSS flow in ecosystems using the SPANs model. The key challenge created by global climate change is to implement effective carbon–neutral programs. The carbon sequestration service (CSS) establishes spatial and temporal connections between carbon sequestration supply and demand, so accurate scientific quantification of the CSS supply–demand balance is essential. However, a standard assessment framework for quantifying CSS supply–demand is currently lacking. In this study, we developed a spatio-temporal assessment framework for quantifying CSS supply–demand balance under land use change, based on the SPANs model. We followed the flow of CSS from supply to demand areas through spatial visualization based on the main wind direction and defined the transport path and quantity of CSS flow, taking Lancang Mekong River Basin (LMRB) as a case. The results showed that: (1) The total supply of CSS decreased by 1.14 million tons from 2000 to 2020, and total demand for CSS increased by 8.1 million tons. (2) CSS surplus areas were mainly concentrated in forested regions, with a maximum surplus of 4.31 t/ha. Deficit areas were dominated by cultivated land and artificial surfaces, with a maximum deficit of −1101.21 t/ha. There was spatial heterogeneity in CSS distribution and a clear imbalance between supply and demand. (3) Three out of six countries in the basin showed significant changes in CSS flow, with a decrease in demand area observed in Thailand and an increase in demand area observed in Cambodia and Vietnam. (4) CSS flow was mainly from north to south, with higher CSS in Thailand and lower flow in China. Thus the analysis revealed supply–demand imbalances in CSS and provided an objective understanding of the spatial flow of CSS. This scientific and intuitive theoretical basis and data support can be used for regional carbon management in LMRB and global carbon balance control. [ABSTRACT FROM AUTHOR]