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The rapid pace of urbanization and industrialization has reshaped land use patterns globally, particularly within the interconnected domains of 'production, living, and ecological spaces' (PLES). Understanding the spatiotemporal evolution of these spaces is crucial for guiding sustainable development. Although a number of previous studies have explored aspects of their dynamics and driving factors, further investigation is needed to fully understand their long-term spatiotemporal evolution and the broader influences of socio-economic and environmental forces. This study aims to fill that important gap by leveraging advanced remote sensing techniques to analyze PLES transformations over a 30-year period. Using Henan Province, China, as a testbed, this study applies high-resolution Landsat data, land use transition matrices, dynamic degree analysis, Principal Component Analysis (PCA), and multiple linear regressions to uncover trends and underlying drivers. The results reveal a substantial reduction in production spaces by 3394.62 km² steady growth in living spaces by 4459.41 km² and complex, non-linear changes in ecological spaces, which decreased by 1067.43 km². Key driving forces, such as economic growth, urbanization, and fiscal policies are identified and discussed. These insights provide a robust framework for sustainable land use planning, with broader implications for rapidly urbanizing regions worldwide. [ABSTRACT FROM AUTHOR]

Given global changes and the loss of ecosystem services, it is crucial to assess the effects of landscape characteristics on ecosystem service distribution for sustainable territory management. Italy's diverse landscapes present an opportunity to study this effect. This study identified optimal elevation and landscape heterogeneity ranges that optimize four ecosystem service provisions across Italy. We mapped ecosystem services across Italy using generalized additive models (GAM) to assess their spatial relationships with landscape characteristics, such as elevation and heterogeneity, and specifically, we identified their optimal values concerning elevation and landscape heterogeneity. In Italy, agricultural production is concentrated at low altitudes, like the Po Valley, while the pre-Alps and Apennines regions at intermediate altitudes provide ecosystem services like timber production and carbon storage. However, elevation gradient and landscape heterogeneity significantly influence trade-offs between agricultural production and these services. The optimal altitude for timber production, carbon storage, and habitat quality is around 1500 m above sea level, while agricultural production peaks at the lowest and highest elevations. Our study shows landscape features' significant role in supporting specific ecosystem services. This information is crucial for guiding land use planning and management decisions, especially under global land use and climate change. [ABSTRACT FROM AUTHOR]

Peri-urban catchment areas are increasingly susceptible to floods due to rapid land use transformations and unplanned urban expansion. This study comprehensively examines flood vulnerability in the rapidly developing peri-urban areas of North Bhubaneswar, focusing on significant changes in Land Use/Land Cover (LULC) and hydrological dynamics from 2004 to 2024, utilizing Geographic Information System (GIS) tools. The analysis reveals substantial shifts in land use patterns, with the urban footprint expanding by 71.8%, cropland decreasing by 21.7%, and forest areas by 13.6%. These changes have led to increased impervious surfaces, resulting in higher surface runoff and decreased groundwater recharge, thereby exacerbating flood risks in the region. The GRID-based vulnerability analysis classifies 90 villages within the catchment area based on their vulnerability levels, identifying 20 villages as high-risk areas requiring urgent attention, 44 villages as medium vulnerable, and 26 villages as low vulnerable. These classifications are based on factors such as proximity to drainage networks, slope, geomorphology, and LULC characteristics, with areas near drainage channels and low-lying regions being prone to flooding. The analysis integrates multiple factors to provide a comprehensive assessment of flood risk, highlighting the need for sustainable land use planning, conservation of vegetated areas, and the implementation of advanced flood prevention strategies in the peri-urban areas. Extending this research to other fringe regions could offer further valuable insights, guiding flood prevention and sustainable development strategies for areas undergoing significant land use transformations to effectively mitigate future flood risks. [ABSTRACT FROM AUTHOR]

Farmland shelterbelts are aimed at farmland protection and productivity improvement, environmental protection and ecological balance, as well as land use planning and management. Farmland shelterbelts play a vital role in determining the structural integrity and overall effectiveness of farmland, and assessing the dynamic changes within these protective forests accurately and swiftly is essential to maintaining their protective functions as well as for policy formulation and effectiveness evaluation in relevant departments. Traditional methods for extracting farmland shelterbelt information have faced significant challenges due to the large workload required and the inconsistencies in the accuracy of existing methods. For example, the existing vegetation index extraction methods often have significant errors, which remain unresolved. Therefore, developing a more efficient extraction method with greater accuracy is imperative. This study focused on Youyi Farm in Heilongjiang Province, China, utilizing satellite data with spatial resolutions ranging from 0.8 m (GF-7) to 30 m (Landsat). By taking into account the growth cycles of farmland shelterbelts and variations in crop types, the optimal temporal window for extraction is identified based on phenological analysis. The study introduced a new index—the Re-Modified Anthocyanin Reflectance Index (RMARI)—which is an improvement on existing vegetation indexes, such as the NDVI and the improved original ARI. Both the accuracy and extraction results showed significant improvements, and the feasibility of the RMARI was confirmed. The study proposed four extraction schemes for farmland shelterbelts: (1) spectral feature extraction, (2) extraction using vegetation indexes, (3) random forest extraction, and (4) RF combined with characteristic index bands. The extraction process was implemented on the GEE platform, and results from different spatial resolutions were compared. Results showed that (1) the bare soil period in May is the optimal time period for extracting farmland shelterbelts; (2) the RF method combined with characteristic index bands produces the best extraction results, effectively distinguishing shelterbelts from other land features; (3) the RMARI reduces background noise more effectively than the NDVI and ARI, resulting in more comprehensive extraction outcomes; and (4) among the satellite images analyzed—GF-7, Planet, Sentinel-2, and Landsat OLI 8—GF-7 achieves the highest extraction accuracy (with a Kappa coefficient of 0.95 and an OA of 0.97), providing the most detailed textural information. However, comprehensive analysis suggests that Sentinel-2 is more suitable for large-scale farmland shelterbelt information extraction. This study provides new approaches and technical support for periodic dynamic forestry surveys, providing valuable reference points for agricultural ecological research. [ABSTRACT FROM AUTHOR]

The availability of current land cover and land use (LCLU) information for monitoring the status of land resources has considerable value in ensuring sustainable land use planning and development. Similarly, the need to provide updated information on the extent of LCLU change in West Africa has become apparent, given the increasing demand for land resources driven by rapid population growth. Over the past decade, multiple projects have been undertaken to produce regional and national land cover maps. However, using different classification systems and legends has made updating and sharing land cover information challenging. This has resulted in the inefficient use of human and financial resources. The development of the Land Cover Meta Language (LCML) based on International Organization for Standardization (ISO) standards offers an opportunity to create a standardized classification system. This system would enable easier integration of regional and national data, efficient management of information, and better resource utilization in West Africa. This article emphasizes the process and the need for multistakeholder collaboration in developing a standardized land cover classification system for West Africa, which is currently nonexistent. It presents the survey data collected to evaluate historical, current, and future land cover mapping projects in the region and provides relevant use cases as examples for operationalizing a standardized land cover classification legend for West Africa. [ABSTRACT FROM AUTHOR]

The establishment of urban ventilation corridors (UVCs) aims to mitigate the urban heat island effect. While most studies focus on the construction and assessment of the environmental benefit of UVCs, they often overlook the analysis of UVCs' topological features. This research integrates multi-source data including 3D urban buildings, historical meteorological observations, high-resolution remote sensing, and land use planning, combined with multiple models, including geographic information system spatial analysis, circuit theory, and complex networks. Based on an assessment of urban ventilation potential, the circuit model was applied to extract UVCs aligned with the prevailing wind direction for both summer and winter seasons. Complex network modeling was employed to analyze the topological features of the ventilation network. From the analytical results, a multi-level wind corridor system for Chengdu was quantitatively developed. The results indicate that the city's overall ventilation resistance is high, with notable spatial clustering, and the southeastern region faces substantial ventilation obstructions. A total of 143 critical ventilation nodes were identified, with the number of air inlets and outlets in summer being significantly fewer than in winter. However, the cooling effect of ventilation corridors in the prevailing summer wind direction is superior to that in winter. The ventilation network comprises 16 communities with distinct ventilation characteristics, exhibiting moderate connectivity, lacking small-world properties, and showing congestion and instability. [ABSTRACT FROM AUTHOR]

The process of urbanization leads to the rapid expansion of construction land and brings a series of ecological and environmental problems. The ecological network, as a linear landscape element, is of great significance to improve the quality of the regional ecological environment. In this study, the Morphological Spatial Pattern Analysis (MSPA) and the model of Minimum Cumulative Resistance (MCR) were used to construct the ecological corridors in the central city of Fuzhou, and the land use pattern under the constraints of the ecological network was simulated and quantified by the patch-level land use simulation (PLUS) tool with the results of the identification of ecological corridors. Meanwhile, with the help of InVEST habitat quality model, the regional habitat quality under different development scenarios was compared. The results show that (1) 19 ecological sources and 35 ecological corridors were identified; (2) under the constraints of ecological corridors, the area of forested land in the study area in 2027 was increased by 1.57% and the area of built-up land was reduced by 0.55% compared with that in 2022; (3) and under the constraints of ecological corridors, the mean value of habitat quality in Fuzhou City improved by 0.0055 and 0.0254 compared with 2022 and 2027 natural evolution scenarios, respectively. The study provides decision-making assistance for the construction of ecological corridors from the perspective of land use planning. [ABSTRACT FROM AUTHOR]

With China's rapid economic development in recent years, enhancing the sense of well-being among citizens has become a critical objective. However, the interests of various stakeholder groups are often overlooked in decision-making surrounding land use. In this study, Yongsheng County, Yunnan Province serves as a case study for land use scenario simulations. The equivalent factor method is combined with Participatory Rural Appraisal (PRA) to investigate the relationship between ecosystem multifunctionality (EMF) and the equity index of multiple stakeholder groups in various land use scenarios. We also explore whether an optimal combination of land use types exists. The results indicate that (1) The current ecosystem service value in Yongsheng County is primarily driven by climate regulation and biodiversity conservation, with a relatively high functional value index but a comparatively low equity index; (2) Different stakeholder groups mainly prioritize food production and ecosystem services impacting food production, such as water resource provision and climate regulation; (3) A land use allocation pattern of 20% farmland, 4% water bodies, 21% mixed forest, 20% coniferous forest, and 35% grassland appears to provide the optimal EMF index while simultaneously achieving the optimal equity index across stakeholder groups. This research may offer valuable insights for optimizing land use planning while taking into account the well-being of diverse stakeholder groups. It also may have practical implications for the formulation of innovative land use management strategies. [ABSTRACT FROM AUTHOR]

Land use regulations have played a critical role in the siting and operation of renewable energy technologies. While there is a growing literature on the siting of wind and solar technologies, less is known about the relationship between local codes and planning decisions and the development of wood-based bioenergy technologies, particularly in rural places. This research examines the relationship between local land use policies and the siting and operation of different types of wood-based bioenergy technologies in northern Michigan, USA. Land use codes including zoning laws and ordinances related to wood-burning devices from 506 cities, townships, and villages within 36 counties in northern Michigan were combined with US Census data in a GIS database. ArcGIS was used to examine geographical differences between communities and socioeconomic factors related to different regulatory approaches. We found that areas with greater population densities and higher income and education levels tended to have more nuanced land use codes related to all scales of wood-burning, including residential wood heating, commercial-scale heating, and power generation. This paper emphasizes the importance of local decision-making and land use policies in shaping the development of wood-based energy technologies, and suggests the need for greater attention to rural community dynamics in planning the shift to a lower-carbon economy. [ABSTRACT FROM AUTHOR]

Spatial Data Infrastructure (SDI) is a decision-making tool that is often used in the area of urban planning. At the same time, many other data sources with great utility potential, such as Big Data, can be identified. The aim of the paper is to present the possibility of using mobile Big Data collections with data from Polish SDI, for the purposes of local spatial planning on the example of the tourist town, Mikolajki in Poland. The publication also focuses on assessing the quality of data, as well as the decision-making process supported by these sources. The draft of the local spatial development plan was verified based on integrated data sources. The results showed that the visualization of Big Data as a heat map may be used in urban tasks and as the thematic layer integrated with vector and raster data sets from the SDI in the geographic information system software. The contribution is the practical example how information about users of mobile devices and some information from behavioral profiles may be analyzed for the purposes of verifying planned land use. [ABSTRACT FROM AUTHOR]

The concept of sustainability has been widely recognized as a pivotal objective for future growth. Therefore, it is imperative to incorporate the principles of sustainability into policies and plans, particularly in land use and agri-food production, sectors often associated with negative environmental impacts. Addressing all three pillars of sustainability—environmental, economic, and social—is essential, within the contexts of agri-food production and land use. Consequently, sustainable rural development is also critical. This study utilizes Iceland as a case to examine whether and how sustainability goals are translated from national policies to municipal plans, which represent the governance level closest to implementation. The research employs content analysis of national policies and municipal plans, utilizing grounded theory to code the content. The findings indicate that while the concept of sustainability is embedded in Icelandic policies and goals, there is a tendency to overlook the economic and social dimensions. Additionally, the study reveals a limited application of sustainability principles in rural development and agri-food production. Recognizing the "wicked" nature of sustainability, which complicates its implementation, is crucial for advancing from goal setting to effective action. [ABSTRACT FROM AUTHOR]

Traditional Newmark models estimate earthquake-induced landslide hazards by calculating permanent displacements exceeding the critical acceleration, which is determined from static factors of safety and hillslope geometries. However, these studies typically predict the potential landslide mass only for the source area, rather than the entire landslide zone, which includes both the source and sliding/depositional areas. In this study, we present a modified Newmark Runout model that incorporates sliding and depositional areas to improve the estimation of landslide chain risks. This model defines the landslide runout as the direction from the source area to the nearest river channel within the same slope unit, simulating natural landslide behavior under gravitational effects, which enables the prediction of the entire landslide zone. We applied the model to a subset of the Minjiang Catchment affected by the 1933 MW 7.3 Diexi Earthquake in China to assess long-term landslide chain risks. The results indicate that the predicted total landslide zone closely matches that of the Xinmo Landslide that occurred on 24 June 2017, despite some uncertainties in the sliding direction caused by the old landslide along the sliding path. Distance-weighted kernel density analysis was used to reduce the prediction uncertainties. The hazard levels of the buildings and roads were determined by the distance to the nearest entire landslide zone, thereby assessing the landslide risk. The landslide dam risks were estimated using the kernel density module for channels blocked by the predicted landslides, modeling intersections of the total landslide zone and the channels. High-risk landslide dam zones spatially correspond to the locations of the knickpoints primarily induced by landslide dams, validating the model's accuracy. These analyses demonstrate the effectiveness of the presented model for Newmark-based landslide risk estimations, with implications for geohazard chain risk assessments, risk mitigation, and land use planning and management. [ABSTRACT FROM AUTHOR]

Featured Application: Determination the scale of hazard caused by episodic water runoff in rural areas will allow better management of the land and limit its negative effects. There has been an increase in the frequency of hazards associated with meteorological and hydrological phenomena. One of them is flash floods occurring episodically in areas of concentrated runoff—valleys without permanent drainage. In the opinion of residents and local authorities, these are potentially safe areas—they are not threatened by floods and are therefore often occupied by buildings. The importance of addressing flash floods in land use planning is essential for sustainable development and disaster risk reduction. The objective of this research was to assess the level of the hazard and to evaluate its presence in land use planning activities. This manuscript fills a research gap, as to date flash flood threats have not been analyzed for individual buildings located in catchments of dry valleys in temperate climates. More than 12,000 first-order catchments were analyzed. The study covered an upland area located in East Poland, which is characterized by high population density and dispersed rural settlement. Within the 10 municipalities, buildings located on potential episodic runoff lines were identified. Qualitative assessment was applied to ascertain the susceptibility of catchments to flash floods. Such criteria as slopes, size, shape of the catchment area, and land cover, among others, were used. Between 10 and 20% of the buildings were located on episodic runoff lines, and about 900 sub-catchments were highly or very highly susceptible to flash floods. The way to reduce the negative effects of these phenomena is to undertake proper land use planning based on knowledge of geohazards, including flash floods. However, an analysis of available planning documents shows that phenomena of this type are not completely taken into account in spatial management processes. [ABSTRACT FROM AUTHOR]

The study of the spatiotemporal evolution characteristics of ecosystem service values (ESVs) is an important basis for the coordinated development of the regional nature, economy, and society and the optimization of the ecological environment. The ecological zone is an important component of the Beijing–Hangzhou Grand Canal cultural belt. Ecosystem services are a concrete manifestation of land use structure and function. A thorough study of the value of ecosystem services in areas along the Beijing–Hangzhou Grand Canal is important for promoting the long-term and stable sustainable development of the regional economy. Based on a revised equivalent factor table, this study selected land use data from 1991, 2006, and 2021 to analyze the temporal and spatial evolution characteristics of ESVs along the Beijing–Hangzhou Grand Canal. The results show that (1) the ESVs along the Grand Canal first increased and then decreased from 1991 to 2021. The reason for this is the change in land use along the Beijing–Hangzhou Grand Canal. Specifically, the conversion of land use types from farmland to water areas contributed to the increase in the value of ecosystem services, while the conversion of farmland and grassland into construction land led to a decrease in the service value of the region. (2) the value of individual ecosystem services along the Beijing–Hangzhou Grand Canal from 1991 to 2021 varied greatly. The ESV provided by hydrological regulation was the largest and the ESV provided by maintenance nutrients was the smallest. (3) the areas along the Beijing–Hangzhou Grand Canal exhibited a specific pattern in terms of the value of ecosystem services, with the regions centered in Beijing and Tianjin showing relatively low values, while the middle section of the Grand Canal demonstrated relatively high ESV. According to the spatial and temporal distribution characteristics and the leading factor for the changes in ESVs, appropriate policies can be formulated in respective regions to implement ecological protection and land use planning, thereby providing a reference for the adaptation and restoration strategies of the ecosystem along the Grand Canal. [ABSTRACT FROM AUTHOR]

Most high-mountain regions worldwide are susceptible to snow avalanches during the winter or all year round. In this study, a Universal Snow Avalanche Modeling Index is developed, suitable for determining avalanche hazard in mountain regions. The first step in the research is the collection of data in the field and their processing in geographic information systems and remote sensing. In the period 2023–2024, avalanches were mapped in the field, and later, avalanches as points in geographic information systems (GIS) were overlapped with the dominant natural conditions in the study area. The second step involves determining the main criteria (snow cover, terrain slope, and land use) and evaluating the values to obtain the Snow Avalanche Formation Index (SAFI). Thresholds obtained through field research and the formation of avalanche inventory were used to develop the SAFI index. The index is applied with the aim of identifying locations susceptible to avalanche formation (source areas). The values used for the calculation include Normalized Difference Snow Index (NDSI > 0.6), terrain slope (20–60°) and land use (pastures, meadows). The third step presents the analysis of SAFI locations with meteorological conditions (winter precipitation and winter air temperature). The fourth step is the modeling of the propagation (simulation) of other parts of the snow avalanche in the Flow-R software 2.0. The results show that 282.9 km2 of the study area (Šar Mountains, Serbia) is susceptible to snow avalanches, with the thickness of the potentially triggered layer being 50 cm. With a 5 m thick snowpack, 299.9 km2 would be susceptible. The validation using the ROC-AUC method confirms a very high predictive power (0.94). The SAFI–Flow-R approach offers snow avalanche modeling for which no avalanche inventory is available, representing an advance for all mountain areas where historical data do not exist. The results of the study can be used for land use planning, zoning vulnerable areas, and adopting adequate environmental protection measures. [ABSTRACT FROM AUTHOR]

Recent anthropogenic activities have escalated human exploitation of riparian zones of river ecosystems, consequently diminishing aquatic biodiversity. This intensification of land use is also causing water quality degradation and changes in water environmental factors, evidenced by increased nutrient levels and adversely impacting the community structure and diversity of aquatic organisms. Notably, the Weihe River Basin, the largest tributary of the Yellow River, has demonstrated signs of significant anthropogenic pressure. Despite this, comprehensive investigations examining the effects of land-use intensity on aquatic organism diversity in this watershed remain limited. In this study, the environmental impacts and macroinvertebrate diversity under high-intensity and low-intensity land-use scenarios within the Weihe River Basin were investigated through field surveys conducted during the spring and autumn seasons. Our results demonstrated that areas under high-intensity land use exhibited elevated nutrient concentrations (e.g., total nitrogen) compared to those under low-intensity land use. These environmental changes significantly influenced the macroinvertebrate community structure, reducing functional and phylogenetic diversities in high-intensity land-use watersheds. Hydrological factors (water depth, river width, and discharge) have a significant impact on macroinvertebrate taxonomic diversity. Thus, understanding the effects of land-use intensity on aquatic biodiversity is essential for ecological assessments of impacted watersheds and developing management strategies for the sustainable use and planning of riparian lands in the Weihe River Basin. [ABSTRACT FROM AUTHOR]

Different types of rural settlement agglomerations have been formed and mixed in space during the rural revitalization strategy implementation in China. Discriminating them from remote sensing images is of great significance for rural land planning and living environment improvement. Currently, there is a lack of automatic methods for obtaining information on rural settlement differentiation. In this paper, an improved encoder–decoder network structure, ASCEND-UNet, was designed based on the original UNet. It was implemented to segment and classify dispersed and clustered rural settlement buildings from high-resolution satellite images. The ASCEND-UNet model incorporated three components: firstly, the atrous spatial pyramid pooling (ASPP) multi-scale feature fusion module was added into the encoder, then the spatial and channel squeeze and excitation (scSE) block was embedded at the skip connection; thirdly, the hybrid dilated convolution (HDC) block was utilized in the decoder. In our proposed framework, the ASPP and HDC were used as multiple dilated convolution blocks to expand the receptive field by introducing a series of dilated rate convolutions. The scSE is an attention mechanism block focusing on features both in the spatial and channel dimension. A series of model comparisons and accuracy assessments with the original UNet, PSPNet, DeepLabV3+, and SegNet verified the effectiveness of our proposed model. Compared with the original UNet model, ASCEND-UNet achieved improvements of 4.67%, 2.80%, 3.73%, and 6.28% in precision, recall, F1-score and MIoU, respectively. The contributions of HDC, ASPP, and scSE modules were discussed in ablation experiments. Our proposed model obtained more accurate and stable results by integrating multiple dilated convolution blocks with an attention mechanism. This novel model enriches the automatic methods for semantic segmentation of different rural settlements from remote sensing images. [ABSTRACT FROM AUTHOR]

Semantic segmentation is primarily employed to generate accurate prediction labels for each pixel of the input image, and then classify the images according to the generated labels. Semantic segmentation of building and water in remote sensing images helps us to conduct reasonable land planning for a city. However, many current mature networks face challenges in simultaneously attending to both contextual and spatial information when performing semantic segmentation on remote sensing imagery. This often leads to misclassifications and omissions. Therefore, this paper proposes a Dual-Branch Network with Spatial Supplementary Information (SPNet) to address the aforementioned issues. We introduce a Context-aware Spatial Feature-Extractor Unit (CSF) to extract contextual and spatial information, followed by the Feature-Interaction Module (FIM) to supplement contextual semantic information with spatial details. Additionally, incorporating the Goal-Oriented Attention Mechanism helps in handling noise. Finally, to obtain more detailed branches, a Multichannel Deep Feature-Extraction Module (MFM) is introduced to extract features from shallow-level network layers. This branch guides the fusion of low-level semantic information with high-level semantic information. Experiments were conducted on building and water datasets, respectively. The results indicate that the segmentation accuracy of the model proposed in this paper surpasses that of other existing mature models. On the building dataset, the mIoU reaches 87.57, while on the water dataset, the mIoU achieves 96.8, which means that the model introduced in this paper demonstrates strong generalization capabilities. [ABSTRACT FROM AUTHOR]

This study first examines changes in the amount of residential area on a regional scale, which is said to shrink following population decline, using Japan as an example, where population decline is already underway in most of the country. Second, it examines how the regional governments have set future targets for residential areas and whether these targets are consistent with the current trend. Third, it examines how prefectures, Japan's regional governments, are responding to this situation through regional land use planning. The methodologies of the paper are a combination of collecting and sorting out the related data, reviewing and extracting information from planning documents, and conducting interviews with persons in charge. In conclusion, residential areas have continued to increase on a regional scale, even as the population has declined. Shrinkage does not follow population decline on a regional scale. It was also found that the amount of residential area changed more closely with the change in households than with the population. National and regional land use plans generally set targets for more shrinkage than the actual trend. The underestimation of the amount of residential area was due to the rapid decline in the number of persons per household. Cases of the three prefectures showed that specific control is left to the individual acts, while the measures are indicated in the wording by the prefectural land use plans. [ABSTRACT FROM AUTHOR]

Land use and land cover (LULC) changes driven by ecological restoration and protection projects play a pivotal role in reshaping landscape patterns. However, the specific impacts of these projects on landscape structure remain understudied. In this research, we applied geographically weighted regression (GWR) to analyze the spatial relationships between typical land use expansion and landscape pattern characteristics in the Lesser Khingan Mountains–Sanjiang Plain region between 2017 and 2022. Our results indicate three key findings: (1) Significant spatial heterogeneity exists in the relationship between landscape patterns and land use expansion, which varies across geographic locations; (2) Ecological restoration projects generally reduce fragmentation, dominance, and heterogeneity while enhancing connectivity, particularly in forest and farmland regions. However, excessive land use expansion in certain areas may reverse these positive effects; (3) Landscape complexity increases in high-altitude mountainous regions due to land use expansion but decreases in plains, particularly in forest-to-farmland conversions. These findings provide new insights into how landscape patterns respond to ecological restoration efforts and offer actionable guidance for improving future land use planning and policy decisions. Our study highlights the need to consider local geomorphological factors when designing ecological projects, ensuring that restoration efforts align with regional landscape dynamics to maintain landscape integrity. [ABSTRACT FROM AUTHOR]

A comprehensive approach to ecological functional zoning in the Shenzhen region of China is presented in this study. Through the integration of advanced geospatial analysis tools, multiple data sources, and sophisticated statistical techniques, different ecological functions have been identified and categorized based on a comprehensive set of indicators and spatial analysis techniques. The three-level zoning framework established in this study offers policymakers, urban planners, and environmental managers a nuanced understanding of the region's environmental characteristics, and highlights areas of ecological significance that warrant special attention and protection. It has been demonstrated that the data-driven approach to ecological functional zoning is effective in delineating distinct ecological zones within the study area. This study's findings carry significant implications for future land use planning, conservation efforts, and sustainable development practices in the Shenzhen region. In essence, this study contributes to the broader discourse on ecological planning and environmental management by providing a systematic and data-driven approach to delineating ecological functional zones in urbanizing regions. [ABSTRACT FROM AUTHOR]

Over the last few years, new land use planning instruments to reduce the negative consequences of recent land use/cover changes (farmland abandonment, wildfires) have been proposed in Galicia (northwest Spain). Understanding the complex relationship between biophysical constraints, socioeconomic drivers and land use/cover changes is paramount for their successful implementation. In this work, we present an analysis of recent (2005–2017) land use/cover changes in the region, along with a classification of municipalities in homogeneous groups with different patterns of land use and land use change. We then characterize those groups regarding the demographic and employment structure, the economic performance, the characteristics of the primary sector, the land ownership structure and the relative importance of recent wildfire events and the biophysical suitability for the main productions of the primary sector in the region. The results allowed us to identify four different groups of municipalities which are clearly separated by specific patterns of land use (an area where most of the population lives, an area devoted to forest production, another for farming production and a final one dominated by semi-natural covers). These four areas followed a gradient of decreasing levels of population density and economic activity. While land use patterns in different areas could be explained largely by biophysical suitability, the fragmentation of land ownership emerged as a relevant factor, which can explain the greater presence of farmland abandonment—and, therefore, higher wildfire risk—in certain areas. These results offer relevant guidelines for the successful implementation of the new land use planning instruments in the region. [ABSTRACT FROM AUTHOR]

Re-considering the interactions between society and natural resources is fundamental in pursuing sustainability and adaptation to climate change in cities. The representation in urban planning instruments reveals an inadequate consideration of valley hillslopes as interface systems or as 'places' with possible multiple roles and meanings for populations. Beyond landslide and flooding considerations, valley hillslopes are scarcely identified as distinct entities from the valley and the plateau, investigated as sites of diverse possible uses, and analysed in terms of which variables related to the relief's forms influence their use. Confronting urban planning instruments that reduce slopes to building spaces, this contribution advocates for a specific representation of valley hillslopes, highlighting the environment's variety within which the system interacts, the diversity of uses, and the interrelationships between form and land cover. By combining GIS mapping and statistical analysis, this research proposes a multi-scalar approach based on identifying valley hillslopes delineated through minimum units (geochore), integrated with land cover clustering and an analysis of the potential relations between land cover and six explanatory variables. The research points out the singularity and complexity of valley hillslopes, which should be incorporated into urban planning policy as potential cultural, ecological, or recreational resources for populations. [ABSTRACT FROM AUTHOR]

Mangrove ecotourism is gaining immense popularity in the Gulf Cooperation Council (GCC) countries as a neoliberal conservation tool, and it has contributed significantly to the growth of the tourism sector in the region over the past two decades. However, there is no comprehensive review on the full extent of mangrove ecotourism activities and the contribution to mangrove conservation/restoration and economic growth in the region. A systematic literature review approach was used to examine the evolution of mangrove ecotourism in the GCC countries from 2010 to 2023. A total of 55 articles were retrieved from the Google and Google Scholar search engines, and the Scopus and Web of Science databases were incorporated. We synthesized the results and provided perspectives on the following: (1) the geographical and temporal distribution of studies in relation to mangrove extent, (2) key sites, attractions, and values for mangrove ecotourism activities, (3) the positive and negative impacts of mangrove ecotourism, and (4) existing mangrove conservation and restoration initiatives for the growth of mangrove ecotourism in the GCC countries. The findings underscore the significance of mangrove ecotourism in supporting economic development, protecting coastal ecosystems, and sustaining local livelihoods in the GCC countries. However, this study highlights the crucial need for sustainable coastal environmental management through integrated land use planning and zoning to address the negative impacts of anthropogenic pressures on mangrove ecosystems and ecotourism attractions. The use of remote sensing tools is invaluable in the monitoring of mangrove ecosystems and associated ecotourism impacts for informing evidence-based conservation and restoration management approaches. Thus, harnessing mangrove ecotourism opportunities can help the GCC countries with balancing economic growth, coastal environmental sustainability, and community well-being. [ABSTRACT FROM AUTHOR]

Biodiversity and ecosystem service models are frequently used to consider current conditions or recent changes in the availability of a service. The application of scenarios for biodiversity and ecosystem service assessment remains underdeveloped, particularly co-designed and fine-granular scenarios across different decision-making boundaries. Consequently, the data created by these modeling efforts may not be as valuable to conservation partners and policy makers. In this project, we used land use and land cover change scenarios co-developed with local and regional decision-makers in northwestern Virginia USA as key inputs for 18 different biodiversity and ecosystem service models. Specifically, we used the InVEST suite of models to predict the change in biodiversity and ecosystem indicators and evaluated differences in that change between scenarios and decision-making boundaries. We found that the scenarios produced distinct results for the majority of biodiversity and ecosystem services, especially as a function of population growth. However, we also found that some services varied more as a function of subregions reflecting the existing diversity of ecosystems and governance structures in the area. The co-designed scenarios and summary of the data across units resulted in the production of varied results that can be used to support land use planning by implementing partners. [ABSTRACT FROM AUTHOR]

The rational selection of subway station locations is an interdisciplinary problem encompassing architecture, transportation, and other fields. Few evaluation index systems and quantitative evaluation methods exist for choosing subway station locations; thus, this paper establishes a novel evaluation framework. Overall, 21 indicators covering the construction and operation phases are selected by a literature review, providing a basis for planning decision makers. The Projection Pursuit Method (PPM) and the Bald Eagle Search (BES) algorithm are employed to assign objective weights. The Continuous Ordered Weighted Averaging (COWA) operator is utilized to obtain subjective weights. A combination weighting method is used based on game theory to improve the accuracy of weight calculation. Game theory and extension cloud theory are applied to develop an improved extension cloud model and evaluate the suitability based on optimal cloud entropy. We conduct a case study of 15 stations on the Chengdu Metro Line 11, China. The results reveal that the coordination of the development plans, the alignment with the land use plan, and regional population density are the most crucial tertiary indicators that should be considered in selecting subway station locations. These findings agree with the actual conditions, demonstrating the scientific validity of the proposed evaluation method, which outperforms classical evaluation methods. The proposed method is efficient and feasible for selecting subway station locations. [ABSTRACT FROM AUTHOR]

Landslide susceptibility maps (LSMs) are valuable tools typically used by local authorities for land use management and planning activities, supporting decision-makers in urban and infrastructure planning. To address this, we proposed a refined method for landslide susceptibility assessment, which comprehensively considered both static and dynamic factors. Neural network methods were used for susceptibility analysis. Land use and land cover (LULC) change and InSAR deformation were then integrated into the traditional susceptibility zoning to obtain a refined susceptibility map with higher accuracy. Validation was conducted on the improved landslide susceptibility map using site landslide data. The results showed that the LULC were proven to be the core driving factors for landslide occurrence in the study area. The GRU model achieved the highest model performance (AUC = 0.886). The introduction of InSAR surface deformation and land use and land cover change data could rationalize the inappropriateness of traditional landslide susceptibility zoning, correcting the false positive and false negative areas in the traditional landslide susceptibility map caused by human activities. Ultimately, 12.25% of the study area was in high-susceptibility zones, with 3.10% of false positive and 0.74% of false negative areas being corrected. The proposed method enabled refined analysis of landslide susceptibility over large areas, providing technical support and disaster prevention and mitigation references for geological hazard susceptibility assessment and land management planning. [ABSTRACT FROM AUTHOR]

The validation of remotely sensed evapotranspiration (ET) products is important for the development of ET estimation models and the accuracy of the scientific application of the products. In this study, different ET products such as HiTLL, MOD16A2, ETMonitor, and SoGAE were compared using multi-source remote sensing data and ground-based data to evaluate their applicability in the Heihe River Basin (HRB) during 2010–2019. The results of the comparison with the site observations show that ETMonitor provides a more stable and reliable estimation of ET than the other three products. The ET exhibited significant variations over the decade, characterized by a general increase in rates across the HRB. These changes were markedly influenced by variations in land use and topographical features. Specifically, the analysis showed that farmland and forested areas had higher ET rates due to greater vegetation cover and moisture availability, while grasslands and water bodies demonstrated lower ET rates, reflecting their respective land cover characteristics. This study further explored the influence of various factors on ET, including land use changes, NDVI, temperature, and precipitation. It was found that changes in land use, such as increases in agricultural areas or reforestation efforts, directly influenced ET rates. Moreover, meteorological conditions such as temperature and precipitation patterns also played crucial roles, with warmer temperatures and higher precipitation correlating with increased ET. This study highlights the significant impact of land use and climatic factors on spatiotemporal variations in ET within the HRB, underscoring its importance for optimizing water resource management and land use planning in arid regions. [ABSTRACT FROM AUTHOR]

Reasonable land use planning and management efficiently allocates land resources, promotes socio-economic development, protects the ecological environment, and fosters sustainable development. It is a crucial foundation for achieving harmonious coexistence between humans and nature. Optimizing land use is key to land use planning and management. Four scenarios are established: an economic development scenario (EDS), an ecological protection scenario (EPS), a natural development scenario (NDS), and a coordinated development scenario (CDS). This study simulates land use patterns under these scenarios through the coupling of the GMOP and PLUS models. It analyzes the land use efficiency transformation index, landscape ecological index, comprehensive land use benefits, and ecosystem service value (ESV) for each pattern. The optimal land use pattern is determined by balancing these factors. The results indicated that under the CDS, the areas of wasteland, grassland, forest land, water bodies, construction land, and unused land in Lvliang City were 6724.29 km2, 6664.74 km2, 6581.84 km2, 126.94 km2, 1017.33 km2, and 0.42 km2, respectively. This represented the optimal land use plan for Lvliang City. The plan minimized human interference with the landscape pattern, achieved the highest land use efficiency transformation index, and reached a reasonable balance between land use benefits and ESV. The research findings provide valuable insights and decision support for regional land use planning, territorial space planning, and related policy formulation. [ABSTRACT FROM AUTHOR]

(1) Background: The use of multiscale prediction or the optimal scaling of predictors can enhance soil maps by applying pixel size in digital soil mapping (DSM). (2) Methods: A total of 200, 50, and 129 surface soil samples (0–30 cm) were collected by the CLHS method in three different areas, namely, the Marvdasht, Bandamir, and Lapuee plains in southwest Iran. Then, four soil properties—soil organic matter (SOM), bulk density (BD), soil shear strength (SS), and mean weighted diameter (MWD)—were measured at each sampling point as representative attributes of soil physical and chemical quality. This study examined different-scale scenarios ranging from resampling the original 30 m digital elevation model and remote sensing indices to various pixel sizes, including 60 × 60, 90 × 90, 120 × 120, and up to 2100 × 2100 m. (3) Results: After evaluating 22 environmental covariates, 11 of them were identified as the most suitable candidates for predicting soil properties based on recursive feature elimination (RFE) and expert opinion methods. Furthermore, among different pixel size scenarios for SOM, BD, SS, and MWD, the highest accuracy was achieved at 1200 × 1200 m (R2 = 0.35), 180 × 180 m (R2 = 0.67), 1200 × 1200 m (R2 = 0.42), and 2100 × 2100 m (R2 = 0.34), respectively, in Marvdasht plain. (4) Conclusions: Adjusting the pixel size improves the capture of soil property variability, enhancing mapping precision and supporting effective decision making for crop management, irrigation, and land use planning. [ABSTRACT FROM AUTHOR]

The incorporation of environmental variables into policies, programs, plans and projects has been achieved through the use of an Environmental Impact Assessment (EIA). However, the recognition by scholars of several limitations of the EIA has prompted the consideration of Strategic Environmental Assessment (SEA) as the appropriate instrument for achieving this objective. Studies on SEA have concentrated in phases prior to the decision-making, despite the fact that, after the strategic decision has been made, it is also necessary to follow up on the environmental impacts or effects produced by the plan, as well as the possibility of adopting measures to correct them when they cause adverse or unforeseen effects. The way in which this following-up takes place will vary from country to country, based on the respective legal system. Therefore, this study aims to understand these forms of follow-up in urban land planning instruments, at the local level which are legally binding, comparing regulations in France, Portugal and Chile, through three research questions focused on determining whether this phase exists, whether it is possible to modify the local planning instrument in the event of adverse effects and whether there are offset measures for those effects. This study employs a mixed methodology based on the law and content analysis, enabling the identification of pertinent aspects for investigation, the compilation of material for this study, and the answering of research questions through the comparative analysis of the laws of the selected countries. Results show differences and similarities between the regulations of the countries analyzed, regarding the ability to reverse undesired, negative or different effects from those originally considered in urban plans. It will shed light on the possibility for other countries to take follow-up action in the face of undesirable scenarios in the application of planning instruments. The gaps found in our research may also exist in the legislation of other countries. [ABSTRACT FROM AUTHOR]

Understanding the dynamics of land use and land cover (LULC) change in today's context of rapid urbanization is critical for sustainable urban planning and environmental conservation. Therefore, the research aim is to understand the LULC changes in the Chattogram Metropolitan Area and to assess the policy implications of these changes for sustainable urban development. Through a comparative analysis of LULC maps for two periods (1997–2007; 2007–2017), we investigated the transformation of a detailed planning zone before and after Detailed Area Plan (DAP) approval. Using quantitative data analysis and policy review, we elucidated the impacts of urbanization trends on local ecosystems—specifically the conversion of forest cover and waterscape use. The findings reveal a significant conversion of forested and waterscape areas to urban and peri-urban landscapes, highlighting the urgent need for sustainable planning interventions that focus on these peri-urban areas. The study further critiques the DAP's effectiveness, revealing a disconnect between regional policy implementation and local outcomes. This research proposes a validated, scalable framework for urban master plans that adapts to the complex socioecological contexts of rapidly urbanizing regions. [ABSTRACT FROM AUTHOR]

Chiang Mai is an emerging tourism-oriented city in Thailand. The booming tourism industry during the past decades has triggered significant expansion in its urban land area, resulting in a large number of newly-built residential communities appearing on unplanned land. In this study, we used multiscale geographically weighted regression (MGWR)-based hedonic price analysis to investigate 4624 housing transactions from 524 residential communities in Chiang Mai. This showed that the recent land-use planning in Chiang Mai has had unusual effects on housing prices; specifically, the effects of accessibility to hospitals, primary and secondary schools, green parks, and shopping malls could be ignored, demonstrating that local residents were well satisfied with land-use planning for high-quality medical and education sources and good living environments throughout the whole of Chiang Mai, and that no more land-use planning and investment on these facilities was needed. However, limited bus routes were only used for tourism and could not provide convenient routes for local residents, leading to their negative effects on housing prices in downtown areas, so the local government should lower the bus stop density in downtown areas and strengthen the transportation links between downtown areas and suburbs. Our study will not only support the urban land planning department of Chiang Mai to optimize residential communities and nearby facilities, but can also provide insights into housing price formation mechanisms in similar tourism-oriented cities in Thailand and beyond. [ABSTRACT FROM AUTHOR]

The North China Plain is the core region of China's economic development, and exploring the impacts of its land use and cover change (LUCC) and different urbanization regional drivers on carbon stocks is conducive to promoting sustainable development and carbon balance within the region. In the study, the North China Plain was selected as the study area, and the Patch-Generating Land Use Simulation (PLUS) model and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model were comprehensively applied to set up three land use policies, predict land use changes in 2030, and calculate carbon stock changes. Meanwhile, the Extreme Gradient Boosting (XGBoost) algorithm was used to analyze the degree of influence of different drivers on the supply of carbon stocks in different urbanization regions. Studies show that if the North China Plain prioritizes economic development, the area of farmland and forests will significantly decrease, leading to a substantial decline in carbon stocks. If ecological protection is the development focus, the reduction in farmland and forests will be less, and carbon stocks will remain relatively stable. If farmland protection is the development focus, the reduction in farmland will be minimal, but there will still be some impact on carbon stocks. The driving forces of carbon stock supply vary significantly across different regions. In underdeveloped regions, population density and vegetation cover have a greater impact on carbon stocks. In developing and urban–rural combined regions, vegetation cover and population migration have a greater impact on carbon stocks. In developed regions, the area of artificial land and gross domestic product (GDP) have a greater impact on carbon stocks. The study results provide scientific evidence for regional land use planning and policy formulation. [ABSTRACT FROM AUTHOR]

Understanding the land use pattern relationships regarding the composition, diversity, and abundance of soil microbial communities in a typical karst depression in southwestern China is crucial for assessing the stability of local karst ecosystems. However, these aspects in typical karst depressions within northern tropical karst seasonal rainforests in China remain limited. Therefore, we examined the differences in soil microorganism abundance, diversity, community composition, and co-occurrence networks under five land use types in a tropical karst region in southwestern China: sugarcane fields, orchards, grasslands, plantation forests, and secondary forests. The soil microbial communities of samples from these areas were analyzed using 16S rRNA gene amplification. The abundances of Acidobacteria and Ascomycota were lowest (20.66% and 66.55%, respectively) in secondary forests and highest (35.59% and 89.35%, respectively) in sugarcane fields. Differences in microbial abundance across land use types were related to soil pH and total phosphorus. PCoA and ANOSIM demonstrated significant differences in soil bacterial and fungal community structures among the five land use types. Bacterial alpha-diversity showed no significant variation among the different land uses, whereas fungal alpha-diversity exhibited significant differences. Observed Chao1, ACE, and Shannon indices indicated that secondary forests had the highest fungal alpha-diversity. Land use changes also influenced bacterial and fungal co-occurrence networks, with the networks in secondary forests, plantation forests, and orchards being more complex and stable than those in grasslands and sugarcane fields. Key taxa such as Proteobacteria, Planctomycetes, Chloroflexi, Ascomycota, and Basidiomycota were predominantly connected within the co-occurrence networks, highlighting their high functional potential. This study provides insights that can inform more effective land use planning and management strategies in karst depressions, thereby enhancing ecological sustainability and balance. [ABSTRACT FROM AUTHOR]

Land use and land cover changes (LULCCs) are vital indicators for assessing the dynamic relationship between humans and nature, particularly in diverse and evolving landscapes. This study employs remote sensing (RS) data and machine learning algorithms (MLAs) to investigate LULCC dynamics within the Indus River Delta region of Sindh, Pakistan. The focus is on tracking the trajectories of land use changes within mangrove forests and associated ecosystem services over twenty years. Our findings reveal a modest improvement in mangrove forest cover in specific areas, with an increase from 0.28% to 0.4%, alongside a slight expansion of wetland areas from 2.95% to 3.19%. However, significant increases in cropland, increasing from 22.76% to 28.14%, and built-up areas, increasing from 0.71% to 1.66%, pose risks such as altered sedimentation and runoff patterns as well as habitat degradation. Additionally, decreases in barren land from 57.10% to 52.7% and a reduction in rangeland from 16.16% to 13.92% indicate intensified land use conversion and logging activities. This study highlights the vulnerability of mangrove ecosystems in the Indus Delta to agricultural expansion, urbanization, resource exploitation, and land mismanagement. Recommendations include harmonizing developmental ambitions with ecological conservation, prioritizing integrated coastal area management, reinforcing mangrove protection measures, and implementing sustainable land use planning practices. These actions are essential for ensuring the long-term sustainability of the region's ecosystems and human communities. [ABSTRACT FROM AUTHOR]

After a landslide, swift and precise identification of the affected area is paramount for facilitating urgent rescue operations and damage assessments. This is particularly vital for land use planners and policymakers, enabling them to efficiently address hazard mitigation, the resettlement of those affected by the hazards, and to strategize land planning in the impacted regions. Despite the importance, conventional methods of monitoring landslides often fall short due to their restricted scope and the challenges associated with data acquisition. This study proposes a landslide detection method based on unsupervised multisource and target domain adaptive image segmentation (LUDAS) that is capable of achieving robust and generalized landslide mapping across multiple sources and target domains. Specifically, LUDAS consists of two phases. In the first phase, we introduce an unsupervised interdomain translation network to align the styles of multiple source domains to multiple target domains, generating pseudotarget domain data. Our interdomain translation network is capable of style transfer between any two domains. Through careful design of the network structure and loss functions, we ensure effective style transfer while preserving the content structure of the source domain images. In the second phase, the landslide segmentation model is trained in a supervised manner using annotated data from multiple source domains and multiple pseudotarget domains, resulting in a model with strong generalization capabilities that can adapt to multiple source and target domains. Finally, through extensive qualitative and quantitative analysis experiments, our study confirms that the proposed domain-adaptive segmentation model not only achieves exceptional landslide segmentation performance across multiple target domains but also, due to its good generalizability and transferability, has great potential for application in the emergency response to landslide. This capability can provide strong support for post-disaster emergency rescue, disaster assessment, and land planning in areas with scarce data. [ABSTRACT FROM AUTHOR]

Amidst the challenges posed by global climate change and accelerated urbanization, the structure and distribution of land use are shifting dramatically, exacerbating ecological and land-use conflicts, particularly in China. Effective land resource management requires accurate forecasts of land use and cover change (LUCC). However, the future trajectory of LUCC, influenced by climate change and urbanization, remains uncertain. This study developed an integrated multi-scenario framework by combining system dynamics and patch-generating land use simulation models to predict future LUCC in high-density urban regions under various Shared Socioeconomic Pathway (SSP)–Representative Concentration Pathway (RCP) scenarios. The results showed the following: (1) From 2020 to 2050, cultivated land, unused land, and water are projected to decrease, while construction land is expected to increase. (2) Future land use patterns exhibit significant spatial heterogeneity across three scenarios. Construction land will expand in all districts of Hangzhou, particularly in the main urban areas. Under the SSP585 scenario, the expansion of construction land is most significant, while it is the least under the SSP126 scenario. (3) Distinct factors drive the expansion of different land use types. The digital elevation model is the predominant factor for the expansion of forest and grassland, contributing 19.25% and 30.76%, respectively. Night light contributes the most to cultivated land and construction land, at 13.94% and 20.35%, respectively. (4) The average land use intensity (LUI) in central urban districts markedly surpasses that in the surrounding suburban areas, with Xiacheng having the highest LUI and Chun'an the lowest. Under the SSP126 scenario, the area with increased LUI is significantly smaller than under the SSP245 and SSP585 scenarios. These findings offer valuable guidance for sustainable planning and built environment management in Hangzhou and similarly situated urban centers worldwide. [ABSTRACT FROM AUTHOR]

This study presents a GIS-based Multi-Criteria Decision Analysis (MCDA) spatial model to assess land suitability for oil palm (OP) cultivation in rainfed conditions. Initially, twelve parameters, viz., rainfall, number of rainy days, mean temperature, RH, ground water level, soil pH, salinity, soil depth, surface texture, stoniness, slope, and drainage, were selected for assessing OP suitability in one of the states (Kerala). However, subsequent ground verification revealed significant discrepancies, which prompted refining the model by focusing on key parameters with greater accuracy and relevance. Accordingly, only five the most critical parameters affecting OP cultivation under rainfed conditions were selected through the rank sum method, and weights were assigned ac-cording to their significance. This study was aimed at creating a comprehensive tool for informed decision making in agricultural planning. District-level spatial data from reliable sources were utilized for Multi-Criteria Decision Analysis. Thematic rasters, representing key factors influencing land suitability, were created in a GIS. Utilizing MCDA techniques, a digital suitability map was generated in ArcGIS 10.3, delineating three distinct classes over an extensive area of 10.5 million hectares. Further, with an aim to focus on actual locations that can be readily planted with oil palm, the suitable locations identified were restricted to eight selected land use/land cover (LULC) classes. This strategic limitation aimed to facilitate the expansion of OP cultivation exclusively to areas deemed most suitable based on the identified criteria. The validation of this developed model involved comparing the suitability map generated with the performance of existing oil palm plantations across diverse locations. The reasonable similarity between the model's predictions and real-world plantation outcomes validated the effectiveness of this MCDA spatial model. This model not only helps identify suitable locations for rainfed oil palm cultivation but also serves as a valuable tool for strategic decision making in agricultural land use planning. [ABSTRACT FROM AUTHOR]

As polities of all kinds are under pressure to achieve socio-environmental sustainability and resilience, existing assessment tools diagnosing communities' vitality assets and vulnerabilities face challenges. These include grappling with incomplete data, incongruent models, and diverse indicator schemes from various scientific and professional domains. Moreover, these assessments draw upon multiple, sometimes unclear, and occasionally overlapping conceptualisations of 'sustainability' and 'resilience'. This complexity makes monitoring system dynamics difficult, particularly in smaller rural communities with limited resources. This essay addresses this science policy and epistemic dilemma by proposing Greimas's actantial model as a solution. The model, initially designed for understanding language and stories, is adapted to connect and integrate diverse data and indicator narratives across disciplines to inform policies at various levels of governance. This essay discusses recent debates on the conceptualisation of sustainability/resilience and its associated challenges, exploring how Greimas's model may allow more constructive dialogue about conflicting views on resilience and sustainability. The model is presented as a planning template to foster communication across disciplines, social actors, and polities. The conclusion emphasises the model's simplicity as a tool to overcome jargon, bridge communication gaps, and provide guidance for smaller rural communities facing resource constraints in assessing and implementing initiatives for sustainability and resilience. [ABSTRACT FROM AUTHOR]

Land use change monitoring is a common theme in achieving sustainable development, while research on ecological barrier transition zones is relatively scarce. This study quantitatively analyzes the characteristics and patterns of land use change in Western Jilin, located in the transitional zone between the northeast forest belt and the northern sand prevention belt, from 1990 to 2020. Land dynamic change index and transition matrix are used to quantify the rates and intensities, and conversions between different land use types over time, respectively. Geodetector is adopted to analyze the impact of 12 factors on 12 types of land use change, such as using the factor detector to quantify the influence of temperature on the conversion from cropland to unused land. The results indicate that from 1990 to 2020, there have been noticeable changes in the area of various land use types in western Jilin. However, the conversion types are relatively limited, mainly involving interchanges between cropland, grassland, unused land, and water bodies. The cropland has increased by 20% overall, but 16% of that increase occurred from 1990–2000. The woodland area has steadily increased at a growth rate of 5–8% from 2000–2020, aligning with sustainable development strategies. Water bodies and grasslands are undergoing continuous recovery, and a positive growth trend is predicted to emerge by 2030. The built-up land is steadily expanding. The influencing factors vary for different types of land-use change. In a short time, policy factors play a significant role in land use, such as the implementation of the "River-lake Connection Project", which has helped to reduce water-body fragmentation and enabled the stable recovery of water resources. However, in the long term, multiple topographic, climatic, and anthropogenic factors exhibit interactive effects in the land use change process in the area. Governments can take corresponding measures and management policies based on the influence of these factors to allocate and plan land use rationally. [ABSTRACT FROM AUTHOR]

Rural house is a fundamental component of rural settlements, and understanding its construction and development characteristics is crucial for rural land use and development planning. This paper focuses on the spatiotemporal characteristics and influencing factors of Rural Houses Construction Development (RHCD) from 1980 to 2019 with a case study of Qingyuan Town in China. Based on the literature review and filed research, a set of evaluation indicators for RHCD was established. The article calculates RHCD indicators from temporal and spatial dimensions, uses the location entropy method to demonstrate the spatial distribution of indicators, and classifies the RHCD type of 14 villages in Qingyuan Town using clustering algorithms. It also analyzes the influencing factors of spatiotemporal distribution. The results show that the RHCD in Qingyuan Town exhibits typical characteristics of mountainous areas and aligns with the development trends of rural society in China. Population growth, geographical location, and economic development are the primary driving factors for the quantity indicator (Qi), while economic growth, construction technology, industrial development, and policy adjustments are the key factors influencing the form indicator (Fi). In future policy-making, greater emphasis should be placed on optimizing development strategies, improving data and monitoring systems, and integrating administrative strength with actual development needs. [ABSTRACT FROM AUTHOR]

The formation and evolution of management gullies is a highly intense process of soil erosion often overlooked in policies and river basin strategies. Despite the worldwide spread of the phenomenon, our ability to assess and simulate gullying and its impacts remains limited; therefore, predicting the development and evolution of these river reaches represents a significant challenge, especially in areas where the loss of productive soil or the hazards linked to landslides or floods represent critical factors. Our study demonstrates how an exclusively morphometric approach, based on the construction of the hypsometric curve and applied to small hydrographic basins that are lithologically homogeneous and hierarchized according to the Strahler classification method, is able to predict the triggering height of the gullies; this height corresponds to the mean elevation of the basin and the inflection point of the hypsometric curve itself, confirming the hypothesis that this point coincides with the point at which a sudden change in surface runoff energy occurs, The study also shows that the portion of the basin necessary to trigger these intense erosive processes is always within a small range, regardless of the size and morphology (slope) of the basin itself. Such an approach, which is quick and relatively easy to apply, could help develop hydrogeological hazard mitigation practices in land planning projects. [ABSTRACT FROM AUTHOR]

Urban land use provides essential information about how land is utilized within cities, which is critical for land planning, urban renewal, and early warnings for natural disasters. Although existing studies have utilized multi-source perception data to acquire land use information quickly and at low cost, and some have integrated urban morphological indicators to aid in land use identification, there is still a lack of systematic discussion in the literature regarding the potential of three-dimensional urban morphology to enhance identification effectiveness. Therefore, this paper aims to explore how urban three-dimensional morphology can be used to improve the identification of urban land use types. This study presents an innovative approach called the UMH–LUC model to enhance the accuracy of urban land use identification. The model first conducts a preliminary classification using points of interest (POI) data. It then improves the results with a dynamic reclassification based on floor area ratio (FAR) measurements and a variance reclassification using area and perimeter metrics. These methodologies leverage key urban morphological features to distinguish land use types more precisely. The model was validated in the Pearl River Delta urban agglomeration using random sampling, comparative analysis and case studies. Results demonstrate that the UMH–LUC model achieved an identification accuracy of 81.7% and a Kappa coefficient of 77.6%, representing an 11.9% improvement over a non-morphology-based approach. Moreover, the overall disagreement for UMH–LUC is 0.183, a reduction of 0.099 compared to LUC without urban morphology and 0.19 compared to EULUC-China. The model performed particularly well in identifying residential land, mixed-use areas and marginal lands. This confirms urban morphology's value in supporting low-cost, efficient land use mapping with applications for sustainable planning and management. [ABSTRACT FROM AUTHOR]

The most extensive carbon reservoir system on Earth is found in the vegetation and soil in terrestrial ecosystems, which are essential to preserving the stability of ecosystems. Land use/cover change (LUCC) patterns in terrestrial ecosystems significantly impact carbon storage (CS). Therefore, it is imperative to investigate the relationship between LUCC and CS to coordinate regional ecological conservation and industrial development. In this study, the characteristics of spatial and temporal changes in land use and CS in the Yanqi Basin from 2000 to 2020 were revealed using the PLUS (patch-generating land use simulation) model and the CS module of the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) model. This study also predicted the spatial and temporal evolution of CS and the response mechanism of the Yanqi Basin from four scenarios—natural development scenario (NDS), ecological protection scenario (EPS), cropland protection scenario (CPS), and urban development scenario (UDS) for the years 2030, 2040, and 2050. This study shows the following: (1) Between 2000 and 2020, the Yanqi Basin witnessed an expansion in cropland and construction land, the order of the land use dynamic degree which is as follows: construction land > cropland > woodland > unused land > water > grassland. At the same time, the CS exhibited a trend of growth that was followed by a decline, a cumulative decrease of 3.61 Tg. (2) Between 2020 and 2050, woodland, grassland, and unused land decreased under the NDS and UDS. Meanwhile, grassland and woodland showed an expanding trend, and there was a decrease in cropland and construction land under the EPS; the CPS projected an increase in cropland to 3258.06 km2 by 2050. (3) CS under the UDS is always the lowest, and CS under the EPS is the highest; moreover, by 2050, CS under the EPS is projected to increase by 1.18 Tg compared with that under the UDS. The spatial distribution of CS shows a high value in the western part of the region and a low value in the eastern part of the region, which is more in line with the historical spatial distribution. (4) The development of land by human activities is one of the major factors leading to the change of CS. The direct cause of the decrease in CS is the transformation of large areas of cropland and woodland into construction land. Therefore, woodlands must be protected to improve CS and prevent ecological degradation. At the same time, future land use planning in the Yanqi Basin needs to limit the conversion rate of various types of land, control the construction land, optimize the urban pattern, improve the regional CS level, adhere to the concept of striving to achieve carbon neutrality, and realize the sustainable development of the region to provide scientific suggestions for carrying out macro-decision making regarding land use planning in arid areas. [ABSTRACT FROM AUTHOR]

Coastal lagoons are highly productive transitional water bodies threatened by human factors and vulnerable to global climate change effects. Monitoring biophysical parameters in these ecosystems is crucial for their preservation. In this work, we used Sentinel-2 and Landsat imagery combined with in situ data to (1) develop preliminary algorithms for retrieving the Chl-a concentration and water surface temperature of six lagoons located in the Ebro Delta (NE Mediterranean Sea, Spain), and to (2) compute maps and trend lines for analysing their spatiotemporal evolution from 2015 to 2022. Our findings showed that the algorithms' accuracy ranged from 72% to 78% and had limited potential under high Chl-a concentration regimes. Even so, they revealed the lagoons' trophic status, usual fluctuations, and deviations of both parameters attributed to seasonal (i.e., light and temperature) and short-term physical (i.e., winds) forcing, as well as valuable spatial patterns potentially useful for conservation efforts and land use planning. Future work will focus on the acquisition of a larger in situ data sample under a range of environmental conditions to improve the algorithms' robustness, which in turn will allow the investigation of natural and human factors controlling the dynamics of the two investigated parameters. [ABSTRACT FROM AUTHOR]

This study presents a conceptual framework proposal for integrating urban freight initiatives (UFIs), or city logistics initiatives, into urban planning and urban management (UPUM) land use and infrastructure systems. As a novel approach, this framework integrates three components: Firstly, a conceptual basis on three economic geography theory principles—location, agglomeration, and urbanisation. Secondly, spatial analysis and subsequent clustering integrate companies' spatial positions, their proximity to other companies, their freight intensity, and the characteristics of the zonal road infrastructure; these clusters are defined as freight traffic zones (FTZs). Thirdly, a functional yet strategic UFI clustering or grouping is proposed to work in an optimised and integrated manner with the FTZs' opportunities for efficiency and reduced externalities. It is expected that the integrated result of these three components can serve to optimise freight initiatives and road infrastructure from a city governance perspective, reduce freight externalities, and function as a stakeholder cooperation tool from government-led, policy-driven perspectives. This research also identifies and characterises various variables influencing the emergence and existence (planned or organic) of FTZs and shows how these could be incorporated into high-level UPUM processes. Although it is deemed that the principles and methodological approach followed here could be common to urban areas, an example for the Metropolitan Area of the Aburra Valley (MAAV), in Colombia, is presented as an initial case study. Conclusively, this paper introduces a pioneering methodology for integrating UFIs into city or metropolitan governance, offering guidance for policymakers to promote sustainable freight systems. [ABSTRACT FROM AUTHOR]

Revealing the relationship between land use changes and soil erosion provides a reference for formulating future land use strategies. This study simulated historical and future soil erosion changes based on the RULSE and GeoSOS-FLUS models and used a random forest model to explain the relative importance of natural and anthropogenic factors on soil erosion. The main conclusions are as follows: (1) From 1990 to 2020, significant changes in land use occurred in Kunming, with a continuous reduction in woodland, grassland, and cropland, being converted into construction land, which grew by 195.18% compared with 1990. (2) During this period, the soil erosion modulus decreased from 133.85 t/(km²·a) in 1990 to 130.32 t/(km²·a) in 2020, with a reduction in soil loss by 74,485.46 t/a, mainly due to the conversion of cropland to construction and ecological lands (woodland, grassland). (3) The expansion of construction land will continue, and it is expected that by 2050, the soil erosion modulus will decrease by 3.77 t/(km²·a), 4.27 t/(km²·a), and 3.27 t/(km²·a) under natural development, rapid development, and ecological protection scenarios, respectively. However, under the cropland protection scenario, the soil erosion modulus increased by 0.26 t/(km²·a) compared with 2020. (4) The spatial pattern of soil erosion is influenced by both natural and anthropogenic factors, and as human activities intensify in the future, the influence of anthropogenic factors will further increase. Traditionally, the expansion of construction land is thought to increase soil loss. Our study may offer a new perspective and provide a reference for future land use planning and soil loss management in Kunming. [ABSTRACT FROM AUTHOR]

This research work arises from the need to design specific techniques for the characterisation of cultural sites. Assuming the increasing complexity of the protection typologies, the expansion of working scales gives thanks to technology and the pursuit of social sustainability objectives. Thus, its main objective is to search for innovative tools that other disciplines can contribute to the work of architects specialising in heritage studies. To this end, the research explores the main methodologies, maps, guides, and registers of landscape and historic landscape characterisation developed in Europe, particularly in Spain, over the last 40 years. Considering this intense and profound evolution of landscape analysis, useful strategies for the assessment of cultural sites from their conception in the 21st century arise. Nevertheless, landscape characterisation methods have been mainly developed and applied by geographers and are absent in many urban and territorial heritage studies. In response, this article proposes a new methodological approach focusing on contextual values to be used in the assessment of architectural heritage at the territorial scale. [ABSTRACT FROM AUTHOR]

The landslide hazard assessment plays a crucial role in landslide risk mitigation and land use planning. The result of landslide hazard assessment corrected by surface deformation, obtained through time-series InSAR, has usually proven to have good application capabilities. However, the issue lies in the uncertainty of InSAR results, where some deformations cannot be calculated, and some are not true deformations. This uncertainty of InSAR results will lead to errors in landslide hazard assessment. Here, we attempt to evaluate landslide hazards by considering combined rainfall and surface deformation. The main objective of this research was to mitigate the impact of bias and explore the accurate landslide hazard assessment method. A total of 201 landslides and 11 geo-environment factors were utilized for landslide susceptibility assessment by support vector machine (SVM) model in Wanzhou District, Three Gorges Reservoir Area (TGRA). The preliminary hazard is obtained by analyzing the statistical data of landslides and rainfall. Based on the SAR image data of Sentinel-1A satellites from September 2019 to October 2021, the SBAS-InSAR method was used to analyze surface deformation. The correlation between surface deformation and rainfall was analyzed, and the deformation factor variables were applied to landslide hazard assessment. The research results demonstrate that the error caused by the uncertainty of InSAR results can be effectively avoided by analyzing the relationship between rainfall and surface deformation. Our results can effectively adjust and correct the hazard results and eliminate the errors in the general hazard assessment. Our proposed method can be used to assess the landslide hazard in more detail and provide a reference for fine risk management and control. [ABSTRACT FROM AUTHOR]