Land Use Change Dynamics Research Articles

Spatio-temporal analysis of scientific research on models to estimate water balance in hydrographic basinsV

Objective: To identify in the world the main models or tools used to evaluate changes in water regulation,through a bibliometric review in the especialized in scientific information, Scopus database, in order to knowthe main variables evaluated that affect the hydrological regime of the basins.Design/methodology/approach: With the help of bibliometric techniques, scientific articles available untilDecember 2022 in the Scopus database were collected using the SUBJAREA (envi) TITLE-ABS-KEY (“waterbalance” AND “land use”) AND (LIMIT-TO (OA, “all”)) AND (LIMIT-TO (DOCTYPE, “ar”)).Results: 407 scientific articles were collected from 1965 to 2022, this scientific production shows an exponentialgrowing trend that was concentrated above all in countries with agricultural traditions such as the UnitedStates (89 publications), China (33), Germany (28), the United Kingdom (25) and Australia (21).Limitations on study/implications: Most of the research was developed on topics associated with land usechange (82 texts), climate change (48), hydrological processes (44), subsoil water (34) and evapotranspirationcalculation (33). The most recurrent models for calculating the water balance were the Direct Water Balance(230 texts) and the Soil and Water Assessment Tool (83).Findings/conclusions: No research development was found in Latin American and African countries, sothese results can help redirect efforts in the research centers of these countries, with the aim of generating newknowledge that helps make decisions about how to improve the efficient use of water in the face of climatechange scenarios and dynamics of land use change

Drivers of mangrove area change and suppression in Brazil from 2000 to 2020.

Mangrove area loss is increasing globally, and drivers of loss differ depending not only on natural conditions but also on national and regional policies. Some countries with the most mangrove area, for instance, Brazil, lack broad systematic quantification of specific drivers of mangrove land-use and land-cover (LULC) change dynamics. We investigated the direct conversion (i.e., replacement) of mangrove forests due to changes in 21 types of LULC across Brazil from 2000 to 2020 based on annual LULC maps developed by the MapBiomas project. We quantified the area changes at national, regional, and state scales. We also determined and quantified mangrove forest conversion for each of the 21 LULC types with a pixel comparison analysis and identified temporal trends with a time-series analysis. The total conversion of mangrove area (3429km2) was offset by a gain that was twice as large (6776km2). Forest formations and water bodies, which may be interpreted as natural or indirect anthropogenic changes, were associated with most of the areas where mangrove cover was lost. Land-use modifications, mainly creation of pastures, accounted for 4% of direct mangrove conversions. We found that changes in LULC categories and patterns of gain and loss of mangrove areas differed among Brazilian states and regions. Based on other research, they also differ between Brazil and other countries. Thus, integrated mangrove forest conservation and management efforts that transcend political boundaries are essential to effectively address negative impacts on mangrove forests. We provide an interactive map to allow qualitative assessments of mangrove conversion drivers by different stakeholders, such as managers, policymakers, and nongovernmental organizations.

An assessment of the seasonally dependent biophysical mechanism and dynamic land use change: A research effort from emerging urban agglomeration of West Bengal

The behavior of the biophysical components needs to be closely observed while taking seasonal perspectives into account. This study focuses on seasonal analysis of biophysical components and dynamics of land use changes. This study examines the spatiotemporal seasonal variation among land surface temperature (LST), normalized difference vegetation index (NDVI), and normalized difference water index (NDWI), with a focus on the two main sub-tropical climatic seasons summer and winter. We use correlation and regression analysis to assess the season-wise relationship between LST and biophysical indices with the help of grouped marginal plots. The comparison analyses of the biophysical components and land use change for a longer period from 1991 to 2021 with their matrix was undertaken in five urban agglomerations (UA) like Asansol, Siliguri, Kolkata, English Bazar and Kharagpur. The maximum likelihood classification technique was used to categorize multi-temporal Landsat images for each of the five growing UA in West Bengal. The most intriguing finding is that in all UAs, from 1991 to 2021, built-up area increased to become the predominant land. Thus, the vegetation and agricultural land are in danger in every location of West Bengal, whether it is plain or hilly, because of the land's gradual conversion to concrete or built-up areas over time. Additionally, the result shows that in summer and winter seasons, LST was observed growth due to the rapid urban built-up area expansion. It is also found that LST and NDVI have a close negative relationship, but LST and NDWI do not have any perfect relationship. Therefore, to lessen the warming effect of urban microclimates, policymakers should be concerned about future urban expansion that is both horizontal and vertical. An appropriate strategy for environmentally friendly construction, green buildings, and cool roof technologies should be developed.

Spatiotemporal dynamics of LULC change and implications for sustainable urban growth in Saudi Arabia

This study investigates the spatiotemporal dynamics of land use and land cover (LULC) change in Saudi cities between 2013 and 2023. Using Landsat satellite imagery and a Maximum Likelihood Classifier, LULC changes are analyzed in nine cities to understand the impact of Saudi Arabia’s rapid urbanization following the oil crisis. The objectives are: (1) to evaluate the LULC changes in nine cities between 2013 and 2023; (2) to explore the spatiotemporal patterns of LULC changes in this period; and (3) to interpret the urban expansion that occurs in Saudi Arabia in the light of the kingdom sustainable development plan. The results identifiy four primary LULC change models: Urbanization, Vegetation Recovery, Land Degradation, and Ecological Transition Models. The Urbanization and Land Degradation Models determine Saudi Arabia’s urban growth trend, posing significant challenges to sustainable development. Most cities experienced substantial increases in impermeable surfaces and developed lands, while concurrently losing high terrain and barren areas. However, the small cities showed lower urbanization and land degradation rates than major cities, showing an opportunity to sustainably grow by adopting sustainable planning approaches. The study’s findings show that more targeted and comprehensive policies are needed to address the challenges of urbanization and land degradation, mitigate environmental impacts, and ensure long-term resilience. It underscores the importance of considering Ecological Urbanism in urban development plans.

Evaluating the Spatio-Temporal Distribution of Nitrogen Dioxide, Land Surface Temperature and NDVI in Nairobi City County

Abstract. Cities are becoming larger and it is estimated that by the year 2050, more than 6 billion people will be living in cities. As cities expand and grow, the quality of life and conditions will also transform. An integral part of environmental studies has been statistical analysis in modelling the spatial dynamics of land use changes. The research involved the use of satellite imagery to determine yearly averaged values of LST and NDVI from Landsat 8 OLI/TIR and monthly mean values of Nitrogen Dioxide (NO2) from Sentinel 5-Precursor (Sentinel-5P) across Nairobi City County. The datasets covered the period 2019, 2020, 2021, 2022 and 2023 and were analysed in Google Earth Engine. Results indicated that the yearly mean values in NO2 and LST in 2020 reduced by 2% and 12% respectively from 2019, while the mean NDVI value significantly increased by 28% in 2020 from 2019. NO2 has a negative correlation with LST in all years and a positive correlation with NDVI. Pearson correlation with population densities in constituencies in Nairobi in 2019 and 2023 indicate a negative correlation with NDVI and a positive correlation with NO2 and LST. Constituencies that have higher population densities tend to have lower vegetation densities and higher NO2 concentrations and temperature. Vegetation therefore plays a crucial role in air quality and that climatic factors such as precipitation and temperature influence the concentration of pollutants.

Spatiotemporal dynamics and driving factors of ecosystem services value in Lanzhou City, China

Aligned with the imperatives of national ecological civilization construction, the systematic investigation into the intricate interplay between shifts in land utilization and the assessment of ecosystem services plays a pivotal and indispensable role in advancing ecological civilization. This endeavor holds significant implications. It aids in optimizing the ecological landscape at the regional level and fosters harmonious coexistence between humanity and the natural world. The study utilizes land-use remote sensing interpretation data from three time periods (2000, 2010, and 2020) and employs various methodologies, including equivalent factor coefficient correction, sensitivity analysis, and spatial autocorrelation. The objective is to uncover the spatiotemporal dynamics of land-use changes and Ecosystem Service Value (ESV) in Lanzhou City. Furthermore, geographic detectors are applied to explore the driving factors influencing ESV spatial heterogeneity and their interactions. The research findings indicate the following: (1) From 2000 to 2020, grassland and cropland were the predominant land-use types in Lanzhou City, with cropland and urban land experiencing the most active changes. (2) ESV in Lanzhou City increased from 179.37 billion RMB in 2000 to 193.86 billion RMB in 2020, reflecting an ESV total growth rate of 8.07% and a gradual improvement in the ecological environment. Spatially, ESV exhibits a “west high, east low” distribution pattern, with the center shifting towards the northwest and southeast, gradually reducing spatial imbalance. (3) Analysis of ESV spatial autocorrelation reveals that high-high clusters are predominantly found within the Tulu Gou National Forest Park and the Xinglong Mountain National Natural Reserve, while low-low clusters are primarily concentrated in the central urban area of Lanzhou City. Over the period from 2000 to 2020, the spatial clustering effect of ESV within the study area has progressively intensified. 4)NDVI, precipitation, and GDP emerge as pivotal factors influencing spatial differentiation within Lanzhou City, with natural and societal elements exerting interactive effects on ESV spatial disparities. The research results integrate environmental considerations into the decision-making process, offering valuable insights for formulating targeted ecological protection policies in Lanzhou City. This study embodies concrete measures taken by Lanzhou City in practicing China’s concept of “green water and green mountains are golden silver mountains,” providing a theoretical basis for the harmonious and sustainable development of the ecological economy.

The impact of land use change on food security under the background of rapid urbanization - a case study of Xiamen city

Abstract China has undergone a long period of rapid urbanization from 2000 to 2020, resulted in huge conversion of arable land into built-up areas. This situation has raised concerns regarding food security, including issues like reduced food supply and challenges to achieving food self-sufficiency, particularly in certain regions and during special period. To address these issues, this study focuses on Xiamen, a rapidly urbanizing coastal city in China, and examined both the food supply and demand. On hand of the supply, this study mainly analyzed the attributes of the food availability, indicators like the food production (FP) of the ecosystem service value (ESV), per capita grain production, imports and exports along with food price were calculated. The findings revealed a significant expansion of built-up areas in Xiamen, mostly at the expense of arable land. The declining arable land coupled with population growth due to rapid urbanization contributed to a decrease in per capita grain production, drop to 6 kg in 2018, which is merely 1% of China’s average. A comparison of per capita grain production across various regions, as well as changes in China’s grain import and export, highlighted a notable discrepancy between urbanization rates and food security in Xiamen. It has become challenging for Xiamen to rely on outside for sustained food import. Therefore, it is imperative for Xiamen to implement a range of measures and policy interventions to ensure a certain level of food self-sufficiency and protect basic arable land.

Assessing the impact of land use and land cover change on the Densu Delta wetland using Markov chain modeling and artificial neural networks

This study investigates the dynamics of land use and land cover (LULC) changes in the Densu Delta wetlands, a critical ecosystem in Ghana. Here, satellite images spanning from 1998 to 2023 were used to analyse the spatio-temporal patterns of LULC changes and their implications for water bodies, wetlands, vegetations, bare lands and urban areas in the Densu Delta wetland. Employing advanced techniques such as Markov chain modelling and artificial neural networks (ANNs), the research assesses and predicts LULC alterations. Significantly, the largest loss of LULC is observed in the Densu Delta wetland, where wetlands transition to waterbody cover type (14.02 km²). Model validation for 2023 attests to the accuracy of the model, boasting a correctness percentage of 70% and a kappa value of 0.74. In-depth analyses explore regional variations in the Densu Delta wetlands, revealing distinct patterns in the rates of LULC change before and after 2013. Notably, urbanization emerges as a prominent factor post-2013, with urban areas experiencing remarkable rates of change in the wetland. Transition matrices underscore the intricate interplay of different land cover classes over the years. Simulated LULC predictions for 2033 and 2043 highlight the urban land cover type as having the highest positive change, recording approximately 0.39% for the Densu Delta wetland. The wetland land cover in the Densu Delta wetland exhibit negative changes of about −0.52%. The synthesis of LULC data enhances our understanding of the complex interactions shaping these critical ecosystems. This research offers valuable insights for sustainable environmental conservation, emphasizing the pivotal role of informed urban planning policies. It also unveils potential challenges posed by climate change, advocating for a holistic approach to preserve these vital wetland ecosystems.

Spatiotemporal Variation and Prediction of Carbon Storage in Terrestrial Ecosystems at Multiple Development Stages in Beijing City Based on the Plus and Integrated Valuation of Ecosystem Services and Tradeoffs Models

Terrestrial ecosystems play a critical role in the global carbon cycle, and their carbon sequestration capacity is vital for mitigating the impacts of climate change. Changes in land use and land cover (LULC) dynamics significantly alter this capacity. This study scrutinizes the LULC evolution within the Beijing metropolitan region from 1992 to 2022, evaluating its implications for ecosystem carbon storage. It also employs the Patch-Generating Land Use Simulation (PLUS) model to simulate LULC patterns under four scenarios for 2035: an Uncontrolled Scenario (UCS), a Natural Evolution Scenario (NES), a Strict Control Scenario (SCS), and a Reforestation and Wetland Expansion Scenario (RWES). The InVEST model is concurrently used to assess and forecast ecosystem carbon storage under each scenario. Key insights from the study are as follows: (1) from 1992 to 2022, Beijing’s LULC exhibited a phased developmental trajectory, marked by an expansion of urban and forested areas at the expense of agricultural land; (2) concurrently, the region’s ecosystem carbon storage displayed a fluctuating trend, peaking initially before declining, with higher storage in the northwest and lower in the central urban zones; (3) by 2035, ecosystem carbon storage is projected to decrease by 1.41 Megatons under the UCS, decrease by 0.097 Megatons under the NES, increase by 1.70 Megatons under the SCS, and increase by 11.97 Megatons under the RWES; and (4) the study underscores the efficacy of policies curtailing construction land expansion in Beijing, advocating for sustained urban growth constraints and intensified afforestation initiatives. This research reveals significant changes in urban land use types and the mechanisms propelling these shifts, offering a scientific basis for comprehending LULC transformations in Beijing and their ramifications for ecosystem carbon storage. It further provides policymakers with substantial insights for the development of strategic environmental and urban planning initiatives.

Analyzing the extent and use of impervious land in rural landscapes

The amount of impervious surface is increasing rapidly worldwide. Although urban expansion has been studied extensively, the alteration of impervious land cover in rural regions remains under-examined. In particular, insights into the utilization of these sealed surfaces are crucially needed to unravel the underlying dynamics of land use changes beyond urban areas. This study focuses on rural regions from a Swiss case study and presents an analysis of the use of sealed surfaces in such regions, rather than solely quantifying the extent of sealed surfaces. Utilizing a synergistic approach that merges detailed cadastral plans with very-high-resolution remote sensing imagery and sophisticated deep learning algorithms, we characterized the uses of sealed surfaces, including buildings and their surroundings. Our findings reveal that 2.1 % of the study area’s rural regions comprises sealed surfaces - an area comparable to the sealed surfaces in the urban regions. Within these rural regions, transport infrastructure represents 68 % of this impervious surface. Buildings account for 12 %, and their surroundings, constituting 13 %, are utilized primarily for agricultural purposes, including farming and livestock activities. The deep learning approach achieved a classification accuracy of 72 % for a shallow model and 79 % for a deeper model, indicating that mapping building types is possible with reasonable accuracy. The outcomes of this study underscore the critical need to factor in the presence and utilization of impervious land cover within rural regions for the sustainable management of land resources.

Analysis Of Land Use And Land Cover Changes In Port Harcourt Metropolis Using Geospatial Techniques

The study examined Land Use and Land Cover Changes in Port Harcourt Metropolis Using Geospatial Techniques from 1990 to 2020. The study made use of geospatial and longitudinal data sourced from the United States Geological Survey (USGS), employing Google Earth Engine to analyse Landsat and Google Earth Imagery of the area. Utilizing satellite imagery with a spatial resolution of 30 meters by 30 meters, supplemented with high-resolution Google Earth imagery, the study offers an extensive concept of the dynamic changes in land use in the four epochs of 1990, 2000, 2010 and 2020. The methodology entails processing and analysing satellite images to identify and classify different land use and land cover types as well as tracking their changes over time. This technique allows for precise mapping and assessment of the trend, extent, rate, and spatial patterns of land use changes. The study employed supervised classification, change detection, and temporal analysis, to ensure robust and accurate results. ANOVA statistics was deployed to test the stated hypothesis for the study. The findings revealed a drastic reduction in land use coverage for the various land use classes in the epochs studied. Open spaces showed a reduction from 62,262.2ha (58.92%) in 1990 to 41,832ha (39.32%) in 2020; farmland reduced from 21,172.5ha (20.04%) in 1990 to 1,474.65ha (1.4%) in 2020; built-up area increased from 9,006.03ha (8.52%) in 1990 to 41,502.8 (39.28%) in 2022; water bodies increased from 1,529.73ha (1.45%) in 1990 to 3,424.32ha (3.24%) in 2020. These changes have profound implications for environmental sustainability, urban planning, and resource management in the area. The study concludes that there has been substantial land use and land cover changes in Port Harcourt metropolis, driven primarily by urbanization. Thus, it is recommended that the government implement stricter urban planning and sustainable land management practices to mitigate the impact of rapid land use and land cover changes in Port Harcourt

Evolution of Land Use and Land Cover Change in Panjim, Goa: A Comparative Analysis from 1990 to 2024

This research paper investigates the dynamics of land use and land cover (LU/LC) change in Panjim, Goa, India, from 1990 to 2024. Using satellite Data and GIS techniques, the study analyzes the spatial and temporal transformations of land cover categories, including forest, agriculture, urban areas, and water bodies. The primary objective is to understand the drivers of LU/LC change and assess their implications for sustainable urban development and environmental conservation. The findings reveal significant urban expansion, encroachment on agricultural lands, and reduction in forest cover. The study highlights the need for effective land use planning and management strategies to mitigate negative environmental impacts and ensure the city's long-term sustainability. Keywords: Land Use, Land Cover, Supervised Classification, Change Detection, Accuracy Assessment

Dynamics of land use and land cover change in the distal Okavango Delta, Botswana

ABSTRACT Population increase and socio-economic progress exert pressure on land use and land cover (LULC) in any geophysical environment. If not minimized, the pressure has the potential to unfold as unplanned and uncontrolled alterations in LULC. Remote sensing (RS) and geographical information systems (GIS) prove to be powerful tools for obtaining accurate and real-time information on the spatial distribution of land use and land cover change (LULCC) both spatially and temporally over a wide area. This research paper uses remotely sensed spatial data and a literature review to examine the extent of LULCC over three decades in the distal Okavango Delta with specific attention on Maun, Botswana. The study assesses changes in population growth, built-up areas, road/pavements, water fluctuations, hydrophytes and shrubs/trees dynamics from April 1990 to April 2020. Findings reveal that while the population of Maun increased from 26,768 to 85,293 between 1990–2020 built-up areas increased from 0.68 km2 to 9.61 km2 and shrubs/trees decreased from 13.53 km2 to 7.06 km2, respectively, within the same period. Grasslands increased from 8.57 km2 in 1990 to 13.44 km2 by 2020. The paper thus recommends the establishment of a two-kilometre-wide green belt around the settlement to stem any progressive encroachment into agricultural reserved land.

Assessing the dynamics of land use and land cover change in semi‐arid savannah: A focus on woody plant encroachment utilising historical satellite data

AbstractThe encroachment of woody plants into grassland and the conversion of grasslands to woodlands is a worldwide phenomenon and has been regarded as a major global problem for decades. The rate of woody plant encroachment (WPE) varies across biomes and can be influenced by land use activities and climate conditions. As a result, the current study assessed the spatial distribution of woody plants and land use and land cover (LULC) change within the Letaba River catchment in the Limpopo province of South Africa's subtropical region. Landsat Thematic Mapper (TM) and Operational Land Imager (OLI) satellite data sets were used to map and quantify WPE and other LULC changes in the Letaba River catchment over a 30‐year period (1989–2019). Random forest classifier was used to determine of the rate of change of WPE and LULC within the study area. The results indicated that the Letaba River catchment has undergone a significant change with an increase in woody plant species. The woody plant cover had increased from 36,014 ha in the year 1989 to approximately 561,493 ha by 2019. Meanwhile, grassland has declined by 486,322 ha (33.7%) from 1989 to 2019. The overall classification accuracy (OA) ranged between 91.7% and 95.5%. The study findings will provide critical insights and baseline information about the state of WPE in semi‐arid environments, as well as provide catchment managers with the information they need to take the necessary actions to manage the rapid increase in woody plants. However, fire and herbivory are important factors that influences the WPE, and this might have also played an important role in the findings. The study suggests that WPE is an ongoing process and management strategies are required to mitigate and maintain the intensity of woody plants.

Changes in land use dynamics following the Fundão dam collapse in the Doce River Basin, Brazil

Although regarded as “unexpected,” the collapse of the Fundão tailings dam in 2015 resulted from the synergistic interplay between the capitalist logic of environmental resource exploitation and environmental degradation in the Doce River Basin (DRB). Our objective was to assess whether this disaster altered land-use dynamics in the DRB. To achieve this, we characterized land-use transitions by comparing changes over three years before (2012–2015) and after (2016–2019) the disaster. We differentiated municipalities adjoining the affected rivers from the remaining municipalities. We evaluated anthropogenic and natural driving forces as explanatory variables: farmland to natural vegetation (land abandonment) or natural vegetation to farmland (farmland expansion). We detected two main driving forces of land abandonment, precipitation and temperature, both before and after the dam collapse. Still, there was a shift between periods: before the dam collapse, the drivers of land abandonment differed between municipalities adjoining and those not adjoining the affected rivers. After the disaster, all municipalities shared the same drivers for land abandonment. For farmland expansion, we detected five drivers for the period before (temperature, precipitation, natural vegetation area, roads, and municipality area) and five drivers after (urban area, slope, natural vegetation area, roads, and municipality area) the dam collapse. Thus, we detected a change in the drivers but no distinction between municipalities adjoining and not adjoining the affected rivers. Our results evidenced a direct effect of the disaster on land abandonment but not farmland expansion, where the observed temporal changes may be related to temporal changes independent of the disaster. Our work shows that the collapse of the Fundão mining dam changed the drivers of “land abandonment,” which may be due to anthropic avoidance of using Doce River’s water for farmland or to a change in socio-economic drivers, such as those related to the monthly financial compensation of affected farmers.

Dynamics of land use and land cover changes in Amibara and Awash-fentale districts, Ethiopia

The analysis of land-use and land-cover (LULC) changes is crucial for rural development planning, food security monitoring, and natural resource conservation. This study focuses on detecting LULC changes in Amibara and Awash-Fentale districts from 1985 to 2021. We utilized five sets of Landsat data (Landsat 5 TM for 1985, 1995, 2002, and Landsat 8 OLI for 2015 & 2020) and applied supervised maximum likelihood classification. Accuracy assessments revealed overall accuracies ranging from 88.9% to 95.3% for Amibara and 89.5%–93.2% for Awash-Fentale. Both districts exhibited six main LULC classes: agriculture, bareland, built-up, mixed forest, shrubland, and water bodies. In Amibara LULC changes from 1985 to 2021 revealed significant shifts, maintaining its primary bareland characteristic, concentrated agriculture, and expanding Prosopis-dominated shrubland due to livestock-mediated seed dispersal. Conversely, in Awash-Fentale bareland dominance decreased from 92.28% to 67.02%, while agriculture, built-up areas, and shrubland expanded. Water bodies emerged between 2015 and 2021 which is associated with the construction of Kesem Kebena dam for sugar cane farm production. The net gains were observed in shrubland (12.9%), agriculture (5.8%), mixed forest (4.1%), water bodies (1.5%), and built-up areas (0.9%), with bareland experiencing a loss of 25.3%. In conclusion, Amibara and Awash-Fentale underwent both comparable and distinct LULC shifts, featuring prevalent bareland and central agriculture, alongside Prosopis-driven shrubland expansion due to livestock dispersal. While mixed forest exhibited fluctuations, built-up areas and water bodies remained limited. Notably, Awash-Fentale showed higher LULC variability. Understanding these land cover changes helps assess vulnerability to climate impacts like droughts and floods, enhancing climate resilience. Insights from this study can inform sustainable land-use planning, conservation strategies, and policy interventions in the Afar region and similar areas. These observations highlight the need for integrated land management approaches that balance socioeconomic development with environmental sustainability.

Spatiotemporal Dynamics of Land Use and Land Cover Change in the Ebo Forest Reserve, Littoral Region of Cameroon

Spatiotemporal Dynamics of Land Use and Land Cover Change in the Ebo Forest Reserve, Littoral Region of Cameroon

Sustainable Urban Planning Challenges in the Peri-Urban Landscape: Evaluating LULC Dynamics and the Policy Effectiveness of the Chattogram Metropolitan Region, Bangladesh

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.

Landslide Hazard Prediction Based on Small Baseline Subset–Interferometric Synthetic-Aperture Radar Technology Combined with Land-Use Dynamic Change and Hydrological Conditions (Sichuan, China)

Le’an Town, located in the southwest of Qingchuan County, Guangyuan City, Sichuan Province, boasts a unique geographical position. The town’s terrain is complex, and its geological environment is fragile. Multiple phases of tectonic movements have resulted in numerous cracks and faults, making the area prone to landslides, debris flows, and other disasters. Additionally, heavy rainfall and fluctuating groundwater levels further exacerbate the instability of the mountains. Human activities, such as overdevelopment and deforestation, have significantly increased the risk of geological disasters. Currently, the methods for landslide prediction in Le’an Town are limited; traditional techniques cannot provide precise forecasts, and the study area is largely covered by tall vegetation. Therefore, this paper proposes a method that combines SBAS-InSAR technology with dynamic changes in land use and hydrological conditions. SBAS-InSAR technology is used to obtain surface deformation information, while land-use changes and hydrological condition data are incorporated to analyze the dynamic characteristics and potential influencing factors of landslide areas. The innovation of this method lies in its high-precision surface deformation monitoring capability and the integration of multi-source data, which can more comprehensively reveal the geological environmental characteristics of the study area, thereby achieving accurate predictions of landslide development. The study results indicate that the annual subsidence rate in most deformation areas of Le’an Town ranges from −10 to 0 mm, indicating slow subsidence. In some areas, the subsidence rate exceeds −50 mm per year, showing significant slope aspect differences, reflecting the combined effects of geological structures, climatic conditions, and human activities. It is evident that land-use changes and hydrological conditions have a significant impact on the occurrence and development of landslides. Therefore, by utilizing SBAS-InSAR technology and cross-verifying it with other techniques, the consistency of identified landslide deformation areas can be enhanced, thereby improving results. This method provides a scientific basis for the monitoring and early warning of landslide disasters and has important practical application value.

Spatio-temporal analysis land use land cover changes in South Kashmir region of North-western Himalayas using Landsat data

This paper presents a comprehensive analysis of the spatial patterns and temporal dynamics of land use and land cover changes in South Kashmir from 2000 to 2022 leveraging remote sensing technologies revealing significant transformations in various land cover classes. The study used maximum likelihood classification, a supervised classification method, to analyze Landsat satellite imagery and identify ten major land use categories. The findings demonstrate notable increases in, barren land by 18.78 km2 (0.35%), built-up areas by 72.28 km2 (1.33%), forests by 274.76 km2 (5.05%), grasslands by 68.06 km2 (1.25%), scrubland by 307.82 km2 (5.66%). horticulture experienced a significant rise of 419.17 km2 (7.70%), Conversely, several land use classes reported decline, agriculture by 757.21 km2 (13.91%), exposed rockmass by 258.58 km2 (4.75%), glaciers and snow by 136.83 km2 (2.51%), and water bodies contracted by 8.23 km2 (0.15%). The primary drivers of land use change in the region are identified as climate change, population growth, and economic factors. Climate change has altered precipitation patterns affecting agricultural productivity and leading to the retreat of glaciers. Population growth and economic reasons, including the rise of horticulture and changes in land use policies, have also played a significant role in shaping the landscape dynamics of South Kashmir. These changes underscore the dynamic nature of land use in South Kashmir, with significant implications for regional planning and environmental management. The study underscores the cost-effectiveness and efficacy of geospatial technologies in conducting spatiotemporal analyses and formulating evidence-based policies for the sustainable management of natural resources.