Land Use Cover Change Research Articles

Shoreline and land use–land cover changes along the 2004-tsunami-affected South Andaman coast: understanding changing hazard susceptibility

Abstract. The 2004 tsunami affected the South Andaman coast, causing it to experience dynamic changes in the coastal geomorphology and making the region vulnerable. We focus on pre-and post-tsunami shoreline and land use–land cover changes from 2004, 2005, and 2022 to analyze the dynamic change in hazard. We used General Bathymetric Chart of the Ocean (GEBCO) data to calculate run-up [m], arrival times [min], and inundation [m] at a few locations using three tsunamigenic earthquake source parameters, namely the 2004 Sumatra, 1941 North Andaman, and 1881 Car Nicobar earthquakes. The Digital Shoreline Analysis System is used for the shoreline change estimates. Landsat data are used to calculate shoreline and land use–land cover (LULC) change in five classes, namely built-up areas, forests, inundation areas, croplands, and water bodies during the above period. We examine the correlation between the LULC changes and the dynamic change in shoreline due to population flux, infrastructural growth, and gross state domestic product growth. The Indian industry estimates the Andaman and Nicobar Islands losses exceeded INR 10 billion during 2004, which would today see a 5-fold increase in economic loss due to a doubling of built-up area, a 3-fold increase in tourist inflow, and population density growth. The unsustainable decline in the forest cover, mangroves, and cropland would affect sustainability during a disaster despite coastal safety measures.

Evolution and Analysis of Water Yield under the Change of Land Use and Climate Change Based on the PLUS-InVEST Model: A Case Study of the Yellow River Basin in Henan Province

Understanding the interrelationships between land use, climate change, and regional water yield is critical for effective water resource management and ecosystem protection. However, comprehensive insights into how water yield evolves under different land use scenarios and climate change remain elusive. This study employs the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) models, Patch-generating Land Use Simulation (PLUS) model, and Geodetector within a unified framework to evaluate the dynamics of land use, water yield, and their relationships with various factors (meteorological, social, economic, etc.). To forecast the land use/cover change (LUCC) pattern of the Yellow River Basin by 2030, three scenarios were considered: economic development priority (Scenario 1), ecological development priority (Scenario 2), and cropland development priority (Scenario 3). Climate change scenarios were constructed using CMIP6 data, representing low-stress (SSP119), medium-stress (SSP245), and high-stress (SSP585) conditions. The results show the following: (1) from 2000 to 2020, cropland was predominant in the Yellow River Basin, Henan Province, with significant land conversion to impervious land (construction land) and forest land; (2) water yield changes during this period were primarily influenced by meteorological factors, with land use changes having negligible impact; (3) by 2030, the water yield of Scenario 1 is highest among different land use scenarios, marginally surpassing Scenario 2 by 1.60 × 108 m3; (4) climate scenarios reveal significant disparities, with SSP126 yielding 54.95 × 108 m3 higher water yield than SSP245, driven predominantly by precipitation; (5) Geodetector analysis identifies precipitation as the most influential single factor, with significant interactions among meteorological and socio-economic factors. These findings offer valuable insights for policymakers and researchers in formulating land use and water resource management strategies.

Quantitative prediction of water quality in Dongjiang Lake watershed based on LUCC

Land Use/ Cover Change (LUCC) plays a crucial role in influencing hydrological processes, nutrient cycling, and sediment transport in watersheds, ultimately impacting water quality on both spatial and temporal scales. Accurately predicting changes in watershed water quality is beneficial for the sustainable management of water resources. Current models often lack the ability to effectively predict water quality changes in a dynamic spatio-temporal context, particularly in complex watershed environments. The overall purpose of the study is to establish a comprehensive and dynamic modeling framework that links LUCC with water quality, allowing for accurate predictions of future water quality under varying land use scenarios. The model, which uses water quality as the dependent variable and LUCC as the independent variable, was developed to quantitatively predict changes in watershed water quality. To achieve this, annual multi-period remote sensing images from Landsat-5, Landsat-8 or Sentinel-2 satellites spanning from 1992 to 2022 were analyzed. Random Forest (achieving a Kappa coefficient of 0.9468) were employed to classify land use within the watershed. Based on classification results, a Cellular Automata-Markov chain model (CA-Markov) was constructed to simulate and predict the spatio-temporal patterns of land use, incorporating driving factors such as proximity to water systems, roads, elevation, and slope. Validation of the model using LUCC data from 2020 yielded a high prediction accuracy with a Kappa coefficient of 0.9505. The CA-Markov model was further utilized to project LUCC under three different scenarios—natural development, ecological protection, and arable land protection—between 2023 and 2033. Based on these projections, the coupled water quality and LUCC model was employed to predict water quality changes in the watershed over the same period. Key findings indicate that water quality is likely to improve under ecological protection scenario, while deterioration is expected under natural development scenario and cropland protection scenario due to urban expansion, agricultural practices, and water diversion for irrigation. This study provides a robust framework for watershed management, offering scientific guidance for source management and water purification efforts, thereby contributing significantly to the sustainable development of water resources.

Natural Water Sources and Small-Scale Non-Artisanal Andesite Mining: Scenario Analysis of Post-Mining Land Interventions Using System Dynamics

Small-scale open-pit, non-artisanal mining of low-value ores is an understudied practice despite its widespread occurrence and potential impact on freshwater resources due to mining-induced land-use/cover changes (LUCCs). This research investigates the long-term impacts of andesite mining in Pasuruan, Indonesia, on the Umbulan Spring’s water discharge within its watershed. System Dynamics (SD) modeling captures the systemic and systematic impact of mining-induced LUCCs on discharge volumes and groundwater recharge. Agricultural and reservoir-based land reclamation scenarios then reveal post-mining temporal dynamics. The no-mining scenario sees the spring’s discharge consistently decrease until an inflection point in 2032. With mining expansion, reductions accelerate by ~1.44 million tons over two decades, or 65.31 thousand tons annually. LUCCs also decrease groundwater recharge by ~2.48 million tons via increased surface runoff. Proposed post-mining land interventions over reclaimed mining areas influence water volumes differently. Reservoirs on reclaimed land lead to ~822.14 million extra tons of discharge, 2.75 times higher than the agricultural scenario. Moreover, reservoirs can restore original recharge levels by 2039, while agriculture only reduces the mining impact by 28.64% on average. These findings reveal that small-scale non-artisanal andesite mining can disrupt regional hydrology despite modest operating scales. Thus, evidence-based guidelines are needed for permitting such mines based on environmental risk and site water budgets. Policy options include discharge or aquifer recharge caps tailored to small-scale andesite mines. The varied outputs of rehabilitation scenarios also highlight evaluating combined land and water management interventions. With agriculture alone proving insufficient, optimized mixes of revegetation and water harvesting require further exploration.

Geo-environmental monitoring of coastal and land resources for Coatzacoalcos coastal region

Coatzacoalcos is one of the notable Mexico coastal areas regarding location, activities, and resources. The purpose of the current study is to use geographic techniques to assess the spatial and temporal changes in Land Use/Cover (LULC), Land Surface Temperature (LST), and Shoreline as a result of anthropogenic and natural factors. Four calibrated multi-temporal Landsat images, dated 1993, 2003, 2013, and 2023, were combined and processed to accomplish this goal. The six primary LULC classes forest, built-up land, mining, water bodies, and agriculture were mapped using RF Machine learning algorithms. The last period (2003–2023) shows the highest rate of built-up land expansion, while the years 1993–2013 show the lowest rate of agricultural land reduction. Forest cover in the southeast decreased steadily from 339.25, 308.49, 287.43, and 211.83 km2 in 1993, 2003, 2013, and 2023. There is a slight difference in mean LST between built-up areas that recorded 26, 29, 32, and 33 °C in 1993, 2003, 2013, and 2023, respectively. The following is an order of LULC from lowest to highest LST during 2023 water body 12 °C, Forest 19 °C, Agriculture Land 22 °C, Mining 26 °C, Barren Land 34 °C and Built-up Land 33 °C. In Zone B near Coatzacoalcos showed particularly high accretion as a result of building artificial structures. Maximum rates of accretion and erosion were recorded at 2.0 m/year and −9.63 m/year, respectively. Fortunately, Zone C has minimal urban development and is home to forests and agricultural areas, so the potential negative effects are reduced. This study aids in understanding spatial and temporal LULC changes, LST variations, and shoreline dynamics, crucial for the sustainable management of Coatzacoalcos coastal resources in Mexico.

Climate and land use/land cover changes increasing habitat overlap among endangered crested ibis and sympatric egret/heron species

Climate and land use/land cover (LULC) changes have far-reaching effects on various biological processes in wildlife, particularly interspecific interactions. Unfortunately, interspecific interactions are often overlooked when assessing the impacts of environmental changes on endangered species. In this study, we examined niche similarities and habitat overlaps between wild Crested Ibis and sympatric Egret and Heron species (EHs) in Shaanxi, China, using Ecological niche models (ENMs). We aimed to forecast potential alterations in habitat overlaps due to climate and LULC changes. The results showed that although EHs possess a broader niche breadth compared to the Crested Ibis, they still share certain niche similarities, as indicated by Schoener’s D and Hellinger’s I values exceeding 0.5, respectively. Notably, despite varying degrees of habitat reduction, the shared habitat area of all six species expands with the changes in climate and LULC. We suggest that with the climate and LULC changes, the habitats of sympatric EHs are likely to suffer varying degrees of destruction, forcing them to seek refuge and migrate to the remaining wild Ibis habitat. This is primarily due to the effective conservation efforts in the Crested Ibis habitat in Yangxian County and neighboring areas. Consequently, due to the niche similarity, they will share and compete for limited habitat resources, including food and space. Therefore, we recommend that conservation efforts extend beyond protecting the Crested Ibis habitat. It is crucial to control human activities that contribute to LULC changes to safeguard the habitats of both Crested Ibis and other sympatric birds.

Land-Based Carbon Effects and Human Well-Being Nexus

In light of international climate agreements and the Sustainable Development Goals (SDGs), there is a growing need to enhance the understanding of the linkages among land use/cover change (LUCC) and its carbon effects (CEs), as well as human well-being (HW). While existing studies have primarily focused on the impacts of LUCC on CEs or ecosystem services, there remains a gap in systematically elucidating the complex relationships among LUCC, CEs, and HW. This paper presents a comprehensive review of the nexus between land-based CEs and HW, examining: (1) the correlation between LUCC and CEs, encompassing methodologies for investigating LUCC CEs; (2) the association between CEs and HW, introducing the concept of “low-carbon human well-being” and evaluation framework; and (3) the proposed framework of “LUCC-CEs-HW,” which delves into the intricate connections among three elements. The study identifies research gaps and outlines potential future directions, including assessments of LUCC CEs and low-carbon HW, exploration of the “LUCC-CEs-HW” nexus, and the development of standardized measurement approaches. Key opportunities for further investigation include establishing a unified evaluation index system and developing scalable methods. This paper elucidates the relationships among LUCC, CEs, and HW, offering insights for future works.

The urban air quality nexus: Assessing the interplay of land cover change and air pollution in emerging South Asian cities

Air quality degradation presents a significant public health challenge, particularly in rapidly urbanizing regions where changes in land use/land cover (LULC) can dramatically influence pollution levels. This study investigates the association between LULC changes and air pollution (AP) in the five fastest-growing cities of Bangladesh from 1998 to 2021. Leveraging satellite data from Landsat and Sentinel-5P, the analysis reveals a substantial increase in urban areas and sparse vegetation, with declines in dense vegetation and water bodies over this period. Urban expansion was most pronounced in Sylhet (22–254%), while Khulna experienced the largest increase in sparse vegetation (2–124%). Dense vegetation loss was highest in Dhaka (20–77%) and water bodies (9–59%) over this period. Concentrations of six major air pollutants (APTs) - aerosol index, CO, HCHO, NO2, O3, and SO2 - were quantified, showing alarmingly high levels in densely populated industrial and commercial zones. Pearson's correlation indicates strong positive associations between APTs and urban land indices (R > 0.8), while negative correlations exist with vegetation indices. Geographically weighted regression modeling identifies city centers with dense urban built-up as pollution hotspots, where APTs exhibited stronger impacts on land cover changes (R2 > 0.8) compared to other land classes. The highest daily emissions were observed for O3 (1031 tons) and CO (356 tons) at Chittagong in 2021. In contrast, areas with substantial green cover displayed weaker pollutant-land cover associations. These findings underscore how unplanned urbanization drives AP by replacing natural land cover with emission sources, providing crucial insights to guide sustainable urban planning strategies integrating pollution mitigation and environmental resilience.

Mega project impact on urban growth and ecosystem service

In an effort to forecast and estimate the value of ecosystem services (ESVs) and land use and land cover changes (LULC), recent global events and research have centered on the evaluation of LULC. This study evaluates the effectiveness of an integrated approach using multi-layer perceptron-Markov chain analysis (MLP-MCA) and remote sensing data for monitoring land use and land cover (LULC) changes. The study area comprises the three Bangladeshi upazilas that the Padma Bridge connects: Shariatpur, Louhajang, and Janjira. The Ecosystem Services Valuation Database (ESVD) was used to evaluate the impacts of changes in land use and land cover (LULC) on Ecosystem Service Values (ESVs). The LULC of the study area was estimated for the years 2000, 2010, and 2020, and the forecast period for urban development was 2030 and 2040. Additionally, the monetary value of ecosystem services was evaluated across the time. As per the LULC change analysis, there is a projected 4.35% growth in the built-up area from 2000 to 2020. After the bridge is constructed, the built-up area is projected to increase by 7% in 2030 and 14% in 2040, according to the forecast. The exponential expansion of developed land has a paradoxical effect on the value of ecosystem services. From 2020 to 2040, it is expected that the ESVs for provision, regulation, culture, and support will experience a reduction of approximately 213.24 million USD/ha. Even if the establishment of a bridge results in economic stability and investment attraction for the nation, unforeseen ecosystem service losses cannot contribute to long-term, sustainable development. This study, by establishing a correlation between urban area expansion and the deterioration of ecosystem services, can serve as a standard and basis for guiding management decisions.

Characteristics and drivers of the soil multifunctionality under different land use and land cover types in the drylands of China

The drylands of China cover approximately 6.6×106 km2 and are home to approximately 5.8×108 people, providing important ecosystem services for human survival and development. However, dryland ecosystems are extremely fragile and sensitive to external environmental changes. Land use and land cover (LULC) changes significantly impact soil structure and function, thus affecting the soil multifunctionality (SMF). However, the effect of LULC changes on the SMF in the drylands of China has rarely been reported. In this study, we investigated the characteristics of the SMF changes based on soil data in the 1980s from the National Tibetan Plateau Data Center. We explored the drivers of the SMF changes under different LULC types (including forest, grassland, shrubland, and desert) and used structural equation modeling to explore the main driver of the SMF changes. The results showed that the SMF under the four LULC types decreased in the following descending order: forest, grassland, shrubland, and desert. The main driver of the SMF changes under different LULC types was mean annual temperature (MAT). In addition to MAT, pH in forest, soil moisture (SM) and soil biodiversity index in grassland, SM in shrubland, and aridity index in desert are crucial factors for the SMF changes. Therefore, the SMF in the drylands of China is regulated mainly by MAT and pH, and comprehensive assessments of the SMF in drylands need to be performed regarding LULC changes. The results are beneficial for evaluating the SMF among different LULC types and predicting the SMF under global climate change.

Study on the characteristics and scenario simulation of land use change in the Chaohu Lake Basin, China

Effectively evaluating the historical and future land use/cover change (LUCC) is significant for effective land use planning and management, ecological conservation, and restoration. Taking the Chaohu Lake Basin (CLB) as the study area, GIS technology and geographic detector were used to quantitatively analyze the change characteristics and driving factors of LUCC under the three periods in 2000, 2010, and 2020 of the CLB. This study aimed to comprehend the alterations that have transpired over the last two decades. In addition, the PLUS model was utilized to forecast LUCC trends under three scenarios: natural development, urban development, and ecological protection by 2030 in the CLB. The results suggest a significant decrease of the cultivated land area, while a considerable increase for the construction land area from 2000 to 2020 in the CLB. The expansion of the construction land area was mainly driven by the conversion of cultivated land area. Additionally, the slope was identified as the primary factor influencing LUCC, with q-values of 0.275, 0.266, and 0.258 in 2000, 2010, and 2020, respectively. The interaction between slope and soil type, distance to the trunk road and the secondary trunk road, and GDP was strong. The explanatory capacity of socioeconomic factors demonstrated a steady increase. The simulation results indicate that a decrease in cultivated land area and an increase in construction land area still occurred by 2030 in the CLB, particularly in the urban development scenario. Nonetheless, a notable deceleration of change was appeared in the ecological protection scenario. The alterations in forest and grassland areas were not significant. However, the water bodies area continued to enlarge, although the expansion was not substantial. The study results can provide policy references for the scientific management and long-term strategic planning of land resources in the CLB.

Estimation of land surface temperature and LULC changes impact on groundwater resources in the semi-arid region of Madhya Pradesh, India

The land surface temperature (LST) changes influence on many factors such as land use and land cover (LULC), vegetation and water resources etc. Now a day’s urban population growth, industrial development and human activity are increased due to human migration and urban expansion. The surface temperature is very harmful to vegetation, groundwater level, and ecosystem health. Urban pollution growth and air pollution factor is also playing important role for increase and decrease the LST with climate change impact. Demand of drinking water are increases particular in the urban city due to the population growth and urban expansion, which all of this direct effect on surface and groundwater sources and resources. Hence we have been chosen the latest technologies such as remote sensing (RS), Geographic information System (GIS) and Google Earth Engine (GEE) are very effective for mapping, monitoring and assessment of spatial maps of LST, LULC, and NDVI (Normalised differential vegetation index) estimation. In this study, main focus on the LULC of 2011 and 2021 were classified using random forest (RF) algorithm, ML and remote sensing datasets. LULC were divided into four categories i. e. agricultural land, built up land, waterbody and waste land. For better understanding about the growth of LST, this study examines the association between LST and NDVI change, what vegetation condition impact on the LST. The main and important results have been found the built-up land and LST positive correlation due to increases both the factors in the urban area. LST increases gradually and its bad effect on the green land, water level and expansion of barren land. The range of LST is 43.60 °C to 45.30 °C. Less vegetation cover showing highest LST and vice versa. All of the LST, NDVI, and LULC direct effect on the groundwater availability in the area. This paper important result found the built-up land and LST both are increased in 2021, NDVI and LST having negative correlation. The results of study can very much useful for understanding the LST, NDVI and LULC, these factors what impact on groundwater availability in the study area.

Patterns of change, driving forces and future simulation of LULC in the Fuxian Lake Basin based on the IM-RF-Markov-PLUS framework

Studying land use and land cover (LULC) patterns, identifying driving forces, and simulating future scenarios are vital for grasping the complex connection between human actions and the environment. This helps in shaping sustainable land management strategies and preparing for the impacts of climate change. However, there is a necessity for a comprehensive system modeling framework that can accurately capture spatial and temporal changes in LULC, analyze driving mechanisms, and provide an integrated analysis of future simulations. In this paper, a comprehensive IM-RF-Markov-PLUS analysis framework is developed, focusing on the Fuxian Lake Basin (FLB) as a study area. The study aims to achieve accurate prediction of LULC by combining the microscopic LULC change trend and the contribution of macroscopic driving forces. The results show that: (1) The IM-RF-Markov-PLUS framework can explore the change patterns and driving mechanisms of LULC in the FLB, and accurately predict the LULC in the FLB. Compared with the PLUS model, its accuracy is improved by 2 %. (2) IM analysis reveals that LULC transformation in the FLB is both general and specific. Although the area of grassland, buildings, roads and structures converted to desert and bare land is minimal, it shows relatively tendentious and specific change characteristics. (3) Different land types are significantly affected by driving factors, with the expansion of LULCs is constrained by major factors. The distance to the lake has the most significant impact on the distribution of garden land, while the primary road has the greatest impact on the distribution of forestland. (4) Under different scenarios, the spatial heterogeneity of LULC patterns is obvious. In 2035, under baseline and economic development scenarios, cultivated land will decrease, while other LULC types will increase. Under the cultivated land protection scenario, cultivated land is protected, with an increase of 5.85 %. Under the ecological protection scenario, there is an increase in ecological land. The largest increase is in forestland, which increases by a total of 3.46 %. The ecological protection scenario presents a viable approach for ensuring the sustainable development of the FLB. The results of this paper may serve as a reliable foundation for implementing LULC strategies in the FLB and offer guidance for crafting sustainable development regulations at the regional level.

Impact of Land-Use–Land Cover Changes on the Service Value of Urban Ecosystems: Evidence from Chengdu, China

Impact of Land-Use–Land Cover Changes on the Service Value of Urban Ecosystems: Evidence from Chengdu, China

Effect of Land Use Land Cover on the Hydrology of Rwizi River Catchment located in Southwestern Uganda

Changes in land use and land cover usually affect the hydrological processes of river flows, sediment transport, and water quality on a global scale. Hence, the objective of this paper was to investigate the effect of Land Use Land Cover (LULCC) on the Hydrology of Rwizi River Catchment located in South-western Uganda using appropriate standard techniques and procedures including Soil and Water Assessment Tool (SWAT). Model calibration and validation demonstrated good agreement (R² = 0.76-0.86, NSE = 0.75-0.78). LULC analysis revealed significant increases in built-up areas and forestland, with declines in grazing land and wetlands. These changes were driven by socio-economic factors and hydro-climatic influences. The study found strong correlations between LULC types and sediment yield, highlighting the implications for water quality and erosion control. The results show that urban growth raises surface runoff and peak flows as a result of a rise in impervious surfaces, whereas agricultural intensification raises water demand and lowers base flow, especially during dry spells. Deforestation has led to increased sedimentation rates, degrading water quality. These findings underscore the significant anthropogenic and climatic impacts on LULCC dynamics and hydrological processes in the catchment. The study emphasizes the critical need for integrated watershed management strategies to mitigate these impacts and ensure sustainable water management practices. By advancing understanding in hydrological sciences, this research informs policy and management decisions for sustainable development in tropical river basins globally.

Spatiotemporal landscape pattern changes and their effects on land surface temperature in greenbelt with semi-arid climate: A case study of the Erbil City, Iraq

Urban expansion of cities has caused changes in land use and land cover (LULC) in addition to transformations in the spatial characteristics of landscape structure. These alterations have generated heat islands and rise of land surface temperature (LST), which consequently have caused a variety of environmental issues and threated the sustainable development of urban areas. Greenbelts are employed as an urban planning containment policy to regulate urban expansion, safeguard natural open spaces, and serve adaptation and mitigation functions. And they are regarded as a powerful measure for enhancing urban environmental sustainability. Despite the fact that, the relation between landscape structure change and variation of LST has been examined thoroughly in many studies, but there is a limitation concerning this relation in semi-arid climate and in greenbelts as well, with the lacking of comprehensive research combing both aspects. Accordingly, this study investigated the spatiotemporal changes of landscape pattern of LULC and their relationship with variation of LST within an inner greenbelt in the semi-arid Erbil City of northern Iraq. The study utilized remote sensing data to retrieve LST, classified LULC, and calculated landscape metrics for analyzing spatial changes during the study period. The results indicated that both composition and configuration of LULC had an impact on the variation of LST in the study area. The Pearson’s correlation showed the significant effect of Vegetation 1 type (VH), cultivated land (CU), and bare soil (BS) on LST, as increase of LST was related to the decrease of VH and the increases of CU and BS, while, neither Vegetation 2 type (VL) nor built-up (BU) had any effects. Additionally, the spatial distribution of LULC also exhibited significant effects on LST, as LST was strongly correlated with landscape indices for VH, CU, and BS. However, for BU, only aggregation index metric affected LST, while none of VL metrics had a relation. The study provides insights for landscape planners and policymakers to not only develop more green spaces in greenbelt but also optimize the spatial landscape patterns to reduce the influence of LST on the urban environment, and further promote sustainable development and enhance well-being in the cities with semi-arid climate.

Urban sprawl impact assessment on the land surface temperature over the green capital of Gujarat using a geospatial approach.

In developing countries, examining land use land cover (LULC) change pattern is crucial to understanding the land surface temperature (LST) effect as urban development lacks coherent policy planning. The variability in LST is often determined by continuously changing LULC patterns. In this study, LULC change effect analysis on LST has been carried out using geometric and radiometric corrected thermal bands of multi-spectral Landsat 7 ETM + and 8 TIRS/OLI satellite imagery over Gandhinagar, Gujarat, in the years 2001 and 2022, respectively. Maximum likelihood classification (MLC) was applied to assess LULC change while an NDVI-based single-channel algorithm was used to retrieve LST using Google Earth Engine (GEE). Results showed a substantial change in built-up (+ 347.08%), barren land (- 50.74%), and vegetation (- 31.66%). With the change in LULC and impervious surfaces, the mean LST has increased by 5.47 ℃. The impact of sparse built-up was seen on vegetation and agriculture as a maximum temperature of > 47 ℃ was noticed in all LULC classes except agriculture, where the temperature reached as high as > 49 ℃ in 2022. Since Gandhinagar is developing a twin-city plan with Ahmedabad, this study could be used as a scientific basis for sustainable urban planning to overcome dynamic LULC change and LST impacts.

Assessment of Landscape Change and its Relationships with Surface Temperature and Geo-spatial Indices during 1992 - 2022 at Haldia Industrial Region, West Bengal, India

Unplanned local development and alterations in Land Use and Land Cover (LULC) are an early alert for towns and cities around the world. The population pressure has resulted in the conversion of natural land into impermeable areas, which has altered the surface energy budget and created microclimatic differences locally. The main objective of the present study is to estimate LULC changes and its relation to increases Land Surface Temperature (LST) in the Haldia Industrial Region (HIR) of West Bengal using multi-temporal Landsat 5 Thematic Mapper (TM) of 1992 and Landsat 8 Operational Land Imager (OLI) of 2022 with 30-m spatial resolution images were obtained from the USGS website. The supervised classification method was applied by using Maximum Likelihood classification (MLC) to classify the satellite images into various LULC classes such as settlement, waterbody, vegetation, agriculture land, and fallow land, respectively. The result suggested an overall increase of settlement area from 13.49 km2 in 1992 to 44.54 km2 in 2022. On the other hand, the agriculture land decreased from 214.26 km2 to 152.34 km2 due to fast urbanization, decline green lands, and expansion of barren lands. The outcome result from LST was exhibited that the LST value has increased 3.77°C during 1992 to 2022 in this study area. The Normalized Difference Vegetation Index (NDVI) was showed a strong negative relationship with LST with a determination coefficient (R2) values found as 0.491 (1992) and 0.356 (2022). The positive determination coefficient between LST with Normalized Difference Water Index (NDWI) was found as 0.0002 (1992), and 0.0417 (2022). R2 values were estimated as 0.174 (1992), and 0.0347 (2022) between LST with Normalized Difference Built-up Index (NDBI) that indicated a positive determination coefficient. The findings enhanced understanding of the relationship between urban LST and LULC in developing an inclusive climate resilience policy and making the HIR more sustainable to the effects of climate change.

Delineation of Shoreline and Associated Land Use/Land Cover Changes along the Coast of Chattogram, Bangladesh Based on Remote Sensing and GIS Techniques

This study aimed at delineating the shoreline by using the Digital Shoreline Analysis System (DSAS 5.0) tool and detected the changes of land use/land cover (LULC) by Google Earth Engine (GEE) platform. The shoreline is divided into two zones, whereas Zone I covered 87.12[Formula: see text]km and Zone II possessed 168.05[Formula: see text]km. According to End Point Rate (EPR), the mean shoreline change rate of Zone I is 3.55[Formula: see text]m/year and Zone II is [Formula: see text]6.84[Formula: see text]m/year. Likewise, based on Linear Regression Rate (LRR), the mean shoreline change rate of Zone I is 5.46[Formula: see text]m/year and Zone II is [Formula: see text]4.71[Formula: see text]m/year, respectively. Apart from that, the Net Shoreline Movement (NSM) recorded in Zone I is 109.42[Formula: see text]m as well as Zone II is [Formula: see text]213.25[Formula: see text]m, which also revealed how much the shoreline has changed during the last 32 years. This study also used the Kalman filter model to forecast the shoreline positions for 20 years. The most destructive signal is that more than 70% of the coastline is vulnerable due to erosion, whereas 6% is highly vulnerable. By contrast, the results of LULC changes demonstrated the increasing trend of water bodies, built up, and agricultural land while vegetation along with bare land is reduced continuously. The overall accuracy is recorded above 88%, and the kappa co-efficient is found above 0.87 for all three years. The outcome of this study will provide fruitful insight into coastal land use management and adaptation measures against the ongoing along with future threats of shoreline changes to coastal ecosystems and livelihoods.

Exploring carbon storage and sequestration as affected by land use/land cover changes toward achieving sustainable development goals

Understanding the impact of changes in land use/land cover (LULC) on carbon sequestration (Cseq) and emission leads to achieving sustainable development goals (SDGs). For this, Business-As-Usual (BAU) and Sustainable Development (SD) scenarios were examined in Azarshar city, Iran which is faced with urban intensification. The spatiotemporal dynamics of the carbon cycle and influences of various urban growth indicators are still unclear even under climate change, rapid urbanization, and ecological deterioration. In this research, total carbon storage (Cts) and Cseq were determined at four carbon pools i.e., aboveground carbon (AGC), belowground carbon (BGC), dead organic carbon (DeOC), and soil organic carbon (SOC). This research revealed a successful implementation of integrated CA-Markov and InVEST models in delineating LULC changes between 2013 and 2033. It was concluded that land resources management play a crucial role in decreasing Cseq along with increasing carbon emission across the study area. The modelling results showed a significant shifting from barren and cropland to developed land uses. This research goes beyond providing supporting evidence that urban expansion is a key factor driving the aforementioned changes, but also illustrates the importance of remote sensing in ecological modelling, especially where information is sparse.