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Quantitative analysis of LULC changes and their effects on carbon stock and sequestration is important for mitigating climate change. Therefore, this study examines carbon stock and sequestration in relation to LULC changes using the Land Change Modeler (LCM) and Ecosystem Services Modeler (ESM) in tropical dry deciduous forests of West Bengal, India. The LULC for 2006, 2014, and 2021 were classified using Google Earth Engine (GEE), while LULC changes and predictions were analyzed using LCM. Carbon stock and sequestration for present and future scenarios were estimated using ESM. The highest carbon was stored in forest land (124.167 Mg/ha), and storage outside the forest declined to 13.541 Mg/ha for agricultural land and 0–8.123 Mg/ha for other lands. Carbon stock and economic value decreased from 2006 to 2021, and are likely to decrease further in the future. Forest land is likely to contribute to 94% of future carbon loss in the study region, primarily due to its conversion into agricultural land. The implementation of multiple-species plantations, securing tenure rights, proper management practices, and the strengthening of forest-related policies can enhance carbon stock and sequestration. These spatial-temporal insights will aid in management strategies, and the methodology can be applied to broader contexts. [ABSTRACT FROM AUTHOR]

Wetlands are disappearing globally at alarming rates; since 1900, 71% of wetlands have changed into other forms of land cover. The CA-Markov model is one of the most effective methods for forecasting LULC change. In order to predict LULC changes of Shadegan wetland in 2050, images for the years 1980, 1990, 2000, 2010, and 2020 were classified based on segmentation and artificial neural networks (ANNs), and three classes were considered, including vegetation, bare land, and water. To assess accuracy of classification and prediction, the Kappa coefficient was calculated. Results indicate that CA-Markov has moderate predictive capability for future changes. Results of the image classification show that most of the changes occurred in vegetation from 2000 to 2020. So, about 170,000 hectares of this class have been converted to bar land. By comparing the LULC map in 2020 and 2050, if the current trend in the region is continued, in the 2050 year, 79.6% of the total area will be covered by the bare land. Increasing the amount of dry land in the area can create dust sources. During the last years, with the intensification and continuation of drought, dried parts of wetlands such as Shadegan became the most active dust sources in the southwest of Iran. The aerosol optical depth time series data were used to verify the model’s prediction findings. The result of the Mann-Kendall (MK) test shows the positive trend in the AOD time series, indicating an increasing trend in dust concentration. [ABSTRACT FROM AUTHOR]

Evaluating how pollutant loads react to changes in land use/land cover (LULC) is a challenging task due to the intricate relationships among the many elements within a watershed. However, the difficulty in connecting LULC change and nonpoint source (NPS) pollution loads to streams may be lessened by combining hydrological modeling with geospatial tools and multivariate statistics. The objective of this study was to investigate the long-term effects of LULC change on NPS pollution loads in a highly human-dominated catchment, in central Ethiopia. In the study, hydrologic modeling was used to estimate the NPS parameters from multispectral Landsat images, and multivariate statistical techniques were then used to extract major LULC types that explain the variances of NPS loads between 1981 and 2020. The results demonstrated that there were human-induced LULC changes in the area, as the built-up and agricultural landscapes are rising (186.4% and 5.8%, respectively), and shrub and forest lands are decreasing (67.1% and 41%, respectively). As a result of these changes, the concentrations of nitrate (NO3), total P, total N, organic N, and organic P loads were increased by 69.41, 19.83, 18.45, 18.88, and 24.05%, respectively. Reductions in natural vegetation, as well as agriculture intensification, are the major contributors to the NPS pollutant losses to surface water sources. The result also revealed that pollution nutrients are strongly related to deforestation and agricultural land expansion. Proper adaptation strategies should be implemented to minimize the negative impact of LULC changes in the area. HIGHLIGHTS The proposed approaches are robust in characterizing diffusive pollution loads.; NPS nutrient loadings are estimated to increase in the area.; Deforestation and intensive agricultural activities are major contributors to the NPS loadings.; Multivariate statistical techniques have great potential for estimating significant pollution loads.;

Historical land use reconstructions help to assess climate change, interactions between ecosystems and human and strengthen the knowledge about these interactions. They are conducted on the basis of historical maps that only cover certain areas. Hence, there is a need to seek other maps enabling historical land use to be reconstructed. The aim of study is to assess the suitability of contemporary maps for reconstructing a historical non-forest area range in the Western Carpathians. The content of contemporary maps was compared with that of historical maps, including the number of glades, their area and the length of their boundaries. Over 60% of glades were reconstructed, which is 90% of the glade area inventoried based on historical maps. Over 50% glades with an area of less than 1ha were not reconstructed. However, the area they occupy does not account for 2% of the total glade area. Thus, it has no significant impact on the total area of the reconstructed glades. As much as 90% of the boundaries' length was reconstructed. The study shows that contemporary maps may be useful in reconstructing the forest and glades range and may be an additional source of information to verify the content of historical maps. • Contemporary maps are useful to reconstruct the historical land cover. • Reconstructing the land cover forms area gives better results than their boundaries. • Invariability of the plot structure make it easier to reconstruct past land use. • Large land fragmentation make it easier to reconstruct past land use. • Spatial range of different plots indicates the maximal range of past deforestation. [ABSTRACT FROM AUTHOR]

Drought events threaten freshwater reservoirs and agricultural productivity, particularly in semi-arid regions characterized by erratic rainfall. This study evaluates a novel technique for assessing the impact of drought on LULC variations in the context of climate change from 2018 to 2022. Various data sources were harnessed, encompassing Sentinel-2 satellite imagery for LULC classification, climate data from the CHIRPS and AgERA5 databases, geomorphological data from JAXA’s ALOS satellite, and a drought indicator (Vegetation Health Index (VHI)) derived from MODIS data. Two classifier models, namely gradient tree boost (GTB) and random forest (RF), were trained and assessed for LULC classification, with performance evaluated by overall accuracy (OA) and kappa coefficient (K). Notably, the GTB model exhibited superior performance, with OA > 90% and a K > 0.9. Over the period from 2018 to 2022, Fez experienced LULC changes of 19.92% expansion in built-up areas, a 34.86% increase in bare land, a 17.86% reduction in water bodies, and a 37.30% decrease in agricultural land. Positive correlations of 0.81 and 0.89 were observed between changes in agricultural LULC, rainfall, and VHI. Furthermore, mild drought conditions were identified in the years 2020 and 2022. This study emphasizes the importance of AI and remote sensing techniques in assessing drought and environmental changes, with potential applications for improving existing drought monitoring systems. [ABSTRACT FROM AUTHOR]

Land use and land cover changes such as agricultural land abandonment along with soil erosion are perceived to be important factors that add to land degradation worldwide. In this study, we used aerial imagery, archival-Structure from Motion (SfM) reconstruction and airborne-LiDAR surveys to reconstruct land abandonment along with pipe collapse and gully development in a semi-arid Mediterranean catchment area of the Ebro Valley (Spain) during 1957–2021. Agricultural land dynamics were analysed from the study of planform changes to field crops. Land degradation associated to pipe collapse and gully development was inferred from the geomorphic change detection deduced from the comparison of topographic models obtained from archival-SfM and LiDAR datasets. Through spatial correlation analysis, we identified that higher, steeper, and more hydrologically connected field crop areas were the first to be abandoned. Additionally, the extent of pipe collapses and gullying processes was significantly correlated with the degree of land abandonment over the duration of the study period. Our findings reveal that approximately 20 % of agricultural lands within the study area were abandoned during said study period, with up to 15 % of the abandoned area directly impacted by pipe collapse and gullying processes. Erosion rates associated with these processes within the catchment, implied erosion areas of 3.9 ha and 1.5 ha for the period 1977–2009 and 2009–2021, ranging between 120 Mg/ha yr−1 and 203.2 Mg/ha yr−1, respectively. Our study highlights that abandonment in said area is predominantly conditioned by land degradation resulting from pipe collapses and gully development. The recognition and protection of piping and gully affected areas as geodiversity sites is presented as an alternative at a local level to mitigate the economic impacts of soil degradation. Understanding the effects that pipe collapse and gully development have on arable lands over long-term study periods (i.e., >50 years) is essential in order to shed light on the interconnected factors influencing land productivity and agricultural sustainability. This ultimately guides us to make informed policy decisions that mitigate these detrimental effects.

ABSTRACTAssessing ecosystem services values (ESV) within land use/land cover (LULC) changes is crucial for promoting human well-being and sustainable development of regional ecosystems. Yet, the spatial relationship between LULC changes and ecosystem services is still unclear in Yemen. This study aimed to assess the impacts of LULC changes on ESV in Ibb City, over three decades (1990–2020), and to predict the ESV changes in 2050. The hybrid land use classification technique for classifying Landsat images, the CA-Markov model for LULC prediction, and the benefit transfer method (BTM) for assessment ESV were employed. Our findings revealed that there was a continuous increase in built-up areas and barren land, with a decrease in cultivated land and grassland, which are predicted to continue for the next 30 years. Consequently, the total ESV has decreased from US$ 68.5 × 106 in 1990 to US$ 65.2 × 106 in 2020 and is expected to further reduce to US$ 61.2 × 106 by 2050, reflecting the impact of urban expansion and socio-economic activities on ESV. The study provides insights for future ESV monitoring, which will contribute to the formulation of effective land-use strategies for more sustainable ecosystem services, particularly in rapidly urbanizing data-limited regions.

In the face of escalating environmental challenges, the changes in land-use and land-cover (LULC) emerges as a persistent and significant threat, profoundly impacting the stability of eco-biodiversity. This study analyzes LULC changes using remote sensing techniques to detect environmental degradation in Abeokuta South, Nigeria, contributing to the discourse on environmental sustainability. LULC maps for the years 2002, 2012, and 2022 were generated, incorporating spectral environmental indicators such as land surface temperature (LST), normalized differential vegetation index (NDVI), and normalized difference built-up index (NDBI) from Landsat 7 and 8 satellite images. The support vector machine (SVM), and FRAGSTATS software, operating within the IDRISI and Arc-MAP environment, were employed to evaluate the area’s LULC changes and land-use metrics. The findings revealed that built-up areas from 2000 to 2022 underwent the most significant changes, increasing by 39.52 km2 (55.85 %), while a noticeable decrease in vegetation cover trend by 27.95 km2 (36.45 %) was observed. Spatial land-use metrics, in conjunction with LST, NDVI, and NDBI, illustrated the quantitative and qualitative environmental changes in the area. Undeniably, the amalgamation of satellite remote-sensed data and spatial land-use metrics offers valuable tools to provide ecological information for urban sustainability. This study underscores the need for urgent attention from society, government, and stakeholders to manage population growth and balance human needs for a sustainable environment, thereby contributing to the broader goal of environmental sustainability. [ABSTRACT FROM AUTHOR]

The purpose of this study is to evaluate the impacts of LULC changes on the hydrological components of a watershed using multivariate statistics, and hydrological modeling approaches. The study analyzed the LULC distributions, and changes corresponding to the years 2000, 2010, and 2020. The SWAT model was then applied to assess the hydrological impacts of these changes in the studied watershed. Finally, changes in LULC types were correlated with the water balance components using a Partial Least Squares Regression (PLSR) method. The result showed a continuous expansion of barren, built-up, and cropland areas, while forests, shrubs, and grassland decreased by about 67.12, 41, and 36.88%, respectively. The modeling result showed that surface runoff, water yield, and evapotranspiration decreased by 16.1, 2.9, and 9.3%, respectively. In contrast, base flow, soil water storage, and lateral flow of the watershed increased by up to 19.1%, 55.9%, and 150.4%, respectively, due to LULC changes. The PLSR model identified the cropland, forest, and shrub LULC types as the major factors affecting the water resource components. The study results provide useful information for policymakers and planners in the implementation of sustainable water resource planning and management in the context of environmental change. HIGHLIGHTS SWAT was calibrated and validated under varying LULC information.; Water balance components were correlated with multi-date LULC changes.; Substantial increases in cropland and built-up area, while a decrease in shrubs and forests in the area.; The declines in surface runoff and total water yield were reflected agricultural intensification, and vegetation removal.;

Gundlakamma sub-basin faces challenges with increasing water demand and climate change impacts, requiring innovative solutions for sustainable water management. The study was conducted to improve the long-term utilization of water resources in Andhra Pradesh. To accomplish this, the study attempts to estimate LULC change detection and its impact on water resources by analyzing the performance of the soil and water assessment tool (SWAT) model. From 2005 to 2021, the amount of cropland decreased while built-up land increased, indicating urban growth. The SWAT model identifies hydrological processes and assesses the temporal and spatial distribution of water resources in the watershed. Statistical parameters results reveal that a good match was found between actual and modeled flows with Nash–Sutcliffe efficiency (NSE) and coefficient of determination (R2) greater than 0.75 for both calibration and validation periods. The area has average annual precipitation, surface runoff, water yield, and actual evapotranspiration of 949.96, 215.6, 469.24, and 429.15 mm, respectively. The SWAT model's fascinating outcomes demonstrate that it could be a promising decision support tool for predicting water balance and water yield in other watersheds of Andhra Pradesh for sustainable water management of water resources where water quality and quantity are critical issues. HIGHLIGHTS The present study attempts to estimate LULC change detection and its impact on water resources by analyzing the performance SWAT model.; Land cover changes are influenced by human activities, environmental changes, and land-use decisions.; The SWAT model's fascinating outcomes demonstrate that it could be a promising decision-support tool for predicting water balance and water yield in other watersheds of Andhra Pradesh.;

Quantitative analysis of LULC changes and their effects on carbon stock and sequestration is important for mitigating climate change. Therefore, this study examines carbon stock and sequestration in relation to LULC changes using the Land Change Modeler (LCM) and Ecosystem Services Modeler (ESM) in tropical dry deciduous forests of West Bengal, India. The LULC for 2006, 2014, and 2021 were classified using Google Earth Engine (GEE), while LULC changes and predictions were analyzed using LCM. Carbon stock and sequestration for present and future scenarios were estimated using ESM. The highest carbon was stored in forest land (124.167 Mg/ha), and storage outside the forest declined to 13.541 Mg/ha for agricultural land and 0–8.123 Mg/ha for other lands. Carbon stock and economic value decreased from 2006 to 2021, and are likely to decrease further in the future. Forest land is likely to contribute to 94% of future carbon loss in the study region, primarily due to its conversion into agricultural land. The implementation of multiple-species plantations, securing tenure rights, proper management practices, and the strengthening of forest-related policies can enhance carbon stock and sequestration. These spatial-temporal insights will aid in management strategies, and the methodology can be applied to broader contexts.

The purpose of this study is to evaluate the impacts of LULC changes on the hydrological components of a watershed using multivariate statistics, and hydrological modeling approaches. The study analyzed the LULC distributions, and changes corresponding to the years 2000, 2010, and 2020. The SWAT model was then applied to assess the hydrological impacts of these changes in the studied watershed. Finally, changes in LULC types were correlated with the water balance components using a Partial Least Squares Regression (PLSR) method. The result showed a continuous expansion of barren, built-up, and cropland areas, while forests, shrubs, and grassland decreased by about 67.12, 41, and 36.88%, respectively. The modeling result showed that surface runoff, water yield, and evapotranspiration decreased by 16.1, 2.9, and 9.3%, respectively. In contrast, base flow, soil water storage, and lateral flow of the watershed increased by up to 19.1%, 55.9%, and 150.4%, respectively, due to LULC changes. The PLSR model identified the cropland, forest, and shrub LULC types as the major factors affecting the water resource components. The study results provide useful information for policymakers and planners in the implementation of sustainable water resource planning and management in the context of environmental change. [ABSTRACT FROM AUTHOR]

Assessing ecosystem services values (ESV) within land use/land cover (LULC) changes is crucial for promoting human well-being and sustainable development of regional ecosystems. Yet, the spatial relationship between LULC changes and ecosystem services is still unclear in Yemen. This study aimed to assess the impacts of LULC changes on ESV in Ibb City, over three decades (1990--2020), and to predict the ESV changes in 2050. The hybrid land use classification technique for classifying Landsat images, the CA-Markov model for LULC prediction, and the benefit transfer method (BTM) for assessment ESV were employed. Our findings revealed that there was a continuous increase in built-up areas and barren land, with a decrease in cultivated land and grassland, which are predicted to continue for the next 30 years. Consequently, the total ESV has decreased from US$ 68.5 x 106 in 1990 to US$ 65.2 x 106 in 2020 and is expected to further reduce to US$ 61.2 x 106 by 2050, reflecting the impact of urban expansion and socioeconomic activities on ESV. The study provides insights for future ESV monitoring, which will contribute to the formulation of effective landuse strategies for more sustainable ecosystem services, particularly in rapidly urbanizing data-limited regions. [ABSTRACT FROM AUTHOR]

Monitoring the change in land cover in disaster-affected areas, such as forests, has become a conventional forest management practice, particularly in protected areas. Most change detection and fragmentation studies rely on single-dated satellite images even while investigating changes over a long temporal span. This study aims to move a step further to compare fragmentation before and after a derecho event that occurred in August 2017 using 23 Landsat-8 images of Brusy Commune within the Tuchola Forest Biosphere Reserve. The supervised classification was carried out in the Google Earth Engine using the machine learning algorithm of random forests within the summer months of 2017 and 2018. The high overall accuracy of 0.92 was obtained for the two images which were then analysed with landscape metrics such as mean patch size, number of patches, total edge and edge density using Patch Analyst. These landscape metrics facilitated the characterisation of landscape fragmentation at both the class and landscape levels. Shannon's Diversity Index was employed to assess heterogeneity across the landscape. The findings indicate significant fragmentation, particularly in the forest and pasture classes, with overall low diversity. This study underscores the potential for future research to employ advanced machine learning techniques and non-parametric classifiers, such as neural networks, to enhance the prediction of fragmentation across various spatial scales. [ABSTRACT FROM AUTHOR]

Understanding the change dynamics of land use and land cover (LULC) is critical for efficient ecological management modification and sustainable land-use planning. This work aimed to identify, simulate, and predict historical and future LULC changes in the Sohag Governorate, Egypt, as an arid region. In the present study, the detection of historical LULC change dynamics for time series 1984–2002, 2002–2013, and 2013–2022 was performed, as well as CA-Markov hybrid model was employed to project the future LULC trends for 2030, 2040, and 2050. Four Landsat images acquired by different sensors were used as spatial–temporal data sources for the study region, including TM for 1984, ETM+ for 2002, and OLI for 2013 and 2022. Furthermore, a supervised classification technique was implemented in the image classification process. All remote sensing data was processed and modeled using IDRISI 7.02 software. Four main LULC categories were recognized in the study region: urban areas, cultivated lands, desert lands, and water bodies. The precision of LULC categorization analysis was high, with Kappa coefficients above 0.7 and overall accuracy above 87.5% for all classifications. The results obtained from estimating LULC change in the period from 1984 to 2022 indicated that built-up areas expanded to cover 12.5% of the study area in 2022 instead of 5.5% in 1984. This urban sprawl occurred at the cost of reducing old farmlands in old towns and villages and building new settlements on bare lands. Furthermore, cultivated lands increased from 45.5% of the total area in 1984 to 60.7% in 2022 due to ongoing soil reclamation projects in desert areas outside the Nile Valley. Moreover, between 1984 and 2022, desert lands lost around half of their area, while water bodies gained a very slight increase. According to the simulation and projection of the future LULC trends for 2030, 2040, and 2050, similar trends to historical LULC changes were detected. These trends are represented by decreasing desert lands and increasing urban and cultivated newly reclaimed areas. Concerning CA-Markov model validation, Kappa indices ranged across actual and simulated maps from 0.84 to 0.93, suggesting that this model was reasonably excellent at projecting future LULC trends. Therefore, using the CA-Markov hybrid model as a prediction and modeling approach for future LULC trends provides a good vision for monitoring and reducing the negative impacts of LULC changes, supporting land use policy-makers, and developing land management. [ABSTRACT FROM AUTHOR]

Context: Counter-urbanization, or the reverse migration from the city to the countryside, is a well-known demographic trend associated with rural restructuring since the 1980s. Counter-urbanization is particularly relevant in social-ecological systems with a long history of human land use, such as the Mediterranean ones. However, the extent and impacts of this phenomenon are largely unknown, particularly in this region. Objectives: We aim to review the state of the issue of counter-urbanization in the Mediterranean region. We focus on the particular determinants and outcomes of this phenomenon in Mediterranean landscapes. Methods: We conducted a bibliographic review using the Web of Science. We summarized and classified the main findings in different categories according to the socio-economic drivers of this process and its impacts on the landscape along the land sharing-sparing gradient. Results: We found 31 studies that met the criteria to be reviewed and classified them as follows: a first group of studies focused on counter-urbanization as an urban sprawl driver; a second group linked counter-urbanization to rural gentrification. These two groups point to a twofold trend of land intensification or abandonment resulting in land-sparing landscapes. A third group of studies explored the urban–rural migration motivated by economic crisis and rural areas' role as refugees that support land-sharing landscapes. A fourth group focused on multi-functional, land-sharing landscapes enhanced by rural newcomers. Conclusions: Although counter-urbanization can follow the usual path of urbanization and gentrification, it may also constitute an alternative way to reverse the current trends of rural abandonment and land-use intensification in Mediterranean landscapes. Public policies play a major role to drive this movement toward the maintenance or recovery of multifunctional landscapes, and to minimize their undesirable impacts. [ABSTRACT FROM AUTHOR]

Floods in urban areas have become a common problem globally. Extensive research has been done to understand the changes in urban areas that are resulting in floods, such as Land Use Land Cover changes and insufficient subsurface sewer systems. However, many of these studies have concentrated on the city-level changes causing increased flood events. Hence, this paper explores the impact of temporal changes in Land Use Land Cover (LULC) at the geographic unit (meso) level on the flood response for inland cities. LULC changes for two watersheds, Ulsoor and Bellandur in Bengaluru, are assessed using Remote Sensing data and GIS, and flood metrics are calculated using the Hydrologic Engineering Center Hydrologic Modeling System (HEC HMS) between the years 2003 and 2021. Changes in LULC classes are correlated with the changes in flood metrics. Results indicate that the LULC changes were similar in the two watersheds but with varying rates of change. While changes in built-up areas impacted flood metrics in the Ulsoor watershed, vegetation and open land changes impacted the Bellandur watershed.

Study region: This study refers to the Upper Tiber basin at the Ponte Nuovo outlet in central Italy. Study focus: This study aims at analyzing runoff coefficient (Rc) trends and connections with hydroclimatic parameters, namely (temperature (T), precipitation (P), soil water storage (SWS), and LULC (Land Use Land Cover) changes) using Mann-Kendall (MK) test and wavelet coherence analysis (WCA). New hydrological insights for the region: The results show a decreasing Rc over 1927–2020, coupled with increasing T and decreasing SWS based on seasonal MK test, and implications for water resource management in Central Italy. Results underscore the need for sustainable hydrological management paradigms to address challenges posed by scarcity of water resources under unpredictable changing climate. Rc-hydroclimatic parameters correlations through WCA revealed complex hydrological interactions. Precipitation exhibited insignificant and erratic patterns from 1950 to 1978, and while it established more significant correlations with Rc from 1990 to 2020, it remained moderately erratic. Conversely, weak correlation found against LULC changes, concurrently with strong positive but lagged correlation with SWS (1 month), and strong lagged (3–6 months) but negative correlation with T indicate the prevailing significance of hydroclimatic factors over LULC changes. These insights underscore the pivotal role of hydroclimatic factors in shaping regional water resources. Policymakers can harness these insights as a bedrock to develop effective strategies for water resources planning and climate change adaptation.

Spatial-temporal changes in land use and land cover (LULC) patterns have led to the fragmentation of forest ecosystems and the reduction of more than one-third of mangrove forests worldwide. Environmental protection challenges and biodiversity threats in mangrove forests have attracted national and international concerns in the last three decades. Accordingly, the present study demonstrates spatial-temporal changes in mangrove forests of Hara Biosphere Reserve using Landsat images from 1989 to 2021. Moreover, habitat integrity in this area was investigated based on ecological landscape metrics. The results of LULC changes revealed that the forest area in Hara Biosphere Reserve is decreasing, while other land use (LU) such as tidal area and bare land are increasing. Likewise, in this area, the tidal area had the top increasing trend in 2021 compared to 1989, and water body revealed the top decreasing trend during the studied years. According to the results of landscape metrics change, fragmentation and patches dispersion have increased at the level of mangrove forest and water body classes, and these results at the level of tidal area and bare land classes have decreased from 1989 to 2021. The obtained results indicate that habitat integrity has decreased at the level of mangrove forest and water body classes due to the increase of LULC spatial-temporal changes and human activities development. Therefore, planners and decision-makers should strive to reduce the human causes that have led to rapid LULC changes‏.‏

Land use and land cover changes depict trends and patterns of an area's land dynamics. The current study revealed the land use characteristics of West Tripura district which is part of the Eastern Himalayan region and shares an international boundary with the neighboring country of Bangladesh. Thus, West Tripura district is a geopolitically highly sensitive area. The capital of Tripura state i.e., Agartala city located in West Tripura district, it gives immense pressure on land use for various developmental activities since Population growth and rapid urbanisation forced. Farmers rely on cash crops rather than subsistence agriculture which impacts the district's land use pattern and modifies the land dynamics. The traditional farmers of West Tripura district very quickly geared to adopt cultivation of rubber plantation from jhum cultivation and tea plantation. All these factors influenced to work out on LULC changes in West Tripura district for the decadal (2000-10 & 2010-20), and for twenty years (2000-20) using Landsat-4 & 5 TM, Landsat-8 OLI and Survey of India topographic maps with help of ArcGIS software for the applications of supervised classification (MLC), Kappa accuracy for Landsat data, conversion matrix, NDVI, NDWI and NDBI. The results revealed that rubber plantations and settlements overlapped on natural vegetation, shrubland, tea plantation, and water bodies in the last 20 years. The water bodies are sinking due to extension of agricultural land. The current study would help to understand the land use characteristics to plan the proper utilization of resources for sustainable development. [ABSTRACT FROM AUTHOR]

The potential drivers of vegetation changes in the Sudano-Sahelian region of Africa remain poorly understood due to complex interactions between climatic and anthropogenic processes. In this study, we analyzed the vegetation greenness trends in relation to rainfall variability that we considered the essence of climatic effects on vegetation in a well-known water-limited environment by using time series of satellite data in the Sudano-Sahelian region during 2001–2020. We quantified in more detail the relative contributions of rainfall variability (climatic factor), land use/land cover (LULC) change, and fire occurrence change (non-climatic factors) to vegetation greenness trends in selected sub-regions. The results showed that vegetation greening was widespread (26.9% of the total study area), while vegetation browning was more clustered in central West Africa (5% of the total study area). About half of the vegetation greening area can be explained by long-term rainfall variability during 2001–2020, but most of the area characterized by a browning trend was unrelated to rainfall variability. An analysis of the relative importance showed that LULC changes had significant local effects on vegetation greenness and that these changes were characterized by a strong spatial heterogeneity in specific sub-regions. Gains in cropland and natural vegetation related to positive land management were probably the dominant drivers of greening in Senegal and Ethiopia. Also, the combined impacts of rainfall variability and LULC changes contributed to greening trends in the arid zone, particularly in Mali and Sudan. In contrast, vegetation browning in central West Africa appeared to be driven by cropland gain and natural vegetation loss associated with extensive agricultural production activities. Furthermore, we found that repeated fires for agricultural expansion in central West Africa intensified vegetation browning. These results advanced our understanding of vegetation dynamics in response to climatic and non-climatic factors in Sudano-Sahelian drylands characterized by increasing pressures on land resources. [ABSTRACT FROM AUTHOR]

In the Mediterranean regions, habitat degradation, alteration, and even destruction were major causes of the rarefaction of species in their natural environment. In the last decade, these phenomena are further amplified by the reduction of natural vegetation cover, urban sprawl, and climate change. In addition, the degradation of plant cover through cropping, and intensive agricultural practices causes soil erosion, habitat destruction, and loss of biodiversity. While to reduce these risks, it is necessary to assess and monitor Land Use Land Cover changes that will be crucial information for managing natural resources and guiding decision-making processes in their development plans. This is the case of a Mediterranean coastal region, Sousse, Tunisia which is characterized by its landscape diversity and the richness enhanced by the coastal and marine fauna and flora. The methodology is based on the use of Remote Sensing and Geographical Information System where different tools and functions have been employed such as Maximum Likelihood classification validated with field truth, thematic changes using classification change matrix, etc. The establishment of a multi-scalar landscape approach revealed changes in land use on a regional scale between 2007 and 2017. The landscape of Sousse region has been strongly modified by the action of Man where we note a significant growth of built-up areas and a regression of cultivated areas. From 11.84 % to 14.14 %, and from 28.83 % to 21.70 %; respectively. Hence, the growing risk of fragmentation of natural habitats, forests and agricultural areas. The development plan proposed in favor of biodiversity conservation offers a concrete example and can be useful for developing appropriate land use policy for sustainable region in Tunisia and similar Mediterranean regions. This is an essential study for all land use planning proposals as a guide to landscape conservation, enhancement and protection.

Rapid and unplanned urbanisation can lead to altered local climate by increasing land surface temperature (LST), particularly in summer months. This study investigates the Urban Heat Island (UHI) in Greater Cairo, Egypt, using remote sensing techniques to estimate LST of summer months over 45 years (1986, 2000, 2017, and predicted year 2030). The research objectives and steps were, 1- mapped land use/ land cover (LULC), 2- conducted spatiotemporal analysis of LST, with a comparison of change in LST across different land cover types, 3- predicted future LST for 2030, and 4- examined this temporal change for a hot-spot area (ring road) and a cool-spot area (the River Nile). The results showed that urban areas have increased over the last 30 years by 179.9 km2 (13 %), while agriculture areas decreased by 148 km2 (12 %) and water bodies decreased by 6 km2 (0.5 %). The mean LST over Greater Cairo increased over time, from 31.3 °C (1986) to 36.0 °C (2017) and is predicted to reach 37.9 °C in 2030. While a notable rise of mean LST in the Cairo ring road buffer zone (88 km2), where it was 31.1 °C (1986), and 37 °C (2017) due to the triple increase of urban areas on account of agriculture areas, and the LST it may reach 38.9 °C by 2030. The mean LST increased slightly more in urban hot-spot areas than in cooler cultivated areas. UHI may induce a modification in the local climate that can negatively affect agricultural land, and human thermal comfort and unfortunately lead to a less sustainable environment.

Wildfires are key drivers of land use/land cover (LULC) dynamics by burning vegetation and affecting human infrastructure. On the contrary, LULC changes (LULCCs) may affect the fire regime by influencing vegetation type, burnable areas, fuel loads and continuity. This study investigates the relationship between LULCC and wildfires. We developed a methodology based on different indicators, which allowed us to quantitatively assess and better understand the transitions between LULC classes and burnt area (BA) in Europe in the last two decades (2000–2019). The assessment was performed for the entire European continent and, independently, for each of the five European countries most affected by wildfires: Portugal, Spain, France, Italy and Greece. The main results are the following: (i) LULCC analysis revealed a net loss in forests and arable land and a net gain in shrubs; (ii) most of the BA occurred in forests (42% for the whole of Europe), especially in coniferous forests; (iii) transitions from BA generally were to transitional woodland/shrub or, again, to BA. Overall, our results confirm the existence of a strong relationship between wildfires and LULCCs in Europe, which was quantified in the present study. These findings are of paramount importance in fire and environmental system management and ecology. [ABSTRACT FROM AUTHOR]

The main objective of this research is to assess the impacts land use and land cover changes (LULC) on hydrological components using novel spatial models at sub-basin scales. The Soil and Water Assessment Tool (SWAT) was employed to analyze the long-term effect of LULC on hydrological components. The results of the calibrated and validated SWAT model demonstrated that run-off and actual evapotranspiration (ET) are expected to experience the largest increase, more than 130% and 90% in autumn, whereas the largest decrease is anticipated to occur in the summer and winter for potential evapotranspiration (PET) (−59%) and ET (−80%) by the projected time. The impacts of hydrological components, elevation, LULC, and an indicator of urbanization and land-use intensity (La) on water yield (WYLD) at sub-basin levels were then considered by four novel spatial models due to the problem of multicollinearity which is prevalent in traditional models. In particular, the Moran eigenvector spatially varying coefficients (MESVC) showed that the soil class out of LULC categories and lateral flow among hydrological properties are expected to have a statistically significant effect on spatial fluctuation of WYLD at the sub-basin scale. The results of spatially filtered unconditional quantile regression (SF-UQR) confirm the findings of the MESVC model and further implied that the lateral flow remains as a statistically significant contributor to WYLD only in lower quantiles (e.g., for quantiles lower than 0.25). The impacts of LULCs on WYLD were statistically lower than the effects caused by the hydrological components. [ABSTRACT FROM AUTHOR]

Land use and land cover (LULC) changes are one of the main factors contributing to ecosystem degradation and global climate change. This study used the Gontougo Region as a study area, which is fast changing in land occupation and most vulnerable to climate change. The machine learning (ML) method through Google Earth Engine (GEE) is a widely used technique for the spatiotemporal evaluation of LULC changes and their effects on land surface temperature (LST). Using Landsat 8 OLI and TIRS images from 2015 to 2022, we analyzed vegetation cover using the Normalized Difference Vegetation Index (NDVI) and computed LST. Their correlation was significant, and the Pearson correlation (r) was negative for each correlation over the year. The correspondence of the NDVI and LST reclassifications has also shown that non-vegetation land corresponds to very high temperatures (34.33°C–45.22°C in 2015 and 34.26°C–45.81°C in 2022) and that high vegetation land corresponds to low temperatures (17.33°C–28.77°C in 2015 and 16.53 29.11°C in 2022). Moreover, using a random forest algorithm (RFA) and Sentinel-2 images for 2015 and 2022, we obtained six LULC classes: bareland and settlement, forest, waterbody, savannah, annual crops, and perennial crops. The overall accuracy (OA) of each LULC map was 93.77% and 96.01%, respectively. Similarly, the kappa was 0.87 in 2015 and 0.92 in 2022. The LULC classes forest and annual crops lost 48.13% and 65.14%, respectively, of their areas for the benefit of perennial crops from 2015 to 2022. The correlation between LULC and LST showed that the forest class registered the low mean temperature (28.69°C in 2015 and 28.46°C in 2022), and the bareland/settlement registered the highest mean temperature (35.18°C in 2015 and 35.41°C in 2022). The results show that high-resolution images can be used for monitoring biophysical parameters in vegetation and surface temperature and showed benefits for evaluating food security.

In the Mediterranean regions, habitat degradation, alteration, and even destruction were major causes of the rarefaction of species in their natural environment. In the last decade, these phenomena are further amplified by the reduction of natural vegetation cover, urban sprawl, and climate change. In addition, the degradation of plant cover through cropping, and intensive agricultural practices causes soil erosion, habitat destruction, and loss of biodiversity. While to reduce these risks, it is necessary to assess and monitor Land Use Land Cover changes that will be crucial information for managing natural resources and guiding decision-making processes in their development plans. This is the case of a Mediterranean coastal region, Sousse, Tunisia which is characterized by its landscape diversity and the richness enhanced by the coastal and marine fauna and flora. The methodology is based on the use of Remote Sensing and Geographical Information System where different tools and functions have been employed such as Maximum Likelihood classification validated with field truth, thematic changes using classification change matrix, etc. The establishment of a multi-scalar landscape approach revealed changes in land use on a regional scale between 2007 and 2017. The landscape of Sousse region has been strongly modified by the action of Man where we note a significant growth of built-up areas and a regression of cultivated areas. From 11.84 % to 14.14 %, and from 28.83 % to 21.70 %; respectively. Hence, the growing risk of fragmentation of natural habitats, forests and agricultural areas. The development plan proposed in favor of biodiversity conservation offers a concrete example and can be useful for developing appropriate land use policy for sustainable region in Tunisia and similar Mediterranean regions. This is an essential study for all land use planning proposals as a guide to landscape conservation, enhancement and protection. [ABSTRACT FROM AUTHOR]

The coastal zone, a highly dynamic and complex environment, has important ecological and jurisdictional implications for governments and coastal managers. Based on the CORINE Land Cover classification system, this paper examined the effects of land use and land cover change (LULC) on the coastlines' dynamics along the ~24 km barrier island of Nador lagoon on the Mediterranean coast of Morocco during a period of 62years (1954-2016). The study utilized high-resolution orthoimages in the geographic information system (GIS) environment to characterize coastline evolution and LULC changes. The evolution of the coastline was assessed using a GIS tool, in particular the Digital Shoreline Analysis System (DSAS). The net rates of coastline change were calculated by using statistical methods: the End Point Rate (EPR) and the Linear Regression Rate (LRR). Results concerning the LULC changes showed that agricultural area and beach/dune classes decreased over the entire study period (62 years) by 11.14% and 28.45%, respectively. Urban fabric, shrub, forest, and saltmarsh/peat bog classes increased during the 62 years of evaluation by 2.69%, 19.92%, 16.77%, and 0.19%, respectively. Results regarding coastal analysis indicated that the accretion and erosion processes along the barrier island of the Nador lagoon (~24km) were observed at 45% (10.6 km) and 55% (12.8 km) of the coastline, respectively. The beaches of Oulad Zehra and Oulad Aissa were characterized by erosion (-0.58m/yr to -0.57m/yr respectively), while accretion was observed on the beaches of Boukana and Kariat Arkmane at rates of +2.15m/yr and +0.82m/yr, respectively. This study highlighted that natural and anthropogenic processes have a strong influence on the erosion/accretion trends identified along the barrier island of Nador lagoon. The changes in LULC have affected the barrier island of the lagoon in two different forms: (1) a significant spatial conversion due to dune reforestation and (2) a fundamental spatial modification that affects the sea-lagoon connection (inlet) and the construction of new hard engineering structures. [ABSTRACT FROM AUTHOR]

• Increasing urban sprawl causes a greater UHI effect. • Urban roads cause rapid urbanisation and a higher LST. • River Nile and cultivated areas are the coolspots in Greater Cairo. • It is recommended to conserve agriculture areas, and improve urban planning. Alteration in land cover (i.e. increase urban areas, decline agriculture land and water bodies) leads to a rise in land surface temperature in the Greater Cairo, Egypt over the last three decades during the summer months. UHI - Urban Heat Island; CI - Cooling Island; LST - land Surface Temperature; LC - Land Cover. [Display omitted] Rapid and unplanned urbanisation can lead to altered local climate by increasing land surface temperature (LST), particularly in summer months. This study investigates the Urban Heat Island (UHI) in Greater Cairo, Egypt, using remote sensing techniques to estimate LST of summer months over 45 years (1986, 2000, 2017, and predicted year 2030). The research objectives and steps were, 1- mapped land use/ land cover (LULC), 2- conducted spatiotemporal analysis of LST, with a comparison of change in LST across different land cover types, 3- predicted future LST for 2030, and 4- examined this temporal change for a hot-spot area (ring road) and a cool-spot area (the River Nile). The results showed that urban areas have increased over the last 30 years by 179.9 km2 (13 %), while agriculture areas decreased by 148 km2 (12 %) and water bodies decreased by 6 km2 (0.5 %). The mean LST over Greater Cairo increased over time, from 31.3 °C (1986) to 36.0 °C (2017) and is predicted to reach 37.9 °C in 2030. While a notable rise of mean LST in the Cairo ring road buffer zone (88 km2), where it was 31.1 °C (1986), and 37 °C (2017) due to the triple increase of urban areas on account of agriculture areas, and the LST it may reach 38.9 °C by 2030. The mean LST increased slightly more in urban hot-spot areas than in cooler cultivated areas. UHI may induce a modification in the local climate that can negatively affect agricultural land, and human thermal comfort and unfortunately lead to a less sustainable environment. [ABSTRACT FROM AUTHOR]

Land use and land cover (LULC) change is one of the clearest representations of the global environmental change phenomenon at various spatial and temporal scales. Chile is worldwide recognized to have areas dedicated to non-native forest plantations that specifically in coastal range show high environmental and economic deterioration, questioning the sustainability of the forestry industry. Currently, there are no studies in Chile that reveal the real effects of the LULC change on the water balance at basin or sub-basin scales associated with future scenarios, which might contribute to territorial decision-making and reveal the real magnitude of the effects of these dynamics. In this study, in order to study LULC dynamics in a coastal basin in South-Central Chile, we assessed and analyzed the effects of future LULC change scenarios on the hydrological processes by generating future synthetic land cover maps from Landsat (Landsat 5 TM and Landsat 8 OLI) image datasets. The hydrological model Soil Water Assessment Tool (SWAT) was calibrated and validated, using hydroclimatic time series, to simulate discharges and other hydrological components over those future LULC scenarios. The LULC future scenarios were projected using combined Markov chain analysis (CA–Markov) and cellular automata algorithms for the near (2025), middle (2035) and far (2045) future. The results revealed that the effects on the different components of the water balance of the basin are not as significant except in the soil water transfer in percolation (increase 72.4%) and groundwater flow (increase 72.5%). This trend was especially observed in sub-basins with non-native forest plantations that dominated land cover in the year 2035, in which an increase of 43.6% in percolation and groundwater flows resulted in increased aquifer recharge and water storage, mainly offset by a decrease of 27% in the evapotranspiration. This work demonstrates the importance of evaluating the impacts of the dynamics of LULC on the hydrological response of a coastal basin, and also on how the land use governance and policy are closely linked to that of water resources. [ABSTRACT FROM AUTHOR]

• Archival-SfM and LiDAR surveys allowed to reconstruct LULC changes and soil erosion. • Higher and steeper croplands were first abandoned, correlating with piping and gullying. • 20% of agricultural abandonment with up to 15% was affected by piping and gullying. • Significant degradation, with erosion rates ranging from 120 to 203.2 Mg/ha yr−1. • Piping and gully affected areas may be recognized as geodiversity sites. Land use and land cover changes such as agricultural land abandonment along with soil erosion are perceived to be important factors that add to land degradation worldwide. In this study, we used aerial imagery, archival-Structure from Motion (SfM) reconstruction and airborne-LiDAR surveys to reconstruct land abandonment along with pipe collapse and gully development in a semi-arid Mediterranean catchment area of the Ebro Valley (Spain) during 1957–2021. Agricultural land dynamics were analysed from the study of planform changes to field crops. Land degradation associated to pipe collapse and gully development was inferred from the geomorphic change detection deduced from the comparison of topographic models obtained from archival-SfM and LiDAR datasets. Through spatial correlation analysis, we identified that higher, steeper, and more hydrologically connected field crop areas were the first to be abandoned. Additionally, the extent of pipe collapses and gullying processes was significantly correlated with the degree of land abandonment over the duration of the study period. Our findings reveal that approximately 20 % of agricultural lands within the study area were abandoned during said study period, with up to 15 % of the abandoned area directly impacted by pipe collapse and gullying processes. Erosion rates associated with these processes within the catchment, implied erosion areas of 3.9 ha and 1.5 ha for the period 1977–2009 and 2009–2021, ranging between 120 Mg/ha yr−1 and 203.2 Mg/ha yr−1, respectively. Our study highlights that abandonment in said area is predominantly conditioned by land degradation resulting from pipe collapses and gully development. The recognition and protection of piping and gully affected areas as geodiversity sites is presented as an alternative at a local level to mitigate the economic impacts of soil degradation. Understanding the effects that pipe collapse and gully development have on arable lands over long-term study periods (i.e., >50 years) is essential in order to shed light on the interconnected factors influencing land productivity and agricultural sustainability. This ultimately guides us to make informed policy decisions that mitigate these detrimental effects. [ABSTRACT FROM AUTHOR]

Understanding the change dynamics of land use and land cover (LULC) is critical for efficient ecological management modification and sustainable land-use planning. This work aimed to identify, simulate, and predict historical and future LULC changes in the Sohag Governorate, Egypt, as an arid region. In the present study, the detection of historical LULC change dynamics for time series 1984–2002, 2002–2013, and 2013–2022 was performed, as well as CA-Markov hybrid model was employed to project the future LULC trends for 2030, 2040, and 2050. Four Landsat images acquired by different sensors were used as spatial–temporal data sources for the study region, including TM for 1984, ETM+ for 2002, and OLI for 2013 and 2022. Furthermore, a supervised classification technique was implemented in the image classification process. All remote sensing data was processed and modeled using IDRISI 7.02 software. Four main LULC categories were recognized in the study region: urban areas, cultivated lands, desert lands, and water bodies. The precision of LULC categorization analysis was high, with Kappa coefficients above 0.7 and overall accuracy above 87.5% for all classifications. The results obtained from estimating LULC change in the period from 1984 to 2022 indicated that built-up areas expanded to cover 12.5% of the study area in 2022 instead of 5.5% in 1984. This urban sprawl occurred at the cost of reducing old farmlands in old towns and villages and building new settlements on bare lands. Furthermore, cultivated lands increased from 45.5% of the total area in 1984 to 60.7% in 2022 due to ongoing soil reclamation projects in desert areas outside the Nile Valley. Moreover, between 1984 and 2022, desert lands lost around half of their area, while water bodies gained a very slight increase. According to the simulation and projection of the future LULC trends for 2030, 2040, and 2050, similar trends to historical LULC changes were detected. These trends are represented by decreasing desert lands and increasing urban and cultivated newly reclaimed areas. Concerning CA-Markov model validation, Kappa indices ranged across actual and simulated maps from 0.84 to 0.93, suggesting that this model was reasonably excellent at projecting future LULC trends. Therefore, using the CA-Markov hybrid model as a prediction and modeling approach for future LULC trends provides a good vision for monitoring and reducing the negative impacts of LULC changes, supporting land use policy-makers, and developing land management.

In this study, the analysis was carried out concerning previous changes in land use/land cover (LULC) for 2 years, 2000 and 2020, and their impact on water resources in the Diyala River Watershed in Iraq was assessed. The Soil and Water Assessment Tool (SWAT) model is a hydrological model used to perform the hydrological modeling process for LULC maps. The data for LULC were collected using the Landsat satellite with a resolution of 30 m, and it was classified using geographical information systems (ArcGIS). Using the confusion matrix, the accuracy of the maps for the years 2000 and 2020 was evaluated, the overall accuracy was more than 90%, and the kappa coefficient (ka) was more than 88%, which indicates the accuracy of the classification and is ideal for use in modeling work. SUFI-2 included with the SWATCUP program was used to perform the calibration and the results were validated for the outflow of the two gauging stations within the study area of Hemren station and Derbendikhan station as a monthly time step for a baseline map LULC 2000, in the period 1996–2020 with 4 years as warm up. Coefficient of determination (R 2), Nash–Sutcliffe efficiency (NSE), and percent bias (Pbias) were used, which were the most common indicators for evaluating the performance of the statistical model. The results indicated that the values of R 2 during the calibration and validation processes were (0.84–0.88) and (0.85–0.87), respectively; the NSE was (0.87–0.85), and the Pbias was (4.2–6.8)% and (5.8 to −4.1)%, respectively. Therefore, the calibration and verification results were good and satisfactory. In addition to the two LULC maps for 2000 and 2020, the parameters of the modified SWAT model were utilized to estimate the effects on the Diyala River Basin. The study found that LULC change affects basins and sub-basins differently. At the basin, hydrological parameters were largely unaffected by LULC changes. However, at the sub-basin level, the water yield and the surface runoff were changed between (−6.45 to 4.67)% and (−2.9 to 9.88)%, respectively.

For the last three decades, Islamabad - a planned city, and Rawalpindi - an unplanned city, have experienced massive land use and land cover changes. The main objective of this study was a comparative assessment and quantification of LULC changes in relation to population growth and urbanization from 1990 to 2021 with the help of satellite imagery and population data in planned and unplanned cities. For classification four land-use land cover classes: built-up, vegetation, bare land, and water were selected. Maximum likelihood algorithm and confusion matrix were employed for classification and accuracy assessment. Results revealed that built-up increased from 5.7% (52 km2) to 25.7% (233 km2) and 3.7% (60 km2) to 14.1% (228 km2) from 1990 to 2021 for Islamabad and Rawalpindi, respectively. Wherein the bare land decreased from 42.2% (382 km2) to 18.1% (164 km2) in Islamabad and 65.5% (1058 km2) to 32.1% (518 km2) in Rawalpindi. Vegetation showed an increment of 4.7% for Islamabad and 24.5% for Rawalpindi. Surface water bodies decreased in both study areas. Population growth showed a strong positive correlation with the built-up class and a strong negative correlation with the bare land class for both cities. The outcomes of this study may be helpful in policymaking for better planning and management of land use land cover and urban sprawl in the context of sustainable development goals.

Global population growth and scarce resources increase the competition for land use. Despite the fact that the impacts of climate change have been recognized, the conversion of LULC is still often neglected and threatens catchment hydrology. This is mostly seen in the developing world, where agriculture is the crucial source of their food security. The conversion of LULC has been jeopardizing water balance components and damaging ecosystem. This study demonstrates the application of SWAT+ in quantifying the impacts of LULC changes on the Guder catchment water balance. The impacts were quantified between 2003 and 2021, and the watershed experienced an increase in agriculture and settlement while forest, shrubland, and wetlands declined. The time-series-based performance of the SWAT + model shows the model is more restructured and capable of simulating streamflow compared to observed during calibration and validation. In this long-term evaluation, the model simulates changes in runoff of 56.5%, water yield of 65.2%, lateral flow of 21.6%, percolation of 46.2%, return flow of 76.4%, and ET of 0.2% between 2003 and 2013. Moreover, some attributes of the water balance have increased from 2013 to 2021, with runoff of 34.3%, water yield of 2.3%, ET of 4.5%, and lateral flow of 72.6%. However, as a result of increasing settlement, which reduces infiltration through interceptions and converts rainfall to runoff, percolation and return flow were decreased by 45.6% and 86.7%, respectively. Water yield and runoff show a linear relationship with changes in LULC, and the most sensitive land use changes that affect them are agriculture, forest, and settlements. The simulation results show a water balance deficit under the impacts of LULC changes in the third simulation. Furthermore, the increased surface of runoff has been limiting the amount of groundwater recharge into the soil and reducing return flow and percolation in the second simulation.

Understanding the hydrological impacts of land use and land cover (LULC) changes is significant for sustainable water resources management and planning. The Lake Victoria basin (LVB) has experienced extensive forest and grass degradation and agricultural land expansion under rapid socio-economic development and population growth in recent decades. However, the hydrological impacts of LULC changes for the whole LVB is still poorly documented. This study first investigated the LULC changing effects of LVB, focusing on its impacts on the annual and seasonal runoff and the hydrological drought based on a distributed hydrological modeling of the Soil and Water Assessment Tool (SWAT). SWAT model showed comparatively good applicability in seasonal runoff simulation of LVB, with the percent bias (PBIAS) kept within ± 20 % and the coefficient of determination (R2) over 0.6 at ten hydrological stations available over the calibration and validation phases. Generally, the annual runoff obtained a monthly increase of 1.5 mm under collective LULC changes. Moreover, the LULC effects presented considerable seasonal dependence. A largest runoff increase of approximately 4 mm was detected in short rainy season attributed to the combined surface runoff and groundwater increase. Insignificant runoff increase was observed in long rainy and dry seasons under the complementary effects of surface runoff increase and groundwater decrease. Additionally, the hydrological drought was generally aggravated with increased drought frequency and lengthened duration, particularly for the central western and eastern regions with massive conversion of forest to agricultural land. The findings provide importance implication for rational water resources management and drought disaster response for the LVB.

Land use and land cover change (LULC) and climate change are significant threats to the global environment. Assessing the causes of land-use change and its relationship with climate change is an essential issue in understanding processes that can help better human interaction with the environment. Therefore, this study aims to evaluate the effects of climate change on changing land use and land cover. The indicators used to achieve the mentioned goal are ((average minimum winter temperatures), number of days (≤ 0 °C), number of days (≤ − 10 °C), and 30-year Landsat satellite images)), CMIP5 (CanESM2) model application to predict temperature changes and the CA–MARKOV model is used to predict land use changes. The results indicated a direct relationship between the minimum winter temperatures and cultivation type change and land use in Urmia county. Also, the simulation of temperature changes showed that there occurs the highest (> 0.8) correlation between RCP4.5 scenarios and land use changes, which indicates a high probability of changes in the specified period (2018–2033). [ABSTRACT FROM AUTHOR]

Wildfires are key drivers of land use/land cover (LULC) dynamics by burning vegetation and affecting human infrastructure. On the contrary, LULC changes (LULCCs) may affect the fire regime by influencing vegetation type, burnable areas, fuel loads and continuity. This study investigates the relationship between LULCC and wildfires. We developed a methodology based on different indicators, which allowed us to quantitatively assess and better understand the transitions between LULC classes and burnt area (BA) in Europe in the last two decades (2000–2019). The assessment was performed for the entire European continent and, independently, for each of the five European countries most affected by wildfires: Portugal, Spain, France, Italy and Greece. The main results are the following: (i) LULCC analysis revealed a net loss in forests and arable land and a net gain in shrubs; (ii) most of the BA occurred in forests (42% for the whole of Europe), especially in coniferous forests; (iii) transitions from BA generally were to transitional woodland/shrub or, again, to BA. Overall, our results confirm the existence of a strong relationship between wildfires and LULCCs in Europe, which was quantified in the present study. These findings are of paramount importance in fire and environmental system management and ecology.

Groundwater resources are enormously affected by land use land cover (LULC) dynamics caused by increasing urbanisation, agricultural and household discharge as a result of global population growth. This study investigates the impact of decadal LULC changes in groundwater quality, human and ecological health from 2009 to 2021 in a diverse landscape, West Bengal, India. Using groundwater quality data from 479 wells in 2009 and 734 well in 2021, a recently proposed Water Pollution Index (WPI) was computed, and its geospatial distribution by a machine learning-based 'Empirical Bayesian Kriging' (EBK) tool manifested a decline in water quality since the number of excellent water category decreased from 30.5% to 28% and polluted water increased from 44% to 45%. ANOVA and Friedman tests revealed statistically significant differences (p < 0.0001) in year-wise water quality parameters as well as group comparisons for both years. Landsat 7 and 8 satellite images were used to classify the LULC types applying machine learning tools for both years, and were coupled with response surface methodology (RSM) for the first time, which revealed that the alteration of groundwater quality were attributed to LULC changes, e.g. WPI showed a positive correlation with built-up areas, village-vegetation cover, agricultural lands, and a negative correlation with surface water, barren lands, and forest cover. Expansion in built-up areas by 0.7%, and village-vegetation orchards by 2.3%, accompanied by a reduction in surface water coverage by 0.6%, and 2.4% in croplands caused a 1.5% drop in excellent water and 1% increase in polluted water category. However, ecological risks through the ecological risk index (ERI) exhibited a lower risk in 2021 attributed to reduced high-risk potential zones. This study highlights the potentiality in linking LULC and water quality changes using some advanced statistical tools like GIS and RSM for better management of water quality and landscape ecology. [Display omitted] • WPI indicated decreasing groundwater quality over a decade from 2009 to 2021. • LULC changes was analyzed using Landsat 7 and 8 satellite data through ArcGIS. • Applied Response Surface Methodology (RSM) for finding statistical WPI-LULC relation. • RSM-3D cross-interaction plot indicated substantial + ve and –ve WPI-LULC correlation. • Noticeable non-carcinogenic health risk prone zone but no significant ecological risks. [ABSTRACT FROM AUTHOR]

Understanding the response of headwater catchments to increasing anthropogenic influences is one of the key issues in hydrological and geomorphological research. Two headwater catchments with contrasting human impacts on the environment were chosen to determine changes in surface water chemistry and solute fluxes. In one catchment, 22 % of the forest area was cleared in 2013 and in the other, 75 % of the arable lands was converted to grassland and forest in the last 25 years. Atmospheric input and solute mass balance were analysed using homogeneity Pettitt test. It seems that in both areas, a very important factor affecting solute fluxes was most likely changes, or lack thereof, in soil erosion. In the partially clear-cut catchment, a small clear-cut area and adequate protection of the soil cover had little effect on the stream water chemistry, and the total solute mass balance remained unchanged during the study period. In this catchment, the more pronounced effect on solute fluxes was using de-icing salts in winter, which contributed to a 62 % increase in total solute flux (mainly by supplying Na+ and Cl−, but also Ca2+, Mg2+ and K+). In a catchment with a decrease in arable lands, there was a 55 % decrease in total solute mass balance (including mass balance of Ca2+, Mg2+, Na+, K+, NH 4 +, SO 4 −, NO 3 −, Cl−) in the stream likely associated with a decrease in soil erosion and fertilization. In both catchments there was a decrease in total monthly atmospheric input (especially in input of NH 4 +, SO 4 − and NO 3 −) of 53 % and 21 %, respectively, over the study period. To summarize, the road salting has increased the amount of transported solutes in the stream and deteriorated surface water chemistry, while the reduction of arable land area has reduced the amount of transported solutes in the stream and improved surface water quality. • We examine effect of human activity on solute fluxes in two contrasting catchments. • 22 % catchment clear-cut did not affect the total solute mass balance in stream. • 42 % catchment LULC changes caused 55 % decrease in solute mass balance in stream. • The use of de-icing salts increased TDS in stream by 62 %. [ABSTRACT FROM AUTHOR]

Climate variability, land use and land cover changes (LULCC) have a considerable impact on runoff–erosion processes. This study analyzed the relationships between climate variability and spatiotemporal LULCC on runoff–erosion processes in different scenarios of land use and land cover (LULC) for the Almas River basin, located in the Cerrado biome in Brazil. Landsat images from 1991, 2006, and 2017 were used to analyze changes and the LULC scenarios. Two simulations based on the Soil and Water Assessment Tool (SWAT) were compared: (1) default application using the standard model database (SWATd), and (2) application using remote sensing multiple gridded datasets (albedo and leaf area index) downloaded using the Google Earth Engine (SWATrs). In addition, the SWAT model was applied to analyze the impacts of streamflow and erosion in two hypothetical scenarios of LULC. The first scenario was the optimistic scenario (OS), which represents the sustainable use and preservation of natural vegetation, emphasizing the recovery of permanent preservation areas close to watercourses, hilltops, and mountains, based on the Brazilian forest code. The second scenario was the pessimistic scenario (PS), which presents increased deforestation and expansion of farming activities. The results of the LULC changes show that between 1991 and 2017, the area occupied by agriculture and livestock increased by 75.38%. These results confirmed an increase in the sugarcane plantation and the number of cattle in the basin. The SWAT results showed that the difference between the simulated streamflow for the PS was 26.42%, compared with the OS. The sediment yield average estimation in the PS was 0.035 ton/ha/year, whereas in the OS, it was 0.025 ton/ha/year (i.e., a decrease of 21.88%). The results demonstrated that the basin has a greater predisposition for increased streamflow and sediment yield due to the LULC changes. In addition, measures to contain the increase in agriculture should be analyzed by regional managers to reduce soil erosion in this biome. [ABSTRACT FROM AUTHOR]

This study was conducted to assess the quality of riparian zones of Zat basin of Morocco by using the QBR index, and to analyze land use changes over 30 years along the Zat River and its tributaries by using remote sensing and Geographic Information System. Five land use/land cover classes were identified: Forest, building area, water, bare soil, and agricultural land using Landsat images. Also, the QBR index was evaluated in 14 localities distributed along the Zat River and its tributaries from 2018-2019. For instance, the total forest area was reduced from 959.07 ha (15.35%) in 1990 to 890.41 ha (14.25%) and 713.25 ha (11.41%) in 2005 and 2020, respectively. Whereas agricultural land and building area classes increased with an estimated rate of change of 24.99% and 33.81% respectively over the last 30 years. Furthermore, our results indicate that 35.7% of the banks in the riparian zone are of very poor quality, 14.3% of poor quality, 28.6% of average quality and 21.4% of good quality. The finding demonstrates that the low QBR score obtained by some sampling localities especially downstream is the result of multiple anthropogenic interventions in riparian ecosystems, including forest plantations, land use for agriculture, and road infrastructures. [ABSTRACT FROM AUTHOR]

Land degradation is a problem which affects large areas of land and the ecological services provided by coastal wetlands. Coastal ecosystems offer significant benefits for humans and the environment, including services like coastal blue carbon sequestration (CBCS), the economic value of which merits further study. The aim of this paper is to estimate the economic value of coastal blue carbon in Moulay Bousselham lagoon (MBL), Morocco, by analysing the changes in carbon storage that have taken place over 49 years in response to changes in land use and cover (LULC). To achieve this, high resolution orthophotos were used to map LULC changes and investigate the flow of cumulative LULC transformation in the MBL over the period 1971-2020. InVEST was then used to model the quantity and economic value of the CBCS service provided by coastal ecosystems. The results indicate that there were 94 types of LULC transformation over the period 1971-2020, most of them involving the conversion of wet lawn and juncus meadow into cultivated land and the extension of non-wetland areas, especially coastal dunes and built-up areas, at the expense of wetland habitats. These conversions have to some extent affected the capacity of coastal habitats to sequester and store CO2, which reached 1.47 Mt C of CBCS in 2020. In addition, the monetary value of CBCS was subject to gains of between US$ 371,053 and 3,803,295 per year, and losses of between US$ 10,127 and 103,806 per year, according to recent estimates by the European Emission Allowances (EUA) social cost of carbon (SCC) and CO2. This study reveals that revenues from CBCS service can accelerate the implementation of wetland rehabilitation strategies, which have a positive impact on climate regulation. [ABSTRACT FROM AUTHOR]

Increase demand of electricity has driven the exploration of Hulu Terengganu hydroelectricity dam as an option to generate electric power supply. Therefore, as a way to monitor the landscape changes, spectral indices were used to study on the spatial-temporal changes over the Hulu Terengganu catchment area. Spectral indices technique was applied on satellite images which acquired on three different years to describe the changes before the construction phase, during the construction phase and post-construction phase. Satellite images used in this study are SPOT-5 and Landsat 7 for year 2006, SPOT-5 and Landsat 8 for year 2014 and Spot-7 and Sentinel 2 for year 2018. Alteration of the land use and land cover has recorded degradation of the forest area by -5.53 % during the dam construction phase (2014) and -8.35 % during post-construction phase (2018). It also found that water body has remarkable change of 10,141% increase from 2014 to 2018. The result from this study would be useful as an overview for future planning, decision making and dam management activity related to the Hulu Terengganu hydroelectric dam operation.

Evaluating how pollutant loads react to changes in land use/land cover (LULC) is a challenging task due to the intricate relationships among the many elements within a watershed. However, the difficulty in connecting LULC change and nonpoint source (NPS) pollution loads to streams may be lessened by combining hydrological modeling with geospatial tools and multivariate statistics. The objective of this study was to investigate the long-term effects of LULC change on NPS pollution loads in a highly human-dominated catchment, in central Ethiopia. In the study, hydrologic modeling was used to estimate the NPS parameters from multispectral Landsat images, and multivariate statistical techniques were then used to extract major LULC types that explain the variances of NPS loads between 1981 and 2020. The results demonstrated that there were human-induced LULC changes in the area, as the built-up and agricultural landscapes are rising (186.4% and 5.8%, respectively), and shrub and forest lands are decreasing (67.1% and 41%, respectively). As a result of these changes, the concentrations of nitrate (NO 3 ), total P, total N, organic N, and organic P loads were increased by 69.41, 19.83, 18.45, 18.88, and 24.05%, respectively. Reductions in natural vegetation, as well as agriculture intensification, are the major contributors to the NPS pollutant losses to surface water sources. The result also revealed that pollution nutrients are strongly related to deforestation and agricultural land expansion. Proper adaptation strategies should be implemented to minimize the negative impact of LULC changes in the area., Competing Interests: The authors declare there is no conflict., (© 2024 The Authors This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY 4.0), which permits copying, adaptation and redistribution, provided the original work is properly cited (http://creativecommons.org/licenses/by/4.0/).)