Bare Land Research Articles

Application of a Multi-Layer Perceptron and Markov Chain Analysis-Based Hybrid Approach for Predicting and Monitoring LULCC Patterns Using Random Forest Classification in Jhelum District, Punjab, Pakistan.

Land-use and land-cover change (LULCC) is a critical environmental issue that has significant effects on biodiversity, ecosystem services, and climate change. This study examines the land-use and land-cover (LULC) spatiotemporal dynamics across a three-decade period (1998-2023) in a district area. In order to forecast the LULCC patterns, this study suggests a hybrid strategy that combines the random forest method with multi-layer perceptron (MLP) and Markov chain analysis. To predict the dynamics of LULC changes for the year 2035, a hybrid technique based on multi-layer perceptron and Markov chain model analysis (MLP-MCA) was employed. The area of developed land has increased significantly, while the amount of bare land, vegetation, and forest cover have all decreased. This is because the principal land types have changed due to population growth and economic expansion. This study also discovered that between 1998 and 2023, the built-up area increased by 468 km2 as a result of the replacement of natural resources. It is estimated that 25.04% of the study area's urbanization will increase by 2035. The performance of the model was confirmed with an overall accuracy of 90% and a kappa coefficient of around 0.89. It is important to use advanced predictive models to guide sustainable urban development strategies. The model provides valuable insights for policymakers, land managers, and researchers to support sustainable land-use planning, conservation efforts, and climate change mitigation strategies.

Spatiotemporal changes in LULC and associated impact on urban Heat Islands over Pakistan using geospatial techniques

Urban Heat Islands arise when the natural land cover changes with dense concentrations of pavement, buildings, roads, and other surfaces that absorb and preserve heat. The current study aimed to assess Land Use Land Cover(LULC) changes and associated impact on Urban Heat Island (UHI) from 2000 to 2020 using Geospatial technologies for four metropolitan cities (Islamabad, Lahore, Multan and Muzaffarabad) of Pakistan. A Supervised Classification algorithm was performed on satellite imageries using ArcGIS software for analyzing LULC changes. The study areas were classified into 4 classes such as built-up, barren land, vegetation, and water bodies. Thermal bands of Landsat 4–5 and 8 were used for retrieved Land Surface Temperature (LST) and UHI. The findings of this study indicate that the urban area in all four districts i.e. Islamabad, Lahore, Multan and Muzaffarabad has increased by 21.3 %, 20.9 %, 6.1 % and 15 % respectively during 2000–2020. The built-up and barren land revealed the highest recorded LST, while vegetation and water bodies showed the lowest measured LST values. From 2000 to 2020, the annual maximum LST in Islamabad rose by 1.1 °C, Lahore by 2.1 °C, and Multan and Muzaffarabad by 1.9 °C and 1.5 °C. The expansion of built-up areas and the reduction in vegetation contribute to a favorable contribution to UHI. The study's findings showed that appropriate action plans are required to manage urban heat and promote sustainable city development.

Evaluating socio-hydrological stress through potential stormwater harvesting sites using multi-criteria analysis in Mumbai, India

Estimating stormwater harvesting (SWH) is a significant characteristic of enhancing regional water obtainability and thereby preserving water resources. The foremost aim of this study was to approximate suitable SWH locations in Mumbai using several physical and geomorphic parameters by employing the Geographical Information System (GIS) based Analytical Hierarchy Process (AHP) method. Several observed and remotely sensed datasets were used to compute SWH after assigning the share of influence at GIS platform. Numerous physical attributes along with geomorphic features are taken into consideration and further reclassified and allocated ranks to produce the SWH map in Mumbai. The study indicates most suitable portion for SWH is associated with northwestern side of Mumbai along with barren land and vegetation cover of around 226 sq. km area. However, highly dense urban areas (182.5 sq. km) in central Mumbai experienced with low suitable SWH zone. Additionally, LULC-wise investigation exhibited that barren and wetlands are the most suitable part for SWH, averaging 62.7 sq.km, however, nearly coastal areas including central Mumbai, and some open urban spaces are also potentially suitable for SWH. Moreover, flood probability-wise SWH site demonstrates maximum suitability near the upper parts of coastal Mumbai (223.3 sq.km), while 82.9 sq.km area witnessed flood possibility. High-resolution Google Earth images were used to overlap the outcome of SWH in Mumbai. Moreover, the SWH sites were further cross-correlated with regional flood susceptibility, which exposed extreme north and northeastern parts of Mumbai and is eventually essential to yield SWH sites to diminish flood hazards and substantial water availability.

The influence of the location of arable land incorporating its roughness on the optimal time when the land reaches its mean diurnal blue-sky albedo value

This work is a supplement the article “Influence of arable land location incorporating its roughness on blue-sky albedo variation” [J Quant Spectrosc Radiat Transf. 296 (2023) 108,440]. It quantifies the influence of the location (expressed by latitude) of bare arable land on a global scale and its roughness on the optimal time (To) of land observation with acceptable errors to determine its mean diurnal blue-sky albedo (αd). The article also discusses how the risk of making these errors changes with the change in land latitude. The study focuses on the influence of the location of one soil unit, Cambisol, common to all latitudes in both hemispheres. This is the same unit whose albedo variation was analyzed in the supplementary article mentioned above.

In situ bioaccumulation of metals by Prosopis juliflora and its detoxification potential at the metal contaminated sites

Heavy metals emanate from diverse anthropogenic activities and the top soil in the vicinity of these activities acts as an immediate sink and facilitates diffusion of heavy metals into the food chain. In the semi-arid plains of India, Prosopis juliflora is the most common and dominant weed along the motorways and barren lands including industrial environs. This investigation hypothesizes the adaptive nature of Prosopis juliflora in the metal enriched soils and attempts to understand its hyper-accumulating potential of metals besides bioconversion/detoxification capability. Prosopis juliflora samples (root, stem, leaves, and pods) from 100 sites in the environs of anthropogenic activities (vehicular emissions and industrial operations) were analyzed for heavy metal concentrations (Cu, Fe, Cr, Cd, Ni, Pb). Prosopis juliflora accumulate metals at the rate of 0.138 mg/kg/day DW for Copper (Cu), Fe: 0.142 mg/kg/day DW, Cr: 0.114 mg/kg/day DW, Ni: 0.048 mg/kg/day DW, Pb: 0.052 mg/kg/day DW, Cd: 0.009 mg/kg/day DW. Furthermore, X-ray Photoelectron Spectroscopy (XPS) metal oxidation state analysis revealed that in the pods of Prosopis juliflora heavy metals (Fe, Cr, Pb) largely existed in non-toxic form (toxic:non-toxic - 3:6), while in the under canopy soil, metals predominantly existed in toxic form (toxic:non-toxic - 7:2); conclusively XPS results ascertains the heavy metal bioconversion/detoxification potential of the plant. These findings suggest that presence of Prosopis juliflora coppice in the barren landscapes across the transportation corridors and metal based industrial zones may ideally favor phyto-remediation of heavy metals.

Tobacco as a promising crop for low-carbon biorefinery

Energy crops play a vital role in meeting future energy and chemical demands while addressing climate change. However, the idealization of low-carbon workflows and careful consideration of cost-benefit equations are crucial for their more sustainable implementation. Here, we propose tobacco as a promising energy crop because of its exceptional water solubility, mainly attributed to a high proportion of water-soluble carbohydrates and nitrogen, less lignocellulose, and the presence of acids. We then designed a strategy that maximizes biomass conversion into bio-based products while minimizing energy and material inputs. By autoclaving tobacco leaves in water, we obtained a nutrient-rich medium capable of supporting the growth of microorganisms and the production of bioproducts without the need for extensive pretreatment, hydrolysis, or additional supplements. Additionally, cultivating tobacco on barren lands can generate sufficient biomass to produce approximately 573 billion gallons of ethanol per year. This approach also leads to a reduction of greenhouse gas emissions by approximately 76% compared to traditional corn stover during biorefinery processes. Therefore, our study presents a novel and direct strategy that could significantly contribute to the goal of reducing carbon emissions and global sustainable development compared to traditional methods.

Erosive Rainfall Thresholds Identification Using Statistical Approaches in a Karst Yellow Soil Mountain Erosion-Prone Region in Southwest China

Karst yellow soil is one of the most important cultivated soils in southwest China. At present, only a few studies have dealt with rainfall erosivity and erosive rainfall thresholds in the karst yellow soil region. This paper utilizes statistical methods to identify erosive rainfall thresholds and slope erosion-prone areas in the Qianzhong region. This analysis is based on long-term experimental data from 10 experimental stations and 69 experimental plots within the region in 2006 to 2022. The findings show the following: The rainfall amount threshold was 12.66 mm for woodland plots, 10.57 mm for grassland plots, 9.94 mm for farmland plots, and 8.93 mm for fallow plots. Soil and water conservation measures in forestry and grassland effectively increase the rainfall amount thresholds. Compared to farmland, the rainfall threshold increased by 27.32% for woodland and 6.32% for grassland. Bare land and farmland are erosion-prone areas in the karst yellow soil region. The erosive rainfall thresholds for farmland plots with slopes of 13°, 15°, 20°, 23°, and 25° were 10.41 mm, 10.28 mm, 9.66 mm, 9.52 mm, and 9.15 mm, respectively. With the increase in the 13–25° slope gradient of farmland, the initial rainfall required for runoff generation leads to a reduction. The wrong selection indices (WSI) of all landcover plots were less than 10%, and the efficiency indices (EFF) were between 80.43% and 90.25%. The relative error index (REI) of the erosive rainfall thresholds for all landcover runoff plots was less than 0.50%, very close to 0, indicating that these thresholds have small errors and high accuracy. This study gained a better understanding of natural rainfall-induced erosion characteristics in the study area, determined rainfall thresholds for distinguishing erosive rainfall events from non-erosive across different landcover types, and reduced the workload of calculating rainfall erosivity while enhancing the accuracy of soil erosion forecasting and simulation in the karst mountain yellow soil area.

Pendampingan Tamanisasi: Upaya Meningkatkan Daya Tarik Bukit Tinatar sebagai Destinasi Wisata Alam

Tinatar Hill is a natural destination located in Sri Mulyo Village, Piyungan District, Bantul Regency, currently requiring management to increase its natural charm to attract more visitors. Pengelola Wisata Bukit Tinatar has synergized with the local community and the Srimulyo Village Government to make various breakthroughs to make Bukit Tinatar a natural tourist destination that is popular with tourists. However, the land on Tinatar Hill is less fertile, so during the dry season, this tourist area looks very barren and hot. Pengelola Wisata has reforested several plants that dry out and die during the dry season. Pengelola Wisata Bukit Tinatar also continues to improve by creating a main park that tourists can find before entering the hill area. However, Pengelola Wisata still encounter obstacles regarding the types of plants that suit the conditions of the barren land and their maintenance. Based on this background, this service activity aims to increase Pengelola Wisata' capacity to create the main park on Tinatar Hill through outreach and mentoring activities. Service is carried out in the form of counseling activities, assistance with ornamental plants, and assistance with garden maintenance. The result of this dedication is the creation of the main park and the Pengelola Wisata' ability to maintain the park, but in the long term, there is still a need for high awareness of caring for the park.

Land Surface Temperature Anomalies as Indicators of Urban Land Cover Change—A Study of Two Indian Cities

Rapid urbanisation over the years has led to the loss of natural land cover, thereby affecting Land Surface Temperature (LST) distribution in urban areas. This study aims to analyse LST anomalies (calculated as the deviation from the normal) over selected Indian cities and check if critical land cover changes can be identified. LST from Landsat Thermal Infrared (TIR) images acquired in March, April and May from 1988 to 2020 were used to estimate LST anomalies. Positive LST anomalies were observed mainly over barren and impervious areas; however, some areas showed a negative anomaly where the barren lands were converted to vegetated areas. The study has demonstrated that while some developed areas exhibit a positive anomaly indicative of significant changes or development, there are instances where the conversion of barren land to developed (i.e. built up) areas has resulted in a negative anomaly. Developed areas that are closer to the water creek or mangroves were associated with lower anomaly values indicating the cooling effect of the water body and vegetation. Conversely, the core urban areas generally exhibited higher LST values with positive anomalies indicating a warming effect. These findings can be used by city planners to identify hotspot areas and develop more effective strategies and policies to address the challenges of urban heat. They also highlight the regions that require infrastructural resources and policy changes to reduce the temperature.

Spatiotemporal Variations in Urban Wetlands in Kazakhstan: A Case of the Taldykol Lake System in Astana City

Acquiring a comprehensive understanding of the spatiotemporal dynamics of urban wetlands in Kazakhstan is crucial for their effective preservation and sustainable urban development. Our findings identify past and present Land Use Land Cover (LULC) in the capital city, providing policymakers with scientific evidence for improved management. Using remote sensing and Geographic Information System (GIS) techniques, this study examines the spatiotemporal changes in the Taldykol catchment area during the rapid development of Astana. In 1992, over 90% of the catchment area was grassland and vegetation. By 2022, 30% of the area became barren land. Urban areas increased by 127%, and water areas decreased by 24%. The most significant changes occurred in lakes Taldykol and Kishi Taldykol, whose areas shrank by 91% and 54%, respectively. The near-disappearance of the Taldykol wetlands is likely to contribute to rising land surface temperatures (LST), decreased natural flood control capacity, reduced biodiversity, and diminished recreational opportunities. The fate of Taldykol lakes underscores the urgent need to raise public awareness about the role of wetlands in Kazakhstan’s ecosystems and take action to preserve urban wetlands.

LUCC-induced dust aerosol change increase surface and reduce atmospheric direct radiative forcing in Northern China

Land use and land cover change (LUCC) can alter surface properties, such as albedo, roughness, and vegetation coverage, directly affecting dust emissions and aerosol concentrations, leading to variations in direct radiative forcing (DRF) of dust aerosols and consequently impacting the climate. This study utilized the Weather Research and Forecasting model with Chemistry (WRF-Chem) to quantify the impact of LUCC in northern China from 2000 to 2020 on dust aerosol DRF. Results indicated that LUCC's influence on shortwave radiative forcing of dust was significantly greater than its influence on longwave radiative forcing and exhibited obvious seasonal variations. Overall, LUCC can cause net direct radiative forcing to increase by 5.3 W m−2 at the surface and decrease by 7.8 W m−2 in the atmosphere. Different types of LUCC transformation showed distinct impacts on dust aerosol DRF, with the conversion from sparse vegetation to barren land had the most significant effect on net radiative intensity, resulting in a decrease of 8.1 W m−2 at the surface, an increase of 12.2 W m−2 in the atmosphere, and an increase of 4.1 W m−2 at the top of the atmosphere. Conversely, the conversion from barren land to sparse vegetation led to surface cooling and atmospheric warming. These findings are of great significance for enhancing our knowledge of the effects of LUCC on the radiative balance of dust aerosols.

Soil Quality Assessment and Influencing Factors of Different Land Use Types in Red Bed Desertification Regions: A Case Study of Nanxiong, China

Soil environmental issues in the red bed region are increasingly conspicuous, underscoring the critical importance of assessing soil quality for the region’s sustainable development and ecosystem security. This study examines six distinct land use types of soils—agricultural land (AL), woodland (WL), shrubland (SL), grassland (GL), bare rock land (BRL), and red bed erosion land (REL)—in the Nanxiong Basin of northern Guangdong Province. This area typifies red bed desertification in South China. Principal component analysis (PCA) was employed to establish a minimum data set (MDS) for calculating the soil quality index (SQI), evaluating soil quality, analyzing influencing factors, and providing suggestions for ecological restoration in desertification areas. The study findings indicate that a minimal data set comprising soil organic matter (SOM), pH, available phosphorus (AP), exchangeable calcium (Ca2+), and available copper (A-Cu) is most suitable for evaluating soil quality in the red bed desertification areas of the humid region in South China. Additionally, we emphasize that exchangeable salt ions and available trace elements should be pivotal considerations in assessing soil quality within desertification areas. Regarding comprehensive soil quality indicators across various land use types, the red bed erosion soils exhibited the lowest quality, followed by those in bare rock areas and forest land. Within the minimal data set, Ca2+ and pH contributed the most to overall soil quality, underscoring the significance of parent rock mineral composition in the red bed desertification areas. Moreover, the combined effects of SOM, A-Cu, and AP on soil quality indicate that anthropogenic land management and use, including fertilization methods and vegetation types, are crucial factors influencing soil quality. Our research holds significant implications for the scientific assessment, application, and enhancement of soil quality in desertification areas.

Prediction of Land Use and Habitat Quality in Harbin City Based on the PLUS- InVEST Model

Analyzing the spatiotemporal evolution of urban land use and habitat quality can reveal the correlation between land use and habitat quality, aiding in rational urban land policies and high-quality ecological environment development. This study was based on land use transition matrices and an Intensity-Migration （IM） model to analyze the changes in land use in Harbin from 2000 to 2020. It combined the PLUS model to explore the driving factors of land use expansion for various land types and predicted land use scenarios for 2030 under natural development, ecological protection, farmland protection, and urban development scenarios. Finally, the InVEST model was used to complete the habitat quality analysis. The results indicated： ① The dominant land use types in Harbin were cropland, forest land, and grassland. From 2000 to 2020, there was a significant tendency of conversion into grassland, cropland, forest land, and artificial surfaces, with noticeable changes in land use intensity. Water bodies, bare land, and wetland types showed less conversion and tended to be restrictive. ② Elevation was the primary factor influencing the expansion of grassland, cropland, forest land, bare land, wetland, and water bodies. Socioeconomic factors were the main factor affecting the expansion of artificial surfaces. ③ Simulation of land use types in Harbin for 2030 under the four scenarios showed an increase in forest land area and a decrease in grassland area, with insignificant changes in wetland, water bodies, and bare land areas. Except for in the ecological protection scenario, the area of artificial surfaces increased, whereas cropland decreased. ④ Overall, habitat quality in Harbin improved from 2000 to 2020. ⑤ In 2030, the spatial pattern of habitat quality in Harbin remained consistent across all scenarios, showing an overall improvement in habitat quality. Under the ecological protection scenario, areas with low and medium habitat quality decreased, whereas areas with higher habitat quality increased, indicating a relatively significant improvement in habitat quality. The research results provide a scientific basis and insights for the development of ecological civilization and urban planning and construction in Harbin.

Changes in Soil Organic Carbon Density and Its Response to Climate Change and Human Activities Before and After the Grain for Green Project on the Loess Plateau

Accurately assessing the changes in soil organic carbon storage （SOCS） before and after the Grain for Green Project （GFG） in the Loess Plateau （LP） and exploring the relationship between its spatial and temporal distribution and the influencing factors were important references for the development of regional recycling as well as the formulation of ecological protection policies. Based on the data of climate, human activities, and SOCD in the surface （0-20 cm） and deep （0-100 cm） soil before and after GFG in the LP from 2001 to 2020, we investigated the changes in SOCD at different spatial and temporal scales by using the methods of trend analysis, the kriging method, and variance partitioning analysis. The results showed that： ① Before and after the GFG, the surface SOCS of the whole region increased by 8 338.7×104 t； the deep SOCS increased by 1 160.02×104 t. ② In each bioclimatic subregion, the whole-region average SOCD of Ⅰ （Semi-Humid Forest Region）, Ⅱ （Semi-Humid Semi-Arid Forest and Grassland Region）, and Ⅲ （Semi-Arid Typical Grassland Region） showed a significant increasing trend, with a decreasing trend in Ⅳ （arid semi-arid desert grassland area） and Ⅴ （arid desert area）. ③ The average surface SOCS increase in different ecosystems was ranked as follows： cropland > grassland > woodland > shrubs > bare land and sparse vegetation. The deep soil increase was ranked as follows： grassland > cropland > woodland > shrubs > bare land and sparse vegetation. ④ Climate factors were the most important driving factors for changes in SOCD； the annual average temperature and precipitation were significantly positively correlated with changes in SOCD. The results of the study could provide data support for regional ecological management and land use policy formulation to promote high quality development of the ecological environment in the LP.

Assessing tropical cyclone impacts in coastal Bangladesh: A change detection analysis on cyclone Bulbul using geospatial analysis and remote sensing techniques

The coastal regions of Bangladesh are highly susceptible to the impacts of tropical cyclones, which frequently pose substantial challenges for disaster management. This research aimed to analyze the immediate consequences of significant catastrophic disasters imposed on coastal regions using geospatial techniques. Cloud-free satellite images and a support vector machine learning algorithm were utilized to examine the outcomes of Land Use and Land Cover (LULC) in the pre- and post-cyclone phase for assessing disaster impact. This study found that after the cyclone Bulbul, 45.08 km2 of land features were changed. It also showed agriculture, bare land, dense vegetation, and settlement areas have decreased by about 4.75 km2, 5.55 km2, 4.56 km2, and 7.72 km2, respectively. Instead, the body of water grew at a terrible rate of 22.49 km2 in areas turned into water body areas. Cyclone made a considerable impact by increasing the waterbody in this study area by flooding, mainly the southern portion, due to the changing process of land characteristics, which increases (waterbody) and reduces (agricultural, dense vegetation, barren land, settlement areas). The accuracy of the analysis was supported by the kappa coefficient. The results underscore the vulnerability of the coastal region and emphasize the need for effective post-cyclone recovery strategies. The study hamper valuable insights into the dynamic changes in the landscape following a cyclone, shedding light on the socio-economic and environmental implications. Further research is recommended to explore the long-term impacts of cyclones on coastal ecosystems and communities, considering the changing climate patterns.

Inventorization of Spring Water Resources in Mid Hills of Himachal Pradesh, India

The study on spring inventory was conducted in the mid hills of Himachal Pradesh, India where 43 springs were inventoried in the Beas catchment area. Hydrogeological characteristics, such as geology, slope, aspect, elevation, rock and soil distribution, landuse, geomorphology, and spring discharge were utilized to access the condition of springs in the study area. The study showed that 40.12% of the springs have seen a drop in water flow and compared to the previous times, the water flow has increased in 4.85% of the springs. A total of 56% of spring is located in the forest, 32% in Agriculture land, 3% in grassland, 6% in Shrubland, 2% in built up area, 1% in barren land. 65% are depression springs, 28% are fracture springs, and 7% are contact springs. 2.32% of the spring sources had discharge rate <0.05 Lmin-1. 79.06% of the springs have average discharge rate of 1-10 Lmin-1. Rest of the 11.60% of the springs have discharge rate ranged from 10-25 Lmin-1. Most of the springs are fed by annual precipitation and those located near the Beas valley are supported by river water course.

Assessment of growth, and ion uptake of plant species, Conocarpus erectus and Dodonaea viscosa, on industrial solid waste

Present study assessed the growth of two plant species and ion uptake by them grown on different proportion of industrial solid waste and garden soil. The industrial waste having high concentration of chemicals were used with garden soil at different proportion i.e. 0% (T0), 5% (T1), 10% (T2), 15% (T3) and 20% (T4). Two species namely Conocarpus erectus (alien plant) and Dodonaea viscosa (indigenous) were used as test plants in pot study. Different parameters including growth, physiology, and anatomy of plants and concentration of cations (Na+, K+, Ca2+, and Mg2+) in the plant shoot and root were measured at different time duration (initial, 1st, 2nd, 3rd and 4th month). The key objective of the study was to use these plants to establish their plantations on the barren lands where industrial solid wastes were being disposed of. C. erectus showed better growth than D. viscosa, as well as more uptake of ions. A significant increase in plant growth was observed in fourth month in T1, where plant height reached 24.5% and 46% for C. erectus and D. viscosa, respectively. At harvest, in C. erectus, no significant difference in the fresh (65–78 g) and dry weight (24–30 g) of the shoot was observed across treatments compared to the control. In D. viscosa, at the time of harvest, the fresh and dry weights of the root and shoot showed a strong, significantly decreasing pattern across T1, T2, and T3, leading to the death of the plant at T3 and T4. Further, optimum ratio of waste soil to garden soil was found as 10:90 and 20:80 to establish the plantations of D. viscosa and C. erectus, respectively in areas where such solid waste from industries are disposed. Findings can be used for the restoration of such solid waste for the sustainable management of industrial areas and their associated ecosystems.

Analysis of Land Use and Land Cover Changes and Trends in Fantalle Range Land, East Shewa Zone, Oromia Regional State, Ethiopia

This study was conducted in Fantalle Range lands in East Shewa zone of, Oromia Region, Ethiopia, to assess land use land cover changes, trends, drivers and their socioeconomics. Household surveys were conducted through simple random sampling to collect qualitative data. Qualitative data are used to investigate the causes and effects of land use and land cover changes. SPSS software (version 20) was used for data analysis, and descriptive research methods were adopted. Additionally, map processing was done using ERDAS Imagine (version 9.1) and ArcGIS (version 10.1). The land use land cover classification activity was started by obtaining Landsat images of 1972, 1990, 2000 and 2020 at different intervals from the Earth Explorer (USGS) from the Landsat 4, Landsat 5, Landsat 7 and Landsat 8, respectively. Land use land cover change (LULCC) maps are generated based on year classification. Range land, agricultural land, woody vegetation, bare land and settlement are the five main LULCC categories generated from satellite data. The findings show that in the presence of LULCC, agricultural land, settlements and bare land expand significantly, while range land and woodland show a decreasing trend. The classification results of the 1972 image show that rangeland/grazing land accounts for the largest proportion of the land in this area, accounting for 31.6%. In addition, due to various factors, the number of livestock owned in pastoral areas is also decreasing. The main cause of changes in livestock types is drought, which can cause different impacts, such as feed and water shortages and health problems. Therefore, intervention in land use manipulation is needed to maintain ecosystems and natural resources. Furthermore, rangeland policies should be developed to maintain pastoral and pastoral systems.

Capturing Snowmelt Runoff Onset Date under Different Land Cover Types Using Synthetic Aperture Radar: Case Study of Sierra Nevada Mountains, USA

Snow plays a crucial role in the global water and energy cycles, and its melting process can have a series of impacts on hydrological or climatic systems. Accurately capturing the timing of snowmelt runoff is essential for the utilization of snow resources and the early warning of snow-related disasters. A synthetic aperture radar (SAR) offers an effective means for capturing snowmelt runoff onset dates (RODs) over large areas, but its accuracy under different land cover types remains unclear. This study focuses on the Sierra Nevada Mountains and surrounding areas in the western United States. Using a total of 3117 Sentinel-1 images from 2017 to 2023, we extracted the annual ROD based on the Google Earth Engine (GEE) platform. The satellite extraction results were validated using the ROD derived from the snow water equivalent (SWE) data from 125 stations within the study area. The mean absolute errors (MAEs) for the four land cover types—tree cover, shrubland, grassland, and bare land—are 24, 18, 18, and 16 d, respectively. It indicates that vegetation significantly influences the accuracy of the ROD captured from Sentinel-1 data. Furthermore, we analyze the variation trends in the ROD from 2017 to 2023. The average ROD captured by the stations shows an advancing trend under different land cover types, while that derived from Sentinel-1 data only exhibits an advancing trend in bare land areas. It indicates that vegetation leads to a delayed trend in the ROD captured by using Sentinel-1 data, opposite to the results from the stations. Meanwhile, the variation trends of the average ROD captured by both methods are not significant (p > 0.05) due to the impact of the extreme snowfall in 2023. Finally, we analyze the influence of the SWE on RODs under different land cover types. A significant correlation (p < 0.05) is observed between the SWE and ROD captured from both stations and Sentinel-1 data. An increase in the SWE causes a delay in the ROD, with a greater delay rate in vegetated areas. These findings will provide vital reference for the accurate acquisition of the ROD and water resources management in the study area.

Deep learning-based modeling of land use/land cover changes impact on land surface temperature in Greater Amman Municipality, Jordan (1980–2030)

Modeling the impacts of Land Use/Land Cover changes (LULCC) on Land Surface Temperature (LST) is crucial in understanding and managing urban heat islands, climate change, energy consumption, human health, and ecosystem dynamics. This study aimed to model past, present, and future LULCC on Land Surface Temperatures in the Greater Amman Municipality (GAM) in Jordan between 1980 and 2030. A set of maps for land cover, LST, Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), and topography was integrated into the Cellular Automata-Artificial Neural Network (CA-ANN) and the Long-Short-Term Model (LSTM) models to predict the LULC and LST for 2030. The results showed an expansion of urban areas in GAM from 54.13 km2 (6.6%) in 1980 to 374.1 km2 (45.3%) in 2023. However, agricultural areas decreased from 152.13 km2 (18.5%) in 1980 to 140.38 km2 (17%) in 2023, while barren lands decreased from 54.44 km2 (6.6%) in 1980 to 34.71 km2 (4.22%) in 2023. Forested areas declined from 4.58 km2 (0.56%) in 1980 to 4.35 km2 (0.53%) in 2023. Rangelands/ sparsely vegetated areas declined from 557 km2 (67.7%) in 1980 to 270.71 km2 (32.9%) in 2023. The results of modeling LST showed an increase in average LST for all land cover types, with the most significant increases evident within urban areas and Rangelands/Sparsely vegetated areas. The slightest increase in LST was within forested areas as the average LST increased from 28.42 °C in 1980 to 34.16 °C in 2023. The forecasts for the future showed a continuous increase in LST values in all land cover types. These findings highlight the impact of land surface dynamics and their impact on increasing land surface temperature, which urges the adoption of more sustainable planning policies for more livable and thermally comfortable cities.