Comprehending drivers of land use land cover change from 1999 to 2021 in the Pithoragarh District,Kumaon Himalaya,Uttarakhand,India

The Himalayan region has been experiencing stark impacts of climate change,demographic and livelihood pattern changes.The analysis of land use and land cover(LULC)change provides insights into the shifts in spatial and temporal patterns of landscape.These changes are the combined effects of anthropogenic and natural/climatic factors.The present study attempts to monitor and comprehend the main drivers behind LULC changes(1999-2021)in the Himalayan region of Pithoragarh district,Uttarakhand.Pithoragarh district is a border district,remotely located in the north-east region of Uttarakhand,India.The study draws upon primary and secondary data sources.A total of 400 household surveys and five group discussions from 38 villages were conducted randomly to understand the climate perception of the local community and the drivers of change.Satellite imagery,CRU(Climatic Research Unit)climate data and climate perception data from the field have been used to comprehensively comprehend,analyze,and discuss the trends and reasons for LULC change.GIS and remote sensing techniques were used to construct LULC maps.This multifaceted approach ensures comprehensive and corroborated information.Five classes were identified and formed viz-cultivation,barren,settlement,snow,and vegetation.Results show that vegetation and builtup have increased whereas cultivation,barren land,and snow cover have decreased.The study further aims to elucidate the causes behind LULC changes in the spatially heterogeneous region,distinguishing between those attributed to human activities,climate shifts,and the interconnected impacts of both.The study provides a comprehensive picture of the study area and delivers a targeted understanding of local drivers and their potential remedies by offering a foundation for formulating sustainable adaptation policies in the region.

Spatiotemporal characteristics and driving mechanisms of land use/land cover(LULC)changes in the Jinghe River Basin,China

Understanding the trajectories and driving mechanisms behind land use/land cover(LULC)changes is essential for effective watershed planning and management.This study quantified the net change,exchange,total change,and transfer rate of LULC in the Jinghe River Basin(JRB),China using LULC data from 2000 to 2020.Through trajectory analysis,knowledge maps,chord diagrams,and standard deviation ellipse method,we examined the spatiotemporal characteristics of LULC changes.We further established an index system encompassing natural factors(digital elevation model(DEM),slope,aspect,and curvature),socio-economic factors(gross domestic product(GDP)and population),and accessibility factors(distance from railways,distance from highways,distance from water,and distance from residents)to investigate the driving mechanisms of LULC changes using factor detector and interaction detector in the geographical detector(Geodetector).The key findings indicate that from 2000 to 2020,the JRB experienced significant LULC changes,particularly for farmland,forest,and grassland.During the study period,LULC change trajectories were categorized into stable,early-stage,late-stage,repeated,and continuous change types.Besides the stable change type,the late-stage change type predominated the LULC change trajectories,comprising 83.31% of the total change area.The period 2010-2020 witnessed more active LULC changes compared to the period 2000-2010.The LULC changes exhibited a discrete spatial expansion trend during 2000-2020,predominantly extending from southeast to northwest of the JRB.Influential driving factors on LULC changes included slope,GDP,and distance from highways.The interaction detection results imply either bilinear or nonlinear enhancement for any two driving factors impacting the LULC changes from 2000 to 2020.This comprehensive understanding of the spatiotemporal characteristics and driving mechanisms of LULC changes offers valuable insights for the planning and sustainable management of LULC in the JRB.

Land use and cover change and influencing factor analysis in the Shiyang River Basin,China

Land use and cover change(LUCC)is the most direct manifestation of the interaction between anthropological activities and the natural environment on Earth's surface,with significant impacts on the environment and social economy.Rapid economic development and climate change have resulted in significant changes in land use and cover.The Shiyang River Basin,located in the eastern part of the Hexi Corridor in China,has undergone significant climate change and LUCC over the past few decades.In this study,we used the random forest classification to obtain the land use and cover datasets of the Shiyang River Basin in 1991,1995,2000,2005,2010,2015,and 2020 based on Landsat images.We validated the land use and cover data in 2015 from the random forest classification results(this study),the high-resolution dataset of annual global land cover from 2000 to 2015(AGLC-2000-2015),the global 30 m land cover classification with a fine classification system(GLC_FCS30),and the first Landsat-derived annual China Land Cover Dataset(CLCD)against ground-truth classification results to evaluate the accuracy of the classification results in this study.Furthermore,we explored and compared the spatiotemporal patterns of LUCC in the upper,middle,and lower reaches of the Shiyang River Basin over the past 30 years,and employed the random forest importance ranking method to analyze the influencing factors of LUCC based on natural(evapotranspiration,precipitation,temperature,and surface soil moisture)and anthropogenic(nighttime light,gross domestic product(GDP),and population)factors.The results indicated that the random forest classification results for land use and cover in the Shiyang River Basin in 2015 outperformed the AGLC-2000-2015,GLC_FCS30,and CLCD datasets in both overall and partial validations.Moreover,the classification results in this study exhibited a high level of agreement with the ground truth features.From 1991 to 2020,the area of bare land exhibited a decreasing trend,with changes primarily occurring in the middle and lower reaches of the basin.The area of grassland initially decreased and then increased,with changes occurring mainly in the upper and middle reaches of the basin.In contrast,the area of cropland initially increased and then decreased,with changes occurring in the middle and lower reaches.The LUCC was influenced by both natural and anthropogenic factors.Climatic factors and population contributed significantly to LUCC,and the importance values of evapotranspiration,precipitation,temperature,and population were 22.12%,32.41%,21.89%,and 19.65%,respectively.Moreover,policy interventions also played an important role.Land use and cover in the Shiyang River Basin exhibited fluctuating changes over the past 30 years,with the ecological environment improving in the last 10 years.This suggests that governance efforts in the study area have had some effects,and the government can continue to move in this direction in the future.The findings can provide crucial insights for related research and regional sustainable development in the Shiyang River Basin and other similar arid and semi-arid areas.

Spatiotemporal dynamics of land use/land cover(LULC)changes and its impact on land surface temperature:A case study in New Town Kolkata,eastern India

Rapid urbanization creates complexity,results in dynamic changes in land and environment,and influences the land surface temperature(LST)in fast-developing cities.In this study,we examined the impact of land use/land cover(LULC)changes on LST and determined the intensity of urban heat island(UHI)in New Town Kolkata(a smart city),eastern India,from 1991 to 2021 at 10-a intervals using various series of Landsat multi-spectral and thermal bands.This study used the maximum likelihood algorithm for image classification and other methods like the correlation analysis and hotspot analysis(Getis–Ord Gi^(*) method)to examine the impact of LULC changes on urban thermal environment.This study noticed that the area percentage of built-up land increased rapidly from 21.91%to 45.63%during 1991–2021,with a maximum positive change in built-up land and a maximum negative change in sparse vegetation.The mean temperature significantly increased during the study period(1991–2021),from 16.31℃to 22.48℃in winter,29.18℃to 34.61℃in summer,and 19.18℃to 27.11℃in autumn.The result showed that impervious surfaces contribute to higher LST,whereas vegetation helps decrease it.Poor ecological status has been found in built-up land,and excellent ecological status has been found in vegetation and water body.The hot spot and cold spot areas shifted their locations every decade due to random LULC changes.Even after New Town Kolkata became a smart city,high LST has been observed.Overall,this study indicated that urbanization and changes in LULC patterns can influence the urban thermal environment,and appropriate planning is needed to reduce LST.This study can help policy-makers create sustainable smart cities.

An Analysis of Land Use and Land Cover Changes, and Implications for Conservation in Mukumbura (Ward 2), Mt Darwin, Zimbabwe, 2002-2022

Understanding trends of land use land cover (LULC) changes is important for biodiversity monitoring and conservation planning, and identifying the areas affected by change and designing sustainable solutions to reduce the changes. The study aims to evaluate and quantify the historical changes in land use and land cover in Mukumbura (Ward 2), Mt Darwin, Zimbabwe, from 2002 to 2022. The objective of the study was to analyse the LULC changes in Ward 2 (Mukumbura), Mt Darwin, Northern Zimbabwe, for a period of 20 years using geospatial techniques. Landsat satellite images were processed using Google Earth Engine (GEE) and the supervised classification with maximum likelihood algorithm was employed to generate LULC maps between 2002 and 2022 with a five (5) year interval, investigating the following variables, forest cover, barren land, water cover and the fields. Findings revealed a substantial reduction in forest cover by 38.8%, water bodies (wetlands, ponds, and rivers) declined by 55.6%, whilst fields (crop/agricultural fields) increased by 93.3% and the barren land cover increased by 26.3% from 2002 to 2022. These findings point to substantial changes in LULC over the observed years. LULC changes have resulted in habitat fragmentation, reduced biodiversity, and the disruption of ecosystem functions. The study concludes that if these deforestation trends, cultivation, and settlement land expansion continue, the ward will have limited indigenous fruit trees. Therefore, the causes for LULC changes must be controlled, sustainable forest resources use practiced, hence the need to domesticate the indigenous fruit trees in arborloo toilets.

Trends of Land Use and Land Cover Change in the Savannah Ecological of the Protected Area Reserve Partielle de Dosso, Niger

Information on the dynamics of savannah is important to a country's plan to overcome the problems of uncontrolled development and environmental hazards. Taking the reserve partielle de Dosso, Niger as the case study area, this paper analyzed the long-term land use land cover change from 2002 to 2022. Satellite images were processed by using Google Earth Engine (GEE). Therefore, four major land cover classes were identified based on spectral characteristics of Land sat, namely, built-up, vegetation, cropland, bare land and water. The result revealed that barren and built-up areas increased at the expense of vegetation and water. From the four major land use land cover the large area is covered by vegetation which comprises about 192963.5 hectares followed by cropland and water consisting of 32506.43 and 1596.4 hectares respectively. The built-up area gained substantial area (most) during the study period. The reduction in some of the land cover/uses underlines the dangerous trend of the pressure poised by population growth and the changing functionality. Land cover change is influenced by a variety of societal factors operating on several spatial and temporal levels. The area estimates and spatial distributions of the LULC classes produced from the current study will assist local authorities, managers, and other stakeholders in decision-making and planning regarding forest land cover and uses.

Historical Changes and Multi-scenario Prediction of Land Use and Terrestrial Ecosystem Carbon Storage in China

Terrestrial carbon storage(CS)plays a crucial role in achieving carbon balance and mitigating global climate change.This study employs the Shared Socioeconomic Pathways and Representative Concentration Pathways(SSPs-RCPs)published by the Intergovernmental Panel on Climate Change(IPCC)and incorporates the Policy Control Scenario(PCS)regulated by China’s land management policies.The Future Land Use Simulation(FLUS)model is employed to generate a 1 km resolution land use/cover change(LUCC)dataset for China in 2030 and 2060.Based on the carbon density dataset of China’s terrestrial ecosystems,the study analyses CS changes and their relationship with land use changes spanning from 1990 to 2060.The findings indicate that the quantitative changes in land use in China from 1990 to 2020 are characterised by a reduction in the area proportion of cropland and grassland,along with an increase in the impervious surface and forest area.This changing trend is projected to continue under the PCS from 2020 to 2060.Under the SSPs-RCPs scenario,the proportion of cropland and impervious surface predominantly increases,while the proportions of forest and grassland continuously decrease.Carbon loss in China’s carbon storage from 1990 to 2020 amounted to 0.53×10^(12)kg,primarily due to the reduced area of cropland and grassland.In the SSPs-RCPs scenario,more significant carbon loss occurs,reaching a peak of8.07×10^(12)kg in the SSP4-RCP3.4 scenario.Carbon loss is mainly concentrated in the southeastern coastal area and the Beijing-TianjinHebei(BTH)region of China,with urbanisation and deforestation identified as the primary drivers.In the future,it is advisable to enhance the protection of forests and grassland while stabilising cropland areas and improving the intensity of urban land.These research findings offer valuable data support for China’s land management policy,land space optimisation,and the achievement of dual-carbon targets.

Uphill or downhill?Cropland use change and its drivers from the perspective of slope spectrum

The continuous decrease of low-slope cropland resources caused by construction land crowding poses huge threat to regional sustainable development and food security.Slope spectrum analysis of topographic and geomorphic features is considered as a digital terrain analysis method which reflects the macro-topographic features by using micro-topographic factors.However,pieces of studies have extended the concept of slope spectrum in the field of geoscience to construction land to explore its expansion law,while research on the slope trend of cropland from that perspective remains rare.To address the gap,in virtue of spatial analysis and geographically weighted regression(GWR)model,the cropland use change in the Yangtze River Basin(YRB)from 2000 to 2020 was analyzed and the driving factors were explored from the perspective of slope spectrum.Results showed that the slope spectrum curves of cropland area-frequency in the YRB showed a first upward then a downward trend.The change curve of the slope spectrum of cropland in each province(municipality)exhibited various distribution patterns.Quantitative analysis of morphological parameters of cropland slope spectrum revealed that the further down the YRB,the stronger the flattening characteristics,the more obvious the concentration.The province experienced the greatest downhill cropland climbing(CLC)was Shannxi,while province experienced the highest uphill CLC was Zhejiang.The most common cropland use change type in the YRB was horizontal expansion type.The factors affecting average cropland climbing index(ACCI)were quite stable in different periods,while population density(POP)changed from negative to positive during the study period.This research is of practical significance for the rational utilization of cropland at the watershed scale.

Response of ecosystem carbon storage to land use change from 1985 to 2050 in the Ningxia Section of Yellow River Basin,China

Regional sustainable development necessitates a holistic understanding of spatiotemporal variations in ecosystem carbon storage(ECS),particularly in ecologically sensitive areas with arid and semi-arid climate.In this study,we calculated the ECS in the Ningxia Section of Yellow River Basin,China from 1985 to 2020 using the Integrated Valuation of Ecosystem Services and Tradeoffs(InVEST)model based on land use data.We further predicted the spatial distribution of ECS in 2050 under four land use scenarios:natural development scenario(NDS),ecological protection scenario(EPS),cultivated land protection scenario(CPS),and urban development scenario(UDS)using the patch-generating land use simulation(PLUS)model,and quantified the influences of natural and human factors on the spatial differentiation of ECS using the geographical detector(Geodetector).Results showed that the total ECS of the study area initially increased from 1985 until reaching a peak at 402.36×10^(6) t in 2010,followed by a decreasing trend to 2050.The spatial distribution of ECS was characterized by high values in the eastern and southern parts of the study area,and low values in the western and northern parts.Between 1985 and 2020,land use changes occurred mainly through the expansion of cultivated land,woodland,and construction land at the expense of unused land.The total ECS in 2050 under different land use scenarios(ranked as EPS>CPS>NDS>UDS)would be lower than that in 2020.Nighttime light was the largest contributor to the spatial differentiation of ECS,with soil type and annual mean temperature being the major natural driving factors.Findings of this study could provide guidance on the ecological construction and high-quality development in arid and semi-arid areas.

Impacts of multi-scenario land use change on ecosystem services and ecological security pattern: A case study of the Yellow River Delta

The Yellow River Delta(YRD), a critical economic zone along China's eastern coast, also functions as a vital ecological reserve in the lower Yellow River. Amidst rapid industrialization and urbanization, the region has witnessed significant land use/cover changes(LUCC), impacting ecosystem services(ES) and ecological security patterns(ESP). Investigating LUCC's effects on ES and ESP in the YRD is crucial for ecological security and sustainable development. This study utilized the PLUS model to simulate 2030 land use scenarios, including natural development(NDS), economic development(EDS), and ecological protection scenarios(EPS). Subsequently, the InVEST model and circuit theory were applied to assess ES and ESP under varying LUCC scenarios from 2010 to 2030. Findings indicate:(1) Notable LUCC from 2010 to 2030, marked by decreasing cropland and increasing construction land and water bodies.(2) From 2010 to 2020, improvements were observed in carbon storage,water yield, soil retention, and habitat quality, whereas 2020–2030 saw increases in water yield and soil retention but declines in habitat quality and carbon storage. Among the scenarios, EPS showed superior performance in all four ES.(3) Between 2010 and 2030, ecological sources, corridors, and pinchpoints expanded, displaying significant spatial heterogeneity. The EPS scenario yielded the most substantial increases in ecological sources,corridors, and pinchpoints, totaling 582.89 km^(2), 645.03 km^(2),and 64.43 km^(2), respectively. This study highlights the importance of EPS, offering insightful scientific guidance for the YRD's sustainable development.

Assessing Spatio-Temporal Land Cover Changes in Dhund River Basin, Eastern Rajasthan (India), Using Multi-Temporal Landsat Data

Land cover is an impression of natural cover on surface of earth such as bare soil, river, grass etc. and utilization of these natural covers for various human needs and purposes by mankind is defined as land use. Land cover identification, delineation and mapping is important for planning activities, resource management and global monitoring studies while baseline mapping and subsequent monitoring is done by application of land use to get timely information about quantity of land that has been used. The present study has been carried out in Dhund river watershed of Jaipur, Rajasthan which covers an area of about 1828 sq∙km. The minimum and maximum elevation of the area is found to be 214 m and 603 m respectively. Land use and land cover changes of three decades from 1991 to 2021 have been interpreted by using remotes sensing and GIS techniques. ArcGIS software (Arc map 10.2), SOI topographic map, Cartosat-1 DEM and satellite data of Landsat 5 and Landsat 8 have been used for interpretation of eleven classes. The study shows an increase in cultivated land, settlement, waterbody, open forest, plantation and mining due to urbanization because of increasing demands of food, shelter and water while a decrease in dense forest, river, open scrub, wasteland and uncultivated land has also been marked due to destruction of aforementioned by anthropogenic activities such as industrialization resulting in environmental degradation that leads to air, soil and water pollution.

Mapping Energy Expansion: Remote Sensing Insights into Oil and Gas Infrastructure and Land Use Changes in Midland, TX

Rapid expansion in global energy demand driven primarily by oil and gas consumption has spurred significant environmental concerns. This study delves into the intricate relationship between energy development and environmental impacts focusing on Midland County, Texas, a pivotal region within the Permian Basin. Leveraging satellite imagery and Geographic Information Systems (GIS) techniques, the research meticulously examines land use dynamics from 2001 to 2019. The findings illuminate a marked decline in vegetation health and density attributable to the burgeoning oil and gas infrastructure in the area. Moreover, the analysis underscores the emergence of barren lands and the displacement of agricultural areas, indicative of the profound alterations in land cover patterns over the study period. These insights underscore the urgent need for concerted efforts to mitigate the adverse environmental effects of energy expansion, emphasizing the importance of collaborative approaches to foster sustainable land use practices. Additionally, the study explores the socio-economic implications of land use changes, addressing how energy expansion affects local communities and economies. Previous studies have emphasized the need for comprehensive assessments of cumulative environmental impacts, advocating for the implementation of effective mitigation strategies.

Migration and Spatiotemporal Land Cover Change: A Case of Bosomtwe Lake Basin, Ghana

Internal migration is highly valued due to its increasingly acknowledged potential for social and economic development. However, despite its significant contribution to the development of towns and cities, it has led to the deterioration of many ecosystems globally. Lake Bosomtwe, a natural Lake in Ghana and one of the six major meteoritic lakes in the world is affected by land cover changes caused by the rising effects of migration, population expansion, and urbanization, owing to the development of tourist facilities on the lakeshore. This study investigated land cover change trajectories using a post-classification comparison approach and identified the factors influencing alteration in the Lake Bosomtwe Basin. Using Landsat imagery, an integrated approach of remote sensing, geographical information systems (GIS), and statistical analysis was successfully employed to analyze the land cover change of the basin. The findings show that over the 17 years, the basin’s forest cover decreased significantly by 16.02%, indicating that population expansion significantly affects changes in land cover. Ultimately, this study will raise the awareness of stakeholders, decision-makers, policy-makers, government, and non-governmental agencies to evaluate land use development patterns, optimize land use structures, and provide a reference for the formulation of sustainable development policies to promote the sustainable development of the ecological environment.

Spatiotemporal detection of land use/land cover changes and land surface temperature using Landsat and MODIS data across the coastal Kanyakumari district, India

This study assesses the changes in land use/land cover(LULC) and land surface temperature(LST) to identify their impacts from 2000 to 2020 along the coast of Kanyakumari district, India using remote sensing techniques. Landsat images are used to estimate the LULC changes and the MODIS data for LST.The Maximum Likelihood Classification(MLC) method is used, and the LULC is classified into six categories: Agriculture Land, Barren Land, Salt Pan, Sandy Beach, Settlement, and Waterbody. Within the two decades of the present change detection study, upheave in the Settlement area of 49.89% is noticed, and the Agriculture Land is exploited by 20.09%. Salt Pan emits a high LST of 31.57°C, and the Waterbodies are noticed with a low LST of 28.9°C. However, the overall rate of LST decreased by 0.56°C during this period. This study will help policymakers make appropriate planning and management to overcome the impact of LULC and LST in the forthcoming years.

Impacts of land use/cover change on water balance by using the SWAT model in a typical loess hilly watershed of China

Land use/cover change(LUCC)plays a key role in altering surface hydrology and water balance,finally affect-ing the security and availability of water resources.However,mechanisms underlying LUCC determination of water-balance processes at the basin scale remain unclear.In this study,the Soil and Water Assessment Tool(SWAT)model and partial least squares regression were used to detect the effects of LUCC on hydrology and water components in the Zuli River Basin(ZRB),a typical watershed of the Yellow River Basin.In general,three recommended coefficients(R^(2)and E ns greater than 0.5,and P bias less than 20%)indicated that the output results of the SWAT model were reliable and that the model was effective for the ZRB.Then,several key findings were obtained.First,LUCC in the ZRB was characterized by a significant increase in forest(21.61%)and settlement(23.52%)and a slight reduction in cropland(-1.35%),resulting in a 4.93%increase in evapotranspiration and a clear decline in surface runoffand water yield by 15.68%and 2.95%at the whole basin scale,respectively.Second,at the sub-basin scale,surface runoffand water yield increased by 14.26%-36.15%and 5.13%-15.55%,respectively,mainly due to settlement increases.Last,partial least squares regression indicated that urbanization was the most significant contributor to runoffchange,and evapotranspiration change was mainly driven by forest expansion.These conclusions are significant for understanding the relationship between LUCC and water balance,which can provide meaningful information for managing water resources and the long-term sustainability of such watersheds.

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

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

Spatiotemporal Analysis of Land Use Land Cover Mapping and Change Detection in Dambatta Local Government Area

This research studied the spatiotemporal changes in land use(LU)/land cover(LC)in Dambatta local government area,with a view to identifying the effect arising from the observable changes in land use patterns.The imageries used in the study were obtained from the National Space Research and Development Agency(NARSDA),Abuja.Spatial analytical techniques and descriptive statistical techniques were employed to analyze the data.The results showed 66.8%reduction in agricultural lands,45.5%reduction in vegetation cover,223.2%increase in built-up areas,269.1%increase in bare lands and 70%increase in water bodies within the 20 years.Spatio-temporal analysis of the three imageries revealed that agricultural lands were largely been taken over by urbanization while vegetation had rapidly given way to bare lands within the 20 years.It was observed that these changes resulted from anthropogenic activities,environmental factors and climate change.These result in the loss of farmlands,inadequate food supply,unemployment,inadequate industrial raw materials,reduction in revenue generated,forest depletion,desertification,wildlife extinction and temperature increase.While it is recommended that reforestation,land reclamation and irrigation agriculture should be promoted in the area,it is also suggested that further research should focus on the impact of climate change on land cover change in the area.

Spatiotemporal evolution and future simulation of land use/land cover in the Turpan-Hami Basin,China

The Turpan-Hami(Tuha)Basin in Xinjiang Uygur Autonomous Region of China,holds significant strategic importance as a key economic artery of the ancient Silk Road and the Belt and Road Initiative,necessitating a holistic understanding of the spatiotemporal evolution of land use/land cover(LULC)to foster sustainable planning that is tailored to the region's unique resource endowments.However,existing LULC classification methods demonstrate inadequate accuracy,hindering effective regional planning.In this study,we established a two-level LULC classification system(8 primary types and 22 secondary types)for the Tuha Basin.By employing Landsat 5/7/8 imagery at 5-a intervals,we developed the LULC dataset of the Tuha Basin from 1990 to 2020,conducted the accuracy assessment and spatiotemporal evolution analysis,and simulated the future LULC under various scenarios via the Markov-Future Land Use Simulation(Markov-FLUS)model.The results revealed that the average overall accuracy values of our LULC dataset were 0.917 and 0.864 for the primary types and secondary types,respectively.Compared with the seven mainstream LULC products(GlobeLand30,Global 30-meter Land Cover with Fine Classification System(GLC_FCS30),Finer Resolution Observation and Monitoring of Global Land Cover PLUS(FROM_GLC PLUS),ESA Global Land Cover(ESA_LC),Esri Land Cover(ESRI_LC),China Multi-Period Land Use Land Cover Change Remote Sensing Monitoring Dataset(CNLUCC),and China Annual Land Cover Dataset(CLCD))in 2020,our LULC data exhibited dramatically elevated overall accuracy and provided more precise delineations for land features,thereby yielding high-quality data backups for land resource analyses within the basin.In 2020,unused land(78.0%of the study area)and grassland(18.6%)were the dominant LULC types of the basin;although cropland and construction land constituted less than 1.0%of the total area,they played a vital role in arid land development and primarily situated within oases that form the urban cores of the cities of Turpan and Hami.Between 1990 and 2020,cropland and construction land exhibited a rapid expansion,and the total area of water body decreased yet resurging after 2015 due to an increase in areas of reservoir and pond.In future scenario simulations,significant increases in areas of construction land and cropland are anticipated under the business-as-usual scenario,whereas the wetland area will decrease,suggesting the need for ecological attention under this development pathway.In contrast,the economic development scenario underscores the fast-paced expansion of construction land,primarily from the conversion of unused land,highlighting the significant developmental potential of unused land with a slowing increase in cropland.Special attention should thus be directed toward ecological and cropland protection during development.This study provides data supports and policy recommendations for the sustainable development goals of Tuha Basin and other similar arid areas.

Investigating the Long-Term Relationship between Aerosol Optical Thickness and Land Use/Cover Change in Guangxi Coastal Cities, China

Land Use/Cover Change (LUCC) has an impact on AOD to a certain extent. It is of great significance for ecological environment and public health to pay attention to and explore the response mechanism of AOD to LUCC. Based on remote sensing satellite technology, using landsat8 and MODIS data, this paper analyzes the correlation between different land use types and AOD in Beibu Gulf coastal urban belt under the background of wide-scale region and long time series, and further discusses the difference value and contribution level of each LUCC to AOD. The results show that: 1) there is a positive correlation between PM concentration and cultivated land, urban land, water area and other types of land, and the correlation coefficient increases in turn, R is 0.812, 0.685, 0.627, 0.416, respectively, which indicates that the increase of cultivated land and urban land increases PM concentration to a certain extent;2) there is a significant negative correlation between PM concentration and forest land, R is -0.924, The results show that the decrease of woodland is an important factor for the increase of atmospheric particulate matter concentration in the study area from 2015 to 2019;3) through the contribution analysis method, the contribution of cultivated land to AOD is the largest, followed by urban land, and the water area is the smallest in 2015-2019, which indicates that the land use mode is closely related to AOD. It can be helpful to reasonably plan land use types and scientifically optimize land use structure. It can effectively reduce the concentration of air pollution particles.

Dynamics of Land Use/Land Cover Considering Ecosystem Services for a Dense-Population Watershed Based on a Hybrid Dual-Subject Agent and Cellular Automaton Modeling Approach

Land use/land cover represents the interactive and comprehensive influences between human activities and natural conditions,leading to potential conflicts among natural and human-related issues as well as among stakeholders.This study introduced economic standards for farmers.A hybrid approach(CA-ABM)of cellular automaton(CA)and an agent-based model(ABM)was developed to effectively deal with social and land-use synergic issues to examine human–environment interactions and projections of land-use conversions for a humid basin in south China.Natural attributes and socioeconomic data were used to analyze land use/land cover and its drivers of change.The major modules of the CA-ABM are initialization,migration,assets,land suitability,and land-use change decisions.Empirical estimates of the factors influencing the urban land-use conversion probability were captured using parameters based on a spatial logistic regression(SLR)model.Simultaneously,multicriteria evaluation(MCE)and Markov models were introduced to obtain empirical estimates of the factors affecting the probability of ecological land conversion.An agent-based CA-SLR-MCE-Markov(ABCSMM)land-use conversion model was proposed to explore the impacts of policies on land-use conversion.This model can reproduce observed land-use patterns and provide links for forest transition and urban expansion to land-use decisions and ecosystem services.The results demonstrated land-use simulations under multi-policy scenarios,revealing the usefulness of the model for normative research on land-use management.