Current situation and trend of arable land change in China

How to protect arable land in the process of economic development and urbanization is a critical issue in China. In this paper, an attempt is made to analyze the situation of arable land change in China and it's relationship with population growth, economic development and urbanization. In depth analysis is also made in different regions. Forecasting is conducted to show the trend of arable land change in China based on the results of correlation analysis. Some suggestions are put forward for the policy making of reasonable utilization and protection of arable land in the future.

ART Based Reliable Method for Prediction of Agricultural Land Changes Using Remote Sensing

This paper focuses on prediction of change in agricultural lands by using ART2 algorithm. The existing method used ENVI and ARCGIS software to predict the changes in land, which showed less accuracy due to human errors. To overcome this user friendly GUI based ART2 algorithm has been developed in java to obtain more accuracy in prediction of changes in land. The input is satellite temporal images of the years 1990 and 2014. By using the ART2 algorithm, the input images of the years 1990 and 2014 are classified, where the features are identified to form cluster. The clustered image is given as input and pixel to pixel comparison method in ART2 is implemented in java, for detecting the changes in agricultural lands. The comparison results of ENVI and ARCGIS and GUI based ART2 with in situ data show that the prediction of changes in agricultural land is more accurate in the case of GUI based ART2 implementation.

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.

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.

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.

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.

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.

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 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.

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.

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.

Spatially Heterogeneous Response of Carbon Storage to Land Use Changes in Pearl River Delta Urban Agglomeration, China

Carbon storage of terrestrial ecosystems plays a vital role in advancing carbon neutrality. Better understanding of how land use changes affect carbon storage in urban agglomeration will provide valuable guidance for policymakers in developing effective regional conservation policies. Taking the Pearl River Delta Urban Agglomeration(PRDUA) in China as an example, we examined the heterogeneous response of carbon storage to land use changes in 1990–2018 from a combined view of administrative units and physical entities. The results indicate that the primary change in land use was due to the expansion of construction land(5897.16 km2). The carbon storage in PRDUA decreased from 767.34 Tg C in 1990 to 725.42 Tg C in 2018 with a spatial pattern of high wings and the low middle. The carbon storage loss was largely attributed to construction land expansion(55.74%), followed by forest degradation(54.81%). Changes in carbon storage showed significant divergences in different sized cities and hierarchical boundaries. The coefficients of geographically weighted regression(GWR) reveal that the alteration in carbon storage in Guangzhou City was more responsive to changes in construction land(-0.11) compared to other cities, while that in Shenzhen was mainly affected by the dynamics of forest land(8.32). The change in carbon storage was primarily influenced by the conversion of farmland within urban extent(5.05) and the degradation of forest land in rural areas(5.82). Carbon storage changes were less sensitive to the expansion of construction land in the urban center, urban built-up area, and ex-urban built-up area, with the corresponding GWR coefficients of 0.19, 0.04, and 0.02. This study necessitates the differentiated protection strategies of carbon storage in urban agglomerations.

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.

Analysis of Land Use Change and Driving Factors in Mojiang County Based on PLUS Model

[Objectives]To explore the characteristics of land use change and its main influencing factors in Mojiang County from 2000 to 2020,and try to provide a scientific reference for alleviating the contradiction between man and land in Mojiang County and realizing the sustainable development of regional land resources.[Methods]Based on the land cover data and socio-economic data of Mojiang County from 2000 to 2020,the dynamic degree of land use,land use transfer matrix and center-of-gravity transfer model were calculated,and the temporal and spatial change characteristics and driving factors of various types of land use were calculated by PLUS model.[Results]From 2000 to 2020,the area and proportion of grassland,waters and construction land in Mojiang County showed an upward trend,while the area and proportion of cultivated land and forest land showed a downward trend.Among them,cultivated land was mainly converted into forest land and grassland,and some were converted into waters and construction land;forest land was mainly converted into cultivated land and grassland,and part of it was converted into waters and construction land.From 2000 to 2020,the center-of-gravity of cultivated land,forest land and construction land in Mojiang County moved to the southeast of the county,and the moving rates were 0.66,1.97 and 10.58 km/yr,respectively;the center-of-gravity of grassland and waters moved to the southwest of the county,and the moving rates were 1.30 and 20.20 km/yr,respectively.Distance from road,distance from government and distance from waters are the main driving forces affecting land use change in Mojiang County;the forecast shows that in 2040,the area of grassland and forest land in Mojiang County will continue to decrease,the area of cultivated land will turn to rise,and the area of waters and construction land will continue to rise.[Conclusions]Reasonable planning and optimizing the allocation of cultivated land and forest land structure and strict control of the expansion scale of construction land are necessary measures to ensure the coordinated development of regional land rational use and economic construction.

Temporal and Spatial Evolution Characteristics of Habitat Quality in Kunming Based on Land Use Change

[Objectives]To analyze the change of urban habitat quality in different periods and study the influence of land use change on habitat quality,which plays an important role in regional sustainable development.[Methods]Taking Kunming as an example,based on land use change,InVEST model was used to evaluate the temporal and spatial evolution characteristics of habitat quality.[Results]During 2000-2020,cultivated land,grassland and woodland in Kunming decreased by 277.43,324.99 and 141.72 km 2,respectively;land use transfer presented obvious stage characteristics,with cultivated land,grassland and woodland changing into construction land as the main characteristics during 2005-2010,and 2015-2020.The average value of habitat quality index in Kunming decreased from 0.3119 to 0.3022,showing a downward trend as a whole;the spatial distribution pattern of habitat quality was"low in the middle and high around"(the high value areas of habitat quality are mainly distributed around Kunming,while the low value areas are mainly distributed in the urban aggregation areas of Kunming).[Conclusions]This study can provide theoretical support for future land use planning.

Response of vegetation variation to climate change and human activities in the Shiyang River Basin of China during 2001-2022

Understanding the response of vegetation variation to climate change and human activities is critical for addressing future conflicts between humans and the environment,and maintaining ecosystem stability.Here,we aimed to identify the determining factors of vegetation variation and explore the sensitivity of vegetation to temperature(SVT)and the sensitivity of vegetation to precipitation(SVP)in the Shiyang River Basin(SYRB)of China during 2001-2022.The climate data from climatic research unit(CRU),vegetation index data from Moderate Resolution Imaging Spectroradiometer(MODIS),and land use data from Landsat images were used to analyze the spatial-temporal changes in vegetation indices,climate,and land use in the SYRB and its sub-basins(i.e.,upstream,midstream,and downstream basins)during 2001-2022.Linear regression analysis and correlation analysis were used to explore the SVT and SVP,revealing the driving factors of vegetation variation.Significant increasing trends(P<0.05)were detected for the enhanced vegetation index(EVI)and normalized difference vegetation index(NDVI)in the SYRB during 2001-2022,with most regions(84%)experiencing significant variation in vegetation,and land use change was determined as the dominant factor of vegetation variation.Non-significant decreasing trends were detected in the SVT and SVP of the SYRB during 2001-2022.There were spatial differences in vegetation variation,SVT,and SVP.Although NDVI and EVI exhibited increasing trends in the upstream,midstream,and downstream basins,the change slope in the downstream basin was lower than those in the upstream and midstream basins,the SVT in the upstream basin was higher than those in the midstream and downstream basins,and the SVP in the downstream basin was lower than those in the upstream and midstream basins.Temperature and precipitation changes controlled vegetation variation in the upstream and midstream basins while human activities(land use change)dominated vegetation variation in the downstream basin.We concluded that there is a spatial heterogeneity in the response of vegetation variation to climate change and human activities across different sub-basins of the SYRB.These findings can enhance our understanding of the relationship among vegetation variation,climate change,and human activities,and provide a reference for addressing future conflicts between humans and the environment in the arid inland river basins.

Considering Regional Connectivity and Policy Factors in the Simulation of Land Use Change in New Areas:A Case Study of Nansha New District,China

Numerous emerging development areas worldwide are receiving attention;however,current research on land use change simulation primarily concentrates on cities,urban clusters,or larger scales.Moreover,there is a limited focus on understanding the impact of regional connectivity with surrounding cities and policy factors on land use change in these new areas.In this context,the present study utilizes a cellular automata(CA)model to investigate land use changes in the case of Nansha New District in Guangzhou,China.Three scenarios are examined,emphasizing conventional locational factors,policy considerations,and the influence of regional connectivity with surrounding cities.The results reveal several key findings:(1)Between 2015 and 2021,Nansha New District experienced significant land use changes,with the most notable shifts observed in cultivated land,water area,and construction land.(2)The comprehensive scenario exhibited the highest simulation accuracy,indicating that Nansha New District,as an emerging area,is notably influenced by policy factors and regional connectivity with surrounding cities.(3)Predictions for land use changes in Nansha by 2030,based on the scenario with the highest level of simulation accuracy,suggest an increase in the proportion of cultivated and forest land areas,alongside a decrease in the proportion of construction land and water area.This study contributes valuable insights to relevant studies and policymakers alike.

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.

Exploring the Spatiotemporal Changes and Driving Forces of Ecosystem Services of Zhejiang Coasts,China,Under Sustainable Development Goals

Ecosystem services(ESs)refer to the continuous provisioning of ecosystem goods and services that benefit human beings.Over recent decades,rapid urbanization has exerted significant pressure on coastal ecosystems,resulting in biodiversity and habitat loss,environmental pollution,and the depletion of natural resources.In response to these environmental challenges,the Sustainable Development Goals(SDGs)were proposed.Given the pressing need to address these issues,understanding the changes in ESs under the SDGs is crucial for formulating specific ecological strategies.In this study,we first analyzed land use and cover change in the Zhejiang coasts of China during 2000–2020.Then,we investigated the spatiotemporal configuration of ESs by integrating carbon storage(CS),soil retention(SR),habitat quality(HQ)and water yield(WY)using the Integrated Valuation of Ecosystem Services and Tradeoffs(InVEST)model.The driving mechanisms of ESs,which varied by space and time,were also explored using the Geo-detector method.The results revealed that,over the past two decades:1)the Zhejiang coasts have experienced a significant increase of 2783.72 km^(2) in built-up land areas and a continuous decrease in farmland areas due to rapid urbanization;2)owing to higher precipitation,extensive vegetation cover,and reduced anthropogenic disturbances,forests emerge as a crucial land use type for maintaining ecosystem services such as HQ,CS,WY,and SR;3)ESs have generally declined across the entire Zhejiang coasts,with a significant decrease observed in the northern areas and an increase in the southern areas spatially;4)the expansion of built-up land areas emerged as the primary factor affecting ecosystem services,while the vegetation factor has been increasingly significant and is expected to become predominant in the near future.Our study provides insights of understanding of ecosystem service theory and emphasizing the importance of preserving biodiversity for long-term sustainable development,and valuable scientific references to support the ecological management decision-making for local governments.

Land Use Land Cover Analysis for Godavari Basin in Maharashtra Using Geographical Information System and Remote Sensing

The dynamic transformation of land use and land cover has emerged as a crucial aspect in the effective management of natural resources and the continual monitoring of environmental shifts. This study focused on the land use and land cover (LULC) changes within the catchment area of the Godavari River, assessing the repercussions of land and water resource exploitation. Utilizing LANDSAT satellite images from 2009, 2014, and 2019, this research employed supervised classification through the Quantum Geographic Information System (QGIS) software’s SCP plugin. Maximum likelihood classification algorithm was used for the assessment of supervised land use classification. Seven distinct LULC classes—forest, irrigated cropland, agricultural land (fallow), barren land, shrub land, water, and urban land—are delineated for classification purposes. The study revealed substantial changes in the Godavari basin’s land use patterns over the ten-year period from 2009 to 2019. Spatial and temporal dynamics of land use/cover changes (2009-2019) were quantified using three Satellite/Landsat images, a supervised classification algorithm and the post classification change detection technique in GIS. The total study area of the Godavari basin in Maharashtra encompasses 5138175.48 hectares. Notably, the built-up area increased from 0.14% in 2009 to 1.94% in 2019. The proportion of irrigated cropland, which was 62.32% in 2009, declined to 41.52% in 2019. Shrub land witnessed a noteworthy increase from 0.05% to 2.05% over the last decade. The key findings underscored significant declines in barren land, agricultural land, and irrigated cropland, juxtaposed with an expansion in forest land, shrub land, and urban land. The classification methodology achieved an overall accuracy of 80%, with a Kappa Statistic of 71.9% for the satellite images. The overall classification accuracy along with the Kappa value for 2009, 2014 and 2019 supervised land use land cover classification was good enough to detect the changing scenarios of Godavari River basin under study. These findings provide valuable insights for discerning land utilization across various categories, facilitating the adoption of appropriate strategies for sustainable land use in the region.