A comprehensive method of image classification was developed for monitoring land use dynamics in Chanthaburi Province of Tailand. RS (Remote Sensing), GIS (Geographical Information System), GPS (Global Positioning Sys...A comprehensive method of image classification was developed for monitoring land use dynamics in Chanthaburi Province of Tailand. RS (Remote Sensing), GIS (Geographical Information System), GPS (Global Positioning System) and ancillary data were combined by the method which adopts the main idea of classifying images by steps from decision tree method and the hybridized supervised and unsupervised classification. An integration of automatic image interpretation, ancillary materials and expert knowledge was realized. Two subscenes of Landsat 5 Thematic Mapper (TM) images of bands 3, 4 and 5 obtained on December 15, 1992, and January 17, 1999, were used for image processing and spatial data analysis in the study. The overall accuracy of the results of classification reached 90%, which was verified by field check.Results showed that shrimp farm land, urban and traffic land, barren land, bush and agricultural developing area increased in area, mangrove, paddy field, swamp and marsh land, orchard and plantation, and tropical grass land decreased, and the forest land kept almost stable. Ecological analysis on the land use changes showed that more attentions should be paid on the effect of land development on ecological environment in the future land planning and management.展开更多
Challenges in land use and land cover(LULC)include rapid urbanization encroaching on agricultural land,leading to fragmentation and loss of natural habitats.However,the effects of urbanization on LULC of different cro...Challenges in land use and land cover(LULC)include rapid urbanization encroaching on agricultural land,leading to fragmentation and loss of natural habitats.However,the effects of urbanization on LULC of different crop types are less concerned.The study assessed the impacts of LULC changes on agriculture and drought vulnerability in the Aguascalientes region,Mexico,from 1994 to 2024,and predicted the LULC in 2034 using remote sensing data,with the goals of sustainable land management and climate resilience strategies.Despite increasing urbanization and drought,the integration of satellite imagery and machine learning models in LULC analysis has been underutilized in this region.Using Landsat imagery,we assessed crop attributes through indices such as normalized difference vegetation index(NDVI),normalized difference water index(NDWI),normalized difference moisture index(NDMI),and vegetation condition index(VCI),alongside watershed delineation and spectral features.The random forest model was applied to classify LULC,providing insights into both historical and future trends.Results indicated a significant decline in vegetation cover(109.13 km^(2))from 1994 to 2024,accompanied by an increase in built-up land(75.11 km^(2))and bare land(67.13 km^(2)).Projections suggested a further decline in vegetation cover(41.51 km^(2))and continued urban land expansion by 2034.The study found that paddy crops exhibited the highest values,while common bean and maize performed poorly.Drought analysis revealed that mildly dry areas in 2004 became severely dry in 2024,highlighting the increasing vulnerability of agriculture to climate change.The study concludes that sustainable land management,improved water resource practices,and advanced monitoring techniques are essential to mitigate the adverse effects of LULC changes on agricultural productivity and drought resilience in the area.These findings contribute to the understanding of how remote sensing can be effectively used for long-term agricultural planning and environmental sustainability.展开更多
This study examines the spatial and temporal patterns of wetland degradation in Delhi from 1991 to 2021 using remote sensing and GIS techniques.The Automated Water Extraction Index(AWEI)was applied to pre-monsoon Land...This study examines the spatial and temporal patterns of wetland degradation in Delhi from 1991 to 2021 using remote sensing and GIS techniques.The Automated Water Extraction Index(AWEI)was applied to pre-monsoon Landsat imagery to delineate surface water bodies over the past 30 years accurately.Supervised classification was employed to generate land use maps,while census data was utilized to analyze urbanization trends across the region.Classification accuracy was assessed using Google Earth reference data through a confusion matrix,ensuring the reliability of the land cover analysis.Results reveal a significant decline in wetland extent,especially in densely populated and rapidly urbanizing districts such as North West,South,and East Delhi.During this time,the urban population increased from 52.7% to 97.4%,accompanied by a 70.2% expansion of built-up areas,while wetlands contracted from 32.9 km^(2) to 30.2 km^(2).South Delhi experienced the most severe wetland loss,with water body coverage dropping from 0.800% to 0.025%,whereas North East and Central Delhi maintained higher wetland coverage due to the influence of the Yamuna River and targeted conservation efforts.The study highlights the strong linkage between urban growth and wetland decline,which threatens biodiversity,groundwater recharge,and ecological stability.These findings emphasize the urgent need for integrated urban planning and conservation policies to safeguard wetlands,thereby promoting sustainability and water security in the National Capital Region.展开更多
The simultaneous increase in development in Pesawaran Regency is closely correlated with the intense competi-tion for land use.However,low policy implementation effectiveness has led to construction beyond designated ...The simultaneous increase in development in Pesawaran Regency is closely correlated with the intense competi-tion for land use.However,low policy implementation effectiveness has led to construction beyond designated spatial plan.The study used a quantitative survey using Landsat images in 2016,2019,and 2022.The data analysis techniques used geographic information systems integrated with Artificial Neural Network(ANN)and Cellular Automata(CA)models.This study aims to predict land-use change in 2031,evaluate its alignment with spatial planning,and provide guidance for controlling land-use change.The results showed that there has been an increase in land use.In 2019,built-up land reached 7,069.65 Ha.The model shows its ability to predict land simulation and transformation,where it is predicted that built-up land in 2031 will experience an increase of up to 40.10%,so development and change cannot be avoided every year.This study also suggests that decision-makers and local governments should reconsider spatial planning strategies.This study shows that there have been many land use changes from 2016 to 2022.The model shows its ability to predict simulation and land transformation.When using the model,there are many changes in the land use area in 2031.This is due to wet agricultural land turning into built-up land by almost 70%.This study shows that road network influence land-use change.The cellular automata model managed to capture the complexity with simple rules.Predictions for future research should focus on conserving wetlands and primary forests.展开更多
Rapid regional population shifts and spatial polarization have heightened pressure on cultivated land—a critical resource demanding urgent attention amid ongoing urban-rural transition.This study selects Jiangsu prov...Rapid regional population shifts and spatial polarization have heightened pressure on cultivated land—a critical resource demanding urgent attention amid ongoing urban-rural transition.This study selects Jiangsu province,a national leader in both economic and agricultural development,as a case area to construct a multidimensional framework for assessing the recessive morphological characteristics of multifunctional cultivated land use.We examine temporal dynamics,spatial heterogeneity,and propose an integrated zoning strategy based on empirical analysis.The results reveal that:(1)The recessive morphology index shows a consistent upward trend,with structural breaks in 2007 and 2013,and a spatial shift from“higher in the east and lower in the west”to“higher in the south and lower in the north.”(2)Coordination among sub-dimensions of the index has steadily improved.(3)The index is expected to continue rising in the next decade,though at a slower pace.(4)To promote coordinated multidimensional land-use development,we recommend a policy framework that reinforces existing strengths,addresses weaknesses,and adapts zoning schemes to current spatial conditions.This research offers new insights into multifunctional cultivated land systems and underscores their role in enhancing human well-being,securing food supply,and supporting sustainable urban-rural integration.展开更多
In order to simulate the evolution of affordable housing land use a dynamic model that combines cellular automata CA and a multi-agent system MAS is established.This paper aims to utilize the approach of decision fact...In order to simulate the evolution of affordable housing land use a dynamic model that combines cellular automata CA and a multi-agent system MAS is established.This paper aims to utilize the approach of decision factors on site selection of affordable housing through a literature review to construct a hierarchy model of those factors identifying the weight of each factor by an analytic hierarchy process AHP .Based on those weight factors the CA-MAS model is designed. Nanjing city is taken as an example to verify the feasibility of the model.The results show that the CA-MAS model is pragmatic and effective in simulating evolution of affordable housing land use which also promotes the fundamental understanding and perception of the development of affordable housing and urbanization.展开更多
Land use transition refers to the changes in land use morphology （both dominant morphology and recessive morphology） of a certain region over a certain period of time driven by socio-economic change and innovation, ...Land use transition refers to the changes in land use morphology （both dominant morphology and recessive morphology） of a certain region over a certain period of time driven by socio-economic change and innovation, and it usually corresponds to the transition of socio-economic development phase. In China, farmland and rural housing land are the two major sources of land use transition. This paper analyzes the spatio-temporal coupling characteristics of farmland and rural housing land transition in China, using high-resolution Landsat TM （Thematic Mapper） data in 2000 and 2008, and the data from the Ministry of Land and Resources of China. The outcomes indicated that： （1） during 2000-2008, the correlation coefficient of farmland vs. rural housing land change is -0.921, and it shows that the change pattern of farmland and rural housing land is uncoordinated; （2） the result of Spearman rank correlation analysis shows that rural housing land change has played a major role in the mutual transformation of farmland and rural housing land; and （3） it shows a high-degree spatial coupling between farmland and rural housing land change in southeast China during 2000-2008. In general, farmland and rural housing land transition in China is driven by socio-economic, bio-physical and managerial three-dimensional driving factors through the interactions among rural population, farmland and rural housing land. However, the spatio-temporal coupling phenomenon and mechanism of farmland and rural housing land transition in China are largely due to the ＂dual-track＂ structure of rural-urban development.展开更多
This study investigated and simulated land use patterns in Beijing for the year 2000 and the year 2005 from the actual land use data for the year 1995 and the year 2000,respectively,by combining spatial land allocatio...This study investigated and simulated land use patterns in Beijing for the year 2000 and the year 2005 from the actual land use data for the year 1995 and the year 2000,respectively,by combining spatial land allocation simulation using the CLUE-S model,and numerical land demand prediction using the Markov model.The simulations for 2000 and 2005 were confirmed to be generally accurate using Kappa indices.Then the land-use scenarios for Beijing in 2015 were simulated assuming two modes of development:1) urban development following existing trends;and 2) under a strict farmland control.The simulations suggested that under either mode,urbanized areas would expand at the expense of land for other uses.This expansion was predicted to dominate the land-use conversions between 2005 and 2015,and was expected to be accompanied by an extensive loss of farmland.The key susceptible to land-use changes were found to be located at the central urban Beijing and the surrounding regions including Yanqing County,Changping District and Fangshan District.Also,the simulations predicted a considerable expansion of urban/suburban areas in the mountainous regions of Beijing,suggesting a need for priority monitoring and protection.展开更多
Detailed analysis of Land Use/Land Cover （LULC） using remote sensing data in complex irrigated basins provides complete profile for better water resource management and planning. Using remote sensing data, this stud...Detailed analysis of Land Use/Land Cover （LULC） using remote sensing data in complex irrigated basins provides complete profile for better water resource management and planning. Using remote sensing data, this study provides detailed land use maps of the Lower Chenab Canal irrigated region of Pakistan from 2005 to 2012 for LULC change detection. Major crop types are demarcated by identifying temporal profiles of NDVI using MODIS 250 m × 250 m spatial resolution data. Wheat and rice are found to be major crops in rabi and kharif seasons, respectively. Accuracy assessment of prepared maps is performed using three dif- ferent techniques： error matrix approach, comparison with ancillary data and with previous study. Producer and user accuracies for each class are calculated along with kappa coeffi- cients （K）. The average overall accuracies for rabi and kharif are 82.83% and 78.21%, re- spectively. Producer and user accuracies for individual class range respectively between 72.5% to 77% and 70.1% to 84.3% for rabi and 76.6% to 90.2% and 72% to 84.7% for kharif. The K values range between 0.66 to 0.77 for rabi with average of 0.73, and from 0.69 to 0.74 with average of 0.71 for kharif. LULC change detection indicates that wheat and rice have less volatility of change in comparison with both rabi and kharif fodders. Transformation be- tween cotton and rice is less common due to their completely different cropping conditions. Results of spatial and temporal LULC distributions and their seasonal variations provide useful insights for establishing realistic LULC scenarios for hydrological studies.展开更多
Landsat Thematic Mapper （TM） and Enhanced Thematic Mapper Plus （ETM＋） images in 1985, 1986, 1993, 1994 and 2001 were used to quantify the land use and land cover changes （LUCC） in the Zhejiang coastal region wi...Landsat Thematic Mapper （TM） and Enhanced Thematic Mapper Plus （ETM＋） images in 1985, 1986, 1993, 1994 and 2001 were used to quantify the land use and land cover changes （LUCC） in the Zhejiang coastal region with a stratified unsupervised classification technique in conjunction with visual interpretation and to attempt an identification of the socioeconomic driving forces. In level I an overall accurate classification was achieved using a modified Anderson＇s Ⅰ/Ⅱ/Ⅲ-level classification scheme. The overall accuracy of the land use classification at Anderson level Ⅰ were 89.7% （1985）, 91.6% （1993）, and 90.4% （2001）. The most rapid land use change was a dramatic increase in urban or built-up areas, which quadrupled from 1985 to 2001. Over 90% of this newly expanded built-up area was originally paddy fields or other croplands. In different parts of the Zhejiang coastal region, urban land expansion was spatially uneven. Temporally, land use development did not stabilized, and the two study periods of time （1985-1993 and 1993-2001） had different transition styles. Socioeconomic factors, such as gross domestic product, total population, and financial expenditure, were all highly correlated with the expansion of urban or built-up areas. Based on the degree of urban sprawl and socioeconomic factors, cities and towns were further divided into six subgroups, which may help decision makers improve land use for the region.展开更多
Fuqing County of southeast China has witnessed significant land use changes during the last decade. Re mote sensing technology using multitemporal Landsat TM images was used to characterize land use types and to monit...Fuqing County of southeast China has witnessed significant land use changes during the last decade. Re mote sensing technology using multitemporal Landsat TM images was used to characterize land use types and to monitor land use changes in the county. Two TM scenes from 1991 and 1996 were used to cover the county and a five-year time period. Digital image processing was carried out for the remotely sensed data to produce classified images. The images were further processed using GIS software to generate GIS databases so that the data could be further spatially analyzed taking the advantages of the software. Land use change areas were determined by using the change detection technique. The comparison of the two classified TM images using the above technologies reveals that during the five study years, a large area of arable lands in the county has been lost and deforestation has taken place largely because of the dramatic in crease in built-up land and orchard. The conclusive statistical information is useful to understand the processes, causes and impacts of the land use changes in the county. The major driving force to the land use changes in the county ap peared to be the rapid economic development. The decision makers of the county have to pay more attention to the land use changes for the county’s sustainable development.展开更多
Due to inappropriate planning and management, accelerated urban growth and tremendous loss in land, especially cropland, have become a great challenge for sustainable urban development in China, especially in develope...Due to inappropriate planning and management, accelerated urban growth and tremendous loss in land, especially cropland, have become a great challenge for sustainable urban development in China, especially in developed urban area in the coastal regions; therefore, there is an urgent need to effectively detect and monitor the land use changes and provide accurate and timely information for planning and management. In this study a method combining principal component analysis (PCA) of multisensor satellite images from SPOT (systeme pour l'observation de la terre or earth observation satellite)-5 multispectral (XS) and Landsat-7 enhanced thematic mapper (ETM) panchromatic (PAN) data, and supervised classification was used to detect and analyze the dynamics of land use changes in the city proper of Hangzhou. The overall accuracy of the land use change detection was 90.67% and Kappa index was 0.89. The results indicated that there was a considerable land use change (10.03% of the total area) in the study area from 2001 to 2003, with three major types of land use conversions: from cropland into built-up land, construction site, and water area (fish pond). Changes from orchard land into built-up land were also detected. The method described in this study is feasible and useful for detecting rapid land use change in the urban area.展开更多
The ecological quality of inland areas is an important aspect of the United Nations Sustainable Development Goals(UN SDGs).The ecological environment of Northwest China is vulnerable to changes in climate and land use...The ecological quality of inland areas is an important aspect of the United Nations Sustainable Development Goals(UN SDGs).The ecological environment of Northwest China is vulnerable to changes in climate and land use/land cover,and the changes in ecological quality in this arid region over the last two decades are not well understood.This makes it more difficult to advance the UN SDGs and develop appropriate measures at the regional level.In this study,we used the Moderate Resolution Imaging Spectroradiometer(MODIS)products to generate remote sensing ecological index(RSEI)on the Google Earth Engine(GEE)platform to examine the relationship between ecological quality and environment in Xinjiang during the last two decades(from 2000 to 2020).We analyzed a 21-year time series of the trends and spatial characteristics of ecological quality.We further assessed the importance of different environmental factors affecting ecological quality through the random forest algorithm using data from statistical yearbooks and land use products.Our results show that the RSEI constructed using the GEE platform can accurately reflect the ecological quality information in Xinjiang because the contribution of the first principal component was higher than 90.00%.The ecological quality in Xinjiang has increased significantly over the last two decades,with the northern part of this region having a better ecological quality than the southern part.The areas with slightly improved ecological quality accounted for 31.26%of the total land area of Xinjiang,whereas only 3.55%of the land area was classified as having a slightly worsen(3.16%)or worsen(0.39%)ecological quality.The vast majority of the deterioration in ecological quality mainly occurred in the barren areas Temperature,precipitation,closed shrublands,grasslands and savannas were the top five environmental factors affecting the changes in RSEI.Environmental factors were allocated different weights for different RSEI categories.In general,the recovery of ecological quality in Xinjiang has been controlled by climate and land use/land cover during the last two decades and policy-driven ecological restoration is therefore crucial.Rapid monitoring of inland ecological quality using the GEE platform is projected to aid in the advancement of the comprehensive assessment of the UN SDGs.展开更多
This article attempts to detail time series characteristics of PM2.5 concentration in Guangzhou(China)from 1 June 2012 to 31 May 2013 based on wavelet analysis tools,and discuss its spatial distribution using geograph...This article attempts to detail time series characteristics of PM2.5 concentration in Guangzhou(China)from 1 June 2012 to 31 May 2013 based on wavelet analysis tools,and discuss its spatial distribution using geographic information system software and a modified land use regression model.In this modified model,an important variable(land use data)is substituted for impervious surface area,which can be obtained conveniently from remote sensing imagery through the linear spectral mixture analysis method.Impervious surface has higher precision than land use data because of its sub-pixel level.Seasonal concentration pattern and day-by-day change feature of PM2.5 in Guangzhou with a micro-perspective are discussed and understood.Results include:(1)the highest concentration of PM2.5 occurs in October and the lowest in July,respectively;(2)average concentration of PM2.5 in winter is higher than in other seasons;and(3)there are two high concentration zones in winter and one zone in spring.展开更多
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...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.展开更多
Land change science （LCS） strives to understand and model land-use change, which will further advance the understanding of multiple issues in the socio-ecological systems. Based on GIS/RS techniques, autologistic mo...Land change science （LCS） strives to understand and model land-use change, which will further advance the understanding of multiple issues in the socio-ecological systems. Based on GIS/RS techniques, autologistic model, and household survey method, this study investigated major land use changes and their causes from 1978 to 2008 in Uxin Banner （county-level）, Inner Mongolia in China and then developed an understanding of the relationships between household livelihood and land-use pattern. Results showed that cultivated land increased from 1988 to 2000, and leveled offafter 2000. Built-up land increased stably for the period 1978 2008. The change of grassland and bare land differed among the three periods. From 1978 to 1988, grassland increased by 23.3%, and bare land decreased by 20.48%. From 1988 to 2000, bare land expanded by 1.7%, but grassland declined by 1.3%. From 2000 to 2008, an increase in grassland area by 1.8% was observed, but a decrease in bare land area by 9.0% was witnessed. The autologistic models performed better than logistic models as indicated by lower Akaike Information Criterion （AIC） values. Factors associated with human activities significantly correlated with the change of cultivated land, forest land, grassland, and built-up land. The produce prices and extensive cultivated land use are major issues in the farming area. This study suggests that completing land circulation systems and maintaining the stability of price are effective solutions. By contrast, reclamation and overgrazing are major concerns in the pastoral areas. Implementing environmental policies effectively, transferring population out of rural pastoral areas, and developing modem animal husbandry are effective ways to address these issues.展开更多
This paper describes a new type of transformed Landsat images (LBV images) and their application in discriminating soil gleization in subtropic region of China. LBV transformation was worked out by the present author ...This paper describes a new type of transformed Landsat images (LBV images) and their application in discriminating soil gleization in subtropic region of China. LBV transformation was worked out by the present author for extracting useful information from original landsat images. Using this method three black and white images, L image, B image and V image, were computer generated from original bands of a Landsat scene, which covers a.large area of 34 528 km2 in Hubei and Hunan provinces in south China. Then a color composite was produced by these three images. This kind of black-and-white and color images contained rich and definite geographic information. By a field work, the relationship between the colors on the composite and the land use/cover categories on the ground was established. 37 composite colors and 70 ground feature categories can be discriminated altogether. Finally, 17 land use/cover categories and 10 subregions suffering from soil gleization were determined, and the gleization area for the study area was estimated to be 731.3 km2.展开更多
Farmland reforestation can contribute substantially to ecological restoration.Previous studies have extensively examined the ecological effects of farmland reforestation,but few of them have investigated the spatiotem...Farmland reforestation can contribute substantially to ecological restoration.Previous studies have extensively examined the ecological effects of farmland reforestation,but few of them have investigated the spatiotemporal responses of broad-scale landscape connectivity to reforestation.By using a typical agro-pastoral ecotone in northern China as a case study,we addressed this issue based on an innovative integration of circuit theory approach and counterfactual analysis.The forest connectivity through multiple dispersal pathways was measured using the circuit theory approach,and its spatiotemporal changes after reforestation were evaluated by counterfactual analysis.The results showed that from 2000–2015,the reforested farmland occupied 2095 km^2,and 12.5% was on steeply sloped land.Farmland reforestation caused a greater increase in ecological connectivity by adding new ecological corridors and stepping stones in scattered forest areas rather than in areas with dense forest distributions.The newly added corridors and stepping stones were fragmented,short and narrow and thus deserve powerful protection.Future reforestation to improve landscape connectivity should highlight pinch point protection and obstacle removal as well as the tradeoff between farmland loss and farmer survival.Our findings are expected to inform the optimization of the Grain for Green policy from the perspective of broad-scale biodiversity conservation.展开更多
A methodology for the selection of the optimal land uses of the reclamation of mined areas is proposed. It takes into consideration several multi-nature criteria and constraints, including spatial constrains related t...A methodology for the selection of the optimal land uses of the reclamation of mined areas is proposed. It takes into consideration several multi-nature criteria and constraints, including spatial constrains related to the permissible land uses in certain parts of the mined area. The methodology combines desirability functions and evolution searching algorithms for selection of the optimal reclamation scheme. Its application for the reclamation planning of the Amynteon lignite surface mine in Greece indicated that it handles effectively spatial and non-spatial constraints and incorporates easily the decision-makers preferences regarding the reclamation strategy in the optimization procedure.展开更多
The application of satellite radiance assimilation can improve the simulation of precipitation by numerical weather prediction models. However, substantial quantities of satellite data, especially those derived from l...The application of satellite radiance assimilation can improve the simulation of precipitation by numerical weather prediction models. However, substantial quantities of satellite data, especially those derived from low-level（surface-sensitive）channels, are rejected for use because of the difficulty in realistically modeling land surface emissivity and energy budgets.Here, we used an improved land use and leaf area index（LAI） dataset in the WRF-3 DVAR assimilation system to explore the benefit of using improved quality of land surface information to improve rainfall simulation for the Shule River Basin in the northeastern Tibetan Plateau as a case study. The results for July 2013 show that, for low-level channels（e.g., channel 3）,the underestimation of brightness temperature in the original simulation was largely removed by more realistic land surface information. In addition, more satellite data could be utilized in the assimilation because the realistic land use and LAI data allowed more satellite radiance data to pass the deviation test and get used by the assimilation, which resulted in improved initial driving fields and better simulation in terms of temperature, relative humidity, vertical convection, and cumulative precipitation.展开更多
基金Project supported by the Tingthanathikul Foundation of Thailand, the Provincial Natural Science Foun- dation of Jiangxi (No. 0230025) the Open Research Foundation of Hubei Provincial Key Labaratory of Waterlogged Disaster and Wetland Agriculture (No. H
文摘A comprehensive method of image classification was developed for monitoring land use dynamics in Chanthaburi Province of Tailand. RS (Remote Sensing), GIS (Geographical Information System), GPS (Global Positioning System) and ancillary data were combined by the method which adopts the main idea of classifying images by steps from decision tree method and the hybridized supervised and unsupervised classification. An integration of automatic image interpretation, ancillary materials and expert knowledge was realized. Two subscenes of Landsat 5 Thematic Mapper (TM) images of bands 3, 4 and 5 obtained on December 15, 1992, and January 17, 1999, were used for image processing and spatial data analysis in the study. The overall accuracy of the results of classification reached 90%, which was verified by field check.Results showed that shrimp farm land, urban and traffic land, barren land, bush and agricultural developing area increased in area, mangrove, paddy field, swamp and marsh land, orchard and plantation, and tropical grass land decreased, and the forest land kept almost stable. Ecological analysis on the land use changes showed that more attentions should be paid on the effect of land development on ecological environment in the future land planning and management.
基金supported by the Deanship of Research and Graduate Studies at the King Khalid University(RGP2/287/46)the Princess Nourah bint Abdulrahman University Researchers Supporting Project(PNURSP2025R733)+1 种基金the Princess Nourah bint Abdulrahman University Research Supporting Project(RSPD2025R787)the King Saud University,Saudi Arabia.
文摘Challenges in land use and land cover(LULC)include rapid urbanization encroaching on agricultural land,leading to fragmentation and loss of natural habitats.However,the effects of urbanization on LULC of different crop types are less concerned.The study assessed the impacts of LULC changes on agriculture and drought vulnerability in the Aguascalientes region,Mexico,from 1994 to 2024,and predicted the LULC in 2034 using remote sensing data,with the goals of sustainable land management and climate resilience strategies.Despite increasing urbanization and drought,the integration of satellite imagery and machine learning models in LULC analysis has been underutilized in this region.Using Landsat imagery,we assessed crop attributes through indices such as normalized difference vegetation index(NDVI),normalized difference water index(NDWI),normalized difference moisture index(NDMI),and vegetation condition index(VCI),alongside watershed delineation and spectral features.The random forest model was applied to classify LULC,providing insights into both historical and future trends.Results indicated a significant decline in vegetation cover(109.13 km^(2))from 1994 to 2024,accompanied by an increase in built-up land(75.11 km^(2))and bare land(67.13 km^(2)).Projections suggested a further decline in vegetation cover(41.51 km^(2))and continued urban land expansion by 2034.The study found that paddy crops exhibited the highest values,while common bean and maize performed poorly.Drought analysis revealed that mildly dry areas in 2004 became severely dry in 2024,highlighting the increasing vulnerability of agriculture to climate change.The study concludes that sustainable land management,improved water resource practices,and advanced monitoring techniques are essential to mitigate the adverse effects of LULC changes on agricultural productivity and drought resilience in the area.These findings contribute to the understanding of how remote sensing can be effectively used for long-term agricultural planning and environmental sustainability.
文摘This study examines the spatial and temporal patterns of wetland degradation in Delhi from 1991 to 2021 using remote sensing and GIS techniques.The Automated Water Extraction Index(AWEI)was applied to pre-monsoon Landsat imagery to delineate surface water bodies over the past 30 years accurately.Supervised classification was employed to generate land use maps,while census data was utilized to analyze urbanization trends across the region.Classification accuracy was assessed using Google Earth reference data through a confusion matrix,ensuring the reliability of the land cover analysis.Results reveal a significant decline in wetland extent,especially in densely populated and rapidly urbanizing districts such as North West,South,and East Delhi.During this time,the urban population increased from 52.7% to 97.4%,accompanied by a 70.2% expansion of built-up areas,while wetlands contracted from 32.9 km^(2) to 30.2 km^(2).South Delhi experienced the most severe wetland loss,with water body coverage dropping from 0.800% to 0.025%,whereas North East and Central Delhi maintained higher wetland coverage due to the influence of the Yamuna River and targeted conservation efforts.The study highlights the strong linkage between urban growth and wetland decline,which threatens biodiversity,groundwater recharge,and ecological stability.These findings emphasize the urgent need for integrated urban planning and conservation policies to safeguard wetlands,thereby promoting sustainability and water security in the National Capital Region.
基金supported by the Ministry of Education,Culture,Research,and Technology Directorate General of Higher Education,Research,and Technology grant number[2147/UN2621/PN/2022].
文摘The simultaneous increase in development in Pesawaran Regency is closely correlated with the intense competi-tion for land use.However,low policy implementation effectiveness has led to construction beyond designated spatial plan.The study used a quantitative survey using Landsat images in 2016,2019,and 2022.The data analysis techniques used geographic information systems integrated with Artificial Neural Network(ANN)and Cellular Automata(CA)models.This study aims to predict land-use change in 2031,evaluate its alignment with spatial planning,and provide guidance for controlling land-use change.The results showed that there has been an increase in land use.In 2019,built-up land reached 7,069.65 Ha.The model shows its ability to predict land simulation and transformation,where it is predicted that built-up land in 2031 will experience an increase of up to 40.10%,so development and change cannot be avoided every year.This study also suggests that decision-makers and local governments should reconsider spatial planning strategies.This study shows that there have been many land use changes from 2016 to 2022.The model shows its ability to predict simulation and land transformation.When using the model,there are many changes in the land use area in 2031.This is due to wet agricultural land turning into built-up land by almost 70%.This study shows that road network influence land-use change.The cellular automata model managed to capture the complexity with simple rules.Predictions for future research should focus on conserving wetlands and primary forests.
基金National Natural Science Foundation of China,No.42101252。
文摘Rapid regional population shifts and spatial polarization have heightened pressure on cultivated land—a critical resource demanding urgent attention amid ongoing urban-rural transition.This study selects Jiangsu province,a national leader in both economic and agricultural development,as a case area to construct a multidimensional framework for assessing the recessive morphological characteristics of multifunctional cultivated land use.We examine temporal dynamics,spatial heterogeneity,and propose an integrated zoning strategy based on empirical analysis.The results reveal that:(1)The recessive morphology index shows a consistent upward trend,with structural breaks in 2007 and 2013,and a spatial shift from“higher in the east and lower in the west”to“higher in the south and lower in the north.”(2)Coordination among sub-dimensions of the index has steadily improved.(3)The index is expected to continue rising in the next decade,though at a slower pace.(4)To promote coordinated multidimensional land-use development,we recommend a policy framework that reinforces existing strengths,addresses weaknesses,and adapts zoning schemes to current spatial conditions.This research offers new insights into multifunctional cultivated land systems and underscores their role in enhancing human well-being,securing food supply,and supporting sustainable urban-rural integration.
基金The National Social Science Foundation of China(No.14AJY013)the Scientific Innovation Research of College Graduates in Jiangsu Province(No.CXLX13_126)
文摘In order to simulate the evolution of affordable housing land use a dynamic model that combines cellular automata CA and a multi-agent system MAS is established.This paper aims to utilize the approach of decision factors on site selection of affordable housing through a literature review to construct a hierarchy model of those factors identifying the weight of each factor by an analytic hierarchy process AHP .Based on those weight factors the CA-MAS model is designed. Nanjing city is taken as an example to verify the feasibility of the model.The results show that the CA-MAS model is pragmatic and effective in simulating evolution of affordable housing land use which also promotes the fundamental understanding and perception of the development of affordable housing and urbanization.
基金National Natural Science Foundation of China, No.41171149 No.41130748 Knowledge Innovation Program of the Chinese Academy of Sciences, No.KZCX2-YW-QN304
文摘Land use transition refers to the changes in land use morphology （both dominant morphology and recessive morphology） of a certain region over a certain period of time driven by socio-economic change and innovation, and it usually corresponds to the transition of socio-economic development phase. In China, farmland and rural housing land are the two major sources of land use transition. This paper analyzes the spatio-temporal coupling characteristics of farmland and rural housing land transition in China, using high-resolution Landsat TM （Thematic Mapper） data in 2000 and 2008, and the data from the Ministry of Land and Resources of China. The outcomes indicated that： （1） during 2000-2008, the correlation coefficient of farmland vs. rural housing land change is -0.921, and it shows that the change pattern of farmland and rural housing land is uncoordinated; （2） the result of Spearman rank correlation analysis shows that rural housing land change has played a major role in the mutual transformation of farmland and rural housing land; and （3） it shows a high-degree spatial coupling between farmland and rural housing land change in southeast China during 2000-2008. In general, farmland and rural housing land transition in China is driven by socio-economic, bio-physical and managerial three-dimensional driving factors through the interactions among rural population, farmland and rural housing land. However, the spatio-temporal coupling phenomenon and mechanism of farmland and rural housing land transition in China are largely due to the ＂dual-track＂ structure of rural-urban development.
基金Under the auspices of National Natural Science Foundation of China (No. 70903061,41171440)National Public Benefit (Land) Research Foundation of China (No. 201111014)Fundamental Research Funds for the Central Universities (No. 2011YXL055)
文摘This study investigated and simulated land use patterns in Beijing for the year 2000 and the year 2005 from the actual land use data for the year 1995 and the year 2000,respectively,by combining spatial land allocation simulation using the CLUE-S model,and numerical land demand prediction using the Markov model.The simulations for 2000 and 2005 were confirmed to be generally accurate using Kappa indices.Then the land-use scenarios for Beijing in 2015 were simulated assuming two modes of development:1) urban development following existing trends;and 2) under a strict farmland control.The simulations suggested that under either mode,urbanized areas would expand at the expense of land for other uses.This expansion was predicted to dominate the land-use conversions between 2005 and 2015,and was expected to be accompanied by an extensive loss of farmland.The key susceptible to land-use changes were found to be located at the central urban Beijing and the surrounding regions including Yanqing County,Changping District and Fangshan District.Also,the simulations predicted a considerable expansion of urban/suburban areas in the mountainous regions of Beijing,suggesting a need for priority monitoring and protection.
文摘Detailed analysis of Land Use/Land Cover （LULC） using remote sensing data in complex irrigated basins provides complete profile for better water resource management and planning. Using remote sensing data, this study provides detailed land use maps of the Lower Chenab Canal irrigated region of Pakistan from 2005 to 2012 for LULC change detection. Major crop types are demarcated by identifying temporal profiles of NDVI using MODIS 250 m × 250 m spatial resolution data. Wheat and rice are found to be major crops in rabi and kharif seasons, respectively. Accuracy assessment of prepared maps is performed using three dif- ferent techniques： error matrix approach, comparison with ancillary data and with previous study. Producer and user accuracies for each class are calculated along with kappa coeffi- cients （K）. The average overall accuracies for rabi and kharif are 82.83% and 78.21%, re- spectively. Producer and user accuracies for individual class range respectively between 72.5% to 77% and 70.1% to 84.3% for rabi and 76.6% to 90.2% and 72% to 84.7% for kharif. The K values range between 0.66 to 0.77 for rabi with average of 0.73, and from 0.69 to 0.74 with average of 0.71 for kharif. LULC change detection indicates that wheat and rice have less volatility of change in comparison with both rabi and kharif fodders. Transformation be- tween cotton and rice is less common due to their completely different cropping conditions. Results of spatial and temporal LULC distributions and their seasonal variations provide useful insights for establishing realistic LULC scenarios for hydrological studies.
文摘Landsat Thematic Mapper （TM） and Enhanced Thematic Mapper Plus （ETM＋） images in 1985, 1986, 1993, 1994 and 2001 were used to quantify the land use and land cover changes （LUCC） in the Zhejiang coastal region with a stratified unsupervised classification technique in conjunction with visual interpretation and to attempt an identification of the socioeconomic driving forces. In level I an overall accurate classification was achieved using a modified Anderson＇s Ⅰ/Ⅱ/Ⅲ-level classification scheme. The overall accuracy of the land use classification at Anderson level Ⅰ were 89.7% （1985）, 91.6% （1993）, and 90.4% （2001）. The most rapid land use change was a dramatic increase in urban or built-up areas, which quadrupled from 1985 to 2001. Over 90% of this newly expanded built-up area was originally paddy fields or other croplands. In different parts of the Zhejiang coastal region, urban land expansion was spatially uneven. Temporally, land use development did not stabilized, and the two study periods of time （1985-1993 and 1993-2001） had different transition styles. Socioeconomic factors, such as gross domestic product, total population, and financial expenditure, were all highly correlated with the expansion of urban or built-up areas. Based on the degree of urban sprawl and socioeconomic factors, cities and towns were further divided into six subgroups, which may help decision makers improve land use for the region.
文摘Fuqing County of southeast China has witnessed significant land use changes during the last decade. Re mote sensing technology using multitemporal Landsat TM images was used to characterize land use types and to monitor land use changes in the county. Two TM scenes from 1991 and 1996 were used to cover the county and a five-year time period. Digital image processing was carried out for the remotely sensed data to produce classified images. The images were further processed using GIS software to generate GIS databases so that the data could be further spatially analyzed taking the advantages of the software. Land use change areas were determined by using the change detection technique. The comparison of the two classified TM images using the above technologies reveals that during the five study years, a large area of arable lands in the county has been lost and deforestation has taken place largely because of the dramatic in crease in built-up land and orchard. The conclusive statistical information is useful to understand the processes, causes and impacts of the land use changes in the county. The major driving force to the land use changes in the county ap peared to be the rapid economic development. The decision makers of the county have to pay more attention to the land use changes for the county’s sustainable development.
基金supported by the National Natural Science Foundation of China (NSFC) (No.30571112).
文摘Due to inappropriate planning and management, accelerated urban growth and tremendous loss in land, especially cropland, have become a great challenge for sustainable urban development in China, especially in developed urban area in the coastal regions; therefore, there is an urgent need to effectively detect and monitor the land use changes and provide accurate and timely information for planning and management. In this study a method combining principal component analysis (PCA) of multisensor satellite images from SPOT (systeme pour l'observation de la terre or earth observation satellite)-5 multispectral (XS) and Landsat-7 enhanced thematic mapper (ETM) panchromatic (PAN) data, and supervised classification was used to detect and analyze the dynamics of land use changes in the city proper of Hangzhou. The overall accuracy of the land use change detection was 90.67% and Kappa index was 0.89. The results indicated that there was a considerable land use change (10.03% of the total area) in the study area from 2001 to 2003, with three major types of land use conversions: from cropland into built-up land, construction site, and water area (fish pond). Changes from orchard land into built-up land were also detected. The method described in this study is feasible and useful for detecting rapid land use change in the urban area.
基金the Key Laboratory Open Subjects of Xinjiang Uygur Autonomous Region Science and Technology Department(2020D04038)the Key Project of Natural Science Foundation of Xinjiang Uygur Autonomous Region(2021D01D06)the National Natural Science Foundation of China(41961059).
文摘The ecological quality of inland areas is an important aspect of the United Nations Sustainable Development Goals(UN SDGs).The ecological environment of Northwest China is vulnerable to changes in climate and land use/land cover,and the changes in ecological quality in this arid region over the last two decades are not well understood.This makes it more difficult to advance the UN SDGs and develop appropriate measures at the regional level.In this study,we used the Moderate Resolution Imaging Spectroradiometer(MODIS)products to generate remote sensing ecological index(RSEI)on the Google Earth Engine(GEE)platform to examine the relationship between ecological quality and environment in Xinjiang during the last two decades(from 2000 to 2020).We analyzed a 21-year time series of the trends and spatial characteristics of ecological quality.We further assessed the importance of different environmental factors affecting ecological quality through the random forest algorithm using data from statistical yearbooks and land use products.Our results show that the RSEI constructed using the GEE platform can accurately reflect the ecological quality information in Xinjiang because the contribution of the first principal component was higher than 90.00%.The ecological quality in Xinjiang has increased significantly over the last two decades,with the northern part of this region having a better ecological quality than the southern part.The areas with slightly improved ecological quality accounted for 31.26%of the total land area of Xinjiang,whereas only 3.55%of the land area was classified as having a slightly worsen(3.16%)or worsen(0.39%)ecological quality.The vast majority of the deterioration in ecological quality mainly occurred in the barren areas Temperature,precipitation,closed shrublands,grasslands and savannas were the top five environmental factors affecting the changes in RSEI.Environmental factors were allocated different weights for different RSEI categories.In general,the recovery of ecological quality in Xinjiang has been controlled by climate and land use/land cover during the last two decades and policy-driven ecological restoration is therefore crucial.Rapid monitoring of inland ecological quality using the GEE platform is projected to aid in the advancement of the comprehensive assessment of the UN SDGs.
基金This work is supported by the National Nature Science Foundation of China[grant number:41201432],the National Science Foundation of Tibet[grant number:2016ZR-TU-05]the Foundation for Innovative Research for Young Teachers in Higher Educational Institutions of Tibet[grant number:QCZ2016-07].
文摘This article attempts to detail time series characteristics of PM2.5 concentration in Guangzhou(China)from 1 June 2012 to 31 May 2013 based on wavelet analysis tools,and discuss its spatial distribution using geographic information system software and a modified land use regression model.In this modified model,an important variable(land use data)is substituted for impervious surface area,which can be obtained conveniently from remote sensing imagery through the linear spectral mixture analysis method.Impervious surface has higher precision than land use data because of its sub-pixel level.Seasonal concentration pattern and day-by-day change feature of PM2.5 in Guangzhou with a micro-perspective are discussed and understood.Results include:(1)the highest concentration of PM2.5 occurs in October and the lowest in July,respectively;(2)average concentration of PM2.5 in winter is higher than in other seasons;and(3)there are two high concentration zones in winter and one zone in spring.
基金This research was jointly supported by the National Natural Science Foundation of China(Grants No.U21A2011,41991233 and 41971129)the National Key Research and Development Program of China(Grant No.SQ2022YFF1300053)the Distinguished Membership Project of the Youth Innovation Promotion Association of Chinese Academy of Sci-ences(Grant No.Y201812).
文摘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.
基金Under the auspices of National Natural Science Foundation of China(No.41371097,40871048)
文摘Land change science （LCS） strives to understand and model land-use change, which will further advance the understanding of multiple issues in the socio-ecological systems. Based on GIS/RS techniques, autologistic model, and household survey method, this study investigated major land use changes and their causes from 1978 to 2008 in Uxin Banner （county-level）, Inner Mongolia in China and then developed an understanding of the relationships between household livelihood and land-use pattern. Results showed that cultivated land increased from 1988 to 2000, and leveled offafter 2000. Built-up land increased stably for the period 1978 2008. The change of grassland and bare land differed among the three periods. From 1978 to 1988, grassland increased by 23.3%, and bare land decreased by 20.48%. From 1988 to 2000, bare land expanded by 1.7%, but grassland declined by 1.3%. From 2000 to 2008, an increase in grassland area by 1.8% was observed, but a decrease in bare land area by 9.0% was witnessed. The autologistic models performed better than logistic models as indicated by lower Akaike Information Criterion （AIC） values. Factors associated with human activities significantly correlated with the change of cultivated land, forest land, grassland, and built-up land. The produce prices and extensive cultivated land use are major issues in the farming area. This study suggests that completing land circulation systems and maintaining the stability of price are effective solutions. By contrast, reclamation and overgrazing are major concerns in the pastoral areas. Implementing environmental policies effectively, transferring population out of rural pastoral areas, and developing modem animal husbandry are effective ways to address these issues.
文摘This paper describes a new type of transformed Landsat images (LBV images) and their application in discriminating soil gleization in subtropic region of China. LBV transformation was worked out by the present author for extracting useful information from original landsat images. Using this method three black and white images, L image, B image and V image, were computer generated from original bands of a Landsat scene, which covers a.large area of 34 528 km2 in Hubei and Hunan provinces in south China. Then a color composite was produced by these three images. This kind of black-and-white and color images contained rich and definite geographic information. By a field work, the relationship between the colors on the composite and the land use/cover categories on the ground was established. 37 composite colors and 70 ground feature categories can be discriminated altogether. Finally, 17 land use/cover categories and 10 subregions suffering from soil gleization were determined, and the gleization area for the study area was estimated to be 731.3 km2.
基金National Natural Science Foundation of China,No.41771429National Key Research and Development Project,No.2017YFB0503505。
文摘Farmland reforestation can contribute substantially to ecological restoration.Previous studies have extensively examined the ecological effects of farmland reforestation,but few of them have investigated the spatiotemporal responses of broad-scale landscape connectivity to reforestation.By using a typical agro-pastoral ecotone in northern China as a case study,we addressed this issue based on an innovative integration of circuit theory approach and counterfactual analysis.The forest connectivity through multiple dispersal pathways was measured using the circuit theory approach,and its spatiotemporal changes after reforestation were evaluated by counterfactual analysis.The results showed that from 2000–2015,the reforested farmland occupied 2095 km^2,and 12.5% was on steeply sloped land.Farmland reforestation caused a greater increase in ecological connectivity by adding new ecological corridors and stepping stones in scattered forest areas rather than in areas with dense forest distributions.The newly added corridors and stepping stones were fragmented,short and narrow and thus deserve powerful protection.Future reforestation to improve landscape connectivity should highlight pinch point protection and obstacle removal as well as the tradeoff between farmland loss and farmer survival.Our findings are expected to inform the optimization of the Grain for Green policy from the perspective of broad-scale biodiversity conservation.
文摘A methodology for the selection of the optimal land uses of the reclamation of mined areas is proposed. It takes into consideration several multi-nature criteria and constraints, including spatial constrains related to the permissible land uses in certain parts of the mined area. The methodology combines desirability functions and evolution searching algorithms for selection of the optimal reclamation scheme. Its application for the reclamation planning of the Amynteon lignite surface mine in Greece indicated that it handles effectively spatial and non-spatial constraints and incorporates easily the decision-makers preferences regarding the reclamation strategy in the optimization procedure.
基金supported by the National Key Research and Development Program of China(Grant No.2016YFA0602701)the National Natural Science Foundation of China(Grant Nos.41721091,41630754,91644225)the Open Program(Grant No.SKLCS-OP-2017-02)from the State Key Laboratory of Cryospheric Science,Northwest Institute of EcoEnvironment and Resources,Chinese Academy of Sciences
文摘The application of satellite radiance assimilation can improve the simulation of precipitation by numerical weather prediction models. However, substantial quantities of satellite data, especially those derived from low-level（surface-sensitive）channels, are rejected for use because of the difficulty in realistically modeling land surface emissivity and energy budgets.Here, we used an improved land use and leaf area index（LAI） dataset in the WRF-3 DVAR assimilation system to explore the benefit of using improved quality of land surface information to improve rainfall simulation for the Shule River Basin in the northeastern Tibetan Plateau as a case study. The results for July 2013 show that, for low-level channels（e.g., channel 3）,the underestimation of brightness temperature in the original simulation was largely removed by more realistic land surface information. In addition, more satellite data could be utilized in the assimilation because the realistic land use and LAI data allowed more satellite radiance data to pass the deviation test and get used by the assimilation, which resulted in improved initial driving fields and better simulation in terms of temperature, relative humidity, vertical convection, and cumulative precipitation.
