Chalet farming,as a specific type of agricultural landscape management,has been established in many European mountain ranges,including the Krkono?e Mountains and the Hruby Jeseník Mountains in Czechia.During the ...Chalet farming,as a specific type of agricultural landscape management,has been established in many European mountain ranges,including the Krkono?e Mountains and the Hruby Jeseník Mountains in Czechia.During the operation of such farming from 16/17th century till 1945,many changes in land use/land cover and landscape at all occurred,which are generally evaluated positively.Turbulent events including political,economic and social changes and the displacement of the German-speaking population associated with them in the mid-20th century rapidly ended this development,causing significant landscape changes,such as the abandonment of agricultural land and succession,afforestation,expansion of the alpine tree line,reduction of diversity.The aim of our study is to evaluate changes of land cover(forests,dwarf pine,grasslands,other areas)from 1936/1946 till 2021,secondary succession and driving forces of change for selected meadow enclaves in the Krkonose Mountains and the Hruby Jeseník Mountains after the decline of mountain chalet farming since the middle of 20th century.We used remote sensing methods(aerial imagery)and field research(dendrochronology and comparative photography)to detect the land use/land cover changes in the selected study areas in the Krkono?e Mountains and the Hruby Jeseník Mountains.We documented the process of the succession,which occurred almost immediately after the end of farming,peaking about 10–20 years later,with an earlier start in the Hruby Jeseník Mountains.The succession led to the significant change of land use/land cover and these processes were similar in both mountain ranges.The largest changes were a decrease in grasslands by 62%–64%and an increase in forest area by 33%–40%for both study areas.The abandonment of land is the main consequence of a crucial political driving forces(displacement of German-speaking population)in the Krkono?e Mountains and the Hruby Jeseník Mountains.展开更多
Human well-being and livelihoods depend on natural ecosystem services(ESs).Following the increment of population,ESs have been deteriorated over time.Ultimately,land use/land cover(LULC)changes have a profound impact ...Human well-being and livelihoods depend on natural ecosystem services(ESs).Following the increment of population,ESs have been deteriorated over time.Ultimately,land use/land cover(LULC)changes have a profound impact on the change of ecosystem.The primary goal of this study is to determine the impacts of LULC changes on ecosystem service values(ESVs)in the upper Gilgel Abbay watershed,Ethiopia.Changes in LULC types were studied using three Landsat images representing 1986,2003,and 2021.The Landsat images were classified using a supervised image classification technique in Earth Resources Data Analysis System(ERDAS)Imagine 2014.We classified ESs in this study into four categories(including provisioning,regulating,supporting,and cultural services)based on global ES classification scheme.The adjusted ESV coefficient benefit approach was employed to measure the impacts of LULC changes on ESVs.Five LULC types were identified in this study,including cultivated land,forest,shrubland,grassland,and water body.The result revealed that the area of cultivated land accounted for 64.50%,71.50%,and 61.50%of the total area in 1986,2003,and 2021,respectively.The percentage of the total area covered by forest was 9.50%,5.90%,and 14.80%in 1986,2003,and 2021,respectively.Result revealed that the total ESV decreased from 7.42×10^(7) to 6.44×10^(7) USD between 1986 and 2003.This is due to the expansion of cultivated land at the expense of forest and shrubland.However,the total ESV increased from 6.44×10^(7) to 7.76×10^(7) USD during 2003-2021,because of the increment of forest and shrubland.The expansion of cultivated land and the reductions of forest and shrubland reduced most individual ESs during 1986-2003.Nevertheless,the increase in forest and shrubland at the expense of cultivated land enhanced many ESs during 2003-2021.Therefore,the findings suggest that appropriate land use practices should be scaled-up to sustainably maintain ESs.展开更多
Riparian land use/land cover(LULC)plays a crucial role in maintaining riverine water quality by altering the transport of pollutants and nutrients.Nevertheless,establishing a direct relationship between water quality ...Riparian land use/land cover(LULC)plays a crucial role in maintaining riverine water quality by altering the transport of pollutants and nutrients.Nevertheless,establishing a direct relationship between water quality and LULC is challenging due to the multi-indicator nature of both factors.Water quality encompasses a multitude of physical,chemical,and biological parameters,while LULC represents a diverse array of land use types.Riparian habitat quality(RHQ)serves as an indicator of LULC.Yet,it remains to be seen whether RHQ can act as a proxy of LULC for assessing the impact of LULC on riverine water quality.This study examines the interplay between RHQ,LULC and water quality,and develops a comprehensive indicator to predict water quality.We measured several water quality parameters,including pH(potential of hydrogen),TN(total nitrogen),TP(total phosphorus),T_(water)(water temperature),DO(dissolved oxygen),and EC(electrical conductivity)of the Yue and Jinshui Rivers draining to the Han River during 2016,2017 and 2018.The water quality index(WQI)was further calculated.RHQ is assessed by the InVEST(Integrated Valuation of Ecosystem Services and Tradeoffs)model.Our study found noticeable seasonal differences in water quality,with a higher WQI observed in the dry season.The RHQ was strongly correlated with LULC compositions.RHQ positively correlated with WQI,and DO concentration and vegetation land were negatively correlated with T_(water),TN,TP,EC,cropland,and construction land.These correlations were stronger in the rainy season.Human-dominated land,such as construction land and cropland,significantly contributed to water quality degradation,whereas vegetation promoted water quality.Regression models showed that the RHQ explained variations in WQI better than LULC types.Our study concludes that RHQ is a new and comprehensive indicator for predicting the dynamics of riverine water quality.展开更多
The Turpan-Hami(Tuha)Basin in Xinjiang Uygur Autonomous Region of China,holds significant strategic importance as a key economic artery of the ancient Silk Road and the Belt and Road Initiative,necessitating a holisti...The Turpan-Hami(Tuha)Basin in Xinjiang Uygur Autonomous Region of China,holds significant strategic importance as a key economic artery of the ancient Silk Road and the Belt and Road Initiative,necessitating a holistic understanding of the spatiotemporal evolution of land use/land cover(LULC)to foster sustainable planning that is tailored to the region's unique resource endowments.However,existing LULC classification methods demonstrate inadequate accuracy,hindering effective regional planning.In this study,we established a two-level LULC classification system(8 primary types and 22 secondary types)for the Tuha Basin.By employing Landsat 5/7/8 imagery at 5-a intervals,we developed the LULC dataset of the Tuha Basin from 1990 to 2020,conducted the accuracy assessment and spatiotemporal evolution analysis,and simulated the future LULC under various scenarios via the Markov-Future Land Use Simulation(Markov-FLUS)model.The results revealed that the average overall accuracy values of our LULC dataset were 0.917 and 0.864 for the primary types and secondary types,respectively.Compared with the seven mainstream LULC products(GlobeLand30,Global 30-meter Land Cover with Fine Classification System(GLC_FCS30),Finer Resolution Observation and Monitoring of Global Land Cover PLUS(FROM_GLC PLUS),ESA Global Land Cover(ESA_LC),Esri Land Cover(ESRI_LC),China Multi-Period Land Use Land Cover Change Remote Sensing Monitoring Dataset(CNLUCC),and China Annual Land Cover Dataset(CLCD))in 2020,our LULC data exhibited dramatically elevated overall accuracy and provided more precise delineations for land features,thereby yielding high-quality data backups for land resource analyses within the basin.In 2020,unused land(78.0%of the study area)and grassland(18.6%)were the dominant LULC types of the basin;although cropland and construction land constituted less than 1.0%of the total area,they played a vital role in arid land development and primarily situated within oases that form the urban cores of the cities of Turpan and Hami.Between 1990 and 2020,cropland and construction land exhibited a rapid expansion,and the total area of water body decreased yet resurging after 2015 due to an increase in areas of reservoir and pond.In future scenario simulations,significant increases in areas of construction land and cropland are anticipated under the business-as-usual scenario,whereas the wetland area will decrease,suggesting the need for ecological attention under this development pathway.In contrast,the economic development scenario underscores the fast-paced expansion of construction land,primarily from the conversion of unused land,highlighting the significant developmental potential of unused land with a slowing increase in cropland.Special attention should thus be directed toward ecological and cropland protection during development.This study provides data supports and policy recommendations for the sustainable development goals of Tuha Basin and other similar arid areas.展开更多
Land use/land cover represents the interactive and comprehensive influences between human activities and natural conditions,leading to potential conflicts among natural and human-related issues as well as among stakeh...Land use/land cover represents the interactive and comprehensive influences between human activities and natural conditions,leading to potential conflicts among natural and human-related issues as well as among stakeholders.This study introduced economic standards for farmers.A hybrid approach(CA-ABM)of cellular automaton(CA)and an agent-based model(ABM)was developed to effectively deal with social and land-use synergic issues to examine human–environment interactions and projections of land-use conversions for a humid basin in south China.Natural attributes and socioeconomic data were used to analyze land use/land cover and its drivers of change.The major modules of the CA-ABM are initialization,migration,assets,land suitability,and land-use change decisions.Empirical estimates of the factors influencing the urban land-use conversion probability were captured using parameters based on a spatial logistic regression(SLR)model.Simultaneously,multicriteria evaluation(MCE)and Markov models were introduced to obtain empirical estimates of the factors affecting the probability of ecological land conversion.An agent-based CA-SLR-MCE-Markov(ABCSMM)land-use conversion model was proposed to explore the impacts of policies on land-use conversion.This model can reproduce observed land-use patterns and provide links for forest transition and urban expansion to land-use decisions and ecosystem services.The results demonstrated land-use simulations under multi-policy scenarios,revealing the usefulness of the model for normative research on land-use management.展开更多
With the increasing number of remote sensing satellites,the diversification of observation modals,and the continuous advancement of artificial intelligence algorithms,historically opportunities have been brought to th...With the increasing number of remote sensing satellites,the diversification of observation modals,and the continuous advancement of artificial intelligence algorithms,historically opportunities have been brought to the applications of earth observation and information retrieval,including climate change monitoring,natural resource investigation,ecological environment protection,and territorial space planning.Over the past decade,artificial intelligence technology represented by deep learning has made significant contributions to the field of Earth observation.Therefore,this review will focus on the bottlenecks and development process of using deep learning methods for land use/land cover mapping of the Earth’s surface.Firstly,it introduces the basic framework of semantic segmentation network models for land use/land cover mapping.Then,we summarize the development of semantic segmentation models in geographical field,focusing on spatial and semantic feature extraction,context relationship perception,multi-scale effects modelling,and the transferability of models under geographical differences.Then,the application of semantic segmentation models in agricultural management,building boundary extraction,single tree segmentation and inter-species classification are reviewed.Finally,we discuss the future development prospects of deep learning technology in the context of remote sensing big data.展开更多
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...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.展开更多
Rapid urbanization creates complexity,results in dynamic changes in land and environment,and influences the land surface temperature(LST)in fast-developing cities.In this study,we examined the impact of land use/land ...Rapid urbanization creates complexity,results in dynamic changes in land and environment,and influences the land surface temperature(LST)in fast-developing cities.In this study,we examined the impact of land use/land cover(LULC)changes on LST and determined the intensity of urban heat island(UHI)in New Town Kolkata(a smart city),eastern India,from 1991 to 2021 at 10-a intervals using various series of Landsat multi-spectral and thermal bands.This study used the maximum likelihood algorithm for image classification and other methods like the correlation analysis and hotspot analysis(Getis–Ord Gi^(*) method)to examine the impact of LULC changes on urban thermal environment.This study noticed that the area percentage of built-up land increased rapidly from 21.91%to 45.63%during 1991–2021,with a maximum positive change in built-up land and a maximum negative change in sparse vegetation.The mean temperature significantly increased during the study period(1991–2021),from 16.31℃to 22.48℃in winter,29.18℃to 34.61℃in summer,and 19.18℃to 27.11℃in autumn.The result showed that impervious surfaces contribute to higher LST,whereas vegetation helps decrease it.Poor ecological status has been found in built-up land,and excellent ecological status has been found in vegetation and water body.The hot spot and cold spot areas shifted their locations every decade due to random LULC changes.Even after New Town Kolkata became a smart city,high LST has been observed.Overall,this study indicated that urbanization and changes in LULC patterns can influence the urban thermal environment,and appropriate planning is needed to reduce LST.This study can help policy-makers create sustainable smart cities.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
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 study explored the land use/land cover(LULC)separability by the machine-generated and user-generated Flickr photo tags(i.e.the auto-tags and the user-tags,respectively),based on an authoritative LULC dataset for ...This study explored the land use/land cover(LULC)separability by the machine-generated and user-generated Flickr photo tags(i.e.the auto-tags and the user-tags,respectively),based on an authoritative LULC dataset for San Diego County in the United States.Ten types of LULCs were derived from the authoritative dataset.It was observed that certain types of the reclassified LULCs had abundant tags(e.g.the parks)or a high tag density(e.g.the commercial lands),compared with the less populated ones(e.g.the agricultural lands).Certain highly weighted terms of the tags derived based on a term frequency–inverse document frequency weighting scheme were helpful for identifying specific types of the LULCs,especially for the commercial recreation lands(e.g.the zoos).However,given the 10 sets of tags retrieved from the corresponding 10 types of LULCs,one set of tags(all the tags located at one specific type of the LULCs)could not fully delineate the corresponding LULC due to semantic overlaps,according to a latent semantic analysis.展开更多
The NCAR Community Atmosphere Model(CAM4.0)was used to investigate the climate efects of land use/land cover change(LUCC).Two simulations,one with potential land cover without significant human intervention and the ot...The NCAR Community Atmosphere Model(CAM4.0)was used to investigate the climate efects of land use/land cover change(LUCC).Two simulations,one with potential land cover without significant human intervention and the other with current land use,were conducted.Results show that the impacts of LUCC on diurnal temperature range(DTR)are more significant than on mean surface air temperature.The global average annual DTR change due to LUCC is–0.1℃,which is three times as large as the mean temperature change.LUCC influences regional DTR as simulated by the model.In the mid-latitudes,LUCC leads to a decrease in DTR,which is mainly caused by the reduction in daily maximum temperature.However,there are some diferences in the low latitudes.The reduction in DTR in East Asia is mainly the result of the decrease in daily maximum temperature,while in India,the decrease in DTR is due to the increase in daily minimum temperature.In general,the LUCC significantly controls the DTR change through the changes in canopy evaporation and transpiration.展开更多
This study assesses the changes in land use/land cover(LULC) and land surface temperature(LST) to identify their impacts from 2000 to 2020 along the coast of Kanyakumari district, India using remote sensing techniques...This study assesses the changes in land use/land cover(LULC) and land surface temperature(LST) to identify their impacts from 2000 to 2020 along the coast of Kanyakumari district, India using remote sensing techniques. Landsat images are used to estimate the LULC changes and the MODIS data for LST.The Maximum Likelihood Classification(MLC) method is used, and the LULC is classified into six categories: Agriculture Land, Barren Land, Salt Pan, Sandy Beach, Settlement, and Waterbody. Within the two decades of the present change detection study, upheave in the Settlement area of 49.89% is noticed, and the Agriculture Land is exploited by 20.09%. Salt Pan emits a high LST of 31.57°C, and the Waterbodies are noticed with a low LST of 28.9°C. However, the overall rate of LST decreased by 0.56°C during this period. This study will help policymakers make appropriate planning and management to overcome the impact of LULC and LST in the forthcoming years.展开更多
Annual Land Use/Land Cover(LULC)change information at medium spatial resolution(i.e.,at 30 m)is used in applications ranging from land management to achieving sustainable development goals related to food security.How...Annual Land Use/Land Cover(LULC)change information at medium spatial resolution(i.e.,at 30 m)is used in applications ranging from land management to achieving sustainable development goals related to food security.However,obtaining annual LULC information over large areas and long periods is challenging due to limitations on computational capabilities,training data,and workflow design.Using the Google Earth Engine(GEE),which provides a catalog of multi-source data and a cloud-based environment,we developed a novel methodology to generate a high accuracy 30-m LULC cover map collection of the Yangtze River Delta by integrating free and public LULC products with Landsat imagery.Our major contribution is a hybrid approach that includes three major components:1)a high-quality training dataset derived from multi-source LULC products,filtered by k-means clustering analysis;2)a yearly 39-band stack feature space,utilizing all available Landsat data and DEM data;and 3)a self-adaptive Random Forest(RF)method,introduced for LULC classification.Experimental results show that our proposed workflow achieves an average classification accuracy of 86.33%in the entire Delta.The results demonstrate the great potential of integrating multi-source LULC products for producing LULC maps of increased reliability.In addition,as the proposed workflow is based on open source data and the GEE cloud platform,it can be used anywhere by anyone in the world.展开更多
The world’s largest mangrove ecosystem,the Sunderbans is experiencing multidimensional threats of degradation.The present study was aimed to understand these problems and search for proper remedies by applying suitab...The world’s largest mangrove ecosystem,the Sunderbans is experiencing multidimensional threats of degradation.The present study was aimed to understand these problems and search for proper remedies by applying suitable remote sensing technologies.South-western parts of Indian Sunderbans Biosphere Reserve had been chosen for assessment of land use/land cover changes in between 1975 and 2006 by using multitemporal Landsat data.Results indicated considerable reduction of open mangrove stands and associated biodiversity mainly in the forest-habitation interference zones of Sunderbans.On the contrary,increase in the coverage of dense mangroves in the reserved forests had been observed indicating the existence of proper centralized management regimes.Overall,a cumulative loss of approximately 0.42%of its original mangrove cover in between 1975 and 2006 had been estimated for this part of the Sunderbans which was at parity with the findings of other studies in the Sunderbans or similar mangrove ecosystems of the tropics.Expansion of non agricultural lands in the last two decades was found to be related with the growth of new settlements,tourism infrastructure,and facilities.This transformation was attributed to the shifting of local peoples’interest from traditional forestry and subsistence farming towards alternative occupations like shrimp culture,coastal tourism,and commercial fishing although environmentally hazardous livelihood activities like collection of prawn seeds along the riverbanks were still persistent.展开更多
The availability of better economic possibilities and well-connected transportation networks has attracted people to migrate to peri-urban and rural neighbourhoods,changing the landscape of regions outside the city an...The availability of better economic possibilities and well-connected transportation networks has attracted people to migrate to peri-urban and rural neighbourhoods,changing the landscape of regions outside the city and fostering the growth of physical infrastructure.Using multi-temporal satellite images,the dynamics of Land Use/Land Cover(LULC)changes,the impact of urban growth on LULC changes,and regional environmental implications were investigated in the peri-urban and rural neighbourhoods of Durgapur Municipal Corporation in India.The study used different case studies to highlight the study area’s heterogeneity,as the phenomenon of change is not consistent.Landsat TM and OLI-TIRS satellite images in 1991,2001,2011,and 2021 were used to analyse the changes in LULC types.We used the relative deviation(RD),annual change intensity(ACI),uniform intensity(UI)to show the dynamicity of LULC types(agriculture land;built-up land;fallow land;vegetated land;mining area;and water bodies)during 1991-2021.This study also applied the Decision-Making Trial and Evaluation Laboratory(DEMATEL)to measure environmental sensitivity zones and find out the causes of LULC changes.According to LULC statistics,agriculture land,built-up land,and mining area increased by 51.7,95.46,and 24.79 km^(2),respectively,from 1991 to 2021.The results also suggested that built-up land and mining area had the greatest land surface temperature(LST),whereas water bodies and vegetated land showed the lowest LST.Moreover,this study looked at the relationships among LST,spectral indices(Normalized Differenced Built-up Index(NDBI),Normalized Difference Vegetation Index(NDVI),and Normalized Difference Water Index(NDWI)),and environmental sensitivity.The results showed that all of the spectral indices have the strongest association with LST,indicating that built-up land had a far stronger influence on the LST.The spectral indices indicated that the decreasing trends of vegetated land and water bodies were 4.26 and 0.43 km^(2)/a,respectively,during 1991-2021.In summary,this study can help the policy-makers to predict the increasing rate of temperature and the causes for the temperature increase with the rapid expansion of built-up land,thus making effective peri-urban planning decisions.展开更多
This study aims to examine the use of Remote Sensing and Geographical Information System (GIS) technology in land use/land cover mapping to aide sustainable planning and development in the Wafi-Golpu project area. At ...This study aims to examine the use of Remote Sensing and Geographical Information System (GIS) technology in land use/land cover mapping to aide sustainable planning and development in the Wafi-Golpu project area. At the same time, this study examines an existing method of Forest Canopy Density (FCD) model to estimate forest canopy density of the proposed deforestation site, which is known as the Advanced Exploration Feasibility Study Activities (AEFSA) area within the Wafi-Golpu Project site. The FCD model calculates the forest canopy density using the three (3) indices of vegetation, soil and shadow from the Landsat-8 Operational Land Imager (OLI) satellite image of year 2013. In this study an attempt has been made to monitor the forest loss or degradation during deforestation in a natural forest stand of the Wafi-Golpu project area using forest FCD mapping and monitoring model and the findings of the study will assist the project planners and developers with their work on forest rehabilitation and reforestation for the purposes of sustainable forest management. The result of the work shows that a considerable amount of forest loss will be undertaken during the AEFSA deforestation exercise and also the findings show that a reliable land use/land cover map will greatly assist sustainable development in a resource project development period.展开更多
The study was aimed at appraising the changing land use/land cover scenario of Tummalapalle region in Cuddapah district of Andhra Pradesh using Remote sensing data and GIS technology. The region is considered as it ha...The study was aimed at appraising the changing land use/land cover scenario of Tummalapalle region in Cuddapah district of Andhra Pradesh using Remote sensing data and GIS technology. The region is considered as it has rich uranium reserves and is experiencing a remarkable expansion in recent times. The land use/land cover change analysis was carried out using IRS P6 LISS-III and LANDSAT-8 OLI multitemporal data pertaining to the years 2006 and 2016. The image classification resulted in five major land use/land cover classes namely built-up, agricultural, forest, wasteland and water bodies. The study noticed that the areas under built-up and agricultural classes are found increased from 0.94 km<sup>2</sup> (0.84%) to 2.75 km<sup>2</sup> (2.44%) and 61.68 km<sup>2</sup> (54.84%) to 63.91 km<sup>2</sup> (56.82%), respectively during 2006-2016. Area under forest, wasteland and water bodies are found decreased considerably from 3.09 km<sup>2</sup> (2.75%) to 0.86 km<sup>2</sup> (0.76%), 43.71 km<sup>2</sup> (38.56%) to 42.60 km<sup>2</sup> (37.88%) and 3.05 km<sup>2</sup> (2.71%) to 2.35 km<sup>2</sup> (2.09%), respectively. The study recommends development of industrial based economy by optimally utilizing the existing land resource (scrub and wasteland classes) and simultaneously extending the agricultural practices to other possible areas to make them more productive.展开更多
In the context of global change,it is essential to promote the rational development and utilization of land resources,improve the quality of regional ecological environment,and promote the harmonious development of hu...In the context of global change,it is essential to promote the rational development and utilization of land resources,improve the quality of regional ecological environment,and promote the harmonious development of human and nature for the regional sustainability.We identified land use/land cover types in northern China from 2001 to 2018 with ENVI images and ArcGIS software.Meteorological data were selected from 292 stations in northern China,the potential evapotranspiration was calculated with the Penman-Monteith formula,and reanalysis humidity and observed humidity data were obtained.The reanalysis minus observation(RMO,i.e.,the difference between reanalysis humidity and observed humidity)can effectively characterize the impact of different land use/land cover types(forestland,grassland,cultivated land,construction land,water body and unused land)on surface humidity in northern China in the early 21^(st) century.The results showed that from 2001 to 2018,the area of forestland expanded(increasing by approximately 1.80×10^(4) km^(2)),while that of unused land reduced(decreasing by approximately 5.15×10^(4) km^(2)),and the regional ecological environment was improved.Consequently,land surface in most areas of northern China tended to be wetter.The contributions of land use/land cover types to surface humidity changes were related to the quality of the regional ecological environment.The contributions of the six land use/land cover types to surface humidity were the highest in northeastern region of northern China,with a better ecological environment,and the lowest in northwestern region,with a fragile ecological environment.Surface humidity was closely related to the variation in regional vegetation coverage;when the regional vegetation coverage with positive(negative)contributions expanded(reduced),the land surface became wetter.The positive contributions of forestland and water body to surface humidity were the greatest.Unused land and construction land were associated with the most serious negative contributions to surface humidity.Affected by the regional distribution pattern of vegetation,surface humidity in different seasons decreased from east to west in northern China.The seasonal variation in surface humidity was closely related to the growth of vegetation:surface humidity was the highest in summer,followed by autumn and spring,and the lowest in winter.According to the results,surface humidity is expected to increase in northeastern region of northern China,decrease in northern region,and likely increase in northwestern region.展开更多
The Tarim River is the longest inland river in China and is considered as an important river to protect the oasis economy and environment of the Tarim Basin.However,excessive exploitation and over-utilization of natur...The Tarim River is the longest inland river in China and is considered as an important river to protect the oasis economy and environment of the Tarim Basin.However,excessive exploitation and over-utilization of natural resources,particularly water resources,have triggered a series of ecological and environmental problems,such as the reduction in the volume of water in the main river,deterioration of water quality,drying up of downstream rivers,degradation of vegetation,and land desertification.In this study,the land use/land cover change(LUCC)responses to ecological water conveyance in the lower reaches of the Tarim River were investigated using ENVI(Environment for Visualizing Images)and GIS(Geographic Information System)data analysis software for the period of 1990-2018.Multi-temporal remote sensing images and ecological water conveyance data from 1990 to 2018 were used.The results indicate that LUCC covered an area of 2644.34 km^(2) during this period,accounting for 15.79%of the total study area.From 1990 to 2018,wetland,farmland,forestland,and artificial surfaces increased by 533.42 km^(2)(216.77%),446.68 km^(2)(123.66%),284.55 km^(2)(5.67%),and 57.51 km^(2)(217.96%),respectively,whereas areas covered by grassland and other land use/land cover types,such as Gobi,bare soil,and deserts,decreased by 103.34 km2(14.31%)and 1218.83 km2(11.75%),respectively.Vegetation area decreased first and then increased,with the order of 2010<2000<1990<2018.LUCC in the overflow and stagnant areas in the lower reaches of the Tarim River was mainly characterized by fragmentation,irregularity,and complexity.By analyzing the LUCC responses to 19 rounds of ecological water conveyance in the lower reaches of the Tarim River from 2000 to the end of 2018,we proposed guidelines for the rational development and utilization of water and soil resources and formulation of strategies for the sustainable development of the lower reaches of the Tarim River.This study provides scientific guidance for optimal scheduling of water resources in the region.展开更多
基金funded by the European Commission,CINEA Horizon Europe project no.101081307“Towards Sustainable Land-Use in the Context of Climate Change and Biodiversity in Europe(Europe-LAND)”。
文摘Chalet farming,as a specific type of agricultural landscape management,has been established in many European mountain ranges,including the Krkono?e Mountains and the Hruby Jeseník Mountains in Czechia.During the operation of such farming from 16/17th century till 1945,many changes in land use/land cover and landscape at all occurred,which are generally evaluated positively.Turbulent events including political,economic and social changes and the displacement of the German-speaking population associated with them in the mid-20th century rapidly ended this development,causing significant landscape changes,such as the abandonment of agricultural land and succession,afforestation,expansion of the alpine tree line,reduction of diversity.The aim of our study is to evaluate changes of land cover(forests,dwarf pine,grasslands,other areas)from 1936/1946 till 2021,secondary succession and driving forces of change for selected meadow enclaves in the Krkonose Mountains and the Hruby Jeseník Mountains after the decline of mountain chalet farming since the middle of 20th century.We used remote sensing methods(aerial imagery)and field research(dendrochronology and comparative photography)to detect the land use/land cover changes in the selected study areas in the Krkono?e Mountains and the Hruby Jeseník Mountains.We documented the process of the succession,which occurred almost immediately after the end of farming,peaking about 10–20 years later,with an earlier start in the Hruby Jeseník Mountains.The succession led to the significant change of land use/land cover and these processes were similar in both mountain ranges.The largest changes were a decrease in grasslands by 62%–64%and an increase in forest area by 33%–40%for both study areas.The abandonment of land is the main consequence of a crucial political driving forces(displacement of German-speaking population)in the Krkono?e Mountains and the Hruby Jeseník Mountains.
文摘Human well-being and livelihoods depend on natural ecosystem services(ESs).Following the increment of population,ESs have been deteriorated over time.Ultimately,land use/land cover(LULC)changes have a profound impact on the change of ecosystem.The primary goal of this study is to determine the impacts of LULC changes on ecosystem service values(ESVs)in the upper Gilgel Abbay watershed,Ethiopia.Changes in LULC types were studied using three Landsat images representing 1986,2003,and 2021.The Landsat images were classified using a supervised image classification technique in Earth Resources Data Analysis System(ERDAS)Imagine 2014.We classified ESs in this study into four categories(including provisioning,regulating,supporting,and cultural services)based on global ES classification scheme.The adjusted ESV coefficient benefit approach was employed to measure the impacts of LULC changes on ESVs.Five LULC types were identified in this study,including cultivated land,forest,shrubland,grassland,and water body.The result revealed that the area of cultivated land accounted for 64.50%,71.50%,and 61.50%of the total area in 1986,2003,and 2021,respectively.The percentage of the total area covered by forest was 9.50%,5.90%,and 14.80%in 1986,2003,and 2021,respectively.Result revealed that the total ESV decreased from 7.42×10^(7) to 6.44×10^(7) USD between 1986 and 2003.This is due to the expansion of cultivated land at the expense of forest and shrubland.However,the total ESV increased from 6.44×10^(7) to 7.76×10^(7) USD during 2003-2021,because of the increment of forest and shrubland.The expansion of cultivated land and the reductions of forest and shrubland reduced most individual ESs during 1986-2003.Nevertheless,the increase in forest and shrubland at the expense of cultivated land enhanced many ESs during 2003-2021.Therefore,the findings suggest that appropriate land use practices should be scaled-up to sustainably maintain ESs.
基金supported by the National Natural Science Foundation of China(Grant No.31670473)the Wuhan Institute of Technology funding to Dr.Siyue Li(Grant No.21QD02).
文摘Riparian land use/land cover(LULC)plays a crucial role in maintaining riverine water quality by altering the transport of pollutants and nutrients.Nevertheless,establishing a direct relationship between water quality and LULC is challenging due to the multi-indicator nature of both factors.Water quality encompasses a multitude of physical,chemical,and biological parameters,while LULC represents a diverse array of land use types.Riparian habitat quality(RHQ)serves as an indicator of LULC.Yet,it remains to be seen whether RHQ can act as a proxy of LULC for assessing the impact of LULC on riverine water quality.This study examines the interplay between RHQ,LULC and water quality,and develops a comprehensive indicator to predict water quality.We measured several water quality parameters,including pH(potential of hydrogen),TN(total nitrogen),TP(total phosphorus),T_(water)(water temperature),DO(dissolved oxygen),and EC(electrical conductivity)of the Yue and Jinshui Rivers draining to the Han River during 2016,2017 and 2018.The water quality index(WQI)was further calculated.RHQ is assessed by the InVEST(Integrated Valuation of Ecosystem Services and Tradeoffs)model.Our study found noticeable seasonal differences in water quality,with a higher WQI observed in the dry season.The RHQ was strongly correlated with LULC compositions.RHQ positively correlated with WQI,and DO concentration and vegetation land were negatively correlated with T_(water),TN,TP,EC,cropland,and construction land.These correlations were stronger in the rainy season.Human-dominated land,such as construction land and cropland,significantly contributed to water quality degradation,whereas vegetation promoted water quality.Regression models showed that the RHQ explained variations in WQI better than LULC types.Our study concludes that RHQ is a new and comprehensive indicator for predicting the dynamics of riverine water quality.
基金supported by the Third Xinjiang Scientific Expedition Program (2022xjkk1100)the Tianchi Talent Project
文摘The Turpan-Hami(Tuha)Basin in Xinjiang Uygur Autonomous Region of China,holds significant strategic importance as a key economic artery of the ancient Silk Road and the Belt and Road Initiative,necessitating a holistic understanding of the spatiotemporal evolution of land use/land cover(LULC)to foster sustainable planning that is tailored to the region's unique resource endowments.However,existing LULC classification methods demonstrate inadequate accuracy,hindering effective regional planning.In this study,we established a two-level LULC classification system(8 primary types and 22 secondary types)for the Tuha Basin.By employing Landsat 5/7/8 imagery at 5-a intervals,we developed the LULC dataset of the Tuha Basin from 1990 to 2020,conducted the accuracy assessment and spatiotemporal evolution analysis,and simulated the future LULC under various scenarios via the Markov-Future Land Use Simulation(Markov-FLUS)model.The results revealed that the average overall accuracy values of our LULC dataset were 0.917 and 0.864 for the primary types and secondary types,respectively.Compared with the seven mainstream LULC products(GlobeLand30,Global 30-meter Land Cover with Fine Classification System(GLC_FCS30),Finer Resolution Observation and Monitoring of Global Land Cover PLUS(FROM_GLC PLUS),ESA Global Land Cover(ESA_LC),Esri Land Cover(ESRI_LC),China Multi-Period Land Use Land Cover Change Remote Sensing Monitoring Dataset(CNLUCC),and China Annual Land Cover Dataset(CLCD))in 2020,our LULC data exhibited dramatically elevated overall accuracy and provided more precise delineations for land features,thereby yielding high-quality data backups for land resource analyses within the basin.In 2020,unused land(78.0%of the study area)and grassland(18.6%)were the dominant LULC types of the basin;although cropland and construction land constituted less than 1.0%of the total area,they played a vital role in arid land development and primarily situated within oases that form the urban cores of the cities of Turpan and Hami.Between 1990 and 2020,cropland and construction land exhibited a rapid expansion,and the total area of water body decreased yet resurging after 2015 due to an increase in areas of reservoir and pond.In future scenario simulations,significant increases in areas of construction land and cropland are anticipated under the business-as-usual scenario,whereas the wetland area will decrease,suggesting the need for ecological attention under this development pathway.In contrast,the economic development scenario underscores the fast-paced expansion of construction land,primarily from the conversion of unused land,highlighting the significant developmental potential of unused land with a slowing increase in cropland.Special attention should thus be directed toward ecological and cropland protection during development.This study provides data supports and policy recommendations for the sustainable development goals of Tuha Basin and other similar arid areas.
基金supported by the Program for Guangdong Introducing Innovative and Entrepreneurial Teams(2021ZT090543)the National Natural Science Foundation of China(U20A20117)the Key-Area Research and Development Program of Guangdong Province(2020B1111380003).
文摘Land use/land cover represents the interactive and comprehensive influences between human activities and natural conditions,leading to potential conflicts among natural and human-related issues as well as among stakeholders.This study introduced economic standards for farmers.A hybrid approach(CA-ABM)of cellular automaton(CA)and an agent-based model(ABM)was developed to effectively deal with social and land-use synergic issues to examine human–environment interactions and projections of land-use conversions for a humid basin in south China.Natural attributes and socioeconomic data were used to analyze land use/land cover and its drivers of change.The major modules of the CA-ABM are initialization,migration,assets,land suitability,and land-use change decisions.Empirical estimates of the factors influencing the urban land-use conversion probability were captured using parameters based on a spatial logistic regression(SLR)model.Simultaneously,multicriteria evaluation(MCE)and Markov models were introduced to obtain empirical estimates of the factors affecting the probability of ecological land conversion.An agent-based CA-SLR-MCE-Markov(ABCSMM)land-use conversion model was proposed to explore the impacts of policies on land-use conversion.This model can reproduce observed land-use patterns and provide links for forest transition and urban expansion to land-use decisions and ecosystem services.The results demonstrated land-use simulations under multi-policy scenarios,revealing the usefulness of the model for normative research on land-use management.
基金National Natural Science Foundation of China(Nos.42371406,42071441,42222106,61976234).
文摘With the increasing number of remote sensing satellites,the diversification of observation modals,and the continuous advancement of artificial intelligence algorithms,historically opportunities have been brought to the applications of earth observation and information retrieval,including climate change monitoring,natural resource investigation,ecological environment protection,and territorial space planning.Over the past decade,artificial intelligence technology represented by deep learning has made significant contributions to the field of Earth observation.Therefore,this review will focus on the bottlenecks and development process of using deep learning methods for land use/land cover mapping of the Earth’s surface.Firstly,it introduces the basic framework of semantic segmentation network models for land use/land cover mapping.Then,we summarize the development of semantic segmentation models in geographical field,focusing on spatial and semantic feature extraction,context relationship perception,multi-scale effects modelling,and the transferability of models under geographical differences.Then,the application of semantic segmentation models in agricultural management,building boundary extraction,single tree segmentation and inter-species classification are reviewed.Finally,we discuss the future development prospects of deep learning technology in the context of remote sensing big data.
基金partly funded by the National Key Research and Development Program of China(NK2023190801)the National Foreign Experts Program of China(G2023041024L)the Key Scientific Research Program of Shaanxi Provincial Education Department,China(21JT028)。
文摘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.
基金the University Grants Commission,New Delhi,India,for providing financial support in the form of the Junior Research Fellowship。
文摘Rapid urbanization creates complexity,results in dynamic changes in land and environment,and influences the land surface temperature(LST)in fast-developing cities.In this study,we examined the impact of land use/land cover(LULC)changes on LST and determined the intensity of urban heat island(UHI)in New Town Kolkata(a smart city),eastern India,from 1991 to 2021 at 10-a intervals using various series of Landsat multi-spectral and thermal bands.This study used the maximum likelihood algorithm for image classification and other methods like the correlation analysis and hotspot analysis(Getis–Ord Gi^(*) method)to examine the impact of LULC changes on urban thermal environment.This study noticed that the area percentage of built-up land increased rapidly from 21.91%to 45.63%during 1991–2021,with a maximum positive change in built-up land and a maximum negative change in sparse vegetation.The mean temperature significantly increased during the study period(1991–2021),from 16.31℃to 22.48℃in winter,29.18℃to 34.61℃in summer,and 19.18℃to 27.11℃in autumn.The result showed that impervious surfaces contribute to higher LST,whereas vegetation helps decrease it.Poor ecological status has been found in built-up land,and excellent ecological status has been found in vegetation and water body.The hot spot and cold spot areas shifted their locations every decade due to random LULC changes.Even after New Town Kolkata became a smart city,high LST has been observed.Overall,this study indicated that urbanization and changes in LULC patterns can influence the urban thermal environment,and appropriate planning is needed to reduce LST.This study can help policy-makers create sustainable smart cities.
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.
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 European Union LandSense project with the project title“A Citizen Observatory and Innovation Marketplace for Land Use and Land Cover Monitoring”,instrument Horizon 2020 and call identifier SC5-17-2015,demonstrating the concept of citizen observatories as an innovation action.
文摘This study explored the land use/land cover(LULC)separability by the machine-generated and user-generated Flickr photo tags(i.e.the auto-tags and the user-tags,respectively),based on an authoritative LULC dataset for San Diego County in the United States.Ten types of LULCs were derived from the authoritative dataset.It was observed that certain types of the reclassified LULCs had abundant tags(e.g.the parks)or a high tag density(e.g.the commercial lands),compared with the less populated ones(e.g.the agricultural lands).Certain highly weighted terms of the tags derived based on a term frequency–inverse document frequency weighting scheme were helpful for identifying specific types of the LULCs,especially for the commercial recreation lands(e.g.the zoos).However,given the 10 sets of tags retrieved from the corresponding 10 types of LULCs,one set of tags(all the tags located at one specific type of the LULCs)could not fully delineate the corresponding LULC due to semantic overlaps,according to a latent semantic analysis.
基金jointly supported by the National Basic Research Program of China(No.2011CB952000)project funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)
文摘The NCAR Community Atmosphere Model(CAM4.0)was used to investigate the climate efects of land use/land cover change(LUCC).Two simulations,one with potential land cover without significant human intervention and the other with current land use,were conducted.Results show that the impacts of LUCC on diurnal temperature range(DTR)are more significant than on mean surface air temperature.The global average annual DTR change due to LUCC is–0.1℃,which is three times as large as the mean temperature change.LUCC influences regional DTR as simulated by the model.In the mid-latitudes,LUCC leads to a decrease in DTR,which is mainly caused by the reduction in daily maximum temperature.However,there are some diferences in the low latitudes.The reduction in DTR in East Asia is mainly the result of the decrease in daily maximum temperature,while in India,the decrease in DTR is due to the increase in daily minimum temperature.In general,the LUCC significantly controls the DTR change through the changes in canopy evaporation and transpiration.
文摘This study assesses the changes in land use/land cover(LULC) and land surface temperature(LST) to identify their impacts from 2000 to 2020 along the coast of Kanyakumari district, India using remote sensing techniques. Landsat images are used to estimate the LULC changes and the MODIS data for LST.The Maximum Likelihood Classification(MLC) method is used, and the LULC is classified into six categories: Agriculture Land, Barren Land, Salt Pan, Sandy Beach, Settlement, and Waterbody. Within the two decades of the present change detection study, upheave in the Settlement area of 49.89% is noticed, and the Agriculture Land is exploited by 20.09%. Salt Pan emits a high LST of 31.57°C, and the Waterbodies are noticed with a low LST of 28.9°C. However, the overall rate of LST decreased by 0.56°C during this period. This study will help policymakers make appropriate planning and management to overcome the impact of LULC and LST in the forthcoming years.
基金Under the auspices of the National Key Research and Development Program of China(No.2017YFB0504205)National Natural Science Foundation of China(No.41571378)Natural Science Research Project of Higher Education in Anhui Provence(No.KJ2020A0089)。
文摘Annual Land Use/Land Cover(LULC)change information at medium spatial resolution(i.e.,at 30 m)is used in applications ranging from land management to achieving sustainable development goals related to food security.However,obtaining annual LULC information over large areas and long periods is challenging due to limitations on computational capabilities,training data,and workflow design.Using the Google Earth Engine(GEE),which provides a catalog of multi-source data and a cloud-based environment,we developed a novel methodology to generate a high accuracy 30-m LULC cover map collection of the Yangtze River Delta by integrating free and public LULC products with Landsat imagery.Our major contribution is a hybrid approach that includes three major components:1)a high-quality training dataset derived from multi-source LULC products,filtered by k-means clustering analysis;2)a yearly 39-band stack feature space,utilizing all available Landsat data and DEM data;and 3)a self-adaptive Random Forest(RF)method,introduced for LULC classification.Experimental results show that our proposed workflow achieves an average classification accuracy of 86.33%in the entire Delta.The results demonstrate the great potential of integrating multi-source LULC products for producing LULC maps of increased reliability.In addition,as the proposed workflow is based on open source data and the GEE cloud platform,it can be used anywhere by anyone in the world.
文摘The world’s largest mangrove ecosystem,the Sunderbans is experiencing multidimensional threats of degradation.The present study was aimed to understand these problems and search for proper remedies by applying suitable remote sensing technologies.South-western parts of Indian Sunderbans Biosphere Reserve had been chosen for assessment of land use/land cover changes in between 1975 and 2006 by using multitemporal Landsat data.Results indicated considerable reduction of open mangrove stands and associated biodiversity mainly in the forest-habitation interference zones of Sunderbans.On the contrary,increase in the coverage of dense mangroves in the reserved forests had been observed indicating the existence of proper centralized management regimes.Overall,a cumulative loss of approximately 0.42%of its original mangrove cover in between 1975 and 2006 had been estimated for this part of the Sunderbans which was at parity with the findings of other studies in the Sunderbans or similar mangrove ecosystems of the tropics.Expansion of non agricultural lands in the last two decades was found to be related with the growth of new settlements,tourism infrastructure,and facilities.This transformation was attributed to the shifting of local peoples’interest from traditional forestry and subsistence farming towards alternative occupations like shrimp culture,coastal tourism,and commercial fishing although environmentally hazardous livelihood activities like collection of prawn seeds along the riverbanks were still persistent.
文摘The availability of better economic possibilities and well-connected transportation networks has attracted people to migrate to peri-urban and rural neighbourhoods,changing the landscape of regions outside the city and fostering the growth of physical infrastructure.Using multi-temporal satellite images,the dynamics of Land Use/Land Cover(LULC)changes,the impact of urban growth on LULC changes,and regional environmental implications were investigated in the peri-urban and rural neighbourhoods of Durgapur Municipal Corporation in India.The study used different case studies to highlight the study area’s heterogeneity,as the phenomenon of change is not consistent.Landsat TM and OLI-TIRS satellite images in 1991,2001,2011,and 2021 were used to analyse the changes in LULC types.We used the relative deviation(RD),annual change intensity(ACI),uniform intensity(UI)to show the dynamicity of LULC types(agriculture land;built-up land;fallow land;vegetated land;mining area;and water bodies)during 1991-2021.This study also applied the Decision-Making Trial and Evaluation Laboratory(DEMATEL)to measure environmental sensitivity zones and find out the causes of LULC changes.According to LULC statistics,agriculture land,built-up land,and mining area increased by 51.7,95.46,and 24.79 km^(2),respectively,from 1991 to 2021.The results also suggested that built-up land and mining area had the greatest land surface temperature(LST),whereas water bodies and vegetated land showed the lowest LST.Moreover,this study looked at the relationships among LST,spectral indices(Normalized Differenced Built-up Index(NDBI),Normalized Difference Vegetation Index(NDVI),and Normalized Difference Water Index(NDWI)),and environmental sensitivity.The results showed that all of the spectral indices have the strongest association with LST,indicating that built-up land had a far stronger influence on the LST.The spectral indices indicated that the decreasing trends of vegetated land and water bodies were 4.26 and 0.43 km^(2)/a,respectively,during 1991-2021.In summary,this study can help the policy-makers to predict the increasing rate of temperature and the causes for the temperature increase with the rapid expansion of built-up land,thus making effective peri-urban planning decisions.
文摘This study aims to examine the use of Remote Sensing and Geographical Information System (GIS) technology in land use/land cover mapping to aide sustainable planning and development in the Wafi-Golpu project area. At the same time, this study examines an existing method of Forest Canopy Density (FCD) model to estimate forest canopy density of the proposed deforestation site, which is known as the Advanced Exploration Feasibility Study Activities (AEFSA) area within the Wafi-Golpu Project site. The FCD model calculates the forest canopy density using the three (3) indices of vegetation, soil and shadow from the Landsat-8 Operational Land Imager (OLI) satellite image of year 2013. In this study an attempt has been made to monitor the forest loss or degradation during deforestation in a natural forest stand of the Wafi-Golpu project area using forest FCD mapping and monitoring model and the findings of the study will assist the project planners and developers with their work on forest rehabilitation and reforestation for the purposes of sustainable forest management. The result of the work shows that a considerable amount of forest loss will be undertaken during the AEFSA deforestation exercise and also the findings show that a reliable land use/land cover map will greatly assist sustainable development in a resource project development period.
文摘The study was aimed at appraising the changing land use/land cover scenario of Tummalapalle region in Cuddapah district of Andhra Pradesh using Remote sensing data and GIS technology. The region is considered as it has rich uranium reserves and is experiencing a remarkable expansion in recent times. The land use/land cover change analysis was carried out using IRS P6 LISS-III and LANDSAT-8 OLI multitemporal data pertaining to the years 2006 and 2016. The image classification resulted in five major land use/land cover classes namely built-up, agricultural, forest, wasteland and water bodies. The study noticed that the areas under built-up and agricultural classes are found increased from 0.94 km<sup>2</sup> (0.84%) to 2.75 km<sup>2</sup> (2.44%) and 61.68 km<sup>2</sup> (54.84%) to 63.91 km<sup>2</sup> (56.82%), respectively during 2006-2016. Area under forest, wasteland and water bodies are found decreased considerably from 3.09 km<sup>2</sup> (2.75%) to 0.86 km<sup>2</sup> (0.76%), 43.71 km<sup>2</sup> (38.56%) to 42.60 km<sup>2</sup> (37.88%) and 3.05 km<sup>2</sup> (2.71%) to 2.35 km<sup>2</sup> (2.09%), respectively. The study recommends development of industrial based economy by optimally utilizing the existing land resource (scrub and wasteland classes) and simultaneously extending the agricultural practices to other possible areas to make them more productive.
基金funded by the National Natural Science Foundation of China (42071112, 41771110)
文摘In the context of global change,it is essential to promote the rational development and utilization of land resources,improve the quality of regional ecological environment,and promote the harmonious development of human and nature for the regional sustainability.We identified land use/land cover types in northern China from 2001 to 2018 with ENVI images and ArcGIS software.Meteorological data were selected from 292 stations in northern China,the potential evapotranspiration was calculated with the Penman-Monteith formula,and reanalysis humidity and observed humidity data were obtained.The reanalysis minus observation(RMO,i.e.,the difference between reanalysis humidity and observed humidity)can effectively characterize the impact of different land use/land cover types(forestland,grassland,cultivated land,construction land,water body and unused land)on surface humidity in northern China in the early 21^(st) century.The results showed that from 2001 to 2018,the area of forestland expanded(increasing by approximately 1.80×10^(4) km^(2)),while that of unused land reduced(decreasing by approximately 5.15×10^(4) km^(2)),and the regional ecological environment was improved.Consequently,land surface in most areas of northern China tended to be wetter.The contributions of land use/land cover types to surface humidity changes were related to the quality of the regional ecological environment.The contributions of the six land use/land cover types to surface humidity were the highest in northeastern region of northern China,with a better ecological environment,and the lowest in northwestern region,with a fragile ecological environment.Surface humidity was closely related to the variation in regional vegetation coverage;when the regional vegetation coverage with positive(negative)contributions expanded(reduced),the land surface became wetter.The positive contributions of forestland and water body to surface humidity were the greatest.Unused land and construction land were associated with the most serious negative contributions to surface humidity.Affected by the regional distribution pattern of vegetation,surface humidity in different seasons decreased from east to west in northern China.The seasonal variation in surface humidity was closely related to the growth of vegetation:surface humidity was the highest in summer,followed by autumn and spring,and the lowest in winter.According to the results,surface humidity is expected to increase in northeastern region of northern China,decrease in northern region,and likely increase in northwestern region.
基金This study was supported by the Key Project of National Natural Science Foundation of China-Xinjiang Joint Fund(U1803241)the Key Project of Xinjiang Uygur Autonomous Region Talent Special Plan-Tianshan Outstanding Youth(2019Q033)+1 种基金the West Light Foundation of the Chinese Academy of Sciences(2017-XBQNXZ-B-019)the Science and Technology Plan Major Projects of the Xinjiang Uygur Autonomous Region,China(2021A03001-3).
文摘The Tarim River is the longest inland river in China and is considered as an important river to protect the oasis economy and environment of the Tarim Basin.However,excessive exploitation and over-utilization of natural resources,particularly water resources,have triggered a series of ecological and environmental problems,such as the reduction in the volume of water in the main river,deterioration of water quality,drying up of downstream rivers,degradation of vegetation,and land desertification.In this study,the land use/land cover change(LUCC)responses to ecological water conveyance in the lower reaches of the Tarim River were investigated using ENVI(Environment for Visualizing Images)and GIS(Geographic Information System)data analysis software for the period of 1990-2018.Multi-temporal remote sensing images and ecological water conveyance data from 1990 to 2018 were used.The results indicate that LUCC covered an area of 2644.34 km^(2) during this period,accounting for 15.79%of the total study area.From 1990 to 2018,wetland,farmland,forestland,and artificial surfaces increased by 533.42 km^(2)(216.77%),446.68 km^(2)(123.66%),284.55 km^(2)(5.67%),and 57.51 km^(2)(217.96%),respectively,whereas areas covered by grassland and other land use/land cover types,such as Gobi,bare soil,and deserts,decreased by 103.34 km2(14.31%)and 1218.83 km2(11.75%),respectively.Vegetation area decreased first and then increased,with the order of 2010<2000<1990<2018.LUCC in the overflow and stagnant areas in the lower reaches of the Tarim River was mainly characterized by fragmentation,irregularity,and complexity.By analyzing the LUCC responses to 19 rounds of ecological water conveyance in the lower reaches of the Tarim River from 2000 to the end of 2018,we proposed guidelines for the rational development and utilization of water and soil resources and formulation of strategies for the sustainable development of the lower reaches of the Tarim River.This study provides scientific guidance for optimal scheduling of water resources in the region.
