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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Analysis on the land use and cover change in Tianjin Binhai New Area based on the remote sensing

This paper carries out quantitative analysis on the land use/cover （LU/C） change of 13anjin Binhai New Area in recent 10 years through using land use transition matrix from the three-stage LU/C classification maps of 2000, 2005 and 2010 drafted by means of the National Land Classification System of China based on Landsat TM satellite remote sensing image and the Tianjin Binhai New Area 1：50 000 relief maps. On this basis, the impact of such driving factors as the economy and population on LU/C is further analyzed. The results show that the area of the building land in Binhai New Area has increased significantly over the ten years, and the greenland, wetland, and shoals of high ecological value have been dramatically transformed into the building land and unused land for the development and construction, and the change is more significant in the later five years.

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

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

Characteristics and drivers of the soil multifunctionality under different land use and land cover types in the drylands of China

The drylands of China cover approximately 6.6×106 km2 and are home to approximately 5.8×10^(8)people,providing important ecosystem services for human survival and development.However,dryland ecosystems are extremely fragile and sensitive to external environmental changes.Land use and land cover(LULC)changes significantly impact soil structure and function,thus affecting the soil multifunctionality(SMF).However,the effect of LULC changes on the SMF in the drylands of China has rarely been reported.In this study,we investigated the characteristics of the SMF changes based on soil data in the 1980s from the National Tibetan Plateau Data Center.We explored the drivers of the SMF changes under different LULC types(including forest,grassland,shrubland,and desert)and used structural equation modeling to explore the main driver of the SMF changes.The results showed that the SMF under the four LULC types decreased in the following descending order:forest,grassland,shrubland,and desert.The main driver of the SMF changes under different LULC types was mean annual temperature(MAT).In addition to MAT,pH in forest,soil moisture(SM)and soil biodiversity index in grassland,SM in shrubland,and aridity index in desert are crucial factors for the SMF changes.Therefore,the SMF in the drylands of China is regulated mainly by MAT and pH,and comprehensive assessments of the SMF in drylands need to be performed regarding LULC changes.The results are beneficial for evaluating the SMF among different LULC types and predicting the SMF under global climate change.

Land Use and Land Cover Dynamics in the Eseka Alluvial Gold Mining District, Centre Region, Cameroon

Local populations in Cameroon thrive on forest resources and the flow of ecosystem services they provide are pivotal in sustaining national economy, improving people’s lives, safeguarding biodiversity, and mitigating the impacts of environmental changes. The exploitation of these resources invariably leads to deforestation and forest degradation. This study was designed to evaluate land use land cover change (LULCC) in the Eseka alluvial gold mining district with the aid of Landsat images. In the investigation of forest cover change, four Landsat satellite images for (1990, 2002, 2015 and 2022) were used. Ground-truthing also helped to identify the activities carried out by the local population and to determine agents, drivers and pressures of land use and land cover change. Four main land cover classes namely: forest, agricultural land, settlement/mining camps and water bodies were selected. Between 1990 and 2022, the proportion of forest decreased from 98% to 34% while those of agricultural land and settlement/mining camps increased from 2% to 60% and 0.54% to 6% respectively. Analysis showed ongoing deforestation with forest cover loss of ~98,263 ha in 32 years giving a cover change percentage of 63.94%. Kappa coefficient for the study period ranged from 0.92 to 0.99. Forest cover loss could be attributed to farming activities, wood extraction and alluvial gold mining activities. Economic motives notably the need to increase household income from a frequent demand for farm and wood products in neighbouring towns and the quest for gold were the main drivers of these activities. Hence, this study assesses the impact of human activities from the mining sector on the forest ecosystem in a bid to inform mitigation policies.

Exploring the Forest Cover Changes and Influential Factors of Dongsithouane National Production Forest Area, Savannakhet Province, Lao PDR

The Dongsithouane National Production Forest (DNPF) is one of the largest natural forest areas in Savannakhet, Lao PDR, which has been a vital support for the local community’s livelihood, Recently, significant changes in land use and land cover (LULC) have been observed in this area, leading to a reduction of natural forests. There were two separate methods of this study: firstly, to identify LULC changes across three different periods, spectral imagery from the Landsat 5 Thematic Mapper (TM) for the years 2001 and 2011, and the Landsat 8 Operational Land Imager (OLI) for 2021 were used as the primary data sources. The satellite images were preprocessed for various forest classes, including pretreatment of the top of atmosphere reflectance by using QGIS software’s semi-automatic classification plug-in (SCP), and ArcGIS was used for post-classification. A supervised classification approach was applied to the satellite images from 2001, 2011, and 2021 to generate diverse maps of LULC. Secondly, a household survey dataset was used to investigate influential factors. Approximately 220 households were interviewed in order to collect socio-economic information (including data on population growth, increased business activities, location of the area, agriculture land expansion, and need for settlement land). Household survey data was analyzed by using SPSS. Descriptive statistics, including frequency distributions and percentages, were applied to observe characteristics. Additionally, a binary logistic regression model was used to analyze the socioeconomic factors related to LULC change in DNPF. Key findings indicated a decline in natural forest areas within the study site. Specifically, both dry dipterocarp forest (−11.35%) and mixed deciduous forest (−0.18%) decreased from 2001 to 2021. The overall accuracy of the LULC maps was 94%, 86%, and 89% for the years 2001, 2011, and 2021 respectively. In contrast, agricultural land increased significantly by 155.70%, while built-up land, and water bodies increased by 65.54% and 35.33%, respectively. The results also highlighted a significant increase in construction land, up to 65.54%. Furthermore, the study found a correlation between agricultural expansion and a reduction of forest areas, along with an increase in built-up land along the forest areas’ boundaries. Timber exploitation and charcoal production also contributed to the decline in forest cover. The logistic regression model identified significant determinants of LULC change, including the area’s location, agricultural land expansion, increased business activity, and the need for settlement land. These factors have influenced the management of DNPF. Urgent sustainable management practices and actions, including forest ecosystem protection, village agricultural zoning, water source and watershed protection and public awareness, are required to preserve the forest areas of DNPF.

Land Use and Land Cover Change Analysis in Ajei Upland Watershed Community Forest, North West Region, Cameroon

This study was carried out in Ajei upland watershed community forest in the North West Region of Cameroon with the aim to analyze spatial and temporal dynamics of land cover and land use from 1988 to 2018 and to identify and characterize the agents, drivers and pressures of this change. The databases used were made up of 3 Lands at satellite images (5 TM of 1988, 7ETM+ of 2003 and 8OLI of 2018). Field survey, interview and focus group discussion methods were used to identify the activities carried out by the local population and to determine agents, drivers and pressures of land use and land cover change. The Ajei community forest is consisted of four main land cover namely;dense vegetation, sparse or degraded vegetation, savanna and bare soil. Between 1988 and 2018, the proportions of dense vegetation and savanna decreased and that of bare soil and sparse vegetation increased. Analysis showed ongoing deforestation with forest cover loss of about 240 ha in 30 years. For the considered time periods 1988-2003 and 2003-2018, deforestation rates were 1.83% per year and 1.49% per year respectively, signifying on average 8 hectares of forest cover undergoing conversion each year. This lost results from the actions of farmers, cattle grazers and wood extractors who through farming, grazing and lumbering activities pressurize and convert the dense forest cover. Economic motives notably the need to increase household income from a frequent demand for farm and wood products in nearby markets represent the drivers of forest cover change. Controlling grazing activities notably in the dry season to check out the use of fires, community sensitization especially among cattle headmen on the importance of the community forest, reforestation activities through natural regeneration or tree planting are needed in the forest.

Analysis of Urban Land Use and Land Cover Change for Sustainable Development: A Case of Lafia, Nasarawa State, Nigeria

Inventories on land use/cover changes are assessed at increasing importance in various sectors, like agriculture, settlement, environmental studies and urban planning. This research was carried out to analyse the changes in urban land use/cover of Lafia for the years 1986, 2000 and 2014. Remotely sensed data from Landsat TM and Nigeria sat 8 were classified using GIS technique, to which six categories of land use/cover were identified such as: bare surfaces, built up areas, cultivated lands, rocky outcrops, vegetation cover and wetlands. Population data of the study area for 1986, 2000 and 2014 were also used to compare the relationship between population growth and landuse/cover changes in the study area using descriptive statistics. The result revealed an increase in built up areas from 1.56% to 15% between 1986 and 2014 while vegetation cover showed decrease: from 25% in 1986 to 12% in 2014. Cultivated lands increased from 56% in 1986 to 67% in 2014. Others classes such as: bare surfaces decreased, as wetlands and rock outcrops seem to be fluctuated. Therefore results from the analyses indicate a general change in landcover for the periods under this study. This study recommends that: there is a need to monitor the changes that occurred on land use so as to provide proper planning and effective management of the land resources in a sustainable manner.

Dynamic Land Use /Cover Change and Analysis of Landscape Pattern in the Hilly and Gully Region of Loess Plateau: A Case Study of Pengyang County in Southern Ningxia

The quantitative evaluation on land use /cover change as well as its influence on landscape pattern under the background of returning grain plots to forestry is significant to the sustainable utilization of land resources and ecological environment reconstruction in the southern Ningxia.Based on multi-temporal remote sensing data from four periods of Landsat TM /ETM,and combination of ecological quantity analytical method with GIS,the change of land use /cover and landscape pattern in Pengyang County of Ningxia Province were analyzed.The conclusions showed that the amount of each land use type was changed with different degrees,the area of forest /grass land increased,while farmland and unused land decreased.The change of landscape pattern was characterized as that the degree of landscape fragmentation,mixed distribution of patches,diversity index and evenness index increased gradually and then decreased,the connectivity between patches decreased gradually and then increased,and landscape shape presented irregular.

RESEARCH ACTIVITIES ON LAND USE/COVER CHANGE IN THE PAST TEN YEARS IN CHINA USING SPACE TECHNOLOGY

Land use/cover change, which in China is characterized by urbanization resulting in a decrease in arable land in the east along with a large area of grassland being cultivated in the west, has been accelerated by rapid economic development in the last years. All of the above changes will affect sustainable development in the next century. The Chinese Academy of Sciences is conducting a study of land use/cover change over the last ten years based on the integration of remote sensing and GIS technology to establish a multitemporal database covering all of China. Fundamental data for land use/cover for the year 1996 has already been developed by the Chinese Academy of Sciences. In order to reconstruct fundamental land use/cover data for the year 1986, a central data processing and analyzing system and a regional data acquisition, processing and analyzing system have been established and are joined together as a network. After the 1986 database is established, the comparative research on the reduction in arable land, urbanization, desertification, changes in forest and grassland, and lake and wetland land use/cover change will be carried out. In addition, a transect for a key regional comparative study was selected along the Changjiang (Yangtze) River. The driving forces of these changes also will be extracted. The result of this study will be not only make a contribution to global land use/cover change research, but will also support decision making for sustainable national development.

Impacts of Land Use and Cover Change on Land Surface Temperature in the Zhujiang Delta

Remote sensing and geographic information systems (GIS) technologies were used to detect land use/cover changes (LUCC) and to assess their impacts on land surface temperature (LST) in the Zhujiang Delta. Multi-temporal Landsat TM and Landsat ETM+ data were employed to identify patterns of LUCC as well as to quantify urban expansion and the associated decrease of vegetation cover. The thermal infrared bands of the data were used to retrieve LST. The results revealed a strong and uneven urban growth,which caused LST to raise 4.56℃in the newly urbanized part of the study area. Overall, remote sensing and GIS technologies were effective approaches for monitoring and analyzing urban growth patterns and evaluating their impacts on LST.

Impacts of Regional-Scale Land Use/Land Cover Change on Diurnal Temperature Range

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.

Validation of CA-Markov for Simulation of Land Use and Cover Change in the Langat Basin, Malaysia

Validity of CA-Markov in land use and cover change simulation was investigated at the Langat Basin, Selangor, Malaysia. CA-Markov validation was performed using validation metrics, allocation disagreement, quantity disagreement, and figure of merit in a three-dimensional space. The figure of merit, quantity error, and allocation error for total landscape simulation using the 1990-1997 calibration data were 5.62%, 3.53%, and 6.13%, respectively. CA-Markov showed a poor performance for land use and cover change simulation due to uncertainties in the source data, the model, and future land use and cover change processes in the study area.