Spatiotemporal variation of land surface temperature and its driving factors in Xinjiang,China

Land surface temperature(LST) directly affects the energy balance of terrestrial surface systems and impacts regional resources, ecosystem evolution, and ecosystem structures. Xinjiang Uygur Autonomous Region is located at the arid Northwest China and is extremely sensitive to climate change. There is an urgent need to understand the distribution patterns of LST in this area and quantitatively measure the nature and intensity of the impacts of the major driving factors from a spatial perspective, as well as elucidate the formation mechanisms. In this study, we used the MOD11C3 LST product developed on the basis of Moderate Resolution Imaging Spectroradiometer(MODIS) to conduct regression analysis and determine the spatiotemporal variation and differentiation pattern of LST in Xinjiang from 2000 to 2020. We analyzed the driving mechanisms of spatial heterogeneity of LST in Xinjiang and the six geomorphic zones(the Altay Mountains, Junggar Basin, Tianshan Mountains, Tarim Basin, Turpan-Hami(Tuha) Basin, and Pakakuna Mountain Group) using geographical detector(Geodetector) and geographically weighted regression(GWR) models. The warming rate of LST in Xinjiang during the study period was 0.24℃/10a, and the spatial distribution pattern of LST had obvious topographic imprints, with 87.20% of the warming zone located in the Gobi desert and areas with frequent human activities, and the cooling zone mainly located in the mountainous areas. The seasonal LST in Xinjiang was at a cooling rate of 0.09℃/10a in autumn, and showed a warming trend in other seasons. Digital elevation model(DEM), latitude, wind speed, precipitation, normalized difference vegetation index(NDVI), and sunshine duration in the single-factor and interactive detections were the key factors driving the LST changes. The direction and intensity of each major driving factor on the spatial variations of LST in the study area were heterogeneous. The negative feedback effect of DEM on the spatial differentiation of LST was the strongest. Lower latitudes, lower vegetation coverage, lower levels of precipitation, and longer sunshine duration increased LST. Unused land was the main heat source landscape, water body was the most important heat sink landscape, grassland and forest land were the land use and land cover(LULC) types with the most prominent heat sink effect, and there were significant differences in different geomorphic zones due to the influences of their vegetation types, climatic conditions, soil types, and human activities. The findings will help to facilitate sustainable climate change management, analyze local climate and environmental patterns, and improve land management strategies in Xinjiang and other arid areas.

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

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

Elucidating Dominant Factors Affecting Land Surface Hydrological Simulations of the Community Land Model over China

In order to compare the impacts of the choice of land surface model(LSM)parameterization schemes,meteorological forcing,and land surface parameters on land surface hydrological simulations,and explore to what extent the quality can be improved,a series of experiments with different LSMs,forcing datasets,and parameter datasets concerning soil texture and land cover were conducted.Six simulations are run for the Chinese mainland on 0.1°×0.1°grids from 1979 to 2008,and the simulated monthly soil moisture(SM),evapotranspiration(ET),and snow depth(SD)are then compared and assessed against observations.The results show that the meteorological forcing is the most important factor governing output.Beyond that,SM seems to be also very sensitive to soil texture information;SD is also very sensitive to snow parameterization scheme in the LSM.The Community Land Model version 4.5(CLM4.5),driven by newly developed observation-based regional meteorological forcing and land surface parameters(referred to as CMFD_CLM4.5_NEW),significantly improved the simulations in most cases over the Chinese mainland and its eight basins.It increased the correlation coefficient values from 0.46 to 0.54 for the SM modeling and from 0.54 to 0.67 for the SD simulations,and it decreased the root-mean-square error(RMSE)from 0.093 to 0.085 for the SM simulation and reduced the normalized RMSE from 1.277 to 0.201 for the SD simulations.This study indicates that the offline LSM simulation using a refined LSM driven by newly developed observation-based regional meteorological forcing and land surface parameters can better model reginal land surface hydrological processes.

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

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

Spatiotemporal Evolution Characteristics of Urban Land Surface Temperature Based on Local Climate Zones in Xi’an Metropolitan,China

Local climate zones(LCZs)are an effective nexus linking internal urban structures to the local climate and have been widely used to study urban thermal environment.However,few studies considered how much the temperature changed due to LCZs transformation and their synergy.This paper quantified the change of urban land surface temperature(LST)in LCZs transformation process by combining the land use transfer matrix with zonal statistics method during 2000–2019 in the Xi’an metropolitan.The results show that,firstly,both LCZs and LST had significant spatiotemporal variations and synchrony.The period when the most LCZs were converted was also the LST rose the fastest,and the spatial growth of the LST coincided with the spatial expansion of the built type LCZs.Secondly,the LST difference between land cover type LCZs and built type LCZs gradually widened.And LST rose more in both built type LCZs transferred in and out.Finally,the Xi’an-Xianyang profile showed that the maximum temperature difference between the peaks and valleys of the LST increased by 4.39℃,indicating that localized high temperature phenomena and fluctuations in the urban thermal environment became more pronounced from 2000 to 2019.

Surface Regional Heat(Cool) Island Effect and Its Diurnal Differences in Arid and Semiarid Resource-based Urban Agglomerations

With the rapid development of urban agglomerations in northwest arid and semiarid regions of China, the scope of the urban heat island(UHI) effect has gradually expanded and gradually connected, and has formed a regional heat island(RHI) with a larger range of impact to the regional environment. However, there are few studies on the heat island effect of urban agglomerations in arid and semiarid regions, so this paper selects the urban agglomeration of Hohhot, Baotou and Ordos(HBO) of Inner Mongolia, China as the study area. Based on the 8-day composite Moderate-resolution Imaging Spectroradiometer(MODIS) surface temperature data(156scenes in all) and land use maps for 2005, 2010, and 2015, we analyze the spatiotemporal distributions of regional heat(cool) islands(RH(C)I) and the responses of surface temperatures to land-use changes in the diurnal and interannual surface cities. The results showed that: 1) from 2005 to 2015, urban areas showed the cold island effect during the day, with the area of the cold island showing a shrinking feature;at night, they showed the heat island effect, with the area of the heat island showing a first decrease and then an increase.2) From 2005 to 2015, the land development(unutilized land to building land) brings the greatest temperature increase(ΔT = 1.36°C)during the day, while the greatest temperature change at night corresponds to the conversion of cultivated land to building land(ΔT =0.78°C) exhibited the largest changes at night. From 2010 to 2015, the land development(grassland to building land) bring the greatest temperature increase(ΔT = 0.85°C) during the day, while the great temperature change at night corresponds to the conversion of water areas to building land(ΔT = 1.38°C) exhibited the largest changes at night. Exploring the spatial and temporal evolution of surface urban heat(cool) islands in urban agglomerations in arid and semiarid regions will help to understand the urbanization characteristics of urban agglomerations and provide a reference for the formulation of policies for the coordinated and healthy development of the region and co-governance of regional environmental problems.

Statistical Downscaling Retrieval of Land Surface Temperature in an Area with Complex Landforms in the Eastern Qinling Mountains of China Based on Sentinel-2/3 Satellite Data

The study of land surface temperature(LST)is of great significance for ecosystem monitoring and ecological environmental protection in the Qinling Mountains of China.In view of the contradicting spatial and temporal resolutions in extracting LST from satellite remote sensing(RS)data,the areas with complex landforms of the Eastern Qinling Mountains were selected as the research targets to establish the correlation between the normalized difference vegetation index(NDVI)and LST.Detailed information on the surface features and temporal changes in the land surface was provided by Sentinel-2 and Sentinel-3,respectively.Based on the statistically downscaling method,the spatial scale could be decreased from 1000 m to 10 m,and LST with a Sentinel-3 temporal resolution and a 10 m spatial resolution could be retrieved.Comparing the 1 km resolution Sentinel-3 LST with the downscaling results,the 10 m LST downscaling data could accurately reflect the spatial distribution of the thermal characteristics of the original LST image.Moreover,the surface temperature data with a 10 m high spatial resolution had clear texture and obvious geomorphic features that could depict the detailed information of the ground features.The results showed that the average error was 5 K on April 16,2019 and 2.6 K on July 15,2019.The smaller error values indicated the higher vegetation coverage of summer downscaling result with the highest level on July 15.

Land Surface Temperature Change in Hangzhou Urban Area in Recent 20 Years Based on Landsat Image

Since the reform and opening-up in 1978, the urbanization level of our country has been continuously improved and the urban development has made great progress. However, with the rapid expansion of urban construction land, the population density and building density have been greatly increased, resulting in the urban heat island effect, which has negative impact on the urban thermal environment and restricts the high-quality development of urbanization. This paper focuses on how the urban surface thermal environment of Hangzhou changes in 20 years. In this paper, the characteristics of land surface temperature (LST) in Hangzhou urban area from 2000 to 2020 were studied by using Landsat images. The radiative transfer equation method is used to retrieve the land surface temperature, and the retrieval results are analyzed. The results show that: 1) the land surface temperature in Hangzhou city area has a slight upward trend in the past 20 years;2) the area of high temperature area is expanding;3) the land surface temperature in the city center area has decreased significantly in the past 20 years, while the ground temperature in other areas around the city center has increased significantly.

Spatio-temporal Evolution Characteristics and Driving Forces of Winter Urban Heat Island:A Case Study of Rapid Urbanization Area of Fuzhou City,China

Under the influence of anthropogenic and climate change,the problems caused by urban heat island(UHI)has become increasingly prominent.In order to promote urban sustainable development and improve the quality of human settlements,it is significant for exploring the evolution characteristics of urban thermal environment and analyzing its driving forces.Taking the Landsat series images as the basic data sources,the winter land surface temperature(LST)of the rapid urbanization area of Fuzhou City in China was quantitatively retrieved from 2001 to 2021.Combing comprehensively the standard deviation ellipse model,profile analysis and GeoDetector model,the spatio-temporal evolution characteristics and influencing factors of the winter urban thermal environment were systematically analyzed.The results showed that the winter LST presented an increasing trend in the study area during 2001–2021,and the winter LST of the central urban regions was significantly higher than the suburbs.There was a strong UHI effect from 2001 to 2021with an expansion trend from the central urban regions to the suburbs and coastal areas in space scale.The LST of green lands and wetlands are significantly lower than croplands,artificial surface and unvegetated lands.Vegetation and water bodies had a significant mitigation effect on UHI,especially in the micro-scale.The winter UHI had been jointly driven by the underlying surface and socio-economic factors in a nonlinear or two-factor interactive enhancement mode,and socio-economic factors had played a leading role.This research could provide data support and decision-making references for rationally planning urban layout and promoting sustainable urban development.

A Land Surface Model(IAP94) for Climate Studies PartI:Formulation and Validation in Off-line Experiments

The IAP (Institute of Atmospheric Physics) land-surface model (IAP94) is described. This model is a comprehensive one with detailed description for the processes of vegetation, snow and soil. Particular attention has been paid to the cases with three water phases in the surface media. On the basis of the mixture theory and the theory of fluid dynamics of porous media, the system of universal conservational equations for water and heat of soil, snow and vegetation canopy has been constructed. On this background, all important factors that may affect the water and heat balance in media can be considered naturally, and each factor and term possess distinct physical meaning. In the computation of water content and temperature, the water phase change and the heat transportation by water flow are taken into account. Moreover, particular attention has been given to the water vapor diffusion in soil for arid or semi-arid cases, and snow compaction. In the treatment of surface turbulent fluxes, the difference between aerodynamic and thermal roughness is taken into account. The aerodynamic roughness of vegetation is calculated as a function of canopy density, height and zero-plane displacement. An extrapolation of log linear and exponential relationship is used when calculating the wind profile within canopy. The model has been validated against field measurements in off-line simulations. The desirable model′s performance leads to the conclusion that the IAP94 is able to reproduce the main physical mechanisms governing the energy and water balances in the global land surface. Part II of the present study will concern the validation in a 3-D experiment coupled with the IAP Two-Level AGCM.

Relief degree of land surface and its influence on population distribution in China

The relief degree of land surface （RDLS） is an important factor for describing the landform at macro-scales. This study defines a concept for RDLS and applies the concept for population distribution study of the entire country. Based on the concept and macro-scale digital elevation model datum and ARC/INFO software, the RDLS at a 10 km×10 km grid size of China is extracted. This paper depicts systemically the spatial distributions of RDLS through analyzing the ratio structure and altitudinal characters of RDLS in China. The conclusions are drawn as follows： the RDLS in more than 63% of the area is less than one （1） （relative altitude is less than 500 m）, reflecting the fact that most of RDLS in China is low. In general, the RDLS in the west is larger than that in the east and so is the south than that of the north in China. The RDLS decreases with the increase of longitude and latitude and the change of RDLS at the latitudes of 28°N, 35°N, 42°N, as well as at the longitudes of 85°E, 102°E, 115°E could reflect the three major ladders of China. In the vertical direction, the RDLS increases with the increase of altitude. Analysis of the correlation between RDLS and population distribution in China and its regional difference shows that the R2 value between RDLS and population density is 0.91 and RDLS is an important factor influencing the spatial distribution of population. More than 85% of the people in China live in areas where the RDLS is less than one （1）, while the population in areas with RDLS greater than 3 accounts only for 0.57% of the total. The regional difference of correlation between RDLS and population within China is significant and such correlation is significant in Central China and South China and weak in Inner Mongolia and Tibet.

A Modeling Study of Land Surface Process Impacts on Inland Behavior of Typhoon Rananim(2004)

On 12 August 2004, Typhoon Rananim （0414） moved inland over China and stagnated over the Poyang Lake area, resulting in torrential rainfall and severe geologic hazards. The Advanced Weather Research and Forecasting （ARW-WRF） model and its different land surface models （LSMs） were employed to study the impacts of land surface process on the inland behavior of Typhoon Rananim. Results show that simulations, coupled with LSMs or not, have no significant differences in predicting typhoon track, intensity, and largescale circulation. However, the simulations of mesoscale structure, rainfall rate, and rainfall distribution of typhoon are more reasonable with LSMs than without LSMs. Although differences are slight among LSMs, NOAH is better than the others. Based on outputs using the NOAH scheme, the interaction between land surtace and typhoon was explored in this study. Notably, typhoon rainfall and cloud cover can cool land surface, but rainfall expands the underlying saturated wetland area, which exacerbates the asymmetric distribution of surface heat fluxes. Accordingly, an energy frontal zone may form in the lower troposphere that enhances ascending motion and local convection, resulting in heavier rainfall. Moreover, the expanded underlying saturated wetlands provide plentiful moisture and unstable energy for the maintenance of Typhoon Rananim and increased rainfall in return.

Using a Modified Soil-Plant-Atmosphere Scheme(MSPAS)to Simulate the Interaction between Land Surface Processes and Atmospheric Boundary Layer in Semi-Arid Regions

This paper uses a Modified Soil-Plant-Atmosphere Scheme (MSPAS) to study the interaction between land surface and atmospheric boundary layer processes. The scheme is composed of two main parts: atmospheric boundary layer processes and land surface processes. Compared with SiB and BATS, which are famous for their detailed parameterizations of physical variables, this simplified model is more convenient and saves much more computation time. Though simple, the feasibility of the model is well proved in this paper. The numerical simulation results from MSPAS show good agreement with reality. The scheme is used to obtain reasonable simulations for diurnal variations of heat balance, potential temperature of boundary layer, and wind field, and spatial distributions of temperature, specific humidity, vertical velocity, turbulence kinetic energy, and turbulence exchange coefficient over desert and oasis. In addition, MSPAS is used to simulate the interaction between desert and oasis at night, and again it obtains reasonable results. This indicates that MSPAS can be used to study the interaction between land surface processes and the atmospheric boundary layer over various underlying surfaces and can be extended for regional climate and numerical weather prediction study.

Turbulent Variance Characteristics of Temperature and Humidity over a Non-uniform Land Surface for an Agricultural Ecosystem in China

This paper describes the application of the variance method for flux estimation over a mixed agricultural region in China. Eddy covariance and flux variance measurements were conducted in a near-surface layer over a non-uniform land surface in the central plain of China from 7 June to 20 July 2002. During this period, the mean canopy height was about 0.50 m. The study site consisted of grass （10% of area）, beans （15%）, corn （15%） and rice （60%）. Under unstable conditions, the standard deviations of temperature and water vapor density （normalized by appropriate scaling parameters）, observed by a single instrument, followed the Monin-Obukhov similarity theory. The similarity constants for heat （CT） and water vapor （Cq） were 1.09 and 1.49, respectively. In comparison with direct measurements using eddy covariance techniques, the flux variance method, on average, underestimated sensible heat flux by 21% and latent heat flux by 24%, which may be attributed to the fact that the observed slight deviations （20% or 30% at most） of the similarity ＂constants＂ may be within the expected range of variation of a single instrument from the generally-valid relations.

A Numerical Study on Effects of Land-Surface Heterogeneity from' Combined Approach' on Atmospheric ProcessPart II: Coupling-Model Simulations

Two land surface schemes, one the standard Biosphere / Atmosphere Transfer Scheme Version ie (BOZ) and the other B1Z based on B0Z and heterogeneously-treated by' combined approach' , were co 'pled to the meso-scale model MM4, respectively. Through the calculations of equations from the companion paper, parameters representing land surface heterogeneity and suitable for the coupling models were found out. Three cases were simulated for heavy rainfalls during 36 hours, and the sensitivity of short-term weather modeling to the land surface heterogeneity was tested. Through the analysis of the simulations of the three heavy rainfalls, it was demonstrated that BIZ, compared with BOZ, could more realistically reflect the features of the land surface heterogeneity, therefore could more realistically reproduce the circulation and precipitation amount in the heavy rainfall processes of the three cases. This shows that even short-term weather is sensitive to the land surface heterogeneity, which is more obvious with time passing, and whose influence is more pronounced in the lower layer and gradually extends to the middle and upper layer. Through the analysis of these simulations with BlZ, it is suggested that the bulk effect of smaller-scale fluxes (i.e., the momentum, water vapor and sensible heat fluxes) near the s ig nificantly-heterogeneous land surface is to change the larger-scale (i.e., meso-scale) circulation, and then to influence the development of the low-level jets and precipitation. And also, the complexity of the land-atmosphere interaction was shown in these simulations.

Effects of Crop Growth and Development on Land Surface Fluxes

In this study, the Crop Estimation through Resource and Environment Synthesis model （CERES3.0） was coupled into the Biosphere-Atmosphere Transfer Scheme （BATS）, which is called BATS CERES, to represent interactions between the land surface and crop growth processes. The effects of crop growth and development on land surface processes were then studied based on numerical simulations using the land surface models. Six sensitivity experiments by BATS show that the land surface fluxes underwent substantial changes when the leaf area index was changed from 0 to 6 m2 m-2. Numerical experiments for Yucheng and Taoyuan stations reveal that the coupled model could capture not only the responses of crop growth and development to environmental conditions, but also the feedbacks to land surface processes. For quantitative evaluation of the effects of crop growth and development on surface fluxes in China, two numerical experiments were conducted over continental China： one by BATS CERES and one by the original BATS. Comparison of the two runs shows decreases of leaf area index and fractional vegetation cover when incorporating dynamic crops in land surface simulation, which lead to less canopy interception, vegetation transpiration, total evapotranspiration, top soil moisture, and more soil evaporation, surface runoff, and root zone soil moisture. These changes are accompanied by decreasing latent heat flux and increasing sensible heat flux in the cropland region. In addition, the comparison between the simulations and observations proved that incorporating the crop growth and development process into the land surface model could reduce the systematic biases of the simulated leaf area index and top soil moisture, hence improve the simulation of land surface fluxes.

Spatio-temporal variation and propagation direction of coal fire in Jharia Coalfield,India by satellite-based multi-temporal night-time land surface temperature imaging

In this paper,the spatio-temporal variation and propagation direction of coal fire were studied in the Jharia Coalfield(JCF),India during 2006–2015 through satellite-based night-time land surface temperature(LST)imaging.The LST was retrieved from Advanced Spaceborne Thermal Emission and Reflection Radiometer(ASTER)night-time thermal-infrared data by a robust split-window algorithm based on scene-specific regression coefficients,band-specific hybrid emissivity,and night-time atmospheric transmittance.The LST-profile-based coal fire detection algorithm was formulated through statistical analysis of the LST values along multiple transects across diverse coal fire locations in the JCF in order to compute date-specific threshold temperatures for separating thermally-anomalous and background pixels.This algorithm efficiently separates surface fire,subsurface fire,and thermally-anomalous transitional pixels.During the observation period,it was noticed that the coal fire area increased significantly,which resulted from new coal fire at many places owing to extensive opencast-mining operations.It was observed that the fire propagation occurred primarily along the dip direction of the coal seams.At places,lateral-propagation of limited spatial extent was also observed along the strike direction possibly due to spatial continuity of the coal seams along strike.Moreover,the opencast-mining activities carried out during 2009–2015 and the structurally weak planes facilitated the fire propagation.

Impact of Spin-up Forcing on Vegetation States Simulated by a Dynamic Global Vegetation Model Coupled with a Land Surface Model

A dynamic global vegetation model （DGVM） coupled with a land surface model （LSM） is generally initialized using a spin-up process to derive a physically-consistent initial condition. Spin-up forcing, which is the atmospheric forcing used to drive the coupled model to equilibrium solutions in the spin-up process, varies across earlier studies. In the present study, the impact of the spin-up forcing in the initialization stage on the fractional coverages （FCs） of plant functional type （PFT） in the subsequent simulation stage are assessed in seven classic climate regions by a modified Community Land Model’s Dynamic Global Vegetation Model （CLM-DGVM）. Results show that the impact of spin-up forcing is considerable in all regions except the tropical rainforest climate region （TR） and the wet temperate climate region （WM）. In the tropical monsoon climate region （TM）, the TR and TM transition region （TR-TM）, the dry temperate climate region （DM）, the highland climate region （H）, and the boreal forest climate region （BF）, where FCs are affected by climate non-negligibly, the discrepancies in initial FCs, which represent long-term cumulative response of vegetation to different climate anomalies, are large. Moreover, the large discrepancies in initial FCs usually decay slowly because there are trees or shrubs in the five regions. The intrinsic growth timescales of FCs for tree PFTs and shrub PFTs are long, and the variation of FCs of tree PFTs or shrub PFTs can affect that of grass PFTs.

Estimation of Land Surface Temperature over the Tibetan Plateau Using AVHRR and MODIS Data

Estimation of large-scale land surface temperature from satellite images is of great importance for the study of climate change. This is especially true for the most challenging areas, such as the Tibetan Plateau （TP）. In this paper, two split window algorithms （SWAs）, one for the NOAA’s Advanced Very High Resolu-tion Radiometer （AVHRR）, and the other for the Moderate Resolution Imaging Spectroradiometer （MODIS）, were applied to retrieve land surface temperature （LST） over the TP simultaneously. AVHRR and MODIS data from 17 January, 14 April, 23 July, and 16 October 2003 were selected as the cases for winter, spring, summer, and autumn, respectively. Firstly, two key parameters （emissivity and water vapor content） were calculated at the pixel scale. Then, the derived LST was compared with in situ measurements from the Coordinated Enhanced Observing Period （CEOP） Asia-Australia Monsoon Project （CAMP） on the TP （CAMP/Tibet） area. They were in good accordance with each other, with an average percentage error （PE） of 10.5% for AVHRR data and 8.3% for MODIS data, meaning the adopted SWAs were applicable in the TP area. The derived LST also showed a wide range and a clear seasonal difference. The results from AVHRR were also in agreement with MODIS, with the latter usually displaying a higher level of accuracy.

Land-Cover Classification and its Impact on Peshawar’s Land Surface Temperature Using Remote Sensing

Spatial and temporal informationon urban infrastructure is essential and requires various land-cover/land-use planning and management applications.Besides,a change in infrastructure has a direct impact on other land-cover and climatic conditions.This study assessed changes in the rate and spatial distribution of Peshawar district’s infrastructure and its effects on Land Surface Temperature(LST)during the years 1996 and 2019.For this purpose,firstly,satellite images of bands7 and 8 ETM+(Enhanced Thematic Mapper)plus and OLI(Operational Land Imager)of 30 m resolution were taken.Secondly,for classification and image processing,remote sensing(RS)applications ENVI(Environment for Visualising Images)and GIS(Geographic Information System)were used.Thirdly,for better visualization and more in-depth analysis of land sat images,pre-processing techniques were employed.For Land use and Land cover(LU/LC)four types of land cover areas were identified-vegetation area,water cover,urbanized area,and infertile land for the years under research.The composition of red,green,and near infra-red bands was used for supervised classification.Classified images were extracted for analyzing the relative infrastructure change.A comparative analysis for the classification of images is performed for SVM(Support Vector Machine)and ANN(Artificial Neural Network).Based on analyzing these images,the result shows the rise in the average temperature from 30.04℃ to 45.25℃.This only possible reason is the increase in the built-up area from 78.73 to 332.78 Area km^(2) from 1996 to 2019.It has also been witnessed that the city’s sides are hotter than the city’s center due to the barren land on the borders.