S patio-temporal pattern of land use and land cover and its effects on land surface temperature using remote sensing and GIS techniques: a case study of Bhubaneswar city,Eastern India (1991–2021)

Urbanization produces substantial land use changes by causing the construction of different urban infrastructures in the city region for habitation, transportation, industry, and other reasons. As a result, it has a significant impact on Land Surface Temperature (LST) by disrupting the surface energy balance. The objective of this paper is to assess the impact of land-use/land-cover (LU/LC) dynamics on urban land surface temperature (LST) of Bhubaneswar City in Eastern India during 30 years (1991–2021) using Landsat data (TM, ETM + , and OLI/TIRS) and machine learning algorithms (MLA). The finding reveals that the mean LST over the entire study domain grows significantly between 1991 and, 2021due to urbanization (β coefficient 0.400, 0.195, 0.07, and 0.06 in 1991, 2001, 2011, and 2021 respectively) and loss of green space (β coefficient − 0.295, − 0.025, − 0.125 and − 0.065 in 1991, 2001, 2011 and 2021 respectively). The highest class recorded for agricultural land (49.60 km², accounting for 33.94% of the total land area) was in 1991 followed by vegetation (41.27 km², 28.19% of the total land area), and built-up land (27.59 km², 18.84% of the total land area). The sharp decline of vegetation cover will continue until 2021 due to increasing built-up areas (r = − 0.531, − 0.329, − 0.538, and − 0.063 in the 1991, 2001, 2011 and 2021 respectively). Built-up land (62.60 km², accounting for 42.76% of the total land area, an increase of 35.01 km² from 1991) as the highest class followed by water bodies (21.57%, 32.60 km² of the land area), and agricultural land (31.57 km², 21.57% of the land area) in 2021. Remote sensing techniques proved to be an important tool to urban planners and policymakers to take adequate steps to promote sustainable development and minimize urbanization influence on LST. Urban green space (UGS) can help improve the overall liveability and environmental sustainability of Bhubaneswar city.

     

Analysing transition of land surface temperature and derived indices with respect to elevation values in Kohima Saddar

Human activities have affected the urban environment resulting in a drastic change in the surface temperature. The impact of urban heat islands is noticeable in urban areas than in rural areas. The thermal band of Landsat 8 data is used to retrieve the spatial distribution of land surface temperature (LST) over Kohima Sadar for the years 2009, 2015 and 2020 with the Mono-window algorithm. Urban Thermal Field Variance Index (UTFVI) is used to assess the ecological condition in the area impacted by LST. Cartosat-1 Digital Elevation Model (Carto DEM) is used to understand the variations of LST and indices values with reference to the elevation profile located at different random points. The variations in the land cover are categorized as per the values of normalized difference vegetation index (NDVI) and built-up density index (BUI). This work estimates the influence of elevation over LST, vegetation, and the built-up area. Results implies a negative correlation between LST and NDVI whereas a positive correlation between LST and BUI. Likewise, NDVI and BUI show a strong negative correlation. It is observed that LST is independent of elevation profile but the variation of LST depends on the impact of change in topography urbanization, deforestation, and afforestation. There is no significant relationship of elevation with the variations in NDVI and BUI values. It is observed that the impact of emissivity influences the estimation of LST values. For the locations having the highest and lowest LST, NDVI, and BUI values, 50 random points are generated for the entire region, and validation is executed with the google earth historical image.

     

2005-2015年贵阳市生境退化程度对土地利用变化的响应

基于2005和2015年贵阳市土地利用数据,利用InVEST模型,分析了2005-2015年贵阳市生境退化程度对土地利用变化的响应,结果表明:（1）2005-2015年贵阳市城镇建设用地、农村居民点和有林地大幅增加,水田和旱地大幅下降,其他地类变化相对较小;水田和旱地转化为城镇建设用地、农村居民点和有林地最为突出;（2）10年间,贵阳市生境退化程度以下降为主,生境退化程度增加区主要分布在南部,下降区主要分布在北部、东部和西部;（3）生境退化程度热点变化以低值减少和高值减少为主;生境退化程度热点空间变化主要分布于南部。退耕还林政策及快速城镇化引起的水田和旱地转化为有林地、城镇建设用地和农村居民点是导致该区生境退化程度变化的主要因素。      

Retrieving of Land Surface Temperature Using Thermal Remote Sensing and GIS Techniques in Kandaihimmat Watershed,Hoshangabad, Madhya Pradesh

Remotely sensed thermal infrared (TIR) data have been widely used to retrieve land surface temperature (LST). LST is an important parameter in the studies of urban thermal environment and dynamics. In the study, an attempt has been made using LANDSAT 8 thermal imagery to compute LST and the associated land cover parameters viz; land surface emissivity (LSE), normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI) and normalized difference water index (NDWI). Landsat 8 TIRS band 10 & 11 (thermal bands) during 21 Oct. 2016, 22 Nov.2016, 24 Dec. 2016 and 09 Jan. 2017 were processed for LST analysis. However, band 5 & band 4 of the imagery was processed for NDVI, band 6 & band 5 for NDBI and band 2 & band 5 for NDWI analysis. LST has been derived from both the bands 10 &11 and validated by in-situ observations on the date and time of satellite overpass from the study area. Band 10 derived LST have shown much temperature difference while comparing with the in-situ observations. However, LST derived from band 11 found similar & close to the in-situ measurements. Relationship between band 11 results and in-situ observed measurements were developed, which has showing a strong correlation with (r² = 0.991). Land surface emissivity were also evaluated which shows variation in different land cover surfaces like vegetation, settlement, forest cover and water body. The study has proven that land surface temperature derived from satellite band 11 is the actual surface temperature of the study area.     

Assessment of the mutual impact between climate and vegetation cover using NOAA-AVHRR and Landsat data in Egypt

The objective of the current study is to use satellite data to assess the mutual influence between vegetation and climate. The Ismailia Governorate was selected as a case study to investigate the impact of vegetation cover expansion on both land surface and air temperature from 1983 to 2010 and vice versa. This observation site was carefully selected as a clear example of the high rate of the reclamation and vegetation expansion process in Egypt. Land surface temperature (LST) was estimated through the Advanced Very High Resolution Radiometer (a space-borne sensor embarked on the National Oceanic and Atmospheric Administration) data while air temperature (T _air) was collected from ground meteorological stations in the study area. Irrigated agriculture is the largest consumer of freshwater resources. However, consistent information on irrigation water use is still lacking. Relative humidity, wind speed, solar radiation, and T _air data were inserted in the Penman–Monteith equation to calculate potential evapotranspiration (ET_o), while both LST and T _air were used to observe the relative water status of the study area as a result of the water deficit index (WDI). Then, both WDI and ET_o were used to calculate actual evepotranspiration (ET_C.). The results showed that LST decreased by about 2.3 °C while T _air decreased by about 1.6 °C during the study period. The results showed also that the vegetation cover expanded from 25,529.85 ha in 1985 to 63,140.49 ha in 2009 with about 147 % increase. This decrease in LST and air temperature was according to the expansion of the cultivated land that was proved through the processing of three Landsat TM and Landsat ETM+ imageries acquired in June 19, 1985, June 7, 1998, and June 29, 2009. The vegetation water consumption was affected by the decreasing surface and air temperature. The results showed that the water deficit index decreased by about 0.35, and actual evapotranspiration increased by about 2.5 mm during the study period.     

库尔勒市城市空间扩展特征及其驱动因素研究

以库尔勒市1990年、1995年、2000年、2005年、2010年以及2015年6个时期的Landsat TM/ETM+影像作为基础数据,借助ENVI 4.5、Arc GIS 10.1等专业软件对影像进行监督分类和空间分析。在此基础上,分析库尔勒市近25 a来土地利用时空变化规律、城市空间扩展趋势及演变过程、城市重心转移方向及距离和城市空间扩展形态变化特征等。研究表明:近25 a间库尔勒市建设用地面积大幅度增加,所占比例不断上升,年均增加速率为15.18%。耕地和未利用地对城市建设用地扩展贡献较大。城市向东南方向扩展,城市重心向东南方向转移了总共2 118.46 m。城市空间扩展紧凑度呈下降趋势,分形维数呈上升趋势,表明城市空间扩展趋于结构疏散化、形状复杂化。针对于以上特征及扩展趋势,分析了库尔勒市城市空间扩展的驱动因素并提出一些对策建议,为城市可持续发展提供科学依据。     

Quantifying the spatio-temporal patterns of settlement growth in a metropolitan region of Ghana

Retrospective understanding of the magnitude and pace of urban expansion is necessary for effective growth management in metropolitan regions. The objective of this paper is to quantify the spatial–temporal patterns of urban expansion in the Greater Kumasi Sub-Region (GKSR)—a functional region comprising eight administrative districts in Ghana, West Africa. The analysis is based on Landsat remote sensing images from 1986, 2001 and 2014 which were classified using supervised maximum likelihood algorithm in ERDAS IMAGINE. We computed three complementary growth indexes namely; Average Annual Urban Expansion Rate, Urban Expansion Intensity Index (UEII) and Urban Expansion Differentiation Index to estimate the amount and intensity of expansion over the 28-year period. Overall, urban expansion in the GKSR has been occurring at an average annual rate of 5.6 %. Consequently, the sub-region’s built-up land increased by 313 km² from 88 km² in 1986 to 400 km² in 2014. The analysis further show that about 72 % of the total built-up land increase occurred in the last 13 years alone, with UEII value of 0.605 indicating a moderate intensity of urban expansion. Moreover, the metropolitan-core of the sub-region, being the focal point of urban development and the historical origins of expansion, accounted for more than half of the total built-up land increase over the 28-year period. Over the last decade and half however, urban expansion has spilled into the neighbouring peripheral districts, with the highest intensity and fastest rate of expansion occurring in districts located north and north east of the sub-regional core. We recommend a comprehensive regional growth management strategy grounded in effective strategic partnerships among the respective administrative districts to curb unsustainable urban expansion.     

Iterative selective spatial variance reduction of MYD11A2 LST data

The aim of this research effort is to develop a method that will allow to map and evaluate thermal anomalies in SW USA from the MYD11A2 night land surface temperature (LST) imagery being available for the year 2014, that present higher spatial (1 km) and temporal (46 images per year) resolution than the MYD11C3 LST data (12 images per year at 5.6 km spatial resolution). The fact that is MYD11A2 LST imagery is projected to a rectangular grid did not affect the X, Y and elevation (H) spatial decorrelation stretch. Principal component analysis and linear regression models isolated and removed the X, Y, H (spatial) dependent variance included in the data while metrics devised verified the selective spatial variance reduction. The reconstructed 46 LST images represent the amount the LST deviates from the X, Y and H predicted for the year 2014. The thematic information content of the reconstructed LST images is verified by cluster analysis and mapped the spatial extend and the temporal variability of thermal anomalies within the study area. The positive thermal anomaly clusters are spatially arranged mainly west of Sierra Nevada in Great Basin Section where extensional tectonics create a series of titled elongated mountain blocks along the N to S direction in between basins bounded by normal faults, while the negative thermal anomaly clusters are spatially arranged along the coastal region, further north and in the western region far from the tilted mountain tectonic blocks of the Great Basin Section. The spatial maps that define regions with (positive or negative) thermal anomalies and distinct mean land response could assist landcover studies and support urban and rural planning in the context of emerging climatic change.     

Dynamics of land surface temperature (LST) in response to land use and land cover (LULC) changes in the Weigan and Kuqa river oasis,Xinjiang, China

Land use and land cover (LULC) changes caused by human activities have strong influences on regional environment. Land surface temperate plays an important role in studying the impact of LULC changes on regional environment. In this paper, remotely sensed thermal infrared data were used to assess land surface temperature (LST) in the Weigan and Kuqa river oasis, Xingjiang, one of the important agricultural areas in the northwestern China. The present study deals with the extraction of LST and the relationship between LULC changes using Landsat 5 TM acquired on September 25, 1989, and September 6, 2011. The results indicate that the surface temperature of water body, bare land, and desert changed significantly between 1989 and 2011. In general, the LST was lower in 1989 than in 2011. There were no lower, higher, and highest temperature zones in 1989. However, the minimum temperature was 10.7 °C in 1989 and 15.8 °C in 2011. The maximum temperature was 29.3 °C in 1989 and 41.8 °C in 2011. Regarding the LULC types, the desert features in the Gobi Desert warmed more quickly than the oasis. So, the temperature of the oasis was lower than the surrounded areas, resulting in a so-called “cold island” phenomenon. Oasis cold island effect index (OCIEI) shows that stability of oasis had rising trend from 1989 to 2011. In addition, the impact of LULC changes on LST was analyzed and the driving forces were also analyzed from 1977 to 2011. This study is significant for further understanding of the energy exchange status of soil-plant-atmospheric system and the regional heat distribution in arid and semi-arid areas of the northwest China.     

Landsat data to evaluate urban expansion and determine land use/land cover changes in Penang Island,Malaysia

Land surface temperature (LST) plays an important role in local, regional and global climate studies. LST controls the distribution of the budget for radiation heat between the atmosphere and the earth’s surface. Therefore, it is important to evaluate abrupt changes in land use/land cover (LULC). Penang Island, Malaysia has been experiencing a rapid and drastic change in urban expansion over the past two decades due to growth in industrial and residential areas. The aim of this study was to investigate and evaluate the impact of LST with respect to land use changes in Penang Island, Malaysia. Three supervised classification techniques known as maximum likelihood, minimum distance-to-mean and parallelepiped were applied to the images to extract thematic information from the acquired scene by using PCI Geomatica 10.1 image processing software. These remote sensing classification techniques help to examine land-use changes in Penang Island using multi-temporal Landsat data for the period of 1999–2007. Training sites were selected within each scene and seven land cover classes were assigned to each classifier. The relative performance of each technique was evaluated. The accuracy of each classification map was assessed using a reference data set consisting of a large number of samples collected per category. Two Landsat satellite images captured in 1999 and 2007 were chosen to classify the LULC types using the maximum likelihood classification method, determined from visible and near-infrared bands. The study revealed that the maximum likelihood classifier produced superior results and achieved a high degree of accuracy. The LST and normalised difference vegetation index (NDVI) were computed based on changes in LULC. The results showed that the urban (highly built-up) area increased dramatically, and grassland area increased moderately. Inversely, barren land decreased obviously, and forest area decreased moderately. While urban (minimally built-up) area decreased slightly. These changes in LULC caused at significant difference in LST between urban and rural areas. Strong correlation values were observed between LST and NDVI for all LULC classes. The remote sensing technique used in this study was found to be efficient; it reduced the time for the analysis of the urban expansion, and it was found to be a useful tool to evaluate the impact of urbanisation with LST.     

Impact of city expansion on hydrological regime of Rispana Watershed,Dehradun, India

Rispana River flows through the heart of Dehradun, the capital city of Uttarakhand State, India. Uttarakhand had separated from Uttar Pradesh State in the year 2000; since then, Dehradun City has witnessed numerous changes. Both urban sprawl and densification were noticed, with around a 32% increase in population. The city had faced recurrent high runoff and urban flood situations in these last 2 decades. Therefore, the study was conducted to detect the change in land use/land cover (LULC), especially urbanization, through remote sensing data; and later to determine the impacts of such changes on the Rispana watershed hydrology. The LULC maps for the year 2003 and the 2017 were generated through supervised classification technique using the Landsat Series satellite datasets. The LULC change analysis depicted that mainly the urban settlement class increased with significant area among other classes from the year 2003–2017. It was noticed that majorly agriculture and fallow land (8.18 km², which is 13.52% of total watershed area) converted to urban, increasing the impervious area. Almost all the municipal wards, falling in the Rispana watershed, showed urbanization during the said period, with an increase of as high as 71%. The change in LULC or effect of urbanization on the hydrological response of the watershed was assessed using the most widely used Natural Resources Conservation Services Curve Number method. It was noticed that the area under moderated runoff potential (approx. 10.23 km²) steeply increased during the lean season, whereas, high runoff potential zones (5 km²) increased significantly under wet season. Therefore, it was concluded that an increase in impervious surface resulted in high runoff generation. Further, such LULC change along with climate might lead to high runoff within the watershed, which the present storm drainage network could not withstand. The situation generally led to urban floods and affected urban dwellers regularly. Therefore, it is critical to assess the hydrological impacts of LULC change for land use planning and water resource management. Furthermore, under the smart city project, the local government has various plans to improve present infrastructure; therefore, it becomes necessary to incorporate such observations in the policies.

     

Effect of land use land cover changes on land surface temperature during 1984–2020: a case study of Baghdad city using landsat image

Natural Hazards - Urban land surface temperature (LST) is dependent on many factors, including land cover, building materials, urban density, and other human activities. The current study evaluated...     

Levels and distribution of total nitrogen and total phosphorous in urban soils of Beijing, China

Urban soil nitrogen and phosphorus have significant implications for the soil and water quality in urban areas. The concentrations of total nitrogen (TN) and total phosphorus (TP) of soil samples collected from six types of land use, which included residential area (RA), business area (BA), classical garden (CG), culture and education area (CEA), public green space (PGS) and roadside area (RSA) of Beijing urban area, were investigated. Results showed that the geometric mean of TP (857 mg/kg) in urban soils was slightly higher than that (745 mg/kg) in rural soils of Beijing. The concentration of soil TP was higher in the center of the city, and showed an increasing trend with the age of the urban area. The TP concentrations in the six types of land use followed the sequence of CG > BA > RSA > RA > CEA > PGS, which were affected by the use and disposal of phosphorus-containing materials in each type of land use. However, the geometric mean of TN (753.8 mg/kg) in urban soils was much lower than that (1,933.3 mg/kg) in rural soils. TN level in urban soils of Beijing had no correlation with the city’s urbanization history, and was influenced by the coverage of natural vegetation and human activities in each type of land use. This study suggested that the city’s urbanization history and land use were the main factors affecting the distribution of nitrogen and phosphorus in urban soils.     

Assessment of land-use change and its impact on the environment using GIS techniques: a case of Kolkata Municipal Corporation,West Bengal,India

It is axiomatically true that urbanization in India's metropolises and large cities has been exacerbated since the beginning of the millennium, consuming the natural and semi-natural ecosystem on the outskirts of the city, resulting in a zone with a distinct climate known as urban climate. Such a climate—the result of a built-up environment is distinctly different from the natural climate as the paved surface and concrete skyscrapers not only destroy the natural ecosystem, it peculiarly induce a different kind of insolation, cooling and air drainage were lacking in green space, water bodies and open space cannot accommodate with environmental rhythm properly, resulting into the accumulation of heat, ecological derangement of subsurface soil which can easily be predicted by GIS analysis. This paper is an attempt to measure urban growth and its impact on the environment in the metropolitan city Kolkata. The use of satellite data and GIS techniques to detect urban expansion is a highly scientific strategy. Using geospatial techniques, the current study attempts to examine major urban changes in Kolkata and its surroundings from 1988 to 2021. Landsat 5 TM and Landsat 8 OLI temporal data are used to identify land-use change through unsupervised classification; Spectral Radiance Model and Split Window Algorithm method are used for identifying land surface temperature change. SRTM DEM (30 m) has been used to identify flood risk zones and several spectral indices like Normalized Difference Vegetation Index and Modified Normalized Difference Water Index are a further extension for environmental assessment. By all such suitable methods, a clearer change in an urban environment is detected within the period of 33 years (1988–2021). The result shows that the population changes, vegetation cover and built-up area, and accessibility are at a rapid rate. These changes are causing major environmental degradation in the city. The classification result indicates that appropriate land use planning and environmental monitoring are required for the long-term exploitation of these resources.

     

基于土地集约利用水平的城市热岛效应影响因子分析

利用乌鲁木齐市1990年8月6日、2001年7月11日和2013年7月4日三期热红外遥感数据,定量反演亮度温度,利用均值-标准差法对温度进行分级后评价城市热岛效应时间变化特征:1990、2001、2013年3个时段,乌鲁木齐市最大热岛强度分别为11.48℃,12.06℃和14.01℃;加权平均热岛强度分别为1.033℃,1.603℃,1.236℃;城市热岛比例指数分别为0.1054,0.3945和0.4328;乌鲁木齐市城市热岛效应在平均水平上呈现先增强、后减弱的趋势,最大热岛强度、热岛比例指数均增加,城市已初步形成区域内的"热岛",城市高温区温度将继续上升且面积存在扩展趋势.利用PSR模型构建指标体系对城市土地集约利用水平进行评价,在同时段内乌鲁木齐市城市土地集约利用水平和协调性均在提高.从评价结果出发,通过相关分析,得出基于土地集约利用的城市热岛效应影响因子包括:人口密度、建成区绿地覆盖率、地均国民生产总值、人均建设用地面积、人均道路铺装面积、地均固定资产投资,这些因子涵盖了经济、社会、环境三个方面.     

黑龙江省漠河地区土地覆被与地表温度时空变化特征研究

以我国高纬度多年冻土区漠河县城区及郊区862 km²的区域为研究对象,基于RS和GIS技术对该区地表覆被变化和地表温度进行研究。结果表明：地表类型和地表温度反演结果与现场比对结果一致;从1988年到2015年,经过火灾后重建和城镇化发展,建设用地面积增加了11.33 km²;以2015年为例,冬季由于积雪覆盖,有79.02%的区域无植被覆盖,夏季有80.91%的区域为高植被覆盖。冬季地表温度和高程具有高度相关性,高程每升高100 m,地表温度平均升高2.27℃,表明该区地表温度也存在显著的逆温现象。该区城镇热岛效应全年存在,城镇区域地表温度高于全区平均值,夏季最显著,最高温差可达6.37℃。地表温度与NDVI具有明显的负相关关系;不同土地利用类型地表温度由低到高的顺序为水体-林地-草地-裸地-建筑用地。     

Analyzing and modeling of a large river basin dynamics applying integrated cellular automata and Markov model

Historical and exact information about the land use/land cover change is very important for regional sustainable development. The aim of this paper is to determine the rapid changes in land use/land cover (LULC) pattern due to agriculture expansion, environmental calamities such as flood and government policies over Upper Narmada basin, India. Multi-temporal Landsat satellite images for years 1990, 2000, 2010 and 2015 were used to analyze and monitor the changes in LULC with an overall accuracy of more than 85%. Results revealed a potential decrease in natural vegetation (? 9.52%) due to the expansion of settlement (+ 0.52%) and cropland (+ 9.43%) from 1990 to 2015. In the present study, Cellular Automata and Markov (CA–Markov), an integrated tool was used to project the short-term LULC map of year 2030. The projected LULC (2030) indicated the expansion of built-up area along with the cropland and degradation in the vegetation area. The outcomes from the study can help as a guiding tool for protection of natural vegetation and the management of the built-up area. Additionally, it will help in devising the strategies to utilize every bit of land in the study area for decision makers.     

新疆乌鲁木齐市城市化与土地利用结构的Granger因果关系分析

在城市化与土地利用结构的协调发展成为焦点问题的时代背景下,以新疆乌鲁木齐市为研究区域,采用Johansen协整检验和Granger因果关系分析法,对乌鲁木齐市2000-2015年的城市化水平及5类代表性城市用地结构变化数据进行了处理,并对城市化与用地结构进行了因果关系分析。结果表明：（1）2000-2012年,乌鲁木齐市城市化水平由84.82%降至77.12%,呈下降趋势;2013-2015年由77.73%升至81.62%,呈上升趋势,造成这一现象的主要原因是非农业人口增长速率相对于农业人口增长速率较慢;（2）2000-2015年各类用地所占比例变化情况如下：居住用地比例均在26%以上,明显高于其他用地;工业用地比例较为稳定,均为15%~19%;公共设施用地2014-2015年明显下降,即从平均比例11.46%降至5.03%;城市道路用地比例较稳定,均为5.8%~7.5%;绿地比例呈上升趋势,由20.01%升至30.94%;（3）城市化与居住用地之间的Granger因果关系不明显,工业用地、公共设施用地、城市道路用地是引起城市化的Granger原因,城市化是绿地的Granger原因。对乌鲁木齐市城市化与土地利用结构进行因果关系分析,对城市用地格局的改善、土地利用战略以及有关政策法规的制定具有一定的参考意义。     

城市不透水面与地表温度定量关系的遥感分析

作为城市下垫面的最主要组成部分,城市不透水面是引发城市热岛效应的主要因素,但目前不透水面与地表温度之间的定量关系仍不明确,不同研究的结论也不尽相同。选取了上海、广州、北京、长沙、兰州、福州等6个代表我国不同区域的城市作为研究区来进一步研究城市不透水面与城市热环境的定量关系。采用Landsat ETM+影像和线性光谱混合分析法提取出各个研究区的不透水面,利用热红外波段反演出各研究区的地表温度,采用多种回归模型和大样本量对二者之间的相关关系进行定量分析;在此基础上讨论了不透水面对城市热环境的影响机制。结果表明：不透水面与地表温度呈明显的正相关关系,并且以指数函数为最佳拟合模型,回归方程的相关系数均为0.750以上,最高可达0.954 1;高不透水面盖度地区的升温幅度更大,比低不透水面盖度地区高出0.600~1.700 ℃,其原因主要是高不透水面盖度地区的植被覆盖率低,蒸腾蒸发作用小。