In this paper, first the land surface brightness temperature was retrieved by single channel algorithm based on multi-temporal Landsat TM/ETM+ data, then NDVI, MNDWI, NDBI and NDBaI indices were calculated to classify the land use/cover types in the study area by the decision tree method and, finally, the spatial and temporal changes of Urban Heat Island (UHI) and the relationship between UHI and land use/cover change in Changsha City were studied. The results show that the extent of UHI increases with the expansion of the built-up area in Changsha City, that the change of land use/cover types is likely to cause the variation of the spatial distribution of Land Surface Temperature (LST), and that the built-up area and the barren land seem to be the major factors responsible for UHI intension, while the water body and the forest land play an important role in reducing LST. Regression analysis shows that there exists a significant correlation between LST and the four indices, and there also exist remarkable LST differences in different land use/cover types.

基于多时相Landsat TM/ETM+影像，首先计算长沙市地表亮度温度，然后利用NDVI(归一化植被指数)、MNDWI(改进 的归一化水体指数)、NDBI(归一化建筑指数)和NDBaI(归一化裸土指数)4个指数，采用决策树分类方法对长沙市影像进行 土地利用/覆盖分类。在此基础上，对长沙市城市热岛的空间分布特征、时空演变特征以及城市热岛与土地利用/覆盖变化和各种影 响因子之间的关系进行研究。结果表明，随着长沙市城区范围的不断扩张，城市热岛范围也不断增大； 土地利用/覆盖类型的变化 会改变地表温度的空间分布，城市用地和裸地是城市热岛强度的主要贡献因素，水体和林地具有较好的降温作用。地表温度与4种 归一化指数的回归分析表明，它们之间存在明显的相关性，不同土地利用/覆盖类型的地表温度存在较大差异。

In urbanization process, greater consideration of the manner in which rural lands are developed for urban lands will become progressively more important. Removal of rural land cover types such as soil, water, and vegetation and their replacement with common urban materials such as asphalt, concrete, and metal have significant environmental implications including reduction in evapotranspiration, promotion of more rapid surface runoff, increased storage and transfer of sensible heat, and reduction of air and water quality. Thermal environment and vegetation cover are two important factors for urban eco-environment. Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) associated with urban land use type and land use pattern are discussed in this paper, using the data collected by the Landsat7 Enhanced Thematic Mapper Plus (ETM+) and aerial photography remote sensing system in the city of Shanghai. Analysis of variance indicates statistically significant differences in mean LST and NDVI values. Mean LST and NDVI values associated with different land use types are significantly different. There is an apparent correlativity between LST and NDVI from the profile line values of the two factors. Multiple comparisons of mean LST and NDVI values associated with pairings of each land use type by Tamhane’s T2 post-hoc tests are also shown to be significantly different. The result of a regressive analysis shows a significant inverse correlation relationship between LST and NDVI associated with all land use polygons, the same associated with each land type, but correlation coefficients associated with land use types are different. Then an analysis was performed about the relationship among LST, NDVI and Shannon Diversity Index (SHDI), which shows a positive correlation between LST and SHDI and a negative correlation between NDVI and SHDI. As the SHDI continue to increase, it’s more sensitive of LST change on the influence of NDVI.According to the above results, LST, SHDI and NDVI can be considered to be three basic indices to reflect urban eco-environmental effect of urban land use/cover and to contribute to further validation of the applicability of relatively low cost, moderate spatial resolution satellite imagery (TM or ETM+) in evaluating environmental impacts of urban land function zoning, then to examine the impact of urban land use/cover on the urban eco-environment in the city of Shanghai, China. And this paper also provides an effective tool in evaluating environmental influences of zoning in urban ecosystems with remote sensing and geographic information system. As higher resolution remote sensing imagery becomes more commonly available, the methods presented in this research could be extended to more specific urban design considerations that impact the thermal and vegetation components of urban ecosystems at finer spatial scales.

城市化过程中，农村的土壤、水面以及植被等土地覆被类型逐渐减少，取而代之的是由沥青、水泥以及金属等组成的不透水表面，这个过程导致地表水分蒸腾减少、径流加速、显热的存储和传输增加以及水质降低等一系列生态环境效应，其中最明显的两个特征就是土地覆被的植被减少、城市热岛的出现。而城市土地利用类型及其空间结构的生态环境效应同时又是城市生态学中的关键问题，其研究对优化城市功能分区和城市规划管理以及城市可持续发展等都具有重要意义。以上海市为例，采用Landsat7的ETM+为基本数据源，首先定量反演了每个像元内的陆地表面温度（LST）和植被指数（NDVI），然后利用GIS中的空间分析功能，将由于城市土地覆被所形成的生态环境效应综合到土地利用的图斑中来，按照这个思路对城市土地利用的生态环境效应进行研究。分析LST、NDVI在不同土地利用类型之间的差异以及二者之间的定量关系，并引入多样性指数（SHDI），讨论了不同土地利用的空间组合下，LST和NDVI的空间差异及相互关系。研究结果显示：LST和NDVI具有明显的相关性，LST大的区域对应NDVI一般都较小，反之亦然；中心城市LST表现出热岛效应，而NDVI则为低谷效应。通过Tamhance T2 post-hoc多重比较发现， LST以及NDVI在两两土地利用类型之间的差异不同。 从土地利用斑块和类型两种尺度水平上建立了LST和NDVI的定量关系，二者具有明显负相关的线性关系，但在不同土地利用类型上二者关系并不同。其中工业仓储、交通用地与公园绿地、农业用地差异最为显著。它们和SHDI之间的关系揭示，LST与土地利用多样性具有正相关关系，而NDVI则与SHDI呈负相关关系，SHDI越大的地区，LST越大，而NDVI越小。由此，可以将LST、NDVI和SHDI作为三个基本指标，来定量评价城市土地利用类型、结构对生态环境的影响，以此作为城市功能分区中生态环境影响评价的参考。也为高性价比的中等分辨率遥感数据与GIS空间分析方法结合在城市规划中的应用提供了一种新的思路。

The fast urban spatial expansion has led to the substitution of the natural vegetation-dominated land surfaces by impervious materials. This has a significant impact on the ecosystem on a local to global scale. Therefore, a clear understanding the relationship of urban impervious surface area with vegetation, water and land surface temperature is of meaningful for scientific urban planning and ecosystem restoring. Nevertheless, such a study is still very rare due probably to the difficulty in getting impervious surface data. Taking the advantage of the remote sensing technology, the information of urban impervious surface area, vegetation, water and land surface temperature can be extracted from remote sensing imagery. Using Fuzhou city of southeastern China as a case, this paper analyzed the relationship between the above-mentioned components of urban ecosystem through enhanced remote sensing images. The study reveals that the urban impervious surface area has a strong positive exponential relationship with the land surface temperature rather than a simple linear relationship. This suggests that the areas with high impervious surface percentage will accelerate the increase in land surface temperature much more than the areas with low percentage. Multivariate statistics has proved that urban impervious surface area is the most important factor contributing to the development of the urban heat island while water and vegetation can significantly reduce the urban heat island effect.

城市空间的快速扩展已使得原来以植被为主的自然景观逐渐被人工不透水建筑物所取代，并对区域乃至全球的生态系统造成了明显的影响。因此，准确了解城市不透水面及其与植被、水体、城市热环境的相关关系对于城市的科学规划和城市生态系统的修复具有重要的意义。以福州市为例，采用遥感空间信息技术，获得了城市不透水面、地表温度、植被和水体的信息，并对它们的关系进行了定量分析。发现了城市不透水面与地表温度之间的关系并不是一种简单的线性关系，而是一种很显著的指数函数关系，说明高不透水面比例地区的升温效应要明显高于低不透水面比例地区。多元统计分析表明不透水面是引发城市热岛的最重要因子。

This paper compares the normalized difference built-up index (NDBI) and normalized difference vegetation index (NDVI) as indicators of surface urban heat island (SUHI) effects in MODIS imagery by investigating the relationships between the land surface temperature (LST), NDBI and the NDVI. MODIS data were used to estimate the LST, NDBI and NDVI from four different dates for Changsha-Zhuzhou-Xiangtan metropolitan area. Our analysis indicates that there is a strong linear relationship between LST and NDBI, whereas the relationship between LST and NDVI is much less strong and varies by season. This result suggests NDBI is an accurate indicator of SUHI effects and can be used as a complementary metric to the traditionally applied NDVI for analyzing LST quantitatively over the seasons for SUHI studies.

基于4个季节的MODIS影像,计算长株潭地区的地表温度、NDBI和NDVI,比较NDBI和NDVI与地表温度之间关系,对地表城市热岛效应研究的指标NDBI和NDVI进行对比分析。结果表明,NDBI与4个季节的地表温度间都存在明显的线性关系,而NDVI与地表温度间关系并不明显且随季节发生变化,说明NDBI是地表城市热岛效应研究的有效指标,在地表城市热岛效应的季节变化研究中NDBI可作为NDVI的一个附加指标。

The Zhujiang Delta has experienced a rapid land cover change, especially urban expansion over the past 25 years due to accelerated economic growth. This paper reports an investigation into the application of the integration of remote sensing and geographic information systems (GIS) for detecting land cover change and urban growth, and assessing their impact on land surface temperature in the region. Remote sensing techniques were used to carry out land use/cover change detection by using multitemporal Landsat TM/ETM data, and retrieve out the land surface temperature by using single Landsat TM/ETM 6 thermal infrared data. The integration of remote sensing and GIS was further applied to examine the impact of land cover change and urban growth on land surface temperatures. The results revealed a notable and uneven urban growth in the study area. This urban development has raised land surface radiant temperature by 8.9K in the urbanized area. The integration of remote sensing and GIS was found to be effective in monitoring and analyzing urban growth patterns, and in evaluating urbanization impact on land surface temperature.

由于经济的快速增长,1978年以来的25年中,珠江三角洲地区的土地覆盖变化,特别是城市扩展速度非常之快。通过把遥感和地理信息系统相结合,研究了土地覆盖变化及城市增长状况,并且评估了城市增长对地表温度的影响。利用陆地卫星多时段数据监测了土地利用和土地覆盖变化;通过陆地卫星热红外单波段反演了地表温度,研究了土地覆盖变化特别是城市增长对地表温度的影响。结果发现,珠江三角洲地区土地覆盖变化明显,城市增长显著且不平衡。城市的发展使城市化地区的地表温度提高了8.9K。研究表明,遥感和地理信息系统的结合,在监测和分析土地覆盖变化,特别是城市增长状况以及评估城市化对地表温度的影响方面,是十分有效的。

Landsat TM data has a thermal band (TM6) to monitor the thermal radiance and surface temperature of the earth. For a long time, retrieval of surface temperature from TM6 data is done through the method called atmospheric correction, which requires the estimate of atmospheric thermal radiance and absorption. The computation is complicated and the accuracy is strongly subjected to the estimate, hence has few applications in real world. In this paper, a new method with simple computation and high accuracy is developed on the basis of thermal radiance transfer equation of the ground. The impacts of both atmosphere and the emitted ground on the thermal radiance transfer of the ground are directly involved into the proposed algorithm, which requires 3 essential parameters for the retrieval: emissivity, transmittance and atmospheric average temperature. Validation indicates that the accuracy of the algorithm is high up to <0.4℃ for the estimate of the essential parameters with no errors and <1.1℃ for the estimate moderate errors. Since the method is applicable for the remote sensing data with only one thermal band, it has been termed as mono window algorithm.

陆地卫星 TM数据 (TM6)热波段表示地表热辐射和地表温度变化。长期以来,从 TM6数据中演算地表温度通常是通过所谓大气校正法。这一方法需要估计大气热辐射和大气对地表热辐射传导的影响,计算过程很复杂,误差也较大,在实际中应用不多。根据地表热辐射传导方程,推导出一个简单易行并且精度较高的演算方法,把大气和地表的影响直接包括在演算公式中。该算法需要用地表辐射率、大气透射率和大气平均温度 3个参数进行地表温度的演算。验证表明,该方法的地表温度演算较高。当参数估计没有误差时,该方法的地表温度演算精度达到 <0 .4℃,在参数估计有适度误差时,演算精度仍达 <1 .1℃。因该方法适用于仅有一个热波段的遥感数据,故称为单窗算法。

A modified normalized difference water index(MNDWI) has been proposed in this paper based on the normalized difference water index(NDWI) of Mcfeeters (1966), which uses MIR(TM5) instead of NIR(TM4) to construct the MNDWI. The MNDWI has been tested in the ocean, lake and river areas with the background of built-up lands and/or vegetated lands, and with both clean and polluted water bodies using Landsat TM/ETM imagery. This reveals that the MNDWI can significantly enhance the water information, especially in the area mainly with built-up land as background. The MNDWI can depress the built-up land information effectively while highlighting water information, and accurately extract the water body information from the study areas. While the enhanced water information using the NDWI always has been mixed with built-up land noise and the area of a water body extracted based on the index is thus overestimated. Therefore, the NDWI is not suitable for enhancing and extracting water information in built-up land-dominated areas. Furthermore, the MNDWI can reveal subtle features of water more efficiently than the NDWI or other visible spectral bands do due largely to its wider dynamic data range. The application of the MNDWI in the Xiamen image has achieved an excellent result. The MNDWI image successfully reveals significant non-point pollution of the water surrounding the Xiamen Island due to agricultural activities. In addition, taking the advantage of the ratio computation, the MNDWI can remove shadow noise from water information without using sophisticated procedures, which is otherwise difficult to be removed.

在对M cfeeters提出的归一化差异水体指数(NDWI)分析的基础上,对构成该指数的波长组合进行了修改,提出了改进的归一化差异水体指数MNDWI(M odified NDWI),并分别将该指数在含不同水体类型的遥感影像进行了实验,大部分获得了比NDWI好的效果,特别是提取城镇范围内的水体。NDWI指数影像因往往混有城镇建筑用地信息而使得提取的水体范围和面积有所扩大。实验还发现MNDWI比NDWI更能够揭示水体微细特征,如悬浮沉积物的分布、水质的变化。另外,MNDWI可以很容易地区分阴影和水体,解决了水体提取中难于消除阴影的难题。