中文摘要：

地表温度是生态系统中极其重要的环境因子，中小尺度区域的热场空间分布对生态系统稳定性的研究以及干旱区流域的农业生产建设具有重要意义。利用MODIS数据，采用劈窗算法反演石羊河流域的陆地表面温度（LST），并计算植被指数（NDVI）；利用TM影像，通过目视解译获得研究区的土地利用数据，结合DEM数据，采用GIS空间分析方法，分析LST的空间分布特征和LST与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。结果表明：研究区陆地表面温度北高南低，东高西低，整体上表现为由东北向西南逐渐降低的趋势；地表温度与海拔呈负线性相关，相关系数为-0．928；不同土地利用类型的地表温度存在差异，地表温度最高的未利用土地要比最低的林地高出16．42K；对于单一土地利用类型，耕地、林地、草地、建设用地的地表温度与NDVI具有明显负相关；对于整个研究区土地利用空间结构，地表温度与NDVI表现为LST—NDVI梯形关系，反映了流域地表温度和植被覆盖之间的关系，由此看出绿色植被对调节区域气候温度的重要性。

英文摘要：

Land surface temperature （LST ） is a very important environmental factor to impact the energy and wa- ter exchange between the atmosphere and the ecosystem. The spatial distribution of LST in small and medi- um-scale region has a great significance on the stability of ecosystems and agricultural production and construction of the arid basins. In this study, the Shiyang River Basin in Gansu Province is chosen as the study area. It is a typi- cally arid inland basin and its ecological environment is very fragile. The LST is retrieved from MODIS data by split-window algorithm, and the normalized difference vegetation index （ NDVI ） is calculated by its first band and second band. At the same time, the land use/cover is acquired from TM data by human-computer interactive inter- pretation. Combined with land use/cover and DEM data, the spatial distribution of LST is identified and the relation between NDVI and LST is analyzed in different land use types. The result shows as follows： （1）The LST in the north and the east is higher than that in the south and the west of the study area, respectively. It performed the trend that the LST reduced gradually from the northeast to the southwest. （2）There is a negative correlation between LST and altitude, and the correlation coefficient is -0.928. Due to the differences in heat capacities, different land use/cover types, LST also has differences. The quantitative difference is 16.42 K between the highest LST of un- used land and the lowest LST of forest land. （3）For single type of land use/cover, LST and NDVI have a signifi- cant negative correlation between cropland, forest land, grassland, and construction land. For the whole configuration of land use/cover in the study area, the relation between LST and NDVI displays ＇trapeziform＇. The feature space of NDVI- LST contains a lot of geo-information, which reflects the relationship between the basin surface tempera- ture and vegetation cover. And from the feature space of NDVI-LST, we can see that the g