Urban heat island (UHI) effect has a close relation to land covers type. This paper investigates the relationship between
land cover ratio and UHI in Guangzhou, south of China using remote sensing and automatic weather stations data. The temperature
data were obtained by Automatic weather stations (AWS) of Guangzhou in October, 2004, at the same time with the CBERS remote
sensing image acquired. Firstly, the hourly mean temperature was computed from hourly AWS data. Secondly, the CBERS remote
sensing image was classified using support vector machine (SVM) and land covers classification were output. Thirdly, the classification
result was overlapped with a round buffer with 1.5 KM radius centered on the AWS, and then the land cover ratio, Edge Density
(ED) and Mean Fractal Dimension (MFRACT) of buffers were computed out. Finally, the correlation coefficient between hourly
mean temperature and land cover ratio, ED and MFRACT was calculated. It concluded that UHI intensity was heavier during nighttime
than daytime. Stations with higher vegetation ratio and higher ED had lower heat island effect. On the contrary, stations
with higher impervious ratio and lower ED had more serious heat island effect. The positive–negative of correlation coefficient
between hourly mean temperature and vegetation ratio during 11:00–17:00 h (local time) was opposite to that during other time.
ED was negatively correlated with hourly mean temperature except during 11:00–17:00 h. On the contrary, MFRACT was positively
correlated with hourly mean temperature. It implied that fragmentations of patches were favorable to UHI alleviation, and
complexities of patch were unfavorable factors. 相似文献
Application scope of geostatistics has been gradually extended from original geologic field to soil science and ecological field, etc. and its successful application results have been widely demonstrated. But little information is reported as to the direct use of geostatistical method to work out the distribu- tion map of groundwater characteristics. In this paper the semivariogram of geostatistics, in combina- tion with GIS, was used to quantitatively study the spatial variation characteristics of groundwater table depth and mineralization degree and their relation to the landuse changes. F test of the used spherical model reached a very significant level, and the theoretical model can well reflect the spatial structural characteristics of groundwater table depth and mineralization degree and achieve an ideal result. This shows that the application of the method in the dynamical simulation of groundwater is feasible. And this paper also provides useful reference for the application of geostatistics in the study of the dy- namical variations of groundwater resources in the oasis. 相似文献