以Landsat 7 ETM+、SPOT 5和IKONOS遥感影像数据为数据源, 利用格网法从1∶500地形图提取的不同空间分辨率的植被覆盖度为参考依据, 通过对不同辐射校正水平的遥感影像获得的植被覆盖度进行精度比较分析, 对多源多尺度和多源同尺度城市植被覆盖度估算的相关问题进行研究.研究表明, 在城市区域进行植被覆盖度估算时, ICM模型为较佳辐射校正模型; 对于高分辨遥感影像, NDVI为植被覆盖度估算的较佳植被指数; 对于中分辨率影像, 植被覆盖度估算的较佳植被指数则为RVI和MSAVI; 就研究区而言GI模型比CR模型估算的植被覆盖度更准确.

The vegetation coverage from multi-source at multi-scale and multi-source at the same scale in urban area was studied. The Landsat 7 ETM+, SPOT 5 and IKONOS remote sensing image data were taken as the data source. The vegetation coverage with different spatial resolutions derived from a 1∶500 topographic map as the reference map by grid method was taken as reference. The accuracies of fraction vegetation coverage extracted from the images, wich were radiometrically corrected using different models, were compared. An optimal radiometric correction model for the extraction of fraction vegetation coverage in urban areas was proposed. The results show that ICM model is the best radiometric correction model for estimating fraction vegetation coverage in urban area. NDVI is the best vegetation index for fraction vegetation coverage estimation for high resolution remote sensing images, while the best vegetation indices for estimating fraction vegetation coverage from moderate spatial resolution images are the RVI and MSAVI. For the studies area, the GI model is more accurate than the CR model in estimating the vegetation coverage.