In order to improve the accuracy of detection for the landscape change, we presented the differencing image PCA method to improve the Principal Component Analysis ( PCA ) and the band difference of images method using the multi-temporal remotely sensed data of TM ( Thematic Mapper(TM) ). 为了提高检测精度,我们利用TM卫星遥感数据,改进了主成分分析法和图像差值法,提出了差分主成分分析法。
Using Thematic Mapper(TM) data, to extracting thematic information, the article explores two kinds of techniques : Separate technique and mask technique, for degrading vegetable cover effects. 探讨了运用TM影像提取专题信息时降低植被影响的两类技术:分离技术和掩膜技术以及分类原因,同时具体介绍了它们所包括的几种方法的基本原理和应用效果。
Analysis of Thematic Mapper(TM) Satellite Data for Automatic Classification of Field Crops 用陆地卫星TM数据对农作物进行自动分类的研究
Landsat thematic mapper ( TM ) has a thermal band ( TM6 ), and this band can be used for retrieving land surface temperature ( LST ). 陆地卫星LANDSATTM有一个热波段(TM6),可以用来反演地表温度。目前共有3种算法可以用来从TM6波段数据中反演地表温度:大气校正法、单窗算法和单通道算法。
Landsat Thematic Mapper(TM) ( TM ) image is rich in spectral information, while SPOT panchromatic data is fine in its spatial resolution. Complementary and effective use of these data has shown in its increasing importance in the field of remote sensing application. 陆地卫星TM图像含有丰富的光谱信息,SPOT全色波段图像数据分辨率较高,因此,如何将这两种图像数据有效地结合起来,在遥感应用领域中显得越来越重要。