Title: Research on land use/cover remote sensing classification using surface biophysical parameters——A case study of Changsha city
Abstract: Spectral reflection images are used for supervised or unsupervised classification.Because of phenomena of the same kinds of targets with different spectral or different kinds of targets with same spectral,the classification accuracy is low.Vegetation Index and surface temperature are two Biophysical parameters that represent condition of land cover,and have successfully applied into large scale land use/cover,but it is seldom reported that they have applied into regional land use/cover.Based on advantage of TM multi-spectrum data,this paper extract four classification features including Vegetation Index NDVI,land surface temperature Ts,Temperature-Vegetation Angel TVA and Temperature-Vegetation Distance TVD for supervised classification.Compared seven image processing routines(incorporation of vegetation index,surface temperature,vegetation index and surface temperature,temperature-vegetation angel,temperature-vegetation distance,temperature-vegetation angel and temperature-vegetation distance),the results indicate that proportion of training samples and test samples influences overall classification accuracy.It hasa higher classification accuracy using NDVI,Ts,NDVI and Ts,TVD,whereas,TVA 、TVA and TVD almost have no effect on classification accuracy improvement.
Publication Year: 2008
Publication Date: 2008-01-01
Language: en
Type: article
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