Accuracy assessment of land cover dynamic in hill land on integration of DEM data and TM image

To accurately assess the area of land cover in hill land, we integrated DEM data and remote sensing image in Lihe River Valley, China. Firstly, the DEM data was combined into decision tree to increase the accuracy of land cover classification. Secondly, a slope corrected model was built to transfer the projected area to surface area by DEM data. At last, the area of different land cover was calculated and the dynamic of land cover in Lihe River Valley were analyzed from 1998 to 2003. The results show that: the area of forestland increased more than 10% by the slope corrected model, that indicates the area correcting is very important for hill land; the accuracy of classification especially for forestland and garden plot is enhanced by integrating of DEM data. It can be greater than 85%. The indexes of land use extent were 266.2 in 1998, 273.1 in 2001, and 276.7 in 2003. The change rates of land use extent were 2.59 during 1998 to 2001 and 1.34 during 2001 to 2003.

[1]  N. Coops,et al.  Extracting urban vegetation characteristics using spectral mixture analysis and decision tree classifications. , 2009 .

[2]  David A. Landgrebe,et al.  A survey of decision tree classifier methodology , 1991, IEEE Trans. Syst. Man Cybern..

[3]  Xu Han-qiu.  Image-based Normalization Technique Used for Landsat TM/ETM~+ Imagery , 2007 .

[4]  Sassan Saatchi,et al.  The use of decision tree and multiscale texture for classification of JERS-1 SAR data over tropical forest , 2000, IEEE Trans. Geosci. Remote. Sens..

[5]  L.L.F. Janssen,et al.  Accuracy assessment of satellite derived land - cover data : a review , 1994 .

[6]  J. Michaelsen,et al.  Regression Tree Analysis of satellite and terrain data to guide vegetation sampling and surveys , 1994 .

[7]  Yang Shan,et al.  An Effective Approach to Automatically Extract Urban Land-use from TM lmagery , 2003, National Remote Sensing Bulletin.

[8]  Gyanesh Chander,et al.  Revised Landsat-5 Thematic Mapper Radiometric Calibration , 2007, IEEE Geoscience and Remote Sensing Letters.

[9]  R. DeFries,et al.  Classification trees: an alternative to traditional land cover classifiers , 1996 .

[10]  Paul M. Mather,et al.  An assessment of the effectiveness of decision tree methods for land cover classification , 2003 .

[11]  L. S. Davis,et al.  An assessment of support vector machines for land cover classi(cid:142) cation , 2002 .

[12]  J. Townshend,et al.  Global land cover classifications at 8 km spatial resolution: The use of training data derived from Landsat imagery in decision tree classifiers , 1998 .