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Remote Sensing Technology and Application  2010, Vol. 25 Issue (3): 366-372    DOI: 10.11873/j.issn.1004-0323.2010.3.366
article     
Land Classification Based on Remote Sensing Data and Analysis of Spatial Distribution in Zuli River Basin
PENG Shou-zhang1,ZHAO Chuan-yan1,BIE Qiang2
1.Key Laboratory of Arid and Grassland Ecology with the Ministry of Education,Lanzhou University, Lanzhou 730000,China; 2.National Laboratory of Western China’s Environmental System,Lanzhou University, Lanzhou 730000,China
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Abstract  

Taking the Zuli River basin in Loess Plateau of Longxi as the study area,the land classification was carried on using Landasat TM7 data in 1993 and 2007 respectively.The land use types were combined with topographical data from DEM and the spatial distribution data of multi-annual mean precipitation.The distribution spaces of terrain and climate for farmland,forest land and grassland were obtained. The conclusion can be drawn from the approach:① the area about 214.82 km2 of farmland is controlled in 14 years,and about 145.08 km2 of farmland should be converted into grassland and forestland in 2007,because it is located at above the threshold of slope(18.2°); ②forest land is distributed the area where precipitation is between 386 mm and 517 mm,and planted forest is increasing in 14 years; ③coverage of grass has generally been reduced due to the human activities.To mediate the soil erosion and water loss in this primarily hilly loess area,the vegetation’s restoration and reconstruction is very important.The objective of this research will provide the scientific support for returning farmland to forestland or grassland,which will contribute to build the positive cycle of the ecosystem in Zuli River basin.

Key words:   Distributed space             Remote sensing      Land classification      Zuli River basin     
Published:  20 October 2010
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PENG Shou-zhang
ZHAO Chuan-yan
BIE Qiang

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PENG Shou-zhang, ZHAO Chuan-yan, BIE Qiang. Land Classification Based on Remote Sensing Data and Analysis of Spatial Distribution in Zuli River Basin. Remote Sensing Technology and Application, 2010, 25(3): 366-372.

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http://www.rsta.ac.cn/EN/10.11873/j.issn.1004-0323.2010.3.366     OR     http://www.rsta.ac.cn/EN/Y2010/V25/I3/366

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