[1]ZHANG Chao,WANG Yan,SONG Wei-feng.Assistant Classification Feature of Terrace in Yuanyang County of Yunnan Province Based on Remote Sensing[J].Research of Soil and Water Conservation,2014,21(05):221-224.
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Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume:
21
Number of periods:
2014 05
Page number:
221-224
Column:
Public date:
2014-10-28
- Title:
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Assistant Classification Feature of Terrace in Yuanyang County of Yunnan Province Based on Remote Sensing
- Author(s):
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ZHANG Chao, WANG Yan, SONG Wei-feng
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Southwest Forestry University, Kunming 650224, China
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- Keywords:
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spatial distribution; vegetation index; Pixel DN; terrace in Yuanyang County
- CLC:
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S157
- DOI:
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- Abstract:
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The analysis and study on the spatial distribution characteristics and spectral characteristics of terrace in Yuanyang County could provide expert knowledge for the classification and recognition based on remote sensing. The deficiency of traditional inventory method would be overcome, and the spatial distribution and the dynamic changes could be accurately monitored. Based on the visual interpretation of terrace in Yuanyang County using the data of SPOT5 image, the information on altitude, slope, aspect, MODIS-NDVI and DN of Landsat TM bands were extracted. The assistant classification feature of terrace including the aspects of spatial distribution characteristic, vegetation index characteristic, and pixel DN characteristic in Yuanyang County was studied. The results showed that: a) the sequence of the influence extent was altitude > slope > aspect, the terrace in Yuanyang County mainly distributed in the area with altitude of 1 000~1 400 m, slope of 12°~33° and aspect of north and northeast; b) the average of MODIS-NDVI decreased gradually with the increase of patch area, the population mean of MODIS-NDVI was 0.754, the minimum was 0.378 and the maximum was 0.849; c) the value of pixel DN was low in visible bands, and it would be high in near-infrared bands. The band curve of Landsat TM pixel DN on the different grades showed the same trend.