Quantitative Assessment of Vegetation Coverage Factor in USLE Model Using Remote Sensing Data

MA Chao-fei; MA Jian-wen; Buhe Aosaier

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Quantitative Assessment of Vegetation Coverage Factor in USLE Model Using Remote Sensing Data

- Quantitative Assessment of Vegetation Coverage Factor in USLE Model Using Remote Sensing Data
- Bulletin of Soiland Water Conservation Vol. 20, Issue 4, Pages: 6-9(2001)
- 作者机构：
  
  中国科学院遥感应用研究所,北京,100101
- 作者简介：
- 基金信息：
- DOI：
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- Published：2001
- 稿件说明：
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MA Chao-fei, MA Jian-wen, Buhe Aosaier. Quantitative Assessment of Vegetation Coverage Factor in USLE Model Using Remote Sensing Data[J]. Bulletin of Soiland Water Conservation, 2001, 20(4): 6-9.
DOI：

MA Chao-fei, MA Jian-wen, Buhe Aosaier. Quantitative Assessment of Vegetation Coverage Factor in USLE Model Using Remote Sensing Data[J]. Bulletin of Soiland Water Conservation, 2001, 20(4): 6-9. DOI：

摘要

植被具有截留降雨、减缓径流、保土固土等功能

对水土流失起着决定性的作用

植被盖度的大小直接影响着水土流失程度的强弱。植被因子是通用水土流失方程 (USLE)中的重要影响因素。选择相适应的卫星遥感时间和空间分辨率ETM数据可以提取植被盖度参数。一般说来

归一化植被指数

比较真实地表现了影像数据上植被的分布

但是

Ic/i>

仅仅定性地反映了植被盖度的相对大小

要想量化植被盖度还必须进行野外采样

样方与影像

作回归统计分析

建立经验公式

最终反演植被覆盖度。这种方法不仅耗费大量的人力物力

而且不利于大区域土壤侵蚀的监控和预测。针对这个问题提出利用线性混合像元分解的方法对影像逐个像元中的植被盖度进行计算和提取

提高了模型中植被盖度因子的精度

降低研究成本

进而可以快速地进行土壤侵蚀量变化动态监测。

Abstract

Vegetation coverage represents an important role in lessening soil loss

protecting environment and improving the standard of living.USLE

as a convenient model

is applied widely.The studies mainly on method extracting vegetation coverage by using spatial and temporal remote sensing data.As a result of mixing pixels

there is something itself shortcoming for the technique of NDVI monitoring vegetation coverage

and it needs much manpoer and time for field sampling.Linear spectral unmixing is a simpler way reducing workload and improving accuracyof extracting vegetation coverage in remo te sensing image.It need not field sampling and regressive analysis.The value extent of vegetation coverage factor C in USLE model lies between 0 and 1

but the value changed greatly.So the precision of C value is a key to USLE model.

关键词

Keywords

references

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