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

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

您当前的位置：

首页 >

文章列表页 >

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：
  CLC：
- Published：2001
- 稿件说明：
移动端阅览
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

蔡崇法,丁树文,史志华,等.应用USLE 模型与地理信息系统IDRISI 预测小流域土壤侵蚀量的研究[J].水土保持学报,2000,14(2):20-26.

景可,卢金发,梁季阳,等.黄河中游侵蚀环境特征和变化趋势[M].郑州:黄河水利出版社,1997.

崔伟宏,微机资源与环境信息系统研究[M].北京:中国科学技术出版社,1990.

林恒章,朱博勤.陕北黄土高原地区土壤侵蚀类型与强度的遥感调查.见:陕北黄土高原地区遥感应用研究[M].北京:科学出版社,1991.46-60.

马霭乃.中国水土流失灾害的分类分级和危险度评价方法研究[M].中国自然灾害影响评价方法研究.北京:中国科学技术出版社, 1993.106-122.

韦中亚.石家庄市土壤侵蚀定量评价研究[J].水土保持研究,1999,6(4):41-44.

Icho ku Charles, Kar nieli Arnon.A review of mixture modeling techniques for sub-pixel land cover estimation[J].Remote sensing review,1996,Vol.13,161-186.

Geotz A F H.Principles of narrow band spectrometry in the visible and IR:instruments and data analysis[M].In imaging spectroscopy:Fundamentals and prospective application.1992.(Euro courses:Remote sensing volume(2).

Roberts D A,Smith M O,Adams J B.Green vegetation, nonphotosynthetic vegetation,and soils in AVIRIS data [J].Remote sens.of environ 44:255-269,1993.

Smith M O,Johnson P E,Adams J B.Quantative determination of mineral types and abundances from reflectance spectra using principal components analysis[C].In Proc.Lunar planet,Sci.Conf.15th, Part 2, J.o f geophysical research 90(suppl.), 1985.797-804.

Mustard J F, Pleters C M.Quantitative abundances estimates from bidirectional reflectance measurements[J].In Proc.Lunar planet, Sci.Conf.17th, part2, J.of geophysical research,1987.92(B4):617-626.

Hapke B.Bidirectional reflectance spectroscopy theory[J]. J.of geophysical research,1981.86(B4):3039-3054.

Johnson P E,Smith M O, Taylor-George S, Adams J B.A semiemprical method for analysis of the reflectance spectra of binary mineral mixtures[J]. J.of geophysical research,1983,88(B4):3557-3561.

Settle J J, Drake N A.Linear mixing and the estimation of ground cover proportions,INT[J].J.Remote sensing,1993,14:1159-1177.

Gong,Miller,Freemantle,Chen.Spectral Decomposition of Landsat Thematic Mapper Data For Urbal Land-Cover Mapping [C].Proceedings of the 14th Canadian Symposium on Remote Sensing,Calgary,Alberta,Canada, May 1991.

Van Kootwijk E J, Van Der Voet H, Berdow ski J J M.Estimation of ground cover composition per pixel after matching imag e and g round data with subpixel accuracy[J].Int.J.of Remote sens,1995,16(1):97-111.

Shimabukuro Y E,Smith J A.The least squares mixing models to generate fraction images derived from remote sensing multispectral data[J].IEEE Transaction on geoscienceand remote sensing,1991,29(1):16-20.

Views

3723

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Soil wind erosion law in degraded bare patches in alpine meadows of Qinghai Province

Evaluation on Eco-environmental Quality Change of Wujiang River Basin in Guizhou Province from 1990 to 2015

Spatiotemporal evolution of productive-living-ecological space at county level of Qinling-Daba Mountains area under background of urban-rural integration

Influence of different amendments on salt ions and maize growth in coastal saline soil

Effects of vegetation restoration duration on runoff and sediment yield in slopes of waste dumps in alpine mining areas

Related Author

Tong Shengchun

Long Yuxiang

Zhu Haili

Liu Yabin

Li Jinfang

Zhao Jianyun

Li Xilai

Hu Xiasong

Related Institution

Department of Geological Engineering， Qinghai University

Key Laboratory of Cenozoic Resource & Environment in Northern Margin of the;Tibetan Plateau

State Key Laboratory of Three-River Source;Ecology and Plateau Agriculture and Animal Husbandry， Qinghai University

School of Geography and Environmental Science, Guizhou Normal University

⁰