IMHE OpenIR  > 山地灾害与地表过程重点实验室
综合137Cs,RS和GIS的土壤侵蚀评估和预测——以云南小江流域为例
Alternative TitleSoil erosion evaluation and prediction approach using 137 Cs,RS, and GIS in Xiaojiang River basin of China
葛永刚; 崔鹏; 林勇明; 庄建琦; 贾松伟
Corresponding Author葛永刚
2014-07
Source Publication遥感学报
Volume18Issue:4Pages:887-901
Other Abstract

综合应用137Cs技术、RS技术和GIS技术,进行云南小江流域土壤侵蚀的评估和预测研究,探索中国西部山区观测资料缺乏、USLE(Universal Soil Loss Equation)方程不适宜区域土壤侵蚀评估与预测方法。通过137Cs技术,采用非农耕地与农耕地土壤侵蚀模型确定区内林地、灌丛、草地、坡耕地和裸地的年均侵蚀模数分别为356-1531 t/(km·a),330-1709 t/(km·a),886-3885 t/(km·a),5197-12454 t/(km·a)和15000 t/(km·a)以上。解译小江流域1987年(Landsat TM)、1995年(Landsat TM)和2005年(Landsat ETM)遥感影像,获得流域不同时期土地利用图,将其与1∶50000 DEM模型进行叠置分析,建立小江流域土地利用的空间分布图,结合利用137Cs确定的土壤侵蚀速率数据,进行土壤侵蚀分区与制图,分析土壤侵蚀的时空变化。结果表明:1987年-2005年流域轻度以上侵蚀面积占总面积的66.0%-67.3%,变化不大,但侵蚀强度明显加剧,1987年-1995年间尤为明显;中度侵蚀、强度侵蚀、极强度侵蚀区面积分别增加30%、23%和26%;小江流域1987年、1995年和2005年土壤侵蚀量分别为7.51×106 t/a,8.19×106 t/a和8.18×106 t/a。进而选用1995年和2005年的土壤侵蚀数据构建Markov-CA(马尔可夫-元胞自动机)预测模型,获得2015年流域土壤侵蚀分区图,并预测2015年土壤侵蚀量为8.17×106 t,与2005年侵蚀量接近。研究结果真实地反映了小江流域土壤侵蚀的变化过程与主要驱动因子,研究方法适合中国西部山区土壤侵蚀评估与预测。

;
It is difficult to evaluate and predict soil erosion and its related effects in mountainous areas without sufficient observation
data. This study aimed to estimate and predict changes in soil erosion using 137Cs,RS,and GIS techniques and propose an a
pproach for soil erosion evaluation in mountainous areas. Using the erosion modulus calculating models based on 137Cs concentration,
the annual average soil erosion modulus of forest lands,shrub lands,grasslands,farmlands,and uncovered land were obtained.
The values were 356—1531 t /( km2·a) ,330—1709 t /( km2·a) ,886—3885 t /( km2·a) ,5197—12454 t /( km2·a) ,
and more than 1 5000 t /( km2·a) ,respectively. Then,erosion zoning was done by combining erosion rates and land use data by
interpreting remote sense images from 1987 ( Landsat TM) ,1995 ( Landsat TM) ,and 2005 ( Landsat ETM) ,and these were overlaid
with 1∶ 50000 DEM data. The results showed that the eroded land changed very little from 1987 to 2005,accounting for about
66%—67. 3% of the total; however,the erosion intensity significantly rose from 1987 to 1995,up to 30% for some land use
types. The eroded land, with the erosion modulus of 2500—5000 t /( km2·a) , 5000—8000 t /( km2·a) , and 8000—
15000 t /( km2·a) rise 30%,23%,and 26%,respectively. The soil erosion amount in the Xiaojiang River basin was 7. 51 × 106
t / a,8. 19 × 106 t /a,and 8. 18 × 106 t /a in 1987,1995,and 2005,r espectively. Moreover,the zoning and amount of soil erosion
for 2015 was predicted using a Markov-Cellar A utomata Model,which was established using the data from 1995 and 2005. The
predicted result,8. 17 × 106 t /a,was very similar to that from 2005. This study provides a valuable solution to evaluate and predict
soil erosion for mountainous areas in southwest China.
Keyword土壤侵蚀 评估 预测 137cs Rs Gis 小江流域
Subject Area自然地理学 ; 水土保持学
DOIDOI:10.11834/jrs.20143128
URL查看原文
Indexed ByCSCD
Language英语
Funding Organization国家科技支撑计划( 编号: 2012BAC06B02) ; 中国科学院山地灾害与地表过程重点实验室重点项目
Citation statistics
Document Type期刊论文
Identifierhttp://ir.imde.ac.cn/handle/131551/7505
Collection山地灾害与地表过程重点实验室
Recommended Citation
GB/T 7714
葛永刚,崔鹏,林勇明,等. 综合137Cs,RS和GIS的土壤侵蚀评估和预测——以云南小江流域为例[J]. 遥感学报,2014,18(4):887-901.
APA 葛永刚,崔鹏,林勇明,庄建琦,&贾松伟.(2014).综合137Cs,RS和GIS的土壤侵蚀评估和预测——以云南小江流域为例.遥感学报,18(4),887-901.
MLA 葛永刚,et al."综合137Cs,RS和GIS的土壤侵蚀评估和预测——以云南小江流域为例".遥感学报 18.4(2014):887-901.
Files in This Item:
File Name/Size DocType Version Access License
综合_137_Cs_RS和GIS_省略_(2663KB) 开放获取CC BY-NC-SAView Application Full Text
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[葛永刚]'s Articles
[崔鹏]'s Articles
[林勇明]'s Articles
Baidu academic
Similar articles in Baidu academic
[葛永刚]'s Articles
[崔鹏]'s Articles
[林勇明]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[葛永刚]'s Articles
[崔鹏]'s Articles
[林勇明]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: 综合_137_Cs_RS和GIS_省略_蚀评估和预测_以云南小江流域为例_葛永刚.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.