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标题

基于遥感抽样的农作物灾害损失评估方法(Ⅱ) ———实证实验研究

作者

蔡 毅 朱秀芳 李慕义 李宜展

机构

北京师范大学地表过程与资源生态国家重点实验室;北京师范大学资源学院

摘要

为实现农业保险中快速精确获取农作物受灾面积与受灾等级的目标,作者设计了一套基于分层系统抽样的 农作物受灾评估方法.本文基于该方法,以GF-1影像为实验数据,对2014年河南襄城2个村进行了旱灾灾情评估.实证 研究表明:研究区受灾面积总量反推精度为90.00%左右,各等级受灾面积精度均在80.00%以上,基于遥感抽样的方法 能获取高精度的受灾总面积和各等级受灾面积,且该方法成本低、效率高,具有广泛应用前景.此外,相对于通常以遥感 反演参数直接人为进行等级划分的受灾等级评估方法,这种以真实减产比率为基础的方法可以为不同灾种、不同地区间 的灾情程度的比较提供依据.

关键词

作物灾害损失评估;分层系统抽样;受灾等级;受灾面积

引用

蔡 毅, 朱秀芳, 李慕义, 李宜展.基于遥感抽样的农作物灾害损失评估方法(Ⅱ)———实证实验研究[J]. 北京师范大学学报(自然科学版),2015,51(Sup.1):114-118.

基金

国家自然科学基金青年科学基金资助项目(41401479);国家高分辨率对地观测重大专项基金资助项目(民用部分)

分类号

TP79

DOI

10.16360/j.cnki.jbnuns.2015.s1.018

Title

Crop loss assessment based on remote sensing technology and sampling design: a Case Study

Author

CAI Yi, ZHU Xiufang, LI Muyi, LI Yizhan

Affiliations

State Key Laboratory of Earth Processes and Resource Ecology,Beijing Normal University;College of Resources Science & Technology, Beijing Normal University

Abstract

To assess extent and area of crop loss accurately and quickly in agricultural insurance claims, a method is designed with stratified systematic sampling combined with remote sensing technology. The feasibility of the method was proved by a previous simulation study. In this work, the practicability and performance of this method was further tested with a case study of Gf-1 remote sensing data. The study area was located in Dazhao and Beisun of Xuchang county, Henan province. It was found that the estimation precision of the total affected areas is about 90% and estimation precision of affected areas at different disaster degree was above 80%. This further demonstrated the practicability of our method. The method was cost-efficient because it estimated disaster degree and affected areas simultaneously. Compared with the general assessment method by artificial separation, the present method makes possible comparison of yield losses in different areas and different types of disasters.

Key words

crop loss assessment; stratified systematic sampling; agricultural disaster degree; area affected by disaster

cite

CAI Yi, ZHU Xiufang, LI Muyi, LI Yizhan. Crop loss assessment based on remote sensing technology and sampling design: a Case Study[J].Journal of Beijing Normal University(Natural Science),2015,51(Sup.1):114-118.

DOI

10.16360/j.cnki.jbnuns.2015.s1.018

Copyright © 2014 Journal of Beijing Normal University (Natural Science)
Designed by Mr. Sun Chumin. Email: cmsun@mail.bnu.edu.cn