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自然资源学报 >

2010 , Vol. 25 >Issue 7: 1122 - 1131

DOI: https://doi.org/10.11849/zrzyxb.2010.07.008

资源生态

基于环境减灾卫星遥感数据的呼伦贝尔草地地上生物量反演研究

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  • 1. 中国科学院 地理科学与资源研究所, 资源与环境信息系统国家重点实验室, 北京 100101;
    2. 中国农业科学院 农业资源与农业区划研究所, 北京 100081
陈鹏飞(1982- ),男,河南许昌人,助理研究员,主要从事农业信息化、农业温室气体排放量估算与减排策略研究。E-mail:pengfeichen-001@hotmail.com

收稿日期: 2009-09-24

  修回日期: 2010-05-19

  网络出版日期: 2010-07-10

基金资助

国家自然科学基金项目(40771146,40801180);科技基础性工作专项中国北方及其毗邻地区综合考察项目(2007FY110300);资源与环境信息系统国家重点实验室自主研究课题(088RA102SA)。

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Using Data of HJ-1A/B Satellite for Hulunbeier Grassland Aboveground Biomass Estimation

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  • 1. Institute of Geographic Sciences and Natural Resources Research, CAS, State Key Lab of Resources and Environment Information System, Beijing 100101, China;
    2. Institute of Natural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China

Received date: 2009-09-24

  Revised date: 2010-05-19

  Online published: 2010-07-10

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摘要

推动国产遥感卫星在资源环境领域中的应用对于促进我国航天事业发展、减少科研成本具有重要意义。我国近期发射的环境减灾卫星具有时间分辨率高、可获得高光谱影像的特点,在陆地资源遥感监测领域将有广阔发展空间。研究于2009年夏季获得三景呼伦贝尔草原区遥感影像和对应地面实测草地生物量信息,基于这些数据探讨了利用环境减灾卫星多光谱影像和植被指数反演草地生物量的可行性。结果表明基于影像提取的NDVI、OSAVI、MSAVI、SAVI、EVI、MTVI2、WDRVI和GNDVI等光谱指数均与草地生物量有较好的定量关系。其中,MTVI2结果最好,预测决定系数达0.61,交叉检验决定系数为0.58,均方根误差仅为58.6 g·m-2,基于MTVI2和环境减灾卫星多光谱影像可准确生成草地生物量空间分布图。

关键词： 环境减灾卫星; 生物量; 草地; 呼伦贝尔

本文引用格式

陈鹏飞, 王卷乐, 廖秀英, 尹 芳, 陈宝瑞, 刘 睿 . 基于环境减灾卫星遥感数据的呼伦贝尔草地地上生物量反演研究[J]. 自然资源学报, 2010 , 25(7) : 1122 -1131 . DOI: 10.11849/zrzyxb.2010.07.008

Abstract

Promoting the application of domestic remote sensing satellite in natural resources and environment monitoring is very important to accelerate the development of national space research and reduce scientific activities cost. The recent launched satellite HJ-1A/B has the characteristic of high time resolution and can acquire hyperspectral image. These make it has the prosperous future in terrestrial resources detection. In the summer of 2009, the study obtained three images and corresponding grass dry biomass in Hulunbeier area. They were used to study the feasibility of using HJ-1A/B multispectral image and spectral indices for grassland biomass prediction. The result showed image based on calculation of spectral indices, including NDVI, OSAVI, MSAVI, SAVI, EVI, MTVI2, WDRVI, GNDVI, have good relationship with grass biomass. MTVI2 gained the best result with R2 value of 0.61, meanwhile the cross validation result of it was also permissible with R2 value of 0.58 and RMSE value of 58.6 g·m-2. The map of grass biomass in the research area can be produced using MTVI2 and HJ multispectral imagery.

Key words： HJ-1A/B satellite; biomass; grassland

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