文献类型：期刊文献

中文题名：北京一号,环境星,Landsat TM传感器估算草地覆盖度、叶面积指数、地上生物量比较研究

英文题名：Accuracy Comparison of BJ-1,HJ and Landsat Data in the Retrieval of Grassland Vegetation Coverage,Leaf Area Index and above Ground Biomass

作者：王红岩[1] 李晓松[2] 张瑾[2] 高志海[1]

第一作者：王红岩

通信作者：Gao, ZH[1]

机构：[1]中国林业科学研究院资源信息研究所;[2]数字地球重点实验室,中国科学院遥感与数字地球研究所

年份：2013

卷号：33

期号：10

起止页码：2803-2808

中文期刊名：光谱学与光谱分析

外文期刊名：Spectroscopy and Spectral Analysis

收录：CSTPCD;;EI(收录号：20134316893818);Scopus(收录号：2-s2.0-84885920598);WOS:【SCI-EXPANDED(收录号:WOS:000326199300044)】；北大核心:【北大核心2011】；CSCD:【CSCD2013_2014】；PubMed;

基金：国家科技支撑计划课题项目(2011BAH23B04);国家重大专项(E0305/1112)资助

语种：中文

中文关键词：京津风沙源;BJ-1;HJ;植被覆盖度;叶面积指数;地上生物量

外文关键词：Sandstorm source region in Beijing and Tianjin; BJ-1; HJ; Fractional coverage; Leaf area index; Aboveground bio-mass

分类号：P237

摘要：以京津风沙源区的草地为研究对象,选取中国自主BJ-1、HJ数据及国外应用最为广泛的Landsat TM为数据源,结合地面同步实测草地植被覆盖度、叶面积指数和地上生物量数据,系统比较三个传感器在草地生理参数估算方面的差异与能力。研究结果表明:(1)HJ-1B与Landsat TM的红光波段与草地生理参量有更高相关性,而BJ-1相对较弱,但BJ-1近红外波段在草地生理参量遥感估算上明显优于HJ-1B与Landsat TM;(2)Landsat TM的植被指数在估测草地生理参量时好于HJ-1B与BJ-1数据,HJ-1B植被指数的表现优于BJ-1;(3)相对于植被指数,全波段多元回归模型可以提升草地生理参量估测精度,基于Landsat TM与HJ-1B的提升效果微弱,而基于BJ-1数据的估算精度有明显提高,其中基于BJ-1估算叶面积指数达到了最高精度(R2=0.61,RMSEP=0.15)。总体来说,自主国产遥感数据有其自己特色,可供深入研究及推广应用的潜力很大。
Domestic satellites BJ-1, HJ and the most widely used satellite Landsat TM were selected to systematically compare their abilities and differences on the estimation of the biophysical parameters of grassland in sandstorm source region in Beijing and Tianjin, with the combination of field-measured fractional coverage, leaf area index and aboveground biomass data. The re- sult shows： （1） In terms of the surface reflectance, HJ-1B and Landsat TM have a higher correlation with biophysical parame- ters in red band, compared with BJ-1, while BJ-1 ＇s near infra-red band was obviously superior to HJ-1B and Landsat TM, （2） with respect to the vegetation indices, Landsat TM performed best, HJ-1B was the second, and BJ-1 was the worst, （3） com- pared with vegetation indices, multiple regression model can raise the estimation accuracy, BJ-1 based model improved signifi- cantly, while Landsat TM and HJ-1B based models were less obvious. Among them, the highest accuracy was acquired for leaf area index estimation through the BJ-1 based model （R2 =0. 61, RMSEP=0. 15）. In general, domestic satellites have their own unique features, which remain a huge potential to be further tapped.