文献类型：期刊文献

中文题名：基于优化三角形植被指数(TVI)的灌丛化草原植被地上生物量遥感估测方法研究

英文题名：An evaluation of a remote sensing method based on optimized triangular vegetation index(TVI)for aboveground shrub biomass estimation in shrub-encroached grassland

作者：许政勇[1] 孙斌[2,3] 张王菲[1] 李毅夫[2,3] 闫紫钰[2,3] 岳巍[2,3] 滕思翰[2,3,4]

第一作者：许政勇

机构：[1]西南林业大学林学院,云南昆明650224;[2]中国林业科学研究院资源信息研究所,北京100091;[3]国家林业和草原局林业遥感与信息技术重点实验室北京100091;[4]内蒙古自治区大数据中心,内蒙古呼和浩特010000

年份：2023

卷号：32

期号：10

起止页码：1-14

中文期刊名：草业学报

外文期刊名：Acta Prataculturae Sinica

收录：CSTPCD;;Scopus;北大核心:【北大核心2020】；CSCD:【CSCD2023_2024】；

基金：国家自然科学基金项目(42001386,42271407,32160365,42161059和31860240)资助。

语种：中文

中文关键词：灌丛化草原;植被地上生物量;植被指数法;优化三角形植被指数

外文关键词：shrub-encroached grassland;aboveground biomass of vegetation;vegetation index method;optimize triangular vegetation index

分类号：Q94

摘要：灌丛化已经成为草原生态系统中重要的生态问题,而灌丛化草原植被地上生物量(AGB)的精细化估测对于开展区域生态系统碳循环研究有着重要的科学意义。受土壤背景噪声和植被生长结构特征差异的双重影响,现有常见植被指数在灌丛化草原区域构建AGB估算模型时表现极不稳定。针对这一问题,基于Sentinel-2遥感数据,通过优化三角形植被指数(TVI)开展灌丛化草原植被AGB遥感估测方法研究。研究结果表明:1)在以草本植被为主的区域中,基于绿R560、红边R705和近红R865组合形成的TVI与AGB拟合效果最好,R2达到了0.684;而在以灌丛植被为主的区域中,以基于绿R560、红边R783和近红R842组合形成的TVI与AGB拟合效果最好,R^(2)达到了0.368。2)分析现有常用的12种植被指数对土壤的噪声敏感性时,在以草本植被为主的区域中,增强型植被指数(EVI)对土壤噪声表现最为敏感;在以灌丛植被为主的区域中,修正土壤调节植被指数(MSAVI)表现最为敏感。3)在草本植被为主的区域中,相对于TVI,优化后植被指数草地三角形植被指数(GTVI)构建线性估算模型的交叉验证决定系数(R2 CV)提高了0.153、交叉验证均方根误差(RMSECV)减小了12.222 g·m^(-2);在灌丛植被为主的区域中,相对于TVI,优化后植被指数GTVI构建线性估算模型的R2 CV提高了0.029、RMSECV减小了1.684 g·m^(-2)。4)与常用的12种植被指数构建的估测模型相比,无论在草本植被区域还是灌丛植被区域,GTVI构建的估测模型都具有最高的精度。该研究结果以期为采用植被指数法开展灌丛化草原植被地上生物量遥感估算提供科学依据和参考。
Shrub-encroachment onto grassland is becoming an important ecological problem in grassland ecosystems,and accurate estimation of the shrub above-ground biomass(AGB)in shrub-encroached grassland vegetation plays a significant role in research into regional ecosystem carbon cycles.Due to the dual effects of soil background noise and differences in vegetation growth structure characteristics,the traditional vegetation indices are extremely unstable for model-building involving shrub-encroached grassland AGB estimation.To solve this problem,in this study we developed a novel way by optimizing the triangular vegetation index(TVI)using Sentinel-2 remote sensing data for shrub-encroached grassland AGB estimation.The results showed that:1)In the area dominated by herbaceous vegetation,TVI calculated using a combination of green,red-edge and near-infrared(R560,R705 and R865)performed best with an R2 of 0.684;in the area dominated by shrub vegetation,the TVI again performed best with R^(2)=0.368.2)When analyzing the sensitivity of the 12 commonly used vegetation indexes to soil noise,the enhanced vegetation index(EVI)was the most sensitive to soil noise in the area dominated by herbaceous vegetation;in the area dominated by shrub vegetation,the modified soil adjusted vegetation index(MSAVI)was the most sensitive.3)In the area dominated by herbaceous vegetation,the optimized vegetation index grassland triangular vegetation index(GTVI)performed better than TVI with the value of R2 CV(coefficient of determination cross validation)increased by 0.153 and the value of RMSECV decreased by 12.222 g·m^(?2);in the area dominated by shrub vegetation,GTVI performed better than TVI and the R2 CV value increased 0.029,while the RMSECV(root mean square error cross validation)decreased 1.684 g·m^(?2).4)The estimation results acquired by GTVI showed the highest accuracy when compared with the results estimated by the commonly used 12 vegetation indices.The results of this study are expected to provide a scientific basis and reference AGB estimation in shrub-encroached grassland using vegetation indices extracted from remote sensing data.