Estimating the Maximal Light Use Efficiency for Different Vegetation through the CASA Model Combined with Time-Series Remote Sensing Data and Ground Measurements

CORC > 成都山地灾害与环境研究所 > 中国科学院水利部成都山地灾害与环境研究所 > 数字山地与遥感应用中心

	Estimating the Maximal Light Use Efficiency for Different Vegetation through the CASA Model Combined with Time-Series Remote Sensing Data and Ground Measurements
	Li, Ainong1,2 ; Bian, Jinhu1 ; Lei, Guangbin1 ; Huang, Chengquan2
刊名	REMOTE SENSING
	2012-12-01
卷号	4 期号:12 页码:3857-3876
关键词	remote sensing light use efficiency CASA model Zoige Plateau
ISSN号	2072-4292
通讯作者	Li Ainong(李爱农)
合作状况	国际
英文摘要	Maximal light use efficiency (LUE) is an important ecological index of a vegetation essential attribute, and a key parameter of the LUE-based model for estimating large-scale vegetation productivity by remote sensing technology. However, although currently used in different models there still exists extensive controversy. This paper takes the Zoige Plateau in China as a case area to develop a new approach for estimating the maximal LUEs for different vegetation. Based on an existing land cover map and MODIS NDVI product, the linear unmixing method with a moving window was adopted to estimate the time-series NDVI for different end members in a MODIS NDVI pixel; then Particle Swarm Optimizer (PSO) was applied to search for the optimization of LUE retrievals through the CASA (Carnegie-Ames-Stanford Approach) model combined with time-series NDVI and ground measurements. The derived maximal LUEs present significant differences among various vegetation types. These are 0.669 gC.MJ(-1), 0.450 gC.MJ(-1) and 0.126 gC.MJ(-1) for the xerophilous grasslands with high, moderate and low vegetation fraction respectively, 0.192 gC.MJ(-1) for the hygrophilous grasslands, and 0.125 gC.MJ(-1) for the helobious grasslands. The field validation shows that the estimated net primary productivity (NPP) by the derived maximal LUE is closely related to the ground references, with R-2 of 0.8698 and root-mean-square error (RMSE) of 59.37 gC.m(-2).a(-1). This indicates that the default set in the CASA model is not suitable for NPP estimation for the regional mountain area. The derived maximal LUEs can significantly improve the capability of NPP mapping, and open up the perspective for long-term monitoring of vegetation ecological health and ecosystem productivity by combining the LUE-based model with remote sensing observations.
学科主题	摄影测量与遥感技术
WOS标题词	Science & Technology ; Technology
类目[WOS]	Remote Sensing
研究领域[WOS]	Remote Sensing
关键词[WOS]	NET PRIMARY PRODUCTIVITY ; RESOLUTION SATELLITE DATA ; GROSS PRIMARY PRODUCTION ; INNER-MONGOLIA ; FOREST ; NDVI ; CLASSIFICATION ; GRASSLAND ; EXCHANGE ; FRACTION
收录类别	SCI
语种	英语
WOS记录号	WOS:000313914800011
公开日期	2012-12-13
内容类型	期刊论文
源URL	[http://192.168.143.20:8080/handle/131551/4477]
专题	成都山地灾害与环境研究所_数字山地与遥感应用中心
作者单位	1.Chinese Acad Sci, Inst Mt Hazards & Environm, Chengdu 610041, Peoples R China 2.Univ Maryland, Dept Geog, College Pk, MD 20742 USA
推荐引用方式 GB/T 7714	Li, Ainong,Bian, Jinhu,Lei, Guangbin,et al. Estimating the Maximal Light Use Efficiency for Different Vegetation through the CASA Model Combined with Time-Series Remote Sensing Data and Ground Measurements[J]. REMOTE SENSING,2012,4(12):3857-3876.
APA	Li, Ainong,Bian, Jinhu,Lei, Guangbin,&Huang, Chengquan.(2012).Estimating the Maximal Light Use Efficiency for Different Vegetation through the CASA Model Combined with Time-Series Remote Sensing Data and Ground Measurements.REMOTE SENSING,4(12),3857-3876.
MLA	Li, Ainong,et al."Estimating the Maximal Light Use Efficiency for Different Vegetation through the CASA Model Combined with Time-Series Remote Sensing Data and Ground Measurements".REMOTE SENSING 4.12(2012):3857-3876.