Estimating canopy water content using hyperspectral remote sensing data

被引:181
作者
Clevers, J. G. P. W. [1 ]
Kooistra, L. [1 ]
Schaepman, M. E. [2 ]
机构
[1] Wageningen Univ, Ctr Geoinformat, NL-6700 AA Wageningen, Netherlands
[2] Univ Zurich, Remote Sensing Labs, CH-8057 Zurich, Switzerland
关键词
Remote sensing; Hyperspectral; Canopy water content; Water absorption features; PROSAIL; First derivative; LEAF OPTICAL-PROPERTIES; VEGETATION INDEXES; REFLECTANCE DATA; RETRIEVAL; VARIABLES; MODEL; INFORMATION; PRODUCTS; PROSPECT;
D O I
10.1016/j.jag.2010.01.007
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Hyperspectral remote sensing has demonstrated great potential for accurate retrieval of canopy water content (CWC). This CWC is defined by the product of the leaf equivalent water thickness (EWT) and the leaf area index (LAI). In this paper, in particular the spectral information provided by the canopy water absorption feature at 970 rim for estimating and predicting CWC was studied using a modelling approach and in situ spectroradiometric measurements. The relationship of the first derivative at the right slope of the 970 nm water absorption feature with CWC was investigated with the PROSAIL radiative transfer model and tested for field spectroradiometer measurements on two test sites. The first site was a heterogeneous floodplain with natural vegetation like grasses and various shrubs. The second site was an extensively grazed fen meadow. PROSAIL simulations (using coupled SAIL/PROSPECT-5 models) showed a linear relationship between the first derivative over the 1015-1050 rim spectral interval and CWC (R-2 = 0.97). For 8 plots at the floodplain site the spectral derivative over the 1015-1050 nm interval obtained with an ASD FieldSpec spectroradiometer yielded an R-2 of 0.51 with CWC. For 40 plots at the fen meadow ASD FieldSpec spectral measurements yielded an R-2 of 0.68 for the derivative over the 1015-1050 nm interval with CWC. Consistency of the results confirmed the potential of using simulation results for calibrating the relationship between this first derivative and CWC. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码:119 / 125
页数:7
相关论文
共 30 条
[1]  
[Anonymous], 1983, INTRO SOLAR RAD
[2]   Object-based retrieval of biophysical canopy variables using artificial neural nets and radiative transfer models [J].
Atzberger, C .
REMOTE SENSING OF ENVIRONMENT, 2004, 93 (1-2) :53-67
[3]   Water content estimation from hyperspectral images and MODIS indexes in Southeastern Arizona [J].
Cheng, Yen-Ben ;
Ustin, Susan L. ;
Riano, David ;
Vanderbilt, Vem C. .
REMOTE SENSING OF ENVIRONMENT, 2008, 112 (02) :363-374
[4]   Monitoring drought effects on vegetation water content and fluxes in chaparral with the 970 nm water band index [J].
Claudio, Helen C. ;
Cheng, Yufu ;
Fuentes, David A. ;
Gamon, John A. ;
Luo, Hongyan ;
Oechel, Walter ;
Qiu, Hong-Lie ;
Rahman, Abdullah F. ;
Sims, Daniel A. .
REMOTE SENSING OF ENVIRONMENT, 2006, 103 (03) :304-311
[5]   Using spectral information from the NIR water absorption features for the retrieval of canopy water content [J].
Clevers, J. G. P. W. ;
Kooistra, L. ;
Schalepman, M. E. .
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2008, 10 (03) :388-397
[6]   Estimation of leaf and canopy water content in poplar plantations by means of hyperspectral indices and inverse modeling [J].
Colombo, R. ;
Merom, M. ;
Marchesi, A. ;
Busetto, L. ;
Rossini, M. ;
Giardino, C. ;
Panigada, C. .
REMOTE SENSING OF ENVIRONMENT, 2008, 112 (04) :1820-1834
[7]   Retrieval of canopy biophysical variables from bidirectional reflectance -: Using prior information to solve the ill-posed inverse problem [J].
Combal, B ;
Baret, F ;
Weiss, M ;
Trubuil, A ;
Macé, D ;
Pragnère, A ;
Myneni, R ;
Knyazikhin, Y ;
Wang, L .
REMOTE SENSING OF ENVIRONMENT, 2003, 84 (01) :1-15
[8]   REMOTE-SENSING OF FOLIAR CHEMISTRY [J].
CURRAN, PJ .
REMOTE SENSING OF ENVIRONMENT, 1989, 30 (03) :271-278
[9]   HIGH-SPECTRAL RESOLUTION DATA FOR DETERMINING LEAF WATER-CONTENT [J].
DANSON, FM ;
STEVEN, MD ;
MALTHUS, TJ ;
CLARK, JA .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 1992, 13 (03) :461-470
[10]  
*ESA, 2006, CHANG EARTH