Literature DB >> 19242776

Predicting vegetation water content in wheat using normalized difference water indices derived from ground measurements.

Chaoyang Wu1, Zheng Niu, Quan Tang, Wenjiang Huang.   

Abstract

Vegetation water content (VWC) is an important variable for both agriculture and forest fire management. Remote sensing technology offers an instantaneous and non-destructive method for VWC assessment provided we can relate in situ measurements of VWC to spectral reflectance in a reliable way. In this paper, based on radiative transfer models, three new normalized difference water indices (NDWI) are proposed for VWC [fuel moisture content (FMC), and equivalent water thickness (EWT)] estimation, taking both leaf internal structure and dry matter content into account. Reflectance at 1,200, 1,450 and 1,940 nm were selected and normalized with reflectance at 860 nm to establish three water indices, NDWI(1200), NDWI(1450) and NDWI(1940). Good correlations were observed between FMC (R (2) = 0.65-0.80) and EWT (both at the leaf scale, R (2) = 0.75-0.81 for EWT(L) and at the canopy scale, R (2) = 0.80-0.83 for EWT(C)) at various stages of wheat crop development.

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Year:  2009        PMID: 19242776     DOI: 10.1007/s10265-009-0215-y

Source DB:  PubMed          Journal:  J Plant Res        ISSN: 0918-9440            Impact factor:   2.629


  2 in total

1.  Comparison of new hyperspectral index and machine learning models for prediction of winter wheat leaf water content.

Authors:  Juanjuan Zhang; Wen Zhang; Shuping Xiong; Zhaoxiang Song; Wenzhong Tian; Lei Shi; Xinming Ma
Journal:  Plant Methods       Date:  2021-03-31       Impact factor: 4.993

2.  Effects of water stress on spectral reflectance of bermudagrass.

Authors:  Lisa Caturegli; Stefania Matteoli; Monica Gaetani; Nicola Grossi; Simone Magni; Alberto Minelli; Giovanni Corsini; Damiano Remorini; Marco Volterrani
Journal:  Sci Rep       Date:  2020-09-14       Impact factor: 4.379

  2 in total

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