Remote estimation of gross primary production in wheat using chlorophyll-related vegetation indices

• Published in: Agricultural and forest meteorology 2009-06, Vol.149 (6), p.1015-1021
• Main Authors: Wu, Chaoyang, Niu, Zheng, Tang, Quan, Huang, Wenjiang, Rivard, Benoit, Feng, Jilu
• Format: Article
• Language: English
• Subjects: Agricultural and forest climatology and meteorology. Irrigation. Drainage; Agronomy. Soil science and plant productions; Biological and medical sciences; Canopy chlorophyll content; chlorophyll; correlation; estimation; field experimentation; Fundamental and applied biological sciences. Psychology; General agronomy. Plant production; GPP; light; LUE; model validation; photosynthetically active radiation; primary productivity; radiation use efficiency; reflectance; remote sensing; Sensitivity; spectral analysis; spectroscopy; Triticum aestivum; Validation; vegetation indexes; Vegetation indices; wheat
• ISSN: 0168-1923; 1873-2240
• DOI: 10.1016/j.agrformet.2008.12.007

A number of recent studies have focused on estimating gross primary production (GPP) using vegetation indices (VIs). In this paper, GPP is retrieved as a product of incident light use efficiency (LUE), defined as GPP/PAR, and the photosynthetically active radiation (PAR). As a good correlation is found between canopy chlorophyll content and incident LUE for six types of wheat canopy ( R 2 = 0.87, n = 24), indices aimed for chlorophyll assessment can be used as an indicator of incident LUE and the product of chlorophyll indices and PAR will be a proxy of GPP. In a field experiment, we investigated four canopy chlorophyll content related indices (Red edge Normalized Difference Vegetation Index [Red Edge NDVI], modified Chlorophyll Absorption Ratio Index [MCARI 710], Red Edge Chlorophyll Index [CI red edge] and the MERIS Terrestrial Chlorophyll Index [MTCI]) for GPP estimation during the growth cycle of wheat. These indices are validated for leaf and canopy chlorophyll estimation with ground truth data of canopy chlorophyll content. With ground truth data, a strong correlation is observed for canopy chlorophyll estimation with correlation coefficients R 2 of 0.79, 0.84, 0.85 and 0.87 for Red Edge NDVI, MCARI 710, CI red edge and MTCI, respectively ( n = 24). As evidence of the existence of a relationship between canopy chlorophyll and GPP/PAR, these indices are shown to be a good proxy of GPP/PAR with R 2 ranging from 0.70 for Red Edge NDVI and 0.75 for MTCI ( n = 240). Remote estimation of GPP from canopy chlorophyll content × PAR is proved to be relatively successful ( R 2 of 0.47, 0.53, 0.65 and 0.66 for Red edge NDVI, MCARI 710, CI red edge and MTCI respectively, n = 240). These results open up a new possibility to estimate GPP and should inspire new models for remote sensing of GPP.