Estimation of chlorophyll content of Phragmites australis based on PROSPECT and DART models in the saltmarsh of Yangtze Estuary

Yuyan Zeng; Runhe Shi; Pudong Liu; Chao Zhang; Jiapeng Wang; Chaoshun Liu; Maosi Chen

doi:10.1117/12.2239922

19 September 2016 Estimation of chlorophyll content of Phragmites australis based on PROSPECT and DART models in the saltmarsh of Yangtze Estuary

Yuyan Zeng, Runhe Shi, Pudong Liu, Chao Zhang, Jiapeng Wang, Chaoshun Liu, Maosi Chen

Author Affiliations +

Proceedings Volume 9975, Remote Sensing and Modeling of Ecosystems for Sustainability XIII; 99750X (2016) https://doi.org/10.1117/12.2239922
Event: SPIE Optical Engineering + Applications, 2016, San Diego, California, United States

Abstract

Phragmites australis is a native dominant specie in the Yangtze Estuary, which plays a key role in the structure and function of wetland ecosystem. One key question is how to estimate the Chlorophyll content quickly and effectively at large scales, which could be used to reflect the growth condition and calculate the vegetation productivity. The aim of this work was to estimate Chlorophyll content of P. australis based on the PROSPECT and DART (Discrete Anisotropic Radiative Transfer) model. A total of 6 widely used Vegetation indices (VIs) were chosen (i.e., Normalized Difference Vegetation Index (NDVI), Structure Insensitive Pigment Index (SIPI), Colouration Index (COI), Simple Ratio Index (SR), Cater Index (CAI), and Red-edge Position Linear Interpolation (REP_Li)) and calculated, and then the relationship between VIs and Cab were analyzed. Results showed that COI and SIPI were sensitive to the leaf chlorophyll content as the chlorophyll content changes at the leaf scale. Meanwhile, no obvious saturation phenomenon was observed for these two indices compared to other indices.

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Yuyan Zeng, Runhe Shi, Pudong Liu, Chao Zhang, Jiapeng Wang, Chaoshun Liu, and Maosi Chen "Estimation of chlorophyll content of Phragmites australis based on PROSPECT and DART models in the saltmarsh of Yangtze Estuary", Proc. SPIE 9975, Remote Sensing and Modeling of Ecosystems for Sustainability XIII, 99750X (19 September 2016); https://doi.org/10.1117/12.2239922

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