Model simulation for sensitivity of hyperspectral indices to LAI, leaf chlorophyll, and internal structure parameter

Jinguo Yuan; Zheng Niu; Wenxue Fu

doi:10.1117/12.760656

8 August 2007 Model simulation for sensitivity of hyperspectral indices to LAI, leaf chlorophyll, and internal structure parameter

Jinguo Yuan, Zheng Niu, Wenxue Fu

Author Affiliations +

Proceedings Volume 6752, Geoinformatics 2007: Remotely Sensed Data and Information; 675213 (2007) https://doi.org/10.1117/12.760656
Event: Geoinformatics 2007, 2007, Nanjing, China

Abstract

The sensitivity of hyperspectral indices to LAI, chlorophyll contents and leaf internal structure at canopy level are investigated using simulated canopy reflectance dataset, this method can avoid expensive and impractical surface reflectance measurement, providing a theoretical basis for satellite-borne remote sensing. The model employed is PROSAIL that couples leaf reflectance model PROSPECT and canopy radiative transfer model SAIL. Hyperspectral indices used are NDVI, EVI, GI, RI, TVI, SIPI, PRI, TCARI, OSAVI, TCARI/ OSAVI, mNDVI705 and NDWI. Using PROSAIL model, leaf and canopy reflectance under different chlorophyll contents, leaf internal structures, LAI and water contents are first simulated and compared. Then using PROSAIL simulated canopy reflectance data, different hyperspectral indices are calculated, the sensitivity of vegetation indices to LAI and chlorophyll contents is analyzed in detail. And the sensitivity of vegetation indices to leaf internal structure is also analyzed. Results show that relationships between hyperspectral indices and LAI are approximately logarithmic while the relationship between hyperspectral indices and leaf internal structure is linear. EVI and TVI are good indicators to estimate LAI. GI, RI, TCARI, MNDVI₇₀₅ can be used to estimate chlorophyll content. N has great influence on hyperspectral indices.

Citation Download Citation

Jinguo Yuan, Zheng Niu, and Wenxue Fu "Model simulation for sensitivity of hyperspectral indices to LAI, leaf chlorophyll, and internal structure parameter", Proc. SPIE 6752, Geoinformatics 2007: Remotely Sensed Data and Information, 675213 (8 August 2007); https://doi.org/10.1117/12.760656

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