Evaluation of Sentinel-2 Red-Edge Bands for Empirical Estimation of Green LAI and Chlorophyll Content

By Jesús Delegido, Jochem Verrelst, Luis Alonso, José F. Moreno. Italian National Conference on Sensors, 2011

606 citations recorded by the source corpus.

ESA’s upcoming satellite Sentinel-2 will provide Earth images of high spatial, spectral and temporal resolution and aims to ensure continuity for Landsat and SPOT observations. In comparison to the latter sensors, Sentinel-2 incorporates three new spectral bands in the red-edge region, which are centered at 705, 740 and 783 nm. This study addresses the importance of these new bands for the retrieval and monitoring of two important biophysical parameters: green leaf area index (LAI) and chlorophyll content (Ch). With data from several ESA field campaigns over agricultural sites (SPARC, AgriSAR, CEFLES2) we have evaluated the efficacy of two empirical methods that specifically make use of the new Sentinel-2 bands. First, it was shown that LAI can be derived from a generic normalized difference index (NDI) using hyperspectral data, with 674 nm with 712 nm as best performing bands. These bands are positioned closely to the Sentinel-2 B4 (665 nm) and the new red-edge B5 (705 nm) band. The method has been applied to simulated Sentinel-2 data. The resulting green LAI map was validated against field data of various crop types, thereby spanning a LAI between 0 and 6, and yielded a RMSE of 0.6. Second, the recently developed “Normalized Area Over reflectance Curve” (NAOC), an index that derives Ch from hyperspectral data, was studied on its compatibility with simulated Sentinel-2 data. This index integrates the reflectance curve between 643 and 795 nm, thereby including the new Sentinel-2 bands in the red-edge region. We found that these new bands significantly improve the accuracy of Ch estimation. Both methods emphasize the importance of red-edge bands for operational estimation of biophysical parameters from Sentinel-2.

Subfields: Atmospheric Science, Ecology, Plant Science

View Paper: https://www.semanticscholar.org/paper/3a9b7afa31ebf64e5a3b992f9bc4f5ad6d8b2831

How researchers see this paper

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In Atmospheric Science

1. Matamyo Simwanda
2. Pierre Defourny
3. Darius Phiri
4. Manjula Ranagalage
5. Y. Murayama
6. Vincent Nyirenda
7. Serajis Salekin

In Ecology

1. Maria Luisa Buchaillot
2. Matamyo Simwanda
3. Jose Luis Araus
4. Pierre Defourny
5. Darius Phiri
6. Manjula Ranagalage
7. Joel Segarra
8. Y. Murayama

In Plant Science

1. C. Delloye
2. Jose Luis Araus
3. Pierre Defourny
4. Marie Weiss
5. G. Slafer
6. Matthew P Reynolds
7. Conxita Royo

Citations in the corpus

• Remote Sensing for Precision Agriculture: Sentinel-2 Improved Features and Applications (2020, background): “This strategy generally includes the three Sentinel-2 RE bands (705, 740, and 783 nm, Figure 2), which are very important for the retrieval of chlorophyll content [82].”
• Sentinel-2 Data for Land Cover/Use Mapping: A Review (2020, background): “The presence of the three red-edge bands has shown high applicability to land cover/use mapping, especially in vegetation land covers/uses [62,120,121].”
• Retrieval of the canopy chlorophyll content from Sentinel-2 spectral bands to estimate nitrogen uptake in intensive winter wheat cropping systems (2018, background): “…Penuelas, 1994; Daughtry et al., 2000; Perry and Roberts, 2008), simulation studies highlighted the potential of S2 red-edge bands for retrieving the Leaf Area Index (LAI) and Cab (Delegido et al., 2011; Schlemmer et al., 2013; Clevers and Gitelson, 2013; Frampton et al., 2013; Peng et al., 2017).”