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Multi-Crop Green LAI Estimation with a New Simple Sentinel-2 LAI Index (SeLI)

1
Image Processing Laboratory (IPL), University of Valencia, 46980 Valencia, Spain
2
Council for Agricultural Research and Economics—Research Centre for Cereal and Industrial Crops, S.S. 673 km 25, 200, 71122 Foggia, Italy
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(4), 904; https://doi.org/10.3390/s19040904
Received: 14 January 2019 / Revised: 5 February 2019 / Accepted: 18 February 2019 / Published: 21 February 2019
(This article belongs to the Special Issue Optical Bio Sensing)
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Abstract

The spatial quantification of green leaf area index (LAIgreen), the total green photosynthetically active leaf area per ground area, is a crucial biophysical variable for agroecosystem monitoring. The Sentinel-2 mission is with (1) a temporal resolution lower than a week, (2) a spatial resolution of up to 10 m, and (3) narrow bands in the red and red-edge region, a highly promising mission for agricultural monitoring. The aim of this work is to define an easy implementable LAIgreen index for the Sentinel-2 mission. Two large and independent multi-crop datasets of in situ collected LAIgreen measurements were used. Commonly used LAIgreen indices applied on the Sentinel-2 10 m × 10 m pixel resulted in a validation R2 lower than 0.6. By calculating all Sentinel-2 band combinations to identify high correlation and physical basis with LAIgreen, the new Sentinel-2 LAIgreen Index (SeLI) was defined. SeLI is a normalized index that uses the 705 nm and 865 nm centered bands, exploiting the red-edge region for low-saturating absorption sensitivity to photosynthetic vegetation. A R2 of 0.708 (root mean squared error (RMSE) = 0.67) and a R2 of 0.732 (RMSE = 0.69) were obtained with a linear fitting for the calibration and validation datasets, respectively, outperforming established indices. Sentinel-2 LAIgreen maps are presented. View Full-Text
Keywords: crops; leaf area index; vegetation indices; remote sensing; Sentinel-2; red-edge crops; leaf area index; vegetation indices; remote sensing; Sentinel-2; red-edge
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Pasqualotto, N.; Delegido, J.; Van Wittenberghe, S.; Rinaldi, M.; Moreno, J. Multi-Crop Green LAI Estimation with a New Simple Sentinel-2 LAI Index (SeLI). Sensors 2019, 19, 904.

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