Abstract
Leaf area index (LAI) and chlorophyll content, at leaf and canopy level, are important variables for agricultural applications because of their crucial role in photosynthesis and in plant functioning. The goal of this study was to test the hypothesis that LAI, leaf chlorophyll content (LCC), and canopy chlorophyll content (CCC) of a potato crop can be estimated by vegetation indices for the first time using Sentinel-2 satellite images. In 2016 ten plots of 30 × 30 m were designed in a potato field with different fertilization levels. During the growing season approximately 10 daily radiometric field measurements were used to determine LAI, LCC, and CCC. These radiometric determinations were extensively calibrated against LAI2000 and chlorophyll meter (SPAD, soil plant analysis development) measurements for potato crops grown in the years 2010–2014. Results for Sentinel-2 showed that the weighted difference vegetation index (WDVI) using bands at 10 m spatial resolution can be used for estimating the LAI (R2 of 0.809; root mean square error of prediction (RMSEP) of 0.36). The ratio of the transformed chlorophyll in reflectance index and the optimized soil-adjusted vegetation index (TCARI/OSAVI) showed to be a good linear estimator of LCC at 20 m (R2 of 0.696; RMSEP of 0.062 g·m−2). The performance of the chlorophyll vegetation index (CVI) at 10 m spatial resolution was slightly worse (R2 of 0.656; RMSEP of 0.066 g·m−2) compared to TCARI/OSAVI. Finally, results showed that the green chlorophyll index (CIgreen) was an accurate and linear estimator of CCC at 10 m (R2 of 0.818; RMSEP of 0.29 g·m−2). Results for CIgreen were better than for the red-edge chlorophyll index (CIred-edge, R2 of 0.576, RMSE of 0.43 g·m−2). Our results show that Sentinel-2 bands at 10 m spatial resolution are suitable for estimating LAI, LCC, and CCC, avoiding the need for red-edge bands that are only available at 20 m. This is an important finding for applying Sentinel-2 data in precision agriculture.
Highlights
Foliar biochemistry is a key proxy of plant productivity and plays a crucial role in photosynthesis and in plant functioning [1]
Our results show that Sentinel-2 bands at 10 m spatial resolution are suitable for estimating Leaf area index (LAI), leaf chlorophyll content (LCC), and canopy chlorophyll content (CCC), avoiding the need for red-edge bands that are only available at 20 m
This paper presents a proof of concept of using Sentinel-2 satellite data in estimating the LAI, LCC, and CCC in order to support potato crop status assessment for precision agriculture applications
Summary
Foliar biochemistry (in particular chlorophyll content) is a key proxy of plant productivity and plays a crucial role in photosynthesis and in plant functioning [1]. Remote sensing data can provide location-specific information of chlorophyll content as a proxy of the crop nitrogen (N) status in order to help farmers with an optimal in-season timing of N application (side dress) [2,3]. It can provide the spatial information needed for the implementation of variable rate application (VRA) in order to optimize production across an entire field. Freely-available data from Sentinel-2 seems to fulfil these requirements
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