Evaluation and exploitation of retrieval algorithms for estimating biophysical crop variables using Sentinel-2, Venµs and PRISMA satellite data

CASA Raffaele; UPRETI Deepak; PALOMBO Angelo; PASCUCCI Simone; YANG Hao; YANG Guijun; HUANG Wenjiang; PIGNATTI Stefano

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Evaluation and exploitation of retrieval algorithms for estimating biophysical crop variables using Sentinel-2, Venµs and PRISMA satellite data
Vol. 24, Issue S1, Pages: 25-32(2020)
Received：21 October 2019，

Accepted：16 April 2020，

Published：07 June 2020
DOI：
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DOI：

format: Casa R,Upreti D,Palombo A,Pascucci S,Yang H,Yang G J,Huang W J and Pignatti S. 2020. Evaluation and exploitation of retrieval algorithms for estimating biophysical crop variables using Sentinel-2, Venµs and PRISMA satellite data. Journal of Remote Sensing(Chinese). 24(S1): 25-32 DOI：

摘要

Abstract

This paper is devoted to the development and testing of the optimal procedures for retrieving biophysical crop variables by exploiting the spectral information of current multispectral optical satellite Sentinel-2 and Venµs and in view of the advent of the new Sin

o-EU hyperspectral satellite (e.g.

PRISMA

EnMAP

and GF-5). Two different methodologies devoted to the estimation of biophysical crop variables Leaf area index (LAI) and Leaf chlorophyll content (Cab) were evaluated: (a) non-kernel-based and kernel-based Machine Learning Regression Algorithms (MLRA); (b) Sentinel-2 and Venμs data comparison for the analysis of the durum wheat-growing season. Results show that for Sentinel-2 data

GPR (Gaussian Process Regression) was the best performing algorithm for both LAI (

= 0.89 and RMSE = 0.59) and Cab (

= 0.70 and RMSE = 8.31). Whereas

for PRISMA simulated data the Kernel Ridge Regression (KRR) was the best performing algorithm among all the other MLRA (

= 0.91 and RMSE = 0.51) for LAI and (

= 0.83 and RMSE = 6.09) for Cab

respectively. Results of Sentinel-2 and Venμs data for durum wheat-growing season were consistent with ground truth data and confirm also that SWIR bands

which are used as tie-points in the PROSAIL inversion

are extremely useful for an accurate retrieving of crop biophysical parameters.

关键词

Keywords

references

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