Retrieval of Biophysical Crop Variables from Multi-Angular Canopy Spectroscopy

Martin Danner,Wolfram Mauser,Tobias Hank,Matthias Wocher,Katja Berger

doi:10.3390/rs9070726

Abstract

The future German Environmental Mapping and Analysis Program (EnMAP) mission, due to launch in late 2019, will deliver high resolution hyperspectral data from space and will thus contribute to a better monitoring of the dynamic surface of the earth. Exploiting the satellite’s ±30° across-track pointing capabilities will allow for the collection of hyperspectral time-series of homogeneous quality. Various studies have shown the possibility to retrieve geo-biophysical plant variables, like leaf area index (LAI) or leaf chlorophyll content (LCC), from narrowband observations with fixed viewing geometry by inversion of radiative transfer models (RTM). In this study we assess the capability of the well-known PROSPECT 5B + 4SAIL (Scattering by Arbitrarily Inclined Leaves) RTM to estimate these variables from off-nadir observations obtained during a field campaign with respect to EnMAP-like sun–target–sensor-geometries. A novel approach for multiple inquiries of a large look-up-table (LUT) in hierarchical steps is introduced that accounts for the varying instances of all variables of interest. Results show that anisotropic effects are strongest for early growth stages of the winter wheat canopy which influences also the retrieval of the variables. RTM inversions from off-nadir spectra lead to a decreased accuracy for the retrieval of LAI with a relative root mean squared error (rRMSE) of 18% at nadir vs. 25% (backscatter) and 24% (forward scatter) at off-nadir. For LCC estimations, however, off-nadir observations yield improvements, i.e., rRMSE (nadir) = 24% vs. rRMSE (forward scatter) = 20%. It follows that for a variable retrieval through RTM inversion, the final user will benefit from EnMAP time-series for biophysical studies regardless of the acquisition angle and will thus be able to exploit the maximum revisit capability of the mission.

Highlights

The retrieval of biophysical plant variables from optical imagery has been playing an important role in remote sensing and ecosystem modelling for more than 30 years
It follows that for a variable retrieval through radiative transfer models (RTM) inversion, the final user will benefit from Environmental Mapping and Analysis Program (EnMAP) time-series for biophysical studies regardless of the acquisition angle and will be able to exploit the maximum revisit capability of the mission
ANIFs were obtained: one for forward scatter (ANIFfs) marginally drops below 1.0 for the VIS-domain and from 1500 nm to 2500 nm at growth stage (2), due to lower reflectances in the off-nadir compared to nadir observations

Summary

Introduction

The retrieval of biophysical plant variables from optical imagery has been playing an important role in remote sensing and ecosystem modelling for more than 30 years. In the agricultural context, many studies have pointed out the suitability of multispectral data (e.g., [1,2,3,4,5]), hyperspectral data (e.g., [6,7,8,9,10,11]) and a combination of both (e.g., [12,13,14]). Variables like the leaf area index (LAI) or leaf chlorophyll content (LCC) are of prime importance for a proper characterization of the canopy and plant biochemistry [15]. Several approaches are known to successfully retrieve hyperspectral canopy variables from measured spectra. The approaches can be divided into empirical and generic methods.

Objectives

Methods

Results

Discussion

Conclusion