Remote estimation of crop and grass chlorophyll and nitrogen content using red-edge bands on Sentinel-2 and -3

Sentinel-2 is planned for launch in 2014 by the European Space Agency and it is equipped with the Multi Spectral Instrument (MSI), which will provide images with high spatial, spectral and temporal resolution. It covers the VNIR/SWIR spectral region in 13 bands and incorporates two new spectral bands in the red-edge region, which can be used to derive vegetation indices using red-edge bands in their formulation. These are particularly suitable for estimating canopy chlorophyll and nitrogen (N) content. This band setting is important for vegetation studies and is very similar to the ones of the Ocean and Land Colour Instrument (OLCI) on the planned Sentinel-3 satellite and the Medium Resolution Imaging Spectrometer (MERIS) on Envisat, which operated from 2002 to early 2012. This paper focuses on the potential of Sentinel-2 and Sentinel-3 in estimating total crop and grass chlorophyll and N content by studying in situ crop variables and spectroradiometer measurements obtained for four different test sites. In particular, the red-edge chlorophyll index (CIred-edge), the green chlorophyll index (CIgreen) and the MERIS terrestrial chlorophyll index (MTCI) were found to be accurate and linear estimators of canopy chlorophyll and N content and the Sentinel-2 and -3 bands are well positioned for deriving these indices. Results confirm the importance of the red-edge bands on particularly Sentinel-2 for agricultural applications, because of the combination with its high spatial resolution of 20

Application of Spectral Remote Sensing for Agronomic Decisions

Remote sensing has provided valuable insights into agronomic management over the past 40 yr. The contributions of individuals to remote sensing methods have lead to understanding of how leaf reflectance and leaf emittance changes in response to leaf thickness, species, canopy shape, leaf age, nutrient status, and water status. Leaf chlorophyll and the preferential absorption at different wavelengths provides the basis for utilizing reflectance with either broad-band radiometers typical of current satellite platforms or hyperspectral sensors that measure reflectance at narrow wavebands. Understanding of leaf reflectance has lead to various vegetative indices for crop canopies to quantify various agronomic parameters, e.g., leaf area, crop cover, biomass, crop type, nutrient status, and yield. Emittance from crop canopies is a measure of leaf temperature and infrared thermometers have fostered crop stress indices currently used to quantify water requirements. These tools are being developed as we learn how to use the information provided in reflectance and emittance measurements with a range of sensors. Remote sensing continues to evolve as a valuable agronomic tool that provides information to scientists, consultants, and producers about the status of their crops. This area is still relatively new compared with other agronomic fields; however, the information content is providing valuable insights into improved management decisions. This article details the current status of our understanding of how reflectance and emittance have been used to quantitatively assess agronomic parameters and some of the challenges facing future generations of scientists seeking to further advance remote sensing for agronomic applications

PROSPECT-D : vers la modélisation des propriétés optiques foliaires durant l'ensemble du cycle de vie

International audienceLeaf pigments provide valuable information about plant physiology. High resolution monitoring of their dynamics will give access to better understanding of processes occurring at different scales, and will be particularly important for ecologists, farmers, and decision makers to assess the influence of climate change on plant functions, and the adaptation of forest, crop, and other plant canopies. In this article, we present a new version of the widely-used PROSPECT model, hereafter named PROSPECT-D for dynamic, which adds anthocyanins to chlorophylls and carotenoids, the two plant pigments in the current version. We describe the evolution and improvements of PROSPECT-D compared to the previous versions, and perform a validation on various experimental datasets. Our results show that PROSPECT-D outperforms all the previous versions. Model prediction uncertainty is decreased and photosynthetic pigments are better retrieved. This is particularly the case for leaf carotenoids, the estimation of which is particularly challenging. PROSPECT-D is also able to simulate realistic leaf optical properties with minimal error in the visible domain, and similar performances to other versions in the near infrared and shortwave infrared domains.Les pigments foliaires fournissent des informations précieuses sur la physiologie des plantes. Le suivi fin de leur dynamique pour permettre de mieux comprendre les processus qui se produisent à différentes échelles et sera particulièrement important pour les écologues, les agriculteurs et les décideurs pour évaluer l'influence du changement climatique sur les fonctions des plantes et l'adaptation des forêts, des cultures, et de la végétation en général. Dans cet article, nous présentons une nouvelle version du modèle PROSPECT largement utilisé, appelé PROSPECT-D, pour Dynamique, qui ajoute les anthocyanes aux chlorophylles et aux caroténoïdes, les deux pigments végétaux pris en compte jusqu'à la version présente. Nous décrivons l'évolution et les améliorations de PROSPECT-D par rapport aux versions précédentes, et réalisons une validation sur différents jeux de données expérimentales. Nos résultats montrent que PROSPECT-D surpasse toutes les versions précédentes. L'incertitude de prédiction du modèle est diminuée et les pigments photosynthétiques sont mieux récupérés. C'est particulièrement le cas des caroténoïdes foliaires, dont l'estimation est particulièrement difficile. PROSPECT-D est également capable de simuler des propriétés optiques réalistes de la feuille avec une erreur minimale dans le domaine visible et des performances similaires aux précédentes versions dans le domaine infrarouge