Agrometerological study of semi-arid areas : an experiment for analysing the potential of time series of FORMOSAT-2 images (Tensift-Marrakech plain)

Earth Observing Systems designed to provide both high spatial resolution (10m) and high capacity of time revisit (a few days) offer strong opportunities for the management of agricultural water resources. The FORMOSAT-2 satellite is the first and only satellite with the ability to provide daily high-resolution images over a particular area with constant viewing angles. As part of the SudMed project, one of the first time series of FORMOSAT-2 images has been acquired over the semi-arid Tensift-Marrakech plain. Along with these acquisitions, an experimental data set has been collected to monitor land-cover/land-use, soil characteristics, vegetation dynamics and surface fluxes. This paper presents a first analysis of the potential of these data for agrometerological study of semi-arid areas

Observation spatiale de l'irrigation d'agrosystèmes semi-arides et Gestion durable de la ressource en eau en plaine de Marrakech.

In this study, we aim at monitoring the water balance over the semi-arid plain of Tensift/Marrakech, a 3000 km² intensively cropped area in center of Morocco. This requires firstly to map the land use, secondly to monitor the vegetation dynamics, and thirdly to evaluate evapotranspiration, which is the key-variable of water balance in semi-arid plains. In this context, we investigate the potential offered by Terra-MODIS satellite, which provide a costless daily global coverage of the Earth. We use a six-year archive of 16-day composite NDVI images from 2000-2001 to 2005-2006 agricultural seasons. However, the use of medium (250 m) spatial resolution data makes difficult to directly monitor land surfaces. Indeed, each pixel (mixed pixel) generally includes different types of surface, and consequently its spectral response results from the contribution of each land classes. In a first phase, the land use and the vegetation dynamics are retrieved using linear unmixing model applied on NDVI time series. Identification of end-members, i.e. the specific NDVI time course of individual land classes, is based on the assumption that pure pixels can be identified directly from MODIS NDVI images. The approach is set up to map the land use fractions of the three classes that are the most important for agricultural water management in the study area (non cultivated areas, orchards, annual crops). In a second phase, the information on land use and vegetation dynamics is used to estimate evapotranspiration. The method is adapted from the FAO-56 algorithm, which computes crop water needs from a reference evapotranspiration (ETo) and cultural crops coefficients (Kc). ETo is calculated by applying spatial interpolation of the meteorological data available in the study area. The crop coefficients, which vary according to the crop type, phenological stage and soil water content, are retrieved for each land classes according to their NDVI time courses using various scenarii of irrigation. The spatio-temporal patterns of evapotranspiration maps are analysed to regional driving variables (climate and water availability). The evaluations of the results are done based on: (1) experimental data collected over some test site of SudMed project; (2) high spatial resolution maps derived from FORMOSAT-2 satellite and (3) water availability from the regional public office. This study may offer perspectives for a better estimate of the quantity of ground water used for agriculture.La plaine semi-aride du Tensift au centre du Maroc est une région confrontée à des difficultés croissantes en terme de gestion de l'eau (pluviométrie faible et irrégulière, croissance des besoins sous l'effet de la démographie galopante et l'extension des zones irriguées). Dans ce contexte et dans le cadre du projet SudMed, l'objectif de la thèse est de décrire, dans l'espace (à la résolution kilométrique) et sur de longues périodes temporelles (la décennie), le fonctionnement hydrique des agro-systèmes irrigués de la plaine du Tensift (~3000 km²). La méthodologie développée repose sur le contrôle de modèles agro-météorologiques par des données satellites issues de capteurs optique à large champ (données MODIS de 2000 à 2006). Dans un premier temps, nous nous sommes intéressés à l'occupation du sol, connaissance préalable à la quantification des besoins en eau des cultures. Etant donné la résolution spatiale de MODIS (250 m), nous avons eu recours à des méthodes de désagrégation, qui ont permis d'identifier et de cartographier les trois principales classes d'occupation du sol: zones non irriguées, cultures annuelles, plantations arborées. Dans une deuxième partie, nous avons utilisé cette information pour spatialiser un modèle de bilan hydrique, en étudiant tout particulièrement les termes d'évapotranspiration et d'irrigation. L'évaluation du modèle est effectuée par comparaison: (1) aux données collectées sur les parcelles d'expérimentation du projet SudMed; (2) à des cartes établies à l'aide d'images à haute résolution spatiale et temporelleFORMOSAT-2 et (3) aux volumes d'eau des barrages distribués par l'office agricole régional. Cette étude ouvre des perspectives pour l'estimation des volumes d'eau d'irrigation transitant par les différents réseaux d'irrigation, et en particulier ceux prélevés dans la nappe phréatique du Tensift

A simple algorithm for yield estimates: Evaluation for semi-arid irrigated winter wheat monitored with green leaf area index

In this study we investigated the perspective offered by coupling a simple vegetation growth model and ground-based remotely-sensed data for the monitoring of wheat production. A simple model was developed to simulate the time courses of green leaf area index (GLAI), dry aboveground phytomass (DAM) and grain yield (GY). A comprehensive sensitivity analysis has allowed addressing the problem of model calibration, distinguishing three categories of parameters: (1) those, well known, derived from the present or previous wheat experiments; (2) those, phenological, which have been identified for the wheat variety under study; (3) those, related to farmer practices, which has been adjusted field by field. The approach was tested against field data collected on irrigated winter wheat in the semi-arid Marrakech plain. This data set includes estimates of GLAI with additional DAM and GY measurements. The model provides excellent simulations of both GLAI and DAM time courses. GY space variations are correctly predicted, but with a general underestimation on the validation fields. Despite this limitation, the approach offers the advantage of being quite simple, without requiring any data on agricultural practices (sowing, irrigation and fertilisation). This makes it very attractive for operational application at a regional scale. This perspective is discussed in the conclusion. 2007 Elsevier Ltd. All rights reserved

Demonstration in Space of a Smart Hyperspectral Imager for Nanosatellites

HyperScout is the first smart hyperspectral imager for nanosatellites. It has been launched on the 2nd of February 2018 at 8:51 CET, from the Jiuquan Satellite Launch Center in China. The launch vehicle Long March 2D lifted off on schedule and the satellite was separated from the launch vehicle minutes later. Approximately after 6 hours the first contact was established by GomSpace in Aalborg, Denmark. HyperScout is based on a long line of development led by cosine. The project to develop, build and launch the first HyperScout was funded by ESA, with support from the Dutch, Belgian and Norwegian national space organizations: Netherlands Space Office, BELSPO and Norsk Romsenter. cosine, as the prime contractor, enlisted the help of consortium partners S&T, TU Delft, VDL and VITO. The applications for which HyperScout has been conceived for are crop water management, fire hazard monitoring, flood detection, change detection of land use and land coverage and vegetation monitoring. The aim of the demonstration mission is to assess the quality of the data that will be acquired and the consequent suitability for the intended applications. Furthermore, the basic functionalities of the instrument as well as the onboard processing in real time will be demonstrated. The demonstration is divided in three operational blocks, during which HyperScout will be operated to acquire data from invariant sites for vicarious calibration, from application sites to qualify HyperScout for all the applications it has been conceived for, and to perform software experiments to demonstrate the novel approach to overcome the bandwidth limitation on small platforms. This paper reports about the outcome of the operations performed so far in orbit, and about the preliminary results obtained from the data evaluation performed during the demonstration project

Un modèle simplifié pour l'estimation du bilan hydrique et du rendement de cultures céréalières en milieu semi-aride

International audienc

Observation spatiale à haute resolution spatiale et temporelle : applications pour le suivi de la ressource hydrique en milieu agricole semi-aride

Les données acquises par télédétection satellitale ont été intensivement utilisées pour l’étude des régions agricoles. Dans le domaine spectral solaire, elles ont principalement été acquises par deux types de systèmes, soit à résolution décamétrique avec des capteurs à capacité de revisite modérées (15 jours), soit quotidiennement à basse résolution (~1 km). Dans les domaines solaire et micro-onde, plusieurs missions spatiales permettant l’acquisition fréquente (tous les 1 à 5 jours) d’images à haute résolution ont été lancées récemment ou vont l’être dans un futur proche (FORMOSAT-2, ENVISAT-ASAR, Sentinel-2, Venμs, Rapid-Eye, Terra-SAR, Cosmo-Skymed). L’objectif de cette communication est d’attirer l’attention sur certaines perspectives offertes par ces missions spatiales à hautes résolutions spatiale et temporelle pour l’étude des agro-écosystèmes. Les exemples, issus principalement de recherches menées dans des régions semi-arides à partir de données FORMOSAT-2, portent sur la cartographie de l’occupation du sol, la détection des opérations agricoles et le suivi de la dynamique des couverts végétaux. L’intérêt de ces informations pour la spatialisation de modèles agro-météorologiques - estimation de la consommation en eau et irrigation des cultures - est également discuté

Surface Albedo Retrieval from 40-Years of Earth Observations through the EUMETSAT/LSA SAF and EU/C3S Programmes: The Versatile Algorithm of PYALUS

Land surface albedo quantifies the fraction of the sunlight reflected by the surface of the Earth. This article presents the algorithm concepts for the remote sensing of this variable based on the heritage of several developments which were performed at Méteo France over the last decade and described in several papers by Carrer et al. The scientific algorithm comprises four steps: an atmospheric correction, a sensor harmonisation (optional), a BRDF (Bidirectional Reflectance Distribution Function) inversion, and the albedo calculation. At the time being, the method has been applied to 11 sensors in the framework of two European initiatives (Satellite Application Facility on Land Surface Analysis—LSA SAF, and Copernicus Climate Change Service—C3S): NOAA-7-9-11-14-16-17/AVHRR2-3, SPOT/VGT1-2, Metop/AVHRR-3, PROBA-V, and MSG/SEVIRI. This work leads to a consistent archive of almost 40 years of satellite-derived albedo data (available in 2020). From a single sensor, up to three different albedo products with different characteristics have been developed to address the requirements of both, near real-time (NRT) (weather prediction with a demand of timeliness of 1 h) and climate communities. The evaluation of the algorithm applied to different platforms was recently made by Lellouch et al. and Sánchez Zapero et al. in 2020 which can be considered as companion papers. After a summary of the method for the retrieval of these surface albedos, this article describes the specificities of each retrieval, lists the differences, and discusses the limitations. The plan of continuity with the next European satellite missions and perspectives of improvements are introduced. For example, Metop/AVHRR-3 albedo will soon become the medium resolution sensor product with the longest NRT data record, since MODIS is approaching the end of its life-cycle. Additionally, Metop-SG/METimage will ensure its continuity thanks to consistent production of data sets guaranteed till 2050 by the member states of the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT). In the end, the common strategy which we proposed through the different programmes may offer an unprecedented opportunity to study the temporal trends affecting surface properties and to analyse human-induced climate change. Finally, the access to the source code (called PYALUS) is provided through an open access platform in order to share with the community the expertise on the satellite retrieval of this variable

Surface Albedo Retrieval from 40-Years of Earth Observations through the EUMETSAT/LSA SAF and EU/C3S Programmes: The Versatile Algorithm of PYALUS

Land surface albedo quantifies the fraction of the sunlight reflected by the surface of the Earth. This article presents the algorithm concepts for the remote sensing of this variable based on the heritage of several developments which were performed at Méteo France over the last decade and described in several papers by Carrer et al. The scientific algorithm comprises four steps: an atmospheric correction, a sensor harmonisation (optional), a BRDF (Bidirectional Reflectance Distribution Function) inversion, and the albedo calculation. At the time being, the method has been applied to 11 sensors in the framework of two European initiatives (Satellite Application Facility on Land Surface Analysis—LSA SAF, and Copernicus Climate Change Service—C3S): NOAA-7-9-11-14-16-17/AVHRR2-3, SPOT/VGT1-2, Metop/AVHRR-3, PROBA-V, and MSG/SEVIRI. This work leads to a consistent archive of almost 40 years of satellite-derived albedo data (available in 2020). From a single sensor, up to three different albedo products with different characteristics have been developed to address the requirements of both, near real-time (NRT) (weather prediction with a demand of timeliness of 1 h) and climate communities. The evaluation of the algorithm applied to different platforms was recently made by Lellouch et al. and Sánchez Zapero et al. in 2020 which can be considered as companion papers. After a summary of the method for the retrieval of these surface albedos, this article describes the specificities of each retrieval, lists the differences, and discusses the limitations. The plan of continuity with the next European satellite missions and perspectives of improvements are introduced. For example, Metop/AVHRR-3 albedo will soon become the medium resolution sensor product with the longest NRT data record, since MODIS is approaching the end of its life-cycle. Additionally, Metop-SG/METimage will ensure its continuity thanks to consistent production of data sets guaranteed till 2050 by the member states of the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT). In the end, the common strategy which we proposed through the different programmes may offer an unprecedented opportunity to study the temporal trends affecting surface properties and to analyse human-induced climate change. Finally, the access to the source code (called PYALUS) is provided through an open access platform in order to share with the community the expertise on the satellite retrieval of this variable

Evaluation of PROBA-V Collection 1: Refined Radiometry, Geometry, and Cloud Screening

PROBA-V (PRoject for On-Board Autonomy–Vegetation) was launched in May-2013 as an operational continuation to the vegetation (VGT) instruments on-board the Système Pour l’Observation de la Terre (SPOT)-4 and -5 satellites. The first reprocessing campaign of the PROBA-V archive from Collection 0 (C0) to Collection 1 (C1) aims at harmonizing the time series, thanks to improved radiometric and geometric calibration and cloud detection. The evaluation of PROBA-V C1 focuses on (i) qualitative and quantitative assessment of the new cloud detection scheme; (ii) quantification of the effect of the reprocessing by comparing C1 to C0; and (iii) evaluation of the spatio-temporal stability of the combined SPOT/VGT and PROBA-V archive through comparison to METOP/advanced very high resolution radiometer (AVHRR). The PROBA-V C1 cloud detection algorithm yields an overall accuracy of 89.0%. Clouds are detected with very few omission errors, but there is an overdetection of clouds over bright surfaces. Stepwise updates to the visible and near infrared (VNIR) absolute calibration in C0 and the application of degradation models to the SWIR calibration in C1 result in sudden changes between C0 and C1 Blue, Red, and NIR TOC reflectance in the first year, and more gradual differences for short-wave infrared (SWIR). Other changes result in some bias between C0 and C1, although the root mean squared difference (RMSD) remains well below 1% for top-of-canopy (TOC) reflectance and below 0.02 for the normalized difference vegetation index (NDVI). Comparison to METOP/AVHRR shows that the recent reprocessing campaigns on SPOT/VGT and PROBA-V have resulted in a more stable combined time series