The development of an innovative computer-based Integrated Water Resources Management System for water resources analyses

International audienceThe European IWRMS (Integrated Water Resources Management System) project is dedicated to developing a toolset for a sustainable use and distribution of water resources in souther African countries. This system integrates various scientific components: remote sensing, information systems, database management, and hydrological modelling. This paper is mainly related to the remote sensing contribution of the project. Two points are discussed: land cover classification and the spatio-temporal processing of remote sensing data to extract hydrological parameters

Fusion of LANDSAT TM, NOAA/AVHRR and DEM data for generating daily high resolution maps of Land Surface Temperature in a semi-arid catchment.

International audienceVegetation and hydrological monitoring by using satellite images has become an important research field. Both high temporal frequency and detailed spatial information are essential for an effective interpretation of satellite images. In particular, we focus on land surface temperature Tsurf, required for estimating evapotranspiration; this paper addresses the problem of computing spatial maps of Tsurf with a good spatial resolution and a high temporal frequency. For this purpose, we define a coupling process between {LANDSAT TM, NOAA/AVHRR} and DEM dat

Evapotranspiration mapping using NOAA/AVHRR images and a simplified model of surface energy balance. Application to the Mkomazi river catchment in South Africa.

International audienceEvapotranspiration measures the quantity of water lost by evaporation from the soil and the plant. It is expressed in mm/day. In semi-arid areas, a main part of precipitation is in fact lost by evapotranspiration. So, this quantity is an important component of the water cycle and it becomes necessary to estimate it and to monitor its temporal evolution with precision. Up date, in Mbuluzi catchment in Swaziland, evapotranspiration is only measured at discrete points where ground measurements stations are available. This paper addresses the problems of computing maps of evapotranspiration with a large coverage and a high temporal frequency, by using only remote sensing data and without additional field and/or meteorological dat

Suivi spatio-temporel de paramètres hydrologiques sur un bassin versant par couplage de données satellitaires

L'étude porte sur l'utilisation de données satellitaires multi-capteurs pour l'estimation de la caractérisation de paramètres hydrologiques selon le type d'occupation de sol. Les données utilisées pour effectuer ce travail proviennent de deux capteurs différents : images quotidiennes NOAA/AVHRR (de faible résolution spatiale) et une image LANDSAT TM (à haute résolution spatiale). Une première étape permet d'estimer la réflectance, la température de surface et l'évapotranspiration à partir de l'imagerie NOAA/AVHRR. On considère pour cela un modèle simplifié du bilan d'énergie à la surface étalonné à partir de mesures in-situ. Des cartes sont présentées sur trois bassins versants à la résolution spatiale de NOAA/AVHRR (1.1.1.1 km2). Par couplage des données quotidiennes NOAA/AVHRR et d'une image de classification issue de LANDSAT TM (résolution spatiale de 30.30 m2), on génère premièrement des profils individuels quotidiens pour chaque occupation de sol, puis des cartes pour chacun des paramètres à la résolution LANDSAT. Deux modèles de composition des pixels sont alors considérés : linéaires pour la réflectance, non linéaire pour la température de surface. L'influence de la topographie sur les profils est également prise en compte par l'analyse simultanée d'un Modèle Numérique de Terrain. On propose également une méthode permettant d'accéder aux proportions des différentes occupations de sols dans les pixels basse résolution, nécessaires à l'estimation des profils, quand aucune donnée haute résolution n'est disponible. Chaque partie présente et analyse des résultats expérimentaux.CALAIS-BU Sciences (621932101) / SudocSudocFranceF

Use of topographic information to improve a land cover classification. Preliminary Results

International audienceIn this paper, we propose a scheme for a land cover classification process from satellite images, with inclusion of topographic effects (elevation) available from a digital elevation model. First, we study and analyse errors provided from the relief on an available non-topographic classification image. We then present a classification process which takes into account, for each land cover type, the non-unicity of reflectance values according to the elevation. We build a new topographic classification, whose results and their analysis are presente

Hydric stress detection through actual evapotranspiration by remote sensing in semi-arid catchments

International audienceThis paper addresses the characterization of Land Surface Temperature (LST) variability according to Land Cover. It is a first step of a study which concerns the extraction of hydrological parameters in a semi-arid catchment applied located in Southern-Africa, and which includes image processing of satellite data. The main applicative interest of this work is to make available profiles of evapotranspiration (ET), which can be derived from LST, and to detect hydric stress by comparison between profiles of ET: potential ET simulated by an hydrological model and that estimated by satellite measurements. LST can be daily computed using the two thermal bands of NOAA/AVHRR. However, due to its coarse resolution (1.1 km at nadir), a NOAA/AVHRR pixel includes several land cover types and LST cannot be linked to a particular component. So, we process a data fusion between NOAA/AVHRR acquisitions and one high resolution land-use classification derived from Landsat-TM (30 meters at nadir), and consider a physical-based mixture model of the temperature pixel. Inverting this model on a learning area outputs individual temporal profiles of LST for each land cover type: bare soil, vegetated surface (grass, arable land, forest...). The obtained results with Landsat classification are then used to generate LST maps at spatial resolution of 30 meters and with a daily frequency

Use of multisensor, multiscale, and temporal data for characterizing land surface temperature variability according to land cover

Image and Signal Processing for Remote SensingInternational audienceThis paper presents the characterization of Land Surface Temperature (LST) variability according to land cover, in order to derive the properties of evapotranspiration and improve the monitoring of a catchment. The land cover can be represented by its Normalized Difference Vegetation Index (NDVI) and first results underscore the relation between T and NDVI at NOAA-AVHRR pixels scale. However, due to their rough resolution, these pixels include several land cover types and this study revealed not useful for catchment monitoring. Therefore, Land Surface Temperature has to be specified with a more precise representation. We employ a physical model of temperature, which requires several parameters such as proportion and emissivity for each component within the pixel; these values are obtained with learning process using high resolution data such as Landsat TM. These results are then extrapolated to the global region with NOAA-AVHRR acquisitions and allow to analyze the land cover effects on Land Surface Temperature variability. By this way, the characterization of evapotranspiration according to land use for a global catchment is improved

Fusion of LANDSAT TM and NOAA/AVHRR data for evaporation maps generation in a semi-arid catchment

International audienceNo abstrac

Etude spatio-temporelle de la temperature du sol par données satellitaires multicapteurs

In frenchNo abstrac

Etude spatio-temporelle de la temperature du sol par données satellitaires multicapteurs

In frenchNo abstrac