Evaluation of the MODIS Albedo Product over a Heterogeneous Agricultural Area

In this article, the Moderate Resolution Imaging Spectroradiometer (MODIS) Bidirectional Reflectance Distribution Function (BRDF)/Albedo product (MCD43) is evaluated over a heterogeneous agricultural area in the framework of the Earth Observation: Optical Data Calibration and Information Extraction (EODIX) project campaign, which was developed in Barrax (Spain) in June 2011. In this method, two models, the RossThick-LiSparse-Reciprocal (RTLSR) (which corresponds to the MODIS BRDF algorithm) and the RossThick-Maignan-LiSparse-Reciprocal (RTLSR-HS), were tested over airborne data by processing high-resolution images acquired with the Airborne Hyperspectral Scanner (AHS) sensor. During the campaign, airborne images were retrieved with different view zenith angles along the principal and orthogonal planes. Comparing the results of applying the models to the airborne data with ground measurements, we obtained a root mean square error (RMSE) of 0.018 with both RTLSR and RTLSR-HS models. The evaluation of the MODIS BRDF/Albedo product (MCD43) was performed by comparing satellite images with AHS estimations. The results reported an RMSE of 0.04 with both models. Additionally, taking advantage of a homogeneous barley pixel, we compared in situ albedo data to satellite albedo data. In this case, the MODIS albedo estimation was (0.210 +/- 0.003), while the in situ measurement was (0.204 +/- 0.003). This result shows good agreement in regard to a homogeneous pixel

Clay contents predicted from hyperspectral vnir/swir imagery, under different atmospheric conditions and spatial resolutions

International audienceVisible, Near-Infrared and Short Wave Infrared hyperspectral satellite imaging is one of the most promising tools for soil property mapping. The objective of this study was to test the sensitivity of soil property prediction results to atmospheric effects and to degradation in image spatial resolutions, to offer a first analysis of the potential of future hyperspectral satellite sensors for Soil applications (HYPXIM, PRISMA, Shalom, ENMAP and HyspIRI). Our results showed that (i) regression methods have robust performances from images from 5 to 30m and are inaccurate from images at 60 and 90m; (ii) when a correct compensation of the atmosphere effects is done, no differences are detected between the soil property maps retrieved from airborne imagery and the ones from spaceborne imagery; (iii) the spatial aggregation of the images induces a loss of the variance of the soil property prediction from 15 m of spatial resolution and a loss of information on soil spatial structures from 30 m of spatial resolution

Evaluating the sensitivity of clay content prediction to atmospheric effects and degradation of image spatial resolution using Hyperspectral VNIR/SWIR imagery

Visible, near-infrared and short wave infrared (VNIR/SWIR, 0.4-2.5 mu m) hyperspectral satellite imaging is one of the most promising tools for topsoil property mapping for the following reasons: i) it is derived from a laboratory technique that has been demonstrated to be a good alternative to costly physical and chemical laboratory soil analysis for estimating a large range of soil properties; ii) it can benefit from the increasing number of methodologies developed for VNIR/SWIR hyperspectral airborne imaging; and iii) it provides a synoptic view of the study area. Despite the significant potential of VNIR/SWIR hyperspectral airborne data for topsoil property mapping, the transposition to satellite data must be evaluated. The objective of this study was to test the sensitivity of clay content prediction to atmospheric effects and to degradation of spatial resolution. This study may offer an initial analysis of the potential of future hyperspectral satellite sensors, such as the HYPerspectral X Imagery (HYPXIM), the Spaceborne Hyperspectral Applicative Land and Ocean Mission (SHALOM), the PRecursore IperSpettrale della Missione Applicativa (PRISMA), the Environmental Mapping and Analysis Program (EnMAP) and the Hyperspectral Infrared Imager (HyspIRI), for soil applications. This study employed VNIR/ SWIR AISA-DUAL airborne data acquired in a Mediterranean region over a large area (300 km(2)) with an initial spatial resolution of 5 m. These hyperspectral airborne data were simulated at the top of the atmosphere and aggregated at six spatial resolutions (10, 15, 20, 30, 60 and 90 m) to correlate with the future hyperspectral satellite sensors. The predicted clay content maps were obtained using the partial least squares regression (PLSR) method. The large area of the studied region allows analysis of different pedological patterns of soil composition and spatial structures. Our results showed the following: (i) when a correct compensation of atmosphere effects was performed, only slight differences were detected between clay maps retrieved from the airborne imagery and those from spaceborne imagery (both at 5 m of spatial resolution); (ii) the PLSR models, built from data with 5 to 30 m spatial resolutions, performed well, and allowed clay mapping, although variations in clay content related to short scale succession of parent material was imperfectly captured beyond 15 m of spatial resolution; (iii) the PLSR models built from data with 60 and 90 m spatial resolutions were inaccurate, and did not enable clay mapping; and (iv) the two latter results could be explained by the combination of a small short-scale clay content variability and small field sizes observed in the study area. Therefore, in the Mediterranean and under the spectral specifications of the AISA-DUAL airborne sensor, most of the future hyperspectral satellite sensors (four of the five sensors examined in this study) will be potentially useful for clay content mapping

Evaluation of the surface urban heat island effect in the city of Madrid by thermal remote sensing

The surface urban heat island (SUHI) effect is defined as the increased surface temperatures in urban areas in contrast to cooler surrounding rural areas. In this article, the evaluation of the SUHI effect in the city of Madrid (Spain) from thermal infrared (TIR) remote-sensing data is presented. The data were obtained from the framework of the Dual-use European Security IR Experiment (DESIREX) campaign that was carried out during June and July 2008 in Madrid. The campaign combined the collection of airborne hyperspectral and in situ measurements. Thirty spectral and spatial high-resolution images were acquired with the Airborne Hyperspectral Scanner (AHS) sensor in a 11, 21, and 4 h UTC scheme. The imagery was used to retrieve the SUHI effect by applying the temperature and emissivity separation (TES) algorithm. The results show a nocturnal SUHI effect with a highest value of 5 K. This maximum value agrees within 1 K with the highest value of the urban heat island (UHI) observed using air temperature data (AT). During the daytime, this situation is reversed and the city becomes a negative heat island

Fluorescence estimation in the framework of the CEFLES2 campaign

International audienceChlorophyll fluorescence (ChF) is a relevant indicator of the actual plant physiological status. In this article different methods to measure ChF from remote sensing are evaluated: The Fraunhofer Line Discrimination (FLD), theFluorescence Radiative Method (FRM) and the improved Fraunhofer Line Discrimination (iFLD). The three methods have been applied to data acquired in the framework of the CarboEurope, FLEX and Sentinel-2 (CEFLES2) campaign in Les Landes, France in September 2007. Comparing with in situ measurements, the results indicate that the methods that provide the best results are the FLD and the iFLD with root mean square errors (RMSEs) of 0.4 and 0.5 mW m-2 sr-1 nm-1, respectively, while the FRM provides an error of 0.8 mW m-2 sr-1 nm-1. © 2011 Taylor & Francis

Synergy of SMOS microwave radiometer, thermal data and vegetation index for monitoring the water status of forest and natural vegetation

International audienc