Canadian Experiment for Soil Moisture in 2010 (CanEX-SM10): Overview and Preliminary Results

The Canadian Experiment for Soil Moisture in 2010 (CanEx-SM10) was carried out in Saskatchewan, Canada from 31 May to 16 June, 2010. Its main objective was to contribute to Soil Moisture and Ocean salinity (SMOS) mission validation and the pre-launch assessment of Soil Moisture and Active and Passive (SMAP) mission. During CanEx-SM10, SMOS data as well as other passive and active microwave measurements were collected by both airborne and satellite platforms. Ground-based measurements of soil (moisture, temperature, roughness, bulk density) and vegetation characteristics (Leaf Area Index, biomass, vegetation height) were conducted close in time to the airborne and satellite acquisitions. Besides, two ground-based in situ networks provided continuous measurements of meteorological conditions and soil moisture and soil temperature profiles. Two sites, each covering 33 km x 71 km (about two SMOS pixels) were selected in agricultural and boreal forested areas in order to provide contrasting soil and vegetation conditions. This paper describes the measurement strategy, provides an overview of the data sets and presents preliminary results. Over the agricultural area, the airborne L-band brightness temperatures matched up well with the SMOS data. The Radio frequency interference (RFI) observed in both SMOS and the airborne L-band radiometer data exhibited spatial and temporal variability and polarization dependency. The temporal evolution of SMOS soil moisture product matched that observed with the ground data, but the absolute soil moisture estimates did not meet the accuracy requirements (0.04 m3/m3) of the SMOS mission. AMSR-E soil moisture estimates are more closely correlated with measured soil moisture

Incertitudes des niveaux d’eau dérivés de l’altimétrie satellitaire pour des étendues d’eau soumises à l’action de la glace

La présence de cibles hétérogènes, comme la glace, reste un défi majeur pour l’utilisation des données altimétriques au-dessus des plans d’eau continentaux. Les satellites Jason-2 et SARAL/Altika utilisent des algorithmes de retraitement conçus pour traiter les formes d’onde non continentales afin d’obtenir des estimations améliorées. Dans cette étude, nous analysons le potentiel des produits dérivés de ces algorithmes pour estimer le niveau d’eau de 20 plans d’eau couverts par la glace répartis à travers le Canada. Les estimations de niveaux d’eau des algorithmes de retraitement sont comparées aux mesures in situ pendant deux périodes: la période entièrement couverte par chacun des deux satellites dans l’étude (2008–2016 pour Jason-2, et 2013–2016 pour SARAL/Altika); ainsi que les périodes de gel-dégel incluses dans les séries chronologiques. Les algorithmes produisent des incertitudes très variables, en fonction de la taille des cours d’eau et des conditions de la glace. Dans l’ensemble, l’algorithme ICE-1 utilisé par Jason-2 fournit les meilleures estimations de niveau d’eau, avec des erreurs RMSE non biaisées ≤0.3 m et des R2 ≥ 0.8 pour 90% des plans d’eau. Tous les algorithmes de retraitement utilisés par SARAL/Altika donnent des résultats très comparables aux observations in situ, démontrant les bonnes performances de la technologie SARAL

Evaluation of simplified polarimetric decomposition for soil moisture retrieval over vegetated agricultural fields

This paper investigates a simplified polarimetric decomposition for soil moisture retrieval over agricultural fields. In order to overcome the coherent superposition of the backscattering contributions from vegetation and underlying soils, a simplification of an existing polarimetric decomposition is proposed in this study. It aims to retrieve the soil moisture by using only the surface scattering component, once the volume scattering contribution is removed. Evaluation of the proposed simplified algorithm is performed using extensive ground measurements of soil and vegetation characteristics and the time series of UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar) data collected in the framework of SMAP (Soil Moisture Active Passive) Validation Experiment 2012 (SMAPVEX12). The retrieval process is tested and analyzed in detail for a variety of crops during the phenological stages considered in this study. The results show that the performance of soil moisture retrieval depends on both the crop types and the crop phenological stage. Soybean and pasture fields present the higher inversion rate during the considered phenological stage, while over canola and wheat fields, the soil moisture can be retrieved only partially during the crop developing stage. RMSE of 0.06–0.12 m3/m3 and an inversion rate of 26%–38% are obtained for the soil moisture retrieval based on the simplified polarimetric decomposition.ISSN:2072-429

An integrated approach to hydro-geological lineament mapping of a semi-arid region of West Africa using Radarsat-1 and GIS.

International audienceIn the 21st century, water resource management will be a major socioeconomic issue and an essential component of progress in semi-arid regions. The Soudano-Sahelian region of Africa suffers from a chronic lack of reliable hydro-geological maps for local water resource managers. To provide better tools for groundwater exploration, this paper focuses on hydro-geological lineament mapping using remote sensing data. The objectives were (1) evaluate the potential of multi-angular and multi-temporal Radarsat-1 images for extracting lineaments in semi-arid regions and (2) provide map of potential hydro-geological lineaments. No significant relationship was found between lineament yield and incidence angle of Radarsat-1 images, while lineament spatial distribution was in good agreement with the land use and geology of the study area. The high scores observed for NNE–SSW and NNW–SSE orientations match the results of local lineament studies of the region. Radarsat-1 image acquired on May 01, 2001 offers the greatest potential, due to the reduced effect of vegetation during this region's dry season. Potential hydro-geological lineaments were mapped using the weighting of well location, presence of green vegetation during the dry season, preferential lineament orientations and presence of cross-points. The mapping revealed five classes (Very low, Low, Moderate, High and Very high) of potential hydro-geological lineaments with high and very high potential poorly represented. Results also reveal that most wells are far enough from lineaments or crosspoints and hence the inefficiency of existing drilling programs. © 2010 Elsevier Inc. All rights reserved

Multi-resolution soil moisture retrievals by disaggregating SMAP brightness temperatures with RADARSAT-2 polarimetric decompositions

Mapping soil moisture (SM) at high spatial resolution assists to trigger important agricultural management, such as irrigation, to enhance crop yields. This study investigates disaggregation of SMAP brightness temperature (TB) using RADARSAT-2 polarimetric decompositions to retrieve high-resolution SM. Compared to Sentinel-1 backscattering coefficients used in the SMAP baseline active–passive SM retrieval algorithms, the RADARSAT-2 surface scattering power Ps with a reduced vegetation influence was hypothesized to be more relevant to disaggregate the SMAP TB. Different polarimetric decompositions were evaluated to extract an optimal Ps, followed by an incidence angle normalization. Then, the optimal Ps parameter was aggregated to the same spatial resolution as the SMAP TB to develop empirical relationships between Ps and TB. Furthermore, the airborne TB data collected by Passive Active l-band Sensor (PALS) were analyzed in terms of the Ps across multiple spatial resolutions, to account for the scale effect on the Ps/TB relationships. Finally, the τ-ω emission model was used to retrieve SM at multiple spatial resolutions (10 km, 1 km, 500 m, 100 m, and 50 m). The impacts of spatial resolution on retrieval accuracy were analyzed to determine the best spatial resolution for SM retrievals. The results indicated that the An polarimetric decomposition with the de-orientation provided the highest surface scattering powers, which may benefit the SM estimation. In contrast to the traditional cosine algorithms, the incidence angle normalization of Ps with span resulted in a temporally decreasing surface scattering power, because of the increasing vegetation attenuation as the crop grows. The sensitivity of TB to Ps decreases as the resolution scale varies from 36 km to 50 m. The SM retrievals across multiple resolutions obtained marginal differences in retrieval accuracy. Although slightly better results were obtained with 1 km spatial resolution which is close to the nominal size of agricultural fields in the study area (R = 0.68–0.8 and RMSE = 0.039–0.062 m3/m3), the retrievals at 50 m spatial resolution (R = 0.63–0.76 and RMSE = 0.046–0.067 m3/m3) capture the spatial heterogeneity of SM within and across different fields which could be very helpful for the precision agriculture

Soil Moisture Retrieval During Crop Growth Cycle Using Satellite SAR Time Series

Satellite SAR-based soil moisture retrieval over agricultural fields, under crop overlain conditions, is a challenging exercise. This is so because the overlying crop volume interacts with both the incoming and the backscattered radar signal. Therefore, the soil moisture linked solely to the top layer (0–5 cm) of the soil cannot be reliably retrieved under such conditions without avoiding the obscuring effect of growing crop volume. In this investigation, we demonstrated a proof-of-concept for a time-series approach to retrieve soil moisture during crop growth cycle. Contrary to the use of the single-scene approach, the novelty of the proposed approach lies in exploiting the satellite SAR time series acquired during a cropping cycle. The proposed time-series approach is effective for capturing the nuances in the crop phenological stages while calibrating the Dubois–water cloud model (WCM) soil moisture retrieval model. By employing this approach, we achieved the 0.04 $\text{m}^{3}\;\text{m}^{-3}$ soil moisture retrieval root-mean-square error benchmark at a high spatial resolution and addressed the issue of solving for the Dubois–WCM model constants under data-constrained conditions. Furthermore, we observed that the combination of temporally non-overlapping vegetation descriptors (optical and SAR) resulted in degradation in the performance of the retrievals and under such circumstances single polarimetric descriptor performed better

Développement collaboratif d'outils d'alerte inondations pour l'Afrique de l'Ouest : rapport final (1/12/2013 - 30/09/2016)

Ce rapport décrit les réalisations du projet intitulé 'Développement Collaboratif d'Outils d'Alerte Inondations' depuis son lancement le 1/12/2013 jusqu’à sa date de clôture (le 30 septembre 2016). Le projet avait pour objectif de la mise en place d'un système opérationnel de prévision des crues sur le bassin du fleuve Niger qui comprendra: a) un modèle SWAT (Soil & Water Assessment Tool : Arnold et al., 1998) qui sera opéré quotidiennement au Centre Régional Agrhymet et b) une plateforme Web de diffusion des prévisions; et la facilitation de l'utilisation de l'information générée pour les services hydrologiques nationaux et les décideurs des villes à fort risque d'inondation par l'organisation de deux ateliers de formation. Le financement du projet vient principalement du CRDI, mais de nombreux partenaires autant au Niger qu’au Canada ont contribué en espèces ou en nature à la conduite des travaux..