Self-calibrated evaporation-based disaggregation of SMOS soil moisture: An evaluation study at 3 km and 100 m resolution in Catalunya, Spain

Abstract

et al.. Self-calibrated evaporation-based disaggregation of SMOS soil moisture: An evaluation study at 3 km and 100 m resolution in Catalunya, Spain. Remote Sensing of Environment, Elsevier, 2012, Abstract A disaggregation algorithm is applied to 40 km resolution SMOS (Soil Moisture and Ocean Salinity) surface soil moisture using 1 km resolution MODIS (MODerature resolution Imaging Spectroradiometer), 90 m resolution ASTER (Advanced Spaceborne Thermal Emission and Reflection radiometer), and 60 m resolution Landsat-7 data. DISPATCH (DISaggregation based on Physical And Theoretical scale CHange) distributes high-resolution soil moisture around the low-resolution observed mean value using the instantaneous spatial link between optical-derived soil evaporative efficiency (ratio of actual to potential evaporation) and near-surface soil moisture. The objective is three-fold: (i) evaluating DISPATCH at a range of spatial resolutions using readily available multi-sensor thermal data, (ii) deriving a robust calibration procedure solely based on remotely sensed data, and (iii) testing the linear or nonlinear behaviour of soil evaporative efficiency. Disaggregated soil moisture is compared with the 0-5 cm in situ measurements collected each month land area in Catalunya, Spain. The target downscaling resolution is set to 3 km using MODIS data and to 100 m using ASTER and Landsat data. When comparing 40 km SMOS, 3 km disaggregated and 100 m disaggregated data with the in situ measurements aggregated at corresponding resolution, results indicate that DISPATCH improves the spatio-temporal correlation with in situ measurements at both 3 km and 100 m resolutions. A yearly calibration of DISPATCH is more efficient than a daily calibration. Assuming a linear soil evaporative efficiency model is adequate at kilometric resolution. At 100m resolution, the very high spatial variability in the irrigated area makes the linear approximation poorer. By accounting for non-linearity effects, the slope of the linear regression between disaggregated and in situ measurements is increased from 0.2 to 0.5. Such a multi-sensor remote sensing approach has potential for operational multi-resolution monitoring of surface soil moisture and is likely to help parameterize soil evaporation at integrated spatial scales.

Downscaling soil moisture over regions that include multiple coarse-resolution grid cells

“…The NSCE of the fixed window output is also greater than the coarse input NSCE for all resolutions considered, which suggests independently downscaled when the fixed window procedure is used. They are also similar to the abrupt changes observed for other methods that downscale each cell independently [Fang and Lakshmi, 2014, Merlin et al, 2013, Merlin et al, 2012.…”

“…Other studies have downscaled multiple coarse grid values but have not considered this issue in depth. Several of these algorithms downscale each coarse grid cell independently from the adjacent coarse grids [Fang and Lakshmi, 2014, Merlin et al, 2013, Merlin et al, 2012, but the resulting soil moisture maps show unnatural discontinuities in the soil moisture values at the coarse grid boundaries. Such discontinuities might be problematic for applications like routing vehicles across the landscape [Flores et al, 2014].…”

“…Merlin et al [2006] added the use of a land surface model and tested this approach. Disaggregation Based on Physical and Theoretical Scale Change (DisPATCh) was also used to downscale SMOS data to 3 km and 100 m resolutions using Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Spaceborne thermal Emission and Reflection radiometer (ASTER), and Landsat 7 data [Merlin et al, 2013]. Fang and Lakshmi [2014] disaggregated SMOS and AMSR-E data to a 1 km resolution and compared the results to in situ observations.…”

Performance Metrics for Soil Moisture Downscaling Methods: Application to DISPATCH Data in Central Morocco

“…Yet, to date, little work has focused on the strategy to assess soil moisture downscaling methods. Table 1 lists some recently published disaggregation methods [11,[13][14][15][16][17][18][19][20][21][22][23][24][25][26]. For each method, Table 1 reports the performance metrics that were used to assess the error statistics in downscaled data, whether such results were compared with those obtained at high resolution in the non-disaggregation case and the nature (spatial, temporal and/or spatio-temporal) of the comparison between disaggregated and reference (often in situ) measurements.…”

Apport de l'observation satellitaire à l'hydrologie continentale

“…Les principales limitations de Smos sont relatives à sa résolution spatiale (40 km échantillonnés à 15 ou 25 km) et sa profondeur de pénétration. Pour la première limitation, des approches de désagrégation ont été mises au point, qui permettent d'obtenir des résolutions kilométriques ou hectométriques (Merlin et al, 2013), favorisant des applications en agronomie et gestion de la ressource en eau. Pour la seconde, différentes techniques ont été développées pour estimer l'humidité dans la zone racinaire par assimilation dans des modèles de l'humidité de surface.…”