Validation Strategies for Satellite-Based Soil Moisture Products Over Argentine Pampas

Publicado en IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , v. 8(8):4094-4105 
Autores

Grings, F., Bruscantini, C.A., Smucler, E., Carballo, F., Dillon, M.E., Collini, E.A., Salvia, M. and Karszenbaum, H.
Año de publicación 2015
DOI https://doi.org/10.1109/JSTARS.2015.2449237
Afiliaciones
  • Instituto de Astronomía y Física del Espacio (IAFE), CONICET-UBA
  • Institute of Astronomy and Space Physics, Quantitative Remote Sensing Group, Buenos Aires, Argentina
  • Quantitative Remote Sensing Group, Institute of Astronomy and Space Physics (IAFE), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) and University of Buenos Aires, Buenos Aires, Argentina
  • Quantitative Remote Sensing Group, Institute of Astronomy and Space Physics (IAFE), University of Buenos, Aires, Buenos Aires 1428, Argentina
  • Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) and Servicio Meteorológico Nacional (SMN), Buenos Aires, Argentina
  • Servicio de Hidrografia Naval (SHN) and Servicio Meteorológico Nacional (SMN), Buenos Aires, Argentina
  • Quantitative Remote Sensing Group, Institute of Astronomy and Space Physics (IAFE), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) and University of Buenos Aires, Buenos Aires, Argentina
  • Quantitative Remote Sensing Group, Institute of Astronomy and Space Physics (IAFE), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) and University of Buenos Aires, Buenos Aires, Argentina
Programa

CRN3
Proyecto CRN3035
Keywords
Cropland
passive microwaves
soil moisture
validation strategies

Abstract

In this paper, an evaluation strategy for twocandidate satellite-derived SM products is presented. In particular, we analyze the performance of two candidate algorithms
[soil moisture ocean salinity (SMOS)-based soil moisture (SM) and advanced scatterometer (ASCAT)-based SM] to monitor SM in Pampas Plain. The difficulties associated with commonly used evaluation techniques are addressed, and techniques that do not require ground-based observations are presented. In particular, we introduce comparisons with a land-surface model (GLDAS) and SM anomalies and triple collocation analyses. Then, we discuss the relevance of these analyses in the context of end-users requirements, and propose an extreme events-detection analysis
based on anomalies of the standardized precipitation index (SPI) and satellite-based SM anomalies. The results show that: 1) both ASCAT and SMOS spatial anomalies data are able to reproduce the expected SM spatial patterns of the area 2) both ASCAT and
SMOS temporal anomalies are able to follow the measured in situ SM temporal anomalies and 3) both products were able to monitor large SPI extremes at specific vegetation conditions.