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New microwave-based missions applications for rainfed crops characterization

Authors :
N. Sánchez
J. M. Lopez-Sanchez
B. Arias-Pérez
R. Valcarce-Diñeiro
J. Martínez-Fernández
J. M. Calvo-Heras
A. Camps
A. González-Zamora
F. Vicente-Guijalba
Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
Universitat Politècnica de Catalunya. RSLAB - Grup de Recerca en Teledetecció
Source :
UPCommons. Portal del coneixement obert de la UPC, Universitat Politècnica de Catalunya (UPC), Recercat. Dipósit de la Recerca de Catalunya, instname, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLI-B1, Pp 101-107 (2016)
Publication Year :
2016
Publisher :
International Society for Photogrammetry and Remote Sensing (ISPRS), 2016.

Abstract

A multi-temporal/multi-sensor field experiment was conducted within the Soil Moisture Measurement Stations Network of the University of Salamanca (REMEDHUS) in Spain, in order to retrieve useful information from satellite Synthetic Aperture Radar (SAR) and upcoming Global Navigation Satellite Systems Reflectometry (GNSS-R) missions. The objective of the experiment was first to identify which radar observables are most sensitive to the development of crops, and then to define which crop parameters the most affect the radar signal. A wide set of radar variables (backscattering coefficients and polarimetric indicators) acquired by Radarsat-2 were analyzed and then exploited to determine variables characterizing the crops. Field measurements were fortnightly taken at seven cereals plots between February and July, 2015. This work also tried to optimize the crop characterization through Landsat-8 estimations, testing and validating parameters such as the leaf area index, the fraction of vegetation cover and the vegetation water content, among others. Some of these parameters showed significant and relevant correlation with the Landsat-derived Normalized Difference Vegetation Index (R>0.60). Regarding the radar observables, the parameters the best characterized were biomass and height, which may be explored for inversion using SAR data as an input. Moreover, the differences in the correlations found for the different crops under study types suggested a way to a feasible classification of crops.

Details

Language :
English
ISSN :
21949034
Database :
OpenAIRE
Journal :
UPCommons. Portal del coneixement obert de la UPC, Universitat Politècnica de Catalunya (UPC), Recercat. Dipósit de la Recerca de Catalunya, instname, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLI-B1, Pp 101-107 (2016)
Accession number :
edsair.doi.dedup.....7fee8b680a0fad6d45dca9449b9457cf
Full Text :
https://doi.org/10.5194/isprsarchives-XLI-B1-101-2016