The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLVI-4/W2-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4/W2-2021, 167–174, 2021
https://doi.org/10.5194/isprs-archives-XLVI-4-W2-2021-167-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4/W2-2021, 167–174, 2021
https://doi.org/10.5194/isprs-archives-XLVI-4-W2-2021-167-2021

  19 Aug 2021

19 Aug 2021

ON THE FEASIBILITY OF APPLYING ORBITAL CORRECTIONS TO SAOCOM-1 DATA WITH FREE OPEN SOURCE SOFTWARE (FOSS) TO GENERATE DIGITAL SURFACE MODELS: A CASE STUDY IN ARGENTINA

S. A. Seppi1, E. A. Solarte Casanova2,5, Y. L. B. Roa3,5, L. Euillades3,5, and M. Gaute4 S. A. Seppi et al.
  • 1Instituto de Altos Estudios Espaciales Mario Gulich, Falda del Cañete, Córdoba, Argentina
  • 2Departamento de Geología Aplicada, Facultad de Ciencias Exactas Físicas y Naturales, Universidad Nacional de Córdoba, Argentina
  • 3Instituto CEDIAC, Facultad de Ingeniería, Universidad Nacional de Cuyo, Argentina
  • 4Ministerio de Agricultura, Ganadería y Pesca, Buenos Aires, Argentina
  • 5Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina

Keywords: SAOCOM-1, Forest Plantations, SAR Interferometry, Orbital Corrections, FOSS, Digital Surface Model (DSM)

Abstract. In this work we present an orbital correction workflow developed with FOSS tools to compensate for orbital errors present in Synthetic Aperture Radar (SAR) interferograms. The technique is tested in forested areas in Argentina, using full polarimetric images from the argentinean SAR constellation SAOCOM-1 (Satélite Argentino Con Microondas). The results are contrasted with field measurements of canopy height provided by local producers, and the results show that the Root Mean Square Error (RMSE) of the satellite measurements is significantly reduced after the orbital correction. Moreover, forest plantation become more distinguishable in the retrieved Digital Surface Models, especially in those pairs with larger spatial baseline. A section of this article is also dedicated to the discussion on which are the best parameters to run the module, and how different configurations can affect the result.