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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Vegetation Characterization through the Use of Precipitation-Affected SAR Signals

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Author(s):
Molijn, Ramses A. [1] ; Iannini, Lorenzo [1] ; Dekker, Paco Lopez [1] ; Magalhaes, Paulo S. G. [2] ; Hanssen, Ramon F. [2]
Total Authors: 5
Affiliation:
[1] Delft Univ Technol, Geosci & Remote Sensing, NL-2628 CN Delft - Netherlands
[2] Univ Estadual Campinas, Fac Engn Agr FEAGRI, BR-13083875 Campinas, SP - Brazil
Total Affiliations: 2
Document type: Journal article
Source: REMOTE SENSING; v. 10, n. 10 OCT 2018.
Web of Science Citations: 3
Abstract

Current space-based SAR offers unique opportunities to classify vegetation types and to monitor vegetation growth due to its frequent acquisitions and its sensitivity to vegetation geometry. However, SAR signals also experience frequent temporal fluctuations caused by precipitation events, complicating the mapping and monitoring of vegetation. In this paper, we show that the influence of a priori known precipitation events on the signals can be used advantageously for the classification of vegetation conditions. For this, we exploit the change in Sentinel-1 backscatter response between consecutive acquisitions under varying wetness conditions, which we show is dependent on the state of vegetation. The performance further improves when a priori information on the soil type is taken into account. (AU)

FAPESP's process: 13/50943-9 - Improved space-based remote sensing for land use mapping: towards a sustainable expansion of the bioethanol sector in Brazil
Grantee:Rubens Augusto Camargo Lamparelli
Support Opportunities: Program for Research on Bioenergy (BIOEN) - Regular Program Grants