Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/346557
Type: Artigo
Title: Vegetation characterization through the use of precipitation-affected SAR signals
Author: Molijn, Ramses A.
Iannini, Lorenzo
Dekker, Paco López
Magalhães, Paulo S. G.
Hanssen, Ramon F.
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.
Subject: Precipitação (Meteorologia)
Vegetação e clima
Country: Suíça
Editor: MDPI
Rights: Aberto
Identifier DOI: 10.3390/rs10101647
Address: https://www.mdpi.com/2072-4292/10/10/1647/htm
Date Issue: 2018
Appears in Collections:FEAGRI - Artigos e Outros Documentos

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