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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.)

Evaluating Moisture and Geometry Effects on L-Band SAR Classification Performance Over a Tropical Rain Forest Environment

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Author(s):
Liesenberg, Veraldo ; de Souza Filho, Carlos Roberto ; Gloaguen, Richard
Total Authors: 3
Document type: Journal article
Source: IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING; v. 9, n. 12, 1, SI, p. 5357-5368, DEC 2016.
Web of Science Citations: 6
Abstract

Multitemporal single (HH) and dual-polarization (i.e., HH, HV) L-band spaceborne synthetic aperture radar (SAR) scenes were evaluated under different moisture conditions caused by precipitation prior to data acquisition at varying incidence angles. The changes affecting backscattering intensity, polarimetric decomposition, backscattering mechanism, and land use/land cover classification performance were evaluated. The study area is a shifting-cultivation environment in the eastern Amazon (Brazil). Several data input scenarios were proposed in the classification scheme (i.e., backscattering intensity alone and combined with alpha/entropy decomposition parameters, band ratios, and textural parameters) using a random forest classifier framework. Integration with optical data was also examined. The classification accuracy scores were then compared with accumulated precipitation data. The results showed that the variation in both the vegetation moisture and incidence angle increases the backscattering intensity for pasture, riparian forest and young regenerated forest by at least 1 dB compared with old successional forest stages due to its more uniform vertical structure and the landscape's increased dielectric constant. The overall classification accuracy proved low for each SAR acquisition date compared with the performance of the Landsat data. Based on SAR data, misclassification occurs for the young successional forest stages and increases in scenes with higher moisture conditions. The classification performance benefits from data integration only for one SAR scene acquired in the dry season. The results highlight the importance of selecting proper temporal intervals for the different SAR polarization modes of the forthcoming SAR missions. Further investigations should address both multitemporal at a single frequency as well as multifrequency SAR approaches. (AU)

FAPESP's process: 13/05081-9 - CHARACTERIZING SECONDARY FOREST STAGES IN DIFFERENT TROPICAL RAIN FOREST ENVIRONMENTS UNDER THE RECENT REDD+ PROTOCOLS: AN ATTEMPT WITH MULTIPLE SOURCES OF REMOTE SENSING DATA
Grantee:Veraldo Liesenberg
Support type: Scholarships in Brazil - Post-Doctorate