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

Bibliographic Details
Main Author: De Souza Filho C.R.
Publication Date: 2016
Other Authors: Gloaguen R., Liesenberg, Veraldo
Format: Article
Language: eng
Source: Repositório Institucional da Udesc
dARK ID: ark:/33523/0013000005vj9
Download full: https://repositorio.udesc.br/handle/UDESC/7369
Summary: © 2016 IEEE.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.
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spelling Evaluating Moisture and Geometry Effects on L-Band SAR Classification Performance Over a Tropical Rain Forest Environment© 2016 IEEE.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.2024-12-06T13:40:39Z2016info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlep. 5357 - 53682151-153510.1109/JSTARS.2016.2617120https://repositorio.udesc.br/handle/UDESC/7369ark:/33523/0013000005vj9IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing912De Souza Filho C.R.Gloaguen R.Liesenberg, Veraldoengreponame:Repositório Institucional da Udescinstname:Universidade do Estado de Santa Catarina (UDESC)instacron:UDESCinfo:eu-repo/semantics/openAccess2024-12-07T20:53:59Zoai:repositorio.udesc.br:UDESC/7369Biblioteca Digital de Teses e Dissertaçõeshttps://pergamumweb.udesc.br/biblioteca/index.phpPRIhttps://repositorio-api.udesc.br/server/oai/requestri@udesc.bropendoar:63912024-12-07T20:53:59Repositório Institucional da Udesc - Universidade do Estado de Santa Catarina (UDESC)false
dc.title.none.fl_str_mv Evaluating Moisture and Geometry Effects on L-Band SAR Classification Performance Over a Tropical Rain Forest Environment
title Evaluating Moisture and Geometry Effects on L-Band SAR Classification Performance Over a Tropical Rain Forest Environment
spellingShingle Evaluating Moisture and Geometry Effects on L-Band SAR Classification Performance Over a Tropical Rain Forest Environment
De Souza Filho C.R.
title_short Evaluating Moisture and Geometry Effects on L-Band SAR Classification Performance Over a Tropical Rain Forest Environment
title_full Evaluating Moisture and Geometry Effects on L-Band SAR Classification Performance Over a Tropical Rain Forest Environment
title_fullStr Evaluating Moisture and Geometry Effects on L-Band SAR Classification Performance Over a Tropical Rain Forest Environment
title_full_unstemmed Evaluating Moisture and Geometry Effects on L-Band SAR Classification Performance Over a Tropical Rain Forest Environment
title_sort Evaluating Moisture and Geometry Effects on L-Band SAR Classification Performance Over a Tropical Rain Forest Environment
author De Souza Filho C.R.
author_facet De Souza Filho C.R.
Gloaguen R.
Liesenberg, Veraldo
author_role author
author2 Gloaguen R.
Liesenberg, Veraldo
author2_role author
author
dc.contributor.author.fl_str_mv De Souza Filho C.R.
Gloaguen R.
Liesenberg, Veraldo
description © 2016 IEEE.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.
publishDate 2016
dc.date.none.fl_str_mv 2016
2024-12-06T13:40:39Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv 2151-1535
10.1109/JSTARS.2016.2617120
https://repositorio.udesc.br/handle/UDESC/7369
dc.identifier.dark.fl_str_mv ark:/33523/0013000005vj9
identifier_str_mv 2151-1535
10.1109/JSTARS.2016.2617120
ark:/33523/0013000005vj9
url https://repositorio.udesc.br/handle/UDESC/7369
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
9
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dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv p. 5357 - 5368
dc.source.none.fl_str_mv reponame:Repositório Institucional da Udesc
instname:Universidade do Estado de Santa Catarina (UDESC)
instacron:UDESC
instname_str Universidade do Estado de Santa Catarina (UDESC)
instacron_str UDESC
institution UDESC
reponame_str Repositório Institucional da Udesc
collection Repositório Institucional da Udesc
repository.name.fl_str_mv Repositório Institucional da Udesc - Universidade do Estado de Santa Catarina (UDESC)
repository.mail.fl_str_mv ri@udesc.br
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