@Article{MartinsSantGalvMaga:2016:SeALIm,
author = "Martins, Flora da Silva Ramos Vieira and Santos, Jo{\~a}o Roberto
dos and Galv{\~a}o, L{\^e}nio Soares and Magalh{\~a}es, Xaud.
Haron Abrahim",
affiliation = "Funda{\c{c}}{\~a}o de Ci{\^e}ncia, Aplica{\c{c}}{\~o}es e
Tecnologia Espaciais (FUNCATE) and {Instituto Nacional de
Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas
Espaciais (INPE)} and {Empresa Brasileira de Pesquisa
Agropecu{\'a}ria - Roraima (Embrapa)}",
title = "Sensitivity of ALOS/PALSAR imagery to forest degradation by fire
in northern Amazon",
journal = "International Journal of Applied Earth Observation and
Geoinformation",
year = "2016",
volume = "49",
pages = "163--174",
month = "July",
keywords = "Amazon, Aboveground biomass, Forest fire, L-band, ALOS/PALSAR,
Polarimetric response.",
abstract = "We evaluated the sensitivity of the full polarimetric Phased Array
type L-band Synthetic Aperture Radar (PALSAR), onboard the
Advanced Land Observing Satellite (ALOS), to forest degradation
caused by fires in northern Amazon, Brazil. We searched for
changes in PALSAR signal and tri-dimensional polarimetric
responses for different classes of fire disturbance defined by
fire frequency and severity. Since the above-ground biomass (AGB)
is affected by fire, multiple regression models to estimate AGB
were obtained for the whole set of coherent and incoherent
attributes (general model) and for each set separately (specific
models). The results showed that the polarimetric L-band PALSAR
attributes were sensitive to variations in canopy structure and
AGB caused by forest fire. However, except for the unburned and
thrice burned classes, no single PALSAR attribute was able to
discriminate between the intermediate classes of forest
degradation by fire. Both the coherent and incoherent polarimetric
attributes were important to explain AGB variations in tropical
forests affected by fire. The HV backscattering coefficient,
anisotropy, double-bounce component, orientation angle, volume
index and HH-VV phase difference were PALSAR attributes selected
from multiple regression analysis to estimate AGB. The general
regression model, combining phase and power radar metrics,
presented better results than specific models using coherent or
incoherent attributes. The polarimetric responses indicated the
dominance of VV-oriented backscattering in primary forest and
lightly burned forests. The HH-oriented backscattering
predominated in heavily and frequently burned forests. The results
suggested a greater contribution of horizontally arranged
constituents such as fallen trunks or branches in areas severely
affected by fire. (C) 2016 Elsevier B.V. All rights reserved.",
doi = "10.1016/j.jag.2016.02.009",
url = "http://dx.doi.org/10.1016/j.jag.2016.02.009",
issn = "0303-2434",
language = "en",
targetfile = "martins_sensitivity.pdf",
urlaccessdate = "15 jun. 2024"
}