@Article{FurtadoSilvNovo:2016:DuFuC,
author = "Furtado, Luiz Felipe de Almeida and Silva, Thiago Sanna Freire and
Novo, Evlyn M{\'a}rcia Le{\~a}o de Moraes",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and
{Universidade Estadual Paulista (UNESP)} and {Instituto Nacional
de Pesquisas Espaciais (INPE)}",
title = "Dual-season and full-polarimetric C band SAR assessment for
vegetation mapping in the Amazon varzea wetlands",
journal = "Remote Sensing of Environment",
year = "2016",
volume = "174",
pages = "212--222",
month = "Mar.",
keywords = "PoISAR, Wetlands, Polarimetric decomposition, Multitemporal,
Mapping accuracy.",
abstract = "This study answered the following questions: 1) Is polarimetric
C-band SAR (PoISAR) more efficient than dual polarization
(dual-pol) C-band SAR for mapping varzea floodplain vegetation
types, when using images of a single hydrological period? 2) Are
single-season C-band PoISAR images more accurate for mapping
varzea vegetation types than dual-season dual-pol C-band SAR
images? 3) What are the most efficient polarimetric descriptors
for mapping varzea vegetation types? We applied the Random Forests
algorithm to classify dual-pol SAR images and polarimetric
descriptois derived from two full-polarimetric Radarsat-2 C-band
images acquired during the low and high water seasons of Lago
Grande de Curuai floodplain, lower Amazon, Brazil. We used the
Kappa index of agreement (kappa), Allocation Disagreement (AD) and
Quantity Disagreement (QD), and Producer's and User's accuracy
measurements to assess the classification results. Our results
showed that single-season full-polarimetric C-band data can yield
more accurate classifications than single-season dual-pol C-band
SAR imagery and similar accuracies to dual-season dual-pol C-band
SAR classifications. Still, dual season PoISAR achieved the
highest accuracies, showing that seasonality is paramount for
obtaining high accuracies in wetland land cover classification,
regardless of SAR image type. On average, single-season
classifications of low-water periods were less accurate than
high-water classifications, likely due to plant phenology and
flooding conditions. Classifications using model-based
polarimetric decompositions (such as Freeman-Durden, Yamaguchi and
van Zyl) produced the highest accuracies (kappa greater than 0.8;
AD ranging from 7.5% to 2.5%; QD ranging from 15% to 12%), while
eigenvector-based decompositions such as Touzi and Cloude-Pottier
had the worst accuracies (kappa ranging from 0.5 to 0.7; AD
greater than 10%; QD smaller than 10%). Vegetation types with
dense canopies (Shrubs, Floodable Forests and Emergent
Macrophytes), whose classification is challenging using C-band,
were accurately classified using dual-season full-polarimetric SAR
data, with Producer's and User's accuracies between 80% and 90%.
We conclude that full polarimetric C-band imagery can yield very
accurate classifications of varzea vegetation (kappa similar to
0.8, AD similar to 3% and QD similar to 10%) and can be used as an
operational tool for forested wetland mapping.",
doi = "10.1016/j.rse.2015.12.013",
url = "http://dx.doi.org/10.1016/j.rse.2015.12.013",
issn = "0034-4257",
language = "en",
targetfile = "1_furtado_dual.pdf",
urlaccessdate = "28 abr. 2024"
}