@InProceedings{PavanelliNeveCampKort:2015:ReSeIm,
author = "Pavanelli, Jo{\~a}o Arthur Pompeu and Neves, Bruna Virginia and
Camphora, Vanessa Priscila and Korting, Thales Sehn",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de
Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas
Espaciais (INPE)}",
title = "Remote sensing image processing to identify spatial units of human
occupation along Trans-Amazonian Highway (BR-230), Brazil",
booktitle = "Proceedings...",
year = "2015",
organization = "Joint Urban Remote Sensing Event, (JURSE).",
abstract = "To investigate the urban phenomenon in the Amazon is necessary to
observe the cities and communities. Identifying these population
nuclei can provide information about where the population is
concentrated and how it relates to the space and environment,
therefore, how Amazonian urban is structured. This study
identified spatial units of human occupation along the
Trans-Amazonian Highway (BR-230) by applying remote sensing image
processing techniques. The study site is located in Par{\'a}
state, Brazil, in the municipalities of Altamira, Brasil Novo,
Medicil{\^a}ndia and Uruar{\'a}, inside a 15 km buffered from
the Highway. Four Landsat-5 Thematic Mapper orthorrectfied scenes
from 2011 were processed using software SPRING. The processing
steps consisted in mosaicking the scenes, the application of
dilation filter, segmentation and maximum likelihood
classification. The validation was based on manual classification
of middle resolution RapidEye images (5 metres) and ancillary data
from Brazilian Institute of Geography and Statistics (IBGE).
Twenty three spatial units of human occupation were mapped and the
validation showed a Kappa coefficient of 0.6785. The application
of dilation filter during the processing was able to identify
spatial units of human occupation in the study site, although some
misclassified pixels occurred mainly in small patches.",
conference-location = "Lausanne, Switzerland",
targetfile = "pavanelli_remote.pdf",
urlaccessdate = "27 abr. 2024"
}