@Article{BarbozaCastilloTASRSBOE:2020:MoWiNo,
author = "Barboza Castillo, Elgar and Turpo Cayo, Efrain Yury and Almeida,
Cl{\'a}udia Maria de and Salas L{\'o}pez, Rolando and Rojas
Briceņo, Nilton Beltr{\'a}n and Silva L{\'o}pez, Jhonsy Omar and
Barrena Gurbill{\'o}n, Miguel {\'A}ngel and Oliva, Manuel and
Espinoza-Villar, Raul",
affiliation = "{Universidad Nacional Toribio Rodr{\'{\i}}guez de Mendoza de
Amazonas (UNTRM)} and {Universidad Nacional Agraria La Molina} and
{Instituto Nacional de Pesquisas Espaciais (INPE)} and
{Universidad Nacional Toribio Rodr{\'{\i}}guez de Mendoza de
Amazonas (UNTRM)} and {Universidad Nacional Toribio
Rodr{\'{\i}}guez de Mendoza de Amazonas (UNTRM)} and
{Universidad Nacional Toribio Rodr{\'{\i}}guez de Mendoza de
Amazonas (UNTRM)} and {Universidad Nacional Toribio
Rodr{\'{\i}}guez de Mendoza de Amazonas (UNTRM)} and
{Universidad Nacional Toribio Rodr{\'{\i}}guez de Mendoza de
Amazonas (UNTRM)} and {Universidad Nacional Agraria La Molina}",
title = "Monitoring wildfires in the northeastern peruvian amazon using
landsat-8 and sentinel-2 imagery in the GEE platform",
journal = "ISPRS International Journal of Geo-Information",
year = "2020",
volume = "9",
number = "10",
pages = "e564",
month = "Oct.",
note = "{Pr{\^e}mio CAPES Elsevier 2023 - ODS 8: Trabalho decente e
crescimento econ{\^o}mico}",
keywords = "remote sensing, GIS, spectral analysis, burn severity, forests,
vegetation cover, biodiversity.",
abstract = "During the latest decades, the Amazon has experienced a great loss
of vegetation cover, in many cases as a direct consequence of
wildfires, which became a problem at local, national, and global
scales, leading to economic, social, and environmental impacts.
Hence, this study is committed to developing a routine for
monitoring fires in the vegetation cover relying on recent
multitemporal data (20172019) of Landsat-8 and Sentinel-2 imagery
using the cloud-based Google Earth Engine (GEE) platform. In order
to assess the burnt areas (BA), spectral indices were employed,
such as the Normalized Burn Ratio (NBR), Normalized Burn Ratio 2
(NBR2), and Mid-Infrared Burn Index (MIRBI). All these indices
were applied for BA assessment according to appropriate
thresholds. Additionally, to reduce confusion between burnt areas
and other land cover classes, further indices were used, like
those considering the temporal differences between pre and
post-fire conditions: differential Mid-Infrared Burn Index
(dMIRBI), differential Normalized Burn Ratio (dNBR), differential
Normalized Burn Ratio 2 (dNBR2), and differential Near-Infrared
(dNIR). The calculated BA by Sentinel-2 was larger during the
three-year investigation span (16.55, 78.50, and 67.19 km2 ) and
of greater detail (detected small areas) than the BA extracted by
Landsat-8 (16.39, 6.24, and 32.93 km2 ). The routine for
monitoring wildfires presented in this work is based on a sequence
of decision rules. This enables the detection and monitoring of
burnt vegetation cover and has been originally applied to an
experiment in the northeastern Peruvian Amazon. The results
obtained by the two satellites imagery are compared in terms of
accuracy metrics and level of detail (size of BA patches). The
accuracy for Landsat-8 and Sentinel-2 in 2017, 2018, and 2019
varied from 82.791.4% to 94.598.5%, respectively.",
doi = "10.3390/ijgi9100564",
url = "http://dx.doi.org/10.3390/ijgi9100564",
issn = "2220-9964",
label = "self-archiving-INPE-MCTIC-GOV-BR",
language = "en",
targetfile = "castillo-monitoring.pdf",
urlaccessdate = "28 abr. 2024"
}