@InProceedings{Bayma-SilvaTeixLeiv:2017:EsPaBi,
author = "Bayma-Silva, Gustavo and Teixeira, Antonio Heriberto de Castro and
Leivas, Janice Freitas",
title = "Estimativa de par{\^a}metros biof{\'{\i}}sicos no bioma Cerrado
do Estado de Minas Gerais",
booktitle = "Anais...",
year = "2017",
editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz
Eduardo Oliveira e Cruz de",
pages = "3703--3710",
organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 18. (SBSR)",
publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
address = "S{\~a}o Jos{\'e} dos Campos",
abstract = "Natural habitats decrease in extension and integrity may be
considered as an indicator of biodiversity decay. Land-use and
land-cover changes (LULCC), original ecosystems conversion to
other anthropic uses, have direct effects on biodiversity and
climate. The Cerrado biome extends over approximately 2,000,000
km2 and between 2002 and 2013 nearly 126,000 kmē of its natural
plant cover was suppressed (-10.7%), 11.4 thousand kmē year-1. The
Simple Algorithm for Evapotranspiration Retrieving (SAFER) is an
agrometeorological spectral model for estimating large-scale
biophysical parameters using satellite images and climate data
interpolated from meteorological stations. SAFER does not require
the use of the thermal band. The SAFER model was used to estimate
biophysical parameters in anthropic and natural land-use classes
in a portion of the Brazilian state of Minas Gerais which is
covered by Cerrado vegetation. Our results show silviculture as
the anthropic land-use class with the highest biomass (146 kg ha-1
day-1) and ET (3.3 mm day-1) values. Among the natural plant-cover
classes, the highest values were estimated for forest (85.8 kg
ha-1 day-1 and 2.4 mm day-1). We recommend that future studies
apply the SAFER model to medium spatial resolution images (e.g.
Landsat-8, Sentinel-2) with the aim of estimating parameters in a
more detailed scale.",
conference-location = "Santos",
conference-year = "28-31 maio 2017",
isbn = "978-85-17-00088-1",
label = "59859",
language = "pt",
organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
ibi = "8JMKD3MGP6W34M/3PSLTDR",
url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSLTDR",
targetfile = "59859.pdf",
type = "Monitoramento e modelagem ambiental",
urlaccessdate = "27 abr. 2024"
}