@Article{SimõesPCMSASFC:2020:LaUsCo,
author = "Sim{\~o}es, Rolf Ezequiel de Oliveira and Picoli, Michelle
Cristina Ara{\'u}jo and C{\^a}mara, Gilberto and Maciel, Adeline
Marinho and Santos, Lorena Alves dos and Andrade Neto, Pedro
Ribeiro de and Sanchez Ipia, Alber Hamersson and Ferreira, Karine
Reis and Carvalho, Alexandre",
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)} and {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)} and {Instituto de
Pesquisas Econ{\^o}micas Aplicadas (IPEA)}",
title = "Land use and cover maps for Mato Grosso State in Brazil from 2001
to 2017",
journal = "Scientific Data",
year = "2020",
volume = "7",
number = "1",
pages = "e34",
month = "Dec.",
abstract = "This paper presents a dataset of yearly land use and land cover
classification maps for Mato Grosso State, Brazil, from 2001 to
2017. Mato Grosso is one of the worlds fast moving agricultural
frontiers. To ensure multi-year compatibility, the work uses MODIS
sensor analysis-ready products and an innovative method that
applies machine learning techniques to classify satellite image
time series. The maps provide information about crop and pasture
expansion over natural vegetation, as well as spatially explicit
estimates of increases in agricultural productivity and trade-offs
between crop and pasture expansion. Therefore, the dataset
provides new and relevant information to understand the impact of
environmental policies on the expansion of tropical agriculture in
Brazil. Using such results, researchers can make informed
assessments of the interplay between production and protection
within Amazon, Cerrado, and Pantanal biomes.",
doi = "10.1038/s41597-020-0371-4",
url = "http://dx.doi.org/10.1038/s41597-020-0371-4",
issn = "2052-4436",
language = "en",
targetfile = "simoes_land.pdf",
urlaccessdate = "21 maio 2024"
}