Title:	A confiabilidade do PRODES: estimativa da acurácia do mapeamento do desmatamento no estado Mato Grosso.
Authors:	ADAMI, M. GOMES, A. R. BELUZZO, A. COELHO, A. dos S. VALERIANO, D. de M. RAMOS, F. de S. NARVAES, I. da S. BROWN, I. F. OLIVEIRA, I. D. de SANTOS, L. B. MAURANO, L. E. P. WATRIN, O. dos S. GRAÇA, P. M. L. de A.
Affiliation:	MARCOS ADAMI, INSTITUTO NACIONAL DE PESQUISAS ESPACIAIS ALESSANDRA RODRIGUES GOMES, INSTITUTO NACIONAL DE PESQUISAS ESPACIAIS AMANDA BELUZZO ANDREA DOS SANTOS COELHO, INSTITUTO NACIONAL DE PESQUISAS ESPACIAIS DALTON DE MORISSON VALERIANO, INSTITUTO NACIONAL DE PESQUISAS ESPACIAIS FELIPE DE SOUZA RAMOS, INSTITUTO NACIONAL DE PESQUISAS DA AMAZÔNIA IGOR DA SILVA NARVAES, INSTITUTO NACIONAL DE PESQUISAS ESPACIAIS IRVIN FOSTER BROWN, UNIVERSIDADE FEDERAL DO ACRE IVANILSON DIAS DE OLIVEIRA, UNIVERSIDADE FEDERAL DO ACRE LUCYANA BARROS SANTOS, INSTITUTO NACIONAL DE PESQUISAS ESPACIAIS LUIS EDUARDO P. MAURANO, INSTITUTO NACIONAL DE PESQUISAS ESPACIAIS ORLANDO DOS SANTOS WATRIN, CPATU PAULO MAURÍCIO LIMA DE ALENCASTRO GRAÇA, INSTITUTO NACIONAL DE PESQUISAS DA AMAZÔNIA.
Date Issued:	2017
Citation:	In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 18., 2017, Santos. Anais... São José dos Campos: INPE, 2017.
Pages:	p. 4189-4196.
Description:	PRODES is completing almost thirty years of uninterrupted monitoring of clear-cut deforestation over the Brazilian Amazon. Until now, no estimate of its mapping accuracy has been made. In this sense, this article brings a first approximation of mapping accuracy estimation of PRODES deforested areas, taking as example the state of Mato Grosso for the year 2014. For this, a random sampling panel was constructed, stratified with two strata, the deforestation of 2014 and the remaining forest. The sample size was calculated using the binomial function. In addition, a web platform was built to evaluate the points drawn by three independent evaluators. The global accuracy of the mapping of deforestation for the state of Mato Grosso, for the year 2014 was 94.5%, and may vary between 92.4% and 96.5%, in the evaluated scenario there was no class discordance to be found. Regarding the Forest class, the user accuracy was 90.5% and the producer's accuracy was 88.4%, this imbalance between user accuracy and producer accuracy indicates that there is a tendency for the forest class area to be underestimated for this mapping, in this year.
Thesagro:	Desmatamento
Keywords:	Acurácia
Type of Material:	Artigo em anais e proceedings
Access:	openAccess
Appears in Collections:	Artigo em anais de congresso (CPATU)