Título:	Mapping Fractional Cropland Distribution in Mato Grosso, Brazil Using Time Series MODIS Enhanced Vegetation Index and Landsat Thematic Mapper Data.
Autoria:	ZHU, C. LU, D. VICTORIA, D. de C. DUTRA, L. V.
Afiliação:	CHANGMING ZHU, JIANGSU NORMAL UNIVERSITY/MICHIGAN STATE UNIVERSITY; DENGSHENG LU, MICHIGAN STATE UNIVERSITY; DANIEL DE CASTRO VICTORIA, CNPM; LUCIANO VIEIRA DUTRA, INPE.
Ano de publicação:	2016
Referência:	Remote Sensing, v. 8, n. 22, p. 1-14, 2016.
Conteúdo:	Mapping cropland distribution over large areas has attracted great attention in recent years, however, traditional pixel-based classification approaches produce high uncertainty in cropland area statistics. This study proposes a new approach to map fractional cropland distribution in Mato Grosso, Brazil using time series MODIS enhanced vegetation index (EVI) and Landsat Thematic Mapper (TM) data. The major steps include: (1) remove noise and clouds/shadows contamination using the Savizky?Gloay filter and temporal resampling algorithm based on the time series MODIS EVI data; (2) identify the best periods to extract croplands through crop phenology analysis; (3) develop a seasonal dynamic index (SDI) from the time series MODIS EVI data based on three key stages: sowing, growing, and harvest; and (4) develop a regression model to estimate cropland fraction based on the relationship between SDI and Landsat-derived fractional cropland data. The root mean squared error of 0.14 was obtained based on the analysis of randomly selected 500 sample plots. This research shows that the proposed approach is promising for rapidly mapping fractional cropland distribution in Mato Grosso, Brazil.
NAL Thesaurus:	Landsat
Palavras-chave:	Seasonal dynamic index Crop phenology analysis Fractional cropland distribution Mato Grosso MODIS EVI
Digital Object Identifier:	10.3390/rs8010022
Tipo do material:	Artigo de periódico
Acesso:	openAccess
Aparece nas coleções:	Artigo em periódico indexado (CNPM)