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Remote Sens. 2016, 8(1), 22; doi:10.3390/rs8010022

Mapping Fractional Cropland Distribution in Mato Grosso, Brazil Using Time Series MODIS Enhanced Vegetation Index and Landsat Thematic Mapper Data

1
Department of Geography and Environment, Jiangsu Normal University, Xuzhou 221116, China
2
Center for Global Change and Earth Observations, Michigan State University, East Lansing, MI 48823, USA
3
Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration of Zhejiang Province, School of Environmental & Resource Sciences, Zhejiang A&F University, Lin An 311300, China
4
Brazilian Agricultural Research Corporation—Embrapa, Campinas, SP 13070, Brazil
5
National Institute for Space Research—INPE, São Jose dos Campos, SP 12245, Brazil
*
Author to whom correspondence should be addressed.
Academic Editors: Yoshio Inoue and Prasad S. Thenkabail
Received: 22 October 2015 / Revised: 10 December 2015 / Accepted: 21 December 2015 / Published: 30 December 2015
View Full-Text   |   Download PDF [5407 KB, uploaded 30 December 2015]   |  

Abstract

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. View Full-Text
Keywords: seasonal dynamic index; crop phenology analysis; fractional cropland distribution; MODIS EVI; Landsat; Mato Grosso seasonal dynamic index; crop phenology analysis; fractional cropland distribution; MODIS EVI; Landsat; Mato Grosso
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Zhu, C.; Lu, D.; Victoria, D.; Dutra, L.V. Mapping Fractional Cropland Distribution in Mato Grosso, Brazil Using Time Series MODIS Enhanced Vegetation Index and Landsat Thematic Mapper Data. Remote Sens. 2016, 8, 22.

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