Assessing the MODIS Crop Detection Algorithm for Soybean Crop Area Mapping and Expansion in the Mato Grosso State, Brazil
Joint Authors
Veronez, Mauricio Roberto
Jr, Luiz Gonzaga
Gusso, Anibal
Arvor, Damien
Ricardo Ducati, Jorge
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-04-10
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
Estimations of crop area were made based on the temporal profiles of the Enhanced Vegetation Index (EVI) obtained from moderate resolution imaging spectroradiometer (MODIS) images.
Evaluation of the ability of the MODIS crop detection algorithm (MCDA) to estimate soybean crop areas was performed for fields in the Mato Grosso state, Brazil.
Using the MCDA approach, soybean crop area estimations can be provided for December (first forecast) using images from the sowing period and for February (second forecast) using images from the sowing period and the maximum crop development period.
The area estimates were compared to official agricultural statistics from the Brazilian Institute of Geography and Statistics (IBGE) and from the National Company of Food Supply (CONAB) at different crop levels from 2000/2001 to 2010/2011.
At the municipality level, the estimates were highly correlated, with R2=0.97 and RMSD = 13,142 ha.
The MCDA was validated using field campaign data from the 2006/2007 crop year.
The overall map accuracy was 88.25%, and the Kappa Index of Agreement was 0.765.
By using pre-defined parameters, MCDA is able to provide the evolution of annual soybean maps, forecast of soybean cropping areas, and the crop area expansion in the Mato Grosso state.
American Psychological Association (APA)
Gusso, Anibal& Arvor, Damien& Ricardo Ducati, Jorge& Veronez, Mauricio Roberto& Jr, Luiz Gonzaga. 2014. Assessing the MODIS Crop Detection Algorithm for Soybean Crop Area Mapping and Expansion in the Mato Grosso State, Brazil. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1051393
Modern Language Association (MLA)
Gusso, Anibal…[et al.]. Assessing the MODIS Crop Detection Algorithm for Soybean Crop Area Mapping and Expansion in the Mato Grosso State, Brazil. The Scientific World Journal No. 2014 (2014), pp.1-9.
https://search.emarefa.net/detail/BIM-1051393
American Medical Association (AMA)
Gusso, Anibal& Arvor, Damien& Ricardo Ducati, Jorge& Veronez, Mauricio Roberto& Jr, Luiz Gonzaga. Assessing the MODIS Crop Detection Algorithm for Soybean Crop Area Mapping and Expansion in the Mato Grosso State, Brazil. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1051393
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1051393