SOYBEAN CROP AREA ESTIMATION AND MAPPING IN MATO GROSSO STATE, BRAZIL
Evaluation of the MODIS Crop Detection Algorithm (MCDA) procedure for estimating historical planted soybean crop areas was done on fields in Mato Grosso State, Brazil. MCDA is based on temporal profiles of EVI (Enhanced Vegetation Index) derived from satellite data of the MODIS (Moderate Resolution...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2012-07-01
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| Series: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/I-7/215/2012/isprsannals-I-7-215-2012.pdf |
| Summary: | Evaluation of the MODIS Crop Detection Algorithm (MCDA) procedure for estimating historical planted soybean crop areas was
done on fields in Mato Grosso State, Brazil. MCDA is based on temporal profiles of EVI (Enhanced Vegetation Index) derived from
satellite data of the MODIS (Moderate Resolution Imaging Spectroradiometer) imager, and was previously developed for soybean
area estimation in Rio Grande do Sul State, Brazil. According to the MCDA approach, in Mato Grosso soybean area estimates can be
provided in December (1<sub>st</sub> forecast), using images from the sowing period, and in February (2<sub>nd</sub> forecast), using images from sowing
and maximum crop development period. The results obtained by the MCDA were compared with Brazilian Institute of Geography
and Statistics (IBGE) official estimates of soybean area at municipal level. Coefficients of determination were between 0.93 and
0.98, indicating a good agreement, and also the suitability of MCDA to estimations performed in Mato Grosso State. On average, the
MCDA results explained 96% of the variation of the data estimated by the IBGE. In this way, MCDA calibration was able to provide
annual thematic soybean maps, forecasting the planted area in the State, with results which are comparable to the official agricultural
statistics. |
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| ISSN: | 2194-9042 2194-9050 |