NDLI: Data Mining, A Promising Tool for Large-Area Cropland Mapping

Content Provider	IEEE Xplore Digital Library
Author	Vintrou, E. Ienco, D. Begue, A. Teisseire, M.
Copyright Year	2008
Abstract	The northern fringe of sub-Saharan Africa is a region that is considered to be particularly vulnerable to climate variability and change, and it is a location in which food security remains a major challenge. To address these issues, it is essential to develop global data sets of the geographic distribution of agricultural land use. The objectives of this study were to test an original data mining approach for classifying and mapping the cropped land in West Africa using coarse-resolution imagery and to compare the classification results with those obtained from a classic ISODATA approach. The data mining approach is able to handle large volumes of data and is based on different descriptors (65) of the land use, including the spatial and temporal satellite-derived metrics of 12 MODIS NDVI 16-day composite images and the static attributes taken from field surveys. The classic ISODATA method showed that 68.3% of pixels from a SPOT reference map were correctly classified in three validation sites versus 57.8% for the data mining approach. Validation by field observations showed equivalent results for both methods with an F-score of 0.72. The results of this study demonstrated the relevance of the use of data-mining tools for large-area monitoring.
Starting Page	2132
Ending Page	2138
Page Count	7
File Size	684838
File Format	PDF
ISSN	19391404
Volume Number	6
Issue Number	5
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-01-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data mining Agriculture Remote sensing MODIS Accuracy Earth West Africa Cropland data mining food security large-scale MODIS time series
Content Type	Text
Resource Type	Article
Subject	Atmospheric Science Computers in Earth Sciences

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