Abstract
To predict and respond to famine and other forms of food insecurity, different early warning systems are using remote analyses of crop condition and agricultural production by using satellite-based information. To improve these predictions, a reliable estimation of the cultivated area at a national scale must be carried out. In this study, we developed a data mining methodology for extracting cultivated domain patterns based on their temporal behavior as captured in time-series of moderate resolution remote sensing MODIS images.
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Pitarch, Y., Vintrou, E., Badra, F., Bégué, A., Teisseire, M. (2011). Mining Sequential Patterns from MODIS Time Series for Cultivated Area Mapping. In: Geertman, S., Reinhardt, W., Toppen, F. (eds) Advancing Geoinformation Science for a Changing World. Lecture Notes in Geoinformation and Cartography(), vol 1. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19789-5_3
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DOI: https://doi.org/10.1007/978-3-642-19789-5_3
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