Individuazione automatica di aree coltivate a riso da serie temporale MODIS: primi risultati in ambiente mediterraneo

Rice is one of the most important crops all over the world and it represents the staple food for more than half of the human population. One fifth of the world's population, more than a billion people, depend on rice cultivation for their livelihoods. Asia, where about 90% of rice is grown, has more than 200 million rice farms (IRRI). Even in Europe rice is cultivated and Italy holds the primacy in the production representing an important farming activity. Rice is unique because it can grow in wet environments and on flooded fields that other crops cannot survive in. This feature is very important because the base of the study is to take advantage of the physic behavior of water for detecting flooding in the paddy rice fields. In this study we tested the approach given by Xiao et al. (2005) as it is, verifying the adaptability in a Mediterranean environment. By using MODIS (Moderate Resolution Imaging Spectroradiometer) imagery of 2006 (46 of 8-days composite images) a number of vegetation indices (NDVI-EVI-LSWI) has been calculated for rice detection in the main rice district in the northern Italy situated between Lombardia and Piemonte. The accuracy at ground level of the derived rice map has been evaluated by using a European Land cover map, the Corine-land cover of 2006 (CLC06), and statistically calculated. After which by modifying the methodology in order to adapt it to the temperate climatic conditions and Italian agronomic techniques, the accuracy of the newest derived maps has been analyzed and compared. The result of this study shows if the MODIS-based paddy rice mapping algorithm could potentially be applied in the Mediterranean environment as it is or if some calibrations are needed.