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Mapping of cropped areas is very important for crop monitoring, irrigation water management, as well as yield estimation and forecasting. However, for large irri-gation schemes such as Gezira (880,000 ha), mapping of cropped area using classical approach based on ground information becomes complex and prohibitively expen-sive. In many cases the accuracy depends very much on reliability of the ground monitoring system. Assessment of cropped area using remote sensing and GIS tech-niques is emerging as a potential methodology in this field.
The objectives of this study are to:
1. Determine the cultivated and non-cultivated area in Gezira Scheme from Feb, 2016 to March 2017.
2. Map crop types throughout the growing seasons in Gezira Scheme (winter/rainy sea-sons).
The methodology include the following:
1. Acquisition of the satellite data (2 scenes/month).
2. Field survey for collecting the training areas (signatures) .
3. Image processing.
4. Land-use/land-cover (LULC) maps .
5. Accuracy assessment (compare results obtained by satellite with the Office one).
Maximum likelihood classification :
Five Blocks were selected to implement the experi-ment and perform the field investigations. Landsat-8 satellite data were used for mapping the cropped area in GS. For that, a supervised classification was em-ployed to identify the LULC classes within the GS. This was applied through two methods, namely: the maxi-mum likelihood classifier (MLC) and the object based image analysis (OBIA). The classification procedures were supported by ground truth data that have been collected during the field surveys.
This project was one of the outcomes of the strategic partnership-setting meeting between the Minister of Irrigation and Water Resources (MoIWR) and the Food and Agricultural Organization (FAO) Sudan...
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