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Introduction 
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.
Objective
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).
Methodology 
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).
Methodology
Maximum likelihood classification :
Result
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.
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