Agricultural Fields Classification in Semi-Arid Central Tunisia using SPOT 7 Image
Host Publication: 4 th International Conference on Control Engineering & Information Technology
Authors: R. Mezzi, M. Allani, M. Perez Gonzalez, H. Boukhari, W. Abdallah, F. Stoffner, M. Elyes Hamza, M. Hans Werner, H. Sahli and A. Sahli
Publication Year: 2016
Number of Pages: 6
This paper reports on classification methods applied and tested for land use classification in a semi-arid environment. Our study, conducted on two irrigates sites located in the Kairouan region, the largest irrigated region in Tunisia, compared Support Vector Machine (SVM) and Maximum Likelihood classification of SPOTǉ data. To produce a per-field classification a Mean-Shift Segmentation has been performed on the pansharpened SPOTǉ images. A field survey has been conducted to. Accuracy assessment was done to evaluate the performance of the proposed using collect ground truth data on land use and extend of all the agricultural fields within the study areas obtained through filed survey.