Arid
Agricultural Fields Classification in Semi-Arid Central Tunisia using SPOT 7 Image
Mezzi, Ranya1; Allani, Mohamed1; Alioscha-Perez, Mitchel2; Boukhari, Haithem1; Abdallah, Wajdi1; Stoffner, Fabian3; Zouabi, Adel4; Chalghaf, Ezzeddine4; Hamza, Mahmoud Elyes1; Mueller, Hans Werner3; Sahli, Hichem2; Sahli, Ali1
通讯作者Mezzi, Ranya
会议名称4th International Conference on Control Engineering and Information Technology (CEIT)
会议日期DEC 16-18, 2016
会议地点Hammamet, TUNISIA
英文摘要

This paper reports on classification methods applied and tested for land use classification in a semi-arid environment. Our study, conducted on two irrigated sites located in the Kairouan region, the largest irrigated region in Tunisia, compared Support Vector Machine (SVM) and Maximum Likelihood classification of SPOT-7 data. To produce a per-field classification a Mean-Shift Segmentation has been performed on the pansharpened SPOT-7 images. A field survey has been conducted. 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.


英文关键词Mean-Shift SVM MLC Agricultural field Spot 7
来源出版物2016 4TH INTERNATIONAL CONFERENCE ON CONTROL ENGINEERING & INFORMATION TECHNOLOGY (CEIT)
出版年2016
EISBN978-1-5090-1055-4
出版者IEEE
类型Proceedings Paper
语种英语
国家Tunisia;Belgium;Germany
收录类别CPCI-S
WOS记录号WOS:000402990700009
WOS关键词SUPPORT VECTOR MACHINES ; MEAN SHIFT
WOS类目Automation & Control Systems ; Computer Science, Information Systems
WOS研究方向Automation & Control Systems ; Computer Science
资源类型会议论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/305253
作者单位1.Univ Carthage, INAT, 43 Ave Charles Nicolle, Tunis 1082, Tunisia;
2.Vrije Univ Brussel, Elect & Informat Dept ETRO, Pl Laan 2, B-1050 Brussels, Belgium;
3.BGR, Geozentrum Hannover, Stilleweg 2, D-30655 Hannover, Germany;
4.Commissariat Reg Dev Agr Kairouan, Cite Sidi Layoun 3100, Kairouan, Tunisia
推荐引用方式
GB/T 7714
Mezzi, Ranya,Allani, Mohamed,Alioscha-Perez, Mitchel,et al. Agricultural Fields Classification in Semi-Arid Central Tunisia using SPOT 7 Image[C]:IEEE,2016.
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