DATA FUSION WITH SAR AND OPTICAL DATA FOR AGRICULTURE FIELD CLASSIFICATION

Abstract

Accurate i i food i security i crop i assessment i studies. i classification i maps i are i an i important i data i source i for i agricultural i monitoring i and processing Now i i capabilities i are i more i developed. i And i a i day i advancements i observation i i satellite i imagery. i The i combination i of i optical i and i on i radar i earth i data i i crop i type i in i sensor i technologies i surveying i is i attention i and i on i is i particularly i promising i in i multi-source the i region i of classification. This paper is overview on data fusion using SAR and optical data to classified the agriculture field. Study on the area of KVK field, Haridwar,India. Supervised classification on Sentinel 1 and Sentinel 2 data and collect accuracy assessment results of unfused and fused data and doing comparison on three crop types, rice, sugar cane and soyabean. To classify the data, Supervised classification is operated such as Mahalanobis distance classification, Maximum likelihood classification, Minimum distance classification, Neural net classification, Parallelepiped classification and Support vector machine classification. Doing confusion matrix to get accuracy assessments of all classification and comparing Producer’s accuracy, User’s accuracy and Overall accuracy of each classification.