Object-Based Crop Mapping Using Multi-Temporal Landsat 8 Imagery
Journal Title: International Journal of engineering Research and Applications - Year 2018, Vol 8, Issue 4
Abstract
This study aimed to map crop pattern using object-based classification technique within a Mediterranean agricultural land in Turkey. Many Mediterranean land covers show similar spectral characteristics that make it difficult to identify in feature space by simple per-pixel classifiers. Therefore, an object-based classification is a potential solution for the classification of land cover in such environments., Appropriate segmentation parameters play a vital role for accurate mapping in object-based image classification. The optimum segmentation parameters were determined by testing on complex agricultural parcels. Each agricultural parcel was assigned a crop type using object-based classification techniques. Two different periods, classified as winter and summer, were classified with high accuracy in the study area. For the crop mapping, March and April are the best imaging times for winter, and between May and August are the best imaging times for summer crop season. Overall accuracy of the classification results, were derived through kappa statistics of 0.85 for winter and summer crop mapping.
Authors and Affiliations
Ahmet Cilek, Suha Berberoglu
Keywords
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- EP ID EP393970
- DOI 10.9790/9622-0804023437.
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