Cannabis (marijuana) planted fields with high-resolution satellite data break

The aim of this thesis is to reveal the detectability and distinguishability of cannabis cultivated areas with high resolution satellite images. Thus, it is aimed to detect the people and places that are not given permission for cultivation and sowing by satellite images. The thesis, co-authored with the technological possibilities presented and a comprehensive literature study, is to distinguish between reflection differences in target plants from other plants by using satellite images. In this context, Cannabis, sunflower, corn and poppy crops were grown on an area of 25 decare in the district of Bucak Burdur; singular, heap and corn and sunflower crops were planted in different proportions. Morphological development of the plants was monitored carefully during the growing phase and their developmental processes were recorded. For the classification process, pixel based classification and accuracy evaluations were made by using Argcis 9.0 and Erdas 9.4 software. As classification methods, NDVI (Normalized vegetation differences index) Unsupervised and Supervised methods were used for classification. The obtained grades were interpreted by blending with the classification methods data.