Spatial Distribution of Honeybee Forage based on Color Satellite Image Segmenting using K-Mean Clustering
Rachid Sammouda, Ameur Touir, Fahman Saeed, Nuru Mohammed, Ahmed Al-Ghammidi
Journal of Multimedia Processing and Technologies, Vol. 4, No. 2, 2013.
DOI: 
Link: http://www.dline.info/jmpt/fulltext/v4n2/1.pdf
Abstract:
Beekeeping plays an important role in increasing and diversifying the incomes of many rural communities in Kingdom of Saudi Arabia. However, despite the regionâ€™s relatively good rainfall, which result in better forage conditions, bees and beekeepers are greatly affected by seasonal shortages of bee forage. Because of these shortages, beekeepers must continually move their colonies in search of better forage. The aim of this paper is to determine the actual bee forage areas with specific characters like population density, ecological distribution, flowering phenology based on colour satellite image segmentation using K-mean clustering. K-mean segment region satellite images into five segments, following that we search in a sample of acacia trees against this image clusters to specify the best region for better forage.