Enhancing the Locational Perception of Soft Classified Satellite Imagery Through Evaluation and Development of the Pixel Swapping Technique

摘要: Spatial component is the key and most likely first element of map making so that accurate spatial information improves locational perception users. In this regard, soft classified satellite imagery conveys class proportions within pixels; however distribution sub-pixels remains unknown. So, different visualization techniques (e.g. pie-chart representation proportions) are suggested to communicate detailed land cover information. However, in each which, actual location definitely difficult for Recently, Super Resolution Mapping (SRM) have been developed optimization arrangement based on concepts dependency. These relatively new methods which a comprehensive study their performance also decisive parameters central issue sub-pixel mapping. research, binary Pixel Swapping (PS) algorithm, as prominent SRM multivariate mapping accuracy proposed method evaluated two procedures independent dependent classification error. Likewise, impact some zoom factor, neighborhood level weighting function) investigated efficiency algorithm. According results, overall PS technique extremely its input data (outputs classification). Furthermore, result chapter, it indicated by increasing algorithm decreases. Also, second inverse/square inverse distance functions has demonstrated highest accuracies. Considering lower values than 5 determined higher 90 % procedure optimizing arrangement.