Accuracy assessment and classification efficiency of object-based image analysis of aerial imagery

Abstract

Following text is focused on finding a proper balance between classification accuracy and classification efficiency of object based image analysis of aerial imagery. For image classification were used tools of Feature Analyst, an ArcGIS extension, which are based on image filtering and searching for homogeneous segments corresponding to the threshold values defined by the training areas and corrected with tools of object recognition. The classification accuracy was assessed using the error matrices and calculating user’s and producer’s accuracy. To evaluate the time and work consumption, index of classification efficiency was introduced, which is a weighted value of accuracy and number of objects. To evaluate the tools of object recognition, the principle of fuzzy logic was used, which calculates accuracy with inclusion of alternative category. For the study was used a cut of aerial imagery of protected area of Křivoklátsko as a typical example of the character of available image data in the territory of Czech Republic - large area of fields, forests and meadows with a very heterogeneous character, water body with sun reflection, net of narrow roads and small villages. From the final values of accuracy is obvious, that Feature analyst provides comparable results with other authors. From the point of view of classification efficiency, application of tools of object recognition and its effect on the time and work consumption, it is a question of the extent of study area and the heterogeneity of the features of the physical world on the image data.