Forest classification map is considered as very important data in a forest management and recommended to be produced covering the whole country for public use. Therefore, it is suggested that more easy and efficient new technique is developed for producing detailed forest classification map using the remote sensing image with high resolution. Here, the object-based classification is mentioned to represent this new technique. In the object-based classification a homogeneous pixel domain in the remote sensing image is first created, and classification process is done using the statistics of a homogeneous pixel domain. Generally color information and image texture used in industrial image processing are contained in the statistics. Image texture is the numerical value that evaluated the difference in the pattern of a homogeneous pixel domain, so that it is difficult to understand the relation between image texture and actual state of the forest in situ. In order to utilize the object-based classification in a forest management it is required to make the algorithm for the object-based classification easy to understand.
Since the spatial distribution of trees reflects its growth, thinning and spacing treatment, regeneration etc, it is possible the spatial distribution can be used as classification rule for object based classification. This research examined the validity of the classification, which used brightness peak in the remote sensing image related to the spatial distribution of trees. The overall accuracy of the proposal method was 0.68. Although this result was not sufficient, the proposal method was effective in classifying early growth stage of cedar and other forest state.
抄録全体を表示