教師付き分類とオブジェクトベースのセグメンテーションを組み合わせた土地利用/土地被覆分類手法の提案—牧草地における農用地及び更新草地の判別—

抄録

To increase the feed self-sufficiency of livestock and management efficiency of dairy farming on a grassland, it is necessary to improve the quality and production of feed grass through grassland renovation. Remote sensing analysis can be used to monitor renovated grassland over a broad area. A few studies have investigated renovated grasslands; however, these contain a misjudgment between renovated grassland and other land use/land cover. Therefore, in this study, we developed a method to integrate pixel- and object-based image analysis to conduct plot based estimation and applied it to grasslands on the Konsen plateau in Hokkaido. First, we created a farmland segment. Second, we overlaid the supervised classification results and decided the final land use/land cover classification. Performing farmland segmentation using SPOT 6 enhanced the kappa coefficient significantly compared with the traditional supervised classification results obtained using both Landsat 8 OLI and SPOT 6. The classification accuracy is also higher compared with that achieved in previous studies.