|
Hokkaido University Collection of Scholarly and Academic Papers >
Graduate School of Agriculture / Faculty of Agriculture >
Peer-reviewed Journal Articles, etc >
XバンドおよびCバンドSARデータを併用した機械学習アルゴリズムによる圃場の作物分類
| Title: | XバンドおよびCバンドSARデータを併用した機械学習アルゴリズムによる圃場の作物分類 |
| Other Titles: | Crop Classification by Machine Learning Algorithm with Combination of X- and C-band SAR Data |
| Authors: | 山谷, 祐貴1 Browse this author | | 谷, 宏2 Browse this author →KAKEN DB | | 王, 秀峰3 Browse this author →KAKEN DB | | 薗部, 礼4 Browse this author →KAKEN DB | | 小林, 伸行5 Browse this author | | 望月, 貫一郎6 Browse this author | | 野田, 萌7 Browse this author |
| Authors(alt): | YAMAYA, Yuki1 | | TANI, Hiroshi2 | | WANG, Xiufeng3 | | SONOBE, Rei4 | | KOBAYASHI, Nobuyuki5 | | MOCHIZUKI, Kan-ichiro6 | | NODA, Megumi7 |
| Issue Date: | 11-May-2018 |
| Journal Title: | 写真測量とリモートセンシング |
| Journal Title(alt): | Journal of the Japan society of photogrammetry and remote sensing |
| Volume: | 57 |
| Issue: | 2 |
| Start Page: | 78 |
| End Page: | 83 |
| Publisher DOI: | 10.4287/jsprs.57.78 |
| Abstract: | A crop classification method using satellite data is proposed as an alternative to the existing ground survey. In this study, crop types were classified using two kinds of SAR data (i.e., TerraSAR-X X-band dual-polarization data and Radarsat-2 C-band fully-polarization data) and Random Forests. Sigma naught polarimetric parameters were calculated from SAR data and classifications were conducted using the following four different datasets ; Case 1 : all parameters calculated from Radarsat-2, Case 2 : all parameters calculated from Radarsat-2 and sigma naught calculated from TerraSAR-X data, Case 3 : all parameters calculated from Radarsat-2 and polarimetric parameters calculated from TerraSAR-X data, and Case 4 : all parameters calculated from Radarsat-2 and both sigma naught and polarimetric parameters calculated from TerraSAR-X. The highest overall accuracy of 0.934 was achieved by Case 4, and there were significant differences with the other classification results (p>0.05, based on Z-test). These results reveal that combining two kinds of SAR data can be improved classification accuracy. |
| Rights: | © 2018 一般社団法人 日本写真測量学会 | | © 2018 Japan Society of Photogrammetry and Remote Sensing |
| Type: | article |
| URI: | http://hdl.handle.net/2115/73921 |
| Appears in Collections: | 農学院・農学研究院 (Graduate School of Agriculture / Faculty of Agriculture) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
|
Submitter: 山谷 祐貴
|
