Evaluation of crop mapping on fragmented and complex slope farmlands through random forest and object-oriented analysis using unmanned aerial vehicles

Re Yang Lee*, Kuo Chen Chang, Deng Yuan Ou, Chia Hui Hsu

*此作品的通信作者

研究成果: 雜誌貢獻期刊論文同行評審

1 引文 斯高帕斯(Scopus)

摘要

Conducting field research in Taiwan can be challenging because of the abundance of steep slopes. This study aimed to establish an automatic interpretation procedure applicable to exploring images of large-scale slope land taken using UAVs. The proposed method was compared with traditional field surveying and manual image interpretation techniques to determine the advantages and disadvantages of the proposed procedure in terms of efficiency. The object-based image analysis (OBIA) and texture features were first combined and the random forest (RF) classifier was then employed to interpret crop types. This study selected three sites of slope land and plains for experimentation. The obtained results indicated that the overall accuracy of the proposed classification method exceeded 91%, and the Kappa value was approximately 0.9 for all sites. In addition, interpretation of the proposed method was more efficient than that of the two traditional methods.

原文英語
頁(從 - 到)1293-1310
頁數18
期刊Geocarto International
35
發行號12
DOIs
出版狀態已發佈 - 2020 9月 9

ASJC Scopus subject areas

  • 地理、規劃與發展
  • 水科學與技術

指紋

深入研究「Evaluation of crop mapping on fragmented and complex slope farmlands through random forest and object-oriented analysis using unmanned aerial vehicles」主題。共同形成了獨特的指紋。

引用此