UAV-BASED CROPS CLASSIFICATION WITH JOINT FEATURES FROM ORTHOIMAGE AND DSM DATA

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences

Liu, B.^1¹ 

[1] Key Laboratory of Agricultural Remote Sensing, Ministry of Agriculture, China /Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China^1

关键词: UAV;    crop classification;    SVM;    DOM;    DSMs;    Texture;   

DOI  :  10.5194/isprs-archives-XLII-3-1023-2018

学科分类：地球科学(综合)

来源: Copernicus Publications

【 摘 要 】

Accurate crops classification remains a challenging task due to the same crop with different spectra and different crops with same spectrum phenomenon. Recently, UAV-based remote sensing approach gains popularity not only for its high spatial and temporal resolution, but also for its ability to obtain spectraand spatial data at the same time. This paper focus on how to take full advantages of spatial and spectrum features to improve crops classification accuracy, based on an UAV platform equipped with a general digital camera. Texture and spatial features extracted from the RGB orthoimage and the digital surface model of the monitoring area are analysed and integrated within a SVM classification framework. Extensive experiences results indicate that the overall classification accuracy is drastically improved from 72.9 % to 94.5 % when the spatial features are combined together, which verified the feasibility and effectiveness of the proposed method.

【 授权许可】

CC BY