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- Title
UAV-based Crops Classification with joint features from Orthoimage and DSM data.
- Authors
Bin Liu; Yun Shi; Yulin Duan; Wenbin Wu
- Abstract
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.
- Subjects
CROP ecology; DRONE aircraft; AGRICULTURE; DIGITAL cameras
- Publication
International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences, 2018, Vol 42, Issue 3, p1023
- ISSN
1682-1750
- Publication type
Article
- DOI
10.5194/isprs-archives-XLII-3-1023-2018