UAV Remote Sensing for Urban Vegetation Mapping Using Random Forest and Texture Analysis
Chinese Academy of Sciences · Institute of Remote Sensing and Digital Earth · +2 more institutions
Abstract
Unmanned aerial vehicle (UAV) remote sensing has great potential for vegetation mapping in complex urban landscapes due to the ultra-high resolution imagery acquired at low altitudes. Because of payload capacity restrictions, off-the-shelf digital cameras are widely used on medium and small sized UAVs. The limitation of low spectral resolution in digital cameras for vegetation mapping can be reduced by incorporating texture features and robust classifiers. Random Forest has been widely used in satellite remote sensing applications, but its usage in UAV image classification has not been well documented. The objectives of this paper were to propose a hybrid method using Random Forest and texture analysis to…
Citation impact
- FWCI
- 31.27
- Percentile
- 100%
- References
- 45
Authors
3- QFQuanlong Feng
Chinese Academy of Sciences, Institute of Remote Sensing and Digital Earth, State Key Laboratory of Remote Sensing Science
- JLJiantao Liu
Chinese Academy of Sciences, Institute of Remote Sensing and Digital Earth, State Key Laboratory of Remote Sensing Science
- JGJianhua GongCorresponding
Chinese Academy of Sciences, Institute of Remote Sensing and Digital Earth, GeoInformation (United Kingdom), State Key Laboratory of Remote Sensing Science
Topics & keywords
- Random forest
- Remote sensing
- Computer science
- Artificial intelligence
- Classifier (UML)
- Vegetation (pathology)
- Environmental science
- Pattern recognition (psychology)
- Sustainable cities and communities