A review of supervised object-based land-cover image classification
Nanjing University · Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application · +1 more institution
Abstract
Object-based image classification for land-cover mapping purposes using remote-sensing imagery has attracted significant attention in recent years. Numerous studies conducted over the past decade have investigated a broad array of sensors, feature selection, classifiers, and other factors of interest. However, these research results have not yet been synthesized to provide coherent guidance on the effect of different supervised object-based land-cover classification processes. In this study, we first construct a database with 28 fields using qualitative and quantitative information extracted from 254 experimental cases described in 173 scientific papers. Second, the results of the meta-analysis are reported,…
Citation impact
- FWCI
- 78.20
- Percentile
- 100%
- References
- 131
Authors
6- LMLei MaCorresponding
Nanjing University, Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application
- MLManchun LiCorresponding
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing University
- XMXiaoxue Ma
Nanjing University, Jiangsu Second Normal University
- LCLiang Cheng
Nanjing University, Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application
- PDPeijun Du
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing University
Topics & keywords
- Land cover
- Computer science
- Artificial intelligence
- Segmentation
- Scale (ratio)
- Object (grammar)
- Pattern recognition (psychology)
- Contextual image classification
- Life in Land