A Review of Remote Sensing Image Classification Techniques: the Role of Spatio-contextual Information

By Miao Li, Shuying Zang, Bing Zhang, Shanshan Li, Changshan Wu. 2014

433 citations recorded by the source corpus.

Abstract This paper reviewed major remote sensing image classification techniques, including pixel-wise, sub-pixel-wise, and object-based image classification methods, and highlighted the importance of incorporating spatio-contextual information in remote sensing image classification. Further, this paper grouped spatio-contextual analysis techniques into three major categories, including 1) texture extraction, 2) Markov random fields (MRFs) modeling, and 3) image segmentation and object-based image analysis. Finally, this paper argued the necessity of developing geographic information analysis models for spatial-contextual classifications using two case studies.

Subfields: Atmospheric Science, Ecology, Media Technology

View Paper: https://www.semanticscholar.org/paper/a8a7f187de931c74d50dde47d004bcf427612561

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atmospheric Science

1. Anuj Karpatne
2. Gowtham Atluri
3. Vipin Kumar
4. Darius Phiri
5. Justin Morgenroth

In Ecology

1. Anuj Karpatne
2. Darius Phiri
3. Justin Morgenroth

In Media Technology

1. Anuj Karpatne
2. Vipin Kumar
3. Darius Phiri
4. Justin Morgenroth

Citations in the corpus

• Remote Sensing Image Scene Classification Meets Deep Learning: Challenges, Methods, Benchmarks, and Opportunities (2020, neutral): “[75] surveyed the pixel-level, subpixel-level, and object-based”
• Developments in Landsat Land Cover Classification Methods: A Review (2017, methodology): “Sub-pixel classification approaches were developed in the 1980s based on fuzzy-set theory, Dempster-Shafter theory and certainty factor theory [7,19,69].”
• Spatio-Temporal Data Mining (2017, methodology): “…a land cover type) has been heavily studied in the remote sensing literature for a variety of problems [DeFries and Chan 2000; Jun and Ghosh 2011; Li et al. 2014b; Vatsavai 2008], e.g., the mapping of surface water dynamics using multi-spectral remote sensing data [Karpatne et al. 2016b;…”