State of the art on automatic road extraction for GIS update: a novel classification

By Juan B. Mena. Pattern Recognition Letters, 2003

472 citations recorded by the source corpus.

Subfields: Environmental Engineering, Media Technology, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/a1bc2b6af1e750578dbddf725a9370b0cf6ee7b9

How researchers see this paper

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

In Environmental Engineering

1. Chunhong Pan
2. Ming Cui
3. John C. Femiani
4. Shiming Xiang
5. Peter Wonka
6. Xiangguo Lin
7. Jiuxiang Hu
8. Qihao Weng

In Media Technology

1. Chunhong Pan
2. Ming Cui
3. John C. Femiani
4. Shiming Xiang
5. Peter Wonka
6. Xiangguo Lin
7. Ying Wang
8. Jiuxiang Hu

In Ocean Engineering

1. Ming Cui
2. John C. Femiani
3. Peter Wonka
4. Xiangguo Lin
5. Jiuxiang Hu
6. Qihao Weng
7. Anshuman Razdan
8. Jixian Zhang

Citations in the corpus

• A Survey on Object Detection in Optical Remote Sensing Images (2016, unknown): “…2004; Laptev et al., 2000; Leninisha and Vani, 2015; Li et al., 2010; Maillard and Cavayas, 1989; Mayer et al., 2006; McKeown and Denlinger, 1988; Mena, 2003; Mokhtarzade and Zoej, 2007; Movaghati et al., 2010; Song and Civco, 2004; Trinder and Wang, 1998; Ünsalan and Sirmacek, 2012; Wang et…”
• Automatic Road Detection and Centerline Extraction via Cascaded End-to-End Convolutional Neural Network (2017, background): “Although various recent studies on road extraction [3]–[6]”
• Advances in fusion of optical imagery and LiDAR point cloud applied to photogrammetry and remote sensing (2017, methodology): “Most existing road extraction methods from images (Mena 2003, Baltsavias 2004, Shi et al. 2014) still suffer from the abrupt irregular geometric deformations and radiometric changes due to appearance of road junctions, material change, traffic jams, shadows of trees and tall buildings, road…”
• Road Network Extraction and Intersection Detection From Aerial Images by Tracking Road Footprints (2007, methodology): “Road network detection can be used for several applications such as automated correction and updating for geographic information systems (GIS) from aerial images [1], [2], registration with multitemporal images for change detection [3]–[5], automatically aligning two spatial datasets [6]–[8], etc.”
• Remote sensing of impervious surfaces in the urban areas: Requirements, methods, and trends (2012, background): “Mena (2003) presented a comprehensive review on automatic road extraction, and grouped themethods/algorithms into six categories: road tracking, mathematical morphology, snake, knowledgebased, multi-resolution and multi-resource methods, and integrated systems.”