Automated extraction of road networks from IKONOS data in urban area

Jong Yeol Lee

doi:10.1109/IGARSS.2005.1526206

Automated extraction of road networks from IKONOS data in urban area

Jong Yeol Lee^*

^*Corresponding author for this work

Division of Electronic Engineering

Korea Research Institute for Human Settlements

Research output: Contribution to conference › Conference paper › peer-review

2 Scopus citations

Abstract

In this paper, one of knowledge-based approaches to extract road networks automatically is presented. The roads are extracted with several spectral and geometric characteristics of them. Seed areas to trace road networks are investigated by spectral and geometric information using linear-shape kernel. Then the road networks are traced by knowledge-based methods from the seed areas. Main difficulties to trace roads are occluding materials such as cars, buildings, casting shadow of buildings, and vegetation area. Vegetation area is masked using NDVI. The frame of road networks is searched, and the interrupted parts of networks are connected to build complete networks using knowledge about the global network characteristics of roads. The results of the extraction are evaluated by comparison with the road networks in the topographic map.

Original language	English
Title of host publication	25th Anniversary IGARSS 2005
Subtitle of host publication	IEEE International Geoscience and Remote Sensing Symposium
Pages	444-447
Number of pages	4
DOIs	https://doi.org/10.1109/IGARSS.2005.1526206
State	Published - 2005
Event	2005 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2005 - Seoul, Korea, Republic of Duration: 2005.07.25 → 2005.07.29

Publication series

Name	International Geoscience and Remote Sensing Symposium (IGARSS)
Volume	1

Conference

Conference	2005 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2005
Country/Territory	Korea, Republic of
City	Seoul
Period	05.07.25 → 05.07.29

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 11 Sustainable Cities and Communities

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10.1109/IGARSS.2005.1526206

Cite this

@inproceedings{c3cca80624ed4a1ea4c256aca588f31f,

title = "Automated extraction of road networks from IKONOS data in urban area",

abstract = "In this paper, one of knowledge-based approaches to extract road networks automatically is presented. The roads are extracted with several spectral and geometric characteristics of them. Seed areas to trace road networks are investigated by spectral and geometric information using linear-shape kernel. Then the road networks are traced by knowledge-based methods from the seed areas. Main difficulties to trace roads are occluding materials such as cars, buildings, casting shadow of buildings, and vegetation area. Vegetation area is masked using NDVI. The frame of road networks is searched, and the interrupted parts of networks are connected to build complete networks using knowledge about the global network characteristics of roads. The results of the extraction are evaluated by comparison with the road networks in the topographic map.",

author = "Lee, \{Jong Yeol\}",

year = "2005",

doi = "10.1109/IGARSS.2005.1526206",

language = "English",

isbn = "0780390504",

series = "International Geoscience and Remote Sensing Symposium (IGARSS)",

pages = "444--447",

booktitle = "25th Anniversary IGARSS 2005",

note = "2005 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2005 ; Conference date: 25-07-2005 Through 29-07-2005",

}

Lee, JY 2005, Automated extraction of road networks from IKONOS data in urban area. in 25th Anniversary IGARSS 2005: IEEE International Geoscience and Remote Sensing Symposium., 1526206, International Geoscience and Remote Sensing Symposium (IGARSS), vol. 1, pp. 444-447, 2005 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2005, Seoul, Korea, Republic of, 05.07.25. https://doi.org/10.1109/IGARSS.2005.1526206

TY - GEN

T1 - Automated extraction of road networks from IKONOS data in urban area

AU - Lee, Jong Yeol

PY - 2005

Y1 - 2005

N2 - In this paper, one of knowledge-based approaches to extract road networks automatically is presented. The roads are extracted with several spectral and geometric characteristics of them. Seed areas to trace road networks are investigated by spectral and geometric information using linear-shape kernel. Then the road networks are traced by knowledge-based methods from the seed areas. Main difficulties to trace roads are occluding materials such as cars, buildings, casting shadow of buildings, and vegetation area. Vegetation area is masked using NDVI. The frame of road networks is searched, and the interrupted parts of networks are connected to build complete networks using knowledge about the global network characteristics of roads. The results of the extraction are evaluated by comparison with the road networks in the topographic map.

AB - In this paper, one of knowledge-based approaches to extract road networks automatically is presented. The roads are extracted with several spectral and geometric characteristics of them. Seed areas to trace road networks are investigated by spectral and geometric information using linear-shape kernel. Then the road networks are traced by knowledge-based methods from the seed areas. Main difficulties to trace roads are occluding materials such as cars, buildings, casting shadow of buildings, and vegetation area. Vegetation area is masked using NDVI. The frame of road networks is searched, and the interrupted parts of networks are connected to build complete networks using knowledge about the global network characteristics of roads. The results of the extraction are evaluated by comparison with the road networks in the topographic map.

UR - https://www.scopus.com/pages/publications/33745713894

U2 - 10.1109/IGARSS.2005.1526206

DO - 10.1109/IGARSS.2005.1526206

M3 - Conference paper

AN - SCOPUS:33745713894

SN - 0780390504

SN - 9780780390508

T3 - International Geoscience and Remote Sensing Symposium (IGARSS)

SP - 444

EP - 447

BT - 25th Anniversary IGARSS 2005

T2 - 2005 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2005

Y2 - 25 July 2005 through 29 July 2005

ER -

Automated extraction of road networks from IKONOS data in urban area

Abstract

Publication series

Conference

UN SDGs

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