NDLI: Feature shape and elevation based road classification and extraction on high spatial resolution remote sensing imageries

Content Provider	IEEE Xplore Digital Library
Author	Tao Tang Xiao Wang Carbonara, J. Zhixin Shi
Copyright Year	2009
Description	Author affiliation: Center of Excellence for Document Analysis and Recognition (CEDAR), Department of Computer Science and Engineering, State University of New York at Buffalo, USA (Zhixin Shi) \|\| Department of Geography and Planning, State University of New York College at Buffalo, 1300 Elmwood Ave., 14222, USA (Tao Tang; Xiao Wang) \|\| Department of Mathematics, State University of New York College at Buffalo, 1300 Elmwood Ave., 14222, USA (Carbonara, J.)
Abstract	Classification and extraction of geospatial features from high spatial resolution imageries approved is one of the most significant steps for spatial database acquisition and updating in GIS. This research is to explore the methodologies of recognizing shape and elevation characteristics of spatial features on the remote sensed images. We focus on the road network classification and extraction among various features on the ground because it carries unique characteristic of elongation. We combined both a pattern recognition model of connected component labeling (CCL) in two dimensional image processing, and a three dimensional DEM elevation filtering model to extract the road and street features from high resolution imageries. Samples of digital aerial photographs in Erie County, New York were used to test the methodology. The results indicated that the correctness of road extraction in rural areas can reach 69.1%; that of completeness is 74.9%; and the overall quality is 73.1%. By contrast, the correctness in urban high-rise region is only 39.5%; that of completeness is 42.8%; and the overall quality is 32.8%.
Starting Page	1
Ending Page	6
File Size	723697
Page Count	6
File Format	PDF
ISBN	9781424445622
DOI	10.1109/GEOINFORMATICS.2009.5293473
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-08-12
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Geographic Information Systems Image recognition Road feature classification and extraction Shape Roads DEM filtering Spatial databases Character recognition Remote sensing Image databases Connected component labeling (CCL) Feature extraction Spatial resolution
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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