An intelligent agent based land encroachment detection approach
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Other Title
Authors
Dacey, Simon
Song, Lei
Pang, Shaoning
Song, Lei
Pang, Shaoning
Author ORCID Profiles (clickable)
Degree
Grantor
Date
2013
Supervisors
Type
Conference Contribution - Paper in Published Proceedings
Ngā Upoko Tukutuku (Māori subject headings)
Keyword
land management
urban planning
encroachment detection
intelligent agents
urban planning
encroachment detection
intelligent agents
ANZSRC Field of Research Code (2020)
Citation
Dacey, S., Song, L. and Pang, S. (2013). An Intelligent Agent Based Land Encroachment Detection Approach. Proceedings in the 20th International Conference on Neural Information Processing, 585-592.
Abstract
Land management and planning is essential to assist the economic growth, sustainable resource use and environmental protection of a city. This paper describes a novel approach to automatic encroachment detection to assist in land management decision making. The approach begins with training the agent to identify and understand the land cover/use features (such as buildings, parks, trees and roads) that are predominant in the region of interest, and carries out segmentation on the park data using the intelligent agent developed from the training samples. Experiments on park images from Auckland New Zealand show the effectiveness of the proposed approach.
Publisher
Asia Pacific Neural Network Assembly (APNNA)
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DOI
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Asia Pacific Neural Network Assembly (APNNA)
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