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    An Intelligent Agent Based Land Encroachment Detection Approach

    Dacey, Simon; Song, Lei; Pang, Shaoning

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    Dacey_Paper.pdf (2.426Mb)
    Date
    2013
    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.
    Permanent link to Research Bank record:
    https://hdl.handle.net/10652/2738
    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.
    Keywords:
    land management, urban planning, encroachment detection, intelligent agents
    ANZSRC Field of Research:
    120507 Urban Analysis and Development, 080101 Adaptive Agents and Intelligent Robotics
    Copyright Holder:
    Asia Pacific Neural Network Assembly (APNNA)
    Available Online at:
    http://www.apnna.net/
    Rights:
    This digital work is protected by copyright. It may be consulted by you, provided you comply with the provisions of the Act and the following conditions of use: Any use you make of these documents or images must be for research or private study purposes only, and you may not make them available to any other person. You will recognise the author's and publishers rights and give due acknowledgement where appropriate.
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    • Computing Conference Papers [147]

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