Geomarketing using Remote Sensing: a Study on Marketing and Planning Development Strategy at Northern Riyadh

  • Authors

    • Zouheir Sallman
    • Fathoni Usman
    https://doi.org/10.14419/ijet.v7i4.35.22338

    Received date: November 29, 2018

    Accepted date: November 29, 2018

    Published date: November 30, 2018

  • Geomarketing, GIS, Market size, Micro-geographic area, planning, remote sensing
  • Abstract

    Determination of market size is a critical factor for the success of any company or business activity. This paper presents a study to provide a clear vision using remote sensing for Geomarketing and industry purposes. In order to estimate market size in the study area based on spatial data, Satellite images, Spot 6, with a 1.5 m resolution, will be used with two different dates during the year 2016. It is used to determine the growth in the housing sector with building types and construction levels in the micro-geographic area of Northern Riyadh. It is also used to identify the expected need for products of each district and the approximate time required for installation. By using remote sensing data for Geomarketing, strategies for marketing, planning and housing development could be setup.

  • References

    1. Peng Chen, Jian Wu,”Method of earthquake collapsed building in-formation extraction based on High resolution remote sensing”, Ge-ography and Geoformation science, 2013,
    2. Hunag and L. Zhang.” a multidirectional and multiscale morpholog-ical index for automatic extraction from multispectral Geo Eye-1 imagery” photogrammetric engineering and remote sensing, 2011),
    3. Jian Yang, Qinayan Meng, “A new method of building extraction from High Resolution remote images based on NSCT and PCNN”, IEEE,
    4. Lin and R. Nevitia, “Building Detection and Description from A Single Intensity Image” Computer Vision and Image Understand-ing, vol. 72, no. 3, pp. 101-121, 1998.
    5. Yihua Tan, Yujie Yu, “Semi-Automatic Building Extraction From Very High Resolution Remote Sensing Imagery Via Energy Mini-mization Model”, IGARSS 2016
    6. Wang, Yang, and X. Qin, “An Efficient Approach for Automatic Rectangular Building Extraction from Very High-Resolution Opti-cal Satellite Imagery” IEEE Geosic. Remote Sens. Letters, vol. 12, no. 3, pp. 487-491, 2015.
    7. Li, Tan, and Tia, “Urban Building Extraction via Visual Graphical Topic Model” 2014 IEEE Geoscience and Remote Sensing Sympo-sium,
    8. Ok, “Automated detection of buildings from single VHR multi-spectral images using shadow information and graph cuts” ISPRS Journal of Photogrammetry and Remote Sensing, vol. 86, no. 12, pp. 21–40, Sep. 2013.
    9. Zhang, “Semantic classification of urban buildings combining VHR image and GIS data: An improved random forest approach” ISPRS Journal of Photogrammetry and Remote Sensing, Apr. 2015.
    10. K. Kraus and N. Pfeifer, “Determination of terrain models inwood-ed areas with airborne laser scanner data” ISPRS Journal of Photo-grammetry and Remote Sensing, 1998.
    11. Junfei Xie and Jianhua Zhou “Classification of Urban Building Type from High Spatial Resolution Remote Sensing Imagery Using Extended MRS and Soft BP Network “IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2017.
    12. Wen, X. Huang, “A Novel Automatic Change Detection Method for Urban High-Resolution Remotely Sensed Imagery Based on Multi-index Scene Representation” IEEE Transactions on Geosci-ence and Remote Sensing, 2016.
    13. Huo, J. Cheng, “Object-oriented change detection based on mul-tiscale fusion” Joint Urban Remote Sensing Event, 2009.
    14. San Martin1 · M. Orive1, “Decision Making Supporting Tool Com-bining AHP Method with GIS for Implementing Food Waste Val-orization Strategies “Springer Science, 2017
    15. Aleksandar, “GIS Based Multi-Criteria Analysis for Industrial Site Selection”, Procedia Engineering, Volume 69, 2014, Pages 1054-1063
    16. Arvydas and Simon, “Property market modelling and fore-casting: simple vs complex models”, Journal of Property investment & finance Journal of Property investment $ fi-nance, 2014
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  • How to Cite

    Sallman, Z., & Usman, F. (2018). Geomarketing using Remote Sensing: a Study on Marketing and Planning Development Strategy at Northern Riyadh. International Journal of Engineering and Technology, 7(4.35), 112-117. https://doi.org/10.14419/ijet.v7i4.35.22338