Remote Sensing, Geographic Information Systems, and Shannons enthropy: Measuring and Monitoring urban Sprawl in a Mountainous Environment: Difference between revisions
(New page: '''Loureal Camille O. Verzosa''' (MS Graduated: 2nd Sem 2009-2010) '''Abstract''' Urban sprawl, or unplanned and uncontrolled spreading out of built-up areas, causes problems in the all...) |
Mqmallonga (talk | contribs) No edit summary |
||
(3 intermediate revisions by one other user not shown) | |||
Line 8: | Line 8: | ||
This study in the mountainous city of Baguio in northern Philippines shows that together with image processing and interpretation tools, built-up can be readily identified and quantified from temporal satellite images and aerial photographs. The horizontal and vertical dimensions of entropy in Baguio City and its selected barangays are shown to have almost reached their critical limit, implying that the area has tremendously grown and is continuously expanding in both dimensions. A methodology for risk equation (risk=hazard x vulnerability). The computed values represent the urban situation of Baguio City, and are recommended for consideration by the city government in monitoring the growth of built-up areas and in drafting measures and policies to address urban sprawl’s imminent effects. | This study in the mountainous city of Baguio in northern Philippines shows that together with image processing and interpretation tools, built-up can be readily identified and quantified from temporal satellite images and aerial photographs. The horizontal and vertical dimensions of entropy in Baguio City and its selected barangays are shown to have almost reached their critical limit, implying that the area has tremendously grown and is continuously expanding in both dimensions. A methodology for risk equation (risk=hazard x vulnerability). The computed values represent the urban situation of Baguio City, and are recommended for consideration by the city government in monitoring the growth of built-up areas and in drafting measures and policies to address urban sprawl’s imminent effects. | ||
Subject Index : Remote sensing, Mountains | |||
[[Category: Theses]] | [[Category: Theses]] | ||
[[Category: | [[Category: Geodetic Engineering Thesis]] | ||
[[Category: College of Engineering Thesis]] | [[Category: College of Engineering Thesis]] |
Latest revision as of 12:31, 11 February 2012
Loureal Camille O. Verzosa
(MS Graduated: 2nd Sem 2009-2010)
Abstract
Urban sprawl, or unplanned and uncontrolled spreading out of built-up areas, causes problems in the allocation of basic needs and increases risk to life and property in the face of disasters. This study integrates remote sensing, photogrammetry, and geographic information systems in adopting Shannon’s entropy top measure and monitor urban sprawl. Shannon’s entropy is an index used to quantify the degree of dispersion or concentration of built-up areas. Previous studies have applied this concept to demonstrate the horizontal spread of built-up. However, through time, people construct multiple-storey houses to accommodate the increasing population. Thus, in order to determine the full scope of sprawl, the concept of Shannon’s entropy is extended to consider the vertical growth of built-up. This study in the mountainous city of Baguio in northern Philippines shows that together with image processing and interpretation tools, built-up can be readily identified and quantified from temporal satellite images and aerial photographs. The horizontal and vertical dimensions of entropy in Baguio City and its selected barangays are shown to have almost reached their critical limit, implying that the area has tremendously grown and is continuously expanding in both dimensions. A methodology for risk equation (risk=hazard x vulnerability). The computed values represent the urban situation of Baguio City, and are recommended for consideration by the city government in monitoring the growth of built-up areas and in drafting measures and policies to address urban sprawl’s imminent effects.
Subject Index : Remote sensing, Mountains