Use of High Resolution Google Earth Satellite Imagery in Landuse Map Preparation for Urban Related Applications. (2016)

• Record Type: Journal Article
• Authors: Malarvizhi, K.; Kumar, S. Vasantha; Porchelvan, P.
• Is Part Of: Procedia technology. Volume 24(2016)
• Page Start: 1835
• Page End: 1842
• Publication Date: 2016
• Subjects: Urban planning -- Landuse map -- Satellite image -- Google earth -- Change detection ;; Technology -- Congresses; Technology -- Periodicals; Engineering -- Congresses; Engineering -- Periodicals; Engineering; Technology; Conference proceedings; Periodicals; 605
• DOI: 10.1016/j.protcy.2016.05.231
• Languages: English
• ISSNs: 2212-0173

Abstract

Abstract: The fundamental data required by urban planners and policy makers is accurate information on current landuse practices in a city or town and how it changes over the past for carrying out various urban planning and management activities. The free satellite imagery provided in global landcover facility (GLCF) which can be used to prepare the landuse maps as attempted in many studies has certain limitations. The images are of lower or medium resolution type and in many cases it may not be possible to obtain the latest image. To overcome this, one has to buy latest high resolution satellite image which is more expensive to purchase and sometimes it may not be possible to get the data due to security reasons. An alternative solution is to utilize Google earth imagery which is open source and provides clear view of buildings, roads, etc. and hence can be best utilized for urban related applications. The present study is an attempt in this direction, in which 340 individual tiles of Google earth images covering Vellore in Tamilnadu were extracted using Elshayal Smart open source software. They were then mosaicked and clipped to facilitate onscreen digitizing using GIS software. The area of various landuse classes was found using the prepared landuse map and zone-wise/ward-wise analysis was also performed. It was found that the area occupied by open land is 56.07 sq.km, which is the highest when compared to other landuse classes. Next to open land, built-up area occupies an area of 28.83 sq.km. The percentage split of all the four landuse classes were 60.69, 31.21, 7.83 and 0.26 for open land, built-up, agricultural and water bodies respectively. Use of Google earth imagery in urban change detection analysis was also explored by utilizing the images of 2007 and 2014. If budget is a constraint in purchasing high resolution satellite imagery, then one could consider utilizing free Google earth images as proposed in the present study for urban related applications.