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

被引:83
作者
Malarvizhi, K. [1 ]
Kumar, S. Vasantha [2 ]
Porchelvan, P. [2 ]
机构
[1] VIT Univ, CDMM, Vellore, Tamil Nadu, India
[2] VIT Univ, SMBS, Vellore, Tamil Nadu, India
来源
INTERNATIONAL CONFERENCE ON EMERGING TRENDS IN ENGINEERING, SCIENCE AND TECHNOLOGY (ICETEST - 2015) | 2016年 / 24卷
关键词
Urban planning; Landuse map; Satellite image; Google earth; Change detection;
D O I
10.1016/j.protcy.2016.05.231
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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. (C) 2016 The Authors. Published by Elsevier Ltd.
引用
收藏
页码:1835 / 1842
页数:8
相关论文
共 14 条
[1]  
[Anonymous], 2012, INT J REMOTE SENS GI
[2]  
Basawaraja R., 2011, J GEOGRAPHY REGIONAL, V4, P455
[3]  
Elshayal M., 2015, ELSHAYAL SMART GIS V
[4]   Spatial Pattern Analysis of Urban Sprawl: Case Study of Jiangning, Nanjing, China [J].
Feng, Li ;
Li, Hui .
JOURNAL OF URBAN PLANNING AND DEVELOPMENT, 2012, 138 (03) :263-269
[5]  
GLCF, 2015, NASA LANDS PROGR
[6]  
Guzelmansur A., 2010, REMOTE SENSING SCI E
[7]  
Hegazy I. R., 2015, INT J SUSTAINABLE BU
[8]   A novel approach to mapping land conversion using Google Earth with an application to East Africa [J].
Jacobson, Andrew ;
Dhanota, Jasjeet ;
Godfrey, Jessie ;
Jacobson, Hannah ;
Rossman, Zoe ;
Stanish, Andrew ;
Walker, Hannah ;
Riggio, Jason .
ENVIRONMENTAL MODELLING & SOFTWARE, 2015, 72 :1-9
[9]   Monitoring and modelling of urban sprawl using remote sensing and GIS techniques [J].
Jat, Mahesh Kumar ;
Garg, P. K. ;
Khare, Deepak .
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2008, 10 (01) :26-43
[10]   Spatiotemporal urbanization processes in the megacity of Mumbai, India: A Markov chains-cellular automata urban growth model [J].
Moghadam, Hossein Shafizadeh ;
Helbich, Marco .
APPLIED GEOGRAPHY, 2013, 40 :140-149