GOOGLE FUSION TABLES AS A GEOGRAPHIC INFORMATION SYSTEM LEARNING TOOLS

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1 6-05 Google Fusion Tables As A Geographic Information System Learning Tools GOOGLE FUSION TABLES AS A GEOGRAPHIC INFORMATION SYSTEM LEARNING TOOLS Adri Gabriel Sooai Department of Computer Science, Engineering Faculty, Widya Mandira Catholic University Jl. A. Yani Kupang adrigabriel@gmail.com ABSTRACT The development of Geographic Information System application, if done from scratch is a very meticulous work, starting with the ground truth / field surveys, rectification / binding geographic coordinates to the satelitte image, image interpretation, suppervised and unsupervised classification through thematic mapping and labeling. Through the development of Cloud Computing, among others, there is a Cloud-Based Service: Google Fusion Tables, the development of GIS applications can immediately begin to create thematic maps. Developers simply do digitize over satellite imagery using Free Open Source applications, which will generate KML / Keyhole Markup Language. Developers do not need complex knowledge as a programmer, the digitization of various land cover in the form of KML fairly united in Google Fusion Tables worksheet and will be stored in Google Drive and Google account owners can share access to Geographic Information System applications. Development of Geographic Information System application will be very easy and faster, Google fusion tables can accommodate a variety of media such as images or video via KML script using a text editor or the built-in facilities. The learning process will be very easy for the participants / students. Keywords: Cloud Based Service, Google Drive, Google Fusion Tables, KML, Free Open Source. 1 INTRODUCTION The development of Geographic Information System application, if done from scratch is a very meticulous work, starting with the ground truth / field surveys, rectification / binding of geographic coordinates to the image, image interpretation, classification of guided and unguided through thematic mapping and labeling. If the development of GIS application is using web-based programming languages such as PHP, JSCRIPT and others, then it takes very basic programming skills. It needs knowledge of programming to create interfaces, spatial database management, creation of thematic maps and layers for complex programming techniques. In a lecture on the course for computer science, Geographic Information System course is only burdened with two (2) credits. This only allows students to get a general knowledge course on Geographic Information System/GIS. If forced to build a real application it should require an additional form of practicum. To overcome the above problem, we need to find alternative solutions in order to accelerate the uptake of GIS lessons. This study aimed to examine the extent to which the use of Google Fusion Tables can facilitate the Geographic Information System learning process. 2 THEORETICAL BASIS Previous research has been done for the development of Google Fusion Tables, which is a cloud-based computing service aimed to help provide greater comfort in developing cloud-based applications [1]. Development of Geographic Information System applications require database. The database is composed of tables and attributes. Each attribute has a data type of each. Text and numeric data types will appear relatively quickly, while the image data type or Binary Large Object / BLOB may contain satellite imagery or video embedded would be relatively very heavy for display. To show satellite Imagery on Geographic Information System / GIS application in WEB Browser, is strongly influenced by the speed and available bandwidth. If the workstations are connected with a wide and rapid infrastructure bandwidth this is not a problem, in contrast to the remote areas where the availability of bandwidth is an issue, then showing images of 179

The Proceedings of The 7th ICTS, Bali, May 15th-16th, 2013 (ISSN: 9772338185001) WEB-based GIS applications is difficult, it is necessary to cut images [2].

2 The Proceedings of The 7th ICTS, Bali, May 15th-16th, 2013 (ISSN: ) WEB-based GIS applications is difficult, it is necessary to cut images [2]. It is hard to argue that Google Maps has not had a fundamental effect on the mapping world. While everyone else was still doing grainy static images, Google developers quietly developed the slickest interface since Gmail. Then they took terabytes of satellite imagery and road data, and just gave it all away for free [3]. KML stands for Keyhole Markup Language, which is a combination of the structure of XML / Extended Markup Language data and results from an application called Keyhole that Google has [3]. Figure 2. Digitation result in KML Software that is used to perform digitizing is Google Earth, which has facilities Placemark, Polygon, and Path sufficient for digitizing land cover to be made. Multimedia objects such as photos or videos can be inserted later using HTML tags <img src>, if the Uniform Resource Locator is too long, to be inserted in the script, then it can be shortened using a facility called ShortenURL (i.e: etc). These facilities are provided free of charge. 3 METHOD This study aims to serve as a learning tool, for selected methods and models that are relatively simple to follow, the method is a method of engineering research using throwaway prototyping model or also known as close-ended prototyping. Figure 1. KML Structure HTML / Hypertext Markup Language, HTML documents are defined by HTML elements. An HTML element is everything between the start tag and the end tag. Initial tag is often called the opening tag. End tag is often called the closing tag [4]. HTML is also required to modify and beautify the appearance of the tematic polygons as a result of map digitizing process. Some HTML TAG that will be used is <img src> <pre> <br>[4][7][8]. Digitizing is the process of determining the outer limits of the land cover, which is characterized by geographic coordinates such as latitude and longitude points, with coordinates in the form of decimal format. The results are stored in digitized with KML TAG opening and closing. Throwaway prototyping, also called close-ended prototyping.throwaway or Rapid Prototyping refers to the creation of a model that will eventually be discarded rather than becoming part of the final delivered software. After preliminary requirements gathering is accomplished, a simple working model of the system is constructed to visually show the users what their requirements may look like when they are implemented into a finished system[5]. The most important factor is the speed of development of the system. The model then becomes the starting point where the user can reexamine their expectations and clarify their requirements. When reached, the prototype model is trashed, and a formal system is developed based on the requirements in more detail [6]. 180

6-05 Google Fusion Tables As A Geographic Information System Learning Tools Figure 3 Prototype Model There are three entities in the Model Prototyping: (a)listen to Customer, (b)build / Revise and

Each translated into land cover that will be digitized (Listen to Customer), digitizing and combining into Google Fusion Tables (Build), Looking at the results of digital thematic maps have been

3 6-05 Google Fusion Tables As A Geographic Information System Learning Tools Figure 3 Prototype Model There are three entities in the Model Prototyping: (a)listen to Customer, (b)build / Revise and (c)test. Each translated into land cover that will be digitized (Listen to Customer), digitizing and combining into Google Fusion Tables (Build), Looking at the results of digital thematic maps have been completed (Test), Modifying (Revise). For more details on the flow chart below: 4 DESIGN AND IMPLEMENTATION Results from this study is an example of the of the Geographic Information System to be developed relatively quickly. In more detail are the following steps: 1. The center point coordinates of the location from the Satellite Imagery for this research is South, east. It is the center point location of Widya Mandira Catholic University campus. 2. Specified altitude eye / eye-level of the satellite image are 415m or according to your eye comfort to perform digitization. At this height, you will get the maximum pixel resolution on Google Earth imagery is ± 0.40 m after repairs (one pixel represents a 40 cm object). 3. Determines land cover such as buildings, roads, and other interesting places. 4. Digitizing Tools. Figure 5. Digitizing Tools 5. Save each land cover polygon into KML format. 6. Repeat step number 4 until all planned land cover digitized and stored in KML format. 7. Go to Google Drive: 8. Enter your Google account drive 9. Select, Create, More, Fusion Tables (Experimental) Figure 4 Flow Diagram Figure 6. Google Drive Menu to Fusion Tables 181

The Proceedings of The 7th ICTS, Bali, May 15th-16th, 2013 (ISSN: 9772338185001) 10. Perform additional tables for each KML file containing the polygons of digitized land cover results. 11.

The results showed on the TAB number three (3) under the title Map of Geometry. To make some adjustments, simply replace the layer from Map to Satellite. 13.

When compared with previous research, with cutting applications to speed up image display[2], the development of the Geographic Information System based on Cloud Computing using Google Fusion Tables

4 The Proceedings of The 7th ICTS, Bali, May 15th-16th, 2013 (ISSN: ) 10. Perform additional tables for each KML file containing the polygons of digitized land cover results. 11. Repeat until all the KML file get into the next row on the worksheet in Google Fusion Tables. Figure 9. Aditional Information for Polygons Figure 7. Fields in Fusion Tables 12. The results showed on the TAB number three (3) under the title Map of Geometry. To make some adjustments, simply replace the layer from Map to Satellite. 13. The process is relatively very fast in building a Geographic Information System and is available for students who have no programming or database skills. When compared with previous research, with cutting applications to speed up image display[2], the development of the Geographic Information System based on Cloud Computing using Google Fusion Tables will help the developer in particular who do not have a programming background. Digitization process can be done from the terminal with minimal hardware specifications, and minimal internet connection, in this study using an internet connection with only 64 to 128kbps bandwidth. The availability of supporting data such as images or videos can be done simply by inserting the source URL, and it can be placed in different locations to share, so it does not require local storage media. 5 CONCLUSION AND RESULT Figure 8. Land Cover result from KML From these results are obtained some conclusions as follow: 1. Google Fusion Tables provide an easy way to develop a Geographic Information System for all disciplines. 2. Developers do not need to master the complex programming techniques and mastery of the basic database management. 3. The results of the GIS, can be shared to fellow users and owners Google account. 4. For the purposes of wider sharing, the iframe code could be pasted into other websites for publication. 5. Availability of learning development of GIS is easy, relatively inexpensive and affordable for all disciplines. 182

5 6-05 Google Fusion Tables As A Geographic Information System Learning Tools These are suggestions for further research as follows: 1. As a learning tool, it should be prepared in supporting data such as images, that have been uploaded to the site preceeding public share, to facilitate the participants / students, in implementing the code URL. 2. Image storage location should be able to use the PC or on the online storage. REFERENCE [1] Hector Gonzalez, Alon Halevy, Christian S. Jensen, Anno Langen, Jayant Madhavan, Rebecca Shapley, Warren Shen., 2010: "Google Fusion Tables: Data Management, Integration and Collaboration in the Cloud", Pages ACM New York, NY, USA 2010 SoCC '10: Proceedings of the 1st ACM symposium on Cloud computing. ISBN: [2] Adri Gabriel Sooai, Aplikasi Pemotongan Citra Pada Web Based GIS Prototype Untuk Mempercepat Penampilan Lokasi Pada Peta Raster Berdasarkan Koordinat GPS, 2010 Proceeding SEMNAS Magister Manajemen Teknologi, Institut Teknologi Sepuluh November - Surabaya. ISBN [3] Michael Purvis, Jeffrey Sambells, Cameron Turner, Beginning Googgle maps Applications with PHP and AJAX, 2006, Appress, ISBN [4] John Wiley, Learn HTML and CSS with w3schools, 2010, Wiley Publishing, Inc, ISBN: [5] John Crinnion: Evolutionary Systems Development, a practical guide to the use of prototyping within a structured systems methodology. Plenum Press, New York, Page 18. [6] Roger S. Pressman, software Engineering A Practitioner Approach, 2001, McGraw-Hill, ISBN [7] John Wiley, Learn JavaScript and AJAX with w3schools, 2010, Wiley Publishing, Inc, ISBN: [8] Peter Lubbers, Brian Albers, Frank Salim, Pro HTML5 Programming: Powerful APIs for Richer Internet Application Development Copyright 2010, ISBN

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Google Maps Mashups WORKSHOP. Jeff Blossom, Senior GIS Specialist Center for Geographic Analysis. Harvard University gis.harvard.

Google Maps Mashups WORKSHOP. Jeff Blossom, Senior GIS Specialist Center for Geographic Analysis. Harvard University gis.harvard. Google Maps Mashups WORKSHOP Jeff Blossom, Senior GIS Specialist Center for Geographic Analysis Harvard University gis.harvard.edu Fall, 2012 Objectives: Workshop objectives and flow 1) In 2 hour, hands