Development of Quality Control Tools for ARCMAP using Python
P. Chinnammalu1, Mahesh Ravindranathan2, Swapan Chowhan3, J. Venkateshr4
1P. Chinnammalu, M. Tech Student, SIT, JNTU, Hyderabad, India.
2R. Mahesh, Deputy Surveyor General, IISM, Survey of India, Hyderabad, India.
3Swapan Chowhan, M. Tech Student, SIT, JNTU, Hyderabad, India
4J. Venkatesh, Associate Professor, CSIT, JNTU, Hyderabad, India.
Manuscript received on 20 August 2019. | Revised Manuscript received on 07 September 2019. | Manuscript published on 30 September 2019. | PP: 3352-3359 | Volume-8 Issue-11, September 2019. | Retrieval Number: K24610981119/2019©BEIESP | DOI: 10.35940/ijitee.K2461.0981119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Topological error free data in the database is very essential for Geographic Information System (GIS) analysis. To minimize some of the most common GIS errors, five Quality Assessment/Quality Control tools has indigenously discussed in this paper, namely Auto registration tool, Dangles correction tool, Irrelevant points removal Tool, Delete polygon less than 4 vertices and Connect and Split using the programming language Python. Tools are developed for ArcMap environment for more effective data cleaning and validation. ArcMap is one of the main components in Architecture Geographical Information system (ArcGIS) suite. These tools will be helpful to identify the possible errors in a particular sheet and will navigate user to the error positions. These tools not only finds the errors they also provides several solutions to solve those errors in automatic or semi-automatic mode, hence making the data best suited for use in GIS. This paper describes the brief details of all the 5 developed tools, and also demonstrates the benefits of applying these tools.
Keywords: QA/QC Tools, ArcMap, ArcGIS, Data Cleaning
Scope of the Article: Application Artificial Intelligence and machine learning in the Field of Network and Database.