An Integrated Approach of GIS and Spatial Data Mining in Big Data | Zendy

Hemlata Goyal | Zendy; Chilka Sharma | Zendy; Nisheeth Joshi | Zendy

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An Integrated Approach of GIS and Spatial Data Mining in Big Data

Author(s) -

Hemlata Goyal,

Chilka Sharma,

Nisheeth Joshi

Publication year - 2017

Publication title -

international journal of computer applications

Language(s) - English

Resource type - Journals

ISSN - 0975-8887

DOI - 10.5120/ijca2017914012

Subject(s) - computer science , data science , spatial analysis , data mining , big data , information retrieval , remote sensing , geology

An explosive growth of spatial data has been demanding to Spatial Data Mining (SDM) technology, emerging as a innovative area for spatial data analysis. Geographical Information System (GIS) contains heterogeneous data from multidisciplinary sources in different formats. Geodatabase is the repository of GIS data, representing spatial attributes, with respect to location. Rapidly increasing satellite imagery and geodatabases generates huge data volume related to real world and natural resources such as soil, water, temperature, vegetation, forest cover etc. Inferring information from geodatabases has gained value using computational algorithms. The intent of this paper is to introduce with GIS, and spatial data mining, GIS and SDM tools, algorithmic approaches, issues and challenges, and role of spatial association rule mining in big data of GIS.

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