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21 November 2019 Thematic geo-visualization for socio-economic data representation in special region of Yogyakarta
Sudaryatno Sudaryatno, Totok Wahyu Wibowo, Zulfa Nur'aini 'Afifah, Shafiera Rosa El-Yasha, Achmad Rofi'i
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Proceedings Volume 11311, Sixth Geoinformation Science Symposium; 113110H (2019) https://doi.org/10.1117/12.2547320
Event: Sixth Geoinformation Science Symposium, 2019, Yogyakarta, Indonesia
Abstract
Data related to socio-economic activities in Indonesia mostly used statistical data. Statistics for large numbers of socioeconomics will make it difficult to interpret and analyze because it consists of many columns and rows with each value. Geo-visualization is a visualization of data represented in a geographic coordinate system. Socio-economic statistics can be visualized to facilitate the process of spatial analysis data that considers spatial surface of earth. Study area is in Special Region of Yogyakarta. This study aims to (1) Select, test and find out color symbol scheme most effective classification method for choropleth mapping of Demographic Map, (2) Mapping happiness profile of population using small area estimation method, (3) Analyzing tourist trends based on Instagram data using space time cube visualization. Secondary data used are population and happiness, while primary data uses social media data for tourist visualization. Geo-visualization of population and happiness used choropleth method. In social media geo-visualization for tourists using space time cube geo-visualization with hexagonal tessellation cells. The results obtained are population maps with best classification scheme, happiness maps at different scale levels, and tourist map using space time cube in Yogyakarta Special Region.
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Sudaryatno Sudaryatno, Totok Wahyu Wibowo, Zulfa Nur'aini 'Afifah, Shafiera Rosa El-Yasha, and Achmad Rofi'i "Thematic geo-visualization for socio-economic data representation in special region of Yogyakarta", Proc. SPIE 11311, Sixth Geoinformation Science Symposium, 113110H (21 November 2019); https://doi.org/10.1117/12.2547320
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KEYWORDS
Visualization
Statistical analysis
Associative arrays
Data modeling
Image classification
Error analysis
Visual analytics
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