Maps and the Internet

Through Scale and Time

4601.1 - GeoTuple: an Open Source Multiscale Dynamic Geo-Analytics Service

Tuesday, July 4
2:50 PM - 3:10 PM
Location: Delaware A

This article describes a framework, based on open source tools, which provides the possibility of performing point-based geospatial analytics dynamically over a range of map scales.
The study is divided into two phases: first, compiling the geographic data themes in a point grid adequately designed to encode and access this information; second, visualizing and analyzing the themes on a map by developing a Web application, offering an on-demand service.

The primary goal is to enable exploratory data analysis of geographic phenomena, specifically using the statistical package R. Despite its strong capabilities in this area (1), R is arguably underutilized by the geographic community (2).
The second goal is to define an appropriate geographic database structure, and a procedure simplifying the often complex task of combining heterogeneous data sources into a uniform spatial resolution (3).

Database: Design and Compilation Workflow
To facilitate the data compilation procedure into a PostGIS database, a workflow for loading and aggregating manageable units of data by area was developed. Initially, a regular grid, serving as sampling points, is defined at a specified resolution. Data is then processed according to thematic type (e.g population density) and assigned as attribute values to their closest point (e.g polygon intersect).
A set of scripts streamlines the processing (possibly in parallel) of data themes by a specified geographic extent, and subsequent appending to a master production database.

Web service: Design and Architecture
A web application, based on OpenCPU (4), integrating the PostGIS database and the statistical package R was developed. OpenCPU facilitates the calling of R functions through AJAX thereby effectively streaming database points via R to a browser client. For example: calculating the linear correlation (cor) between two data themes.
Points are extracted at a given resolution (map scale), encoded as JSON and rendered on a map interface. The overall load is minimized by coordinating resolution to zoom level, such that an optimal number of points are being processed/transferred as the user zooms the map.

Analytics Experiments
Openly available data including elevation, landcover, major roads (distance from) and population, covering a major portion of the state of California, were captured at 250 meter resolution, loaded into a database and configured as a custom OpenCPU server app.
The system was deployed on a modest Google Cloud Compute Engine Instance (2 vCPUs, 7.5 GB).

Results and Discussion
The study revealed that “large” datasets can be effectively accessed and analyzed dynamically as a web service. Future testing on user and computational load are to be performed.
Additionally, it is critically important to ensure that assumptions, such as spatial autocorrelation, of the statistical models are met and that the user is informed or guided to properly account for them.

1. Bivand, R. S., Pebesma, E. J., & Gómez-Rubio, V. (2013). Applied spatial data analysis with R. New York, Springer.
2. Robin Lovelace, Rachel Oldroyd Centre for Spatial Analysis and Policy, University of Leeds. Geomatics Workbooks n° 12 – "FOSS4G Europe Como 2015" Teaching R as a GIS: problems, solutions and lessons learned.
3. Gloria Re Calegari, Irene Celino CEFRIEL – Politecnico di Milano. Geomatics Workbooks n° 12 – "FOSS4G Europe Como 2015" A Data Scientist Exploration in the World of Heterogeneous Open Geospatial Data.
4. Ooms, Jeroen. "The OpenCPU system: Towards a universal interface for scientific computing through separation of concerns." arXiv preprint arXiv:1406.4806 (2014).

Roland Hansson

Nova Spatial

Roland is a full stack developer with extensive experience in GIS, mapping and databases. He enjoys to tinker with technology and find new ways to work with geospatial information.
He has been instrumental in the successful development and implementation of solutions, involving: map production, cartography, data management/modeling, spatial analysis, and visualization for national agencies around the world.


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Rex G. Cammack

Associate Professor
University of Nebraska Omaha

Dr. Cammack is currently the Co-Chair of the ICA Commission on Maps and the Internet and serves as the Geography Program Director at University of Nebraska Omaha. He as been and active member of the ICA, AAG and NACIS for 20 years. He primary research interest are in Web Mapping and Location Based Services.


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4601.1 - GeoTuple: an Open Source Multiscale Dynamic Geo-Analytics Service

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