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This tool converts geoJSON or topoJSON polygon file to the "Nodes" CSV file with longitude and latitude coordinates of polygons centroids. Click "Submit" to download the file to your browser's download folder.
Flow normalization helps remove the effect of total flow or population size by calculating modularity, i.e., the difference between the actual flow and the expected volume of flow for each pair of locations (nodes). We use the adjusted flow volume formula below to calculate the expected number of flows between locations.
For more details in modularity function please refer to Guo (2009).
1. Select your flow file with columns: origin, destination, and volume, then click "Submit".
2. Once processed, your file will be downloaded into your browser's download folder. It will have columns for origin, destination, modularity, rawvolume, and expectation. The modularity column reflects the difference between observed (rawvolume) and expected flow (expectation) using the given formula.
3. Modularity can be negative or positive. Negative values indicate fewer observed flows, while positive values suggest more observed flows than expected between origins and destinations.
This is a testing tool to connect to the backend Java code, which will provide more complicated analysis tools for pre-processing your data before visualization.
Only for testing use! please input your file below:
Testing result:
Example data sets are available to download and visualize with FlowMapper in the following link: https://github.com/geo-social/flowmapper.
Version: 1.1.4
Developers: Maeve Biscupski (2023 06-10), Geng Tian (2020-2022)
Supervisor/Developer: Caglar Koylu
Citation: Please cite the reference below if you use FlowMapper in a manuscript:
Koylu, C., Tian, G., & Windsor, M. (2022). FlowMapper.org: A web-based framework for designing origin-destination flow maps, Journal of Maps, 19:1, DOI:10.1080/17445647.2021.1996479.
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Error.
Please make sure the origin and destination IDs used in flow CSV file exist in the node file. Please upload your files and select the matching ID columns.
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