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# urbansprawl | ||
Urbansprawl is an open framework for calculating spatial urban sprawl indices using open data | ||
# Urbansprawl | ||
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The urbansprawl project provides an open framework to assess the urban sprawl phenomenon. | ||
It uses OpenStreetMap data to calculate its sprawling indices, divided in Accessibility, Land use mix, and Dispersion. | ||
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**For more details, refer to:** | ||
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* Gervasoni Luciano, Bosch Martí, Fenet Serge, and Sturm Peter. 2016. "[A framework for evaluating urban land use mix from crowd-sourcing data](https://hal.inria.fr/hal-01396792)." 2nd International Workshop on Big Data for Sustainable Development. | ||
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* Gervasoni Luciano, Bosch Martí, Fenet Serge, and Sturm Peter. 2017. "[LUM_OSM: une plateforme pour l'évaluation de la mixité urbaine à partir de données participatives](https://hal.inria.fr/hal-01548341)." GAST Workshop, Conférence Extraction et Gestion de Connaissances (EGC 2017). | ||
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* Gervasoni Luciano, Bosch Martí, Fenet Serge, and Sturm Peter. 2017. "[Calculating spatial urban sprawl indices using | ||
open data](https://hal.inria.fr/hal-01535469)." 15th International Conference on Computers in Urban Planning and Urban Management. | ||
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## Dependencies | ||
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urbansprawl works with Python 2+3. | ||
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- Python dependencies: | ||
```sh | ||
osmnx utm scipy statsmodels h5py | ||
``` | ||
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* Using anaconda: | ||
```sh | ||
conda update -c conda-forge --all | ||
conda install -c conda-forge osmnx utm scipy statsmodels h5py | ||
``` | ||
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## Example | ||
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PostGIS-enabled PostgreSQL databases are used in this framework (refer to [OSM2PGSQL tools](https://mapzen.com/data/metro-extracts/)): | ||
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Results are depicted for the city of **Grenoble, France**: | ||
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- Locations and densities of residential and activity land usages | ||
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<img src="examples/images/Grenoble_Activity_points.png" width="550"> | ||
<img src="examples/images/Grenoble_Activity_densities.png" width="550"> | ||
<img src="examples/images/Grenoble_Residential_points.png" width="550"> | ||
<img src="examples/images/Grenoble_Residential_densities.png" width="550"> | ||
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- Street network | ||
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<img src="examples/images/Grenoble.png" width="550"> | ||
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- Buildings | ||
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<img src="examples/images/Grenoble_Buildings.png" width="550"> | ||
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**Sprawling indices:** | ||
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- Land use mix indices | ||
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<img src="examples/images/Grenoble_Land_use_mix.png" width="550"> | ||
<img src="examples/images/Grenoble_Bubble_land_use_mix.png" width="550"> | ||
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- Accessibility indices | ||
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<img src="examples/images/Grenoble_Accessibility.png" width="550"> | ||
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- Dispersion indices | ||
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<img src="examples/images/Grenoble_Dispersion.png" width="550"> |
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examples/input_data/Zagreb_Croatia/zagreb_croatia_osm_point.prj
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GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]] |
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examples/input_data/Zagreb_Croatia/zagreb_croatia_osm_polygon.prj
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GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]] |
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