Computational Planning

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“Blue Temple� workflow

Problematic: Where: How:

Where to concentrate actions to achieve maximum impact ? Energy distribution, environmental protection, education / medical programs Mapping descrepencies, vulnerabilities and need for development

Synopsis:

Today, data is being collected everywhere, there are many initiatives in creating dashboards to visualize them dynamically. However, the impact simple visualizations have on people is very questionable. Moreover, accessibility is monitored with different levels of security allowances. These elitists tools are reserved for a selected class of decision makers. We are trying to redestribute information in a format that is a conversation started instead of decision making tool. Data is public, therefore should be accessible to public, no matter their digital litteracy and wealth.

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Data acquisition - Harvesting - Mining

Source of the data we have used: - MIMU (Myanmar Information Management Unit) - NASA (SRTM) Shuttle Radar Topography Mission - NASA Nightlight satellite recordings - Open Street Map (.osm) - ESRI (Environmental Systems Research Institute) - Shapefiles (.shp) on government websites - Chin State government (MOC, MOHT) - Tourism Agencies (need to sign NDAs) - Personal recordings - Asia Foundation TDI data (availble since May 20) - One Map Myanmar ?? - ...

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Data Sets - Benchmarked

Data Evaluation Example: - Incompleatness - Inconcessnet - Trustworthyness -

Data Analysis

3 Macro programming (Python) Grasshopper on Rhino6 Re-formating to usuable configuration

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Influencers - Coefficients

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Topography Modelling

Data Evaluation

Democratization of data

Examples: - Accessibility - Proximity to different services - Topographic coanditions -

Visualization and representation Intangible data


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Computational Planning by Raphaël Ascoli - Issuu