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 ?? - ...

2

Data Sets - Benchmarked

Data Evaluation Example: - Incompleatness - Inconcessnet - Trustworthyness -

Data Analysis

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

4

Influencers - Coefficients

5

Topography Modelling

Data Evaluation

Democratization of data

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

Visualization and representation Intangible data


ShanTou Competition , GuangDong, China - 2017 - Land Value Analysis

The given value of the land depends on its location. We have narrowed the influence of the value to five different criterias. Each criteria have been assigned with a coefficient that varies according to its importance. The distance each plot has to the generated 3d topography assignes its final value. The blue color corresponds to the current land price, while the red corresponds to the current land price times its value factor. This study was made according to our original urban design strategy. After further exchange and discussion, the model can be adapted to new requirements.


Ngapali Resort Plannig, Rhanike, Myanmar - 2017 - Land Value Analysis The given value of the land depends on its location.We have narrowed the influence of the value to five different criterias. Each criteria have been assigned with a coefficient that varies according to its importance. The distanceeachplothastothegenerated3dtopographyassigneditsfinalvalue.

Proximity to water: 0.5

Road access: 0.35

Urban design strategy: 0.5

Seclusion and views: 0.35

Constructiblity slope: 2

Tree location: 0.35


M.A.P.S

{ Myanmar Algorithmic Parametrical Systems }

\\ blue temple co., ltd. raphaĂŤl monnier \\

Source of the data we have used: - MIMU - Myanmar Information Management Unit (excel spread sheet) - NASA - (SRTM) Shuttle Radar Topography Mission + Nightlight satellite recordings - Open Street Map (.osm) - ESRI ArcGIS Base Maps - Environmental Systems Research Institute - Blue Temple - Data analysis / Treatment - Shapefiles (.shp) format of geographic data - Chin State government - MOC, MOHT - Personal recordings - Asia Foundation TDI data

{0;0} 0. Myanmar 1. LON: 96.511886379 2. LAT: 21.12494983


grasshopper - parametrical scripting rhino6 - 3D modelling

importing data - analysis visual representation


Source: “In Plain Sight” by Diller Scofidio + Renfro


BaselineData_Census_MIMU_2015

BlackMarble_2016_D1_geo

List_all_dams_MRR


mapping 4 change

kachin state topography \\ NASA sattelite recordings

Credit: NASA - (SRTM) Shuttle Radar Topography Mission data procesed by blue temple., co.





Education

Religious

Agriculture

DisasterRiskReduction

Nutrition

Coordination

Infrastructure

Governance

Infrastructure



Data from Chin ESE Department provided by Bernard Robin- Summeo Consulting

Production of energy in Chin State


BlackMarble_2016_D1_geo // Chin State // Myanmar

Suoni Satellite photo remastered

Amplified photos

Village names that are the most light


Census 2014 // Chin State // Myanmar

3D mesh

Contour lines

Village names the most populated


Processed data population/amount of light // Chin State // Myanmar

Artificial processed topography

Village with the most need to lighting

Decision making tool for development


Implementation of mini grid

Nothern Chin State

Southern Chin State


thank you

M.A.P.S

{ Myanmar Algorithmic Parametrical Systems }

\\ blue temple co., ltd. raphaël monnier \\

Credit: NASA Earth Observatory images by Joshua Stevens Suomi NPP VIIRS data from Miguel Román NASA’s Goddard Space Flight Center


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