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Archive for January, 2016

Risk exposure. Geoprocessing using Open Source Data!! Next steps!!

2016/01/29

Now that we have completed a first example, let’s continue with a real-world one. Its important working on a Data Model to define what we understand as a Risk and how important this is. Meaning. High voltage power lines are an actual risk but the closer we are, i guess the bigger the risk is, meaning i.e 3 if we are within 50m and 1 if we are 150m away… It’s only a guess.

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Same thing related to antennas, Petrol stations, etc.

This is my Data Model defined over the city of Madrid, Spain.

1 LINES- Roads speed >50 km/h within 100m risk=3
2 LINES- Power lines within 100m risk=3

3 POINTS-

Antenna,
High voltage towers,
Petrol stations:

risk if within 50m=3; risk if within 100m=2; risk if within 150m=1; 

4 AREAS-

Cement factories,
Electric Sub-stations,
Waste storage facilities:

risk if within 50m=3; risk if within 100m=2; risk if within 150m=1; 

(NOTE: You can choose your own risk thresholds and importance. Also note these information downloaded from Open Source data (Cartociudad, CNIG) has not been double checked and it has been used as is).

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How is this risk, or these combination of risks impacting in the population of Madrid?

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Can we extrapolate these patterns to other cities in the world?
We will definitely continue  this analysis shortly.

You can also visuallize this analysis using CartoDB, the field regarding “risk exposure level” is called ALL2, and ranges from 2 to 12:

Software: ArcGIS 10.3, Global Mapper 17, CartoDB

Please share if you enjoyed it… or just to say hello!

Alberto C
MSc GIS and remote sensing UAH

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Risk exposure. First steps

2016/01/15

Knowing how to geoprocess features is key if what we want is assesing risk exposure. What’s a risk? Which are the risks? Where are the risks? How important a risk is?

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Jugando con CartoDB

2016/01/15

Hace ya mucho tiempo que he oído hablar de CartoDB y que vengo practicando en su página web a visualizar bases de datos sencillas.

  1. Crea una cuenta
  2. Incorpora tus datos o tómalos de la galería
  3. Selecciona en modo datos la columna que quieres simbolizar/visualizar
  4. Conviértela en NUMBER si estuviera en STRING
  5. Selecciona en modo mapa en WIZARD
  6. COROPLETAS, columna _población
  7. Visualiza el resultado

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