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Posts Tagged ‘carte’

Running in Madrid. A GIS approach!

2018/05/22

Love running. I have been running without stop (well, three months after my Marathon in Valencia i had to stop due to a minor surgery) for the last -almost- four years. I love running and and love GIS and statistics. This is a bomb combination.

I wanted to figure out visually where i normally run. Well, i know it, that’s true, but its just what i remember, i go here and there. I love running in Casa de Campo and in Parque Lineal del Manzanares mostly, but not only. Also i have run in every country i have the chance to visit, normally for business purposes.

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I have run in South Africa (Cape Town), in Tunis (Tunis), in Santiago (Chile), in Lima (Peru), in Cannes (France) and i dont even remember where else… running5

Anyway, these density maps performed in Global Mapper overlay the geometry lines saved out my running application (Garmin Connect). and once they are exported to points, i can generate a density map, chosing a legend easy to understand and i overlay to Google Earth so its also easy to be sent if needed be (why for? i don’t know!).

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Anyway, hope you guys like it.

Alberto CONCEJAL
MSc GIS

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DTM from SRTM? Let’s compare sources using RMSE (Root Mean Square Error) and a gaussian kernell density map

2014/10/29

I guess we all can make a DTM out of many sources but SRTM is one of the most common ones, right?. Then let’s learn from this very simple approach how close we are from the SRTM raw data.

  1. Selecting a not very big representative area to be able to handle it,
  2. exporting raster to polygon (from SRTM 3 arcsec/90m) dataset 1
  3. exporting raster to polygon 30m (our DTM dataset) dataset 2
  4. exporting to POIs 30m (our DTM dataset) dataset 2b
  5. Spatial join POIs dataset 2b vs dataset 1
  6. RMSE
  7. visualizing delta using a density map/gaussian kernell +appropriate symbolization

In yellow we see theres a full correspondence between SRTM and our DTM dataset and in blue there’s a ‘hole’ and in red there’s a ‘mountain’, this means it’s in here where the shift is more important.

This way we can highlight if sources are OK.

It’s simple but it works. How do you like it?. Please feel free to send some feedbak.
(Software used: ArcGIS 10.1, Global Mapper 13.2)

Cheers,
Alberto Concejal
MSc GIS, QC

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density maps parameters

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Spatial join between both DTM datasets

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Density map for highlighting differences between both datasets (ours and SRTM’s)

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RMSE. It’s not too big so there’s need to visualize to find potential bizarre spots

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bizarre DTM heights