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Posts Tagged ‘lidar’

Descargas del CNIG. Open Source bien hecho!

2016/02/08

Hola amigos del GIS,
Por motivos de trabajo que no vienen al caso, he tenido que bucear de manera sistemática la web de descargas del CNIG. http://centrodedescargas.cnig.es/CentroDescargas/inicio.do
Una maravilla.

cnig-20160208-01

Por motivos que tampoco viene al caso, he de hacer esto mismo de vez en cuando en todos los Institutos cartográficos del mundo y el del CNIG es sin duda en el que me resulta más fácil, en el que el modelo de datos en más lógico y en el que los links son más fiables de todo el mundo. La única obligación es la atribución obligatoria de los datos. ¿No es mucho pedir, no? Desde el día 27 de diciembre, los datos del IGN son libres CC By 4.0.
https://creativecommons.org/licenses/by/4.0/

Por tanto es obligatorio que mencione la procedencia a pie de imagen, créditos, etc.., sobre todo en publicaciones, usos comerciales, artículos, etc… (Por ejemplo puede poner “<tal dato> CC by instituto Geográfico Nacional” o más bien “derivado de <tal dato” CC by ign.es” o similares…).

cnig-20160208-02

Ya sea porque necesitemos las imágenes del PNOA (Plan Nacional de Ortofotografía Aérea), un modelo digital del terreno de alta resolución o imágenes históricas de nuestro pueblo… tan solo hay que bucear un poco en el catálogo de geodatos del Instituto Geográfico Nacional (Centro Nacional de Información Geográfica) y los conseguiremos.

Por ejemplo, la semana pasada tuve que encontrar datos sobre algunas ciudades españolas para hacer varios escenarios 3D para un cliente y aquí encontré por un lado un DSM 5m elaborado con fuentes LIDAR, por otro lado me bajé de Cartociudad los datos relativos a vectores lineales, manzanas y luego desde la web de CATASTRO (https://www.sedecatastro.gob.es/OVCFrames.aspx?TIPO=TIT&a=masiv) me bajé las geometrías de todos los edificios de la ciudad (que planeo geoprocesar para eliminar las formas no deseadas y para adjudicar alturas precisas gracias al LIDAR bajado con anterioridad).

Por qué no añadir geometrías de Open Street Maps (https://www.openstreetmap.org/export) o de la propia Base Topográfica Nacional BTN25 para completar dicho escenario?

barcelona-bldg-osm-capture-20160112
MADRID-GISDATA

La verdad amigos es que desde que empezó a funcionar el Open Data, los Geógrafos y derivados tenemos mucho con lo que ‘jugar’ para hacer nuestros análisis.
http://idee.es/

Espero que os resulte interesante.

Un saludo cordial,

Alberto
Geógrafo/ Máster SIG UAH/ Diseñador Multimedia

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RSME comparing LIDAR data with a third party’s 3D dataset

2014/05/02

I would like to share with you an easy analysis i have been working in the last days. I had a vector dataset of buildings and i knew how high they were (there was a field called ‘AGL’ or Above Ground Level) and a LIDAR 2m resolution dataset over the city of London. My aim was comparing both sources, understanding LIDAR data was the actual reality (or a closer version to it) and my source of 3D buildings was the dataset i needed to deliver to my customer…  Te actual height of those 3D buildings had been extracted using stereo photogrammetry methods. I also needed to focus on residential data, so heights below 15m… So make it easy. The question was:

How accurate is my dataset of residential buildings over London?. Which is the RMSE measuring them both?

I used Global Mapper v.13.2 (b062012) and ArcGIS 10.0 (b3200)

This is the 2m resolution LIDAR data provided by geomatics-group.co.uk

LIDAR-01

I also needed to get a layer of points out of this dataset so i used Global Mapper and went to Files/Export elevation grid format and choose ASCII as the format.LIDAR-06

This is the layer of buildings and their AGL as label
LIDAR-02

I flagged those residential buildings
LIDAR-03

and using ArcGIS i performed a Spatial Analysis using Arctoolbox/Spatial analysis to join the Lidar heights in ASCII format and the residential heights… to be able to measure the difference between both datasets

this way i got a new vector layer which table contained both elevation fields (Lidar and my 3D buildings)
LIDAR-07

As you can see, i added a new field in ArcGis using table/add field and added ‘compare’ and SQL [“AGL”- “ELEVATION”]
LIDAR-04

then i measured it visually using a density grid in Global Mapper. Create density Grid.
LIDAR-05

And finally measured the RMSE by opening the table in excell format and usign the actual formula for extracting RSME values:

= SQRT(SUMSQ(M1:Mn)/COUNTA(M1:Mn)) —> Note this formula is only valid for this case. You’d need to update Mx values using yours:-)

LIDAR-07

Wow! a very high value. Does this value corresponds to our accuracy figures? Yes? No?.

Now it’s the time for decission makers to bring into action!

LIDAR-08

And what about some geostatistical analysis. I performed this using North East Trends in ArcGis. We can see from West to East there’s no variation  but we can see it increases the error the further the south…

LIDAR-09

So this is the area concentrating the higher differences comparing both datasets.

Hope you liked the analysis, if so…share!!!!

LIDAR-10

Alberto CONCEJAL
MSc GIS

 

Visualizing LAS LIDAR data with sketch-up

2010/07/02

While trying to figure out the way to get a 3D model from raw Lidar data, I first opened my LAS file in Global Mapper, exported it to DXF, imported then into Sketch-up and after recording a few scenes, I saved the animation… this is it!.

Alberto

Using Excel to calculate the RMSE for LiDAR vertical ground control points

2010/06/30

(source: http://dominoc925.blogspot.com/)

The height accuracy of the collected LiDAR data can be verified by comparing with independently surveyed ground control points on hard, flat, open surfaces. It is essentially just calculating the height differences for all the control points and then determining the height root mean squared error (RMSE) or differences. Most LiDAR processing software have the reporting function built-in. However, plain Microsoft Excel can also do the job (except for extracting the elevation from the LiDAR data).

Assuming that you are able to calculate the height differences for all the control points and place in a spreadsheet as shown in the figure below. I have a column of delta Z values in column A.

Then to calculate the RMS value for the elevation differences, I can do the following.

  1. In a cell, type in the formula:= SQRT(SUMSQ(A2:A18)/COUNTA(A2:A18))where A2:A18 are the values from cell A2 to A18 in the spreadsheet. Simply replace these with the actual locations on your spreadsheet.
  2. Press RETURN.
    The RMSE value is calculated.

(source: http://dominoc925.blogspot.com/)