Advertisements

Archive for the ‘lidar’ Category

LIDAR Madrid LAZ 20cm

2018/05/18

Ya van varias veces en el último mes que alguien no especialista en temas geográficos-cartográficos me habla de ‘ese sistema’ de láser para saber ‘la altura del terreno’ y es que la verdad es que LIDAR parece magia. Es bastante increible que pase un avión con una tecnología invisible a ojos humanos y que se genere una nube de billones de puntos que responde al 100% a la realidad. Es tan fácil capturar el interés de la gente con cosas que se parecen tanto a las cosas que manejas a diario… la montaña de al lado de casa, el río, el edificio, la manzana…

Si además podemos ‘pintar’ esas geometrías con datos provinientes de diferentes fuentes pues el resultado está a la vista: se empieza a generalizar el interés.

Y eso, para un geógrafo culo-inquieto como yo, deseoso de explicarse y buscar aplicaciones para esto o lo otro… mola. Y mucho.

Y sie sos datos están a libre disposición de la ciudadanía bajo el espectro del Open Data o Datos Abiertos, si podemos superponer otras capas pertinentes como por ejemplo los edificios de catastro y todas sus subparcelas catalogadas… pues miel sobre hojuelas.

Aquí algunos ejemplos:

lidar01.png

lidar02.png

lidar03.png

 

Advertisements

Comparación de DTM usando Global Mapper 17.0.1

2016/02/12

Hagamos hoy algo sencillo, comparar, primero cualitativamente (visualmente) y después cuantitativamente dos DTM. Por un lado elegimos una fuente muy usual, SRTM de 3 arc sec (aproximadamente 90m) con un DTM derivado de Fotogrametría Stereo.

  • Comparación CUALITATIVA (i.e visual)
  • Comparación CUANTITATIVA (i.e RMSE)

Abrimos por un lado un DTM cuya fuente sea SRTM, en este caso me he conectado via WMS (Web Mapping Service) a través del data online disponible dentro de la misma aplicación Global Mapper (File/Download Online Imagery/data). La resolución es de aproximadamente 90m (3 arc sec).

DTM-COMPARISON-20160212

Por otro lado he encontrado este DTM cuya fuente conozco (Stereo Photogrammetry). La resolución es de 5m.

DTM-COMPARISON-20160212-02

A través de la herramienta ‘digitizer tool’ (Tools/Digitizer) seleccionamos una línea dibujada al azar sobre los dos. Botón derecho del ratón-> analysis/measurement/path profile. Exporto ambas imágenes (es importante en path setup definir un mismo mínimo y máximo para poder compararlas adecuadamente).

Con Photoshop superpongo (Layer display/ multiply) ambas imágenes y veo cuán diferente son.

DTM-COMPARISON-20160212-03

Esto nos da una primera idea de la comparación, pero vayamos un poco más allá: ¿Cuál es el RMSE (Error medio cuadrático, Root Mean Square Error) entre ambas bases de datos?.

DTM-COMPARISON-20160212-04

Esta es una medida de desviación que nos va a definir mucho más exactamente que una simple visualización. Podéis ver algo más desarrollado este punto en este link de esta misma página:

https://geovisualization.net/2010/06/30/using-excel-to-calculate-the-rmse-for-lidar-vertical-ground-control-points/

DTM-COMPARISON-20160212-05

Ahora tan solo hemos de verificar que esta cifra sea la correcta teniendo en cuenta los valores de precisión prometidos en la entrega.

Espero que os haya resultado interesante, si así es, no olvidéis comentar, compartir o simplemente decir Hola. Cualquiera de estas opciones es apreciada.

Un saludo cordial,
Alberto CONCEJAL
MSc GIS and Remote Sensing

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

Remote Sensing, Photogrammetry, Lidar and Landuse IGN Spain

2014/11/18

teledeteccion-fotogrametria-lidar-usos-del-suelo-ign-20141118b

A few more lines for leting you know again that i passed this other course just now in Instituto Geográfico of Spain (IGN).

Remote Sensing, Photogrammetry, Lidar and Landuse, a comprehensive 40h update on relevant information i need tu use on a daily basis. This ‘update’ helps me to better understand what i am working with and this way, being able to properly describe it for my daily analysis,

HTML High resolution DTM visualization using Quantum GIS (Qgis)

2014/11/03

This QGIS Plugin, Qgis2threejs, exports terrain data, map canvas image and vector data to your web browser!!

3dvisualizatio-DTM-QGIS-20141103

All you have to do is opening the DTM in Qgis (2.4.0 Chugiak), go to plugins library and install Qgis2threejs.

3dvisualizatio-DTM-QGIS-20141103-03

Once its installed you will see this icon on screen iconand you will need to clic on it.

3dvisualizatio-DTM-QGIS-20141103-04

Then choosing the parameters of the visualization and voilá!!

I have used a 5m DTM which source was LIDAR so the quality is very good

3dvisualizatio-DTM-QGIS-20141103-05

Hope you guys like it. Feedback would be greatly appreciated.

Alberto Concejal
MSc GIS and Quality Control
albertoconcejal [at] gmail.com

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

 

Airmap: UAV aerial surveying technology

2012/06/10

The most efficient way to monitor our environment is from above. Traditionally, aerial photography and mapping is a costly and time consuming business. However, by using our UAV technology, we are able to offer a cost and time effective solution for your aerial photography and mapping needs. Obtaining high resolution Orthorectified image mosaics and Digital Elevation Models has never been this easy.

Q: Can the UAV fly in all weather conditions?

A: Technically, our UAV can fly with winds up to 7 m/s (i.e. moderate breeze), in low-visibility conditions, or even at night. Although light rain will usually not affect its flight characteristics, the swinglet is not water-proof and should therefore not be used when raining or snowing. For best image quality, the UAV should be used on clear days with light wind (up to 5 m/s, i.e. a normal breeze is fine).

Q: What are the specifications of the camera used in the UAV?

A: The UAV is equipped with a 12 MP compact camera with a focal length of 24 mm (in 35-mm equivalent). The resulting ground resolution is adjusted by choosing an appropriate flight altitude (typically between 50 and 1000 metres above ground) and will range from 2 to 40 cm/pixels.

Q: What is the area that can be typically imaged during one flight?

A: This depends on the flight altitude (and thus the ground resolution): At 140 m (ground resolution of 5 cm/pixel), one picture covers 0.03 square km (3 ha, 7 acres) and one flight covers up to 1.5 square km (150 ha, 370 acres). * At 280 m (ground resolution of 10 cm/pixel), one picture covers 0.12 square km (12 ha, 29 acres) and one flight covers up to 4 square km (400 ha, 990 acres). * At 840 m (ground resolution of 30 cm/pixel), one picture covers 1.07 square km (107 ha, 265 acres) and one flight covers up to 10 square km (1000 ha, 2470 acres).

Q:What are the flight performances of the UAV?

A: The UAV has a flight endurance of about 30 minutes with a fully charged battery. The endurance is reduced with wind, frequent altitude changes or very low temperatures. The cruise speed is 10 m/s (36 km/h, 22 mph). The climb rate is about 3 m/s. The maximum wind speed is 7 m/s (25 km/h, 16 mph), which corresponds to a moderate breeze. This includes a safety margin to allow the UAV to fly back home automatically when strong wind is detected by the autopilot.

Q: How many images can be taken during one flight?

A: When photos are triggered at maximum rate (every 3-4 seconds), the number of images in one flight can reach 400. The provided onboard memory card has more than enough space to store such a number of images at full resolution.

Q: What level of accuracy should be expected?

A: The accuracy of the orthomosaics and the digital elevation models (DEM) strongly depends on the flight height, lighting conditions, availability of textures, image quality, overlap, and type of terrain. In standard conditions (flying at 100-150 meters above natural terrains with 50 to 70% image overlap), a relative accuracy of 10 cm and an absolute accuracy of 3-5 meters is obtained without the use of Ground Control Points (GCP). However, GCP’s can be introduced, reducing the absolute error to the level of a few centimeters.

Interested? Visit http://airmap.co.za

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/)