Monthly Archives: November 2012

Unmanned aerial vehicle (UAV) topography

Posted on by
Reply

This is a new technology we are going to use in a wind farm we are going to build in Chile.

The area that we need is too small to make LIDAR topography cost effective, but too big to use standard field topography: with this new solution we can have the needed data for a reasonable price.

The vehicle comes in 2 shapes: airplane like (fixed wing) and helicopter like (rotatory wing). The fixed wing plane is launched with a sling.

The vehicle weight around 3 kilos, and it can fly for about 1 hour at a height of a couple hundred meters, with a speed of about 75 Km/h.

It is possible to obtain several useful outputs:

  • Cartography
  • Digital Model of the Terrain
  • Aerial pictures
  • Thermography
  • Multispectral images
  • Video

It normally flies alone without any input, but it can be used with a remote control as well.

The main advantage is that it is clearly cheaper: you don’t need to book a flight, wait for a days without clouds (because you can fly lower) and it’s quick and safe.

 

Wind Farm LIDAR topography

Posted on by
Reply

LIDAR topography is the best available solution available nowadays.

We have used it in several wind farms and I’m enthusiast of the results. It can be used to define earthworks with great precision.

Basically it is made with an airplane flying with a laser, a digital camera and a GPS.

The laser “sweep” the requested area and a receiver on the plane register the laser beam waves reflected by all the surfaces. At the same time high quality digital pictures are taken, and the position of the plane is registered thanks to the GPS.

This is how the equipment used looks like:

After the flight, the cloud of point obtained is filtered: first of all points are divided in classes, depending on the type of reflection (“echoes”). Groups of points representing trees, bushes, buildings and so on can be defined.

In the second filtering the intensity of the reflected beams is considered (vegetation and ground reflect with very different intensity).

The next step is to calculate a mean between different laser passages, as the same point may appear in slightly different coordinated.

This kind of mistake introduces a noise in the results, and contour lines may results as broken lines instead of smooth lines:

As a result of this data cleaning process, all the point can be classified as belonging to a type surface (trees, grass, building, and ground) and it’s possible to visualize them with a different color.

You can see in the following image some examples. In the first, an agricultural area is mapped. In green you can see the trees and in brown the ground:

In this other example, we mark in green the ground, in violet the trees and in brown the buildings:

In this final example, you can see as a whole town would look like in a cloud of points:

Control point are manually selected identifying them in the picture. They are used to put the data in the correct absolute coordinates:

Finally, a digital terrain model is produced using the Delaunay triangulation, to maximize the area of the triangles.

As you can see, the results are often exceptional:

Wind farms projects using Google Earth topography

Posted on by
Reply

One of the biggest problems in wind farms preliminary projects is the lack of a reliable topography.

Due to the tight budgets developers are often working with, it is often impossible to obtain a good topography (like the ones you can get with a LIDAR instrumented flight) or at list a decent one (as the standard field topographic surveys).

One of the possible solutions is to work with the Google Earth topography. Software like AutoCAD civil 3D makes it possible to download a cloud of points with coordinates and elevations and work with them.

The question is: how good is this info?

Unfortunately it’s impossible to answer univocally. The base grid, covering almost all the inhabited surface of the planet, has been obtained with a space mission (the NASA SRTM, Shuttle Radar Topography Mission).

The points are approximately spaced 50 meters, so it is a very rough starting point.

This base has been integrated with a “mosaic” of different DEM (digital elevation models) freely available material, so there are states in the US with a 1 meter contour line, or even cities with a very dense cloud of points (even a point every 20 centimeters).

It is currently impossible to know from where the points you are using are coming from, and if a point is “true” or interpolated. It is possible to have an impression seeing the shape of the contour lines (if you “zoom out” from the topography you will often see a pattern of squares coming from the available points).

This data is normally reasonably acceptable for a somehow preliminary project. Several commercial plug in are available to enhance the results.

For instance Plex Earth allows you to import Google Earth data (pictures and points) in different coordinates systems, importing contours in an area with any shape specified. It can also be used for preliminary volume calculation, to export objects from AutoCAD to visualize them inside Google Earth or doing the opposite (that is, importing a Google Earth KML file).