Archive for December, 2008

California LIDAR 2

December 24, 2008

Okay, so I can’t get over these data quite yet.  One more post.  Oh, and yes, Happy Holidays!  I’m heading to New York this evening — nothing like a Christmas Eve red eye, but I’m excited to see family.  Back to LIDAR for one second.  I wanted to show what the calculation of the DEM with trees minus the DEM without trees (which equals trees, basically) looks like without symbolizing by land cover type.  I originally got this idea from an article discussing LIDAR analysis of gigantic redwoods along the Northern California coast, a project funded by Save the Redwoods League.  So, just below you can see the height of vegetation simply shown with a color ramp.  The darkest red represent the tallest trees, the light blue shows the water or barren land.  This image says so much, it kind of blows my mind.  In the northwest, you can see where the tallest trees follow the natural ravine, along the banks of a stream.  But that square in the center, and the line of trees in the southeast, that could only be created by one thing:  humans and their crazy “property rights.”

So, the next image shows parcel boundaries, and yes, they line right up with the drastic difference in tree height.  This goes to show that just because an area may be forested with identical tree species, there can still be extreme differences in habitat type caused by forest management.

Is there really a difference between looking at these images and just inspecting some aerial imagery?  There is, check it out below.  Zooming to the property line in the southeast, you see the original calculation, just as above, then an aerial image with parcel lines, followed by just an aerial image.  If you look close enough at the aerial, you can make out a property line, but it is definitely not as glaring as the original calculation.  Cheers!  Happy Holidays!

California LIDAR

December 23, 2008

A search for California LIDAR brought up a NASA Planetary Geodynamics Laboratory link with some very localized LIDAR geotiffs.  I recognized the name Fort Ross, so downloaded these images, and they’re great.  There are four files for each area, a digital elevation model (DEM) with tree heights, a DEM without tree heights, and hillshades of each DEM.  I thought about how I could call out forested areas, and came to the conclusion that I could subtract the DEM without trees from the DEM with trees to just get heights of objects above the ground.  The biggest differences, the highest trees, are shown as dark green, the smaller differences are shown as yellowish grasses and shrubs, and no difference is shown as blue water.  Set transparencies between this layer and both hillshades, and we get a pretty great land cover map.  Click on the image below to see a high resolution version, and further below you will see the DEMs and calculation described above.