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  • (gentle music)

  • - [Instructor] All right, I'm gonna speak about

  • the digital camera data.

  • Here's a sample of a picture, an image we took

  • over Boulder, that one year, and you are right there.

  • That's NEON Headquarters, in the classroom.

  • The, this image has been orthorectified, and the ground

  • distance is about 800 by 600 meters.

  • And this is a 10 centimeter resolution.

  • All right, the camera itself is a,

  • the camera back is made by PhaseOne.

  • You can see the number of pixels.

  • At best it can take one frame every two seconds.

  • It's got a forward motion compensator,

  • so that as the plane is flying along at 100 knots,

  • it minimizes the blurring on the ground.

  • The output format of this camera is, something called IIQ.

  • It's proprietary to PhaseOne, meaning,

  • in order to actually deal with the really raw images,

  • you need to use their software, called CaptureOne,

  • which is free to use for this particular image format.

  • And the nominal resolution when you're flying at 1000 meters

  • above ground level is 8.5 centimeters for the raw data.

  • All right, so what do you use the camera images for?

  • Well it's a complement to the spectral data on the

  • left here, you see, spectrometer data.

  • We selected three bands, 52, 34, and 18, and they mimic RGB.

  • It's typical to see what you're looking at on the ground,

  • over on the right, we see the camera image (inaudible)

  • camera image, and you can see that there are roads,

  • trees, shadows, and then right here,

  • well this by the way is San Joaquin

  • right here is the central tower, San Joaquin Central Tower.

  • You notice that it looks like it's falling over

  • at 45 degrees, obviously it's not,

  • but that's an artifact of the back that,

  • you're at 1000 meters above ground, and this is

  • over toward the edge of an image, so it's distorted.

  • All right, in operations, it's coincident,

  • it's coincident with the spectrometer.

  • We have about a 50% overlap along track, 33% cross track.

  • Nominally the frame rate is about 4 images per second.

  • And each site, it may collect between 2000 and 11,000 images

  • over several days.

  • Well there's three major steps to processing.

  • The first one is to adjust the color balance and exposure,

  • and since the image is mainly taken, on different days,

  • and on the same day over a period of several hours,

  • where conditions change, you may have to adjust the

  • color balance and exposure separately over the time period.

  • 2nd step is orthorectification.

  • You have to remap the image from the camera frame to

  • a regular fixed grid on the ground.

  • Same grid that the spectrometer is projected on,

  • except that it's 10 centimeter resolution, not one meter

  • resolution like the spectrometer.

  • And finally, mosaicking.

  • Like I said you can have 11,000 images over one site.

  • Mosaicking takes all of those images, overlaps them,

  • and creates one single image.

  • We, and then, because the single image is so large,

  • you subdivide that single mosaic image into

  • separate tiles, which are one kilometer on a side.

  • All right, preprocessing.

  • You can see on the left, a raw image.

  • On the right, a processed image.

  • We try and make it appear as close to what you would see

  • if you were actually up there and looking down.

  • Or you may have to adjust these separately,

  • it can be a very tedious process.

  • Orthorectification, we remap from the camera frame,

  • down to a regular UTM grid on the ground that is shown

  • on the picture.

  • And to do this, we require several other pieces of data.

  • One's called a smooth best estimate of trajectory,

  • we get that from the lidar, and that tells you

  • exactly where the plane is at any second.

  • And exactly how it's oriented, the roll, pitch and yaw.

  • And from this we can trace any line of sight from the camera

  • down to the ground, and also from the lidar

  • we get a digital elevation map, a DEM.

  • And that's this, the grid you see there.

  • So we shoot a ray down from each camera pixel

  • down to the ground and see where it intersects the DEM,

  • and then project that down to this UTM grid.

  • We also need a camera model, which, describes the

  • distortions in the camera image due to the lens.

  • And also, the offset of the camera itself from

  • the lidar (inaudible) site.

  • Here's an example of a, an image before orthorectification.

  • This is the raw image.

  • But after preprocessing.

  • And over here it's been orthorectified.

  • The plane wasn't going exactly north south,

  • and you can see on the sides here, were there's

  • curvature on the side of the image,

  • and that's due to the uneven ground surface.

  • Now, the orthorectification process introduces

  • other distortions.

  • And that's because of a mismatch between the camera

  • resolution, which is a 10th of a meter, and the lidar DEM

  • resolution, which is one meter.

  • So you get straight, here's a image of a intersection,

  • and you can see here where these straight lines

  • are distorted, and that's because of trees, and holes

  • nearby which, the DEM, again has a one meter resolution,

  • so it may trace a ray down to the top of this tree,

  • but it really belongs here.

  • Over here, is the very, over on the right of the screen,

  • edge of an image, in, where you've seen the tree canopy,

  • and you see a lot of swirls in the tree canopy.

  • Again, you're seeing partly through the ground, partly

  • to the top of the tree, so you get these artifacts

  • that look kinda weird, especially when you compare them

  • to let's say a satellite image, where the line of sight

  • is very narrowly vertical,

  • and you don't see this kind of distortion.

  • Finally, mosaicking.

  • A single survey will produce between 2000 and 11,000 images.

  • The mosaicking combines all of these into one image.

  • Okay and from all of these overlapping images,

  • these selected, the pixel with the smallest zenith angle,

  • most vertical, most vertical angle,

  • to minimize the distortions that we talked about earlier.

  • And the result is a set of, and then you tile it into

  • a set of images which are one kilometer on the side.

  • And you can end up with between 100 and 450 of these tiles.

  • Now, one ongoing issue is, how do you blend these images

  • from different days and different times and days,

  • with different solar zenith angles, into something

  • that's, looks uniform.

  • You'll see that in a bit.

  • All right, here's an example of a mosaic

  • we made earlier this year.

  • Here is the full mosaic,

  • including all the different images.

  • And over here, is one tile from this mosaic.

  • You can see along here these, seams, and that's because

  • you're taking different images with slightly

  • different lighting conditions, as it shows up

  • at these boundaries.

  • All right, now, how do you deal with 11,000 images

  • or 450 tiles.

  • In order to deal with all these, we have created a KMZ

  • file, which you can load into Google Earth.

  • Here is a picture of a, this is, Google Earth

  • centered over the NEON hangar, at Boulder Airport.

  • About two miles just north of here.

  • So, we created these things, KMZ files,

  • and here's an example of San Joaquin this year.

  • And if you load it into Google Earth and then double

  • click on it, here's what you see initially.

  • And, this purple boundary, the extreme purple boundary

  • is the limits of a digital elevation map,

  • that we use for processing.

  • But, let me turn that off.

  • You'll see this other purple boundary, and that's

  • the limits of the actual DEM from the lidar.

  • We've included all this other area, but that's

  • from a USGS DEM at eight meter resolution.

  • We just used it for filler and it's necessary for

  • some of the analysis.

  • If we blow it up, you'll see that the there's some

  • interior portions outlined in purple, and that's

  • where those no good lidar data.

  • So, this has also been filled with the USGS DEM.

  • Typically, you'll see that over water bodies

  • where you don't get a decent lidar return.

  • But the water bodies are flat, so there's not, no

  • features that you'll see.

  • You'll also see here the location of the central tower.

  • All right, then, if you click on mosaic tiles,

  • this shows you the location of each tile.

  • So, supposed you're interested in the central site,

  • blow it up there, if you click on the tile,

  • it gives you the name of the file that

  • corresponds to this tile.

  • And the name consists of the year, the site,

  • San Joaquin Experimental Range.

  • The (inaudible) was the 2nd visit we have ever made

  • of San Joaquin, we went there once before from one year.

  • And these two numbers here, are the Universal

  • Transverse Mercator locations in meters

  • of the lower, left corner of the image.

  • And, that's just the way that (inaudible) is.

  • See, that's for something else, but, so

  • so that's, if you're interested in this area,

  • this tells you how to find this tile.

  • You can also go over to this button,

  • and that shows the location of each individual image.

  • So, like this one, #0499,

  • if we click on it, it gives you the file name of that image

  • plus the exact location, the altitude, and the heading

  • of the plane when it took the image.

  • And then, finally there is a five meter resolution

  • (inaudible)

  • This is taken from the mosaic but it reduced resolution

  • because it was just too big.

  • This image by itself was already 10 megabytes.

  • And this gives you a sort of overview and perspective

  • of what you're looking at.

  • And it includes things like cloud shadows,

  • and you can also see those boundaries between

  • individual images.

  • Okay, and, so, and one more feature of Google Earth.

  • Now, this is Google Earth Pro, and Google Earth Pro

  • is now free for anybody to use and download.

  • Google isn't gonna support it anymore,

  • so if you can still get it, I'd use it.

  • So, one feature of Google Earth Chrome is that you can

  • actually take some of the, well, let's go to this tile here.

  • It's tile 3257411.

  • We go over here to natural images, and find that one.

  • There it is, 257411.

  • And we drag that into Google Earth.

  • Now the problem is, is this image is too large

  • to fit into Google Earth.

  • So you got two choices, you can either

  • look at the whole image and scale it down in resolution

  • or you can crop it.

  • So you get full resolution over a limited area.

  • So let's crop it, and center it right on the tower.

  • And then you can blow it up and look at the image in detail.

  • Again, here is that tower we saw at the very beginning,

  • plus the roads, trees, so forth.

  • And this is to locate things of interest.

  • And again, you can do the same thing with,

  • you can scale it.

  • There's this also great super overlay but don't,

  • don't push that button.

  • (audience laughs)

  • That shows you the full image, again, at reduced resolution.

(gentle music)

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B1 US image resolution google earth camera tile dem

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