Most of the time I’m doing kite aerial photography, it is to create a picture I like; that I would want to hang on my wall. But on occasion I’ve done KAP strictly as a method of remote sensing. The pictures are data rather than an attempt at art. I’ve flown at Kiholo Bay several times now, usually in the former category of creating pleasing images. This most recent trip was strictly in the latter sense: to take data. But any time I’m out in the field doing KAP, I try to have fun and to stretch what I can do with what I’ve got. This outing was no exception.
The requirements for the flight strictly called for oblique angles. I settled on 45 degrees for most of them, though occasionally I used a steeper or a shallower angle as best suited the subject. But I took some ortho images anyway. It’s always fun to compare against what Google Earth shows for a particular region, and ortho can be useful when I’m going through the pictures later to judge distance and height. The field of view of my camera is such that the horizontal width of the frame corresponds to the height of the camera to within 5%. By taking the occasional orthogonal image, I can typically go back through the images with a map or Google Earth to figure out how high the camera was. Besides, it’s always fun to compare the KAP image to the Google Earth image, if for no other reason than to point out that comparing satellite imagery and low altitude aerial imagery is seriously comparing apples and oranges.
Ever since doing some work for an archaeologist from Oahu, I’ve been trying various false color techniques to try to get information out of my images. Most of the time this has been done with orthogonal pictures, though as you can see from my previous post, the same tricks can be used on practically any picture. But it works well with the orthos:
There are a number of features in this picture that are worth trying to isolate. There are kiawe trees, a patch of fountain grass, pahoehoe lava from a Mauna Loa lava flow, aa lava from a Hualalai lava flow, water, coral rock, and even a swimmer in the water.
The first approach I tried was to use ImageJ with the DStretch plug-in. It’s a really good false color filter that can be used to boost any manner of color combinations in an image. In this case I used the YDS setting with a 315 degree rotation in hue, and managed to isolate most of the features listed above: Kiawe trees are rendered as a combination of yellowish green in the upper branches, and red for the dead undergrowth. The fountain grass is rendered as a bright red. Pahoehoe lava is rendered as a blackish purple, and the aa is rendered as a reddish purple, as are the cracks in the pahoehoe lava. Coral shows up as a very light blueish purple, almost white, and the water is rendered as antifreeze green. Lurid though the colors may be, it makes picking out individal elements in the image quite easy.
Another approach that has worked well in the past is to separate the R, G, and B channels in the image, and treat them as components in a mathematical expression. This is a tried and true technique that’s been used in astronomy for ages. B-V (or in the RGB world, B-G) images can be used to judge the temperature of a star, for example. I wasn’t taking pictures of stars, but there’s still validity in the idea. Let’s say I want to find the redder aa lava, but don’t want to get a false positive from the coral rock in the frame. Subtracting the blue channel from the red channel picks up primarily red objects, in this case aa lava and cracks in the darker pahoehoe lava, though this catches the green vegetation as well:
Similarly, green vegetation can be isolated by subtracting red or blue from the green component, and in this case it doesn’t do such a good job of picking up the rocks:
Slightly more complicated expressions can be used to isolate other colors in the image, or to further separate colors. And likewise, this trick can be used on false color images that have been produced through some other tool, such as DStretch.
Despite having resources like Google Earth available to us, kite aerial photography still offers a great deal of utility as a remote sensing platform. But I still like making pretty pictures best of all. The next time I grab my bag and head out the door, it’ll be to go somewhere nice and take pictures I like: the kind I want to hang on my wall.