Hi all,
we have shuffled together a few IR photos, extracted 3D model with PhotoSynth, meshed, textured, projected and other stupid things.
Now could somebody tell me if it serves any purpose because I got creativity crisis.
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Remote Sensing (RS) is incredibly useful for a wide variety of applications and will be the primary use of civilian UASs. A UAS gives you both high spatial and temporal resolution at a low cost, a difficult to impossible task with other methods. I come from a GIS/RS background and this is where my interest lies not so much in the airframe or autopilot software. UASs are a tool to lug sensors into the air.
To be useful for RS most people are going to expect at least four "bands" of data. These would the primary and expected bands for land management:
Beyond that the more data you can give me as separate bands the better. With the above bands I can assemble a "natural color" aerial photo (what your eye sees) or a "false-color infrared" which should turn healthy vegetation bright red and water black. NIR is important for identifying photosynthetically-active vegetation and can be a good indicator of plant health. NIR is by far the most useful band for most RS applications related to land management.
Full-spectrum isn't that interesting to me because the three bands captured by the camera are mixed. Remember that for most RS applications we care about the data, not how it looks. By using two cameras Clark is capturing only NIR in one using a filter and is capturing natural-color RGB in the other camera. Tassel Cap and other common RS methods rely on having standard bands of data.
The go-to book for remote sensing is "Remote Sensing and Image Interpretation" by Lillesand, Kiefer, and Chipman published by Wiley. Another incredible reference and introduction to RS is the Canadian Centre for Remote Sensing tutorial: http://www.ccrs.nrcan.gc.ca/resource/tutor/fundam/chapter1/01_e.php This is a great fact sheet the USDA put together describing CIR four-band imagery as part of the NAIP program (standard for US agricultural RS imagery): http://www.fsa.usda.gov/Internet/FSA_File/fourband_info_sheet_2010.pdf
Id' say if we can nail down the spectral bands, figure out the geo-rectification part of the toolchain, and demonstrate a spatial error below around a meter we'd be all set. Krzysztof's and the work of some others on here is incredibly exciting and interesting to me. I've yet to build a UAS system but have been messing around with the geospatial software side of things while lurking. I hope to get started on my airframe in the next month or so.
Also, a few terminology notes. I've noticed people get hyperspectral and multispectral mixed up. Everything we're talking about falls under multispectral (3+ bands). Hyperspectral is a form of multispectral imaging that divides the full spectrum into consistent and adjacent bands and typically has 50 or more bands. These sensors are incredibly expensive. NASA refers to hyperspectral imaging as "imaging spectroscopy" because it's a lot more descriptive in a lot of ways.
I hope that helps.
@Condor "Looks like your NIR camera is firing late..."
Rather at different angle. Plus maybe some time jitter around. We dont really care because we intend to compare the map after georeferencing. Of course we woudl prefer things to be perfect.
Looks like your NIR camera is firing late...
I don't know is full spectrum works the say way, what Clark is talking about removes the blue channel and replaces it with the IR image I believe. Full spectrum mixes difference wavelengths of IR radiation into the different color channels distorting the colors of the pictures.
Other then that IR can be used to spot disturbances in soil, see through fog and show other thing normal light can't. I know other uses like seeing through plastics, the top layer of skin and …some forms of clothing but don’t see how they’d be as much help here. lol
Just need to say the 3D reconstruction is amazing!
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