For those unfamiliar with NIR imaging, in Geography we primarily use the near-infrared portion of the spectrum to help us measure a multitude of things just beyond the visible portion of the electromagnetic spectrum. Some of the primary uses for NIR imaging are to measure vegetation types, vegetation health, and help differentiate different landuse/landcover types. Here's a NASA link to more information on NIR and another on the Normalized Difference Vegetation Index (results below).
The NIR camera is a Canon Powershot A4000IS that I converted myself by removing the IR cut filter from in front of the sensor (definitely not an operation for the faint hearted). To only allow IR light into the camera I use an IR pass filter (Lee #87) placed over the lens. The result is a grayscale image the represents the intensity of NIR light in the scene. The details of the camera will be the subject of a future post.
|Sample NIR image, lighter colors indicate more NIR light|
Here is a sample some sample images from the Inspire 1's camera and the NIR camera from roughly the same spot:
To get the images from the two cameras to align properly, I processed multiple photos from each camera through Agisoft Photoscan to produce orthorectified image mosaics. I then stacked the individual orthophotos to produce a 4-band multi-spectral image. The series below: 3D views from Photoscan (Natural Color and NIR), the Natural Color ortho (from the Inspire 1's camera), the NIR ortho (from the Canon), a false color composite (NIR - Red - Green), and the calculated NDVI.
Click on the images below to bring up the full size images.