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I've recently finished a research project using UAVs to classify land cover types on British upland heath. I'm using an APM controlled hexacopter (H550) carrying a Canon Powershot S95 modified for NIR photography. I've successfully surveyed and classified around 15 hectares in 10 minutes. Using image analysis software I've been able to classify the major land cover types with about 90% accuracy which is comparable to that obtained from imagery captured from much larger platforms using many more spectral bands.

An NDVI colour index of the orthomosaic was created and used in the classification process. This really helps in the spectral differentiation process. I think the results here show massive potential for the frequent, low-cost monitoring of the status of, and temporal changes in (sorry for the academic speak) many habitats, not just heathland.

The images below show the various outputs.

1. The full NIR orthomosaic

Screen%20Shot%202015-03-19%20at%2015.38.15.png

2. The NDVI colour index

Screen%20Shot%202015-03-19%20at%2015.37.50.png

3. The colour index overlaid on the green channel of the orthomosaic highlighting healthy and dead vegetation

Screen%20Shot%202015-03-19%20at%2015.44.42.png

4. The classified land cover types in the GIS software (Purple is Calluna dominated heath, light green is rank grass cover, brown is cut heath and green are trees)

Screen%20Shot%202015-03-19%20at%2015.37.07.png?width=649

I used ImageJ to create the NDVI colour index image, unfortunately it doesn't keep the GeoTIFF data in the output so I've used GDAL to georeference the colour index TIFF

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