An increasing desired use case for OpenDroneMap is to use it for non-drone maps. For example:

• I have a bucket of scanned images from the 1950’s. I want to make them into a mosaic. I have the geographic center for each image. Can I process these in OpenDroneMap?
• I have a bucket of individually orthorectified images from a sensor like from the Wildfire Airborne Sensor Program (WASP). I’d like to mosaic them into one image. Can I process these in OpenDroneMap?

The answer is unknown for the first question, and I’m looking forward to testing. For the second question, I have done some testing with great success.

The WASP sensor, as flown for the mission I’m testing outputs a whole bucket of individually orthorectified imagery.

The problem that we encounter is both radiometric inconsistencies between images and geometric offsets.

Fortunately, OpenDroneMap is good at dealing with both. The questions for this dataset simply were — is there enough overlap to allow ODM to do its magic && and does it create usable output?

Looking at overlap was promising:

The best thing to next is to try. One problem. ODM doesn’t read GeoTiffs. Oops. Two problems — ODM assumes that your data has exif headers describing the location of the camera when the image was taken.

The first problem is easy. If we want jpegs, we might run something like the following:

for f in *.tif; do

gdal_translate -of JPEG -co QUALITY=100 -co worldfile=yes -scale 0 1024 0 255 $f $f.jpg

; done

The second problem is a little trickier. We can extract info from our new jpegs pretty easily with gdal:

gdalinfo orthoVNIR2549_flatfield.tif.jpg

Resulting in something like the following:

Driver: JPEG/JPEG JFIF

Files: orthoVNIR2549_flatfield.tif.jpg

orthoVNIR2549_flatfield.tif.jpg.aux.xml

orthoVNIR2549_flatfield.tif.wld

Size is 3233, 4303

Coordinate System is:

GEOGCS[“WGS 84”,

DATUM[“WGS_1984”,

SPHEROID[“WGS 84”,6378137,298.2572229328696,

AUTHORITY[“EPSG”,”7030″]],

AUTHORITY[“EPSG”,”6326″]],

PRIMEM[“Greenwich”,0],

UNIT[“degree”,0.0174532925199433],

AUTHORITY[“EPSG”,”4326″]]

Origin = (-72.222122858200009,18.545027305599998)

Pixel Size = (0.000001126600000,-0.000001126600000)

Metadata:

AREA_OR_POINT=Point

EXIF_GPSLatitude=(18) (32) (33.3722)

EXIF_GPSLatitudeRef=N

EXIF_GPSLongitude=(72) (13) (13.0861)

EXIF_GPSLongitudeRef=W

EXIF_GPSVersionID=0x2 0x3 00 00

EXIF_ResolutionUnit=1

EXIF_XResolution=(1)

EXIF_YCbCrPositioning=1

EXIF_YResolution=(1)

Image Structure Metadata:

COMPRESSION=JPEG

INTERLEAVE=PIXEL

SOURCE_COLOR_SPACE=YCbCr

Corner Coordinates:

Upper Left  ( -72.2221229,  18.5450273) ( 72d13’19.64″W, 18d32’42.10″N)

Lower Left  ( -72.2221229,  18.5401795) ( 72d13’19.64″W, 18d32’24.65″N)

Upper Right ( -72.2184806,  18.5450273) ( 72d13′ 6.53″W, 18d32’42.10″N)

Lower Right ( -72.2184806,  18.5401795) ( 72d13′ 6.53″W, 18d32’24.65″N)

Center      ( -72.2203017,  18.5426034) ( 72d13’13.09″W, 18d32’33.37″N)

Band 1 Block=3233×1 Type=Byte, ColorInterp=Red

Overviews: 1617×2152, 809×1076, 405×538

Image Structure Metadata:

COMPRESSION=JPEG

Band 2 Block=3233×1 Type=Byte, ColorInterp=Green

Overviews: 1617×2152, 809×1076, 405×538

Image Structure Metadata:

COMPRESSION=JPEG

Band 3 Block=3233×1 Type=Byte, ColorInterp=Blue

Overviews: 1617×2152, 809×1076, 405×538

Image Structure Metadata:

COMPRESSION=JPEG

From this we can just extract what we need from the image center info:

gdalinfo orthoVNIR2549_flatfield.tif.jpg | grep Center

Which results in the following:

Center      ( -72.2203017,  18.5426034) ( 72d13’13.09″W, 18d32’33.37″N)

Ok, this will require a little filtering to extract what we need. Then we’ll use exiftool to write it back to the file as follows:

Voila! Now we can process in OpenDroneMap. Now to find an older historical dataset to attempt this on.