[GIS] Creating image with specific latitude/longitude positions using GDAL

Question

I have an ASCII file with latitude, longitude, and data_val in the following format.

35-13.643782N, 080-57.190157W, 118.6
...

I have a GeoTiff image file, and I can easily view it.

I want to place a "pin" (can be a dot/flag/star or whatever is easiest) on the image at the specific latitude/longitude position found in the ASCII file.

Here is what I've managed to do so far:

My source image looks like this:

Driver: GTiff/GeoTIFF
Files: /tmp/Charlotte SEC 100.tif
Size is 16867, 12358
Coordinate System is:
PROJCS["Lambert Conformal Conic",
    GEOGCS["NAD83",
        DATUM["North_American_Datum_1983",
            SPHEROID["GRS 1980",6378137,298.2572221010042,
                AUTHORITY["EPSG","7019"]],
            AUTHORITY["EPSG","6269"]],
        PRIMEM["Greenwich",0],
        UNIT["degree",0.0174532925199433],
        AUTHORITY["EPSG","4269"]],
    PROJECTION["Lambert_Conformal_Conic_2SP"],
    PARAMETER["standard_parallel_1",38.66666666666666],
    PARAMETER["standard_parallel_2",33.33333333333334],
    PARAMETER["latitude_of_origin",34.11666666666667],
    PARAMETER["central_meridian",-78.75],
    PARAMETER["false_easting",0],
    PARAMETER["false_northing",0],
    UNIT["metre",1,
        AUTHORITY["EPSG","9001"]]]
Origin = (-365041.822331817995291,240536.419747152860509)
Pixel Size = (42.334586069440391,-42.334898968590878)
Metadata:
  AREA_OR_POINT=Area
  TIFFTAG_DATETIME=2016:06:24 12:46:45
  TIFFTAG_RESOLUTIONUNIT=2 (pixels/inch)
  TIFFTAG_SOFTWARE=Adobe Photoshop CS5 Windows
  TIFFTAG_XRESOLUTION=300
  TIFFTAG_YRESOLUTION=300
Image Structure Metadata:
  COMPRESSION=LZW
  INTERLEAVE=BAND
Corner Coordinates:
Upper Left  ( -365041.822,  240536.420) ( 82d48'55.43"W, 36d13' 4.92"N)
Lower Left  ( -365041.822, -282638.262) ( 82d35'10.11"W, 31d30'17.00"N)
Upper Right (  349015.641,  240536.420) ( 74d51'46.40"W, 36d13'26.16"N)
Lower Right (  349015.641, -282638.262) ( 75d 4'55.60"W, 31d30'36.99"N)
Center      (   -8013.091,  -21050.921) ( 78d50'12.11"W, 33d55'36.35"N)
Band 1 Block=16867x1 Type=Byte, ColorInterp=Palette
  Color Table (RGB with 256 entries)
    0: 255,255,255,255
...

Here is what I've managed to cobble together in Python:

from osgeo import gdal, osr

src_filename = '/tmp/Charlotte SEC 100.tif'
dst_filename = '/tmp/foo.tiff'

# Opens source dataset
src_ds = gdal.Open(src_filename)
format = "GTiff"
driver = gdal.GetDriverByName(format)

# Open destination dataset
dst_ds = driver.CreateCopy(dst_filename, src_ds, 0)

# Specify raster location through geotransform array
# (upperleftx, scalex, skewx, upperlefty, skewy, scaley)
# Scale = size of one pixel in units of raster projection
# this example below assumes 100x100
gt = [-365041.822, 100, 0, 240536.420, 0, -100]

# Set location
dst_ds.SetGeoTransform(gt)

# Get raster projection
epsg = 4269            # http://spatialreference.org/ref/sr-org/lambert_conformal_conic_2sp/
srs = osr.SpatialReference()
srs.ImportFromEPSG(epsg)
dest_wkt = srs.ExportToWkt()

# Set projection
dst_ds.SetProjection(dest_wkt)

# Close files
dst_ds = None
src_ds = None

But, I can't quite figure out how to place a "red dot" at
35-13.643782N, 080-57.190157W

I'm having to learn some new details here (nomenclature about GIS).

Answer 1

Your gdalinfo output shows you have a single band GeoTIFF with a colour table (AKA palette). I can't see the values in that colour table so the commands below convert the single band + colour table to a three band RGB GeoTIFF. The commands also assume your ASCII file has a header row and has coordinates in decimal degrees, you may need to modify your file if it doesn't.

Inputs:

$ cat testlonlat.csv
LON,LAT
143.798425,-15.551485
143.827437,-15.535119
143.84561,-15.530017
143.859107,-15.54819
143.812347,-15.523641
143.853581,-15.534694
143.883337,-15.537669
143.885356,-15.561687
143.887694,-15.588468

$ gdalinfo testutm.tif
Driver: GTiff/GeoTIFF
Files: testutm.tif
Size is 1102, 959
Coordinate System is:
PROJCS["WGS 84 / UTM zone 54S",
    GEOGCS["WGS 84",
        DATUM["WGS_1984",
            SPHEROID["WGS 84",6378137,298.257223563,
                AUTHORITY["EPSG","7030"]],
            AUTHORITY["EPSG","6326"]],
        PRIMEM["Greenwich",0,
            AUTHORITY["EPSG","8901"]],
        UNIT["degree",0.0174532925199433,
            AUTHORITY["EPSG","9122"]],
        AUTHORITY["EPSG","4326"]],
    PROJECTION["Transverse_Mercator"],
    PARAMETER["latitude_of_origin",0],
    PARAMETER["central_meridian",141],
    PARAMETER["scale_factor",0.9996],
    PARAMETER["false_easting",500000],
    PARAMETER["false_northing",10000000],
    UNIT["metre",1,
        AUTHORITY["EPSG","9001"]],
    AXIS["Easting",EAST],
    AXIS["Northing",NORTH],
    AUTHORITY["EPSG","32754"]]
Origin = (798741.168775000027381,8282084.855279999785125)
Pixel Size = (10.000000000000000,-10.000000000000000)
Metadata:
  AREA_OR_POINT=Area
Image Structure Metadata:
  INTERLEAVE=BAND
Corner Coordinates:
Upper Left  (  798741.169, 8282084.855) (143d47' 4.96"E, 15d31'16.22"S)
Lower Left  (  798741.169, 8272494.855) (143d47' 9.15"E, 15d36'27.98"S)
Upper Right (  809761.169, 8282084.855) (143d53'14.43"E, 15d31'11.47"S)
Lower Right (  809761.169, 8272494.855) (143d53'18.78"E, 15d36'23.20"S)
Center      (  804251.169, 8277289.855) (143d50'11.83"E, 15d33'49.74"S)
Band 1 Block=1102x7 Type=Byte, ColorInterp=Palette
  Color Table (RGB with 256 entries)
    0: 120,112,136,255
    1: 96,104,88,255
    ...
    254: 76,124,140,255
    255: 232,228,236,255

Process:

$ gdal_translate -expand rgb testutm.tif testutm_rgb.tif

$ ogr2ogr -f "GeoJSON" -dialect sqlite                      \
  -sql "select ST_buffer(Geometry,0.001) from testlonlat"   \
  -s_srs EPSG:4326 -t_srs EPSG:32754                        \
  /vsistdout/ CSV:testlonlat.csv -oo X_POSSIBLE_NAMES=Lon   \
  -oo Y_POSSIBLE_NAMES=Lat |  gdal_rasterize -b 1 -b 2 -b 3 \
  -burn 255 -burn 0 -burn 0 /vsistdin/ testutm_rgb.tif

The last command does the following:

• buffers the Lon/Lat point to a bigger polygon so it shows up better (you can skip that if you just want a single pixel coloured red)
• converts from WGS84 Lat/Lon (EPSG:4326) to the same coordinate system as the raster (EPSG:32754 which is WGS 84 UTM Zone 54S, your CRS will be different)
• writes the output polygon as GeoJSON to STDOUT and pipes it to gdal_rasterize
• burns RGB 255,0,0 into the RGB raster bands 1, 2 & 3

Result: