By Rupert
GDAL/OGR
Using GDALWARP to reproject raster that will fit with Google Satellite
Jul 29th
Just a couple of notes to onself using gdal: Use gdalwarp to reproject your GeoTIFF files! I wanted to use my own satellite images acquired from GeoEye, however, on some areas I wanted to use google sat images as well since I don’t have the coverage. In order to do so, I need to reproject the sat images to 900913. Note you need to specify this in your epsg file in my previous post.
rupert:beijing_900913_satellite rupert$ gdalinfo Mosaic_RGB.tif Driver: GTiff/GeoTIFF Files: Mosaic_RGB.tif Size is 4248, 4553 Coordinate System is: GEOGCS["WGS 84", DATUM["WGS_1984", SPHEROID["WGS 84",6378137,298.2572235630016, AUTHORITY["EPSG","7030"]], AUTHORITY["EPSG","6326"]], PRIMEM["Greenwich",0], UNIT["degree",0.0174532925199433], AUTHORITY["EPSG","4326"]] Origin = (116.291476140000000,40.025198500000002) Pixel Size = (0.000046860000000,-0.000035970000000) Metadata: AREA_OR_POINT=Area TIFFTAG_XRESOLUTION=100 TIFFTAG_YRESOLUTION=100 Image Structure Metadata: INTERLEAVE=BAND Corner Coordinates: Upper Left ( 116.2914761, 40.0251985) (116d17'29.31"E, 40d 1'30.71"N) Lower Left ( 116.2914761, 39.8614271) (116d17'29.31"E, 39d51'41.14"N) Upper Right ( 116.4905374, 40.0251985) (116d29'25.93"E, 40d 1'30.71"N) Lower Right ( 116.4905374, 39.8614271) (116d29'25.93"E, 39d51'41.14"N) Center ( 116.3910068, 39.9433128) (116d23'27.62"E, 39d56'35.93"N) Band 1 Block=4248x1 Type=Byte, ColorInterp=Red Band 2 Block=4248x1 Type=Byte, ColorInterp=Green Band 3 Block=4248x1 Type=Byte, ColorInterp=Blue
rupert:beijing_900913_satellite rupert$ gdalwarp -s_srs epsg:4326 -t_srs epsg:900913 Mosaic_RGB.tif sat_4m_rgb.tif Creating output file that is 4245P x 4556L. Processing input file Mosaic_RGB.tif. 0...10...20...30...40...50...60...70...80...90...100 - done.
rupert:beijing_900913_satellite rupert$ gdalinfo sat_4m_rgb.tif Driver: GTiff/GeoTIFF Files: sat_4m_rgb.tif Size is 4245, 4556 Coordinate System is: PROJCS["Google Maps Global Mercator", GEOGCS["WGS 84", DATUM["WGS_1984", SPHEROID["WGS 84",6378137,298.2572235630016, AUTHORITY["EPSG","7030"]], AUTHORITY["EPSG","6326"]], PRIMEM["Greenwich",0], UNIT["degree",0.0174532925199433], AUTHORITY["EPSG","4326"]], PROJECTION["Mercator_1SP"], PARAMETER["central_meridian",0], PARAMETER["scale_factor",1], PARAMETER["false_easting",0], PARAMETER["false_northing",0], UNIT["metre",1, AUTHORITY["EPSG","9001"]]] Origin = (12945507.907502911984921,4869604.732793668285012) Pixel Size = (5.219801430503303,-5.219801430503303) Metadata: AREA_OR_POINT=Area Image Structure Metadata: INTERLEAVE=PIXEL Corner Coordinates: Upper Left (12945507.908, 4869604.733) (116d17'29.31"E, 40d12'53.10"N) Lower Left (12945507.908, 4845823.317) (116d17'29.31"E, 40d 3'2.78"N) Upper Right (12967665.965, 4869604.733) (116d29'25.89"E, 40d12'53.10"N) Lower Right (12967665.965, 4845823.317) (116d29'25.89"E, 40d 3'2.78"N) Center (12956586.936, 4857714.025) (116d23'27.60"E, 40d 7'58.12"N) Band 1 Block=4245x1 Type=Byte, ColorInterp=Red Band 2 Block=4245x1 Type=Byte, ColorInterp=Green Band 3 Block=4245x1 Type=Byte, ColorInterp=Blue
OGR Quick Reference
Jul 10th
Here is a list of the most widely used OGR commands I use..
OGR2OGR
1. POSTGRES -> MAPINFO
$ ogr2ogr -f "Mapinfo File" busline_buffer10m.tab PG:"host=localhost user=postgres dbname=cybersoftbj" -sql "select * from table_name" -a_srs WGS84 -nln layer_name -nlt MULTIPOLYGON
2. MAPINFO -> POSTGRES
ogr2ogr -f "PostgreSQL" PG:"host=127.0.0.1 user=rupert dbname=australia password=*****" AUS_ROAD.TAB -nln AUS_ROAD -a_srs EPSG:4269 -t_srs EPSG:3857 -skip-failures ogr2ogr -f "PostgreSQL" PG:"host=myhost user=myloginname dbname=mydbname password=mypassword" mytabfile.tab -nln newtablename -select columnName
Note: If you have Chinese characters, might as well do MAPINFO -> SHAPE -> POSTGRES
http://222.128.19.19/wordpress/?p=108
3. SHAPE -> POSTGRES
shp2pgsql -W "gbk" -s 4326 lbjrdnt_small_polyline roads > roads.sql
4. POSTGRES -> SHAPE
pgsql2shp -h 127.0.0.1 -u lbs -P tracking -f roads.shp databasename tablename
4. MAPINFO TO ORACLE
ogr2ogr -f OCI OCI:username/password@orcl C:\path_to_tabfile\EMPLOYEES.TAB -nln employees
Note: This assumes you already have Oracle 10g Client installed and “orcl” is defined as an instance in tnsnames.ora. OGR2OGR automatically updates USER_SDO_GEOM_METADATA and creates a spatial index.
5. MAPINFO to MAPINFO but different projection. From EPSG:4326 to EPSG:3857
ogr2ogr -f "MapInfo File" BaseMaps_3857/AUS_CITIES_3857.TAB BaseMaps/AUS_CITIES.TAB -a_srs "EPSG:4326" -t_srs "EPSG:3857"
Where on earth is Beijing, China?
Jul 4th
Beijing China is located in EPSG:32650, UTM ZONE 50N on WGS84. UTM ZONE of the WORLD.
EPSG:4267 NAD27 EPSG:26710 NAD27 / UTM zone 10N EPSG:26711 NAD27 / UTM zone 11N EPSG:26712 NAD27 / UTM zone 12N EPSG:26713 NAD27 / UTM zone 13N EPSG:26714 NAD27 / UTM zone 14N EPSG:26715 NAD27 / UTM zone 15N EPSG:26716 NAD27 / UTM zone 16N EPSG:26717 NAD27 / UTM zone 17N EPSG:26718 NAD27 / UTM zone 18N EPSG:26719 NAD27 / UTM zone 19N EPSG:26720 NAD27 / UTM zone 20N EPSG:26721 NAD27 / UTM zone 21N EPSG:26722 NAD27 / UTM zone 22N EPSG:26703 NAD27 / UTM zone 3N EPSG:26704 NAD27 / UTM zone 4N EPSG:26705 NAD27 / UTM zone 5N EPSG:26706 NAD27 / UTM zone 6N EPSG:26707 NAD27 / UTM zone 7N EPSG:26708 NAD27 / UTM zone 8N EPSG:26709 NAD27 / UTM zone 9N EPSG:4269 NAD83 EPSG:26930 NAD83 / Alabama West EPSG:26987 NAD83 / Massachusetts Island EPSG:26986 NAD83 / Massachusetts Mainland EPSG:32118 NAD83 / New York Long Island EPSG:32128 NAD83 / Pennsylvania North EPSG:32129 NAD83 / Pennsylvania South EPSG:26910 NAD83 / UTM zone 10N EPSG:26911 NAD83 / UTM zone 11N EPSG:26912 NAD83 / UTM zone 12N EPSG:26913 NAD83 / UTM zone 13N EPSG:26914 NAD83 / UTM zone 14N EPSG:26915 NAD83 / UTM zone 15N EPSG:26916 NAD83 / UTM zone 16N EPSG:26917 NAD83 / UTM zone 17N EPSG:26918 NAD83 / UTM zone 18N EPSG:26919 NAD83 / UTM zone 19N EPSG:26920 NAD83 / UTM zone 20N EPSG:26920 NAD83 / UTM zone 20N EPSG:26921 NAD83 / UTM zone 21N EPSG:26922 NAD83 / UTM zone 22N EPSG:26923 NAD83 / UTM zone 23N EPSG:26903 NAD83 / UTM zone 3N EPSG:26904 NAD83 / UTM zone 4N EPSG:26905 NAD83 / UTM zone 5N EPSG:26906 NAD83 / UTM zone 6N EPSG:26907 NAD83 / UTM zone 7N EPSG:26908 NAD83 / UTM zone 8N EPSG:26909 NAD83 / UTM zone 9N EPSG:27582 NTF (Paris) / France II EPSG:27700 OSGB 1936 / British National Grid EPSG:4326 WGS 84 EPSG:32610 WGS 84 / UTM zone 10N EPSG:32710 WGS 84 / UTM zone 10S EPSG:32611 WGS 84 / UTM zone 11N EPSG:32711 WGS 84 / UTM zone 11S EPSG:32612 WGS 84 / UTM zone 12N EPSG:32712 WGS 84 / UTM zone 12S EPSG:32613 WGS 84 / UTM zone 13N EPSG:32713 WGS 84 / UTM zone 13S EPSG:32614 WGS 84 / UTM zone 14N EPSG:32714 WGS 84 / UTM zone 14S EPSG:32615 WGS 84 / UTM zone 15N EPSG:32715 WGS 84 / UTM zone 15S EPSG:32616 WGS 84 / UTM zone 16N EPSG:32716 WGS 84 / UTM zone 16S EPSG:32617 WGS 84 / UTM zone 17N EPSG:32717 WGS 84 / UTM zone 17S EPSG:32618 WGS 84 / UTM zone 18N EPSG:32718 WGS 84 / UTM zone 18S EPSG:32619 WGS 84 / UTM zone 19N EPSG:32719 WGS 84 / UTM zone 19S EPSG:32601 WGS 84 / UTM zone 1N EPSG:32701 WGS 84 / UTM zone 1S EPSG:32620 WGS 84 / UTM zone 20N EPSG:32720 WGS 84 / UTM zone 20S EPSG:32621 WGS 84 / UTM zone 21N EPSG:32721 WGS 84 / UTM zone 21S EPSG:32622 WGS 84 / UTM zone 22N EPSG:32722 WGS 84 / UTM zone 22S EPSG:32623 WGS 84 / UTM zone 23N EPSG:32723 WGS 84 / UTM zone 23S EPSG:32624 WGS 84 / UTM zone 24N EPSG:32724 WGS 84 / UTM zone 24S EPSG:32625 WGS 84 / UTM zone 25N EPSG:32725 WGS 84 / UTM zone 25S EPSG:32626 WGS 84 / UTM zone 26N EPSG:32726 WGS 84 / UTM zone 26S EPSG:32627 WGS 84 / UTM zone 27N EPSG:32727 WGS 84 / UTM zone 27S EPSG:32628 WGS 84 / UTM zone 28N EPSG:32728 WGS 84 / UTM zone 28S EPSG:32629 WGS 84 / UTM zone 29N EPSG:32729 WGS 84 / UTM zone 29S EPSG:32602 WGS 84 / UTM zone 2N EPSG:32702 WGS 84 / UTM zone 2S EPSG:32630 WGS 84 / UTM zone 30N EPSG:32730 WGS 84 / UTM zone 30S EPSG:32631 WGS 84 / UTM zone 31N EPSG:32731 WGS 84 / UTM zone 31S EPSG:32632 WGS 84 / UTM zone 32N EPSG:32732 WGS 84 / UTM zone 32S EPSG:32633 WGS 84 / UTM zone 33N EPSG:32733 WGS 84 / UTM zone 33S EPSG:32634 WGS 84 / UTM zone 34N EPSG:32734 WGS 84 / UTM zone 34S EPSG:32635 WGS 84 / UTM zone 35N EPSG:32735 WGS 84 / UTM zone 35S EPSG:32636 WGS 84 / UTM zone 36N EPSG:32736 WGS 84 / UTM zone 36S EPSG:32637 WGS 84 / UTM zone 37N EPSG:32737 WGS 84 / UTM zone 37S EPSG:32638 WGS 84 / UTM zone 38N EPSG:32738 WGS 84 / UTM zone 38S EPSG:32639 WGS 84 / UTM zone 39N EPSG:32739 WGS 84 / UTM zone 39S EPSG:32603 WGS 84 / UTM zone 3N EPSG:32703 WGS 84 / UTM zone 3S EPSG:32640 WGS 84 / UTM zone 40N EPSG:32740 WGS 84 / UTM zone 40S EPSG:32641 WGS 84 / UTM zone 41N EPSG:32741 WGS 84 / UTM zone 41S EPSG:32642 WGS 84 / UTM zone 42N EPSG:32742 WGS 84 / UTM zone 42S EPSG:32643 WGS 84 / UTM zone 43N EPSG:32743 WGS 84 / UTM zone 43S EPSG:32644 WGS 84 / UTM zone 44N EPSG:32744 WGS 84 / UTM zone 44S EPSG:32645 WGS 84 / UTM zone 45N EPSG:32745 WGS 84 / UTM zone 45S EPSG:32646 WGS 84 / UTM zone 46N EPSG:32746 WGS 84 / UTM zone 46S EPSG:32647 WGS 84 / UTM zone 47N EPSG:32747 WGS 84 / UTM zone 47S EPSG:32648 WGS 84 / UTM zone 48N EPSG:32748 WGS 84 / UTM zone 48S EPSG:32649 WGS 84 / UTM zone 49N EPSG:32749 WGS 84 / UTM zone 49S EPSG:32604 WGS 84 / UTM zone 4N EPSG:32704 WGS 84 / UTM zone 4S EPSG:32650 WGS 84 / UTM zone 50N EPSG:32750 WGS 84 / UTM zone 50S EPSG:32651 WGS 84 / UTM zone 51N EPSG:32751 WGS 84 / UTM zone 51S EPSG:32652 WGS 84 / UTM zone 52N EPSG:32752 WGS 84 / UTM zone 52S EPSG:32653 WGS 84 / UTM zone 53N EPSG:32753 WGS 84 / UTM zone 53S EPSG:32654 WGS 84 / UTM zone 54N EPSG:32754 WGS 84 / UTM zone 54S EPSG:32655 WGS 84 / UTM zone 55N EPSG:32755 WGS 84 / UTM zone 55S EPSG:32656 WGS 84 / UTM zone 56N EPSG:32756 WGS 84 / UTM zone 56S EPSG:32657 WGS 84 / UTM zone 57N EPSG:32757 WGS 84 / UTM zone 57S EPSG:32658 WGS 84 / UTM zone 58N EPSG:32758 WGS 84 / UTM zone 58S EPSG:32659 WGS 84 / UTM zone 59N EPSG:32759 WGS 84 / UTM zone 59S EPSG:32605 WGS 84 / UTM zone 5N EPSG:32705 WGS 84 / UTM zone 5S EPSG:32660 WGS 84 / UTM zone 60N EPSG:32760 WGS 84 / UTM zone 60S EPSG:32606 WGS 84 / UTM zone 6N EPSG:32706 WGS 84 / UTM zone 6S EPSG:32607 WGS 84 / UTM zone 7N EPSG:32707 WGS 84 / UTM zone 7S EPSG:32608 WGS 84 / UTM zone 8N EPSG:32708 WGS 84 / UTM zone 8S EPSG:32609 WGS 84 / UTM zone 9N EPSG:32709 WGS 84 / UTM zone 9S
Mapinfo Utility for gdal_translate.
Jun 21st
I made a small perl utility to automate the gcp’s from Mapinfo Raster TABS to gdal_translate command line. Currently your tabfile would have:
!table !version 300 !charset WindowsLatin1 Definition Table File "beijing_6th_1.jpg" Type "RASTER" (116.522865,40.016316) (347,184) Label "Pt 1", (116.681215,40.015286) (7729,243) Label "Pt 2", (116.679777,39.777904) (7666,14674) Label "Pt 3", (116.523827,39.779108) (397,14606) Label "Pt 4" CoordSys Earth Projection 1, 104 Units "degree" RasterStyle 4 1 RasterStyle 7 1677695
How to use
gdal_mapinfo
1. ls *.TAB > init.sh
2. vi init.sh to reflect the ff:
perl gdal_mapinfo.pl Beijing_6th_1.TAB >> final.bat perl gdal_mapinfo.pl Beijing_6th_10.TAB >> final.bat perl gdal_mapinfo.pl Beijing_6th_11.TAB >> final.bat perl gdal_mapinfo.pl Beijing_6th_12.TAB >> final.bat perl gdal_mapinfo.pl Beijing_6th_13.TAB >> final.bat perl gdal_mapinfo.pl Beijing_6th_2.TAB >> final.bat perl gdal_mapinfo.pl Beijing_6th_3.TAB >> final.bat perl gdal_mapinfo.pl Beijing_6th_4.TAB >> final.bat perl gdal_mapinfo.pl Beijing_6th_5.TAB >> final.bat perl gdal_mapinfo.pl Beijing_6th_6.TAB >> final.bat perl gdal_mapinfo.pl Beijing_6th_7.TAB >> final.bat perl gdal_mapinfo.pl Beijing_6th_8.TAB >> final.bat perl gdal_mapinfo.pl Beijing_6th_9.TAB >> final.bat
3. The resulting final.bat should have the ff:
gdal_translate -gcp 347 184 116.522865 40.016316 -gcp 7729 243 116.681215 40.015286 -gcp 7666 14674 116.679777 39.777904 -gcp 397 14606 116.523827 39.779108 -of GTiff Beijing_6th_1.jpg I:\\satimages\translated\Beijing_6th_1_translated.tif
gdalwarp -s_srs epsg:4326 -t_srs epsg:4326 I:\\satimages\translated\Beijing_6th_1_translated.tif
I:\\satimages\warped\Beijing_6th_1.tif
Processing Mapinfo Raster JPEG Images using GDAL
Jun 14th
I have a couple of sat images (raw jpegs) from Google that I want to use with Openlayers/Mapserver. The raw jpegs were registered using Mapinfo via GCP (Ground Control Points).
Mapinfo Raster JPEG Images example:
rupert@rupert-winxp /e/home/map/beijing/new/satimages$ ll
-rw-r–r– 1 rupert None 358 Jan 30 03:23 2NE1.TAB
-rw-r–r– 1 rupert None 7.1M Jan 30 02:38 2NE1.jpg
-rw-r–r– 1 rupert None 356 Feb 1 18:56 2NE2a.TAB
-rw-r–r– 1 rupert None 3.8M Feb 1 08:57 2NE2a.jpg
You cannot fully reference 2NE1.TAB as a Mapserver Layer. I tried to use 2NE1.jpg, but the problem its not georeferenced.
rupert@rupert-winxp /e/home/map/beijing/new/satimages $ gdalinfo 2NE1.jpg Driver: JPEG/JPEG JFIF Size is 8650, 6744 Coordinate System is `' Corner Coordinates: Upper Left ( 0.0, 0.0) Lower Left ( 0.0, 6744.0) Upper Right ( 8650.0, 0.0) Lower Right ( 8650.0, 6744.0) Center ( 4325.0, 3372.0) Band 1 Block=8650x1 Type=Byte, ColorInterp=Red Band 2 Block=8650x1 Type=Byte, ColorInterp=Green Band 3 Block=8650x1 Type=Byte, ColorInterp=Blue
The georeference coordinates of 2NE1.jpg, just like an ESRI World File, is found in 2NE1.TAB…
rupert@rupert-winxp /e/home/map/beijing/new/satimages $ cat 2NE1.TAB !table !version 300 !charset WindowsLatin1 Definition Table File "2ne1.jpg" Type "RASTER" (116.38575,39.906105) (349,6619) Label "Pt 1", (116.390072,39.93201) (1160,317) Label "Pt 2", (116.42786,39.932296) (8210,253) Label "Pt 3", (116.4295878,39.90722318) (8522,6358) Label "Pt 4" CoordSys Earth Projection 1, 0 Units "degree"
I found hurting myself in trying to create an ESRI world file from the current MAPINFO Raster TABS. So, I decided to go for GeoTIFF since its native in Mapserver. Using GDAL utilities my only problem is how to put a coordinate system and reference to the raster.
On windows, you could use Frank’s FWTools. For Linux, compile GDAL by source with python would be extremely helpful later on. For installation of GDAL on Linux, we can use Mapserver’s Verbose Installation in Linux Guide.
GDAL – the saviour!.
GDAL utilities is extremely helpful in reprojection, scaling, image mosaics, etc. For now, we will use gdal_translate and gdal_warp. Please RTFM the utilities.
1. Using gdal_translate to specify the gcp’s registered in Mapinfo.
gdal_translate -gcp pixel line easting northing
Add the indicated ground control point to the output dataset. This option may be provided multiple times to provide a set of GCPs.
$ gdal_translate -gcp 349 6619 116.38575 39.906105 -gcp 1160 317 116.390072 39.93201 -gcp 8210 253 116.42786 39.932296 -gcp 8522 6358 116.4295878 39.90722318 -of GTiff 2NE1.jpg 2NE1translated.tif
Input file size is 8650, 6744
0...10...20...30...40...50...60...70...80...90...100 - done.
Note: even if we specify the gcp’s, gdal_translate would not specify the corner coordinates of the tiff.
rupert@rupert-winxp /e/home/map/beijing/new/satimages
$ gdalinfo 2NE1translated.tif
Driver: GTiff/GeoTIFF
Size is 8650, 6744
Coordinate System is `'
GCP Projection =
GCP[ 0]: Id=1, Info=
(349,6619) -> (116.38575,39.906105,0)
GCP[ 1]: Id=2, Info=
(1160,317) -> (116.390072,39.93201,0)
GCP[ 2]: Id=3, Info=
(8210,253) -> (116.42786,39.932296,0)
GCP[ 3]: Id=4, Info=
(8522,6358) -> (116.4295878,39.90722318,0)
Corner Coordinates:
Upper Left ( 0.0, 0.0)
Lower Left ( 0.0, 6744.0)
Upper Right ( 8650.0, 0.0)
Lower Right ( 8650.0, 6744.0)
Center ( 4325.0, 3372.0)
Band 1 Block=8650x1 Type=Byte, ColorInterp=Red
Band 2 Block=8650x1 Type=Byte, ColorInterp=Green
Band 3 Block=8650x1 Type=Byte, ColorInterp=Blue2. Use gdalwarp to reproject using the gcp and specify the coordinates.
The gdalwarp utility is an image mosaicing, reprojection and warping utility. The program can reproject to any supported projection, and can also apply GCPs stored with the image if the image is “raw” with control information.
$ gdalwarp -s_srs epsg:4326 -t_srs epsg:4326 2NE1translated.tif warped.tif
Creating output file that is 9422P x 5631L.
Processing input file 2NE1translated.tif.
:0...10...20...30...40...5050...60...70...80...90...
Let’s check after gdalwarp using gdalinfo…
$ gdalinfo warped.tif
Driver: GTiff/GeoTIFF
Size is 9422, 5631
Coordinate System is:
GEOGCS["WGS 84",
DATUM["WGS_1984",
SPHEROID["WGS 84",6378137,298.2572235630016,
AUTHORITY["EPSG","7030"]],
AUTHORITY["EPSG","6326"]],
PRIMEM["Greenwich",0],
UNIT["degree",0.0174532925199433],
AUTHORITY["EPSG","4326"]]
Origin = (116.383841930499160,39.933342296341991)
Pixel Size = (0.000004927579869,-0.000004927579869)
Metadata:
AREA_OR_POINT=Area
Corner Coordinates:
Upper Left ( 116.3838419, 39.9333423) (116d23'1.83"E, 39d56'0.03"N)
Lower Left ( 116.3838419, 39.9055951) (116d23'1.83"E, 39d54'20.14"N)
Upper Right ( 116.4302696, 39.9333423) (116d25'48.97"E, 39d56'0.03"N)
Lower Right ( 116.4302696, 39.9055951) (116d25'48.97"E, 39d54'20.14"N)
Center ( 116.4070558, 39.9194687) (116d24'25.40"E, 39d55'10.09"N)
Band 1 Block=9422x1 Type=Byte, ColorInterp=Red
Band 2 Block=9422x1 Type=Byte, ColorInterp=Green
Band 3 Block=9422x1 Type=Byte, ColorInterp=BlueSweet. Now, all we need to do is display the raster images in Mapserver/OpenLayers.
Specifying a raster image in Mapserver
LAYER
NAME “2NE1″
DATA “satimages/2NE1.tif”
TYPE RASTER
STATUS DEFAULT
ENDLAYER
NAME “2NE2″
DATA “satimages/2NE2a.tif”
TYPE RASTER
STATUS DEFAULT
END
Here is the end result…
.
Lessons learned, I tried to specify coordinate extents using gdal_translate -a_ullr ulx uly lrx lry. Specifying the coordinates was subjective by just looking at the cursor location of the registered image in Mapinfo. It is still best to use the GCP’s. Simply put, we need to be accurate in specifying corner coordinates in raster images to project them accurately.
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