The output of this image from gdalinfo 20141030-wv03.tif is like this:
Driver: GTiff/GeoTIFF
Files: 20141030-wv03.tif
Size is 16484, 15253
Coordinate System is:
GEOGCRS["WGS 84",
DATUM["World Geodetic System 1984",
ELLIPSOID["WGS 84",6378137,298.257223563,
LENGTHUNIT["metre",1]]],
PRIMEM["Greenwich",0,
ANGLEUNIT["degree",0.0174532925199433]],
CS[ellipsoidal,2],
AXIS["geodetic latitude (Lat)",north,
ORDER[1],
ANGLEUNIT["degree",0.0174532925199433]],
AXIS["geodetic longitude (Lon)",east,
ORDER[2],
ANGLEUNIT["degree",0.0174532925199433]],
ID["EPSG",4326]]
Data axis to CRS axis mapping: 2,1
Origin = (113.959353776485997,23.091020758099145)
Pixel Size = (0.000002966620901,-0.000002966620901)
Metadata:
AREA_OR_POINT=Area
DataType=Generic
Image Structure Metadata:
COMPRESSION=LZW
INTERLEAVE=PIXEL
Corner Coordinates:
Upper Left ( 113.9593538, 23.0910208) (113d57'33.67"E, 23d 5'27.67"N)
Lower Left ( 113.9593538, 23.0457709) (113d57'33.67"E, 23d 2'44.78"N)
Upper Right ( 114.0082556, 23.0910208) (114d 0'29.72"E, 23d 5'27.67"N)
Lower Right ( 114.0082556, 23.0457709) (114d 0'29.72"E, 23d 2'44.78"N)
Center ( 113.9838047, 23.0683958) (113d59' 1.70"E, 23d 4' 6.22"N)
Band 1 Block=128x128 Type=Byte, ColorInterp=Red
NoData Value=256
Band 2 Block=128x128 Type=Byte, ColorInterp=Green
NoData Value=256
Band 3 Block=128x128 Type=Byte, ColorInterp=Blue
NoData Value=256
The spatial resolution is (0.000002966620901,-0.000002966620901), how to understand this value?
I also check another image from WorldView 2, ths output is:
Driver: GTiff/GeoTIFF
Files: 20150708.tif
Size is 9984, 10132
Coordinate System is:
PROJCRS["WGS 84 / UTM zone 50N",
BASEGEOGCRS["WGS 84",
DATUM["World Geodetic System 1984",
ELLIPSOID["WGS 84",6378137,298.257223563,
LENGTHUNIT["metre",1]]],
PRIMEM["Greenwich",0,
ANGLEUNIT["degree",0.0174532925199433]],
ID["EPSG",4326]],
CONVERSION["UTM zone 50N",
METHOD["Transverse Mercator",
ID["EPSG",9807]],
PARAMETER["Latitude of natural origin",0,
ANGLEUNIT["degree",0.0174532925199433],
ID["EPSG",8801]],
PARAMETER["Longitude of natural origin",117,
ANGLEUNIT["degree",0.0174532925199433],
ID["EPSG",8802]],
PARAMETER["Scale factor at natural origin",0.9996,
SCALEUNIT["unity",1],
ID["EPSG",8805]],
PARAMETER["False easting",500000,
LENGTHUNIT["metre",1],
ID["EPSG",8806]],
PARAMETER["False northing",0,
LENGTHUNIT["metre",1],
ID["EPSG",8807]]],
CS[Cartesian,2],
AXIS["(E)",east,
ORDER[1],
LENGTHUNIT["metre",1]],
AXIS["(N)",north,
ORDER[2],
LENGTHUNIT["metre",1]],
USAGE[
SCOPE["unknown"],
AREA["World - N hemisphere - 114°E to 120°E - by country"],
BBOX[0,114,84,120]],
ID["EPSG",32650]]
Data axis to CRS axis mapping: 1,2
Origin = (291153.100000000034925,2705938.760000000242144)
Pixel Size = (0.510000000000000,-0.510000000000000)
Metadata:
AREA_OR_POINT=Area
TIFFTAG_XRESOLUTION=1
TIFFTAG_YRESOLUTION=1
Image Structure Metadata:
INTERLEAVE=BAND
Corner Coordinates:
Upper Left ( 291153.100, 2705938.760) (114d56'22.85"E, 24d27'10.88"N)
Lower Left ( 291153.100, 2700771.440) (114d56'25.58"E, 24d24'22.98"N)
Upper Right ( 296244.940, 2705938.760) (114d59'23.60"E, 24d27'13.32"N)
Lower Right ( 296244.940, 2700771.440) (114d59'26.26"E, 24d24'25.41"N)
Center ( 293699.020, 2703355.100) (114d57'54.57"E, 24d25'48.15"N)
Band 1 Block=9984x1 Type=Byte, ColorInterp=Red
Band 2 Block=9984x1 Type=Byte, ColorInterp=Green
Band 3 Block=9984x1 Type=Byte, ColorInterp=Blue
The spatial resolution is (0.510000000000000,-0.510000000000000). How do I understand their difference between them? Thanks.
Your images are in two different coordinate systems.
Your second file 20150708.tif is in an UTM projection (UTM 50N to be exact) which has map units in meters - that's why the pixel resolutions is in meters (0.51m).
Your first file 20141030-wv03.tif is in a geographic coordinate system, the widely used World Geodetic System 1984 (or WGS84) which has map units in degrees, giving you the pixel resolution also in (decimal) degrees. On the equator 0.00001 degrees is around 1.11 meters so both images have likely the same resolution.
For more info on WGS84 vs UTM, this post on GIS stackexchange might be interesting.