I am having an ‘adventure’ connecting OCAD to a New York state WMS server that provides Ortho images of the state.
The servers url is : "http://www.orthos.dhses.ny.gov/ArcGIS/services/2014/MapServer/WMSServer?"
No password is required, and the ‘?’ is part of the url.
The problem I am having is that Ocad is complaining that it does not support the coordinate system used by the server.
I have tried selecting other coordinate systems in the map menu and experimented with setting up a custom coordinate system but not luck yet. I am starting with a blank map using with real world coordinates using ocad 11 and 12.
Any advice or help on how to resolve this would be… helpful.
I know its not the answer you want, but stop trying to use OCAD as a GIS system. It does very poorly in this area, and there are much better tools. Spend the time learning how to use QGIS, GDAL, OGR, and similar tools and you will actually be able to deal with different data sources and outputs. You will always be running into SRS errors on data sources, and need to learn how to figure out what projection the data actually is in, and override what it thinks it is. OCAD just doesn't have the flexibility to deal with all the issues you will encounter.
The WMS is stating that it supports the following CRS:
Use Pseudo-Mercator in OCAD - it's EPSG 3857
Grumpy Old Coach - I will try this tonight. Not sure if I had tried that setting.
Did you actually try to connect?
edwarddes: QGIS looks very interesting. Do you think that a valid workflow would be to use QGIS to create a background map and then use that in OCAD to create an O-Map? Or are you suggesting QGIS as an alternative to OCAD? Keep in mind that my ultimate goal is to use this data to create an O map.
Yeah i tried. I got the orthophotos loaded. 2nd provided layer of the wms worked. Looked quite blurried though.
works! Now I have a lot of geo-referenced data to work with. Time to start experimenting. Thank you both. I am also checking out QGIS.
I am sure I will be asking more questions.
So, I have question, which may mean I have no understanding what is transpiring here, but aren't ortho photos meant to be viewed stereoscopic ly? If so , then I would think they would be blurry if viewed together, in mono optic .
No, the things you view stereoscopically aren't orthophotos.
QGIS is great once you start getting into it. It also pairs well with Grass GIS.
The NY orthos I looked at were not so much blurry as they were not very high resolution. Depending of where in the sate you are looking the resolution seems to vary.
Coach: from wikipedia: "an aerial photograph geometrically corrected ('orthorectified') such that the scale is uniform: the photo has the same lack of distortion as a map."
I like to think of ortho photo as a picture taken orthogonally over the area. In other words, taken at a 90% angle - directly overhead so there is no distortion from taking the picture at a steep angle.
I'm sure there are map hackers out there that have a better explanation.
@Bernard: thats pretty much it.
Yeah, orthophotos are corrected for the fish-eye effect that the camera lens has, so that it behaves (in certain respects) like it it was straight down everywhere, not ust in the center of the image. Stereophotos don't have that correction.
I don't know what NY does but at the VT GIS site they indicate the resolution of all the different series of imagery. Some are 1m, some .5m, some .3m but if I'm lucky, there will be some that are 15 cm
@Bernard: Your description is correct, the main problem when orthorectifying images occur away from the center of the image in steep terrains: Even if you take each image vertically, and correct for all optical projection imperfections, there is no way to completely correct for height differences without first making a 3D model of the terrain surface.
Taking the images from higher altitude with a tele lens makes the problem much less acute.
@coach: Stereoscopic photos must also be rectified before you can use them to construct contour lines etc: This basically means using visible fixed points in each image (trig points, road junctions, houses etc, anything for which you have really accurate 3D coordinates) to do a reverse projection and calculate exactly where the camera was located when the image was taken and what the FOV was.
When you have that info for both images in a stereo pair then you'll know the exact 2D location for any feature which is visible in both images, and the stereo angle determines the altitude.
All this has become far, far easier when you start with good LiDAR scans. :-)
Thank you to all the brilliant minds on Attackpoint :-)
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