New answers tagged distance
Intersection of two paths given start points and bearings could be used. You would need to check the resulting point to make sure it is between B and C. Since there's no spheroid flattening, I'm not sure how close it would match up with Vincenty's formula. Formula: d12 = 2.asin( √(sin²(Δφ/2) + cos(φ1).cos(φ2).sin²(Δλ/2)) ) φ1 = acos( sin(φ2) − ...
If all you want are smaller polygons, you can use a negative buffer (buffer tool with a negative buffer size). You might want to combine the negative buffer with a simplification depending on what you want to use the output for.
If you have an ArcInfo (or Advanced) license level the Near Analysis tool should give you exactly what you need. It will add the ID of the nearest feature to your input point feature class attribute table, and a distance as well. FYI - The distance will be in the units of your input data's projection.
In Arc10.1 there are 3 tools that will complete this task: Near Near3d (3d analyst) Generate Near Table Both Near and Near 3d will change your original data while Generate Near Table will create a separate table output. Near 3d may be the best option for mountainous terrain with high relief, but if you lack the 3d Analyst license or are working ...
As stated the question seems to me that designing a transmission system from thin air with 9 subs is infeasable. So assuming that the OP has some design in place and/or existing infrastructure is the only way I can see that there can be a solution. That said some improvisation can be accomplished by assuming that the network will folow existing ...
If you have ArcInfo you can run a Near analysis to calculate the distance to the nearest feature and then get the average from the NEAR_DIST field. If you don't have you may need to write a script and depending on the size of your data-sets, you may want to create a fishnet first to minimize the amount of processing time.
You could try running your point and polyline dataset through the spatial join geo-processing tool. If you set the match option to closest you can also specify a distance field which gives you the distance to the nearest polyline. From that you can do your summary statistics. So fire up desktop help and look for the spatial join tool.
If your facilities and incidents are both feature layers, and you only care about finding the closest (and not 2nd closest, 3rd closest, etc.) then you can just run Spatial Join. Set your incidents as the target_features, facilities as join_features, and closest as the match_option, and it will join the attributes of the nearest facility to each incident.
Although I have found no documentation to the effect that a Projected Coordinate System is required it is perhaps unsurprising that a Geographic Coordinate System is unsupported because the length of a degree varies depending on the latitude. I suspect that a documentation enhancement is the most that is likely to happen with this but I encourage you to ...
Make sure your point data is in a projected coordinate system, then you can use the Euclidean Distance tool. This should produce a raster of distance that you can plug into your Fuzzy Membership tool.
gis-lab.info has a tutorial on using the network analysis library in QGIS using Python. It's not in English but Google Translate should be able to make it comprehensible. Good luck!
There are a handful of useful tools on this page. One of them calculates the distance between two points. It has the option to draw the points on the map with the Great Circle showing as well as the option to draw a profile and export the data.
Try removing ::geography. That might help
The simplest way to do this is to use the linear referencing methods with Shapely. from shapely.geometry import LineString, Point # Example data busRoute = LineString([(80, 380), (160, 380), (220, 370), (280, 330), (310, 210), (379, 185)]) currentLocation = Point(280, 350) # The current location is not exactly on the bus route ...
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