I'm looking for some guidance on the approach I should take to mapping some points with R.
Earlier this year I went off to a forest to map the spatial distribution of some seedlings. I created a grid—every two meters I set down a flag with a tagname, and what I did is I would measure the distance from a flag to a seedling, as well as the angle using a military compass. I chose this method in hopes of getting better accuracy (GPS Garmins prove useless for this sort of task under canopy cover).
I am really new to spatial distribution work altogether, so I was hoping someone could provide guidance on what R packages I should use.
First step is to create a grid with my reference points (the flags). Second step is to tell R to use a reference point and my directions to mark the location of a seedling. From there come other things, such as cluster analysis.
The largest R package for analysing point pattern data like yours is spatstat which has a very detailed documentation and an accompanying book.
For more specific help you would need to upload (part of) your data so we can see how it is organised and how you should read it in and convert to standard x,y coordinates.
Full disclosure: I'm a co-author of both the package and the book.
Related
Background:
I got a unidirectional planner graph, each node in the graph contains its location and to which nodes it's connected to(up to 4 nodes each one in a separated variable).
Each connection between nodes is an edge, a road segment and each node is a junction\dead end.
The road should follow a 2D polar grid layout and will be edited in runtime.
This will be used as a road-building tool for city building game.
I'm using UE4 C++ and I'm pretty new to procedural generation.
The issue:
I'm looking for some guidance on how to generate the topology.
1. What algorithms\method\technic\math I should use or know about?
2. If I should use the extrude method then how do I include the junctions?
3. Where should I have overlapping verts? (other then places where I need to cut for UVs)
4. How do I incorporate sidewalk to the road segments and the junctions
Research:
The best way that I found is basically the extrude method which seems too primitive and will be problematic with intersections since it requires to lookup verts locations which seems extremely inefficient.
More details about the graph:
https://gamedev.stackexchange.com/questions/179214/generate-road-mesh-from-a-graph
(I'm posting here because game dev seems to be pretty dead sadly)
I'm trying to figure out the best way to analyse a grasshopper/rhino floor plan. I am trying to create a room map to determine how many doors it takes to reach an exit in a residential building. The inputs are the room curves, names and doors.
I have tried to use space syntax or SYNTACTIC, but some of the components are missing. Alot of the plugins I have been looking at are good at creating floor plans but not analysing them.
Your help would be greaty appreciated :)
You could create some sort of spine that goes through the rooms that passes only through doors, and do some path finding across the topology counting how many "hops" you need to reach the exit.
So one way to get the topology is to create a data structure (a tuple, keyValuePair) that holds the curve (room) and a point (the door), now loop each room to each other and see if the point/door of each of the rooms is closer than some threshold, if it is, store the relationship as a graph (in the abstract sense you don't really need to make lines out of it, but if you plan to use other plugins for path-finding, this can be useful), then run some path-finding (Dijkstra's, A*, etc...) to find the shortest distance.
As for SYNTACTIC: If copying the GHA after unblocking from the installation path to the special components folder (or pointing the folder from _GrasshopperDeveloperSettings) doesn't work, tick the Memory load *.GHA assemblies using COFF byte arrays option of the _GrasshopperDeveloperSettings.
*Note that SYNTACTIC won't give you any automatic topology.
If you need some pseudo-code just write a comment and I'd be happy to help.
I am working on an image manipulation problem. I have an overhead projector that projects onto a screen, and I have a camera that takes pictures of that. I can establish a 1:1 correspondence between a subset of projector coordinates and a subset of camera pixels by projecting dots on the screen and finding the centers of mass of the resulting regions on the camera. I thus have a map
proj_x, proj_y <--> cam_x, cam_y for scattered point pairs
My original plan was to regularize this map using the Mathscript function griddata. This would work fine in MATLAB, as follows
[pgridx, pgridy] = meshgrid(allprojxpts, allprojypts)
fitcx = griddata (proj_x, proj_y, cam_x, pgridx, pgridy);
fitcy = griddata (proj_x, proj_y, cam_y, pgridx, pgridy);
and the reverse for the camera to projector mapping
Unfortunately, this code causes Labview to run out of memory on the meshgrid step (the camera is 5 megapixels, which apparently is too much for labview to handle)
I then started looking through openCV, and found the cvRemap function. Unfortunately, this function takes as its starting point a regularized pixel-pixel map like the one I was trying to generate above. However, it made me hope that functions for creating such a map might be available in openCV. I couldn't find it in the openCV 1.0 API (I am stuck with 1.0 for legacy reasons), but I was hoping it's there or that someone has an easy trick.
So my question is one of the following
1) How can I interpolate from scattered points to a grid in openCV; (i.e., given z = f(x,y) for scattered values of x and y, how to fill an image with f(im_x, im_y) ?
2) How can I perform an image transform that maps image 1 to image 2, given that I know a scattered mapping of points in coordinate system 1 to coordinate system 2. This could be implemented either in Labview or OpenCV.
Note: I am tagging this post delaunay, because that's one method of doing a scattered interpolation, but the better tag would be "scattered interpolation"
So this ends up being a specific fix for bugs in Labview 8.5. Nevertheless, since they're poorly documented, and I've spent a day of pain on them, I figure I'll post them so someone else googling this problem will come across it.
1) Meshgrid bombs. Don't know when this was fixed, definitely a bug in 8.5. Solution: use the meshgrid-like function on the interpolation&extrapolation pallet instead. Or upgrade to LV2009 which apparently works (thanks Underflow)
2) Griddata is defective in 8.5. This is badly documented. The 8.6 upgrade notes say that a problem with griddata and the "cubic" setting, but it is fact also a problem with the DEFAULT LINEAR setting. Solutions in descending order of kludginess: 1) pass 'v4' flag, which does some kind of spline interpolation, but does not have bugs. 2) upgrade to at least version 8.6. 3) Beat the ni engineers with reeds until they document bugs properly.
3) I was able to use the openCV remap function to do the actual transformation from one image to another. I tried just using the matlab built in interp2 vi, but it choked on large arrays and gave me out of memory errors. On the other hand, it is fairly straightforward to map an IMAQ image to an IPL image, so this isn't that bad, except for the addition of the outside library.
Say I want to build a check-in aggregator that counts visits across platforms, so that I can know for a given place how many people have checked in there on Foursquare, Gowalla, BrightKite, etc. Is there a good library or set of tools I can use out of the box to associate the venue entries in each service with a unique place identifier of my own?
I basically want a function that can map from a pair of (placename, address, lat/long) tuples to [0,1) confidence that they refer to the same real-world location.
Someone must have done this already, but my google-fu is weak.
Yes, you can submit the two addresses using geocoder.net (assuming you're a .Net developer, you didn't say). It provides a common interface for address verification and geocoding, so you can be reasonably sure that one address equals another.
If you can't get them to standardize and match, you can compare their distances and assume they are the same place if they are below a certain threshold away from each other.
I'm pessimist that there is such a tool already accessible.
A good solution to match pairs based on the entity resolution literature would be to
get the placenames, define and use a good distance function on them (eg. edit distance),
get the address, standardize (eg. with the mentioned geocoder.net tools), and also define distance between them,
get the coordinates and get a distance (this is easy: there are lots of libraries and tools for geographic distance calculations, and that seems to be a good metric),
turn the distances to probabilities ("what is the probability of such a distance, if we suppose these are the same places")(not straightforward),
and combine the probabilities (not straightforward also).
Then maybe a closure-like algorithm (close the set according to merging pairs above a given probability treshold) also can help to find all the matchings (for example when different names accumulate for a given venue).
It wouldn't be a bad tool or service however.
I'm working on a project that contains Thomas Brothers Map page and grid numbers. Is there a way to programatically convert from this map page to a latitude & longitude?
An Example would be for the intersection of the US101 & I405 freeways.
ThomasBrothers: 561-3G (page-grid)
Not that I know of, but I don't have a lot of experience with Thomas bros maps. Are you talking about printed version of the maps or is there a link somewhere to an online map?
If you just need a few lat/longs, then you can look up the locations that correspond to the grid and get the lats and longs manually at many websites, including http://itouchmap.com/latlong.html
If you provide a link to a Thomas bros map that you are using, I might be able to help further.
By looking at the link above, you can determine that US 101 and I-405 has a latitude of 34.16073390017978 and a longitude of -118.46952438354492.
Your best source would be the map publisher. If they choose to help, someone there can tell you exactly what you need to know. If they won't help you, it's unlikely that they've released the information to anyone else.
If that's the case, you could do some work by hand to correlate one point from the map grid to your target coordinate system. Effectively, you could reverse engineer a mapping "datum" for each page. You'd also have to know what map projection was used to render the maps, so that you can calculate the transform from the map coordinates to the geographic coordinates as you move away from your "origin". Finally, you'll need to establish the orientation of the map, since different notions of "north" exist.
It sounds like the Thomas maps use a new grid for every page, rather than bleeding the grid continuously from page to page. If that's the case, you'll have to correlate one point on each map. For example, find a spot where a map grid intersection coincides with a notable road intersection. Then you can find the coordinates of the road intersection using a map with latitude and longitude (a topographic map, TerraServer, etc.). Doing this with two points on the same vertical grid line should help you establish the north used on the map as well.
The short answer is that each of the nine regions has a grid derived from a Lambert conformal conic projection with custom parameters, so you cannot write a conversion program without the parameters.
I've also got ThomasBros. pages that I would like to convert to lat/long for lookup against Google Maps API. They also provided something called TBXY ... not sure what this is -- perhaps some notation for GPS/lat/long?
<Area>"El Cajon"</Area>
<ThomasBrothers>"1297 5E"</ThomasBrothers>
<TBXY>"6481390:1827008"</TBXY>
Thomas Brothers Maps invested a lot when developing their GIS system to create their digital mapping system. Though the first "digitally produced" map was Sacramento County-1990, the development began back in 1986. I expect that their map projection equations are a well guarded trade-secret, which Rand McNally now owns. I'd don't know those equations, but would also like to know them.
There are 9 projections covering the 48 states. If you know the equations for Los Angeles, it is valid across California & Nevada. Oregon & Washington have their own projection. Arizona, New Mexico, Colorado, and Utah share another projection.
I do know this...
As many know, the page grid is an exact 1/2 mile square, or 2640 feet by 2640 feet. The coordinate measurement unit is 1 foot.
To determine the Thomas Brothers XY Coordinate, get one or more of the Thomas Guide CD- ROM maps, which were recently discontinued. The last ones produced for certain California counties were the 2008 edition. Last editions for Seattle, Portland, Las Vegas, and Phoenix/Tucson were the 2007 edition. Each is still available on the Rand McNally website for $20.
When you geo-code a group of addresses, you'll see an output file with the TGXY coordinates and Lat/Lon for the addresses you specified, and the page # and grid that point is in. Once that file is open, you can click on the map to add additional geo-coded points, which will also provide both the coordinates. The output file is saved in an Access database ".mdb" file.
If you know a lot about map projections or solid geometry, the set of corresponding TGXY and Lat/Lon coordiantes will provide you some good data for testing.
As you mentioned San Diego Page 1297, I'll provide its bordering coordinates.
West x=3062760
East x=3086520
North y=0985040
South-y=0966560
This is not in range of the "TBXY" you found on Google. Maybe it's the same projection, with a relocated origin.