I'm trying to create a Grid Layer of Either Rectangles or Hexagons in React Map GL(Map Box) and Deck GL, that cover an entire country.
This is what I'm trying to achieve: http://webcoveragemap.rootmetrics.com/en-US
These are the Solutions I've found:
https://deck.gl/#/documentation/deckgl-api-reference/layers/s2-layer
https://deck.gl/#/documentation/deckgl-api-reference/layers/h3-cluster-layer
The problem I'm facing with is that s2-layer uses S2 Cell token (Which I can't seem to understand how to calculate and similarly h3-cluster-layer uses H3 and for that too I can't find any code samples for React. So can anybody explain me either how to use H3, S2 and calculate 50sq km boxes that can be viewed on React Map Gl with Deck GL (if needed). Or suggest another Solution?
Turns out there's java script version of H3-Core Library (A hexagon-based geographic grid system). https://www.npmjs.com/package/h3-js
All it require's to convert a lat/lng point to a hexagon index at some resolution is following code:
const h3Index = h3.geoToH3(37.3615593, -122.0553238, 7);
// -> '87283472bffffff'
Related
I am using GMap.NET to display a lot of Marker (about more than 10.000 markers). R-Tree is a solution to optimize render markers at area which window is showing.
STRtree in NetTopologySuite is a library to support R-tree. But I'm not sure it suitable for this problem.
My question is how to use R-Tree in NetTopologySuite to show markers. I don't know how to use library. (I'm new in WPF). How to catch event when GMap render marker to get marker from R-Tree and remove previous marker at same time?
Please give me some example about R-tree in NetTopologySuite.
I did it by my way. This is the way STRtree is decleared: STRtree<Coordinate> gpsSTRtree = new STRtree<Coordinate>(); You can change Coordinate data type by any other data type but STRtree need to Envelope to insert to tree.
For example: insert to STRtree:
Coordinate gps = new Coordinate(9.74233, 106.0213);
Envelope item = new Envelope(gps);
gpsSTRtree.Insert(item, gps);
Envelope is a node in STRtree to store the boundary of item.
STRtree query from two points. point1 and point2 are Coordinate
Envelope gpsQuery = new Envelope(p1, p2);
Coordinate gpsItems = gpsSTRtree.Query(gpsQuery);
Then you have a list of Coordinate
Good luck
My Codename One app features a MapContainer. I need to show points of interest (POIs) on it which coordinates reside on the server. There can be hundreds (maybe thousands in the future) of such POIs on the server. That's why I would like to only download from the server the POIs that can be shown on the map. Consequently I need to get the map boundaries to pass them to the server.
I read this for Android and this other SO question for iOS and the key seems to get the map Projection and the map bounding box. However the getProjection() method or the getBoundingBox() seem not to be exposed.
A solution could be to mix the coordinates from getCameraLocation() which is the map center and getZoom() to infer those boundaries. But it may vary depending on the device (see the shown area can be larger).
How can get the map boundaries in Codename one ?
Any help appreciated,
Cheers,
The problem is in the javadocs for getCoordAtPosition(). This will be corrected. getCoordAtPosition() expects absolute coordinates, not relative.
E.g
Coord NE = currentMap.getCoordAtPosition(currentMap.getWidth(), 0);
Coord SW = currentMap.getCoordAtPosition(0, currentMap.getHeight());
Should be
Coord NE = currentMap.getCoordAtPosition(currentMap.getAbsoluteX() + currentMap.getWidth(), currentMap.getAbsoluteY());
Coord SW = currentMap.getCoordAtPosition(currentMap.getAbsoluteX(), currentMap.getAbsoluteY() + currentMap.getHeight());
I tried this out on the coordinates that you provided and it returns valid results.
EDIT March 21, 2017 : It turns out that some of the platforms expected relative coordinates, and others expected absolute coordinates. I have had to standardize it, and I have chosen to use relative coordinates across all platforms to be consistent with the Javadocs. So your first attempt:
Coord NE = currentMap.getCoordAtPosition(currentMap.getWidth(), 0);
Coord SW = currentMap.getCoordAtPosition(0, currentMap.getHeight());
Will now work in the latest version of the library.
I have also added another method : getBoundingBox() that will get the bounding box for you without worrying about relative/absolute coordinates.
This is probably something that can be exposed easily by forking the project and providing a pull request. We're currently working on updating the map component so this is a good time to make changes and add features.
I am working on a custom game map. This map is basically a raster image, overlayed with some paths and markers. I want to use Leaflet to display the map.
What I am struggling with, is that Leaflet uses Latitude and Longitude to calculate positions, while it uses meters for distances (path lengths, radii of circles, etc).
This is very understandable when dealing with a spherical world like our Earth, but it complicates the custom map, which is flat a lot.
I would like to be able to specify the positions in the same unit as the distances.
Now, by default Leaflet uses a Spherical Mercator projection. According to the Docs, it is possible to define your own projections and coordinate reference systems, but I have been unable to do this thus far.
How would this be possible? Or is there a simpler way?
You should take a look at the simple coordinate reference system (L.CRS.Simple) included with Leaflet:
A simple CRS that maps longitude and latitude into x and y directly. May be used for maps of flat surfaces (e.g. game maps).
You can define the CRS of your L.Map instead upon initialization like so:
new L.Map('myDiv', {
crs: L.CRS.Simple
});
Some further elaboration: As #ghybs pointed out in the comment below and the comment to your question the default sperical mercator projection (L.CRS.EPSG3857) already works in meters. When you calculate the distance between two coordinates, Leaflet returns meters, example:
var startCoordinate = new L.LatLng(0, -1);
var endCoordinate = new L.LatLng(0, 1);
var distance = startCoordinate.distanceTo(endCoordinate);
console.log(distance);
The above will print 222638.98158654713 to your console which is the distance between those two coordinates in meters. Problem is that when using spherical projection, distance between two coordinates will become less the further you get from the equator which will become problematic when creating a flat gameworld. That's why you should use L.CRS.Simple, you won't have said problem.
I'm using PostGIS on ruby/rails, and have created a simple box-like polygon under which I wish to search for land parcels in a county. The st_overlaps tool has worked for this before and it has worked this time, sort of.
So I created the polygon to search for parcels (multi-polygons, as it turns out) underneath it
factory = RGeo::Cartesian.factory
coords = [[1554780, 1101102], [1561921, 1062647], [1634713, 1097531], [1630867, 1140657]]
points = coords.map { |pair| RGeo::WKRep::WKTParser.new.parse("POINT (#{pair.first} #{pair.last})") }
ring = factory.linear_ring(points)
polygon = factory.polygon(ring)
After running the active record call:
Parcel.where{st_overlaps(:parcel_multipolygon, polygon)}
I get 157 results. Far less than expected. I exported them a kml file using a custom script of mine. I will upload it soon for viewing.
What you'll see in that kml once loaded in Google Earth, is a parallelogram of pins marking parcels whose areas (polygons) are clearly saddling the outer ring of the parameter-polygon I created to search under. There are so many parcels along these invisible lines in such a clear, distinct shape, the fact that there are no pins in the middle of the shape clearly indicate that the search results were only at the overlappings of parcel multipolygons with the exterior edges (LinearRing) of the search polygon.
Based on my re-reading of the documentation for st_overlaps, I'm left puzzled as to what seems to be the problem here.
Here's a link to view the kmz export. (coordinates converted to geographic before export). You can view it in your browser. The search-polygon itself is not included, but its easy to see where its exterior ring is
https://docs.google.com/file/d/0B5inC0VAuhH1TXdTbWQ2RngxZk0/edit?usp=sharing
I think it is behaving as expected. St_overlaps will give features that actually lie on top of each other. If you want all features inside the polygon try ST_Intersects.
I am now working on an eye tracking project. In this project I am tracking eyes in a webcam video (resolution if 640X480).
I can locate and track the eye in every frame, but I need to locate the pupil. I read a lot of papers and most of them refer to Alan Yuille's deformable template method to extract and track the eye features. Can anyone help me with the code of this method in any languages (matlab/OpenCV)?
I have tried with different thresholds, but due to the low resolution in the eye regions, it does not work very well. I will really appreciate any kind of help regarding finding pupil or even iris in the video.
What you need to do is to convert your webcam to a Near-Infrared Cam. There are plenty of tutorials online for that. Try this.
A Image taken from an NIR cam will look something like this -
You can use OpenCV then to threshold.
Then use the Erode function.
After this fill the image with some color takeing a corner as the seed point.
Eliminate the holes and invert the image.
Use the distance transform to the nearest non-zero value.
Find the max-value's coordinate and draw a circle.
If you're still working on this, check out my OptimEyes project: https://github.com/LukeAllen/optimeyes
It uses Python with OpenCV, and works fairly well with images from a 640x480 webcam. You can check out the "Theory Paper" and demo video on that page also. (It was a class project at Stanford earlier this year; it's not very polished but we made some attempts to comment the code.)
Depending on the application for tracking the pupil I would find a bounding box for the eyes and then find the darkest pixel within that box.
Some psuedocode:
box left_location = findlefteye()
box right_location = findrighteye()
image_matrix left = image[left_location]
image_matrix right = image[right_location]
image_matrix average = left + right
pixel min = min(average)
pixel left_pupil = left_location.corner + min
pixel right_pupil = right_location.corner + min
In the first answer suggested by Anirudth...
Just apply the HoughCirles function after thresholding function (2nd step).
Then you can directly draw the circles around the pupil and using radius(r) and center of eye(x,y) you can easily find out the Center of Eye..