I have data with lat/lon attributes that I'm plotting onto a map. I then use the "line" mark to link the data points. It seems to automatically order them by the latitude attribute, which happens to bring two of my data points out of order:
How can I manually change the order of the linking?
Thanks!
There is a path shelf in Tableau, details of the usage can be found here:
http://kb.tableau.com/articles/knowledgebase/using-path-shelf-pattern-analysis
You just need to create a dimension and give each coordinate of your path a running number. Once you drop that dimension on the path shelf, Tableau will use it to determine the order of the coordinates.
Related
Below is a JavaScript page I have created that allows me add and freely move markers on the map. From this map I can figure out the regions I am interested in.
Basically what I want to do is show the same map using ggplot2/MarMap with coastline indicators + bathymetry data. I am really just interested in getting bathymetry data per GPS location, basically getting negative/positive elevation per Lat+Long, so I was thinking if I can plot it then I should be able to export data to a Database. I am also interested in coastline data, so I want to know how close I am (Lat/Long) to coastline, so with plot data I was also going to augment in DB.
Here is the R script that I am using:
library(marmap);
library(ggplot2);
a_lon1 = -79.89836596313478;
a_lon2 = -79.97179329675288;
a_lat1 = 32.76506070891712;
a_lat2 = 32.803624214389615;
dat <- getNOAA.bathy(a_lon1,a_lon2,a_lat1,a_lat2, keep=FALSE);
autoplot(dat, geom=c("r", "c"), colour="white", size=0.1) + scale_fill_etopo();
Here is the output of above R script:
Questions:
Why do both images not match?
In google-maps I am using zoom value 13. How does that translate in ggplot2/MarMap?
Is it possible to zoom in ggplot2/MarMap into a (Lat/Long)-(Lat/Long) region?
Is it possible to plot what I am asking for?
I don't know how you got this result. When I use your script, I get an error since the area your are trying to fetch from the ETOPO1 database using getNOAA.bathy() is too small. However, adding resolution=1 (this gives the highest possible resolution for the ETOPO1 database), here is what I get:
To answer your questions:
Why do both images not match?
Probably because getNOAA.bathy() returned an error and the object dat you're using has been created before, using another set of coordinates
In google-maps I am using zoom value 13. How does that translate in ggplot2/MarMap?
I have no clue!
Is it possible to zoom in ggplot2/MarMap into a (Lat/Long)-(Lat/Long) region?
I urge you to take a look at section 4 of the marmap-DataAnalysis vignette. This section is dedicated to working with big files. You will find there that you can zoom in any area of a bathy object by using (for instance) the subsetBathy() function that will allow you to click on a map to define the desired area
Is it possible to plot what I am asking for? Yes, but it would be much easier to use base graphics and not ggplot2. Once again, you should read the package vignettes.
Finally, regarding the coastline data, you can use the dist2isobath() function to compute the distance between any gps point and any isobath, including the coastline. Guess where you can learn more about this function and how to use it...
I have analysed tree core images through the raster package in an attempt to perform image analysis. In the image:
http://dx.doi.org/10.6084/m9.figshare.1555854
You can see the measured "vessels" (black and numbered) and also annual lines (red) which have been drawn using the locator function and represent each year of growth of the tree core.
By generating a list of the maximum y coordinates of each annual line I have been able to sort the vessels into years for this image. Which is what I am looking for. However, it has occurred to me that in reality things can get a little more difficult as seen in the next image:
http://figshare.com/articles/Complicated/1555855
The approach above will not work on this image as vessels from each year overrun so using the maximum y coordinates will not return the correct result.
So can anyone suggest another approach which may overcome this limitation? I have thought about using spatialpolygons but not sure this will achieve what I am looking for.
If you are creating the lines by clicking on the plot, you can use raster function drawLine or, for polygons, drawPoly. You could rasterize the polygons and mask that with the original image to get the vessels grouped by polygon (year).
I am trying to render some geographic data onto the map in Tableau. However, some data points located at the same point, so the shape images of the data points overlaps together. By clicking on a shape, you could only get the top one.
How can we distinguish the overlapped data points in Tableau? I know that we can manually exclude the top data to see another, but is there any other way, for example, make a drop down list in the right click menu to select the overlapped data points?
Thank you!
There are a couple of ways to deal with this issue.
Some choices you can try are:
Add some transparency to the marks by editing the color shelf properties. That way at least you get a visual indication when there are multiple marks stacked on top of each other. This approach can be considered a poor man's heat map if you have many points in different areas as the denser/darker sections will have more marks. (But that just affects the appearance and doesn't help you select and view details for marks that are covered by others)
Add some small pseudo-random jitter to each coordinate using calculated fields. This will be easier when Tableau supports a rand() function, but in the meantime you can get creative enough using other fields and the math function to add a little jitter. The goal here is to slightly shift locations enough that they don't stack exactly, but not enough to matter in precision. Depends on the scale.
Make a grid style heat map where the color indicates the number of data points in each grid. To do this, you'll need to create calculated fields to bin together nearby latitudes or longitudes. Say to round each latitude to a certain number of decimal places, or use the hex bin functions in Tableau. Those calculated fields will need to have a geographic role and be treated as continuous dimensions.
Define your visualization to display one mark for each unique location, and then use color or size to indicate the number of data points at that location, as opposed to a mark for each individual data point
I would like to create an online interactive map with filled contour plot layer like the ones can be seen on openweathermaps (I would like to use my own data for the plots).
What I need is also similar to the Leaflet heatmap (heatmap.js) but without dynamically changing the colors and the extent of the graphical objects (as in case of heatmap.js). Let's call them static heat maps.
I would like to know which mapping code/library can be used to produce such maps.
I am really newbie to these things, so please bear with me.
I tried Leaflet but did not find any plugin which would create filled contour map layers (static heatmap). I created the following map with Leaflet where the rectangles are geojson polylines and the color is based on some assigned values to every rectangle (elevation)
my leaflet attempt
The problem with this approach is that if higher resolution (smaller and more rectangles) is needed the site would really slow down.
I checked OpenLayers but did not see any similar examples.
I have the data in a matrix format:
Lat; Long; Value
.
.
Values are given in every gridpoints.
(if needed I would convert into other formats, like in case of the above attempt into geojson format)
The data is static, would be saved on the server.
So what I basically want to accomplish is a site where some spatial data is represented as filled contour map (static heatmap) and it is plotted over a map.
Here is my solution to the problem using open-source programs and free, online service:
(1) Processing the data in a GIS program. I used QGIS. I interpolated my data which is in grid points to get a high resolution raster map.
(2) Save the post-processed raster map as a georeferenced *.tif image.
(3) Import the image into TileMill. Remove the basemap and keep only the image as the only layer (style it).
(4) Export the 'map' from TileMill as MBTiles. This will save numerous *.png files (tiles) corresponding to different zoom levels. These are the same type as google or openstreetmap use for their online maps.
(5) Create a free account at Mapbox and create a new map project. Upload the MBTiles created by TileMill (can be directly uploaded from it). Style it.
(6) Use the Map ID corresponding to your created project to embed the map into html sites, e.g. the javascript code:
// Provide your access token
L.mapbox.accessToken = 'Mapbox will generate this for you';
// Create a map in the div #map
var map = L.mapbox.map('map', 'username.mapid', {
minZoom: 5,
maxZoom: 10
}).setView([47, 20], 8);
Example hosted on Mapbox
Sample image(I do not how long will the above link live):
In retrospect, the question would have been better fit to GIS stack exchange.
I have a scanned map from which i would like to extract the data into form of Long Lat and the corresponding value. Can anyone please tell me about how i can extract the data from the map. Is there any packages in R that would enable me to extract data from the scanned map. Unfortunately, i cannot find the person who made this map.
Thanks you very much for your time and help.
Take a look at OCR. I doubt you'll find anything for R, since R is primarily a statistical programming language.
You're better off with something like opencv
Once you find the appropriate OCR package, you will need to identify the x and y positions of your characters which you can then use to classify them as being on the x or y axis of your map.
This is not trivial, but good luck
Try this:
Read in the image file using the raster package
Use the locator() function to click on all the lat-long intersection points.
Use the locator data plus the lat-long data to create a table of lat-long to raster x-y coordinates
Fit a radial (x,y)->(r,theta) transformation to the data. You'll be assuming the projected latitude lines are circular which they seem to be very close to but not exact from some overlaying I tried earlier.
To sample from your image at a lat-long point, invert the transformation.
The next hard problem is trying to get from an image sample to the value of the thing being mapped. Maybe take a 5x5 grid of pixels and average, leaving out any gray pixels. Its even harder than that because some of the colours look like they are made from combining pixels of two different colours to make a new shade. Is this the best image you have?
I'm wondering what top-secret information has been blanked out from the top left corner. If it did say what the projection was that would help enormously.
Note you may be able to do a lot of the process online with mapwarper:
http://mapwarper.net
but I'm not sure if it can handle your map's projection.