I have a few building data in shapefile. Now I want to add some small circules/rectangles/anything suitable to represent the lighting poles beside the building. How could I do that in R.
Currently I read in the shapefile in R by readOGR command.
and display it in shiny as below:
After adding the lighting poles, it should look like:
Moving forward, the size of the circle should be the brightness of the lighting. Could anyone kindly advise how to implement this or which package is useful to do it?
Thank you!
Related
So I hope I can clearly communicate my issue. Since I'm fairly new to R and ArcGIS I may miss some obvious things.
Basically, I'm using R to process spatial data to make a canopy height model and detect tree tops. That parts fine. I then make a watershed segment plot using forestTools package, and visually it looks great, but how do I export that as a file I can add into ArcGIS?
I'll copy some of the code that goes into what I'm discussing.
Basically, I just followed this guide's supplemental material to get the tree detection https://www.degruyter.com/document/doi/10.1515/geo-2020-0290/html?lang=en.
With that done, I then used the forestTools package to creat an interesting segmentation polygon grid on the map. https://www.rdocumentation.org/packages/ForestTools/versions/0.2.5/topics/mcws
This is quickly the plotting code to get visualized what I want.
[1]: https://i.stack.imgur.com/7Y0EF.png
This is what the map looks like with those plotted.
[2]: https://i.stack.imgur.com/Kdfl6.png
The layer that I want to bring solo to ArcGIS is that last plot the mcws one. I'll show a pic of that as well here.
[3]: https://i.stack.imgur.com/3PKfk.png
Is there a way that I can export that as a .shp or .tif?
Any help would be wonderful and much appreciated!
Nvmd I figured it out.
What you have to do is use the Raster package to export a shapefile.
raster::shapefile(site2_ttops,"Products/site2plot_ttops.shp")
I would like to use ggmap to plot several data points on top of a koppen-geiger climate map.
The kopper-geiger data and GIS/KMZ maps can be downloaded here:
http://koeppen-geiger.vu-wien.ac.at/present.htm
I've managed to have a code to plot the points on regular maps, obtained through the get_map function but I fail to use other maps such as koppen-geiger.
Any help will be appreaciated!
Your basic problem is that the map you are attmepting to use is an image file that is not georeferenced. So unless you want to go through the unnecessary and probably time consuming process of georeferencing this image yourself, you will be better taking an alternative approach. There are perhaps a few ways to do this. But, unless you have very few data points to overlay on the map which you can place manually using the lat-long grid of the image, then the least painful method will certainly be to redraw the map yourself using the shapefile.
This is not the right place to give you an introductory lesson on GIS, but the basic steps are to
Download shapefile (which is available at the same website as the image you linked)
Project map to desired coordinate system
Plot map, coloring by climate class
Color the ocean layer
Add labels, legend, and graticule, as desired
Overplot with your own climate data, and legend for these.
If you are unsure how to approach any of these steps, then take an introductory course on GIS, and search the Web for instructional materials. You may find this resource useful.
https://cran.r-project.org/doc/contrib/intro-spatial-rl.pdf
I have the following SpatialPolygonsDataFrame.
require(raster)
usa <- getData('GADM', country='USA', level=2)
metro <- subset(usa, NAME_1=="Nebraska" & NAME_2 %in% c("Dodge","Douglas","Sarpy","Washington"))
plot(metro)
I would like to be able to replicate the following map boundaries (defined by the colors):
Does anyone know a good plan of attack? I realize this is a somewhat manual process. I have already downloaded all US Census files that are of a more detailed geography. I was hoping that a more detailed level of geography could be aggregated to answer the above question, but unfortunately the districts do not line up the same.
Is there a R function already out there that would be helpful in assisting this manual process? At the very minimum, I would like to be able to leverage the perimeter of the 4-county area.
Use writeOGR from the rgdal package to create a shapefile of your metro object. Then install QGIS (http://www.qgis.org/), a free and open-source GIS, and load the shapefile as a new layer.
Then you can edit the layer, add new polygons, edit lines etc, then save as a shapefile to read back into R.
Additionally, you may be able to "georeference" your image (by identifying known lat-long points on the image) and load that into QGIS as a raster layer. That makes it easier to digitise your new areas. All you need for that is a few lat-long coordinates of specific points, such as the corners of polygons or line intersections, and then QGIS has a georeferencing plugin that can do it.
I don't think you'll find any R code as suitable for digitising new geometries over an image as good as QGIS.
After half an hour (and twenty years experience, not all of which you'll need) I've got this:
I didn't precisely digitise your new boundaries though, just roughly for speed. That QGIS screen cap shows the five coloured areas under the four metro areas.
Step one was georeferencing. This screengrab shows how the PNG has been georeferenced - the red line is the metro area shapefile drawn with transparency over the PNG after the PNG has been converted to a GeoTIFF by matching control points.
Step two was then using QGIS editing tools to split, join, and create new polygons. Then I just coloured them and added labelling to pretty it up.
I could probably bundle these files all up for you to neaten, but it really doesn't take that long and you'll learn a lot from doing it. Also, this is probably a gis.stackexchange.com question...
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.
I need to plot, in 3D, a set of densities associated to a time series. More precisely, I would like to be able in R to build an image close to this example
This image is taken from [1]. The transparency plays an important role as let us see the trajectory of the "measures" in the x-y plane.
Any help will be greatly appreciated.
[1]: Juban and Kariniotakis, "Uncertainty Estimation of Wind Power Forecasts", presentation at EWEC 2008 - 01 April - Brussels, Belgium. (I can't post the link, google will help interested readers).
In 1996 I wrote a paper (published in JCGS) with a figure very similar to that but without the transparency. See http://robjhyndman.com/papers/estimating-and-visualizing-conditional-densities/ for the details. The plotting function is implemented in the R package hdrcde available on CRAN. The package contains some examples in the help files. You should be able to adapt my code to add the transparency.
This is how far I got thanks to Rob's hint. I used persp() to create an empty plot and added polygons and lines to it:
However, it is not as pretty as the original one... :(