I'm working on rainfall data. I have grid of rainfall points of 1 square kilometer with time step of 10 minutes. I want interpolate those point at every time step. also I want to check the temporal correlation of my rainfall points. The program I'm using is R. But I'm stuck I cant find my way forward...! Here is a link of my single rainfall data
https://drive.google.com/file/d/0B430nIYqp_1OLXZia2htbGRGWTQ/edit?usp=sharing
The CRAN taskview for spatial temporal analysis suggests packages to use.
http://cran.r-project.org/web/views/SpatioTemporal.html
I see that you have tagged gstat, so the gstat way might be of interest to you.
http://cran.r-project.org/web/packages/gstat/vignettes/st.pdf
Does this help?
Related
I have time series of 4 years. What I need to do, is to display the density of the time series by only visualising the dates for that data exists. The data doesn't matter. The picture shows a sketch. Anybody knows how to this in R? Thanks a lot.
sketch
I'm a new student of R and my current goal is to build the monthly precipitation 3d data (lon,lat,time) of south korea from 2018-2021 from the netcdf files in https://downloads.psl.noaa.gov/Datasets/cpc_global_precip/ (which is daily data).
I was able to extract the data from one cm file following a youtube video but after that I am totally lost. I suspect that I have to use loops to make a dataframe of the data I need.
Can anyone point me in the right direction?
I'm trying to summarize raster cell values in overlapping polygons in ArcMap. This can be done in Geospatial Modelling Environment (GME), an extension for ArcMap. They have a command called isectpolyrst that calculates for values in overlapping polygons. My problem is, my version of ArcGIS (10.6.2), doesn't support the use of GME, so I can't use this function. I've heard that isectpolyrst can still accomplished in R Studio using R script, but I haven't found it anywhere.
I have a number of GPS points with 10 km buffers around them (these buffers overlap a lot). I'm trying to calculate proportions of different vegetation types within these buffer zones. I'm using ArcMap 10.6.2., and zonal statistics can't calculate for overlapping polygons.
You can use raster::extract for that. As you seem entirely new to R, you will need to study it a bit first. You can start here: https://rspatial.org/
I have home range data sets for 6 animals using UTM coordinates. I have successfully read them into R and calculated each home range using the Minimum Convex Polygon(MCP) method. I would like to know if it is possible to do an "incremental area analysis" on these data. What I am looking for is a graph for each home range data set that has the number of data points on the X axis, and the MCP area of the points on the Y axis. The idea is to look for an asymptote. If an asymptote is found, then the area is not increasing with additional data. This would allow me to conclude that the home range of the animal has been fully revealed.
Essentially, I need to know the area gained for each sequential data point. Does adehabitatHR or its brother packages have this capability?
You can find a script for IAA at the Faunalia webpage, I used it and it worked perfectly for MCP:
https://trac.faunalia.it/animove/wiki/AnimoveHowto
I'm trying to use a kriging function to create vertical maps of chemical parameters in an ocean transect, and I'm having a hard time getting started.
My data look like this:
horiz=rep(1:5, 5)
depth=runif(25)
value = horiz+runif(25)/5
df <- data.frame(horiz, depth, value)
The autoKrige function in the automap package looks like it should do the job for me but it takes an object of class SpatialPointsDataFrame. As far as I can tell, the function spTransform in package rgdal creates SpatialPointsDataFrame objects, but there are two problems:
OSX binaries of this aren't available from CRAN, and my copy of RStudio running on OXS 10.7 doesn't seem to be able to install it, and
This function seems to work on lat/long data and correct distance values for the curvature of the Earth. Since I'm dealing with a vertical plane (and short distances, scale of hundreds of meters) I don't want to correct my distances.
There's an excellent discussion of kriging in R here, but due to the issues listed above I don't quite understand how to apply it to my specific problem.
I want a matrix or dataframe describing a grid of points with interpolated values for my chemical parameters, which I can then plot (ideally using ggplot2). I suspect that the solution to my problem is considerably easier than I'm making it out to be.
So there a a few question you want answered:
The spTransform function does not create SPDF's, but transforms between projections. To create a SPDF you can use a simple data.frame as a start. To transform df to a SPDF:
coordinates(df) = c("horiz", "depth")
OS X binaries of rgdal can be found at http://www.kyngchaos.com. But I doubt if you need rgdal.
spTransform can operate on latlong data, but also on projected data. But I do not think you need rgdal, or spTransform, see also point 1.
After you create the SPDF using point 1, you can use the info at the post you mentioned to go on.