Re: [R-sig-Geo] MODIS package released to CRAN

Great stuff to finally see it make it! Well done to all involved! On Fri, Jan 13, 2017 at 8:24 AM Matteo Mattiuzzi wrote: > Dear list, > > > We would like to announce the release of the MODIS package to CRAN. This > was finally possible thanks to the constant efforts of

Re: [R-sig-Geo] Landscape connectivity in R

Check out sdmtools if fragstats like patch/class metrics are what you're looking for: https://cran.r-project.org/web/packages/SDMTools/index.html Sincerely, Forrest On Tue, Dec 13, 2016 at 1:29 PM Manuel Spínola wrote: > Dear list members, > > Is there any R package,

Re: [R-sig-Geo] Simple features now on CRAN

. Congratulations, Forrest Stevens On Fri, Nov 4, 2016 at 11:04 AM Edzer Pebesma <edzer.pebe...@uni-muenster.de> wrote: > Package sf (for "simple features") is now on CRAN: > > https://cran.r-project.org/package=sf > > The package vignette is found here: > >

Re: [R-sig-Geo] How to reduce the buffering time with the function "buffer" (package raster)

system.time(dist_rf <- distance(rf)) > > > I stopped the code with the functions "buffer" and "distance" after two > hours. > > > Thanks a lot for your time. > > Have a nice day. > > Nell > > > > >

Re: [R-sig-Geo] How to reduce the buffering time with the function "buffer" (package raster)

For the moment, I haven't find solutions. > > > Thanks a lot for your time. > > Have a nice day. > > Nell > > > > > -- > *De :* Forrest Stevens <r-sig-...@forreststevens.com> > *Envoyé :* lundi 11 avril 2016 09:09 > *À :* Nelly Redua

Re: [R-sig-Geo] How to reduce the buffering time with the function "buffer" (package raster)

Five million cells isn't all that many, how slow is too slow? Buffering a raster of about 10 million cells on my laptop takes on the order of 20 seconds or so for a binary raster. Is it possible that you're fighting memory problems? In the past when doing multiple ring buffers I've found it

Re: [R-sig-Geo] extract mean raster value from polygon

y have routines that do the same thing faster for large > raster data. In raster, ``aggregate'' has a very different meaning. > > > On 11/03/16 11:07, Alexander Shenkin wrote: > > Hello All, > > > > I've been working to be able to make elevation profiles from a DEM along >

Re: [R-sig-Geo] Elevation profiles

Hey Allie, long time, hope things are going well! Coincidentally I was working on something for a student of mine to do this so I'll throw my two bits in. Starting from two points which specify a line perpendicular to your swath and separated by the distance of your swath width, you can create a

Re: [R-sig-Geo] random number generation

Hi Leila, to generate spatially autocorrelated data, which I think is what you're trying to get at, I use the gstat package. You need to decide on the geostatistical model that describes the nature of your correlation structure, and then simulating a field is pretty easy: library(gstat) ##

Re: [R-sig-Geo] Exporting Multipolygon geojson with rgdal::writeOGR

This is fantastic work, thank you both for troubleshooting it and the fix Roger. Your tireless work is greatly appreciated! I just ran across this problem a couple of weeks ago when exporting from R to GeoJSON, and will happily test out the new version. Sincerely, Forrest On Mon, Nov 2, 2015 at

Re: [R-sig-Geo] Package MODIS error in function runMrt( ) object 'ftpdirs' not found

Thanks for catching that! I've responded directly with a package file attached, but the incomplete fix should be corrected in the next R-Forge release. Sincerely, Forrest On Thu, Jul 16, 2015 at 4:09 PM Roberto Horn robertomh...@gmail.com wrote: Hello, No, it is different:

Re: [R-sig-Geo] Package MODIS error in function runMrt( ) object 'ftpdirs' not found

Does it fail in exactly the same way? And no, in practice you shouldn't see any large differences in reprojected/mosaicked output. The only difference is less hassle with getting a working MRT in place. :) Sincerely, Forrest On Thu, Jul 16, 2015 at 3:52 PM Roberto Horn robertomh...@gmail.com

Re: [R-sig-Geo] Package MODIS error in function runMrt( ) object 'ftpdirs' not found

Hi guys, thank you for bringing this to our attention. I believe I've fixed the bug in the R-Forge version of the MODIS package. If either of you could install this from R-Forge and test it in your environments that would be ideal. Notice that these changes won't be reflected in the automated

Re: [R-sig-Geo] MODIS Whittaker Smoothing multicore support

! Amit Forrest Stevens forr...@ufl.edu schrieb am 15:26 Dienstag, 31.März 2015: Hi Amit, I can provide you with some help to get smoothing working to leverage multiple cores. This is already baked into the whittaker.raster() function of our MODIS package and it makes sense to use

Re: [R-sig-Geo] How to count unique TRUE's

I'm guessing based on the data and situation you describe that some variant of this would probably get you close: ## Sample data: d - data.frame(A=c(T,F,F,T), B=c(F,T,F,T)) ## Count row-wise trues: sum( apply(d, MARGIN=1, sum) = 1 ) Hope that helps, Forrest -- Forrest R. Stevens Ph.D.

Re: [R-sig-Geo] MODIS Whittaker Smoothing multicore support

Hi Amit, I can provide you with some help to get smoothing working to leverage multiple cores. This is already baked into the whittaker.raster() function of our MODIS package and it makes sense to use it since the problem is of the embarrassingly parallel variety. To leverage multiple cores you

Re: [R-sig-Geo] Map of pixel area?

The easiest way I can think of would be to create an index raster based on your raster of interest, convert it to polygons, project it to an equal area projection with linear units amenable to you, then extract the polygon areas and assign them back to your index raster for weighting. Perhaps

Re: [R-sig-Geo] Map of pixel area?

Institute University of Florida www.clas.ufl.edu/users/forrest On Fri, Jan 9, 2015 at 6:11 PM, Forrest Stevens forr...@ufl.edu wrote: The easiest way I can think of would be to create an index raster based on your raster of interest, convert it to polygons, project it to an equal area projection

Re: [R-sig-Geo] Mann-kendall

Not to dissuade any interesting new algorithm development, and I may be missing something in the motivation for what you're trying to accomplish, but have you looked at the Kendall package and tried using it on your raster object? I've been pleasantly surprised at its efficiency for at least

Re: [R-sig-Geo] Mann-kendall

comments. So I will improve the documentation for Kendall by terminating the program with an error message when n=3 (this case is of no interest to me) and warning message when n12 that the p-values may be inaccurate. Thank you for everything! Nuno On 9 October 2014 00:26, Forrest Stevens

Re: [R-sig-Geo] zonal statistics as table

Hi Joseph.. With datasets that large, in my experience you're looking at spatial subsetting to get something manageable and I've given up on zonal() as it's just too slow for my needs. Rather, I would do your own feature to raster conversion on the polygons based on the raster layer so cells

Re: [R-sig-Geo] a KMZ question, please

I've had no problems just using 7Zip to package the kml and images together. I'm surprised WinZip doesn't work? Forrest -- Forrest R. Stevens Ph.D. Candidate, QSE3 IGERT Fellow Department of Geography Land Use and Environmental Change Institute University of Florida

Re: [R-sig-Geo] How to buffer a polygon by area

I've been following this with some interest as it's an interesting problem. I really like Thierry's solution and I think that he's right in that it should converge across most cases I can think of. I was concerned it would have problems with complex, multi-part polygons or polygons with holes,

Re: [R-sig-Geo] spatial analyses from picture

Hi Julien, you've posed a really interesting problem, and the bulk of which I'd argue might not be best solved using R but I'll be very interested to hear other people's opinions on it. A large portion of your project is going to rely on good image processing, so the raster and jpeg packages will

Re: [R-sig-Geo] Iteratively subsample a rater and reassemble

I've used a similar technique with subs() in the past, but you'll still be relying on the rather slow raster zonal() function to do population totals and SD calculations for each country. As an alternative I've created much more workable solutions by converting large rasters to data.table objects

Re: [R-sig-Geo] loops in rasterEngine

Hi Yan, I guess I would be surprised for such a simple process if rasterEngine() would be worth the overhead? Though, admittedly, Jonathan Greenberg might have more information on the topic. To do such an operation this is the approach I would take without using rasterEngine(): for (i in 1:5) {

Re: [R-sig-Geo] Taking elevation into account when calculating distance

Are these in projected coordinates with the same units? (They probably should be if they aren't..) But if so then you can just use the Pythagorean theorem, assuming two points, distance in 3D space is: dist3d - sqrt((x1-x2)^2 + (y1-y2)^2 + (z1-z2)^2) Example: x1=0 y1=0 z1=0 x2=1 y2=2

Re: [R-sig-Geo] spatial networks

Hi Edzer, this is definitely very cool. This may make some recent work I've been doing on spatial and social network analyses of academic co-authorship easier (early code is here if you're interested: http://refnet.r-forge.r-project.org/ ). Thanks for providing this to the community!

Re: [R-sig-Geo] Prediction variance (map) for predictions derived using RandomForest package

Hi Tom, I've done something similar in the past to visualize the distribution of the predictions attained for each observation across the many trees within a random forest while looking at various aspects of those ranges and correlating that with cross-validated prediction errors. It's relatively

Re: [R-sig-Geo] Prediction variance (map) for predictions derived using RandomForest package

You can do this to get the mean and SD for each observation (note the mean should match the value in predictions$aggregate: y_data$rf_mean - apply(predictions$individual, MARGIN=1, mean) y_data$rf_sd - apply(predictions$individual, MARGIN=1, sd) y_data$rf_cv - apply(predictions$individual,

Re: [R-sig-Geo] for loop with kde (ks package) function not working

I am trying to run a for loop 1000 times to randomly sample spatial points ... different values). However, when I look at the results from the kde function the first two outputs are different and then each iteration after that just produces the exact same values. Hi Kathryn, I believe the

Re: [R-sig-Geo] foreach progress bar?

*100, 0),% done)) } close(pb) Forrest Stevens -- Ph.D. Candidate, QSE3 IGERT Fellow Department of Geography Land Use and Environmental Change Institute University of Florida www.clas.ufl.edu/users/forrest ___ R-sig-Geo mailing list R-sig-Geo@r

Re: [R-sig-Geo] Alternative to zonal for large images

that analysis chain, with a bottleneck that can hopefully be bypassed at some point soon (I haven't had time to dig into the source but maybe one day!) Sincerely, Forrest Stevens -- Ph.D. Candidate, QSE3 IGERT Fellow Department of Geography Land Use and Environmental Change Institute University of Florida

Re: [R-sig-Geo] Error in Modis mosaic tool

Hi Kat, a little more information would help. Which package are you using, what are the symptoms you're experiencing (including a self-contained code snippet would be great) and which original post are you referring to? I'm a contributor to the MODIS package (

Re: [R-sig-Geo] Extracting weird temperature and EVI values from MODIS data

what the raw, digital numbers are. But 10,000 is a pretty standard scaling factor for shifting floating point numbers to integers, and is used for a wide variety of remotely sensed data in order to decrease the file size requirement for storing certain data. Good luck, Forrest Stevens -- Ph.D

Re: [R-sig-Geo] Merging/averaging rasters with different extents

? Sincerely, Forrest Stevens Ph.D. Candidate Department of Geography Land Use and Environmental Change Institute University of Florida http://www.clas.ufl.edu/users/forrest On Wed, Jan 4, 2012 at 2:23 PM, Tara Bridwell tarabridw...@gmail.comwrote: My overall analytical goal is to take the mean (and later

Re: [R-sig-Geo] ASCII grid file - extracting data after import with readGDAL()

ASCII grid, on which you can pull subsets or index like you would a normal vector (e.g. pretend your map object has band1 as its only data, you can pull a subset of the first 10 grid values like this: map$band1[1:10] I hope that gets you closer to solving the rest of your question, Forrest Stevens