search for: lidar

I have got following error in drawing wavelet fitting. can some one help? > library(faraway) > data(lidar) > newlidar<-lidar[c(1:128),] > library(wavethresh) > wds <- wd(newlidar$logratio) > draw(wds) Error in plot.default(x = x, y = zwr, main = main, sub = sub, xlab = xlab, : formal argument "type" matched by multiple actual arguments [[alternative HTML version deleted]...

Hi All, I am a PhD student in forestry science and I am working with LiDAR data set (huge data set). I am a brand-new in R and geostatistic (SORRY, my background it?s in forestry) but I wish improve my skill for improve myself. I wish to develop a methodology to processing a large data-set of points (typical in LiDAR) but there is a problem with memory. I had created a su...

? stato filtrato un testo allegato il cui set di caratteri non era indicato... Nome: non disponibile URL: <https://stat.ethz.ch/pipermail/r-help/attachments/20080716/338e44b9/attachment.pl>

Dear R-Help members, I am using Simon Wood`s mgcv package version1.7-22and R version 3.0.0 (2013-04-03) for fitting a GAM-Model to the LIDAR Data contained in the "SemiPar" package. Here is the code for fitting the model and for plotting the result: data("lidar") attach(lidar) ### # mgcv fitting ### gam_fit <- gam(logratio ~ s(range, k = 40, bs = "cr"), gamma = 1.4, method = "REML") plot(g...

Hi, I've collected quite a bit of elevation data (LIDAR elevation points) and am looking for a suitable platform to do analysis and modeling on it. The data is sitting in an Oracle database, one table, 200 million rows of x,y, and z. I'm trying to figure out what hardware resources we need to reserve in order to run 64 BIT R for this size data. He...

Could someone give me a hand with the format of the gsummary function? Basically, I have a large set of xyz coordinates generated by LiDAR data (>37 million points) and I am trying to derive various summary statistics on the z-coordinates by a grid cell. I wrote a function to do this by creating factors from the x- and y- coordinates and then using gsummary. However, I want the function to calculate BOTH the max z-value in a grid...

...aid i am not understanding something very fundamental.... and does not matter how much i am looking into the book "Generalized Additive Models" of S. Wood i still don't understand my result. I am trying to model presence / absence (presence = 1, absence = 0) of a species using some lidar metrics (i have 4 of these). I am using different models and such .... and when i used gam i got this very weird (for me) result which i thought it is not possible - or i have no idea how to interpret it. > can3.gam <- gam(can>0~s(be)+s(crr)+s(ch)+s(home), family = 'binomial') &gt...

...viance i get out from different glm and gam models. I came up with this solution, but sincerely i would like to get yours'all opinion on the matter. p1.glm <- glm(count ~be+ch+crr+home, family = 'poisson') # count - is count of species (vegetation) # be, ch, crr, home - different lidar metrics # calculating d^2 d2.p1 <- round((p1.glm[[12]]-p1.glm[[10]])/p1.glm[[12]],4) d2.p1 0.6705 # calculating f statistics with N = 148 and n=4; f = (N-n-1)/(N-1)(1-d^2) f <- (148-4-1)/(147*(1-0.6705)) f [1] 2.952319 #calculating p-value pval.glm <- 1-pf(f, 147,143) pval.glm [1] 1.13...

Dear R users, I am a remote sensing researcher currently studying the use of LiDAR data for quantifying tree height, in particular I would like to determine the sample size needed to capture and quantify canopy height variability. To do this I have employed the use of automap(), which automatically calculates variograms including reporting the range of the variogram. The program...