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Questions tagged [kriging]

A statistical interpolation method, also known as Gaussian process regression, most used in geo-statistics. The goal is to map a surface given limited sample data. The process evaluates the variability of supplied data, then uses a weighted average of neighbouring points -- considering both distance and direction -- to interpolate the desired map points.

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Interpolation over regular grid in Python

I have been struggling to inteprolate the data for "empty" pixels in my 2D matrix. Basically, I understand (but not deeply) interpolation techniques such as Inverse Distance Weighting, Kriging, Bicubic etc. I dont know the starting point exactly…
Spider
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How to overlap kriging spatial prediction map on a particular area of a country map in R?

I have a hourly PM10 dataset for 81 observation named "seoul032823". You can download from Here. I have performed ordinary kriging on this dataset and also got spatial map for kriging prediction. I also can show the observation data points on…
Orpheus
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How can I interpolate station data with Kriging in Python?

Browsing the web I've found that some tools to use Kriging in Python are pyKriging and Gaussian Process Regression. However, I couldn't make any of them to work. The first one doesn't work for me (can't even import it): import pyKriging File…
lanadaquenada
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Create Grid in R for kriging in gstat

lat long 7.16 124.21 8.6 123.35 8.43 124.28 8.15 125.08 Consider these coordinates, these coordinates correspond to weather stations that measure rainfall data. The intro to the gstat package in R uses the meuse dataset. At some point…
ace_01S
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Python - Kriging (Gaussian Process) in scikit_learn

I am considering using this method to interpolate some 3D points I have. As an input I have atmospheric concentrations of a gas at various elevations over an area. The data I have appears as values every few feet of vertical elevation for several…
Cliff S
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Regression kriging of binomial data

I use gstat to predict a binomial data, but the predicted values go above 1 and below 0. Does anyone know how I can deal with this issue? Thanks. data(meuse) data(meuse.grid) coordinates(meuse) <- ~x+y coordinates(meuse.grid) <-…
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Spatio-temporal kriging in python using sklearn?

I have weather data available for about 6 weather stations. For all these stations I have the longitude and latitude available, and also the datetime (every 10 minutes from beginning of 2016 or so). I want to use the kriging interpolation method to…
Tim
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How to back transform normal score transformed data

I have daily rainfall from 61 gauging stations for 12 years in a catchment(8000 Km2). The goal is create 5Km and 25 Km resolution gridded daily rainfall product. As the no of stations are small and not all stations have rain even in rainy season, i…
user1142937
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options to allow heavily-weighted points on a map to overwhelm other points with low weights

what are some good kriging/interpolation idea/options that will allow heavily-weighted points to bleed over lightly-weighted points on a plotted R map? the state of connecticut has eight counties. i found the centroid and want to plot poverty rates…
Anthony Damico
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How to push the for-loop down to numpy

I have the following piece of code doing exactly what i want (it is part of a kriging method). But the problem is that it goes too slow, and i wish to know if there is any option to push the for-loop down to numpy? If i push out the numpy.sum, and…
usethedeathstar
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heatmap on ggmap error and best practice

I want to plot a heatmap on a ggmap. library(ggmap) turku<-get_map('turku', zoom=13) turkumap<-ggmap(turku, extent="device", legend="topleft") turkumap turkumap+geom_density2d(mapping=aes(x = lon, y = lat),data = test, ) the error i get…
Irene
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Plotting Probability Density Heatmap Over Time in R

Let's say I have the output of a monte-carlo simulation of one variable over several different iterations (think millions). For each iteration, I have the values of the variable at each point in time (ranging from t=1 to t=365). I would like to…
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how to change the lag distance while calculating a Variogram in R

I am trying to calculate an Experimental-Variogram value at different lag distances, so I am using the variogramm command variog1 <- variogram((Copper)~1,ds) but I can't know how to specify the needed lag distance. For example I want to get a…
Ahmed Emam
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How to apply kriging for 3D arrays in Python?

I have a 3D numpy array with some elevation values. I would like to apply kriging interpolation method to them and get a full valued array with same given shape. My purpose is to create a surface actually. The values, I have, are hydrogelogical…
Mustafa Uçar
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Universal kriging using lat long gstat R

I'm new at R and I'm having some trouble to perform a universal kriging with gstat R. As Hengl et al. (2004) say "Universal kriging should be reserved for the case where the drift (or trend) is modelled as a function of the coordinates only". So, I…
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