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.
Questions tagged [kriging]
186 questions
26
votes
1 answer
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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12
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3 answers
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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12
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1 answer
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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11
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2 answers
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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10
votes
2 answers
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…
Josh
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8
votes
2 answers
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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8
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1 answer
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) <-…
Geo-sp
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6
votes
1 answer
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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6
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3 answers
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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6
votes
2 answers
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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6
votes
1 answer
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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5
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Advance a Interpolation
Note; No special knowledge of Pykrige is needed to answer the question, as I already mention examples in the question!
Hi I would like to use Universal Kriging in my code. For this I have data that is structured as follows:
Latitude …
Weiss
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5
votes
1 answer
GAM with "gp" smoother: predict at new locations
I am using the following geoadditive model
library(gamair)
library(mgcv)
data(mack)
mack$log.net.area <- log(mack$net.area)
gm2 <- gam(egg.count ~ s(lon,lat,bs="gp",k=100,m=c(2,10,1)) +
s(I(b.depth^.5)) +
…
user3036416
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4
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2 answers
Different outcomes from autokriging and manual kriging
Can someone help me understand why I am getting such different results from auto- and manual kriging? I see the two algorithms are using different variogram models, but is that alone the reason for all the discrepancy? I am also uncomfortable with…
Manojit
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iOS map kriging (interpolation)
Is there any way (or framework) which will allow me to krig my map. I have a few sensors on my map, each with a value (which is dynamic), and based on that value the surrounding area should be painted with some color.
I would like the map to look…
Jovan Angelov
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