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Questions tagged [spatial-interpolation]

Estimating new data points based on existing spatial observations

Spatial interpolation is a method of estimating new data points based on existing spatial interpolation. This tag focusses on spatial interpolation (data with a geographic component), although interpolation in a general also applies to e.g. timeseries.

Commonly, spatial interpolation involves using of the surrounding observations to estimate a new data point. This can be done using some kind of weighted mean (inverse distance weighted interpolation), by fitting a mathematical function through the existing points (splines), or a combination of both (kriging with external drift).

More information regarding which packages can be used to perform interpolation can be found on the Spatial Task View on CRAN, but in general the gstat, automap, Fields, and geoR packages are a good start for a wide range of spatial interpolation methods.

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Interpolation with tempdisagg package in R

I have a daily frequency data of stock prices with some missing values and I want to interpolate them using the package tempdisagg. Does anyone have an example of interpolation with this package? I am using this code: my_td \<- td(merged_df, High…
Manuel Prado
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Wondering if my code is correct for Simple Kriging

I am a student and we learned about simple kriging with an example of 3 points with known elevations and 1 point with unknown elevation with the assumption that the empirical semivariogram is represented by the linear regression line with Y…
Frank D
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I am trying to do an interpolation with IDW and I get TypeError: cannot convert the series to

idw.idw_interpolation( input_point_shapefile="C:/INFORMATICA APLICADA 22-23/Estaciones.shp", extent_shapefile="C:/INFORMATICA APLICADA 22-23/zonas_urbana_dmq.shp", column_name="SO2", power=2, search_radious=4, …
MJCD2913
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st_interpolate_aw returns error - replacement has x rows, data has y

I am working to re-aggregate population counts from one administrative level to another. One particular row keeps returning the error "replacement has 4 rows, data has 2". I have tried validating the geometries, but it has not worked. Neither did a…
Pablo Herreros Cantis
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2d interpolators of scipy for scattered data going crazy

I want to find the derivatives of some scattered data. I have tried two different methods: projecting the scattered data on a regular grid using scipy.interpolate.griddata, then computing the gradients with numpy.gradients, and then projecting…
Romain
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is there any interpolation method in python which is similar to Empirical Bayesian Kriging?

EBK Regression Prediction is ESRI propriety tool for interpolation. But I am looking for some open source solution with same method Empirical Bayesian Kriging. I have 10 location rainfall data. I want to interpolate the data to fill the gap in…
sachin jain
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How to resample a 2-D spatial matrix (not a time series) using a weighted average to from the 1km grid to the 0.25 degree

I have a bumpy matrix A with shape [num_X, num_Y]. The corresponding lattitude and longitude array is A_lat (of size [num_Y,1]) and A_lon (of size [num_X,1]). And the each element of this matrix for example A[i, j] represents a value of geophysical…
Xu Shan
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Aggregate interpolated data at county level with R

The raw data is at the state level and I would like to go down to the county level. To do this, I first adjusted the data to county level and then interpolated it. The raw data on state level looks like this: object name "df.sf" Simple feature…
AriWhatElse
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Reduce artifacts when resampling a Brain MRI scan using scipy affine_transform

I have a Brain MRI. It is gray scale with 20 slices. I put it into a numpy array with shape (20,256,256). I use scipy.ndimage affine_transform to rotate and resample the array as below. The dark stipes in the image is the artifact that I want…
John Henckel
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Is it possible to do interpolation over 4d data?

I am trying to implement this paper. I have to try to interpolate the latent code of an autoencoder, as mentioned in the paper. The latent code is the encoded input of an autoencoder. The shape of the latent code (for two samples) is (2, 64, 64,…
Ravish Jha
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Filling Missing data in shapefile using spatial interpolation python

This is my first question. I am new to python so please bear with me. I have a shapefile that contains data as given below. ID Data geometry 111 0.1 POINT(X,Y) 112 0.2 POINT(X,Y) 113 0.5 POINT(X,Y) 114 NaN POINT(X,Y) 115 0.3 …
RDK19
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Problem loading mlr package in R due to memory limit

I am trying to reproduce the example of Spatial interpolation / prediction using Ensemble Machine Learning for which I need to use the "mlr" package I have installed it and everything is fine, but when trying to load it I have the following error: >…
dovat_
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IDW(Inverse Distance Weighted) Interpolation in openlayers 6.4.3

I have a django3.1 web application with map using ol6 in which I want to show IDW. I have generated an idw image using python & added to map as an image layer but it does not overlay in accurate point positions. So I am looking for a method or…
Adithya
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What is a non rational function and how to choose its degree?

I am trying to approximate a surface from a set of given points in 3D space in sets like [[X1,Y1,Z1],[X2,Y2,Z2],.....] and I found this very nice library called geomdl this approximates the surface quite well. but I am not able to understand its…
Yash Bhambhu
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Polygon boundary interpolation in R

I have a polygon dataframe: With vertice coordinates: 43740.95 40726.46 43741.36 40720.19 43742.67 40729.28 43743.99 40716.16 43745.52 40730.97 43748.72 40714.19 43748.72 40731.14 43748.72 40714.19 43752.23 …
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