Questions tagged [geostatistics]
Statistical modeling and analysis of georeferenced data, often modeling spatial covariance. An example is kriging.
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Statistical Integration of Bayesian and Frequentist Approaches: Weighing Methodology
I'm uncertain about where to post this question. I'm currently working with geotechnical data (soil parameters) and aiming to obtain realistic and safer parameter values.
To achieve this goal, I've ...
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Statistical test whether data conforms to a spatial point process--gaza bombing locations
I came across this image on twitter, and it made me think about testing a point process hypothesis. Now this is a politically sensitive image, and I don't want to run afoul of any SE posting ...
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Compare and aggregate indicators at different geographic scale
I encountered a problem in developing an aggregation model of several indicators. Almost all the indicators are at a small geographical scale (admin2 / Provinces), but one is at larger geographical ...
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Larger vs smaller areas for analysis: how to make a choice?
I am researching the composition of labour force, and my variable of interest is the share of workers in a specific occupational category. I measure it by parish and also measure a set of explanatory ...
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How to model user behavior with a time series of discrete locations in continuous time?
I have a dataset that contains the sequential locations a user has visited, with start and end times. A small sample:
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Geostatistics: Covariance vs Semivariance
I am confused by the following page in Geostatistics for
Environmental Scientists, Webster & Oliver:
My understanding
Given locations specified by a vector $\mathbf{x}$, we assume an underlying ...
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Creating a linear interpolation estimation from cluster averages of samples
I don't know the correct terminology to describe my problem, so the title is probably inadequate and I'll have to describe the background information in extra detail.
I have an instrument that takes ...
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Spatial analysis: How to find region most prone to storm loss when only have loss data for whole region?
I'm thinking about a statistical problem and I would be grateful if you could give me some hints of how I could address this problem:
I have data of n insurance companies and for each insurance ...
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Covariance estimation in simple kriging: the "dead end" problem (authorization of using variogram)
I am confused about the presentation of using variogram in simple kriging in the book of Multivariate geostatistics by H. Wackernagel (1995).
I understand the process of derivation of simple kriging ...
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Declustering spatial data and kriging
I am doing a simple project on a mining dataset and came across some problems:
Should I use the declustered values to model the variogram?
Do I apply ordinary kriging to the original or to the ...
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Algorithm for generating a Poisson process on a complicated 2d geometry
I am looking at some count data by geographic counties in California. As a starting point, a Poisson process came to mind--though there are other good choices like negative binomial, etc.
Given a $\...
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How to constrain ordinary kriging weights to sum to 1 in R
I need to perform ordinary kriging on a dataset and I understand that I need the weights to sum to 1, I just don't understand how to set that up properly. For example, my covariance function is C(h) =...
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Showing RMSE and MAE results as percentage error
I have the results of RMSE and MAE from different spatial interpolation methods as a monthly averages (See the figure below). As ...
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Is inference about interior bear population from observation boundary an un"bear"able estimation problem?
The following map shows a density-coloured grid of observations of American black bear reported on iNaturalist. In the top half of the province you can see a loose boundary of observations around an ...
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Estimating probability of attack in Ukraine, given count data
I was looking at some attack count data in Ukraine for different days. The data is gathered from the ACCLED dataset, and there is a picture below. The picture shows individual attacks, but I can apply ...
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Can I simulate a random field with nested variogram by a summation of independently simulated random field for each componnet of the nested variogram?
I want to simulate a random field $Z(u)$ that has a nested variogram, say $\gamma(h)=\gamma_1(h) + \gamma_2(h) + \gamma_3(h)$, assuming the variogram is isotropic. Whether can I simuate independently ...
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Whether the correlation structure of random field $Z(u) + Y(u)$ is equal to the correlation structure of $Z(u)$ plus that of $Y(u)$?
I want to simulate a Gaussian random field (RF) with correlation structure (represented by the geostatistic tool 'semivariogram' $\gamma (h) \: +\: pure \: nugget \: effect$). I want to know whether ...
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Measure "dispersion" of geospatial data
I have a dataframe of lat and longs (of postal codes of Canada), let's say they look something like this.
I'd like to come up with a measure of dispersion - basically how spread out these postal ...
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Which model to use for space-time classification?
in my current dataset I have 30 years of max daily temperature history for the whole USA area (points on a lon/lat grid, each point is 10 km apart). I would like to predict if a max daily temperature ...
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Quantifying magnitude of change in dataset containing base values of 0?
I have a dataset with the low-water and high-water surface area of lakes/ponds within a delta for each year obtained from satellite imagery. These lakes vary substantially in surface area and can ...
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Parametrization of the Matérn Covariance Function
For geostatistics problems, I am used to working with the following parametrization for the Matérn covariance function.
For a stationary and isotropic Gaussian random field $X(\boldsymbol{s})$, $\...
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How could I even try to analyze map data? [closed]
I have a situation where I'm trying to analyze how users interact with maps.
Here's an example to illustrate: Below is an image of Google maps after searching for Chicago, IL pizza.
Now, say that I ...
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calculating b from the Gutenberg-Richter distribution [closed]
I'm trying to calculate b from the Gutenberg-Richter distribution though, I'm struggling in understanding the calculation.
For example, the equation is this:
$Log_{10}N(M) = a-b(M-M_1); M \ge M_1$
$...
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How to calculate the interannual variability and Seasonal Amplitude?
I have a time series of remote sensing observables. For example, the observed brightness from 2007 to 2019. And we have 2 datapoints per day. How can I calculate the interannual variability of this ...
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Cokriging and collocated cokriging data requirements
In this wiki article and elsewhere in educational materials/papers, I have seen people refer to the idea that secondary data, if used (appropriately) in cokriging or collocated cokriging, is usually ...
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Data partitioning for spatial data
I am constructing different configurations of a Random Forest in order to investigate the influence of well-design variables and location, on the first-year production volumes of shale oil wells, ...
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Integrating logistic regression with CA to simulate land cover after prediction
I have used logistic regression in R to predict the probability of change in 3 types of land cover, the map of probability is generated for my case study.
I do not know how to use the probability ...
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Which is the best model for explaining spatial distance between points?
I have a dataset with distances between beneficiaries and the nearest provision point (nearest hub).
I want to develop a model to explain distances based on several atrributes like category of ...
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How to predict the time of next trajectory for users
I am working with the Geolife dataset and would like to create a statistical model to predict when users will go on their next trip. The implication is to see if we can build a model to be able to ...
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Why do we treat a value at each location as a random variable?
Apology if my question is very simple to you (I am very new to geostatistic). Suppose that X is a random variable (e.g., the concentration of the Zinc at a specific ...
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How can I create a map of variance for IDW predictions?
Unlike with kriging, predicting spatial variation using the IDW function from gstat returns only predicted values, not estimates of variation.
...
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How to use regression of data linked in space and over time?
I have an R data frame, set up like so:
...
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Is the spherical covariance function not positive definite for d > 3?
I read in a textbook (Japanese one) that the spherical covariance function is only valid for dimensions $d = 1,$ $2,$ and $3.$ I have the following questions:
Does that mean the spherical covariance ...
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Cokriging variances differ using cross validation
I'm investigating cokriging using various metals in the Meuse dataset but the variances output by R when I predict values at gridded points differ substantially from the variances produced by cross ...
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What are the possible machine learning models for this geospatial analysis task?
I am new to ML and have some experience with building CNN models. I recently got involved with a research project and here is the task I have to work on:
I've been given some (latitudes,longitudes) ...
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Zonal statistics (mean± StDev) from polygons with different area
I am analyzing a temperature image using a land cover map with the overall goal to prepare a barplot where I report the mean ± StDev temperature for each land cover class. To do so I assigned each ...
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Correlating Two Time Series with Gaps in Data and of Different Lengths
I am attempting to correlate the time series from 4 separate tilt monitors that sample every 5 minutes. The time series have slightly different base times and end times, and the resulting arrays are ...
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Controlling for spatial confounding in point-referenced data
I have a point-referenced data set with 2 binary outcomes.
The data shows a strong correlation between these binary attributes - however, the geographic clustering is also qualitatively clear.
I would ...
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Finding the effect of nodes on a density heatmap
Let's say I have a geo-tagged dataset of all payment transactions for businesses in a city. I know whether each payment is made by cash or card, and have made a heatmap of where in the city the ...
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Return Period and Probability
My question is simple: If I assume that the probability to be hit by a lightning strike for a person in this year was 0.5 percent would it mean that if I was able to live 200 years I would be hit by ...
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Using Markov random field spatial weights to account for spatial autocorrelation
I am looking at the relationship between life expectancy and smoking rate within the London boroughs.
I thus created a bayesx spatial regression model including a term which assigns spatial ...
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Can I create a test dataset with known errors to validate accuracy assessment? [closed]
I developed a procedure to measure the geometric accuracy of 3D building models based on the similarity to a 3D point cloud. Therefore I created mainly two quality criteria. The result of my automatic ...
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Statistical analysis of polygons QGIS : find areas of statistical difference
I have polygons for the country divided into E.D. areas.
These polygons illustrate the average annual rainfall in their ED area.
Is there any way to statistically tell if one polygon area has a ...
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How can I understand these variograms?
Using grf function from R package geoR, I simulated 6 replicates (each with 1000 samples) of a Gaussian random field on ...
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Anomaly detection with geo spatial data
I have geo spatial data.
Dataset represents concentration of something. For instance, social media activity of people in point [time, lat, lon]
I have some list of feature for every points (lat, lon):...
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Cerioli's modified test of indepence with spatial data
I have to two datasets $X$ and $Y$ with binary observations on a regular grid. A regular contingency test for independence would be flawed by the presence of spatial autocorrelation. Cerioli (1997) ...
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What is the nugget effect?
I don't understand exactly what is meant by the term "nugget effect" in geostatistics. When looking at empirical variograms plotting the variogram $\gamma(h)$ vs. the lag $h$, the nugget is defined as ...
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Temporal Variogram
Can we compute temporal variograms just like spatial variograms? I know about spatio-temporal variograms but I am more interested in doing a comparison of separate spatial and temporal variograms and ...
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How much data do I need in spatial hotspot analysis?
I'm now doing a project about spatial hotspot analysis. I read many literatures, however, I can't find any papers tell how they determine the data size they used.
I mean, suppose we have crime ...
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How do you interpret this variogram?
Description:
8000 spatial data points spanned over an entire state
200 bins are used
My question: Is the variogram telling something about the nature of the data? Why is it fluctuating? Should I do ...
