Questions tagged [geostatistics]
Statistical modeling and analysis of georeferenced data, often modeling spatial covariance. An example is kriging.
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How to correctly standardize spatial data?
I have measurements of a set of socio-economic variables on italian municipalities; the aim is to run a series of clustering algorithms on them, in order to see if any significant pattern of local ...
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Data transform introducing a bias in kriged geostatistical model?
I am kriging a 3D geospatial model of saturation data. There is water saturation ($SWT$), gas saturation ($SGT$) and oil saturation ($SOT$). A constraint is that the saturations must add up to one. ($...
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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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Can we apply geostatistics on data which is not normally distributed?
If we work on groundwater data, if the data is not normally distributed, can we apply geostatistics on this data without transforming it to normal distribution?
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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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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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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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What is the best procedure to detrend data without loosing its anisotropy?
I wand to detrend some spatial data "A" with respect to two parameter "B&C". What is the best procedure to detrend A without loosing its anisotropy. Theoretically values of "A" should be ...
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What is the difference between accounting for anisotropy and trend removal when performing Kriging?
Without being geostatistician, I read a bit about anisotropy detection, mostly from ArcGIS documentation and the R gstat package tutorial. But still, it is hard to have a confident understanding of ...
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Spatial prediction on surface: very fine grid vs coarse grid + quick interpolation
Once I have fitted a spatial model (point-referenced data), I need to make a prediction map.
A natural approach is to make prediction over a fine grid over the region. However, the required ...
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Condensing spatial time series data and spatial interpolation
I have spatio-temporal albedo (roughly, the 'reflectivity' of earth's surface) dataset, from NASA's MODIS satellite, for a 130 square kilometer area. The dataset contains raster files in the NetCDF ...
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Are two approaches to kriging equivalent?
Is Ordinary Kriging the same as Universal Kriging in which the predicting variable X is constant and equal to 1?
The reason for my question is that in the source code of the gstat package, this seems ...
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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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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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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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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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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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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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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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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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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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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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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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What is 5th order kriging?
For our foray into geostatistics we got data that consists of measurements taken from the soil. The dataset has like concentrations of various different minerals.
We were divided into a number of ...
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type of continuity in geo-statistics
I am reading the book by Wackernagel, H. (1995) Multivariate Geostatistics: An Introduction with Applications and on page 49 The fit is done by eye because it is generally not so relevant how well the ...
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Clustering/pairing users based on multiple lat/lon values?
I have a data set that contains entities and lat/lon values for each one, potentially multiple lat/lon values.
I believe that some of these entities may actually be the same person, although I can't ...
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Predictive model with geospatial data
I have datas of random events with gps and time variables. I would like to compute probabilities of an event happening at a given time and location. In the training set, we have about 1500 possibles ...
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Improve rate estimates of geo. events by other attributes?
I have somewhat rare events (at given times) at geographical locations. I also have a lot of static data about each micro-region. Some of the static data is likely to be correlated with the true event ...
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AIC or similar selection techniques for Variograms?
I have a very basic question: how does one choose the "best" variogram? It is possible to fit different models to an empirical variogram, e.g. nugget, ...
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Details on kriging and variograms
I was wondering what are the steps to perform factoring kriging. I know it is used to extract specific components that may have a physical meaning and this is achieved by kriging. However, I have some ...
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How do you constrain variogram estimates to be a percentage?
I am interpolating soil texture data with GeoR and ARCGIS. The ordinary kriging process is straight forward and GeoR facilitates cross validation. Has anyone else produced variogram parameters, nugget ...
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geographic distance and mahalanobis distance
I am trying to match individuals based on monthly consumption and geographic consumption in a dense metro area. Essentially I want to create treatment and control pairs with the having both geo ...
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How to calculate the significance of change between values in the frame of an equal territory over time?
I do not know much about statistics as you could notice below.
I need to calculate the significance of change in land cover in two periods of time. The problem is I have two equal by surface ...
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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 cluster trips, i.e. directed lines on a plain
I need to cluster transports/trips based on their start point and end point in longitude/latitude.
I have about 5000 trips. Each has a starting point (lon/lat) and an end point (lon/lat). I computed ...
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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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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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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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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 ...
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How to generate distance variable using street addresses [closed]
I have data of sold apartments. There is a street address for every apartment and I would like to generate a new variable that tells the distance from the train station. There are over thousand units ...
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Simple Kriging with linear semivariogram
While studying how to develop a simple kriging model with a linear semivariogram, the various tutorials point towards creating a covariogram using $\sigma(h) = \sigma(0) - \gamma(h)$, but the value of ...
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Imputing missing observations of zip code level data
I am looking for a sufficient imputation method for missing observations in my zip code level data, using R.
I have a random sample consisting of households which live in different zip codes within ...
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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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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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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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