Questions tagged [geostatistics]

Statistical modeling and analysis of georeferenced data, often modeling spatial covariance. An example is kriging.

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17
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3answers
892 views

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, ...
11
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1answer
1k views

What is the proper way of calculating the kernel density estimate from geographical coordinates?

I have to calculate the 2d kernel density estimate (kde) from a list of latitude and longitude coordinates. But one degree in latitude is not the same distance as one degree in longitude, this means ...
8
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1answer
1k views

Stationarity - assumptions and examination

I am examining rodent captures on six permanent rodent trapping grids measuring 150 x 150 meters and consisting of 121 trap stations evenly spaced 15 meters apart. There are six such trapping grids ...
6
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4answers
1k views

Any easy way to cluster GPS trajectories?

Can anyone recommend an easy way to cluster hundreds of GPS trajectories to find out their common paths? The GPS data is coming from different vehicles that have traveled thousands of miles.
6
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1answer
170 views

How, in practice, are spatial covariances determined?

How, in practice, are spatial covariances determined? If one has a single realisation of some observed field, how can the spatial covariance ever be determined? Unless one has access to the many other ...
6
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2answers
6k views

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 ...
5
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1answer
991 views

What is the difference between (universal) kriging and spatial autoregressive models?

As part of a course on missing observations in social/survey statistics I am trying to explore existing methods of predicting either point pattern or polygon data. I got quite confused by all the ...
5
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1answer
1k views

How to make adjustment for correlation coefficient?

Suppose that there are two two-dimensional maps. For simplification, let's say one map is the temperatures in the 48 continental U. S. states, and the other map is the corresponding humidities. The ...
5
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0answers
318 views

How to impose spatial continuity constraint onto clustering?

Statistics version: I have a few measurements of a function that takes three inputs and produces a few 2D fields of outputs: $f(a,b,c;x,y)$, with $f$ being a vector of several quantities. I would like ...
5
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0answers
1k views

CAR spatial models in JAGS

WinBUGS comes with the GeoBUGS add-on, which contains a number of predefined model structures that are suitable for modelling spatial data structures e.g. geostatical structures (spatial.exp), ...
4
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2answers
133 views

How to analyse several types of geo data together?

I have some data gathered from a survey conducted within my city. All responses include an approximate geo location of where they were gathered (accurate to probably a couple of hundred yards which is ...
4
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1answer
970 views

Is it okay to convert PCA scores to absolute value?

I am calculating PCA using a numpy/python approach. The principal components are in the form of GIS grids (rasters), created in a manner very similar to the GRASS GIS approach described here: http://...
4
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2answers
4k views

The right way to use Machine Learning to predict latitude and longitude

There are some simple ML techniques that can be used to easily predict latitude/longitude co-ordinates, such as predicting the latitude and longitude separately using two different models. However, I ...
4
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1answer
327 views

Is it valid to use a model-variogram fit not on the full range of lag distance?

I am trying to implement a form of 2 stage least squares, in step 1 I ignored the spatial correlation between the observations, now in step 2 I look at the spatial correlation of the residuals of step ...
4
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0answers
178 views

cokriging and generalised linear spatial models

The answer to this question gave me an interesting idea. The part that interested me was a brief description of kriging concluded by The way, kriging as usually practiced is not quite the same as ...
3
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1answer
581 views

Kriging without covariance?

I am trying to krige monthly snowfall totals using data from weather stations and elevation. When I use a linear variogram model (set using a GUI and appears to be a good fit), the resulting layer ...
3
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1answer
62 views

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 ...
3
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2answers
314 views

What effect does data averaging have on the variogram?

What effect does data averaging have on the variogram? To be specific, please see a simple example: ...
3
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1answer
511 views

Stationarity assumption for a point process

as I understand stationarity of a point process implies that it is invariant under translation. Imagine one has numerous realizations of the same point process. Due to the nature of this process, it ...
3
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1answer
619 views

Using von Mises-Fisher distributions for geo-spatial machine learning

There's an interesting paper about predicting the geographical co-ordinates of Twitter users based on the kinds of words that they use in their posts. I'd like to do something similar that involves ...
3
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2answers
1k views

How to test for correlation between two weather station's data

I have about 15 weather stations, separated by quite a bit of kilometers. The data in these stations are the same for all, so is the resolution (daily). I want to try and find which of the stations ...
3
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1answer
23 views

How to use regression of data linked in space and over time?

I have an R data frame, set up like so: ...
3
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0answers
185 views

Interpretation of probability in geostatistics

In geostatistics, the concept of a random field is used in e.g. Kriging. Hence, at each point in your study area, there is a probability distribution. Should this probability be given a frequentistic ...
3
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0answers
95 views

Car out of route

I have one KML file that describes the movement of a car. Data comes from sensor in the car, contains wrong or noisy measurements. I want to filter the wrong measurements, i.e. throw away the ...
2
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1answer
183 views

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 ...
2
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2answers
653 views

Predicting lat/long from binary features

I have a number of observations that occur around my city (a small area), and several of them have latitude and longitude. I have been looking into predicting the latitude/longitude of the ...
2
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2answers
514 views

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 ...
2
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1answer
1k views

ML model selection for prediction of latitude and longitude

I am doing a project in which my aim is to predict the likely locations of a set of latitude/longitude points based on a couple of variables. Since I've never done any ML on locational data, which ...
2
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0answers
61 views

Which methodology/algorithm can be used to complete this 'fill in the blanks' problem?

I have 'n' realization of some phenomenon (historical observations). From the image below, blue cells represent observing a specific event and the white cells represent not observing the event. The ...
2
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0answers
19 views

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 ...
2
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0answers
71 views

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 ...
2
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0answers
33 views

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 ...
2
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0answers
85 views

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):...
2
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0answers
116 views

What is the computational complexity of the empirical variogram?

If we use the method of moments estimator: $2\hat{\gamma}(h) = \frac{1}{| N(h) |} \sum_{N(h)} (Z(s_i) - Z(s_j))^2$ What is the computational complexity? My initial assumption was that it would be $...
2
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0answers
93 views

Is there an approach to combining variograms?

If we compute two seperate variograms for the same type of measurement, but the areas which they cover overlap, is there a logical way (or does it even make sense) to combine the two variograms? ...
2
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0answers
408 views

Combining probabilities for overlapping regions

For two regions which have independent probabilities of an event happening and share an overlapping region, what is the probability of an event happening in the combined region? I'm speaking of ...
2
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0answers
394 views

Help understanding a kriging variation for bare earth extraction

Problem: The authors of a paper (http://www.isprs.org/proceedings/XXXIV/part3/papers/paper106.pdf) develop a bare earth extraction algorithm for LiDAR that is based on kriging. What I don't ...
2
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0answers
214 views

how t values are calculated in Geographically weighted regression?

I can't find the explanation of how local t-values are computed in Geographically weighted regression. Does anybody know what's the equation used how it works? Thank you
2
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0answers
470 views

How should I deal with non-normality in geostatistics?

I am working with two parameters, one is normally distributed the other is not. I have read several different books and articles with different opinions on what to do with non-normal data. Since ...
2
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0answers
90 views

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 ...
2
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0answers
88 views

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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1answer
38 views

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 ...
1
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1answer
42 views

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 ...
1
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1answer
675 views

Support Vector Machine for Longitude-Latitude data

I am wondering if someone could point me to the direction of support vector machines being used for longitude latitude. It seems logical that the possible complexity in SVM would be great for ...
1
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1answer
137 views

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 ...
1
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1answer
435 views

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 ...
1
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1answer
110 views

Gaussian Mixture Model: bandwidth parameter versus variogram fitting?

I'm estimating a stationary, spatially random variable over a 2-dimensional domain. I have ground-truth measurements in several locations, over time. I need some way of spatially-interpolating ...
1
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1answer
471 views

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 ...
1
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1answer
114 views

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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0answers
16 views

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 ...