Questions tagged [geostatistics]

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

88 questions
Filter by
Sorted by
Tagged with
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, ...
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 ...
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 ...
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.
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 ...
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 ...
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 ...
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 ...
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 ...
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), ...
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 ...
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://...
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 ...
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 ...
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 ...
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 ...
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 ...
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: ...
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 ...
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 ...
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 ...
23 views

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

I have an R data frame, set up like so: ...
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 ...
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 ...
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 ...
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 ...
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 ...
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 ...
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 ...
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 ...
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 ...
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 ...
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):...
116 views

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 ...
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 ...
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 ...
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 ...
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 ...
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 ...
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 ...