Questions tagged [geostatistics]

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

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3answers
856 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, ...
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0answers
15 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 ...
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0answers
6 views

Gradient map based on probability of incident

I have a binary classification model that outputs the probability of an instance belonging to the positive or negative class. I already have the probability threshold by which an instance will be ...
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2answers
35 views

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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0answers
28 views

Smoothing methods for geographically aggregated data?

I have some Canadian census data with various statistics defined by dissemination block. These blocks are irregular in shape since their boundaries are based on the road network. I thought it would be ...
2
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0answers
59 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 ...
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0answers
21 views

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 ...
3
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1answer
61 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 ...
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2answers
124 views

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. ...
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: ...
2
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1answer
176 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 ...
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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 ...
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1answer
30 views

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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2answers
50 views

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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0answers
10 views

why variogram models take only one independent variable

lznr.vgm = variogram(log(zinc)~sqrt(dist), meuse) i am using meuse data for practicing to create variogram models, but i am confused to know there are 14 ...
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0answers
67 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 ...
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1answer
46 views

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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1answer
23 views

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 ...
1
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1answer
41 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 ...
2
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0answers
31 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 ...
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2answers
49 views

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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0answers
27 views

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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1answer
136 views

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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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):...
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0answers
23 views

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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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 ...
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2answers
500 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 ...
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1answer
89 views

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 ...
0
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1answer
136 views

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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1answer
136 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 ...
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1answer
32 views

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 ...
3
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1answer
501 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 ...
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1answer
414 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 ...
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 ...
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0answers
86 views

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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0answers
82 views

Explain Like I'm Five version for Variograms in R's gstat package

Long story short, I asked a question on StackOverflow about Variograms in the gstat package in R. The person who answered gave me some tips on creating the variogram using the package. My dataset is ...
3
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0answers
184 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 ...
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0answers
13 views

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 ...
0
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1answer
179 views

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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0answers
15 views

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 ...
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 ...
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 $...
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0answers
90 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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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 ...
3
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1answer
614 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 ...
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0answers
215 views

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 ...
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 ...
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0answers
126 views

Do I need a special kind of linear regression for aggregated data?

I have two separate databases on individuals. But these individuals are not both present in the two databases. So I decided to aggregate them into area-level data (such as State-level). One of the ...
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 ...
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0answers
56 views

Why likelihood based geostatistical modelling slower than non likelihood based counterpart

Likelihood based geo-statistics (geoR etc.) are usually slower than non-likelihood based geo-statistics (i.e. those based on just least square fitting, for example <...