Geodetector

A software tool to measure and attribute stratified heterogeneity

                      

 

Articles using Geodetector [Numbered]

 

2010

[1 - 2]

2011

[3 - 4]

2012

[5 - 8]

2013

[9 - 14]

2014

[15 - 32]

2015

[33 - 48]

2016

[49 - 84]

2017

[85 - 182]

2018

[183 - 391]

2019

[392 - 755]

2020

[756 - 1304]

2021

[1305 - 2248]

2022

[2249 - 3416]

2023

[3417 - 4818]

2024

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Updated on 29 November 2023

 

 

1. Introduction

2. Tutorial

3. Output

4. Download of the software, with example datasets

5. Citations

6. Bibliography

7. FAQs

8. Developer and Contact

 

1.      Introduction

Spatial Stratified Heterogeneity (SSH) is a phenomena that the within strata are more similar than the between strata. Examples of this include landuse types and climate zones in spatial data, seasons and years in time series, occupations, age groups, incomes strata. SSH occurs in all scales from universe to DNA, and has been studied since Aristotle time.

Geodetector, or Geographical Detector, is a statistical tool to measure SSH and to make attributions for or by SSH (Fig. 1):

(1) Measure and identity SSH among data;

(2) Test the coupling between two variables Y and X without assuming linearity of the association and with clear physical meanings; and

(3) Investigate the general interaction between two explanatory variables X1 and X2 and a response variable Y, without any specific form of interaction such as the assumed product in econometrics (Fig. 2).

Each of the above tasks can be accomplished using the Geodetector q-statistic:

 

Fig. 1. Principle of Geodetector q-statistic (Wang et al 2016)

(The bottom map, the color indicates the values of a population Y. The top map, the population Y is composed of L strata (h = 1, 2, …, L); the terms “stratification” and “partition” are equivalent, can be either classification or zonation. Between the two maps is the equation q(Y|{h}), in which the numerator is the summation of the within strata variance and the denominator is the pooled variance; N and s2 stand for the number of units and the variance of Y in a study area, respectively.

[(N-L)q]/[(L-1)(1-q)] ~ F(L-1, N-L, g), where g is a non central parameter)

.

The strata of Y (blue polygons in Fig.1) are a partition of Y, either by Y itself or by an explanatory variable X. X is a categorical variable or should be stratified if it is a numerical variable (please refer to Section 7. FAQs). The number of strata L might be 2-10 or more, according to prior knowledge or a classification algorithm. The “spatial” in “spatial stratified heterogeneity” can be either spatial in geoscience or in a broad mathermatical sense such as time and any dimensions.

Interpretation of Geodetector q-statistic (Fig.1).

The value of q is strictly within [0, 1].

(1) If Y is stratified by Y itself, then a q-statistic of 0 indicates that Y is absent of spatial stratified heterogeneity; a q-statistic of 1 indicates that Y is perfectly spatially stratified heterogenous; and a q-statistic of 100q% measures the degree of spatial stratified heterogeneity of Y.

(2) If Y is stratified by an explanatory variable X, then a q-statistic of 0 indicates that there is no coupling between Y and X; a q-statistic of 1 indicates that Y is completely determined by X; and X explains 100q% of Y. Please note that the q-statistic measures the association between X and Y without assuming the linearity between X and Y.

Geodetector q-statistic can be used to understand spatial confounding, sample bias and overfitting.

(1)   Confounding can occur if a model is applied to a (spatial) stratified heterogeneneous population, leading to a misleading interpretation and statistical insignificance of the model outcome. This problem can be avoided by identifying SSH (by Geodetector q statistic) then modelling in the strata, separately.

(2)   A sample would be biased if a population is (spatial) stratified heterogeneous and the sample do not cover all strata. The problem can be solved by identifing (spatial) stratified heterogeneity (using Geodetector q statistic) then applying bias remedy models such as Heckman regression and Bshade method.

(3)   Local models aim to overcome heterogeneity but often suffer from overfitting and too many parameters to interpret. These problems can be avoided by modelling in strata or stratifying the outputs of a local model then interpreting the stratified parameters.

Functions of Geodetector:

(1)   The risk detector maps response variable Y in strata according to X;

(2)   The factor detector q-statistic measures the degree of spatial stratified heterogeneity of a variable Y if Y is stratified by itself; and the determinant power of an explanatory variable X on Y if Y is stratified by X;

(3)   The ecological detector identifies the difference in the impacts between two explanatory variables X1 and X2;

(4)   The interaction detector reveals whether the risk factors X1 and X2 (and more X, if applicable) have an interactive influence on a response variable Y (Fig.2).

 

Fig. 2. The General interaction between explanatory variables X1 and X2 impacting on a response variable Y: q(Y|X1X2).

 

back to the top ||

 

2.      Tutorial

The Geodetector software was developed using Excel, R, and QGIS, respectively. The tools are free of charge, freely downloadable, and easy to use, and were designed without any GIS plug-in components and with “one click” execution. Users can run the following demo, then simply replace the demo data in the software using your own data, click Run and get results ! We henceforth describe Excel Geodetector software. R users can download the R Geodetector software in the following section “Download of Geodetector Software and Example Datasets”.

As a demo, neural-tube birth defects (NTD) Y and suspected risk factors or their proxies Xs in villages are provided, including data for the health effect layers “NTD prevalence” and environmental factor layers, “elevation”, “soil type”, and “watershed”. Their field names are defined as Y and