115 lines
4.5 KiB
Markdown
115 lines
4.5 KiB
Markdown
# @turf/quadrat-analysis
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<!-- Generated by documentation.js. Update this documentation by updating the source code. -->
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## quadratAnalysis
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Quadrat analysis lays a set of equal-size areas(quadrat) over the study area and counts
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the number of features in each quadrat and creates a frequency table.
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The table lists the number of quadrats containing no features,
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the number containing one feature, two features, and so on,
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all the way up to the quadrat containing the most features.
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The method then creates the frequency table for the random distribution, usually based on a Poisson distribution.
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The method uses the distribution to calculate the probability for 0 feature occuring,
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1 feature occuring, 2 features, and so on,
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and lists these probabilities in the frequency table.
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By comparing the two frequency tables, you can see whether the features create a pattern.
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If the table for the observed distribution has more quadrats containing many features than the
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table for the random distribution dose, then the features create a clustered pattern.
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It is hard to judge the frequency tables are similar or different just by looking at them.
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So, we can use serval statistical tests to find out how much the frequency tables differ.
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We use Kolmogorov-Smirnov test.This method calculates cumulative probabilities for both distributions,
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and then compares the cumulative probabilities at each class level and selects the largest absolute difference D.
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Then, the test compares D to the critical value for a confidence level you specify.
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If D is greater than the critical value, the difference between the observed distribution and
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the random distribution is significant. The greater the value the bigger the difference.
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Traditionally, squares are used for the shape of the quadrats, in a regular grid(square-grid).
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Some researchers suggest that the quadrat size equal twice the size of mean area per feature,
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which is simply the area of the study area divided by the number of features.
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### Parameters
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* `pointFeatureSet` **[FeatureCollection][1]<[Point][2]>** point set to study
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* `options` **[Object][3]** optional parameters (optional, default `{}`)
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* `options.studyBbox` **\[[number][4], [number][4], [number][4], [number][4]]?** bbox representing the study area
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* `options.confidenceLevel` **(`20` | `15` | `10` | `5` | `2` | `1`)** a confidence level.
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The unit is percentage . 5 means 95%, value must be in [K\_TABLE][5] (optional, default `20`)
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### Examples
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```javascript
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var bbox = [-65, 40, -63, 42];
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var dataset = turf.randomPoint(100, { bbox: bbox });
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var result = turf.quadratAnalysis(dataset);
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```
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Returns **[QuadratAnalysisResult][6]** result
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## K\_TABLE
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the confidence level
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Type: [Object][3]
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### Properties
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* `20` **[number][4]** 1.07275
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* `15` **[number][4]** 1.13795
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* `10` **[number][4]** 1.22385
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* `5` **[number][4]** 1.3581
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* `2` **[number][4]** 1.51743
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* `1` **[number][4]** 1.62762
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## QuadratAnalysisResult
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the return type of the quadratAnalysis
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Type: [object][3]
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### Properties
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* `criticalValue` **[number][4]** 
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* `maxAbsoluteDifference` **[number][4]** 
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* `isRandom` **[boolean][7]** 
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* `observedDistribution` **[Array][8]<[number][4]>** the cumulative distribution of observed features,
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the index represents the number of features in the quadrat.
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[1]: https://tools.ietf.org/html/rfc7946#section-3.3
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[2]: https://tools.ietf.org/html/rfc7946#section-3.1.2
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[3]: https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Object
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[4]: https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Number
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[5]: #k_table
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[6]: #quadratanalysisresult
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[7]: https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Boolean
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[8]: https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Array
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<!-- This file is automatically generated. Please don't edit it directly. If you find an error, edit the source file of the module in question (likely index.js or index.ts), and re-run "yarn docs" from the root of the turf project. -->
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---
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This module is part of the [Turfjs project](https://turfjs.org/), an open source module collection dedicated to geographic algorithms. It is maintained in the [Turfjs/turf](https://github.com/Turfjs/turf) repository, where you can create PRs and issues.
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### Installation
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Install this single module individually:
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```sh
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$ npm install @turf/quadrat-analysis
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```
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Or install the all-encompassing @turf/turf module that includes all modules as functions:
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```sh
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$ npm install @turf/turf
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```
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