[feature][processing] A brand new spatiotemporal ST-DBSCAN clustering algorithm

2025-10-06 00:07:29 -04:00 · 2021-07-03 15:29:31 +07:00 · 2021-07-03 15:29:31 +07:00 · f68ef8fb60
commit f68ef8fb60
parent 402cf1129e
9 changed files with 390 additions and 20 deletions
--- a/python/plugins/processing/tests/testdata/expected/stdbscan_multiple_clusters.gml
+++ b/python/plugins/processing/tests/testdata/expected/stdbscan_multiple_clusters.gml
@ -0,0 +1,104 @@
+<?xml version="1.0" encoding="utf-8" ?>
+<ogr:FeatureCollection
+     xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
+     xsi:schemaLocation="http://ogr.maptools.org/ stdbscan_multiple_clusters.xsd"
+     xmlns:ogr="http://ogr.maptools.org/"
+     xmlns:gml="http://www.opengis.net/gml">
+  <gml:boundedBy>
+    <gml:Box>
+      <gml:coord><gml:X>0</gml:X><gml:Y>-5</gml:Y></gml:coord>
+      <gml:coord><gml:X>8</gml:X><gml:Y>3</gml:Y></gml:coord>
+    </gml:Box>
+  </gml:boundedBy>
+                                                                                                                                                               
+  <gml:featureMember>
+    <ogr:stdbscan_multiple_clusters fid="points.8">
+      <ogr:geometryProperty><gml:Point srsName="EPSG:4326"><gml:coordinates>0,-1</gml:coordinates></gml:Point></ogr:geometryProperty>
+      <ogr:id>9</ogr:id>
+      <ogr:id2>0</ogr:id2>
+      <ogr:date>2017/08/13</ogr:date>
+      <ogr:CLUSTER_ID>1</ogr:CLUSTER_ID>
+      <ogr:CLUSTER_SIZE>2</ogr:CLUSTER_SIZE>
+    </ogr:stdbscan_multiple_clusters>
+  </gml:featureMember>
+  <gml:featureMember>
+    <ogr:stdbscan_multiple_clusters fid="points.1">
+      <ogr:geometryProperty><gml:Point srsName="EPSG:4326"><gml:coordinates>3,3</gml:coordinates></gml:Point></ogr:geometryProperty>
+      <ogr:id>2</ogr:id>
+      <ogr:id2>1</ogr:id2>
+      <ogr:date>2017/09/13</ogr:date>
+      <ogr:CLUSTER_ID>1</ogr:CLUSTER_ID>
+      <ogr:CLUSTER_SIZE>2</ogr:CLUSTER_SIZE>
+    </ogr:stdbscan_multiple_clusters>
+  </gml:featureMember>
+  <gml:featureMember>
+    <ogr:stdbscan_multiple_clusters fid="points.0">
+      <ogr:geometryProperty><gml:Point srsName="EPSG:4326"><gml:coordinates>1,1</gml:coordinates></gml:Point></ogr:geometryProperty>
+      <ogr:id>1</ogr:id>
+      <ogr:id2>2</ogr:id2>
+      <ogr:date xsi:nil="true"/>
+      <ogr:CLUSTER_ID xsi:nil="true"/>
+      <ogr:CLUSTER_SIZE xsi:nil="true"/>
+    </ogr:stdbscan_multiple_clusters>
+  </gml:featureMember>
+  <gml:featureMember>
+    <ogr:stdbscan_multiple_clusters fid="points.3">
+      <ogr:geometryProperty><gml:Point srsName="EPSG:4326"><gml:coordinates>5,2</gml:coordinates></gml:Point></ogr:geometryProperty>
+      <ogr:id>4</ogr:id>
+      <ogr:id2>2</ogr:id2>
+      <ogr:date>2001/01/01</ogr:date>
+      <ogr:CLUSTER_ID>2</ogr:CLUSTER_ID>
+      <ogr:CLUSTER_SIZE>1</ogr:CLUSTER_SIZE>
+    </ogr:stdbscan_multiple_clusters>
+  </gml:featureMember>
+  <gml:featureMember>
+    <ogr:stdbscan_multiple_clusters fid="points.2">
+      <ogr:geometryProperty><gml:Point srsName="EPSG:4326"><gml:coordinates>2,2</gml:coordinates></gml:Point></ogr:geometryProperty>
+      <ogr:id>3</ogr:id>
+      <ogr:id2>0</ogr:id2>
+      <ogr:date>2005/09/13</ogr:date>
+      <ogr:CLUSTER_ID>3</ogr:CLUSTER_ID>
+      <ogr:CLUSTER_SIZE>1</ogr:CLUSTER_SIZE>
+    </ogr:stdbscan_multiple_clusters>
+  </gml:featureMember>
+  <gml:featureMember>
+    <ogr:stdbscan_multiple_clusters fid="points.5">
+      <ogr:geometryProperty><gml:Point srsName="EPSG:4326"><gml:coordinates>0,-5</gml:coordinates></gml:Point></ogr:geometryProperty>
+      <ogr:id>6</ogr:id>
+      <ogr:id2>0</ogr:id2>
+      <ogr:date xsi:nil="true"/>
+      <ogr:CLUSTER_ID xsi:nil="true"/>
+      <ogr:CLUSTER_SIZE xsi:nil="true"/>
+    </ogr:stdbscan_multiple_clusters>
+  </gml:featureMember>
+  <gml:featureMember>
+    <ogr:stdbscan_multiple_clusters fid="points.4">
+      <ogr:geometryProperty><gml:Point srsName="EPSG:4326"><gml:coordinates>4,1</gml:coordinates></gml:Point></ogr:geometryProperty>
+      <ogr:id>5</ogr:id>
+      <ogr:id2>1</ogr:id2>
+      <ogr:date>2014/03/13</ogr:date>
+      <ogr:CLUSTER_ID>4</ogr:CLUSTER_ID>
+      <ogr:CLUSTER_SIZE>3</ogr:CLUSTER_SIZE>
+    </ogr:stdbscan_multiple_clusters>
+  </gml:featureMember>
+  <gml:featureMember>
+    <ogr:stdbscan_multiple_clusters fid="points.7">
+      <ogr:geometryProperty><gml:Point srsName="EPSG:4326"><gml:coordinates>7,-1</gml:coordinates></gml:Point></ogr:geometryProperty>
+      <ogr:id>8</ogr:id>
+      <ogr:id2>0</ogr:id2>
+      <ogr:date>2011/09/13</ogr:date>
+      <ogr:CLUSTER_ID>4</ogr:CLUSTER_ID>
+      <ogr:CLUSTER_SIZE>3</ogr:CLUSTER_SIZE>
+    </ogr:stdbscan_multiple_clusters>
+  </gml:featureMember>
+  <gml:featureMember>
+    <ogr:stdbscan_multiple_clusters fid="points.6">
+      <ogr:geometryProperty><gml:Point srsName="EPSG:4326"><gml:coordinates>8,-1</gml:coordinates></gml:Point></ogr:geometryProperty>
+      <ogr:id>7</ogr:id>
+      <ogr:id2>0</ogr:id2>
+      <ogr:date>2010/10/10</ogr:date>
+      <ogr:CLUSTER_ID>4</ogr:CLUSTER_ID>
+      <ogr:CLUSTER_SIZE>3</ogr:CLUSTER_SIZE>
+    </ogr:stdbscan_multiple_clusters>
+  </gml:featureMember>
+</ogr:FeatureCollection>
--- a/python/plugins/processing/tests/testdata/expected/stdbscan_multiple_clusters.xsd
+++ b/python/plugins/processing/tests/testdata/expected/stdbscan_multiple_clusters.xsd
@ -0,0 +1,53 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<xs:schema targetNamespace="http://ogr.maptools.org/" xmlns:ogr="http://ogr.maptools.org/" xmlns:xs="http://www.w3.org/2001/XMLSchema" xmlns:gml="http://www.opengis.net/gml" elementFormDefault="qualified" version="1.0">
+<xs:import namespace="http://www.opengis.net/gml" schemaLocation="http://schemas.opengis.net/gml/2.1.2/feature.xsd"/>
+<xs:element name="FeatureCollection" type="ogr:FeatureCollectionType" substitutionGroup="gml:_FeatureCollection"/>
+<xs:complexType name="FeatureCollectionType">
+  <xs:complexContent>
+    <xs:extension base="gml:AbstractFeatureCollectionType">
+      <xs:attribute name="lockId" type="xs:string" use="optional"/>
+      <xs:attribute name="scope" type="xs:string" use="optional"/>
+    </xs:extension>
+  </xs:complexContent>
+</xs:complexType>
+<xs:element name="stdbscan_multiple_clusters" type="ogr:stdbscan_multiple_clusters_Type" substitutionGroup="gml:_Feature"/>
+<xs:complexType name="stdbscan_multiple_clusters_Type">
+  <xs:complexContent>
+    <xs:extension base="gml:AbstractFeatureType">
+      <xs:sequence>
+        <xs:element name="geometryProperty" type="gml:PointPropertyType" nillable="true" minOccurs="0" maxOccurs="1"/>
+        <xs:element name="id" nillable="true" minOccurs="0" maxOccurs="1">
+          <xs:simpleType>
+            <xs:restriction base="xs:long">
+              <xs:totalDigits value="10"/>
+            </xs:restriction>
+          </xs:simpleType>
+        </xs:element>
+        <xs:element name="id2" nillable="true" minOccurs="0" maxOccurs="1">
+          <xs:simpleType>
+            <xs:restriction base="xs:long">
+              <xs:totalDigits value="10"/>
+            </xs:restriction>
+          </xs:simpleType>
+        </xs:element>
+        <xs:element name="date" nillable="true" minOccurs="0" maxOccurs="1" type="xs:date">
+        </xs:element>
+        <xs:element name="CLUSTER_ID" nillable="true" minOccurs="0" maxOccurs="1">
+          <xs:simpleType>
+            <xs:restriction base="xs:integer">
+              <xs:totalDigits value="10"/>
+            </xs:restriction>
+          </xs:simpleType>
+        </xs:element>
+        <xs:element name="CLUSTER_SIZE" nillable="true" minOccurs="0" maxOccurs="1">
+          <xs:simpleType>
+            <xs:restriction base="xs:integer">
+              <xs:totalDigits value="10"/>
+            </xs:restriction>
+          </xs:simpleType>
+        </xs:element>
+      </xs:sequence>
+    </xs:extension>
+  </xs:complexContent>
+</xs:complexType>
+</xs:schema>
--- a/python/plugins/processing/tests/testdata/qgis_algorithm_tests4.yaml
+++ b/python/plugins/processing/tests/testdata/qgis_algorithm_tests4.yaml
@ -878,6 +878,23 @@ tests:
        name: expected/dbscan_multiple_clusters.gml
        type: vector

+  - algorithm: native:stdbscanclustering
+    name: ST-DBScan multiple clusters
+    params:
+      DATETIME_FIELD: date
+      DBSCAN*: false
+      EPS: 5.0
+      EPS2: 1000.0
+      FIELD_NAME: CLUSTER_ID
+      INPUT:
+        name: custom/points_with_date.shp
+        type: vector
+      MIN_SIZE: 1
+    results:
+      OUTPUT:
+        name: expected/stdbscan_multiple_clusters.gml
+        type: vector
+
  - algorithm: qgis:rastersampling
    name: Single band raster
    params:
--- a/src/analysis/CMakeLists.txt
+++ b/src/analysis/CMakeLists.txt
@ -198,6 +198,7 @@ set(QGIS_ANALYSIS_SRCS
  processing/qgsalgorithmsplitlinesbylength.cpp
  processing/qgsalgorithmsplitvectorlayer.cpp
  processing/qgsalgorithmsplitwithlines.cpp
+  processing/qgsalgorithmstdbscanclustering.cpp
  processing/qgsalgorithmstringconcatenation.cpp
  processing/qgsalgorithmswapxy.cpp
  processing/qgsalgorithmsubdivide.cpp
--- a/src/analysis/processing/qgsalgorithmdbscanclustering.cpp
+++ b/src/analysis/processing/qgsalgorithmdbscanclustering.cpp
@ -38,7 +38,7 @@ QString QgsDbscanClusteringAlgorithm::shortDescription() const

 QStringList QgsDbscanClusteringAlgorithm::tags() const
 {
-  return QObject::tr( "clustering,clusters,density,based,points" ).split( ',' );
+  return QObject::tr( "clustering,clusters,density,based,points,distance" ).split( ',' );
 }

 QString QgsDbscanClusteringAlgorithm::group() const
@ -113,7 +113,8 @@ QVariantMap QgsDbscanClusteringAlgorithm::processAlgorithm( const QVariantMap &p
    throw QgsProcessingException( invalidSourceError( parameters, QStringLiteral( "INPUT" ) ) );

  const std::size_t minSize = static_cast< std::size_t>( parameterAsInt( parameters, QStringLiteral( "MIN_SIZE" ), context ) );
-  const double eps = parameterAsDouble( parameters, QStringLiteral( "EPS" ), context );
+  const double eps1 = parameterAsDouble( parameters, QStringLiteral( "EPS" ), context );
+  const double eps2 = parameterAsDouble( parameters, QStringLiteral( "EPS2" ), context ) * 24 * 60 * 60;
  const bool borderPointsAreNoise = parameterAsBoolean( parameters, QStringLiteral( "DBSCAN*" ), context );

  QgsFields outputFields = source->fields();
@ -135,13 +136,31 @@ QVariantMap QgsDbscanClusteringAlgorithm::processAlgorithm( const QVariantMap &p
  if ( feedback->isCanceled() )
    return QVariantMap();

-  // dbscan!
+  std::unordered_map< QgsFeatureId, QDateTime> idToDateTime;
+  const QString dateTimeFieldName = parameterAsString( parameters, QStringLiteral( "DATETIME_FIELD" ), context );
+  if ( !dateTimeFieldName.isEmpty() )
+  {
+    const int dateTimefieldIndex = source->fields().lookupField( dateTimeFieldName );
+    if ( dateTimefieldIndex == -1 )
+      throw QgsProcessingException( QObject::tr( "Datetime field missing" ) );
+
+    // fetch temporal values
+    feedback->pushInfo( QObject::tr( "Fetching temporal values" ) );
+    QgsFeatureIterator features = source->getFeatures( QgsFeatureRequest().setSubsetOfAttributes( QgsAttributeList() << dateTimefieldIndex ), QgsProcessingFeatureSource::FlagSkipGeometryValidityChecks );
+    QgsFeature feature;
+    while ( features.nextFeature( feature ) )
+    {
+      idToDateTime[ feature.id() ] = feature.attributes().at( dateTimefieldIndex ).toDateTime();
+    }
+  }
+
+  // stdbscan!
  feedback->pushInfo( QObject::tr( "Analysing clusters" ) );
  std::unordered_map< QgsFeatureId, int> idToCluster;
  idToCluster.reserve( index.size() );
-  QgsFeatureIterator features = source->getFeatures( QgsFeatureRequest().setNoAttributes() );
  const long featureCount = source->featureCount();
-  dbscan( minSize, eps, borderPointsAreNoise, featureCount, features, index, idToCluster, feedback );
+  QgsFeatureIterator features = source->getFeatures( QgsFeatureRequest().setNoAttributes() );
+  stdbscan( minSize, eps1, eps2, borderPointsAreNoise, featureCount, features, index, idToCluster, idToDateTime, feedback );

  // cluster size
  std::unordered_map< int, int> clusterSize;
@ -182,14 +201,15 @@ QVariantMap QgsDbscanClusteringAlgorithm::processAlgorithm( const QVariantMap &p
  return outputs;
 }

-
-void QgsDbscanClusteringAlgorithm::dbscan( const std::size_t minSize,
-    const double eps,
+void QgsDbscanClusteringAlgorithm::stdbscan( const std::size_t minSize,
+    const double eps1,
+    const double eps2,
    const bool borderPointsAreNoise,
    const long featureCount,
    QgsFeatureIterator features,
    QgsSpatialIndexKDBush &index,
    std::unordered_map< QgsFeatureId, int> &idToCluster,
+    std::unordered_map< QgsFeatureId, QDateTime> &idToDateTime,
    QgsProcessingFeedback *feedback )
 {
  const double step = featureCount > 0 ? 90.0 / featureCount : 1;
@ -231,13 +251,22 @@ void QgsDbscanClusteringAlgorithm::dbscan( const std::size_t minSize,
      continue;
    }

+    if ( !idToDateTime.empty() && !idToDateTime[ feat.id() ].isValid() )
+    {
+      // missing datetime value
+      feedback->reportError( QObject::tr( "Feature %1 is missing a valid datetime value." ).arg( feat.id() ).arg( QgsWkbTypes::displayString( feat.geometry().wkbType() ) ) );
+      feedback->setProgress( ++i * step );
+      continue;
+    }
+
    std::unordered_set< QgsSpatialIndexKDBushData, KDBushDataHashById, KDBushDataEqualById> within;

    if ( minSize > 1 )
    {
-      index.within( point, eps, [ &within]( const QgsSpatialIndexKDBushData & data )
+      index.within( point, eps1, [&within, pointId = feat.id(), &idToDateTime, &eps2]( const QgsSpatialIndexKDBushData & data )
      {
-        within.insert( data );
+        if ( idToDateTime.empty() || ( idToDateTime[ data.id ].isValid() && std::abs( idToDateTime[ pointId ].secsTo( idToDateTime[ data.id ] ) ) <= eps2 ) )
+          within.insert( data );
      } );
      if ( within.size() < minSize )
        continue;
@ -278,10 +307,12 @@ void QgsDbscanClusteringAlgorithm::dbscan( const std::size_t minSize,
      QgsPointXY point2 = j.point();

      std::unordered_set< QgsSpatialIndexKDBushData, KDBushDataHashById, KDBushDataEqualById > within2;
-      index.within( point2, eps, [&within2]( const QgsSpatialIndexKDBushData & data )
+      index.within( point2, eps1, [&within2, point2Id = j.id, &idToDateTime, &eps2]( const QgsSpatialIndexKDBushData & data )
      {
-        within2.insert( data );
+        if ( idToDateTime.empty() || ( idToDateTime[ data.id ].isValid() && std::abs( idToDateTime[ point2Id ].secsTo( idToDateTime[ data.id ] ) ) <= eps2 ) )
+          within2.insert( data );
      } );
+
      if ( within2.size() >= minSize )
      {
        // expand neighbourhood
--- a/src/analysis/processing/qgsalgorithmdbscanclustering.h
+++ b/src/analysis/processing/qgsalgorithmdbscanclustering.h
@ -54,14 +54,18 @@ class ANALYSIS_EXPORT QgsDbscanClusteringAlgorithm : public QgsProcessingAlgorit
    QVariantMap processAlgorithm( const QVariantMap &parameters,
                                  QgsProcessingContext &context, QgsProcessingFeedback *feedback ) override;
  private:
-    static void dbscan( std::size_t minSize,
-                        double eps,
-                        bool borderPointsAreNoise,
-                        long featureCount,
-                        QgsFeatureIterator features,
-                        QgsSpatialIndexKDBush &index,
-                        std::unordered_map< QgsFeatureId, int> &idToCluster,
-                        QgsProcessingFeedback *feedback );
+
+    static void stdbscan( std::size_t minSize,
+                          const double eps1,
+                          const double eps2,
+                          bool borderPointsAreNoise,
+                          long featureCount,
+                          QgsFeatureIterator features,
+                          QgsSpatialIndexKDBush &index,
+                          std::unordered_map< QgsFeatureId, int> &idToCluster,
+                          std::unordered_map< QgsFeatureId, QDateTime> &idToDateTime,
+                          QgsProcessingFeedback *feedback );
+
 };

 ///@endcond PRIVATE
--- a/src/analysis/processing/qgsalgorithmstdbscanclustering.cpp
+++ b/src/analysis/processing/qgsalgorithmstdbscanclustering.cpp
@ -0,0 +1,102 @@
+/***************************************************************************
+                         qgsalgorithmstdbscanclustering.cpp
+                         ---------------------
+    begin                : July 2018
+    copyright            : (C) 2018 by Nyall Dawson
+    email                : nyall dot dawson at gmail dot com
+ ***************************************************************************/
+
+/***************************************************************************
+ *                                                                         *
+ *   This program is free software; you can redistribute it and/or modify  *
+ *   it under the terms of the GNU General Public License as published by  *
+ *   the Free Software Foundation; either version 2 of the License, or     *
+ *   (at your option) any later version.                                   *
+ *                                                                         *
+ ***************************************************************************/
+
+#include "qgsalgorithmstdbscanclustering.h"
+
+///@cond PRIVATE
+
+QString QgsStDbscanClusteringAlgorithm::name() const
+{
+  return QStringLiteral( "stdbscanclustering" );
+}
+
+QString QgsStDbscanClusteringAlgorithm::displayName() const
+{
+  return QObject::tr( "ST-DBSCAN clustering" );
+}
+
+QString QgsStDbscanClusteringAlgorithm::shortDescription() const
+{
+  return QObject::tr( "Clusters spatiotemporal point features using a time and density based scan algorithm." );
+}
+
+QStringList QgsStDbscanClusteringAlgorithm::tags() const
+{
+  return QObject::tr( "clustering,clusters,density,based,points,temporal,time,interval,distance" ).split( ',' );
+}
+
+QString QgsStDbscanClusteringAlgorithm::group() const
+{
+  return QObject::tr( "Vector analysis" );
+}
+
+QString QgsStDbscanClusteringAlgorithm::groupId() const
+{
+  return QStringLiteral( "vectoranalysis" );
+}
+
+void QgsStDbscanClusteringAlgorithm::initAlgorithm( const QVariantMap & )
+{
+  addParameter( new QgsProcessingParameterFeatureSource( QStringLiteral( "INPUT" ),
+                QObject::tr( "Input layer" ), QList< int >() << QgsProcessing::TypeVectorPoint ) );
+  addParameter( new QgsProcessingParameterField( QStringLiteral( "DATETIME_FIELD" ),
+                QObject::tr( "Date/time field" ), QVariant(),
+                QStringLiteral( "INPUT" ), QgsProcessingParameterField::DateTime, false, false ) );
+
+  addParameter( new QgsProcessingParameterNumber( QStringLiteral( "MIN_SIZE" ), QObject::tr( "Minimum cluster size" ),
+                QgsProcessingParameterNumber::Integer, 5, false, 1 ) );
+  addParameter( new QgsProcessingParameterDistance( QStringLiteral( "EPS" ),
+                QObject::tr( "Maximum distance between clustered points" ), 1, QStringLiteral( "INPUT" ), false, 0 ) );
+  addParameter( new QgsProcessingParameterNumber( QStringLiteral( "EPS2" ),
+                QObject::tr( "Maximum date/time interval (in days unit) between clustered points" ), QgsProcessingParameterNumber::Double, 1, false, 0 ) );
+
+  auto dbscanStarParam = std::make_unique<QgsProcessingParameterBoolean>( QStringLiteral( "DBSCAN*" ),
+                         QObject::tr( "Treat border points as noise (DBSCAN*)" ), false, true );
+  dbscanStarParam->setFlags( dbscanStarParam->flags() | QgsProcessingParameterDefinition::FlagAdvanced );
+  addParameter( dbscanStarParam.release() );
+
+  auto fieldNameParam = std::make_unique<QgsProcessingParameterString>( QStringLiteral( "FIELD_NAME" ),
+                        QObject::tr( "Cluster field name" ), QStringLiteral( "CLUSTER_ID" ) );
+  fieldNameParam->setFlags( fieldNameParam->flags() | QgsProcessingParameterDefinition::FlagAdvanced );
+  addParameter( fieldNameParam.release() );
+  auto sizeFieldNameParam = std::make_unique<QgsProcessingParameterString>( QStringLiteral( "SIZE_FIELD_NAME" ),
+                            QObject::tr( "Cluster size field name" ), QStringLiteral( "CLUSTER_SIZE" ) );
+  sizeFieldNameParam->setFlags( sizeFieldNameParam->flags() | QgsProcessingParameterDefinition::FlagAdvanced );
+  addParameter( sizeFieldNameParam.release() );
+
+  addParameter( new QgsProcessingParameterFeatureSink( QStringLiteral( "OUTPUT" ), QObject::tr( "Clusters" ), QgsProcessing::TypeVectorPoint ) );
+
+  addOutput( new QgsProcessingOutputNumber( QStringLiteral( "NUM_CLUSTERS" ), QObject::tr( "Number of clusters" ) ) );
+}
+
+QString QgsStDbscanClusteringAlgorithm::shortHelpString() const
+{
+  return QObject::tr( "Clusters point features based on a 2D implementation of spatiotemporal density-based clustering of applications with noise (ST-DBSCAN) algorithm.\n\n"
+                      "For more details, please see the following papers:\n"
+                      "* Ester, M., H. P. Kriegel, J. Sander, and X. Xu, \"A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise\". In: Proceedings of the 2nd International Conference on Knowledge Discovery and Data Mining, Portland, OR, AAAI Press, pp. 226-231. 1996\n"
+                      "* Birant, Derya, and Alp Kut. \"ST-DBSCAN: An algorithm for clustering spatial–temporal data.\" Data & Knowledge Engineering 60.1 (2007): 208-221.\n"
+                      "* Peca, I., Fuchs, G., Vrotsou, K., Andrienko, N. V., & Andrienko, G. L. (2012). Scalable Cluster Analysis of Spatial Events. In EuroVA@ EuroVis." );
+}
+
+QgsStDbscanClusteringAlgorithm *QgsStDbscanClusteringAlgorithm::createInstance() const
+{
+  return new QgsStDbscanClusteringAlgorithm();
+}
+
+///@endcond
+
+
--- a/src/analysis/processing/qgsalgorithmstdbscanclustering.h
+++ b/src/analysis/processing/qgsalgorithmstdbscanclustering.h
@ -0,0 +1,56 @@
+/***************************************************************************
+                         qgsalgorithmstdbscanclustering.h
+                         ---------------------
+    begin                : July 2021
+    copyright            : (C) 2021 by Mathieu Pellerin
+    email                : nirvn dot asia at gmail dot com
+ ***************************************************************************/
+
+/***************************************************************************
+ *                                                                         *
+ *   This program is free software; you can redistribute it and/or modify  *
+ *   it under the terms of the GNU General Public License as published by  *
+ *   the Free Software Foundation; either version 2 of the License, or     *
+ *   (at your option) any later version.                                   *
+ *                                                                         *
+ ***************************************************************************/
+
+#ifndef QGSALGORITHMDSTBSCANCLUSTERING_H
+#define QGSALGORITHMDSTBSCANCLUSTERING_H
+
+#define SIP_NO_FILE
+
+#include "qgis_sip.h"
+#include "qgis_analysis.h"
+#include "qgsprocessingalgorithm.h"
+#include "qgsalgorithmdbscanclustering.h"
+
+///@cond PRIVATE
+
+
+/**
+ * Native ST-DBSCAN density based scan with noise clustering algorithm.
+ */
+class ANALYSIS_EXPORT QgsStDbscanClusteringAlgorithm : public QgsDbscanClusteringAlgorithm
+{
+
+  public:
+
+    QgsStDbscanClusteringAlgorithm() = default;
+    void initAlgorithm( const QVariantMap &configuration = QVariantMap() ) override;
+    QString name() const override;
+    QString displayName() const override;
+    QString shortDescription() const override;
+    QStringList tags() const override;
+    QString group() const override;
+    QString groupId() const override;
+    QString shortHelpString() const override;
+    QgsStDbscanClusteringAlgorithm *createInstance() const override SIP_FACTORY;
+
+};
+
+///@endcond PRIVATE
+
+#endif // QGSALGORITHMDSTBSCANCLUSTERING_H
+
+
--- a/src/analysis/processing/qgsnativealgorithms.cpp
+++ b/src/analysis/processing/qgsnativealgorithms.cpp
@ -186,6 +186,7 @@
 #include "qgsalgorithmsplitlinesbylength.h"
 #include "qgsalgorithmsplitvectorlayer.h"
 #include "qgsalgorithmsplitwithlines.h"
+#include "qgsalgorithmstdbscanclustering.h"
 #include "qgsalgorithmstringconcatenation.h"
 #include "qgsalgorithmsubdivide.h"
 #include "qgsalgorithmsumlinelength.h"
@ -458,6 +459,7 @@ void QgsNativeAlgorithms::loadAlgorithms()
  addAlgorithm( new QgsSplitLinesByLengthAlgorithm() );
  addAlgorithm( new QgsSplitVectorLayerAlgorithm() );
  addAlgorithm( new QgsSplitWithLinesAlgorithm() );
+  addAlgorithm( new QgsStDbscanClusteringAlgorithm() );
  addAlgorithm( new QgsStringConcatenationAlgorithm() );
  addAlgorithm( new QgsStyleFromProjectAlgorithm() );
  addAlgorithm( new QgsSubdivideAlgorithm() );