AnalyticDB:Spatio-temporal data analysis

Spatio-temporal data types

• Vector data: digital map data and digital elevation model (DEM) data.

• Raster data: remote sensing and panoramic image data.

• Perceptual data: location data from smart terminals and laser point cloud data.

Spatio-temporal data models

• Geometry model: complies with OpenGIS standards and supports 2D (x, y), 3D (x, y, z), and 4D (x, y, z, m) geometries.

• Raster model: consists of a matrix of cells or pixels that are organized into rows and columns (or grids). Each cell contains a value that represents information such as temperature. Raster data can be digital aerial photographs, satellite images, digital images, or scanned maps.

• Trajectory model: records the location information of a moving feature, such as a vehicle or a person.

Scenarios

• Business scenarios

  • Commercial site selection based on the analysis of foot traffic and demographics

  • Delivery personnel tracking or planning based on delivery trajectories or paths

  • Message or advertisement push based on an LBS

  • Analysis of spatial correlations based on consumers and their active regions

• Traffic scenarios

  • Real-time location services for public transportation, Internet plus transportation, and intelligent logistics

  • Traffic flow statistics on roads and crossroads, analysis and prediction of flows of people and vehicles, and estimated time of arrival (ETA)

  • Aggregate analysis of vehicle departure and destination points

  • Optimization on vehicle monitoring, scheduling, or dispatching

  • Trajectory matching and analysis on similar trajectories or paths

  • Transport capacity distribution or analysis and real-time operational heat map of moving objects

  • Dynamic management, monitoring, and alerting of electronic fences

• Public security scenarios

  • Special group tracking and child custody

  • Special vehicle tracking and abnormal vehicle identification

  • Alert push and danger warning

  • Travel monitoring and management based on health quick response (QR) codes

• Autopilot scenarios

  • Storage, retrieval, analysis, and spatio-temporal pattern mining of laser point cloud data

  • High-precision trajectory matching and planning of local paths

  • Production and storage management of high-precision maps

Spatio-temporal engines of AnalyticDB for PostgreSQL

AnalyticDB for PostgreSQL provides two extension modules to efficiently store, index, query, analyze, and calculate spatial or spatio-temporal data.

• PostGIS: an open source spatial database engine that is developed by the PostgreSQL community.

• GanosBase: a spatio-temporal engine that is developed by Alibaba Cloud based on PostgreSQL.

  Engine	Feature
  PostGIS	Support for geometry models. PostGIS fully complies with the OpenGIS standards and provides rich features such as objects, indexes, operation functions, and operators in geometric space. Support for raster models. PostGIS provides specific raster operation functions and operators. No support for trajectory models.
  GanosBase	Support for geometry models. GanosBase is fully compatible with the geometry models of PostGIS and allows you to smoothly migrate existing applications. Support for raster models. GanosBase supports data sources that are stored in Object Storage Service (OSS) and provides rich functions for management, analysis, and calculation of raster data. Therefore, GanosBase outperforms PostGIS. Support for trajectory models. GanosBase provides a set of data types, functions, and stored procedures to help you efficiently manage, query, and analyze spatio-temporal trajectory data.

  Benefits:

  • Easy to use. You can smoothly switch between PostGIS and GanosBase. Data can be migrated from a standalone PostgreSQL database to an AnalyticDB for PostgreSQL instance.

  • Cost-effective. AnalyticDB for PostgreSQL uses the massively parallel processing (MPP) architecture. An AnalyticDB for PostgreSQL instance can process more spatio-temporal data than a standalone PostgreSQL database based on the same performance metrics and computing resources. AnalyticDB for PostgreSQL integrates with OSS to implement tiered storage of hot and cold data. This way, costs can be reduced without decreasing performance, especially for the storage and calculation of raster data and laser point cloud data.