点云数据通常是由3D扫描仪扫描资料并以点的形式输出的记录,每一个点包含有三维坐标,有些可能含有颜色信息(RGB)或反射强度信息(Intensity),点云数据含有空间坐标信息,且具有数量众多、属性维度复杂的特点。

概述

Ganos PointCloud是云原生关系型数据库PolarDB的一个扩展,使PolarDB能够有效快速存储和管理点云数据,并提供点云数据压缩、解压缩、属性统计等功能,同时联合Ganos Geometry模块提供点云空间分析的能力。

点云数据类型

点云数据类型主要分为两种,一种是pcpoint数据类型,一个点一行记录存储。点的维度信息在元数据中定义。另一种是pcpatch数据类型,该类型将点以集合的方式进行存储,支持压缩,减少存储空间,支持空间检索。压缩方式由元数据中的“compression”决定。

点云元数据

表pointcloud_formats记录了点云的schema(元数据)信息。元数据包括点云的属性维度,以及每个维度的数据大小、类型、名称以及解释说明等。

快速入门

  • 创建扩展
    Create extension ganos_pointcloud cascade;
    Create extension ganos_pointcloud_geometry cascade;
  • 插入点云schema
    INSERT INTO pointcloud_formats (pcid, srid, schema) VALUES (1, 4326,
    '<?xml version="1.0" encoding="UTF-8"?>
    <pc:PointCloudSchema>
      <pc:dimension>
        <pc:position>1</pc:position>
        <pc:size>4</pc:size>
        <pc:description>X coordinate as a long integer. You must use the
                        scale and offset information of the header to
                        determine the double value.</pc:description>
        <pc:name>X</pc:name>
        <pc:interpretation>int32_t</pc:interpretation>
        <pc:scale>0.01</pc:scale>
      </pc:dimension>
      <pc:dimension>
        <pc:position>2</pc:position>
        <pc:size>4</pc:size>
        <pc:description>Y coordinate as a long integer. You must use the
                        scale and offset information of the header to
                        determine the double value.</pc:description>
        <pc:name>Y</pc:name>
        <pc:interpretation>int32_t</pc:interpretation>
        <pc:scale>0.01</pc:scale>
      </pc:dimension>
      <pc:dimension>
        <pc:position>3</pc:position>
        <pc:size>4</pc:size>
        <pc:description>Z coordinate as a long integer. You must use the
                        scale and offset information of the header to
                        determine the double value.</pc:description>
        <pc:name>Z</pc:name>
        <pc:interpretation>int32_t</pc:interpretation>
        <pc:scale>0.01</pc:scale>
      </pc:dimension>
      <pc:dimension>
        <pc:position>4</pc:position>
        <pc:size>2</pc:size>
        <pc:description>The intensity value is the integer representation
                        of the pulse return magnitude. This value is optional
                        and system specific. However, it should always be
                        included if available.</pc:description>
        <pc:name>Intensity</pc:name>
        <pc:interpretation>uint16_t</pc:interpretation>
        <pc:scale>1</pc:scale>
      </pc:dimension>
      <pc:metadata>
        <Metadata name="compression">dimensional</Metadata>
      </pc:metadata>
    </pc:PointCloudSchema>');
  • 创建点云表
    -- 使用pcpoint数据类型
    CREATE TABLE points (
        id SERIAL PRIMARY KEY,
        pt PCPOINT(1)
    );
    
    -- 使用pcpatch数据类型
    CREATE TABLE patches (
        id SERIAL PRIMARY KEY,
        pa PCPATCH(1)
    );
  • 插入pcpoint类型数据
    INSERT INTO points (pt)
    SELECT ST_MakePoint(1, ARRAY[x,y,z,intensity])
    FROM (
      SELECT
      -127+a/100.0 AS x,
        45+a/100.0 AS y,
             1.0*a AS z,
              a/10 AS intensity
      FROM generate_series(1,100) AS a
    ) AS values;
    
    SELECT ST_MakePoint(1, ARRAY[-127, 45, 124.0, 4.0]);
    -------------------------
    010100000064CEFFFF94110000703000000400
    
    SELECT ST_AsText('010100000064CEFFFF94110000703000000400'::pcpoint);
    -------------------------
    {"pcid":1,"pt":[-127,45,124,4]}
  • 插入pcpatch类型数据
    INSERT INTO patches (pa)
    SELECT ST_Patch(pt) FROM points GROUP BY id/10;
    
    SELECT ST_AsText(ST_MakePatch(1, ARRAY[-126.99,45.01,1,0, -126.98,45.02,2,0, -126.97,45.03,3,0]));
    -------------------------
    {"pcid":1,"pts":[
     [-126.99,45.01,1,0],[-126.98,45.02,2,0],[-126.97,45.03,3,0]
    ]}
  • pcpatch属性平均值计算
    SELECT ST_AsText(ST_PatchAvg(pa)) FROM patches WHERE id = 7;
    -------------------------
    {"pcid":1,"pt":[-126.46,45.54,54.5,5]}
  • 删除扩展
    Drop extension ganos_pointcloud_geometry;
    Drop extension ganos_pointcloud cascade;

SQL参考

详细SQL手册请参见PointCloud SQL参考