en to zh_Hans translation catalogue (72 entries)

note: Tag: title
en: Spatial Queries
zh_Hans: 空间查询

note: Tag: para
en: The <emphasis>raison d'etre</emphasis> of spatial databases is to perform queries inside the database which would ordinarily require desktop GIS functionality. Using PostGIS effectively requires knowing what spatial functions are available, how to use them in queries, and ensuring that appropriate indexes are in place to provide good performance.
zh_Hans: 空间数据库<emphasis>存在的理由</emphasis>是在数据库内执行查询，这通常需要桌面 GIS 功能。有效使用 PostGIS 需要了解哪些空间函数可用、如何在查询中使用它们，并确保适当的索引以提供良好的性能。

note: Tag: title
en: Determining Spatial Relationships
zh_Hans: 空间关系的确定

note: Tag: para
en: Spatial relationships indicate how two geometries interact with one another. They are a fundamental capability for querying geometry.
zh_Hans: 空间关系显示两个几何图形如何相互关联。用于查询几何的基本功能。

note: Tag: title
en: Dimensionally Extended 9-Intersection Model
zh_Hans: 维度扩展9相交模型（Dimensionally Extended 9-Intersection Model）

note: Tag: para
en: According to the <ulink url="http://www.opengeospatial.org/standards/sfs">OpenGIS Simple Features Implementation Specification for SQL</ulink>, "the basic approach to comparing two geometries is to make pair-wise tests of the intersections between the Interiors, Boundaries and Exteriors of the two geometries and to classify the relationship between the two geometries based on the entries in the resulting 'intersection' matrix."
zh_Hans: 根据<ulink url="http://www.opengeospatial.org/standards/sfs">OpenGIS SQL简单特征实现规范</ulink>，“比较两个几何图形的基本方法是对两个几何图形的内部、边界和外部之间的相交进行交集测试，并根据'交集矩阵'的元素对两个几何之间的关系进行分类。”

note: Tag: para
en: In the theory of point-set topology, the points in a geometry embedded in 2-dimensional space are categorized into three sets:
zh_Hans: 在点集拓扑理论中，嵌入二维空间的几何中的点被分为三个集合：

note: Tag: glossterm
en: <glossterm>Boundary</glossterm>
zh_Hans: <glossterm>边界</glossterm>

note: Tag: para
en: The boundary of a geometry is the set of geometries of the next lower dimension. For <varname>POINT</varname>s, which have a dimension of 0, the boundary is the empty set. The boundary of a <varname>LINESTRING</varname> is the two endpoints. For <varname>POLYGON</varname>s, the boundary is the linework of the exterior and interior rings.
zh_Hans: 几何的边界是下一个较低维度的几何的集合。 对于维数为 0 的 <varname>POINT</varname>s，边界是空集。<varname>LINESTRING</varname>的边界是两个端点。 对于<varname>POLYGON</varname>s，边界是外环和内环的线条。

note: Tag: glossterm
en: <glossterm>Interior</glossterm>
zh_Hans: <glossterm>内部</glossterm>

note: Tag: para
en: The interior of a geometry are those points of a geometry that are not in the boundary. For <varname>POINT</varname>s, the interior is the point itself. The interior of a <varname>LINESTRING</varname> is the set of points between the endpoints. For <varname>POLYGON</varname>s, the interior is the areal surface inside the polygon.
zh_Hans: 几何图形的内部是几何图形中不在边界内的那些点。对于<varname>POINT</varname>s来说，内部就是点本身。<varname>LINESTRING</varname>的内部是端点之间的点集。 对于<varname>POLYGON</varname>s，内部是多边形内的面。

note: Tag: glossterm
en: <glossterm>Exterior</glossterm>
zh_Hans: <glossterm>外部</glossterm>

note: Tag: para
en: The exterior of a geometry is the rest of the space in which the geometry is embedded; in other words, all points not in the interior or on the boundary of the geometry. It is a 2-dimensional non-closed surface.
zh_Hans: 几何体的外部是几何体嵌入的空间的其余部分；换句话说，所有不在几何内部或边界上的点。 它是一个二维非封闭曲面。

note: Tag: para
en: The <ulink url="http://en.wikipedia.org/wiki/DE-9IM">Dimensionally Extended 9-Intersection Model</ulink> (DE-9IM) describes the spatial relationship between two geometries by specifying the dimensions of the 9 intersections between the above sets for each geometry. The intersection dimensions can be formally represented in a 3x3 <emphasis role="bold">intersection matrix</emphasis>.
zh_Hans: The <ulink url="http://en.wikipedia.org/wiki/DE-9IM">Dimensionally Extended 9-Intersection Model</ulink> (DE-9IM)通过指定每个几何图形的上述集合之间的 9 个相交的维度来描述两个几何图形之间的空间关系。交集维度可以正式表示为 3x3 <emphasis role="bold">交集矩阵</emphasis>。

note: Tag: para
en: For a geometry <emphasis>g</emphasis> the <emphasis>Interior</emphasis>, <emphasis>Boundary</emphasis>, and <emphasis>Exterior</emphasis> are denoted using the notation <emphasis>I(g)</emphasis>, <emphasis>B(g)</emphasis>, and <emphasis>E(g)</emphasis>. Also, <emphasis>dim(s)</emphasis> denotes the dimension of a set <emphasis>s</emphasis> with the domain of <literal>{0,1,2,F}</literal>:
zh_Hans: 对于几何图形<emphasis>g</emphasis>，<emphasis>内部</emphasis>、<emphasis>边界</emphasis>和<emphasis>外部</emphasis>使用符号<emphasis>I(g)</emphasis>、<emphasis>B(g)</emphasis>和<emphasis>E(g)</emphasis>表示。 此外，<emphasis>dim(s)</emphasis> 表示域为 <literal>{0,1,2,F}</literal>的集合<emphasis>s</emphasis> ：

note: Tag: para
en: <literal>0</literal> =&gt; point
zh_Hans: <literal>0</literal> =&gt; 点集合

note: Tag: para
en: <literal>1</literal> =&gt; line
zh_Hans: <literal>1</literal> =&gt; 线集合

note: Tag: para
en: <literal>2</literal> =&gt; area
zh_Hans: <literal>2</literal> =&gt; 面集合

note: Tag: para
en: <literal>F</literal> =&gt; empty set
zh_Hans: <literal>F</literal> =&gt;空集合

note: Tag: para
en: Using this notation, the intersection matrix for two geometries <emphasis>a</emphasis> and <emphasis>b</emphasis> is:
zh_Hans: 使用此表示法，两个几何<emphasis>a</emphasis>和<emphasis>b</emphasis>的交集矩阵为：

note: Tag: emphasis
en: <emphasis role="bold">Interior</emphasis>
zh_Hans: <emphasis role="bold">内部（Interior）</emphasis>

note: Tag: emphasis
en: <emphasis role="bold">Boundary</emphasis>
zh_Hans: <emphasis role="bold">边界（Boundary）</emphasis>

note: Tag: emphasis
en: <emphasis role="bold">Exterior</emphasis>
zh_Hans: <emphasis role="bold">外部（Exterior）</emphasis>

note: Tag: para
en: Visually, for two overlapping polygonal geometries, this looks like:
zh_Hans: 从视觉上看，对于两个重叠的多边形几何图形，如下所示：

note: Tag: para
en: Reading from left to right and top to bottom, the intersection matrix is represented as the text string '<emphasis role="bold">212101212</emphasis>'.
zh_Hans: 从左到右，从上到下阅读。交集矩阵的字符串表示形式为“<emphasis role="bold">212101212</emphasis>”。

note: Tag: para
en: For more information, refer to:
zh_Hans: 欲了解更多信息，请访问：

note: Tag: para
en: <ulink url="http://www.opengeospatial.org/standards/sfs">OpenGIS Simple Features Implementation Specification for SQL</ulink> (version 1.1, section 2.1.13.2)
zh_Hans: <ulink url="http://www.opengeospatial.org/standards/sfs">适用于 SQL 的 OpenGIS 简单功能实现规范</ulink> (1.1版本, 第 2.1.13.2 节)。

note: Tag: ulink
en: Wikipedia: Dimensionally Extended Nine-Intersection Model (DE-9IM)
zh_Hans: 维基百科：维度扩展九交集模型 （DE-9IM）

note: Tag: ulink
en: GeoTools: Point Set Theory and the DE-9IM Matrix
zh_Hans: 地理工具：点集理论和DE-9IM矩阵

note: Tag: title
en: Named Spatial Relationships
zh_Hans: 命名空间关系

note: Tag: para
en: To make it easy to determine common spatial relationships, the OGC SFS defines a set of <emphasis>named spatial relationship predicates</emphasis>. PostGIS provides these as the functions <xref linkend="ST_Contains"/>, <xref linkend="ST_Crosses"/>, <xref linkend="ST_Disjoint"/>, <xref linkend="ST_Equals"/>, <xref linkend="ST_Intersects"/>, <xref linkend="ST_Overlaps"/>, <xref linkend="ST_Touches"/>, <xref linkend="ST_Within"/>. It also defines the non-standard relationship predicates <xref linkend="ST_Covers"/>, <xref linkend="ST_CoveredBy"/>, and <xref linkend="ST_ContainsProperly"/>.
zh_Hans: 为了便于确定常见的空间关系，OGC SFS 定义了一组<emphasis>命名空间关系谓词</emphasis>。PostGIS 将这些功能提供为函数 <xref linkend="ST_Contains"/>, <xref linkend="ST_Crosses"/>, <xref linkend="ST_Disjoint"/>, <xref linkend="ST_Equals"/>, <xref linkend="ST_Intersects"/>, <xref linkend="ST_Overlaps"/>, <xref linkend="ST_Touches"/>, <xref linkend="ST_Within"/>。 它还定义了非标准关系谓词 <xref linkend="ST_Covers"/>, <xref linkend="ST_CoveredBy"/>, 和<xref linkend="ST_ContainsProperly"/>。

note: Tag: para
en: Spatial predicates are usually used as conditions in SQL <code>WHERE</code> or <code>JOIN</code> clauses. The named spatial predicates automatically use a spatial index if one is available, so there is no need to use the bounding box operator <code>&amp;&amp;</code> as well. For example:
zh_Hans: 空间谓词通常用作 SQL <code>WHERE</code>或<code>JOIN</code>子句中的条件。如果空间索引可用，命名空间谓词会自动使用空间索引，因此无需使用边界框运算符<code>&amp;&amp;</code>。例如：

note: Tag: para
en: For more details and illustrations, see the <ulink url="https://postgis.net/workshops/postgis-intro/spatial_relationships.html">PostGIS Workshop.</ulink>
zh_Hans: 有关更多详细信息和插图，请参阅<ulink url="https://postgis.net/workshops/postgis-intro/spatial_relationships.html">PostGIS Workshop.</ulink>。

note: Tag: title
en: General Spatial Relationships
zh_Hans: 一般空间关系

note: Tag: para
en: In some cases the named spatial relationships are insufficient to provide a desired spatial filter condition.
zh_Hans: 在某些情况下，指定的空间关系不足以提供所需的空间过滤条件。

note: Tag: para
en: For example, consider a linear dataset representing a road network. It may be required to identify all road segments that cross each other, not at a point, but in a line (perhaps to validate some business rule). In this case <xref linkend="ST_Crosses"/> does not provide the necessary spatial filter, since for linear features it returns <varname>true</varname> only where they cross at a point.
zh_Hans: 例如，考虑表示道路网络的线性数据集。 可能需要识别所有相互交叉的路段，不是在一个点，而是在一条线上（也许是为了验证某些业务规则）。 在这种情况下，<xref linkend="ST_Crosses"/>不提供必要的空间过滤器，因为对于线性要素，它仅在它们在某个点交叉的地方返回<varname>true</varname>。

note: Tag: para
en: A two-step solution would be to first compute the actual intersection (<xref linkend="ST_Intersection"/>) of pairs of road lines that spatially intersect (<xref linkend="ST_Intersects"/>), and then check if the intersection's <xref linkend="ST_GeometryType"/> is '<varname>LINESTRING</varname>' (properly dealing with cases that return <varname>GEOMETRYCOLLECTION</varname>s of <varname>[MULTI]POINT</varname>s, <varname>[MULTI]LINESTRING</varname>s, etc.).
zh_Hans: 两步解决方案是首先计算空间相交 (<xref linkend="ST_Intersection"/>)的道路线对的实际交叉点 (<xref linkend="ST_Intersects"/>)，然后检查交叉点的 <xref linkend="ST_GeometryType"/> 是否为“<varname>LINESTRING</varname>”（正确处理返回 <varname>GEOMETRYCOLLECTION</varname>s、<varname>[MULTI]POINT</varname>s、<varname>[MULTI]LINESTRING</varname>s等情况）。

note: Tag: para
en: Clearly, a simpler and faster solution is desirable.
zh_Hans: 显然，更简单、更快捷的解决方案更可取。

note: Tag: para
en: A second example is locating wharves that intersect a lake's boundary on a line and where one end of the wharf is up on shore. In other words, where a wharf is within but not completely contained by a lake, intersects the boundary of a lake on a line, and where exactly one of the wharf's endpoints is within or on the boundary of the lake. It is possible to use a combination of spatial predicates to find the required features:
zh_Hans: 第二个例子是定位与湖泊边界相交的码头，并且码头的一端位于岸上。换句话说，如果码头位于湖泊内但未完全被湖泊包围，则与湖泊边界相交于一条线，并且码头的端点之一恰好位于湖泊边界内或湖泊边界上。 可以使用空间谓词的组合来查找所需的特征：

note: Tag: para
en: ... but needless to say, this is quite complicated.
zh_Hans: ... 不用说，这非常复杂。

note: Tag: para
en: These requirements can be met by computing the full DE-9IM intersection matrix. PostGIS provides the <xref linkend="ST_Relate"/> function to do this:
zh_Hans: 这些要求可以通过计算完整的 DE-9IM 交集矩阵来满足。PostGIS 提供了<xref linkend="ST_Relate"/> 函数来执行此操作：

note: Tag: para
en: To test a particular spatial relationship, an <emphasis role="bold">intersection matrix pattern</emphasis> is used. This is the matrix representation augmented with the additional symbols <literal>{T,*}</literal>:
zh_Hans: 为了测试特定的空间关系，使用<emphasis role="bold">相交矩阵模式</emphasis>。这是用附加符号<literal>{T,*}</literal>增强的矩阵表示：

note: Tag: para
en: <literal>T</literal> =&gt; intersection dimension is non-empty; i.e. is in <literal>{0,1,2}</literal>
zh_Hans: <literal>T</literal> =&gt; 表示交集的维度不为空;即<literal>{0,1,2}</literal>

note: Tag: para
en: <literal>*</literal> =&gt; don't care
zh_Hans: <literal>*</literal> =&gt; 任何东西

note: Tag: para
en: Using intersection matrix patterns, specific spatial relationships can be evaluated in a more succinct way. The <xref linkend="ST_Relate"/> and the <xref linkend="ST_RelateMatch"/> functions can be used to test intersection matrix patterns. For the first example above, the intersection matrix pattern specifying two lines intersecting in a line is '<emphasis role="bold">1*1***1**</emphasis>':
zh_Hans: 使用交叉矩阵模式，可以以更简洁的方式评估特定的空间关系。<xref linkend="ST_Relate"/>和<xref linkend="ST_RelateMatch"/> 函数可用于测试相交矩阵模式。 对于上面的第一个示例，指定两条线相交的交集矩阵模式为<emphasis role="bold">1*1***1**</emphasis>'：

note: Tag: para
en: For the second example, the intersection matrix pattern specifying a line partly inside and partly outside a polygon is '<emphasis role="bold">102101FF2</emphasis>':
zh_Hans: 这是第二个示例。当线部分位于多边形内部和外部时，相交矩阵模式为<emphasis role="bold">102101FF2</emphasis>。

note: Tag: title
en: Using Spatial Indexes
zh_Hans: 使用空间索引

note: Tag: para
en: When constructing queries using spatial conditions, for best performance it is important to ensure that a spatial index is used, if one exists (see <xref linkend="build-indexes"/>). To do this, a spatial operator or index-aware function must be used in a <code>WHERE</code> or <code>ON</code> clause of the query.
zh_Hans: 使用空间条件构建查询时，为了获得最佳性能，确保使用空间索引（如果存在）非常重要（请参阅<xref linkend="build-indexes"/>）。为此，必须在查询的<code>WHERE</code>或<code>ON</code>子句中使用空间运算符或索引感知函数。

note: Tag: para
en: Spatial operators include the bounding box operators (of which the most commonly used is <xref linkend="geometry_overlaps"/>; see <xref linkend="operators-bbox"/> for the full list) and the distance operators used in nearest-neighbor queries (the most common being <xref linkend="geometry_distance_knn"/>; see <xref linkend="operators-distance"/> for the full list.)
zh_Hans: 空间运算符包括边界框运算符（其中最常用的是<xref linkend="geometry_overlaps"/>; 有关完整列表，请参见<xref linkend="operators-bbox"/>）以及最近邻查询中使用的距离运算符（最常见的是<xref linkend="geometry_distance_knn"/>; 有关完整列表，请参见 <xref linkend="operators-distance"/>)。

note: Tag: para
en: Index-aware functions automatically add a bounding box operator to the spatial condition. Index-aware functions include the named spatial relationship predicates <xref linkend="ST_Contains"/>, <xref linkend="ST_ContainsProperly"/>, <xref linkend="ST_CoveredBy"/>, <xref linkend="ST_Covers"/>, <xref linkend="ST_Crosses"/>, <xref linkend="ST_Intersects"/>, <xref linkend="ST_Overlaps"/>, <xref linkend="ST_Touches"/>, <xref linkend="ST_Within"/>, <xref linkend="ST_Within"/>, and <xref linkend="ST_3DIntersects"/>, and the distance predicates <xref linkend="ST_DWithin"/>, <xref linkend="ST_DFullyWithin"/>, <xref linkend="ST_3DDFullyWithin"/>, and <xref linkend="ST_3DDWithin"/> .)
zh_Hans: 索引感知函数会自动将边界框运算符添加到空间条件中。 索引感知函数包括命名空间关系谓词  <xref linkend="ST_Contains"/>, <xref linkend="ST_ContainsProperly"/>, <xref linkend="ST_CoveredBy"/>, <xref linkend="ST_Covers"/>, <xref linkend="ST_Crosses"/>, <xref linkend="ST_Intersects"/>, <xref linkend="ST_Overlaps"/>, <xref linkend="ST_Touches"/>, <xref linkend="ST_Within"/>, <xref linkend="ST_Within"/>, 和<xref linkend="ST_3DIntersects"/> 以及距离谓词<xref linkend="ST_DWithin"/>, <xref linkend="ST_DFullyWithin"/>, <xref linkend="ST_3DDFullyWithin"/>, 和 <xref linkend="ST_3DDWithin"/>。）

note: Tag: para
en: Functions such as <xref linkend="ST_Distance"/> do <emphasis>not</emphasis> use indexes to optimize their operation. For example, the following query would be quite slow on a large table:
zh_Hans:  <xref linkend="ST_Distance"/> 等函数<emphasis>不</emphasis>使用索引来优化其操作。例如，以下查询在大型表上会非常慢：

note: Tag: para
en: This query selects all the geometries in <code>geom_table</code> which are within 100 units of the point (100000, 200000). It will be slow because it is calculating the distance between each point in the table and the specified point, ie. one <varname>ST_Distance()</varname> calculation is computed for <emphasis role="bold">every</emphasis> row in the table.
zh_Hans: 此查询选择<code>geom_table</code>中距离 (100000, 200000)该点100个单位以内的所有几何图形。它会很慢，因为它正在计算表中每个点与指定点之间的距离，即为表中的 <emphasis role="bold">每一</emphasis>行计算一个<varname>ST_Distance()</varname>。

note: Tag: para
en: The number of rows processed can be reduced substantially by using the index-aware function <xref linkend="ST_DWithin"/>:
zh_Hans: 通过使用索引感知函数<xref linkend="ST_DWithin"/> 可以大大减少处理的行数：

note: Tag: para
en: This query selects the same geometries, but it does it in a more efficient way. This is enabled by <varname>ST_DWithin()</varname> using the <varname>&amp;&amp;</varname> operator internally on an expanded bounding box of the query geometry. If there is a spatial index on <code>geom</code>, the query planner will recognize that it can use the index to reduce the number of rows scanned before calculating the distance. The spatial index allows retrieving only records with geometries whose bounding boxes overlap the expanded extent and hence which <emphasis>might</emphasis> be within the required distance. The actual distance is then computed to confirm whether to include the record in the result set.
zh_Hans: 此查询选择相同的几何图形，但采用更有效的方法。 通过使用<varname>ST_DWithin()</varname>带有查询几何图形的放大边界框的<varname>&amp;&amp;</varname>运算符，可以在内部实现。 如果<code>geom</code>存在空间索引，则查询规划器知道该索引可用于在计算距离之前减少感兴趣的行数。空间索引允许您仅搜索与边界框扩展范围重叠的几何，从而搜索 <emphasis>可能</emphasis>位于所需距离内的几何。 然后执行实际距离计算以查看结果集中的记录是否包括在内。

note: Tag: para
en: For more information and examples see the <ulink url="https://postgis.net/workshops/postgis-intro/indexing.html">PostGIS Workshop</ulink>.
zh_Hans: 有关详细信息和示例，请参阅<ulink url="https://postgis.net/workshops/postgis-intro/indexing.html">PostGIS Workshop</ulink>。

note: Tag: title
en: Examples of Spatial SQL
zh_Hans: 空间SQL示例

note: Tag: para
en: The examples in this section make use of a table of linear roads, and a table of polygonal municipality boundaries. The definition of the <varname>bc_roads</varname> table is:
zh_Hans: 本节中的示例使用线性道路表和多边形城市边界表。<varname>bc_roads</varname> 表的定义是：

note: Tag: para
en: The definition of the <varname>bc_municipality</varname> table is:
zh_Hans: <varname>bc_municipality</varname>表定义如下：

note: Tag: para
en: What is the total length of all roads, expressed in kilometers?
zh_Hans: 道路的总长度是多少公里？

note: Tag: para
en: You can answer this question with a very simple piece of SQL:
zh_Hans: 这个问题可以用非常简单的SQL来回答，例如：

note: Tag: para
en: How large is the city of Prince George, in hectares?
zh_Hans: 乔治王子城有多大（以公顷为单位）？

note: Tag: para
en: This query combines an attribute condition (on the municipality name) with a spatial calculation (of the polygon area):
zh_Hans: 此查询将空间计算（面面积）与属性条件（自治市名称）结合使用。

note: Tag: para
en: What is the largest municipality in the province, by area?
zh_Hans: 按面积计算，该省最大的直辖市是哪个？

note: Tag: para
en: This query uses a spatial measurement as an ordering value. There are several ways of approaching this problem, but the most efficient is below:
zh_Hans: 此查询使用空间测量作为排序值。 有多种方法可以解决此问题，但最有效的方法如下：

note: Tag: para
en: Note that in order to answer this query we have to calculate the area of every polygon. If we were doing this a lot it would make sense to add an area column to the table that could be indexed for performance. By ordering the results in a descending direction, and them using the PostgreSQL "LIMIT" command we can easily select just the largest value without using an aggregate function like MAX().
zh_Hans: 请注意，为了回答这个查询，我们必须计算每个多边形的面积。 如果我们经常这样做，那么向表中添加一个区域列是有意义的，可以为性能建立索引。 通过按降序对结果进行排序，并使用 PostgreSQL“LIMIT”命令，我们可以轻松地仅选择最大值，而无需使用 MAX() 等聚合函数

note: Tag: para
en: What is the length of roads fully contained within each municipality?
zh_Hans: 每个城市包含的道路总长度是多少？

note: Tag: para
en: This is an example of a "spatial join", which brings together data from two tables (with a join) using a spatial interaction ("contained") as the join condition (rather than the usual relational approach of joining on a common key):
zh_Hans: 这是“空间联接”的示例，它使用空间交互（“包含”）作为联接条件（而不是在公共键上联接的通常关系方法）将来自两个表（带有联接）的数据汇集在一起 :

note: Tag: para
en: This query takes a while, because every road in the table is summarized into the final result (about 250K roads for the example table). For smaller datsets (several thousand records on several hundred) the response can be very fast.
zh_Hans: 此查询需要一段时间，因为表中的每条道路都会汇总到最终结果中（示例表中大约有 250K 条道路）。 对于较小的数据集（数百条记录中的数千条），响应可能非常快。

note: Tag: para
en: Create a new table with all the roads within the city of Prince George.
zh_Hans: 创建一个包含乔治王子市内所有道路的新表。

note: Tag: para
en: This is an example of an "overlay", which takes in two tables and outputs a new table that consists of spatially clipped or cut resultants. Unlike the "spatial join" demonstrated above, this query creates new geometries. An overlay is like a turbo-charged spatial join, and is useful for more exact analysis work:
zh_Hans: 这是“覆盖”的一个示例。 也就是说，我们取两个表并输出一个由空间切割结果组成的新表。 与上面显示的“空间连接”不同，此查询实际上会生成新的几何图形。 生成的叠加就像涡轮增压的空间耦合，对于更精确的分析工作非常有用。

note: Tag: para
en: What is the length in kilometers of "Douglas St" in Victoria?
zh_Hans: 维多利亚州的“道格拉斯街”有多长（公里）？

note: Tag: para
en: What is the largest municipality polygon that has a hole?
zh_Hans: 哪个市政面的孔洞最大？
