gis多边形地图叠加交集运算
有许多用于矢量数据格式的二进制地图叠加操作的算法，它们采用两层地图并产生结果层，即叠加层作为输出。我想知道是否有任何算法可以同时采用两层以上（例如三层）并产生叠加结果？
There are many algorithms for binary map overlay operation in vector data format which take two layers of map and produce resultant layer i.e overlaid layer as output. I am wondering whether there are any algorithms which take more than two layers say 3 layers simultaneously and produce the overlay result?
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有多种可用于多层的地理计算叠加程序。这些属于多标准决策分析组，其中多个标准（地图）图层被标准化并组合（叠加）以生成结果（地图）图层。然而，其中许多都是用于栅格数据输入！
如果实际上您只想组合矢量数据来生成交集，那么程序模型将最有效，正如 @Thomas 所评论的那样。这可以通过 vis python（独立）或使用 arcgis 内的模型构建器来完成。唉，还有其他方法可用于编写程序覆盖过程的脚本。
我希望你考虑一下你到底想做什么。让我们考虑以下场景：
您有某个城市的矢量多边形，您的目标是覆盖所有工业、住宅和商业用地。这将使您从城市多边形中一一减去不同的土地用途。或者，您可以将三种土地用途合并为一个多边形，然后从城市多边形中减去。
鉴于多种标准决策分析方法（例如加权线性组合），如果您正在寻找“最佳位置”，则栅格方法可能适合。例如，如果您正在寻找城市中具有以下特征的位置：工业、商业和零售用地的优化组合可以采用加权线性组合。
让我们将土地利用权重定义为 20%、40%、40%（工业、商业、零售）。我们还必须将土地利用图层值标准化在 0 和 1 之间。以下图层值组合给出了三个标准的最佳组合：0.2、0.4 和 0.4 = 1。
There are a variety of geographic computational overlay procedures available for multiple layers. These fall into the group of multiple criteria decision analysis, whereby multiple criteria (map)layers are standardized and combined (overlayed) to produce a resulting (map)layer. However, many of these are for raster data inputs!
If in fact you want to just combine vector data to produce an intersection, a procedural model would work best as @Thomas has commented. This can be done vis a vis python (standalone) or with model builder inside arcgis. Alas, there are other methods that can be used to script the procedural overlay process.
I would like you to think about what exactly you're aiming to do. Let's think about the following scenarios:
You have a vector polygon of some City, and your goal is to overlay all the industrial, residential and commercial land usage. This would leave you to subtract the different land uses from your City polygon, one by one. Or, you can merge your three land uses into one poylgon and subtract from your City polygon.
Given the wide range of multiple criteria decision analysis methodologies (eg. weighted linear combination), a raster methodology might be suitable if you're looking for the "optimal location" For instance, if you were looking for a location in the City that has an optimal combination of industrial, commercial and retail land use, weighted linear combination could be used.
Let us define our land use weights as 20%, 40%, 40% (industrial, commercial, retail). We must also standardize our land use layer values between 0 and 1. The following combination of layer values give the most optimal combination of the three criteria: 0.2, 0.4 and 0.4 = 1.