密度分析计算区域跨区域的事件或物体数量。计算结果揭示了最高浓度在该区域内的位置。您是否知道您还可以分析代表值大于1的点？仅仅因为可能存在一组点并不一定意味着某个区域具有最高浓度。所有您需要的是批量的属性。以下示例显示了在ArcGIS Pro 2.2中使用具有点密度工具的属性进行密度分析。此地图显示报告犯罪的地址位置。每个点可以代表多个报告。报告数量存储在属性表中的报告字段中。在“分析”选项卡上，单击“工具”。 In the search box, type Point Density. On the Analysis tab, click Tools. Select your input points. For Population field, select the attribute with the quantity value. Your Point Density geoprocessing pane should look something like this: Set your output raster. The output density raster shows the areas with the highest density based upon the number of reports at each address location. When you compare running the Point Density tool without a population field versus with a population field, you can see the difference in the results. Point density without population Point density with population By adding in the population field, a high-density area becomes more apparent in the northern area of the map. Upon further investigation, that particular area contains a mall, shopping center, and movie theatre—which probably contributes to the higher number of crime reports. Spatial analysis provides the tools you need to make informed decisions. Learning how to use the available tools will help you choose the specific analysis tool that will best meet your particular needs. Are you new to spatial analysis? I suggest that you take a look at the Getting Started with Spatial Analysis web course. This course builds a foundation of knowledge on the six categories of spatial analysis and how they are used in the spatial analysis workflow. Additional information on density analysis can be found in the Calculating Density Using ArcGIS web course. *Note: The data used in this example is fictitious and does not represent real crime data.
每个行业都有自己独特的GIS工作流。其中一些很简单，只需运行一两个工具。其他的更复杂，涉及多个工具和过程。对于每个工作流，必须有人花时间完成流程的每个步骤，然后在出现新项目或提供数据时再次(一次又一次)重复该流程。这些手工的、重复的工作流不仅耗费时间，而且容易出错。如果遗漏了一个步骤或在任何一个步骤中引入了错误，那么至少可以这样说，结果可能是有问题的。如果有一种方法可以在不涉及每一个任务的情况下重复您的工作流呢?如果你能找到一种节省时间的方法呢?你可以!Python为这些问题提供了解决方案。 Python scripts can help you: Streamline your GIS work. Easily repeat processes on different datasets. Save time by automating a series of complicated steps. But where do you begin? Exactly what tasks can you perform using Python? How can you improve the performance of your current Python scripts? For example, suppose you want a Python script that takes a table of customer locations and creates an outer polygon boundary of those locations. You have been manually drawing a polygon around an XY event layer of the locations each time they are updated, but the process takes a lot of time and is not entirely accurate. You can use Python lists and ArcPy geometry objects to complete this workflow efficiently and accurately. The Python script can be broken down into basic tasks: Define input and output variables. Create a Python list from the table of XY coordinates. Create a multipoint geometry object from the Python list. Use the convexHull() geometry method to create the boundary. Save geometry object of the boundary to a feature class. You can run this script as often as you need by simply modifying the variables. You can also create a Python script tool from it. Would you like to learn how to script your GIS tasks and workflows? Creating Python Scripts for ArcGIS is a new Esri course that takes you from minimal Python knowledge to creating Python scripts that automate a complete workflow . You’ll learn practical Python skills such as how to access and run geoprocessing tools, automate tasks with lists, work directly with GIS data, create Python script tools, and more. If you want to simplify your GIS workflows and get more work done in less time, take a look at the upcoming class schedule.