代写URBAN5111 Principles and Applications of GIS Lab 5 Spatial Analysis代做留学生SQL 程序

URBAN5111 Principles and Applications of GIS (University of Glasgow)

Lab 5 Spatial Analysis (2)

Learning Objectives

•     Explore Spatial Analyst toolbox in ArcGIS Pro

•     Explore 3D Analyst toolbox in ArcGIS Pro

•     Learn to generate distance surface

•     Learn to create TIN, DTM and DSM from Lidar data

•     Learn to derive slope, aspect and hillshade from DTM

5.1 Spatial Analyst and 3D Analyst in ArcGIS Pro

5.1.1 Spatial Analyst

The Spatial Analyst extension for ArcGIS Pro provides a suite of tools and capabilities for performing comprehensive, raster-based spatial analysis. With this extension, you can employ a wide range of data formats to combine datasets, interpret new data, and perform. complex raster operations. Examples of the analysis that you can do with Spatial Analyst include terrain analysis, surface modelling, surface interpolation, suitability modelling, hydrological analysis, statistical analysis, and image classification.

Spatial Analyst provides many geoprocessing tools to perform. spatial analysis operations. In addition to the purely analytic tools, general categories of these tools include those that perform. basic mathematical and logical operations, as well as raster dataset creation and processing. The tools are organized by groups of related functionality into toolsets.

We will look at the tools in Distance toolbox in section 5.2.

5.1.2 3D Analyst

ArcGIS 3D Analyst extension in ArcGIS Pro provides tools for creating, visualizing, and analysing GIS data in a three-dimensional (3D) context.

•    Using ArcGIS 3D Analyst extension, you can do the following:

•    Create and analyse surfaces and other 3D data.

•    Import 3D feature data from multiple sources.

•    Use TINs as an elevation source.

•    Manage and maintain lidar data using the LAS dataset.

•    Edit point classification of lidar data using the LAS dataset and geoprocessing tools.

•    Update surface data over time.

•    Conduct visibility analysis with 3D feature and surface data.

•    Evaluate geometric properties and relationships between three-dimensional features.

•    Use deep learning to classify point clouds.

We will use the tools in 3D Analyst to create TIN, DTM and DSM from Lidar data, based on which we can calculate slope, aspect and hillshade. We will also visualize 3D buildings with the height information derived from Lidar data.

5. 1.3 Configure licensing setting

To be able to use the tools in 3D Analyst and Spatial Analyst toolboxes for the exercises in this Lab, we need to enable the relevant licenses.

1.    Create a new project.

Start ArcGIS Pro on your computer.

Create a new project and save it in the folder “…\Lab\Lab 5\Lab5_prj”. Name it as Lab5_prj.

2.    Click the Project tab on the ribbon. In the list oftabs on the left, click Licensing. Then click Configure your licensing options.

3.    In the Licensing dialogue box, select 3D Analyst and Spatial Analyst. Click OK.

4.    You need to restart ArcGIS Pro to enable the 3D Analyst and Spatial Analyst extensions. Restart ArcGIS Pro and open Lab5_prj.

5.2 Generate Distance Surfaces

5.2.1 Euclidean distance analysis

In this exercise, we will calculate the Euclidean distance to the nearest train station from any point within Glasgow. We will use the Euclidean Distance tool in the Spatial Analyst toolbox.

The source identifies the location of the objects of interest, such as wells, shopping malls, roads, and forest stands. If the source is a raster, it must contain only the values of the source cells, while other cells must be NoData. If the source is a feature, it will internally be transformed into a raster when you run the tool.

Euclidean distance is calculated from the centre of the source cell to the centre of each of the surrounding cells. Conceptually, the Euclidean algorithm works as follows: for each cell, the distance to each source cell is determined by calculating the hypotenuse with x_max andy_max as the other two legs of the triangle. This calculation derives the true Euclidean distance, rather than the cell distance. The shortest distance to a source is determined, and if it is less than the specified maximum distance, the value is assigned to the cell location on the output raster.

Set the geoprocessing environment for raster analysis

Environmental settings affect how geoprocessing is carried out by tools in the current project. You’ll set the cell size of raster datasets you create to 50 m, and you’ll use Glasgow boundary as the default mask.

1.    On the Analysis tab, click Environments.

2.    In the Environments settings for the Raster Analysis category, type 50 for Cell Size, and select SG_SIMD_2020_Glasgow for the default Extent and Mask.

3.    Click OK.

Calculate Euclidean distance

1.    Add data.

In the Contents pane, turn off all the layers. Add the following two datasets from “…\Lab\Lab 1\Data\Lab1.gdb” to the Map view (You can change the symbols if you like):

• NS_RailwayStation_Glasgow

• SG_SIMD_2020_Glasgows

2.    On the Analysis ribbon tab, in the Geoprocessing group, click Tools.

3.    This will open the Geoprocessing pane.

4.    In the Geoprocessing pane, click the Toolboxes tab.

Browse to Spatial Analyst ToolsDistanceLegacy.

5.    In the Legacy toolset, click Euclidean Distance.

The Euclidean Distance tool opens in the

Geoprocessing pane.

6.    On the Euclidean Distance tool, click the Input raster

or feature source data drop-down arrow and click NS_RailwayStation_Glasgow.

7.    Change the default Output distance raster name

to DistanceToRailwayStation (saved in “…\Lab\Lab 5\Lab5_prj\Lab5_prj.gdb”).

8.    Set the Output cell size 50 m.

9.    At the bottom of the Geoprocessing pane, click Run .

The output values for the Euclidean distance raster are floating-point distance values. If the cell is at an equal distance to two or more railway stations, the cell is assigned to the station that is first encountered in the scanning process. You cannot control this scanning process.

10. On the Quick Access Toolbar, click Save to save the project.

5.2.2 Euclidean allocation analysis

We can use Euclidean Allocation tool to assign space to objects such as identifying the customers served by a group of stores. In the example below, the Euclidean Allocation tool has identified the railway station that is closest to each cell. This could be valuable information if you needed to get to the nearest railway station from a remote location.

1.    In the Geoprocessing pane, click the Toolboxes tab.

Browse to Spatial Analyst ToolsDistanceLegacy.

2.    In the Legacy toolset, click Euclidean Allocation.

The Euclidean Allocation tool opens in the

Geoprocessing pane.

3.    On the Euclidean Allocation tool, click the Input raster or feature source data drop-down arrow and

click NS_RailwayStation_Glasgow.

4.    Change the default Output distance raster name to RailwayStation_Allocation (saved in “ …\Lab\Lab 5\Lab5_prj\Lab5_prj.gdb”).

5.    Set the Output cell size 50 m.

6.    At the bottom of the Geoprocessing pane, click Run .

Every cell in the output raster is assigned the value (OBJECTID in this case) of the railway

station to which it is closest, as determined by the Euclidean distance algorithm. Each cell in an allocation receives the value (OBJECTID in this case) of the zone to which it will be allocated.

7.    On the Quick Access Toolbar, click Save to save the project.