Lab8. Raster Data Analysis and Suitability Model in ArcGIS Pro

Lab8. Raster Data Analysis and Suitability Model in ArcGIS Pro
Objectives:
• Learn how to perform fundamental spatial analysis for raster data.
Data:
• Download the Landsat Harrisonburg image from the ArcGIS Online Portal.
• Download the DEM Harrisonburg from the ArcGIS Online Portal.
Steps:
1. Download the data
1.1. Start a new project in ArcGIS Pro and name it Lab8.
1.2. Search and drag Landsat Harrisonburg (authored by weixx_jmu) image from the ArcGIS Online Portal to your project.
1.3. Search and drag the DEM Harrisonburg (authored by weixx_jmu) image from the ArcGIS Online Portal to your project.
1.4. Export all the raster data to your project geodatabase. Make sure the appropriate PCS is selected.
1.5. Remove the downloaded raster datasets and only keep the exported datasets.
2. Terrain analysis
2.1. In Analysis/Environments, set the appropriate Output Coordinates and Processing Extent.
2.2. Calculate the Slope with the DEM dataset and choose PercentRise for the Scaling.
2.3. Calculate the Aspect with the DEM dataset.
2.4. Export the aspect and slope dataset to your geodatabase.
2.5. Use colors to show the change of the Slope.
2.6. Use arrows to show the Aspect.
3. Suitability analysis: suppose you are looking for a location for new residential buildings, and the site should be:
3.1. Far away from the regions where the elevation is above 500 meters
3.1.1. Reclassify the DEM to extract the elevation areas above 500 meters.
3.1.2. Use Distance Accumulation to calculate the distance to the extracted area.
3.1.3. Export the result of the distance to geodatabase and change the color of the result.
3.2. Flat area, e.g., the Slop is less than 3 PERCENT_RISE and facing the East, i.e., the Aspect ranges from 0 to 180
3.2.1. Reclassify the Slop to extract the areas where the Slope is less than a 3 percent rise.
3.2.2. Reclassify the Aspect to extract the areas where the Aspect is from 0 to 180.
3.2.3. Use Boolean And to intersect the reclassified aspect dataset with the reclassified slope dataset.
3.2.4. Export the Boolean result to geodatabase and name it flat_and_east.
3.3. Surrounded by more vegetation
3.3.1. Calculate the NDVI with the Landast dataset.
3.3.2. Export the result to the geodatabase and change the colors.
3.4. Build the Suitability model.
3.4.1. In the analysis, start the Suitability modeler
3.4.2. Drage the distance, flat_and_east, and NDVI datasets to the model
3.4.3. Double-click the flat_and_East parameter to bring up the transformation pane.
3.4.4. Change the function for the flat_and_east to Unique Categories.
3.4.5. Change the function for the distance to the Range of Classes.
3.4.6. Change the function for the NDVI to Countious/Invert MMSmall.
3.4.7. Adjust the weights for all the input rasters, and you can see the change in the suitability map when changing the weights.
3.4.8. Run the model to create the final suitability map.

[@thomasrquintero]

Great tutorial!

[@sheypaiva3698]

Just Great! Thank you

[@ahmedayed3505]

nice thanx

[@geoempowerinitiative7390]

I want to replicate this workflow for my City. What is the spatial resolution of the Landsat image you used? The resolution looks high for a landsat image. Secondly, would a sentinel images fit the same purpose with its 10-meter resolution? Thank you!

[@LBSocial]

I think the Landsat image I used has 30 m resolution. The sentinel images should work

[@geoempowerinitiative7390]

@@LBSocial thank you