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Calculate areas of eligible open space

In the previous lesson, you filtered the national raster based on your desired impervious surface threshold and clipped to your area of interest. Now, pursuant to the requirements of the CRS review process, you need to determine the acreage of eligible open space per parcel in your community. Since the acreage calculated also needs to be joined back to the raster data for final analysis, you'll run zonal statistics. Zonal statistics will calculate the majority statistic for a specified boundary layer, which is the same as the value attribute you gave your PADUS_CRS_final.tif layer in the previous lesson. Once you have this information, you'll join the tables to the parcel and raster datasets.

Calculate the majority statistic

The Zonal Statistics geoprocessing tool allows you to calculate a variety of statistics, including mean and median, within a defined area. The majority statistic summarizes the most common value found in all the PADUS_CRS_final raster cells within each parcel. This field will be used later to join the parcel tables together.

  1. If necessary, open your CRS_Georgetown_Co project.
  2. If necessary, open the Geoprocessing pane. In the search box, type Zonal Statistics as Table.
  3. Click Zonal Statistics as Table (Spatial Analyst Tools).

    Zonal Statistics as Table tool

  4. For Input raster or feature zone data, choose GeorgetownCo_Parcels. For Zone field, choose PARCEL_ID.
  5. For Input value raster, choose PADUS_CRS_final.tif. Name the output table Parcels_Zonal.
  6. For Statistics type, choose Majority.

    Zonal Statistics parameters

  7. Click Run.

    If the warning message "some zones may not have been rasterized" appears, just ignore it. The result table is added to the Contents pane under Standalone Tables.

  8. Right-click Parcels_Zonal and choose Open.

    The table includes columns for area (sq m) of open space per unique PARCEL_ID. The majority statistic summarizes the most common value found in all the PADUS_CRS_final raster cells within each parcel. Majority is the same attribute as the Value field in the attribute table you created for the PADUS_CRS_final.tif raster. Majority also is the same as the ObjectID field in the PADUS_CRS_attributes lookup table. You'll use this common field to join these data sources later.

    Majority column

Estimate open space acreage

FEMA encourages conservative estimations of OSP eligible area per parcel. When using coarse data, you can incorporate the accuracy of the underlying data to accomplish this. In this case, 0.85 represents the measured level of interpretation accuracy for the 2011 National Land Cover Database (NLCD) Impervious Surface Estimation layer. The NLCD is the source for the max_imperv variable that you filtered the image by in the previous lesson. Multiplying the cumulative OSP area in each parcel by this value states that you are 85 percent confident that a given parcel has at least "X" acres of eligible open space. Additionally, eligible OSP area per parcel is required to be reported in acres for the CRS program, so you'll convert square meters to acres.

  1. At the top of the Parcels_Zonal attribute table, click Add.

    Add field

    The Fields: Parcel_Zonal pane opens. In this editor, you can change the properties of the new field.

  2. In the last row (the new field), for Field Name, type ACRES. For Data Type, double-click the cell and choose Double.

    Edit new field

  3. On the ribbon, on the Fields tab, click Save.

    Save table edits

    The ACRES field is added to the table.

  4. Close the Fields: Parcels_Zonal table.

    The field is currently populated by the default null value. Next, you'll calculate the values for the field.

  5. In the Parcels_Zonal attribute table, right-click the ACRES field and choose Calculate Field.

    Calculate Field

    The Calculate Field tool opens in the Geoprocessing pane.

  6. On the Parameters tab, for ACRES =, type (or copy and paste) (!AREA! * 0.85) * 0.000247105. Click Run.

    ACRES expression

    The ACRES field is ultimately what the CRS reviewer will use to validate the eligible area of open space your community is claiming per parcel. If only a small portion of the parcel overlaps the floodplain area, only that overlapping area is eligible, not the entire parcel. To make your final analysis easier, you'll remove the smallest parcels.

  7. On the ribbon, on the Table View tab, in the Selection group, click Select By Attributes.

    Select By Attributes

  8. In the Geoprocessing pane, for Input Rows, confirm that Parcels_Zonal is selected. If necessary, for Selection type, choose New selection. Click New expression.

    New expression

  9. Use the drop-down menus to create the query ACRES Is Less Than 1.

    Select by query

  10. Click Run.

    The acreages that meet your query are now highlighted in the attribute table. These are the smallest pieces of land that are likely too small to provide many credits.

  11. On the ribbon, click the Table View tab. In the Selection group, click Delete.

    Delete small values

    Approximately 245 parcels remain.

  12. Close the attribute table.

Join the datasets

You now have all the information you need, but it is spread across three locations: your parcel dataset, the zonal table, and the PADUS_CRS_attrib table. The CRS review process requires that you report eligible OSP acreages per parcel. You ultimately need the OSP acreage values and the PADUS information included in the attribute table of your parcel dataset. To accomplish this, you will use multiple joins to integrate this data by a common attribute.

  1. In the Contents pane, right-click the Georgetown_Co_Parcels layer, point to Joins and Relates, and choose Add Join.

    Add Join

    The Add Join tool opens in the Geoprocessing pane.

  2. For Input Join Field, choose PARCEL_ID.
  3. For Join Table, choose Parcels_Zonal. For Output Join Field, choose PARCEL_ID.
    Note:

    You may receive a warning about the join field not being indexed. Indexes are useful if you need to query your data frequently, as they speed up searches in ArcGIS. For the purpose of this analysis, your data is more for presentation than continued use, so you won't index it.

    Add Join

  4. Click Run.
  5. Open the GeorgetownCo_Parcels attribute table and confirm that the Parcels_Zonal attributes have been added.

    There will be many null values because you created the Parcels_Zonal table by removing smaller parcels from the GeorgetownCo_Parcels layer. You want to keep all these records, because you have another dataset to join to the GeorgetownCo_Parcels layer.

  6. In the Geoprocessing pane, for Input Join Field, choose Parcels_Zonal.MAJORITY.
  7. For Join Table, choose PADUS_CRS_attrib. For Output Join Field, choose OBJECTID.

    Add Join

  8. Click Run.
  9. In the GeorgetownCo_Parcels attribute table, confirm that the PADUS_CRS_attrib fields were added.

    For the CRS review process, you only need to submit the parcels you claim are OSP eligible. Next, you'll filter these out.

  10. On the ribbon, on the Table View tab, click Select By Attributes.
  11. In the Geoprocessing pane, for Input Rows, confirm that GeorgetownCo_Parcels is chosen. Click New Expression.
  12. Create the expression MAJORITY is Not Null and press Enter.

    Select by Attribute query

  13. Click Run.

    The result is a comprehensive dataset of only parcels with at least 1 acre of likely eligible open space and all the attributes from the PADUS dataset.

  14. Below the attribute table, click the Show selected records button.

    Show selected records

    The data sorts so that the 245 records that fit your criteria are shown at the top of the table. Next, you'll export these results so you can symbolize them.

  15. In the Contents pane, right-click GeorgetownCo_Parcels, point to Data, and choose Export Features.
  16. Name the Output Feature ClassGeorgetownCo_OSP and click Run.

    When the Copy Features tool finishes, the new GeorgetownCo_OSP layer is added to the Contents pane.

  17. Close the attribute table and save the map.

In this lesson, you learned how to aggregate raster information into parcel zones and used a network of joins to create a comprehensive parcel data table that contains all the information required for the CRS review process. In the next lesson, you'll create a custom map to pair with the final parcel data table that your planner can submit to apply for CRS credits during the review process.