2022 Natural Resources Inventory

2022 Natural Resources Inventory Executive Summaryopens PDF file

2022 Natural Resources Inventory Reportopens PDF file

2022 Natural Resources Inventory Interactive Map

The 2022 Natural Resources Inventory (NRI) uses aerial imagery and mapping to identify areas of local and regional importance. These important areas include landscape features like streams, trees, buildings, roads, and plants. As you look across the city, you may see houses surrounded by grass, trees, streets, and sidewalks. Each landscape feature has an electromagnetic signature. Using these signatures, Geographic Information Systems experts can identify objects across the landscape from aerial imagery. 

The City hired Biohabitats and Davey Resource Group to classify landscape features, analyze landscape changes from the 2007 NRI, and write the 2022 NRI report. The study area encompasses the City of Columbia limits and most of the Columbia Metropolitan Area. City staff added lands surrounding the airport, south of town because of ecological importance, and northeast of Columbia, where staff expects development to expand quickly. 

The six basic land cover classes in this natural resources inventory are: 

  • Forest
  • Streams and Wetlands
  • Grassland
  • Cropland
  • Impervious (e.g., roads, buildings, etc.)
  • Bare Ground (e.g., bare soil, scant vegetation) 

Within some classes, there are subclasses to analyze land cover further. For example, the user can explore forests by age category or tree type (e.g., deciduous vs. coniferous). Some landscape feature signatures are distinct and easy to identify, while others are very similar and may be more challenging to distinguish. This misclassification is the case for some croplands, such as hay fields classified as grasslands. GIS Analysts viewed the imagery following the computer model to correct misidentified classes. For more information on how the Davey Resource Group collected and analyzed data, please refer to Appendix lopens PDF file

The 2022 NRI Report summarizes the results for each land class and provides context for possible future applications. Read the whole report here or explore the data through this interactive map

*NRI data support planning and policy-level analysis and are not designed for accurate parcel-level mapping.