Landcover Classification for Conservation Planning

Reason for Improved Landcover Classification: Habitat Modeling when data is not available for RSFs Identifying Ecological Communities Many Problems with Existing Classifications: One size fits all attitude Extent of area covered Disconnect between botanical and remote sensing classifications Lack of consistent standards End result: 1,000s of project specific landcover classifications They are usually incompatible with each other Existing classifications are manipulated or less than desired classifications are used

Montana GAP Landcover

Montana & Wyoming GAP

Wyoming Classification 8028 acres 80% lodgepole pine 20% subalpine meadow

Methods to Account for Differences Crosswalk Independent rating

Conservation Needs of a Landcover Classification (emphasis on wildlife modeling) Information and Scale Must Match the Needs of the Species Structure Adaptable across different scales Minimize source of errors Compatibility Easy to produce Cost effective

Vegetation Resources Inventory The B.C. Landcover Classification Scheme

Proposed Classification Scheme

Proposed Classification Scheme - continued

Ancillary Data Elevation Hydrology Landscape position Ancillary Data Ecoregion Slope Aspect Imagery Bands Indices PCA Level 1Level 2 Lifeform Level 3 Landscape position Level 4 Species Level 4 Structure Supervised Classification Fuzzy Classification Model Unsupervised Classification CART Proposed Methods Can be used for any resolution imagery Allows nesting of different types of imagery

Ecoregions Provinces Sections Sub-Sections

QuickBird Scene

Orthophoto Classification