Nongame Conservation Section Greg Krakow and NCS staff

March 1, 2017 Nongame Conservation Section

Our Mission: Conserving Nongame Wildlife Nongame means animals not legally hunted, fished or trapped, as well as rare plants and natural habitats Core Areas • Rare Species Surveys and Monitoring • Environmental review • Habitat Restoration • Land Acquisition/Easements • Conservation Planning • Education and Outreach

Work Flow

Enter Data Process Data Present Data

Spatial SQL Spatial databases work with Spatial Features to: • Measure length, area, distance • Modify creating buffers, merges, intersections, etc. • Observe spatial relationships • Create new geometries • Return specific information about a feature and associated attributes. • Aggregate spatial and non-spatial data PostGIS, Carto and Spatialite

• PostGIS is a full feature multiuser, networkable spatial GIS database • Carto as feature rich, open source, tool that fully supports PostGIS • Spatialite is a single user, single computer that implements spatial SQL in a similar way as PostGIS Enter Data Network of independent agencies collecting and analyzing data for biodiversity conservation Biotics 5 is a web based GIS platform developed by NatureServe for managing biodiversity conservation data.

Process Data How I use Spatialite

• Convert table structure: Makes it easy to assemble disparate feature data sets with various types of feature types and CRS into one data set. • Clean up and organize data • Transform data • Aggregate data using spatial aggregation features such as spatial union (st_union).

Cleanup, convert and format ~5.5 million streams incoming spatial ~500 sampling sites data

Get nearest stream to each With SpatiaLite kNN (K- collection Nearest Neighbor) indexing point it took only 30 seconds. Aggregate data by most recent range of years Format some data Aggregate some data

Traditional county range map

Quercus oglethorpensis Oglethorpe Oak

. . . with digital interactive maps we can make this data available online.

What can you do? Understand data acquisition needs

• Find locations to target for field surveys • Understanding missing database information – In people’s heads – In institutions – From survey records • Possible new locations for elements • Where elements have declined or are potentially extirpated (when map units are adequately surveyed)

How was all this done? Things tried but not used

Manual: • ArcGIS Spatial Join in Analysis tools Automation: • Arc GIS Model Builder • Python & ArcPy • Python & QGIS • Python & OGR Preparing the data

Biotics5 Biotics5 Oracle View Shapefile Select and format attribute EO polygons and formatted EOs records categories attribute values

Shapefiles County, Watershed, Ecoregion, hexagon, quarter quad Python/Spatialite Carto PostGIS SQL join & aggregate EO Spatial Database info with range map units on the web CSV text files EO age attributes and range map unit names Still use Python as “glue” language but prefer Spatial SQL for processing vector data

The End

Spatial SQL Thank you!