Maryland/Wetlands Import

Like this tower, this page is under construction.

Situated on the Upper Chesapeake Bay, much of Maryland borders the large tidal estuary that is lined with many bays, coves, and tidal rivers. Wetlands cover 10% of the Maryland's land surface, with some coastal counties having over 25% wetland coverage.

The state defines a wetland as areas, "that hold water for significant periods during the year and are characterized by anaerobic (low oxygen) conditions favoring the growth of specific plant species and the formation of specific soil types."

Wetlands are an essential component of the coastal landscape as protected resources and barriers to transportation. Despite its importance, wetland mapping on OpenStreetMap is limited. As of January 2017, there are only 37.5 square miles of wetlands mapped in the state. This figure represents a mere 3% of the total wetland area statewide.

Wetlands may be difficult to add to the map. They are certainly tedious to trace, with edges usually overlapping with an equally complex water feature. The edges can be difficult to spot on aerial photography without special infrared filtered imagery and a trained eye.

Wetlands are great in number, critical, and hard to map. These factors provide the basis for a useful import process, converting geospatial wetland data to OpenStreetMap features.

ETL Process

Blackwater National Wildlife Refuge is located in Maryland

The data must undergo an ETL (extract, transform, load) to get the data from the source, a government GIS file, to the target, the OSM database. The process is broken down into three phases, extraction, transformation, and loading.

Extraction

The data reside on the Maryland DoIT GIS Data Portal and are the product of Maryland's Department of Natural Resources. Maryland DNR data was the source for the Maryland State Parks import, and the public domain license is identical.

The data are extracted by downloading the shapefile from the website. The wetland data represent both surveyed wetlands and wetlands traced from aerial imagery. The data was first published in 1995 and has been updated periodically.

For ease of manipulation during the following processes, the extracted shapefile is loaded into a working file geodatabase without any transformation.

Transformation

Transforming the data from data involves modification for the attribution tables for the data to fit the OpenStreetMap tagging schema, and modifying the geometry to comply with the best common practices for OSM. Preprocessing is accomplished using the Esri ArcGIS for Desktop software, while post-processing occurs in JOSM.

Attribute Preprocessing

The attribution of the data is based on published Classification of Wetlands and Deepwater Habitats of the United States (2013, PDF) based on the de facto standard published by Cowardin et al in 1979. The Cowardin system is the federal standard for wetland classification used in the National Wetlands Inventory. The system uses an alphanumeric code to represent a wetlands characteristics. The codes are concatenated into a single string and are sometimes nested with other classifications. While useful for wetland inventory and research, the 500+ classification possibilities are outside of the scope of usefulness for the OpenStreetMap project (which has around ten wetland classifications in common use).

It is necessary to generalize the classifications for OSM. The United States Fish and Wildlife Service has a simple classification scheme that is based on the first few characters of the full Cowardin classification code, that this project will replicate.

Using ArcMap, a few new fields are added to the data. The fields include a "MapCode", a description, and a Cowardin identifier. Using python, the MapCode is populated using the Field Calculator. The python code matches the first few letters according the USFWS Simplified schema. A similar process is used to populate the description and Cowardin type. The generalization script ignored 8,342 rows of data (around 6%) in the data table most of which were farmed wetland.

The following table shows the generalized Cowardin wetland types and their OSM equivalent.

Wetland Type	MapCode	cowardin:description	wetland:description	OSM Natural	OSM Detail 1
Estuarine Deepwater	E1	Estuarine subtidal water and wetland	Open water estuary, bay, sound, open ocean	natural=water	tidal=yes
Marine Deepwater	M1	Marine subtidal water and wetland	Open water estuary, bay, sound, open ocean	natural=water	tidal=yes
Estuarine wetland	E2	Estuarine intertidal wetland	Vegetated and non-vegetated brackish and saltwater marsh, shrubs, beach, bar, shoal or flat	natural=wetland	wetland=saltmarsh
Marine wetland	M2	Marine intertidal wetland	Vegetated and non-vegetated brackish and saltwater marsh, shrubs, beach, bar, shoal or flat	natural=wetland	wetland=saltmarsh
Lakes	L	Lacustrine wetland and deepwater	Lake or reservoir basin	natural=water	water=lake
Freshwater Emergent wetland	PEM	Palustrine emergent	Herbaceous march, fen, swale and wet meadow	natural=wetland	wetland=marsh
Freshwater Shrub wetland	PSS	Palustrine shrub	Forested swamp or wetland shrub bog or wetland	natural=wetland	wetland=bog
Freshwater Forested wetland	PFO	Palustrine forested	Forested swamp or wetland shrub bog or wetland	natural=wetland	wetland=swamp
Freshwater pond	PUB	Palustrine unconsolidated bottom	Pond	natural=water	water=pond
Freshwater pond	PAB	Palustrine aquatic bed	Pond	natural=water	water=pond
Riverine	R	Riverine wetland and deepwater	River or stream channel	natural=water	water=pond

Geometry Preprocessing

The data requires filtering and geoprocessing to modify the geometry into functional OSM features. ArcMap is used extensively for the geometry modifications.

The data are first filtered using a definition query. The query filters out and MapCodes that are not in the list above. These filtered lands are typically classified as uplands, which is just any land that isn't wetland, or a typ

There are a three primary geoprocessing steps: Integrate, Dissolve, Simplify Polygon.

License

Public Domain.