Maryland, USA mountains, coastlines, streams, and lakes in a dual or single color topographic and hydrographic map! All topographic states in the USA of Plastic collection are at 1:2500000 scale and interlock with each other similar to a puzzle.
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Recommended to download only the model file name you need for faster download and less storage usage.
STATE-ESCALING-EXTRUDER-STYLE-REVISION-PIECE##.3mf │ │ └────────VARIANT────────┘
Definition | Meaning |
---|---|
STATE | State Abbreviation |
ESCALING | Linear or Square Root (sqrt) elevation scaling. |
EXTRUDER | Dual or Single color (extrusion) model |
STYLE* (optional) | Model special style or subregion. STYLE is only present when the model file is a special style or the model is exclusive to a special subregion. |
REVISION | Revision number. See release notes for the latest improvements. |
PIECE##† (optional) | Interlocking pre-cut piece ## sized for 180 mm x 180 mm bed. |
*Default STYLE is water features model located over submerged low lying lands. This submerged land may be visible when water layers are printed with a transparent filament. Default style minimizes usage of secondary (water) filament color. transparent style has water model features that extend all the way through the land for maximum light transmission when used with glow and transparent filaments.
†If multi-part files are not present, I have not created interlocking models for this state yet. Follow me and comment with your request to get future additions and updates.
Need a custom map modeled or a commercial license? Let's talk! (maps@ansonliu.com)
USAofPlastic topographic map project uses data from NASA SRTM V3.0, USGS GMTED2010, USGS HYDRO1K based on 1996 GTOPO30, HydroLAKES, and USCB TIGER/Line.
Tools used include QGIS, GDAL, GRASSGIS, TouchTerrain, Anaconda, GeoPandas, Matplotlib, Blender. Please support open data and FOSS software.
Tags topography dual usa hydrography usaofplastic transparent topographic hydrographic rivers lakes streams mountains forests canyons valleys wall map cartography gis dem