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Landscape Builder: software for the creation of initial landscapes for LANDIS from FIA dataAuthor(s): William Dijak
Source: Computational Ecology and Software. 3(2): 17-25.
Publication Series: Scientific Journal (JRNL)
Station: Northern Research Station
PDF: Download Publication (251.26 KB)
DescriptionI developed Landscape Builder to create spatially explicit landscapes as starting conditions for LANDIS Pro 7.0 and LANDIS II landscape forest simulation models from classified satellite imagery and Forest Inventory and Analysis (FIA) data collected over multiple years. LANDIS Pro and LANDIS II models project future landscapes by simulating tree growth, tree species succession, disease, insects, fire, wind, and management disturbance. Landscape Builder uses inventory plot attributes from the FIA inventory database, FIA unit map, National Forest type map, National Forest size class map, land cover map, and landform map to assign FIA plot attributes to raster pixels representing a real forest landscape. In addition to creating a detailed map of current (initial) forest landscape conditions, the software produces specific files required for use in LANDIS Pro 7.0 or LANDIS II format. Other tools include the ability to create a dominant species and age-class map from previously created LANDIS maps, a tool to create a dominant species and age-class map from a stand map and field plot data, and a tool to convert between Esri ascii rasters and Erdas file format types.
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CitationDijak, William. 2013. Landscape Builder: software for the creation of initial landscapes for LANDIS from FIA data. Computational Ecology and Software. 3(2): 17-25.
KeywordsLandscape Builder, forest inventory and analysis, LANDIS Pro, LANDIS II, Landscape HSImodels
- A large-scale forest landscape model incorporating multi-scale processes and utilizing forest inventory data
- An innovative computer design for modeling forest landscape change in very large spatial extents with fine resolutions
- A framework for evaluating forest landscape model predictions using empirical data and knowledge
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