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  • Imputed Forest Composition Map for New England Screened by Species Range Boundaries 2001-2006
  • Duveneck, Matthew
  • Thompson, Jonathan
  • Wilson, B. Tyler
  • 2015
  • Initializing forest landscape models (FLMs) to simulate changes in tree species composition requires accurate fine-scale forest attribute information mapped contiguously over large areas. Nearest-neighbor imputation maps have high potential for use as the initial condition within FLMs, but the tendency for field plots to be imputed over large geographical distances results in species frequently mapped outside of their home ranges, which is problematic. We developed an approach for evaluating and selecting field plots for imputation based on their similarity in feature-space, their species composition, and their geographical distance between source and imputation to produce a map that is appropriate for initializing an FLM. We applied this approach to map 13m ha of forest throughout the six New England states (Rhode Island, Connecticut, Massachusetts, New Hampshire, Vermont, and Maine). The map itself is a .img raster file of FIA plot CN numbers. To access FIA data from this map, one has to link the mapcodes in this map to FIA data supplied by USDA FIA database (http://apps.fs.fed.us/fiadb-downloads/datamart.html). Due to plot confidentiality and integrity concerns, pixels containing FIA plots were always assigned to some other plot than the actual one found there.
  • N: 47.4      S: 40.9      E: -66.9      W: -74.0
  • This dataset is released to the public and may be freely downloaded. Please keep the designated Contact person informed of any plans to use the dataset. Consultation or collaboration with the original investigators is strongly encouraged. Publications and data products that make use of the dataset must include proper acknowledgement. For more information on LTER Network data access and use policies, please see: http://www.lternet.edu/data/netpolicy.html.
  • doi:10.6073/pasta/2962d7b58045b935821115cd9a2e677a
  • https://pasta.lternet.edu/package/eml/knb-lter-hfr/234/2
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