4.5 Article

Reconstructing Historical Forest Cover and Land Use Dynamics in the Northeastern United States Using Geospatial Analysis and Airborne LiDAR

Journal

ANNALS OF THE AMERICAN ASSOCIATION OF GEOGRAPHERS
Volume 111, Issue 6, Pages 1656-1678

Publisher

ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
DOI: 10.1080/24694452.2020.1856640

Keywords

airborne LiDAR; Anthropocene; historical land use; human– land use dynamics

Categories

Funding

  1. Carville Earle award from the Historical Geography Specialty Group of the American Association of Geographers
  2. University of Connecticut Graduate School
  3. National Science Foundation [BCS-1654462]
  4. NOAA through the Cooperative Institute for Satellite Earth System Studies [NA19NES4320002]

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The northeastern United States experienced extensive deforestation from the 17th to 20th centuries, primarily for European agriculture, peaking in the mid-19th century. LiDAR analysis revealed historical land-use features, such as stone walls and charcoal hearths, associated with deforestation. The study shows that LiDAR is effective in reconstructing and quantifying historical forest cover distribution and extent.
The northeastern United States experienced extensive deforestation during the seventeenth through twentieth centuries primarily for European agriculture, which peaked in the mid-nineteenth century, and followed by widespread farmstead abandonment and reforestation. Analysis of airborne light detection and ranging (LiDAR) data has revealed thousands of historical land-use features with topographic signatures across the landscape under the region's now-dense forest canopy. This study investigates two different types of features-stone walls and relict charcoal hearths-both of which are associated with widespread deforestation in the region. Our results demonstrate that LiDAR is an effective tool in reconstructing and quantifying the distribution and magnitude of historical forest cover using these relict land use features as a reliable proxy. Furthermore, these methods allow for direct quantification of cumulative land clearing over time in each town, in addition to the extent, intensity, and spatial distribution of cleared land and forest cover.

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