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Data - Forest harvest patterns on private lands in the Cascade Mountains, Washington, USA


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Soulard, C.E., Walker, J.J., and Griffith, G.E., 2017, Data - Forest harvest patterns on private lands in the Cascade Mountains, Washington, USA: U.S. Geological Survey data release,


Forests in Washington State generate substantial economic revenue from commercial timber harvesting on private lands. To investigate the rates, causes, and spatial and temporal patterns of forest harvest on private tracts throughout the central Cascade Mountain area, we relied on a new generation of annual land-use/land-cover (LULC) products created from the application of the Continuous Change Detection and Classification (CCDC) algorithm to Landsat satellite imagery collected from 1985 to 2014. We calculated metrics of landscape pattern using patches of intact and harvested forest patches identified in each annual layer to identify changes throughout the time series. Patch dynamics revealed four distinct eras of logging trends that [...]

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The objectives of this study are to characterize and interpret the patterns of forest disturbances on private lands in the Cascade Mountains, Washington using LCMAP land cover data for the period 1985-2014. Our hypotheses are that the high temporal and spatial resolution of the dataset will allow us to (1) detect and track short-term fluctuations in forest land cover conversion rates and patterns that can be linked to contemporaneous driving forces, and (2) identify the key biophysical parameters that influence forest conversion during periods of consistent timber demand. Within broad ecoregion boundaries, our focus is on timber harvest on private lands given their more elastic response to driving factors compared to the constrained logging practices on federal and state lands. Our overall intent is to determine the facility of the annual LCMAP products for capturing and providing insight into forest cover dynamics, with the goal of extending the analyses to broad-scale investigations of diverse land cover classes across the U.S.


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Annual patch statistics and samples of presence and absence used in the multiple logistic regression are provided on USGS Sciencebase. The two machine readable comma-separated values (CSV) files presented in this USGS Data Release are intended to supplement a journal article on the same topic. The data have led to the final conclusions made in the manuscript.

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DOI doi:10.5066/F7X63KWW

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