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Comparative analysis of forest classification in forest management information databases in Michigan

Posted on:2006-12-22Degree:M.SType:Thesis
University:Michigan State UniversityCandidate:Subedi, NirmalFull Text:PDF
GTID:2453390008467020Subject:Agriculture
Abstract/Summary:
In Michigan, there are four primary sources of forest management information for public forest lands, namely a raster land-cover map (IFMAP), Forest Inventory and Analysis (FIA) plot-level information, Natural Resource Information System Field Sampled Vegetation (NRIS-FSVeg) for national forest lands, and Operations Inventory (OI) for state-owned forest lands. The objective of this study is to compare forest classifications between and among the forest management databases with FIA data as the reference location for comparison. Difference matrices were created between and among forest classifications and descriptive accuracy assessments for overall accuracy, producer's accuracy and user's accuracy were computed. The overall accuracy of IFMAP with FIA as reference was 63.6% for state forest lands and 64.8% for national forest lands. Overall accuracy of IFMAP with OI as a reference was 60.3% and IFMAP with NRIS-FSVeg as a reference was 68.3%. Overall accuracy of OI with FIA was 84.5% and NRIS-FSVeg with FIA was 82.2%. Overall accuracy of three-way forest classification was 54.8% and 58.5% for state and national forests lands, respectively. Kappa statistic, calculated from three approaches, ranged from 0.568 to 0.628 for state forest lands and 0.555 to 0.612 for national forest lands. This finding is consistent with a previous study of IFMAP.
Keywords/Search Tags:Forest, Information, IFMAP, Overall accuracy, FIA
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