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Pb1679 Forest - A - Syst: Self-Assessment To Prioritize Your Forest Uses, The University Of Tennessee Agricultural Extension Service
Pb1679 Forest - A - Syst: Self-Assessment To Prioritize Your Forest Uses, The University Of Tennessee Agricultural Extension Service
Forestry, Trees, and Timber
You are unique. The title “Forest Landowner” is one not held by many Tennesseans. Your ownership carries with it a sense of treasure, of enjoyment, of wildness. But it’s also a privilege, one that imparts responsibility, one that can be observed and one that increasingly can be measured.
If you were to be judged on your forestry practices, how would you score? Would you even know which parameters to assess or what questions to ask? Which of these forest uses aesthetics, recreation, soil, timber, water, wildlife—are more important? Have you ever intelligently, and intentionally, began a planning process for your …
Pb1756 The All Season Pocket Guide To Identifying Common Tennessee Trees, The University Of Tennessee Agricultural Extension Service
Pb1756 The All Season Pocket Guide To Identifying Common Tennessee Trees, The University Of Tennessee Agricultural Extension Service
Forestry, Trees, and Timber
This booklet was prepared by professional foresters to help you identify Tennessee’s most common trees. It is designed to go to the woods with you (where it is needed) by comfortably riding in your back pocket, pack or cruiser’s jacket. Enjoy!
Standardized, Cost-Effective, And Repeatable Remote Sensing Methodology To Quantify Forested Resources In Texas, Daniel Unger, James Kroll, I-Kuai Hung, Jeffrey M. Williams, Dean W. Coble
Standardized, Cost-Effective, And Repeatable Remote Sensing Methodology To Quantify Forested Resources In Texas, Daniel Unger, James Kroll, I-Kuai Hung, Jeffrey M. Williams, Dean W. Coble
Faculty Publications
A standardized remote sensing methodology was evaluated for its use in quantifying the forested resources of the state of Texas in a timely and cost-effective manner. Landsat data from 2002 were used to create a land cover base map encompassing a four-county study area in East Texas. Site-specific and non-site-specific accuracy assessments of the classified map indicate that overall the 2002 base map accuracy of 72.78% was within acceptable remote sensing standards for Landsat data and that forest cover types derived from 2002, 1987, and 1980 Landsat data were within 4.4, 0.5, and 7.4% agreement with Forest Inventory and Analysis …