Small scale photo probability sampling and vegetation classification in southeast Arizona as an ecological base for resource inventory Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/kh04dt49n

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  • Increasing demands on earth resources require the need to know how much resource is present. A new technology, which is developing partially with the support of the National Aeronautics and Space Administration, will help to inventory and monitor surface resources in a more comprehensive manner than previously possible. Research in southeastern Arizona for the past six years has been developing methodology that would permit the use of space and high altitude imagery for natural vegetation and related resource investigations. This paper reports on three meaningful research contributions in remote sensing of natural vegetation. They are (1) a natural vegetation classification suitable for remote sensing use, (2) a technique for objectively comparing space imagery for relative information content, and (3) a sample scheme for using small scale photography to identify and estimate areas of vegetation types. The natural vegetation classification contains 31 "vegetation types" that were developed for a 3, 200 square mile area. The types are ecologically determined from association tables, and are, therefore, suitable for use in remote sensing applications. This is possible primarily because the types are related to photo identifiable landform variables. The classification is suitable for generalized levels of land use planning, but this was not tested. Three types of space imagery were evaluated for apparent photographic information content. The technique avoided subject-image relationships by concentrating directly on image characteristics. The approach, coined "image groupability", should be a worthwhile contribution to the larger problem of comparative imagery interpretations. An example demonstrates an approach to objective photo stratification based on image groupability results. The third accomplishment involved design and execution of a comparative two stage sampling scheme to estimate kind and extent of vegetation types. The comparison was between two space photos substituted at the first sampling stage. At the second stage (high altitude photography) potential secondary sampling units were categorized by image similarity rather than by the more complicated process of ground subject interpretations. Efficiency gains from space photo stratification were not substantial; however, the sample scheme was effective. Furthermore, clustering, a space photo sampling artifact, saved an estimated 32-35 percent in "working time" expenses when making ground checks by helicopter.
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