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Accurate characterization of forest canopy cover from satellite imagery hinges on the development of a model that considers the level of detail achieved by field methods. With the improved precision of both optical sensors and various spatial techniques, models built to extract forest structure attributes have become increasingly robust, yet

Accurate characterization of forest canopy cover from satellite imagery hinges on the development of a model that considers the level of detail achieved by field methods. With the improved precision of both optical sensors and various spatial techniques, models built to extract forest structure attributes have become increasingly robust, yet many still fail to address some of the most important characteristics of a forest stand's intricate make-up. The objective of this study, therefore, was to address canopy cover from the ground, up. To assess canopy cover in the field, a vertical densitometer was used to acquire a total of 2,160 percent-cover readings from 30 randomly located triangular plots within a 6.94 km2 study area in the central highlands of the Bradshaw Ranger District, Prescott National Forest, Arizona. Categorized by species with the largest overall percentage of cover observations (Pinus ponderosa, Populus tremuloides, and Quercus gambelii), three datasets were created to assess the predictability of coniferous, deciduous, and mixed (coniferous and deciduous) canopies. Landsat-TM 5 imagery was processed using six spectral enhancement algorithms (PCA, TCT, NDVI, EVI, RVI, SAVI) and three local windows (3x3, 5x5, 7x7) to extract and assess the various ways in which these data were expressed in the imagery, and from those expressions, develop a model that predicted percent-cover for the entire study area. Generally, modeled cover estimates exceeded actual cover, over predicting percent-cover by a margin of 9-13%. Models predicted percent-cover more accurately when treated with a 3x3 local window than those treated with 5x5 and 7x7 local windows. In addition, the performance of models defined by the principal components of three vegetation indices (NDVI, EVI, RVI) were superior to those defined by the principal components of all four (NDVI, EVI, RVI, SAVI), as well as the principal and tasseled cap components of all multispectral bands (bands 123457). Models designed to predict mixed and coniferous percent-cover were more accurate than deciduous models.
ContributorsSchirmang, Tracy Lynn (Author) / Myint, Soe W (Thesis advisor) / Fall, Patricia L. (Thesis advisor) / Brazel, Anthony J. (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Use of off-highway vehicles (OHV) in natural landscapes is a popular outdoor activity around the world. Rapid-growing OHV activity causes impacts on vegetation and land cover within these landscapes and can be an important factor in land degradation and ecosystem change. The Algodones Dunes in southeastern California is one of

Use of off-highway vehicles (OHV) in natural landscapes is a popular outdoor activity around the world. Rapid-growing OHV activity causes impacts on vegetation and land cover within these landscapes and can be an important factor in land degradation and ecosystem change. The Algodones Dunes in southeastern California is one of the largest inland sand dune complexes in the United States and hosts many endangered species. This study examines changes in land cover and OHV activity within two OHV active sites in comparison to an adjoined protected area. The study also investigates potential associations between land cover changes, climate trends, and OHV activity over recent decades. Time-series analysis was used to investigate the spatial-temporal changes and trends in the land cover in the Algodones Dunes from 2001 to 2016. In addition, high-resolution aerial photographs were analyzed to determine spatial patterns of OHV usage in comparison to visitor estimation collected by the Bureau of Land Management and observed changes in land cover composition between the control site and OHVs areas.

A decreasing trend in Normalized Difference Vegetation Index over time indicates a decline in the amount of vegetation cover, which corresponds with an increasing trend in albedo and land surface temperature. Results also show a substantial difference in land cover between the control site and OHVs areas, which typically have a lower amount of vegetation cover, higher exposed sand surface, and increased anthropogenic features. Both climatic variations and OHV activity are statistically associated with land cover change in the dune field, although distinct causal mechanisms for the observed declines in vegetation cover could not be separated. The persistence of drought could inhibit vegetation growth and germination that, in turn, would hinder vegetation recovery in OHV areas. Meanwhile, repeated OHV driving has direct physical impacts on vegetation and landscape morphology, such as canopy destruction, root exposure, and increased aeolian sand transport. Active ecosystem protection and restoration is recommended to mitigate the response of declining vegetation cover and habitat loss to the impacts of OHV activity and climatic variability and allow natural recovery of re-establishement of nebkha dune ecosystems in the Algodones Dunes.
ContributorsCheung, Suet Yi (Author) / Walker, Ian J (Thesis advisor) / Myint, Soe W (Committee member) / Dorn, Ronald I. (Committee member) / Arizona State University (Publisher)
Created2018