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Showing items 1 through 9 of 55.
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Library Resource
The influence of social others in private landowner decision-making has received limited attention despite growing support for peer-to-peer learning and landowner cooperative behavior. We applied social network analysis (SNA), a relatively novel methodology in the context of private forestry, to evaluate the influence of landowners' social networks on their forestry management decisions and as related to current policy arrangements in Wisconsin, USA.
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Library Resource
This paper examines the potential effects of urbanization on streamflow in Maine, USA, from 1950 to 2000. The study contrasts nine watersheds in southern Maine, which has seen steady urban growth over the study period, with nine rural watersheds from northern Maine. Historical population data and current land cover data are used to develop an urbanization score for each watershed. Trends in watershed urbanization over the study period are compared to trends in ecologically relevant streamflow characteristics.
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Library Resource
We examined macroinvertebrate community data from Missouri reference streams collected approximately 12 years apart to evaluate whether substantial changes in community metrics and/or taxonomic composition occurred over that period. We used analysis of variance to test whether metrics differed between years or between other variables and used non-metric multidimensional scaling to examine compositional differences among samples and the environmental variables that were most associated with these differences.
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Library Resource
A simple, efficient, and practical approach for detecting cloud and shadow areas in satellite imagery and restoring them with clean pixel values has been developed. Cloud and shadow areas are detected using spectral information from the blue, shortwave infrared, and thermal infrared bands of Landsat Thematic Mapper or Enhanced Thematic Mapper Plus imagery from two dates (a target image and a reference image).
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Library Resource
The U.S. Department of the Interior (DOI) manages one-fifth of the land in the United States, including public lands administered by the National Park Service, U.S. Fish and Wildlife Service, and Bureau of Land Management. Federal agencies have included public input in decision-making since the Administrative Procedure Act in 1946, with varying degrees of effectiveness. Recently, policy and reporting directives have broadened to include possibilities for collaborative conservation. Many disciplines are identifying this rise in collaboration as a new era of governance.
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Library Resource
National Agriculture Imagery Program (NAIP) orthophotography is a potentially useful data source for land cover classification in the United States due to its nationwide and generally cloud-free coverage, low cost to the public, frequent update interval, and high spatial resolution. Nevertheless, there are challenges when working with NAIP imagery, especially regarding varying viewing geometry, radiometric normalization, and calibration.
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Library Resource
Compact Airborne Spectrographic Imager (CASI) hyperspectral imagery was acquired over the Little Miami River Watershed in Ohio, USA, which was one of the largest hyperspectral image acquisitions. A hierarchical approach was employed using two different classification algorithms: ‘image object segmentation’ for level 1 and ‘spectral angle mapper’ (SAM) for level 2. This classification scheme was developed to overcome the spectral inseparability of urban and rural features and to deal with radiometric distortions due to cross-track illumination.
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Library Resource
A total of 458 in situ hyperspectral data were collected from 13 urban tree species in the City of Tampa, FL, USA using a spectrometer. The 13 species include 11 broadleaf and two conifer species. Three different techniques, segmented canonical discriminant analysis (CDA), segmented principal component analysis (PCA) and segmented stepwise discriminate analysis (SDA), were applied and compared for dimension reduction and feature extraction.
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Library Resource
We developed a set of generalized value categories and average relative marginal values using resource and valuation information collected at seven federal land management planning units in the USA. The categories and average values are intended to be used for rapid strategic wildland fire program planning or as foundation values for a more extended planning effort. To divide the original information into logical and statistically valid value categories, we used a k-means cluster analysis combined with expert knowledge of how each resource type is managed with respect to fire.
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Library Resource
The iterative and convergent nature of ensemble learning algorithms provides potential for improving classification of complex landscapes. This study performs land-cover classification in a heterogeneous Massachusetts landscape by comparing three ensemble learning techniques (bagging, boosting, and random forests) and a non-ensemble learning algorithm (classification trees) using multiple criteria related to algorithm and training data characteristics.
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