R
Rutherford V. Platt
Researcher at Gettysburg College
Publications - 21
Citations - 733
Rutherford V. Platt is an academic researcher from Gettysburg College. The author has contributed to research in topics: Land cover & Wildland–urban interface. The author has an hindex of 12, co-authored 21 publications receiving 661 citations. Previous affiliations of Rutherford V. Platt include University of Kentucky & University of Colorado Boulder.
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Journal ArticleDOI
An Evaluation of an Object-Oriented Paradigm for Land Use/Land Cover Classification∗
TL;DR: It is found that the combination of segmentation into image objects, the nearest neighbor classifier, and integration of expert knowledge yields substantially improved classification accuracy for the scene compared to a traditional pixel-based method.
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Historical, Observed, and Modeled Wildfire Severity in Montane Forests of the Colorado Front Range
Rosemary L. Sherriff,Rutherford V. Platt,Thomas T. Veblen,Tania Schoennagel,Meredith H. Gartner +4 more
TL;DR: Based on present-day fuels, predicted fire behavior under extreme fire weather continues to indicate a mixed-severity fire regime throughout most of the montane forest zone.
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A comparison of AVIRIS and Landsat for land use classification at the urban fringe
TL;DR: In this paper, the authors tested whether AVIRIS data allowed for improved land use classification over synthetic Landsat ETM+ data for a location on the urban-rural fringe of Colorado.
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Recruitment facilitation and spatial pattern formation in soft‐bottom mussel beds
John A. Commito,John A. Commito,Ann E. Commito,Rutherford V. Platt,Benjamin M. Grupe,Wendy E. D. Piniak,Natasha J. Gownaris,Kyle A. Reeves,Allison M. Vissichelli +8 more
TL;DR: A simple lattice model, field sampling, and field and laboratory experiments were used to examine facilitation of recruitment and its role in the development of power-law spatial patterns observed in Maine, USA, soft-bottom mussel beds and demonstrated that recruitment facilitation produces power- law spatial structure similar to that in natural beds.
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An object-oriented approach to assessing changes in tree cover in the Colorado Front Range 1938–1999
TL;DR: In this paper, the authors used object-oriented image analysis to compare change in tree cover delineated from historical and modern imagery, and found that the highest increase in tree density is in areas characterized by low initial density, south-facing slopes, low elevations, and ponderosa pine dominance.