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Accession Number
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PB2013-100702
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Title
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Machine-Learning Approach to Change Detection Using Multi-Scale Imagery.
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Publication Date
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2012
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Media Count
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10p
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Personal Author
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B. Maurizi C. Fischer J. Suero L. M. Levien P. Roffers X. Huang
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Abstract
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The USDA Forest Service and the California Department of Forestry and Fire Protection are collaborating on a statewide change detection program to identify landcover change across all ownerships within five-year time periods. This program uses Landsat Thematic Mapper satellite imagery to derive landcover change and aid in assessing its cause. Landscape changes are initially detected using a multi-temporal Kauth-Thomas transform. Unsupervised classification of the transformed imagery creates a preliminary landscape-level change map portraying change classes with multiple levels of vegetation increase, decrease, and no change. Using a stratified random sampling scheme, this preliminary change map facilitates selection of field sites for collecting vegetation canopy cover measurements. Ground truth for the classifier is obtained by estimating canopy cover change over the 5-year timeframe using color-IR digital photos, digital orthophoto quads, and aerial photography. Canopy cover estimates from the second date of photography are calibrated using transect measurements of canopy cover from a sample of field sites. Attributes such as species and vegetative cover are also noted. A machine learning classifier approach is then employed. The classifier uses an inductive learning algorithm to generate production rules from training data, including the transformed change data and other ancillary data layers. The resultant knowledge base is then used by an expert classifier to produce classes of crown closure change. Approximately half of the field.
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Keywords
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Detection
Image processing
Monitor changes
Monitoring
Remote sensing
Satellite imagery
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Source Agency
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Forest Service Engineering Staff Washington DC
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NTIS Subject Category
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84G - Unmanned Spacecraft
63 - Detection & Countermeasures
46C - Optics & Lasers
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Corporate Author
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California Dept. of Forestry and Fire Protection, Sacramento.
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Document Type
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Technical report
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Title Note
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N/A
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NTIS Issue Number
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1307
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Contract Number
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N/A
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