This reference contains the imagery data used in the completion of the baseline vegetation inventory project for the NPS park unit. Orthophotos, raw imagery, and scanned aerial photos are common files held here. On April 28, 2003, William Frament, USDA Forest Service (Northeastern Area State and Private Forestry, Durham, NH) acquired color infrared 1:8,000 scale (1 inch = 666.7 feet) aerial photography for a digital orthophoto mosaic of ROVA; however, the photography was incomplete in that it only covered Vanderbilt Mansion NHS. The following spring (May 12, 2004) during leaf-on conditions, Mr. Frament acquired a complete set of aerial photography for the four properties that currently comprise ROVA (including RFF). The mosaic was produced from 47 color infrared aerial photographs and published on September 24, 2004.

This reference contains the imagery data used in the completion of the baseline vegetation inventory project for the NPS park unit. Orthophotos, raw imagery, and scanned aerial photos are common files held here. NISI Photo dates: 10/24/2000, Scale: 1:12000, size: 948ac The CIR aerial photographs in transparency format were scanned at 600 dpi (42 μm) using an Epson Expression 10000XL flatbed scanner.

This reference contains the imagery data used in the completion of the baseline vegetation inventory project for the NPS park unit. Orthophotos, raw imagery, and scanned aerial photos are common files held here. NISI Photo dates: 10/24/2000, Scale: 1:12000, size: 948ac The CIR aerial photographs in transparency format were scanned at 600 dpi (42 μm) using an Epson Expression 10000XL flatbed scanner.

This reference contains the imagery data used in the completion of the baseline vegetation inventory project for the NPS park unit. Orthophotos, raw imagery, and scanned aerial photos are common files held here. Aerial photography was acquired from the USFS covering the entire project area. Photographs were acquired on July 03 and 07 and August 24, 1996. True color photographs were taken at 1:24,000 (1"=2,000') scale and printed as 9"x9" contact glass positives. For interpretation purposes, these were enlarged to 18"x18" and an approximately 1:12,000 scale. To economize, every other aerial photo was enlarged. Overlap for the 9"x9" photos is approximately 50-60% (approximately 20% for every other 18"x18" photo) and sidelap between flight lines is approximately 20-30%.

This reference contains the imagery data used in the completion of the baseline vegetation inventory project for the NPS park unit. Orthophotos, raw imagery, and scanned aerial photos are common files held here. Aerial photography was acquired from the USFS covering the entire project area. Photographs were acquired on July 03 and 07 and August 24, 1996. True color photographs were taken at 1:24,000 (1"=2,000') scale and printed as 9"x9" contact glass positives. For interpretation purposes, these were enlarged to 18"x18" and an approximately 1:12,000 scale. To economize, every other aerial photo was enlarged. Overlap for the 9"x9" photos is approximately 50-60% (approximately 20% for every other 18"x18" photo) and sidelap between flight lines is approximately 20-30%.

This reference contains the imagery data used in the completion of the baseline vegetation inventory project for the NPS park unit. Orthophotos, raw imagery, and scanned aerial photos are common files held here. Base Imagery used for mapping (acquired by MoRAP): April 2010, SPOT, color infrared, leaf-off, 10 m 2009 NAIP, leaf-on, true color, 1 m Additional Imagery acquired and viewed by MoRAP: 2012, leaf-on, Bing Imagery

This reference contains the imagery data used in the completion of the baseline vegetation inventory project for the NPS park unit. Orthophotos, raw imagery, and scanned aerial photos are common files held here. Base Imagery used for mapping (acquired by MoRAP): April 2010, SPOT, color infrared, leaf-off, 10 m 2009 NAIP, leaf-on, true color, 1 m Additional Imagery acquired and viewed by MoRAP: 2012, leaf-on, Bing Imagery

This reference contains the imagery data used in the completion of the baseline vegetation inventory project for the NPS park unit. Orthophotos, raw imagery, and scanned aerial photos are common files held here. Ecologists at the State Geological and Natural History Survey of Connecticut completed photointerpretation based on a review of Connecticut DEP 2001 black and white, 1:12,000 aerial photographs and field reconnaissance guided by NPS staff.

This reference contains the imagery data used in the completion of the baseline vegetation inventory project for the NPS park unit. Orthophotos, raw imagery, and scanned aerial photos are common files held here. Ecologists at the State Geological and Natural History Survey of Connecticut completed photointerpretation based on a review of Connecticut DEP 2001 black and white, 1:12,000 aerial photographs and field reconnaissance guided by NPS staff.

This reference contains the imagery data used in the completion of the baseline vegetation inventory project for the NPS park unit. Orthophotos, raw imagery, and scanned aerial photos are common files held here. Several imagery datasets were available for the mapping project. Table 7 lists the types of imagery used in the LEWI mapping project, including the date the imagery was produced and the source of the data. Landsat satellite imagery was acquired from GLOVIS (http://glovis.usgs.gov/). SPOT 4 imagery was downloaded from EarthExplorer (http://edcsns17.cr.usgs.gov/NewEarthExplorer/). Landsat imagery at 30 m resolution consists of 7 bands: 3 visible, 2 mid-infrared, 1 shortwave infrared and 1 thermal band. SPOT 4 imagery consists of 4 bands: 2 visible (10m), 1 shortwave infrared (10m), and 1 mid-infrared (20 m). Imagery used was from the summer 2008 (Landsat) and late fall 2010 (SPOT 4) to provide a phenological contrast useful in differentiating vegetation types. Every homogeneous vegetation type has a unique reflectance which is referred to as a signature. This unique signature is often more apparent and distinct in the infrared wavelengths outside of the human eye visible spectrum, enabling a remote sensing expert to use these unique satellite signature snapshots in time to differentiate various vegetation types.