This data set consists of land cover derived from high resolution orthoimagery, LiDAR data and ancillary data sources such as SSURGO and National Wetlands Inventory, and was analyzed according to the Coastal Change Analysis Program (C-CAP) protocol. This data set was developed through a collaboration between the Old Woman Creek, Ohio, National Estuarine Research Reserve and the NOAA Office for Coastal Management.

This dataset represents land cover for the San Lorenzo River basin in Santa Cruz County, California derived from high resolution imagery. The land cover features in the imagery were classified to the Coastal Change Analysis Program (C-CAP) classification scheme. Land cover data was derived through a combination of image processing methods including image segmentation and rule-based techniques available from the eCognition software package, and more traditional "cluster-busting" methods.

This data set contains the 2007 and 2012 classifications of St. Croix and can be used to analyze change. This data set utilized CIR imagery captured from Microsoft UltraCAM X (2011 flights) and Z/I Imaging DMC-II 230 (2012 flights) digital sensors and the 2007 high resolution St. Croix C-CAP dataset which were analyzed according to the Coastal Change Analysis Program (C-CAP) protocol to determine land cover.

This data set consists of land cover derived from high resolution imagery and was analyzed according to the Coastal Change Analysis Program (C-CAP) protocol to determine land cover. This data set utilized CIR imagery captured from Microsoft UltraCAM X (2011 flights) and Z/I Imaging DMC-II 230 (2012 flights) digital sensors. The land cover is based on the 2007 high resolution St. Croix C-CAP dataset. Changes were identified using aerial photo interpretation of the 2007 dataset against the 2011-2012 imagery.

This data set contains the 2007 and 2012 classifications of St. John and can be used to analyze change. This data set utilized CIR imagery captured from a Z/I Imaging DMC-II 230 (2012 flights) digital sensor and the 2007 high resolution St. John C-CAP dataset which were analyzed according to the Coastal Change Analysis Program (C-CAP) protocol to determine land cover.

This data set consists of land cover derived from high resolution imagery and was analyzed according to the Coastal Change Analysis Program (C-CAP) protocol to determine land cover. This data set utilized CIR imagery captured from a Z/I Imaging DMC-II 230 (2012 flights) digital sensor. The land cover is based on the 2007 high resolution St. John C-CAP dataset. Changes were identified using aerial photo interpretation of the 2007 dataset against the 2012 imagery.

This data set contains the 2007 and 2012 classifications of St. Thomas and can be used to analyze change. This data set utilized CIR imagery captured from Microsoft UltraCAM X (2010-11 flights) and Z/I Imaging DMC-II 230 (2012 flights) digital sensors and the 2007 high resolution St. Thomas C-CAP dataset which were analyzed according to the Coastal Change Analysis Program (C-CAP) protocol to determine land cover.

This data set consists of land cover derived from high resolution imagery and was analyzed according to the Coastal Change Analysis Program (C-CAP) protocol to determine land cover. This data set utilized CIR imagery captured from Microsoft UltraCAM X (2010-11 flights) and Z/I Imaging DMC-II 230 (2012 flights) digital sensors. The land cover is based on the 2007 high resolution St. Thomas C-CAP dataset. Changes were identified using aerial photo interpretation of the 2007 dataset against the 2010-2012 imagery.

These lidar data were collected by the National Oceanic Atmospheric Administration National Geodetic Survey Remote Sensing Division using a Riegl VQ820G system. The data were acquired from 20140717 - 20140809 in twenty two missions.

These data were collected by the National Oceanic Atmospheric Administration National Geodetic Survey Remote Sensing Division using a Riegl VQ820G system. The data were acquired from 201311- 201406. The data includes topobathy data with points classified by target type (e.g. ground, water, etc). The final classified LiDAR data were then used to create topobathymetric DEMs in IMG format with 1m pixel size using ground points. The full project consists of 2,775 square miles along the Atlantic Coast from New York to South Carolina, or 41,388 - 500 m x 500 m lidar tiles.