Data Management Plan (Deprecated)

This data set consists of salt marsh habitats for the state of New Hampshire derived from high resolution (1ft) imagery collected on August 24, 2013. This data set relied on 4 Band multispectral aerial orthoimagery acquired by the Piscataqua Region Estuaries Partnership and LiDAR data collected through the LiDAR for the NorthEast project (2011).

Process Steps:

• 2019-11-01 00:00:00 - This data set was created by NOAA Office of Coastal Management (NOAA OCM) to include multiple vegetation communities that individually and collectively indicate aspects of marsh health. This section outlines the classification procedure for the New Hampshire Salt Marsh Habitats map. This product was developed through a partnership between Great Bay NERR and the NOAA OCM. The product was derived from high resolution 4 band digital imagery in combination with derivatives from LiDAR data. The mapping methodology employed an Object Based Image Analysis (image segmentation) approach. Data Preparation: The aerial imagery was supplied to NOAA OCM by Great Bay NERR. Orthoimagery during low tide on August 24, 2013 was pre-processed into spectral indices and band derivatives. LiDAR data collected through the LiDAR for the NorthEast project (2011) were processed into elevation models, surface models and tidal layers. Field Data Collection: Field samples were collected prior to (July 2016) the mapping effort. Salt Marsh Extent Classification: Image segmentation was performed in Trimble's eCognition Developer software package. The resulting image objects or segments were classified using modeling routines which leveraged existing wetland datasets acquired from the state of New Hampshire. Boundaries were refined using spectral and elevation information. The final extent was used to focus the supervised habitat classification process. Salt Marsh Habitat Classification: A new set of image objects were derived within the salt marsh extent boundary. The resulting image objects classified into habitat classes using a Random Forest classifier. Logical rule sets and contextual modeling were used to improve, and refine the habitat classification. Anomalies in the classification that were not addressed through the automated processes were corrected through manual editing. Review and Map Finalization: Once various stages of the salt marsh extent and habitat classification processing were completed, the resulting maps were provided to the Great Bay NERR and other local experts for comments. The majority of the resulting feedback was incorporated to improve the final habitat dataset.