(Source: Producer defined) Range of values Seg Segment ID number used in processing (also labeled "segment"). State State segment file identification (ID) number. Sequential unique whole numbers that are automatically generated. How does the data set describe geographic features? smi14_DCpts Attribute values of 1197 dune crest positions recorded in the Esri shapefile smi14_DCpts.shp.What coordinate system is used to represent geographic features? Grid_Coordinate_System_Name: Universal Transverse Mercator Universal_Transverse_Mercator:Īltitude_Datum_Name: NAVD88 Altitude_Resolution: 0.000001 Altitude_Distance_Units: meter Altitude_Encoding_Method: Attribute values.How are geographic features stored in the data set?.What is the general form of this data set? Geospatial_Data_Presentation_Form: vector digital data.Does the data set describe conditions during a particular time period? Beginning_Date: 0 Ending_Date: 2 Currentness_Reference: Ground condition measured by source lidar data.This example is for Assateague Island, MD and may not represent this dataset. What geographic area does the data set cover? West_Bounding_Coordinate: -75.92402568 East_Bounding_Coordinate: -75.83143243 North_Bounding_Coordinate: 37.18093091 South_Bounding_Coordinate: 37.1108064Įxample geomorphology points (mean high water shoreline, dune toe, and dune crest) overlain on the DEM.Suggested citation: Sturdivant, E.J., Zeigler, S.L., Gutierrez, B.T., and Weber, K.M., 2019, Barrier island geomorphology and shorebird habitat metrics-Sixteen sites on the U.S. This work is one component of a larger research and management program that seeks to understand and sustain the ecological value, ecosystem services, and habitat suitability of beaches in the face of storm impacts, climate change, and sea-level rise. These datasets and models are being developed for sites along the northeastern coast of the United States. This data release contains the extracted metrics of barrier island geomorphology and spatial data layers of habitat characteristics that are input to Bayesian networks for piping plover habitat availability and barrier island geomorphology. The metrics are then incorporated into predictive models and the training data used to parameterize those models. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. What legal disclaimers am I supposed to read?.What's the catalog number I need to order this data set?.Are there legal restrictions on access or use of the data?.How can someone get a copy of the data set?.How consistent are the relationships among the data, including topology?.Where are the gaps in the data? What is missing?.How accurate are the heights or depths?.How accurate are the geographic locations?.How well have the observations been checked?.How reliable are the data what problems remain in the data set?.What similar or related data should the user be aware of?.How were the data generated, processed, and modified?.From what previous works were the data drawn?.To whom should users address questions about the data?.
Who are the originators of the data set?.How does the data set describe geographic features?.How does the data set represent geographic features?.What is the general form of this data set?.Does the data set describe conditions during a particular time period?.