No abstract

Three-dimensional visualization of the ecological marine units (EMUs) for the Banda Sea. EMUs are depicted as bands on cylinders, and pink colors indicate warmer EMUs, where blue colors represent colder EMUs. On land, the global ecological land units (ELUs) of Sayre et al. (2014) are shown. Global Open Ocean and Deep Seabed (GOODS) Biogeographic Characterization (UNESCO, 2009) Global, Benthic and Pelagic Expert recommended regions Deep-Sea Provinces (Watling et al., 2013) Global, Benthic Expert-derived revision of GOODS based on literature review Biogeochemical Provinces (Longhurst, 2007) Global Satellite ocean color Seafloor Map (GSFM) (Harris et al., 2014) Global Expert geomorphological feature extraction using 30 arcsecond bathymetry data Deep-Sea Seascapes Map (Harris and Whiteway, 2009) Global Multivariate analysis of seabed morphology and sediments

Reed (2019) A new 30 meter resolution global shoreline vector and associated global islands database for the development of standardized ecological coastal units,

The availability and use of geographic information technologies and data for describing the patterns and processes operating on or near the Earth's surface have grown substantially during the past fifty years. The number of geographic information systems software packages and algorithms has also grown quickly during this period, fueled by rapid advances in computing and the explosive growth in the availability of digital data describing specific phenomena. Geographic information scientists therefore increasingly find themselves choosing between multiple software suites and algorithms to execute specific analysis, modeling, and visualization tasks in environmental applications today. This is a major challenge because it is often difficult to assess the efficacy of the candidate software platforms and algorithms when used in specific applications and study areas, which often generate different results. The subtleties and issues that characterize the field of geomorphometry are used here to document the need for (1) theoretically based software and algorithms; (2) new methods for the collection of provenance information about the data and code along with application context knowledge; and (3) new protocols for distributing this information and knowledge along with the data and code. This article discusses the progress and enduring challenges connected with these outcomes.

No abstract