This dataset contains projections of shoreline change and uncertainty bands for future scenarios of sea-level rise (SLR). Scenarios include 25, 50, 75, 100, 150, 200, and 300 centimeters (cm) of SLR by the year 2100. Output for SLR of 0 cm is also included, reflective of conditions in 2005, in accordance with recent SLR projections and guidance from the National Oceanic and Atmospheric Administration (NOAA; see process steps).Projections were made using the Coastal Storm Modeling System - Coastal One-line Assimilated Simulation Tool (CoSMoS-COAST), a numerical model (described in Vitousek and others, 2017; 2021; 2023) run in an ensemble forced with global-to-local nested wave models and assimilated with satellite-derived shoreline (SDS) observations. Shoreline positions from models are generated at pre-determined cross-shore transects and output includes different cases covering important model behaviors (cases are described in process steps of metadata; see citations listed in the Cross References section for more details on the methodology and supporting information). This model shows change in shoreline positions along transects, considering sea level, wave conditions, along-shore/cross-shore sediment transport, long-term trends due to sediment supply, and estimated variability due to unresolved processes (as described in Vitousek and others, 2021). Variability associated with complex coastal processes (for example, beach cusps/undulations and shore-attached sandbars) are included via a noise parameter in a model, which is tuned using observations of shoreline change at each transect and run in an ensemble of 200 simulations; this approach allows for a representation of statistical variability in a model that is assimilated with sequences of noisy observations. The model synthesizes and improves upon numerous, well-established shoreline models in the scientific literature; processes and methods are described in this metadata (see lineage and process steps), but also described in more detail in Vitousek and others 2017, 2021, and 2023. KMZ data are readily viewable in Google Earth. For best display of results, it is recommended to turn off any 3D features or terrain. For technical users and researchers, shapefile and KMZ data can be ingested into geographic information system (GIS) software such as Global Mapper or QGIS.

The United States geospatial analytics market is experiencing robust growth, projected to reach a significant size within the forecast period (2025-2033). The market's Compound Annual Growth Rate (CAGR) of 10.04% from 2019-2033 indicates a consistently expanding demand for geospatial data analysis across diverse sectors. Key drivers include the increasing availability of high-resolution satellite imagery, advancements in data processing capabilities (cloud computing, AI), and the growing need for data-driven decision-making in various industries. Specific sectors like agriculture, utilizing geospatial analytics for precision farming, and the defense and intelligence sectors, leveraging it for surveillance and strategic planning, are major contributors to market growth. Further fueling expansion are trends like the rising adoption of Internet of Things (IoT) devices generating location-based data, and the increasing sophistication of geospatial analytics software, incorporating advanced visualization and predictive modeling techniques. While data security concerns and the high cost of implementation pose some restraints, the overall market outlook remains positive, driven by the substantial benefits offered by geospatial analytics in improving efficiency, optimizing resource allocation, and enhancing situational awareness across a wide spectrum of applications. The market segmentation reveals significant opportunities across different types of geospatial analytics (surface analysis, network analysis, and geovisualization) and end-user verticals. While the provided data indicates a significant presence of companies like Harris Corporation, Bentley Systems Inc., and ESRI Inc., the market's competitive landscape is dynamic, with both established players and emerging technology companies vying for market share. The United States' dominance in geospatial technology and data infrastructure further supports the market's projected growth trajectory. The substantial investments in R&D and the prevalence of skilled professionals in the country further contribute to the market's expansion. Looking ahead, the integration of geospatial analytics with other technologies like blockchain and big data is expected to unlock new possibilities, further driving market growth and innovation in the coming years. Recent developments include: May 2023 : CAPE Analytics, a player in AI-powered geospatial property intelligence, has extended its partnership with The Hanover Insurance Group, which provides independent agents with the best insurance coverage and prices. Integrating geospatial analytics and inspection and rating models into Hanover's underwriting procedure is the central component of the partnership expansion. The company's rating plans will benefit from this strategic move, which will improve workflows, new and renewal underwriting outcomes, and pricing segmentation., March 2023 : Carahsoft Technology Corp., The Trusted Government IT Solutions Provider, and Orbital Insight, a player in geospatial intelligence, announced a partnership. By the terms of the agreement, Carahsoft will act as Orbital Insight's Master Government Aggregator, making the leading AI-powered geospatial data analytics available to the public sector through Carahsoft's reseller partners and contracts for Information Technology Enterprise Solutions - Software 2 (ITES-SW2), NASA Solutions for Enterprise-Wide Procurement (SEWP) V, National Association of State Procurement Officials (NASPO) ValuePoint, National Cooperative Purchasing.. Key drivers for this market are: Increasing in Demand for Location Intelligence, Advancements of Big Data Analytics. Potential restraints include: Increasing in Demand for Location Intelligence, Advancements of Big Data Analytics. Notable trends are: Network Analysis is Expected to Hold Significant Share of the Market.

The data illustrates the expanded “Urbanized Area” for the Municipal Separate Storm Sewer System (MS4) program from the 2020 census data. "Urbanized area" means a place and the adjacent densely populated territory that together have a minimum population of 50,000 people, as defined by the United States bureau of the census and as determined by the latest available decennial census. The data is provided to the Michigan Department of Environment, Great Lakes, and Energy (EGLE) by the United States Environmental Protection Agency. The urbanized area is the regulated area for municipalities that are regulated under the MS4 program, including but not limited to cities, township, and villages."2020 Census Populations of 50K or more" and "Automatically Designated Areas" was provided by US EPA in July 2023 and combined with Michigan Open GIS Data (Minor Civil Divisions: Cities, Townships and Villages) using ESRI's ArcGIS Pro Software. Tools used include Pairwise Intersect, Merge, Pairwise Erase, and manual editing to combine the two layers.Please contact the individuals below with any questions.Christe Alwin: ALWINC@michigan.gov (point of contact)Patrick Klein: kleinp3@michigan.gov (creator)FIELD NAMEDESCRIPTIONNameShort name of the municipality (Lansing)LabelThe municipalities full name (City of Lansing)TypeThe type of municipality (city, township, or village)SQMILEArea of the shape in Square MilesACRESArea of the shape in AcresPublished in June 2024. Learn more about EGLE's Municipal Storm Water Program.Additional information describing Part 21 Wastewater Discharge Permits.