This Scene consists of the detailed 2014 USGS CMGP Post Sandy LiDAR Survey of New York City. along with over 1 million 3D Buildings for the city of New York available as part of the New York Cities OpenData initiative. A thematically symbolized 3D tree inventory for Roosevelt Island shows the value of LiDAR in validating tree survey heights. The LiDAR Dataset consists of data acquired and processed to assist in the evaluation of storm damage and erosion of the local environment as part of USGS Hurricane Sandy response along the Atlantic Seaboard.

Topographic and bathymetric LiDAR data was collected for New York City in 2017. Topographic data was collected for the entire city, plus an additional 100 meter buffer, using a Leica ALS80 sensor equipped to capture at least 8 pulse/m². Dates of capture for topographic data were between 05/03/2017 and 05/17/2017 during 50% leaf-off conditions. Bathymetric data was collected in select areas of the city (where bathymetric data capture was expected) using a Riegl VQ-880-G sensor equipped to capture approximately 15 pulses/m² (1.5 Secchi depths). Dates of capture for bathymetric were between 07/04/2017 - 07/26/2017. LiDAR data was tidally-coordinated and captured between mean lower low water (+30% of mean tide) ranges.

The horizontal datum for all datasets is NAD83, the vertical datum is NAVD88, Geoid 12B, and the data is projected in New York State Plane - Long Island. Units are in US Survey Feet.

To learn more about these datasets, visit the interactive “Understanding the 2017 New York City LiDAR Capture” Story Map -- https://maps.nyc.gov/lidar/2017/ Please see the following link for additional documentation on this dataset -- https://github.com/CityOfNewYork/nyc-geo-metadata/blob/master/Metadata/Metadata_LiDAR_Summary.md

The following datasets are available for download via the New York State GIS Clearinghouse.

The following links direct to the New York State website which includes links to download. Users may use the statewide interactive DEM download application to download specific areas of interest (hydroflattened DEM and classified point clouds only). Tile index for DEMs on the application correspond to tile indexes for hydro-enforced and digital surface models.

Product: Calibrated LiDAR version 1.4 .las tiles, classified to bare earth for subsequent derivatives. Geographic Extent: Erie, Genesee, and Livingston Counties, New York, covering approximately 2,188 square miles. Dataset Description: Erie, Genesee, and Livingston Counties, New York 2019 Lidar project called for the Planning, Acquisition, processing and derivative products of lidar data to be...

description: Light Detection and Ranging (LiDAR) data is remotely sensed high-resolution elevation data collected by an airborne collection platform. This LiDAR dataset is a survey of areas of coastal New York, including Long Island, eastern Westchester, and the tidal extents of the Hudson River. The project area consists of approximately 950 square miles. The project design of the LiDAR data acquisition was developed to support a nominal post spacing of 1.0 meter or better (1.0 meter GSD). The LiDAR data vertical accuracy is in compliance with the National Standard for Spatial Data Accuracy (NSSDA) RMSE estimation of elevation data in support of 1 ft. contour mapping products. GMR Aerial Surveys Inc. d/b/a Photo Science, Inc. acquired 740 flight lines in 63 lifts between November 2011 and April 2012, while no snow was on the ground, rivers were at or below normal levels, no strong onshore winds, high waves, floods, or other anomalous weather conditions. Specified areas of the project were collected at a tide stage where water levels are at least 1-foot below mean sea level (MSL). This collection was a joint effort by the NOAA Office for Coastal Management (OCM) and the New York State Department of Environmental Conservation. The data collection was performed with three Cessna 206 single engine aircrafts, utilizing Optech Gemini sensors; collecting multiple return x, y, and z as well as intensity data. The data were classified as Unclassified (1), Ground (2), Low Point (Noise) (7), Water (9), Breakline Edge (10), Withheld (11), Tidal Water (14), Overlap Default (17), and Overlap Ground (18), Overlap Water (25), and Overlap Tidal Water (30). Upon receipt, the NOAA Office for Coastal Management (OCM), for data storage and Digital Coast provisioning purposes, converted these classifications to the following: 1 - Unclassified 2 - Ground 7 - Low Point (Noise) 9 - Water NOAA tide gauges were used as the basis for flight planning the tidally coordinated areas. The Stevens Institute NY Harbor Observation and Prediction System (NYHOPS) data were used to confirm accuracy of NOAA predicted tides in Hudson. Some areas were collected using tidal restraints as listed below: Tidal Wetlands and tributary mouths selected for tidal coordination at Mean Sea Level (MSL) minus 1 foot were: Rondout Creek Outlet; Vanderburg Cove, Moodna Creek, Constitution Marsh, Iona Marsh, Annsville Creek, Croton River Outlet, Marlboro Marsh, Manitou Marsh, Fishkill Creek Outlet, and Wappingers Creek Outlet. The Upper Hudson area from North of Goose Island was also collected to the same specification. Tidal Wetlands and tributary mouths selected for tidal coordination at Mean Sea Level (MSL) were Haverstraw at Minisceongo Creek and Piermont Marsh. On Long Island the following areas were collected at MSL: 1) the northern shore of Nassau and Suffolk counties from approximately Glen Cove on the western boundary to Nissequogue on the eastern boundary 2) the Peconic Bay from Riverhead on the western boundary to the east end of Shelter Island and Accabonac Harbor on the eastern boundary 3) western Great South Bay. The remainder of the project area had no tidal restrictions for collection. LAS tiles indicate if they are tidally coordinated or not. If tidal coordination only covers part of the tile the tile will be labeled tidally coordinated (i.e.MSL-1). In order to post process the LiDAR data to meet task order specifications, Photo Science, Inc. established a total of 81 control points that were used to calibrate the LiDAR to known ground locations established throughout the New York project area. Trimble R8-3 GNSS receivers were used to complete the collection. Real Time Kinematic (RTK) survey methodology was typically performed using the New York State Spatial Reference Network (NYSNet), a CORS/Real Time GPS Network. Additionally, control values from various other projects completed by Photo Science in and around the project area, were used as supplemental control points to assist in the calibration of the LiDAR dataset. The dataset was developed based on a horizontal projection/datum of UTM NAD83 (NSRS2007), UTM Zone 18, meters and vertical datum of NAVD1988 (GEOID09), meters. Upon receipt, for data storage and Digital Coast provisioning purposes, the NOAA Office for Coastal Management converted the data to GRS80 Ellipsoid (GEOID09) heights, to geographic (NAD83, NSRS2007) coordinates, and from las format to laz format. LiDAR data were collected in RAW flightline swath format, processed to create Classified LAS 1.2 files formatted to 2093 individual 750m x 750m tiles, Hydro Flattening Breaklines in ESRI shapefile format, 1.0 meter gridded Tidal Water ERDAS IMAGINE (.img) files formatted to 670 individual 3000m x 3000m tiles, and 1.0 meter gridded V-Datum ERDAS IMAGINE (.img) files formatted to the same 3000m x3000m tile schema. LiDAR data were originally delivered to NOAA/Dewberry for quality control validation under Delivery Lots 1 and 2. The lineage (data quality), positional, content (completeness), attribution, logical consistency, and accuracies of all digital elevation data produced conform to the specifications stipulated in NOAA Task Order EA133C11CQ0009 - T011.; abstract: Light Detection and Ranging (LiDAR) data is remotely sensed high-resolution elevation data collected by an airborne collection platform. This LiDAR dataset is a survey of areas of coastal New York, including Long Island, eastern Westchester, and the tidal extents of the Hudson River. The project area consists of approximately 950 square miles. The project design of the LiDAR data acquisition was developed to support a nominal post spacing of 1.0 meter or better (1.0 meter GSD). The LiDAR data vertical accuracy is in compliance with the National Standard for Spatial Data Accuracy (NSSDA) RMSE estimation of elevation data in support of 1 ft. contour mapping products. GMR Aerial Surveys Inc. d/b/a Photo Science, Inc. acquired 740 flight lines in 63 lifts between November 2011 and April 2012, while no snow was on the ground, rivers were at or below normal levels, no strong onshore winds, high waves, floods, or other anomalous weather conditions. Specified areas of the project were collected at a tide stage where water levels are at least 1-foot below mean sea level (MSL). This collection was a joint effort by the NOAA Office for Coastal Management (OCM) and the New York State Department of Environmental Conservation. The data collection was performed with three Cessna 206 single engine aircrafts, utilizing Optech Gemini sensors; collecting multiple return x, y, and z as well as intensity data. The data were classified as Unclassified (1), Ground (2), Low Point (Noise) (7), Water (9), Breakline Edge (10), Withheld (11), Tidal Water (14), Overlap Default (17), and Overlap Ground (18), Overlap Water (25), and Overlap Tidal Water (30). Upon receipt, the NOAA Office for Coastal Management (OCM), for data storage and Digital Coast provisioning purposes, converted these classifications to the following: 1 - Unclassified 2 - Ground 7 - Low Point (Noise) 9 - Water NOAA tide gauges were used as the basis for flight planning the tidally coordinated areas. The Stevens Institute NY Harbor Observation and Prediction System (NYHOPS) data were used to confirm accuracy of NOAA predicted tides in Hudson. Some areas were collected using tidal restraints as listed below: Tidal Wetlands and tributary mouths selected for tidal coordination at Mean Sea Level (MSL) minus 1 foot were: Rondout Creek Outlet; Vanderburg Cove, Moodna Creek, Constitution Marsh, Iona Marsh, Annsville Creek, Croton River Outlet, Marlboro Marsh, Manitou Marsh, Fishkill Creek Outlet, and Wappingers Creek Outlet. The Upper Hudson area from North of Goose Island was also collected to the same specification. Tidal Wetlands and tributary mouths selected for tidal coordination at Mean Sea Level (MSL) were Haverstraw at Minisceongo Creek and Piermont Marsh. On Long Island the following areas were collected at MSL: 1) the northern shore of Nassau and Suffolk counties from approximately Glen Cove on the western boundary to Nissequogue on the eastern boundary 2) the Peconic Bay from Riverhead on the western boundary to the east end of Shelter Island and Accabonac Harbor on the eastern boundary 3) western Great South Bay. The remainder of the project area had no tidal restrictions for collection. LAS tiles indicate if they are tidally coordinated or not. If tidal coordination only covers part of the tile the tile will be labeled tidally coordinated (i.e.MSL-1). In order to post process the LiDAR data to meet task order specifications, Photo Science, Inc. established a total of 81 control points that were used to calibrate the LiDAR to known ground locations established throughout the New York project area. Trimble R8-3 GNSS receivers were used to complete the collection. Real Time Kinematic (RTK) survey methodology was typically performed using the New York State Spatial Reference Network (NYSNet), a CORS/Real Time GPS Network. Additionally, control values from various other projects completed by Photo Science in and around the project area, were used as supplemental control points to assist in the calibration of the LiDAR dataset. The dataset was developed based on a horizontal projection/datum of UTM NAD83 (NSRS2007), UTM Zone 18, meters and vertical datum of NAVD1988 (GEOID09), meters. Upon receipt, for data storage and Digital Coast provisioning purposes, the NOAA Office for Coastal Management converted the data to GRS80 Ellipsoid (GEOID09) heights, to geographic (NAD83, NSRS2007) coordinates, and from las format to laz format. LiDAR data were collected in RAW flightline swath format, processed to create Classified LAS 1.2 files formatted to 2093 individual 750m x 750m tiles, Hydro Flattening Breaklines in ESRI shapefile format, 1.0 meter gridded Tidal Water ERDAS IMAGINE (.img) files formatted to 670 individual 3000m x 3000m

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline derived from the 2012 Post-Hurricane Sandy New York U.S. Army Corps of Engineers (USACE) lidar survey. Beach width is included and is defined as the distance between the dune toe and shoreline along a cross-shore profile. The beach slope is calculated using this beach width and the elevation of the shoreline and dune toe.

Vertical profiles of wind, temperature, and moisture at 10 minute temporal resolution from the 17 profiling stations of the New York State Mesonet. The wind profiles are from scanning Doppler Lidars and the temperature and moisture profiles are from microwave radiometers (MWR). Data are available in NetCDF format for the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms 2023 (IMPACTS 2023) campaign.

LiDAR (Light Detection and Ranging) is a remote sensing technology, i.e. the technology is not in direct contact with what is being measured. From satellite, aeroplane or helicopter, a LiDAR system sends a light pulse to the ground. This pulse hits the ground and returns back to a sensor on the system. The time is recorded to measure how long it takes for this light to return. Knowing this time measurement scientists are able to create topography maps.LiDAR data are collected as points (X,Y,Z (x & y coordinates) and z (height)). The data is then converted into gridded (GeoTIFF) data to create a Digital Terrain Model and Digital Surface Model of the earth. This LiDAR data was collected on 25th March 2015.An ordnance datum (OD) is a vertical datum used as the basis for deriving heights on maps. This data is referenced to the Malin Head Vertical Datum which is the mean sea level of the tide gauge at Malin Head, County Donegal. It was adopted as the national datum in 1970 from readings taken between 1960 and 1969 and all heights on national grid maps are measured above this datum. Digital Terrain Models (DTM) are bare earth models (no trees or buildings) of the Earth’s surface.Digital Surface Models (DSM) are earth models in its current state. For example, a DSM includes elevations from buildings, tree canopy, electrical power lines and other features. Hillshading is a method which gives a 3D appearance to the terrain. It shows the shape of hills and mountains using shading (levels of grey) on a map, by the use of graded shadows that would be cast by high ground if light was shining from a chosen direction.This data shows the hillshade of the DSM.This data was collected by New York University. All data formats are provided as GeoTIFF rasters. Raster data is another name for gridded data. Raster data stores information in pixels (grid cells). Each raster grid makes up a matrix of cells (or pixels) organised into rows and columns. NYU data has a grid cell size of 1meter by 1meter. This means that each cell (pixel) represents an area of 1meter squared.

Product: Calibrated LiDAR version 1.4 .las tiles, classified to bare earth for subsequent derivatives. Geographic Extent: Cayuga and Oswego County, New York, covering approximately 1,720 square miles. Dataset Description: Cayuga and Oswego County, New York 2018 Lidar project called for the Planning, Acquisition, processing and derivative products of lidar data to be collected at a nominal pulse...

A 6-in resolution 8-class land cover dataset derived from the 2017 Light Detection and Ranging (LiDAR) data capture. This dataset was developed as part of an updated urban tree canopy assessment and therefore represents a ''top-down" mapping perspective in which tree canopy overhanging features is assigned to the tree canopy class. The eight land cover classes mapped were: (1) Tree Canopy, (2) Grass\Shrubs, (3) Bare Soil, (4) Water, (5) Buildings, (6) Roads, (7) Other Impervious, and (8) Railroads. The primary sources used to derive this land cover layer were 2017 LiDAR (1-ft post spacing) and 2016 4-band orthoimagery (0.5-ft resolution). Object based image analysis was used to automate land-cover features using LiDAR point clouds and derivatives, orthoimagery, and vector GIS datasets -- City Boundary (2017, NYC DoITT) Buildings (2017, NYC DoITT) Hydrography (2014, NYC DoITT) LiDAR Hydro Breaklines (2017, NYC DoITT) Transportation Structures (2014, NYC DoITT) Roadbed (2014, NYC DoITT) Road Centerlines (2014, NYC DoITT) Railroads (2014, NYC DoITT) Green Roofs (date unknown, NYC Parks) Parking Lots (2014, NYC DoITT) Parks (2016, NYC Parks) Sidewalks (2014, NYC DoITT) Synthetic Turf (2018, NYC Parks) Wetlands (2014, NYC Parks) Shoreline (2014, NYC DoITT) Plazas (2014, NYC DoITT) Utility Poles (2014, ConEdison via NYCEM) Athletic Facilities (2017, NYC Parks) For the purposes of classification, only vegetation > 8 ft were classed as Tree Canopy. Vegetation below 8 ft was classed as Grass/Shrub. To learn more about this dataset, visit the interactive "Understanding the 2017 New York City LiDAR Capture" Story Map -- https://maps.nyc.gov/lidar/2017/ Please see the following link for additional documentation on this dataset -- https://github.com/CityOfNewYork/nyc-geo-metadata/blob/master/Metadata/Metadata_LandCover.md

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2011 East Coast New York/New Jersey National Oceanic and Atmospheric Administration (NOAA) National Geodetic Survey (NGS) lidar survey. Beach width is included and is defined as the distance between the dune toe and shoreline along a cross-shore profile. The beach slope is calculated using this beach width and the elevation of the shoreline and dune toe.

LiDAR (Light Detection and Ranging) is a remote sensing technology, i.e. the technology is not in direct contact with what is being measured. From satellite, aeroplane or helicopter, a LiDAR system sends a light pulse to the ground. This pulse hits the ground and returns back to a sensor on the system. The time is recorded to measure how long it takes for this light to return.Knowing this time measurement scientists are able to create topography maps.LiDAR data are collected as points (X,Y,Z (x & y coordinates) and z (height)). The data is then converted into gridded (GeoTIFF) data to create a Digital Terrain Model and Digital Surface Model of the earth. This LiDAR data was collected on 25th March 2015.This data shows the areas in Dublin for which you can download LiDAR data and contains links to download the data. This is a vector dataset. Vector data portray the world using points, lines, and polygons (areas).The LiDAR coverage is shown as polygons. Each polygon is 2000m by 2000m in size and holds information on: the location, county, data provider, owner, licence, published date, capture date, surveyor, RMS error, resolution and a link to download the LiDAR raster data in 2000m by 2000m sections.

description: The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Niagara River and Lake Erie and Lake Ontario coasts of NY in 2007. The data types collected include bathymetry and topographic lidar point data, true color imagery and hyperspectral imagery. The collection effort follows the coastline and extends 500m inland and 1000m offshore or to laser extinction, whichever comes first. Topographic lidar is collected with 200% coverage, yielding a nominal 1m x 1m post-spacing. Where water conditions permit, the bathymetry lidar data will have a nominal post spacing of 4m x 4m. The true color imagery will have a pixel size approximately 35cm and the hyperspectral imagery will be provided in 1m pixels containing 36 bands between 375 - 1050 nm with 19 nm bandwidth. The final data will be tied to horizontal positions, provided in decimal degrees of latitude and longitude, and are referenced to the North American Datum of 1983 (NAD83). Vertical positions are referenced to the NAD83 ellipsoid and provided in meters. The National Geodetic Survey's (NGS) GEOID03 model is used to transform the vertical positions from ellipsoid to orthometric heights referenced to the North American Vertical Datum of 1988 (NAVD88). Once converted to orthometric heights, the data are then converted to the International Great Lakes Datum of 1985 (IGLD85) using the VDatum program from NOAA (National Oceanic and Atmospheric Administration).; abstract: The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Niagara River and Lake Erie and Lake Ontario coasts of NY in 2007. The data types collected include bathymetry and topographic lidar point data, true color imagery and hyperspectral imagery. The collection effort follows the coastline and extends 500m inland and 1000m offshore or to laser extinction, whichever comes first. Topographic lidar is collected with 200% coverage, yielding a nominal 1m x 1m post-spacing. Where water conditions permit, the bathymetry lidar data will have a nominal post spacing of 4m x 4m. The true color imagery will have a pixel size approximately 35cm and the hyperspectral imagery will be provided in 1m pixels containing 36 bands between 375 - 1050 nm with 19 nm bandwidth. The final data will be tied to horizontal positions, provided in decimal degrees of latitude and longitude, and are referenced to the North American Datum of 1983 (NAD83). Vertical positions are referenced to the NAD83 ellipsoid and provided in meters. The National Geodetic Survey's (NGS) GEOID03 model is used to transform the vertical positions from ellipsoid to orthometric heights referenced to the North American Vertical Datum of 1988 (NAVD88). Once converted to orthometric heights, the data are then converted to the International Great Lakes Datum of 1985 (IGLD85) using the VDatum program from NOAA (National Oceanic and Atmospheric Administration).

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and the USGS Lower Mississippi-Gulf Water Science Center (LMG WSC) in Montgomery, Alabama, collected terrestrial-based light detection and ranging (T-lidar) elevation data at Fire Island, New York. The data were collected on May 18, 2015 as part of the ongoing beach monitoring within Hurricane Sandy Supplemental Project GS2-2B, and will be used to document and assess the morphological storm response and post-storm beach recovery. The survey extended along 30 kilometers(km) of the Fire Island National Seashore, from the eastern boundary of Robert Moses State Park to the western boundary of Smith Point County Park. This USGS Data Release includes the resulting processed elevation point data (xyz) and an interpolated digital elevation model (DEM). For further information regarding data collection and/or processing methods, refer to previously published USGS Data Series 980 (https://doi.org/10.3133/ds980).

description: TASK NAME: USGS New York CMGP Sandy Lidar 0.7 Meter NPS LIDAR lidar Data Acquisition and Processing Production Task USGS Contract No. G10PC00057 Task Order No. G14PD00797 Woolpert Order No. 073666 CONTRACTOR: Woolpert, Inc. This data set is comprised of lidar point cloud data, raster DEM, hydrologic 3-d breaklines, raster intensity, survey control, project tile index, and project data extent. This task order requires lidar data to be acquired over several areas in New York State to include the entire counties of Bronx, Kings, New York, Richmond, and Queens. Governors, Hoffman, and Swinburne Islands are part of the New York area of interest (AOI), and will be acquired as part of this task order. The total area of the New York Sandy Lidar AOI is approximately 304 square miles. Woolpert acquired lidar data of New York City as part of a task order for the NGA. The flight plan for the New York City NGA Lidar task order was developed with 11 additional cross flights over the Manhattan Metropolitan area to minimize data shadowing and data voids in the lidar dataset caused by tall buildings. The lidar data for the NGA task order was acquired between August 5, 2013 and August 15, 2013. USGS requested use of this data from the NGA, in order to reduce the duplication of lidar data acquisition effort on the New York CMGP Sandy Lidar task order. The NGA approved the use of this lidar data for the USGS task order.Following the approval by NGA, Woolpert was able to utilize the cross flights acquired as part of the NGA task order to minimize data shadowing and data voids caused by tall buildings in the USGS New York CMGP Sandy Lidar task order AOI. The cross flights used in the New York CMGP Sandy 0.7M NPS Lidar Processing task order from the NGA New York City task order were flown on August 6, 2013. The lidar data acquisition parameters for this mission are detailed in the lidar processing report for this task order. The lidar data will be acquired and processed under the requirements identified in this task order. lidar data is a remotely sensed high resolution elevation data collected by an airborne platform. The lidar sensor uses a combination of laser range finding, GPS positioning, and inertial measurement technologies. The lidar systems collect data point clouds that are used to produce highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures, and vegetation. The task required the LiDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. The final products include classified LAS, one (1) meter pixel raster DEMs of the bare-earth surface in ERDAS IMG Format, and 8-bit intensity images. Each LAS file contains lidar point information, which has been calibrated, controlled, and classified. Additional deliverables include hydrologic breakline data, control data, tile index, lidar processing and survey reports in PDF format, FGDC metadata files for each data deliverable in .xml format, and LAS swath data. Collected swath files that were that were larger than 2GB were provided in multiple sub-swath files, each less than 2GB. Ground conditions: Water at normal levels; no unusual inundation; no snow; leaf off. The tide window requirements for the lidar data acquisition; Tidally impacted waters within the AOI are expected to be acquired at Predicted MLW +- 2 hours exclusive of neap tide.; The bare earth DEMs along the coast may have a variance in the water heights due to temporal differences during the lidar data acquisition and will be represented in DEM as a seam-like anomaly.; One coastal elevation was applied to entire project area. Due to differing acquisition dates and thus differing tide levels there will be areas in the DEM exhibiting what appears to be "digging" water features. Sometimes as much as approximately 1 meter. This was done to ensure that no coastal hydro feature was "floating" above ground surface. This coastal elevation will also affect connected river features wherein a sudden increase in flow will be observed in the DEM to accommodate the coastal elevation value; During Hydrologic breakline collection, Woolpert excluded obvious above-water piers or pier-like structures from the breakline placement. Some features extend beyond the apparent coastline and are constructed in a manner that can be considered an extension of the ground. These features were treated as ground during classification and subsequent hydrologic delineation. In all cases, professional practice was applied to delineate what appeared to be the coast based on data from multiple sources; Due to the many substructures and the complexity of the urban environment, interpolation and apparent "divots" (caused by tinning) may be evident in the surface of the bare earth DEM. In all cases, professional practice was applied to best represent the topography. NOAA OCM has not received any finalized DEMs for this project and do not expect to, therefore any request for these should be directed to USGS' National Map or a contact at Woolpert directly (as listed below).; abstract: TASK NAME: USGS New York CMGP Sandy Lidar 0.7 Meter NPS LIDAR lidar Data Acquisition and Processing Production Task USGS Contract No. G10PC00057 Task Order No. G14PD00797 Woolpert Order No. 073666 CONTRACTOR: Woolpert, Inc. This data set is comprised of lidar point cloud data, raster DEM, hydrologic 3-d breaklines, raster intensity, survey control, project tile index, and project data extent. This task order requires lidar data to be acquired over several areas in New York State to include the entire counties of Bronx, Kings, New York, Richmond, and Queens. Governors, Hoffman, and Swinburne Islands are part of the New York area of interest (AOI), and will be acquired as part of this task order. The total area of the New York Sandy Lidar AOI is approximately 304 square miles. Woolpert acquired lidar data of New York City as part of a task order for the NGA. The flight plan for the New York City NGA Lidar task order was developed with 11 additional cross flights over the Manhattan Metropolitan area to minimize data shadowing and data voids in the lidar dataset caused by tall buildings. The lidar data for the NGA task order was acquired between August 5, 2013 and August 15, 2013. USGS requested use of this data from the NGA, in order to reduce the duplication of lidar data acquisition effort on the New York CMGP Sandy Lidar task order. The NGA approved the use of this lidar data for the USGS task order.Following the approval by NGA, Woolpert was able to utilize the cross flights acquired as part of the NGA task order to minimize data shadowing and data voids caused by tall buildings in the USGS New York CMGP Sandy Lidar task order AOI. The cross flights used in the New York CMGP Sandy 0.7M NPS Lidar Processing task order from the NGA New York City task order were flown on August 6, 2013. The lidar data acquisition parameters for this mission are detailed in the lidar processing report for this task order. The lidar data will be acquired and processed under the requirements identified in this task order. lidar data is a remotely sensed high resolution elevation data collected by an airborne platform. The lidar sensor uses a combination of laser range finding, GPS positioning, and inertial measurement technologies. The lidar systems collect data point clouds that are used to produce highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures, and vegetation. The task required the LiDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. The final products include classified LAS, one (1) meter pixel raster DEMs of the bare-earth surface in ERDAS IMG Format, and 8-bit intensity images. Each LAS file contains lidar point information, which has been calibrated, controlled, and classified. Additional deliverables include hydrologic breakline data, control data, tile index, lidar processing and survey reports in PDF format, FGDC metadata files for each data deliverable in .xml format, and LAS swath data. Collected swath files that were that were larger than 2GB were provided in multiple sub-swath files, each less than 2GB. Ground conditions: Water at normal levels; no unusual inundation; no snow; leaf off. The tide window requirements for the lidar data acquisition; Tidally impacted waters within the AOI are expected to be acquired at Predicted MLW +- 2 hours exclusive of neap tide.; The bare earth DEMs along the coast may have a variance in the water heights due to temporal differences during the lidar data acquisition and will be represented in DEM as a seam-like anomaly.; One coastal elevation was applied to entire project area. Due to differing acquisition dates and thus differing tide levels there will be areas in the DEM exhibiting what appears to be "digging" water features. Sometimes as much as approximately 1 meter. This was done to ensure that no coastal hydro feature was "floating" above ground surface. This coastal elevation will also affect connected river features wherein a sudden increase in flow will be observed in the DEM to accommodate the coastal elevation value; During Hydrologic breakline collection, Woolpert excluded obvious above-water piers or pier-like structures from the breakline placement. Some features extend beyond the apparent coastline and are constructed in a manner that can be considered an extension of the ground. These features were treated as ground during classification and subsequent hydrologic delineation. In all cases, professional practice was applied to delineate what appeared to be the coast based on data from multiple sources; Due to the many substructures and the complexity of the urban environment, interpolation and apparent "divots" (caused by tinning) may be evident in the surface of the bare earth DEM. In all cases, professional practice was applied to best represent the topography. NOAA OCM has not received any finalized DEMs

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) in Florida and the USGS Lower Mississippi-Gulf Water Science Center (LMG WSC) in Montgomery, Alabama, collaborated to gather alongshore terrestrial-based lidar beach elevation data at Fire Island, New York. This high-resolution elevation dataset was collected on June 11, 2014, to characterize beach topography and document ongoing beach evolution and recovery, and is part of the ongoing beach monitoring within the Hurricane Sandy Supplemental Project GS2-2B. This USGS data series includes the resulting processed elevation point data (xyz) and an interpolated digital elevation model (DEM).

Governor's Island Dataset for GRASS GIS This geospatial dataset contains raster and vector data for Governor's Island, New York City, USA. The top level directory governors_island_for_grass is a GRASS GIS location for NAD_1983_StatePlane_New_York_Long_Island_FIPS_3104_Feet in US Surveyor's Feet with EPSG code 2263. Inside the location there is the PERMANENT mapset, a license file, data record, readme file, workspace, color table, category rules, and scripts for data processing. This dataset was created for the course GIS for Designers.

Instructions Install GRASS GIS, unzip this archive, and move the location into your GRASS GIS database directory. If you are new to GRASS GIS read the first time users guide.

Data Sources

https://orthos.dhses.ny.gov/

https://data.cityofnewyork.us/

Maps

Orthophotographs from 2012, 2014, 2016, 2018, and 2020

Digital elevation model from 2017

Digital surface models from 2014 and 2017

Landcover from 2014

License This dataset is licensed under the ODC Public Domain Dedication and License 1.0 (PDDL) by Brendan Harmon.

Product: Several products were collected and created for the project extent in Allegany and Steuben County, New York. These products include unclassified Swath LAS, Classified & Tiled LAS files, and Bare Earth Digital Elevation Models (DEM). This metadata record describes the las point data.

Geographic Extent: Allegany and Steuben County, New York, covering approximately 1,316 square miles....

Vertical profiles of wind, temperature, and moisture at 10 minute temporal resolution from the 17 profiling stations of the New York State Mesonet. The wind profiles are from scanning Doppler Lidars and the temperature and moisture profiles are from microwave radiometers (MWR). Data are available in NetCDF format for the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign. There were no IMPACTS field operations in 2021 due to COVID, but these data were collected for the period the operations were initially planned.

NYS Building Footprints - metadata info:The New York State building footprints service contains building footprints with address information. The footprints have address point information folded in from the Streets and Address Matching (SAM - https://gis.ny.gov/streets/) address point file. The building footprints have a field called “Address Range”, this field shows (where available) either a single address or an address range, depending on the address points that fall within the footprint. Ex: 3860 Atlantic Avenue or Ex: 32 - 34 Wheatfield Circle Building footprints in New York State are from four different sources: Microsoft, Open Data, New York State Energy Research and Development Authority (NYSERDA), and Geospatial Services. The majority of the footprints are from NYSERDA, except in NYC where the primary source was Open Data. Microsoft footprints were added where the other 2 sources were missing polygons. Field Descriptions: NYSGeo Source : tells the end user if the source is NYSERDA, Microsoft, NYC Open Data, and could expand from here in the futureAddress Point Count: the number of address points that fall within that building footprintAddress Range : If an address point falls within a footprint it lists the range of those address points. Ex: if a building is on a corner of South Pearl and Beaver Street, 40 points fall on the building, and 35 are South Pearl Street it would give the range of addresses for South Pearl. We also removed sub addresses from this range, primarily apartment related. For example, in above example, it would not list 30 South Pearl, Apartment 5A, it would list 30 South Pearl.Most Common Street : the street name of the largest number of address points. In the above example, it would list “South Pearl” as the most common street since the majority of address points list it as the street. Other Streets: the list of other streets that fall within the building footprint, if any. In the above example, “Beaver Street” would be listed since address points for Beaver Street fall on the footprint but are not in the majority.County Name : County name populated from CIESINs. If not populated from CIESINs, identified by the GSMunicipality Name : Municipality name populated from CIESINs. If not populated from CIESINs, identified by the GSSource: Source where the data came from. If NYSGeo Source = NYSERDA, the data would typically list orthoimagery, LIDAR, county data, etc.Source ID: if NYSGeo Source = NYSERDA, Source ID would typically list an orthoimage or LIDAR tileSource Date: Date the footprint was created. If the source image was from 2016 orthoimagery, 2016 would be the Source Date. Description of each footprint source:NYSERDA Building footprints that were created as part of the New York State Flood Impact Decision Support Systems https://fidss.ciesin.columbia.edu/home Footprints vary in age from county to county.Microsoft Building Footprints released 6/28/2018 - vintage unknown/varies. More info on this dataset can be found at https://blogs.bing.com/maps/2018-06/microsoft-releases-125-million-building-footprints-in-the-us-as-open-data.NYC Open Data - Building Footprints of New York City as a polygon feature class. Last updated 7/30/2018, downloaded on 8/6/2018. Feature Class of footprint outlines of buildings in New York City. Please see the following link for additional documentation- https://github.com/CityOfNewYork/nyc-geo-metadata/blob/master/Metadata/Metadata_BuildingFootprints.mdSpatial Reference of Source Data: UTM Zone 18, meters, NAD 83. Spatial Reference of Web Service: Spatial Reference of Web Service: WGS 1984 Web Mercator Auxiliary Sphere.

The intensity values of the Green and NIR LiDAR laser returns from the New York City Topobathymetric LiDAR dataset. Collected between 05/03/17 and 07/26/17.