This data set represents a 0.76-meter resolution LiDAR-derived bare earth hillshaded terrain (illumination from the northeast) layer for New Hampshire. It was generated from a statewide bare earth DEM which was developed from 7 separate LiDAR collections that covered the state as of July 2022.

Product: These lidar data are processed Classified LAS 1.4 files, formatted to 6235 individual 2500 ft x 2500 ft tiles; used to create intensity images, 3D breaklines, and hydro-flattened DEMs as necessary. Geographic Extent: 8 counties in New Hampshire, covering approximately 1311 total square miles. Dataset Description: The NH Coastal Lidar Work Package 183374, Work Unit 183371 project call...

This map provides access to vector data layers that incorporate Landsat reflectance data and LiDAR elevation data within the state of New Hampshire. These data were developed by NH GRANIT using data collected between 2011 and 2018. The polygon boundaries represent "image objects" that were derived using eCognition image segmentation software, grouping image pixels into contiguous segments based on spectral reflectance and LiDAR. The attributes for each polygon were then calculated from the LiDAR crown height layer. Attributes include maximum, minimum, and mean elevation above the ground and standard deviation within each polygon. Elevation is in meters. The boundary of each layer is determined by the extent of a LiDAR data collection; Landsat reflectance data were clipped to the extent of the LiDAR. The dates of data collection are listed in the metadata for each data layer.These data were developed by NH GRANIT using funding from the New Hampshire Space Grant Consortium.

This data set represents a 2-meter resolution LiDAR first return surface or Digital Surface Model (DSM) for New Hampshire. It was derived from a statewide LAS Dataset which comprised 8 separate LiDAR collections that covered the state as of January, 2020. The LAS Dataset was used as input to the ArcGIS "LAS Dataset to Raster" geoprocessing tool which converted the LAS first return values to raster values in the output data set. In some areas, users may notice unusual linear edges which appear unlikely or anomalous. The LiDAR vendor explained that these anomalies may be the result of changes in the degrees of tree canopy closure that occurred between the times adjacent flight lines were completed. Although leaf-off conditions were specified for data collection, strict adherence to the project specifications was not possible in all locations and exceptions occurred in order to complete data acquisition in a timely manner. As a result, abrupt discontinuities may be noticeable where data were collected on different dates. Eamples of these anomalies can be found in the areas of Cave Mountain in Bartlett and to the west of Woodstock.

Geographic Extent: Partial coverage of six counties in New Hampshire and Maine, covering approximately 3,276 total square miles. Dataset Description: The Umbagog NH/ME 2016 LiDAR project called for the planning, acquisition, processing, and derivative products of LiDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters for the New Hampshire, Maine, and FEMA R1 (MOD1) areas of i...

This data set represents a 0.76-meter resolution LiDAR-derived bare earth Digital Elevation Model (DEM) layer for New Hampshire. It was generated from a statewide Esri Mosaic Dataset which comprised 7 separate LiDAR collections that covered the state as of, July 2022. The Mosaic Dataset was converted to this img raster data set.

This data set represents a 5-meter resolution LiDAR-derived degree slope layer for New Hampshire. It was generated from a statewide Esri Mosaic Dataset which comprised 8 separate LiDAR collections that covered the state as of January, 2020. The Mosaic Dataset was used as input to the ArcGIS Spatial Analyst "Slope" geoprocessing tool which calculates the degree slope for each cell of the input raster, in this case, the statewide mosaic dataset.

This data set represents a 5-meter resolution LiDAR-derived percent slope layer for New Hampshire. It was generated from a statewide Esri Mosaic Dataset which comprised 8 separate LiDAR collections that covered the state as of January, 2020. The Mosaic Dataset was used as input to the ArcGIS Spatial Analyst "Slope" geoprocessing tool which calculates the percent slope for each cell of the input raster, in this case, the statewide mosaic dataset.

Original Product: These are Digital Elevation Model (DEM) data for New Hampshire as part of the required deliverables for the NH Coastal Lidar project. Class 2 (ground) LiDAR points in conjunction with the hydro breaklines were used to create a 1.25 foot hydro-flattened Raster DEM.

Original Dataset Geographic Extent: 8 counties in New Hampshire, covering approximately 1311 total square miles...

This data set represents a 0.76-meter resolution LiDAR-derived bare earth hillshaded terrain (illumination from the northeast) layer for New Hampshire. It was generated from a statewide Esri Mosaic Dataset which comprised 8 separate LiDAR collections that covered the state as of January, 2020.

NCALM Seed Project PI: Danna Truslow, University of New Hampshire. The survey area is an irregular polygon approximately 16 km West of Portsmouth, NH and enclosing 42.5 square kilometers. The data were collected to study hyporheic zone extent and exchange in a coastal New Hampshire stream using heat as a tracer.

Publications associated with this dataset can be found at NCALM's Data Tracking Center

These files contain classified topo/bathy lidar data. Data are classified as 1 (valid non-ground topographic data), 2 (valid ground topographic data), and 29 (valid bathymetric data). Classes 1 and 2 are defined in accordance with the American Society for Photogrammetry and Remote Sensing (ASPRS) classification standards. These data were collected by the Coastal Zone Mapping and Imaging Lidar (...

These files contain rasterized topobathy lidar elevations generated from data collected by the Coastal Zone Mapping and Imaging Lidar (CZMIL) system. CZMIL integrates a lidar sensor with simultaneous topographic and bathymetric capabilities, a digital camera and a hyperspectral imager on a single remote sensing platform for use in coastal mapping and charting activities. Horizontal positions, p...

These files contain classified topo/bathy lidar data. Data are classified as 1 (valid non-ground topographic data), 2 (valid ground topographic data), and 29 (valid bathymetric data). Classes 1 and 2 are defined in accordance with the American Society for Photogrammetry and Remote Sensing (ASPRS) classification standards. These data were collected by the Coastal Zone Mapping and Imaging Lidar (...

NCALM Seed Project PI: Adam Finkelman, Plymouth State University. The survey area is an irregular polygon approximately 42 square kilometers approximately 20 kilometers north of Plymouth, NH in the White Mountain National Forest. The data were collected to study the hydrologic and topographic controls on the distribution of organic carbon in forest soils. Publications associated with this dataset can be found at NCALM's Data Tracking Center

NCALM Project. PI: John Gartner, Dartmouth College. The survey area covers a 45 square kilometers along the Ashelot River, south of Keene and crossing West Swanzey, New Hampshire. Data were collected to quantify the geomorphic and sedimentological responses to dam removal. Repeat survey from 2011: West Swanzey, NH: Geomorphic Response to Dam Removal, Ashuelot River (2011)

Publications associated with this dataset can be found at NCALM's Data Tracking Center

TASK NAME: New England CMGP Sandy Lidar LiDAR Data Acquisition and Processing Production Task USGS Contract No. G10PC00057 Task Order No. G13PD00796 Woolpert Order No. 073667 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 which encompasses approximately 2120 square miles along with a 100 meter buffer over several areas in central to eastern Massachusetts. The coverage of the data includes slivers of areas that were missed by previous lidar acquisitions. 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 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 0.7m. The final products include files containing 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. The LiDAR data was provided in 1,500 meters x 1,500 meters tiles in the UTM projection. The LiDAR tile file names were derived from the southwest corner of each tile and are named based on the US National Grid. Product specifics can be found in the processing description section of this file. Ground conditions: 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. This is especially true in areas of tidal flats. 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; Cranberry bogs are existent in the project. These are filled with shallow water for short periods during the year but were not collected as hydrologic features; 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 DEM. Temporal differences from lidar collects in and around hydrologic features may manifest in the DEM as differing water levels. In all cases, professional practice was applied to best represent the topography. Data for the task order is referenced to the UTM Zone 19N, North American Datum of 1983 (2011), and NAVD88, in meters. However, a small portion of the AOI crossed into UTM 18 and this data is referenced to the UTM18N, North American Datum of 1983 (2011), and NAVD88 GEOID12A, in meters

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Geographic Extent: Connecticut River Watershed (4,437 sq mi), Winnipesaukee River Watershed (796 sq mi), and portions of the White Mountain National Forest (WMNF) in New Hampshire (181 sq mi), covering approximately 5,233 total square miles. Dataset Description: The Connecticut River Watershed 2015 project called for the planning, acquisition, processing and derivative products of LIDAR dat...