Provides bathymetric depth contours in feet for New Hampshire lakes surveyed by the New Hampshire Department of Environmental Services since 2000 and New Hampshire Fish and Game.

This data set represents smoothed, 2-foot bare earth contours (isolines) for the Lake Winnipesaukee (0107000201) HUC 10 unit. It was derived from a data set which was compiled from LIDAR collections in NH available as of spring, 2019. The raster was filtered using the ArcGIS FOCAL STATISTICS tool with a 3x3 circular neighborhood. The contours were generated using the ArcGIS CONTOUR tool while applying a Z factor of 3.2808 to convert the elevation values from meters to feet. The filtered contours were then smoothed using the ArcGIS SMOOTH LINE tool. The data include an INDEX field with values of 10 and 100 to flag 10 and 100-foot contours. Note on HUC 01060000310: Due to limitations in the source LIDAR data, some anomalies exist in the generated contours in coastal areas of the state. These were left in the data so that users can determine what further processing best meets their application needs.

This data set represents smoothed, 2-foot bare earth contours (isolines) for the Ossipee Lake (0106000208) HUC 10 unit. It was derived from a data set which was compiled from LIDAR collections in NH available as of spring, 2019. The raster was filtered using the ArcGIS FOCAL STATISTICS tool with a 3x3 circular neighborhood. The contours were generated using the ArcGIS CONTOUR tool while applying a Z factor of 3.2808 to convert the elevation values from meters to feet. The filtered contours were then smoothed using the ArcGIS SMOOTH LINE tool. The data include an INDEX field with values of 10 and 100 to flag 10 and 100-foot contours. Note on HUC 01060000310: Due to limitations in the source LIDAR data, some anomalies exist in the generated contours in coastal areas of the state. These were left in the data so that users can determine what further processing best meets their application needs.

We developed a mapped classification of lakes and ponds based on variables that structure lacustrine natural communities and that could be mapped consistently across Northeastern US. The classification was built upon four key attributes: water temperature, trophic state, alkalinity, and depth. Water temperature was mapped into three classes (very cold, cold, and warm-cool) to reflect the requirements and limits of aquatic organisms. Trophic states, representing the productivity of a lake, were mapped into two classes (oligomesotrophic -mesotrophic and eutrophic- hypereutrophic). Alkalinity was grouped into three classes (high, medium, low) to reflect how well the lake system was buffered from acidification. Depth was divided into two classes (lake, pond) based on a light penetration zone, using maximum depth and trophic state as a proxy for this zone. A steering committee of state and regional experts contributed sampled data with measured values of these and other variables for waterbodies in their states. To create the mapped classification, we compiled the location of every waterbody in the region (n = 36, 675) , and for each waterbody we generatedover 300 descriptive attributes including: morphology, dams, climate, soils, geology, conservation lands, landforms, and land cover in the buffer zone or watershed. We used Random Forest software to develop a predictive model for each classification variable class based on the sampled data points and the descriptive attribute variables, and we then extrapolated the model to the unsampled waterbodies to estimate their class. After estimating each variable class, all waterbodies were assigned to one of 18 classification types based on the combination of 3 variables, temperature + trophic + alkalinity class. These types can be further subdivided into lake or pond categories to yield mapped occurrences, for example: cold, oligo-mesotrophic, low alkalinity, lake. The 18 primary lake and pond types are described in the addition to the “Northeast Terrestrial and Aquatic Habitat Guide”, December 2015.

This data set represents smoothed, 2-foot bare earth contours (isolines) for the Umbagog Lake (0104000102) HUC 10 unit. It was derived from a data set which was compiled from LIDAR collections in NH available as of spring, 2019. The raster was filtered using the ArcGIS FOCAL STATISTICS tool with a 3x3 circular neighborhood. The contours were generated using the ArcGIS CONTOUR tool while applying a Z factor of 3.2808 to convert the elevation values from meters to feet. The filtered contours were then smoothed using the ArcGIS SMOOTH LINE tool. The data include an INDEX field with values of 10 and 100 to flag 10 and 100-foot contours. Note on HUC 01060000310: Due to limitations in the source LIDAR data, some anomalies exist in the generated contours in coastal areas of the state. These were left in the data so that users can determine what further processing best meets their application needs.

This data set represents smoothed, 2-foot bare earth contours (isolines) for the Hopkinton Lake-Contoocook River (0107000303) HUC 10 unit. It was derived from a data set which was compiled from LIDAR collections in NH available as of spring, 2019. The raster was filtered using the ArcGIS FOCAL STATISTICS tool with a 3x3 circular neighborhood. The contours were generated using the ArcGIS CONTOUR tool while applying a Z factor of 3.2808 to convert the elevation values from meters to feet. The filtered contours were then smoothed using the ArcGIS SMOOTH LINE tool. The data include an INDEX field with values of 10 and 100 to flag 10 and 100-foot contours. Note on HUC 01060000310: Due to limitations in the source LIDAR data, some anomalies exist in the generated contours in coastal areas of the state. These were left in the data so that users can determine what further processing best meets their application needs.

This dataset combines the work of several different projects to create a seamless data set for the contiguous United States. Data from four regional Gap Analysis Projects and the LANDFIRE project were combined to make this dataset. In the northwestern United States (Idaho, Oregon, Montana, Washington and Wyoming) data in this map came from the Northwest Gap Analysis Project. In the southwestern United States (Colorado, Arizona, Nevada, New Mexico, and Utah) data used in this map came from the Southwest Gap Analysis Project. The data for Alabama, Florida, Georgia, Kentucky, North Carolina, South Carolina, Mississippi, Tennessee, and Virginia came from the Southeast Gap Analysis Project and the California data was generated by the updated California Gap land cover project. The Hawaii Gap Analysis project provided the data for Hawaii. In areas of the county (central U.S., Northeast, Alaska) that have not yet been covered by a regional Gap Analysis Project, data from the Landfire project was used. Similarities in the methods used by these projects made possible the combining of the data they derived into one seamless coverage. They all used multi-season satellite imagery (Landsat ETM+) from 1999-2001 in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform) to model natural and semi-natural vegetation. Vegetation classes were drawn from NatureServe's Ecological System Classification (Comer et al. 2003) or classes developed by the Hawaii Gap project. Additionally, all of the projects included land use classes that were employed to describe areas where natural vegetation has been altered. In many areas of the country these classes were derived from the National Land Cover Dataset (NLCD). For the majority of classes and, in most areas of the country, a decision tree classifier was used to discriminate ecological system types. In some areas of the country, more manual techniques were used to discriminate small patch systems and systems not distinguishable through topography. The data contains multiple levels of thematic detail. At the most detailed level natural vegetation is represented by NatureServe's Ecological System classification (or in Hawaii the Hawaii GAP classification). These most detailed classifications have been crosswalked to the five highest levels of the National Vegetation Classification (NVC), Class, Subclass, Formation, Division and Macrogroup. This crosswalk allows users to display and analyze the data at different levels of thematic resolution. Developed areas, or areas dominated by introduced species, timber harvest, or water are represented by other classes, collectively refered to as land use classes; these land use classes occur at each of the thematic levels. Raster data in both ArcGIS Grid and ERDAS Imagine format is available for download at http://gis1.usgs.gov/csas/gap/viewer/land_cover/Map.aspx Six layer files are included in the download packages to assist the user in displaying the data at each of the Thematic levels in ArcGIS. In adition to the raster datasets the data is available in Web Mapping Services (WMS) format for each of the six NVC classification levels (Class, Subclass, Formation, Division, Macrogroup, Ecological System) at the following links. http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Class_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Subclass_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Formation_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Division_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Macrogroup_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_Ecological_Systems_Landuse/MapServer

The surficial geologic map of the Eastern and Central United States depicts the areal distribution of surficial geologic deposits and other materials that accumulated or formed during the past 2+ million years, the period that includes all activities of the human species. These materials are at the surface of the earth. They make up the "ground" on which we walk, the "dirt" in which we dig foundations, and the “soil” in which we grow crops. Most of our human activity is related in one way or another to these surface materials that are referred to collectively by many geologists as regolith, the mantle of fragmental and generally unconsolidated material that overlies the bedrock foundation of the continent. The map is based on 31 published maps in the U.S. Geological Survey's Quaternary Geologic Atlas of the United States map series (U.S. Geological Survey Miscellaneous Investigations Series I-1420). It was compiled at 1:1,000,000 scale, to be viewed as a digital map at 1:2,000,000 nominal scale and to be printed as a conventional paper map at 1:2,500,000 scale. This map is not a map of soils as recognized and classified in agriculture. Rather, it is a generalized map of soils as recognized in engineering geology, or of substrata or parent materials in which agricultural, agronomic, or pedologic soils are formed. Where surficial deposits or materials are thick, agricultural soils are developed only in the upper part of the engineering soils. Where they are very thin, agricultural soils are developed through the entire thickness of a surficial deposit or material. The surficial geologic map provides a broad overview of the areal distribution of surficial deposits and materials. It identifies and depicts more than 150 types of deposits and materials. In general, the map units are divided into two major categories, surface deposits and residual materials. Surface deposits are materials that accumulated or were emplaced after component particles were transported by ice, water, wind, or gravity. The glacial sediments that cover the surface in much of the northern United States east of the Rocky Mountains are in this category, as are the gravel, sand, silt, and clay that were deposited in past and present streams, lakes, and oceans. In contrast, residual materials formed in place, without significant transport of component particles by ice, water, wind, or gravity. They are products of modification or alteration of pre-existing surficial deposits, surficial materials, or bedrock. For example, intense weathering of solid rock, or even stream deposits, by chemical processes may produce a residual surficial material that is greatly transformed from its original physical and chemical state. In recent years, surficial deposits and materials have become the focus of much interest by scientists, environmentalists, governmental agencies, and the general public. They are the foundations of ecosystems, the materials that support plant growth and animal habitat, and the materials through which travels much of the water required for our agriculture, our industry, and our general well being. They also are materials that easily can become contaminated by pesticides, fertilizers, and toxic wastes. In this context, the value of the surficial geologic map is evident The map and its digital database provide information about four major aspects of the surficial materials, through description of more than 150 types of materials and depiction of their areal distribution. The map unit descriptions provide information about (1) genesis (processes of origin) or environments of deposition (for example, deposits related to glaciation (glacial deposits), flowing water (alluvial deposits), lakes (lacustrine deposits), wind (eolian deposits), or gravity (mass-movement deposits)), (2) age (for example, how long ago the deposits accumulated or were emplaced or how long specific processes have been acting on the materials), (3) properties (the chemical, physical, and mechanical or engineering characteristics of the materials), and (4) thickness or depth to underlying deposits or materials or to bedrock. This approach provides information appropriate for a broad user base. The map is useful to national, state, and other governmental agencies, to engineering and construction companies, to environmental organizations and consultants, to academic scientists and institutions, and to the layman who merely wishes to learn more about the materials that conceal the bedrock. The map can facilitate regional and national overviews of (1) geologic hazards, including areas of swelling clay and areas of landslide deposits and landslide-prone materials, (2) natural resources, including aggregate for concrete and road building, peat, clay, and shallow sources for groundwater, and (3) areas of special environmental concern, i... Visit https://dataone.org/datasets/d863e647-d00d-4994-89bc-be4be9d4adf0 for complete metadata about this dataset.

Drying has a major impact on pattern and process in streams, particularly in small or headwater streams. Such streams that dry recurrently are called non-perennial streams and represent most of the channel length across river networks. In spite of their prevalence, non-perennial streams are vastly underrepresented in existing stream gaging networks and in maps and hydrographic datasets. However, diverse and spatially extensive datasets of surface water presence observations exist as well as recently developed mobile applications that could help fill the data gap in characterizing the spatial extent of non-perennial streams. Hydrological data from perennial and non-perennial reaches were compiled from a series of studies on headwater streams to expand available data for mapping and modeling efforts in the United States. Hydrologic data within this compilation include visually recorded observations of hydrological status (dry, isolated pools, interstitial flow, and continuous surface flow), point measurements of discharge (cubic meters per second), and logger-based measurements for the timing and duration of streamflow and drying. These data were compiled across a series of studies on headwater streams (drainage area ~2.6 km2 or less) and were used to characterize their hydrology. Hydrologic data within this compilation are organized into files based on type of hydrologic data and study area. The types of hydrologic data include visually recorded observations of hydrological status (dry, isolated pools, interstitial flow, and continuous surface flow), point measurements of discharge (cubic meters per second), and logger-based measurements for the timing and duration of streamflow and drying. The study areas included in the compilation include headwater streams in Kentucky (Robinson Forest), Illinois (Shawnee National Forest), Indiana (Hoosier National Forest), New Hampshire (Dodge Brook), New York (Balsam Lake Mountain), North Dakota (Pipestem), Ohio (Congress Run, Edgewood Preserve, Edge of Appalachia, Wayne National Forest), South Carolina (Carolina Sandhills, Sugarloaf Mountain, Sumter National Forest Enoree and Long Cane Districts), Tennessee (Big Ridge), Vermont (Hinesburg), Washington (Mt. Baker-Snoqualmie), and West Virginia (Coopers Rock). A more detailed description of the data files are included within the Data description.docx and Data Dictionary for logger data compilation.xlsx files.

The USGS compiles online access to water-resources data collected at approximately 1.5 million sites in all 50 States, the District of Columbia, Puerto Rico, the Virgin Islands, Guam, American Samoa and the Commonwealth of the Northern Mariana Islands.

The U.S. Geological Survey in cooperation with the University of New Hampshire and the University of New Brunswick mapped the nearshore regions off Los Angeles and San Diego, California using multibeam echosounders. Multibeam bathymetry and co-registered, corrected acoustic backscatter were collected in water depths ranging from about 3 to 900 m offshore Los Angeles and in water depths ranging from about 17 to 1230 m offshore San Diego. Continuous, 16-m spatial resolution, GIS ready format data of the entire Los Angeles Margin and San Diego Margin are available online as separate USGS Open-File Reports.

For ongoing research, the USGS has processed sub-regions within these datasets at finer resolutions. The resolution of each sub-region was determined by the density of soundings within the region. This Open-File Report contains the finer resolution multibeam bathymetry and acoustic backscatter data that the USGS, Western Region, Coastal and Marine Geology Team has processed into GIS ready formats as of April 2004. The data are available in ArcInfo GRID and XYZ formats. See the Los Angeles or San Diego maps for the sub-region locations.

These datasets in their present form were not originally intended for publication. The bathymetry and backscatter have data-collection and processing artifacts. These data are being made public to fulfill a Freedom of Information Act request. Care must be taken not to confuse artifacts with real seafloor morphology and acoustic backscatter.

[Summary provided by the USGS.]