In 2012, the CPUC ordered the development of a statewide map that is designed specifically for the purpose of identifying areas where there is an increased risk for utility associated wildfires. The development of the CPUC -sponsored fire-threat map, herein "CPUC Fire-Threat Map," started in R.08-11-005 and continued in R.15-05-006.

A multistep process was used to develop the statewide CPUC Fire-Threat Map. The first step was to develop Fire Map 1 (FM 1), an agnostic map which depicts areas of California where there is an elevated hazard for the ignition and rapid spread of powerline fires due to strong winds, abundant dry vegetation, and other environmental conditions. These are the environmental conditions associated with the catastrophic powerline fires that burned 334 square miles of Southern California in October 2007. FM 1 was developed by CAL FIRE and adopted by the CPUC in Decision 16-05-036.

FM 1 served as the foundation for the development of the final CPUC Fire-Threat Map. The CPUC Fire-Threat Map delineates, in part, the boundaries of a new High Fire-Threat District (HFTD) where utility infrastructure and operations will be subject to stricter fire‑safety regulations. Importantly, the CPUC Fire-Threat Map (1) incorporates the fire hazards associated with historical powerline wildfires besides the October 2007 fires in Southern California (e.g., the Butte Fire that burned 71,000 acres in Amador and Calaveras Counties in September 2015), and (2) ranks fire-threat areas based on the risks that utility-associated wildfires pose to people and property.

Primary responsibility for the development of the CPUC Fire-Threat Map was delegated to a group of utility mapping experts known as the Peer Development Panel (PDP), with oversight from a team of independent experts known as the Independent Review Team (IRT). The members of the IRT were selected by CAL FIRE and CAL FIRE served as the Chair of the IRT. The development of CPUC Fire-Threat Map includes input from many stakeholders, including investor-owned and publicly owned electric utilities, communications infrastructure providers, public interest groups, and local public safety agencies.

The PDP served a draft statewide CPUC Fire-Threat Map on July 31, 2017, which was subsequently reviewed by the IRT. On October 2 and October 5, 2017, the PDP filed an Initial CPUC Fire-Threat Map that reflected the results of the IRT's review through September 25, 2017. The final IRT-approved CPUC Fire-Threat Map was filed on November 17, 2017. On November 21, 2017, SED filed on behalf of the IRT a summary report detailing the production of the CPUC Fire-Threat Map(referenced at the time as Fire Map 2). Interested parties were provided opportunity to submit alternate maps, written comments on the IRT-approved map and alternate maps (if any), and motions for Evidentiary Hearings. No motions for Evidentiary Hearings or alternate map proposals were received. As such, on January 19, 2018 the CPUC adopted, via Safety and Enforcement Division's (SED) disposition of a Tier 1 Advice Letter, the final CPUC Fire-Threat Map.

Additional information can be found here.

Bringing under-represented histories to light has become a top priority in historic preservation because it helps to tell the full story of our history while also working to improve equity and build strong communities. Cape Cod has no shortage of these stories to highlight. Local preservation groups are expanding their historic inventory work to recognize previously overlooked stories, and new museums and exhibits in the region are bringing these stories into focus. This StoryMap aims to elevate the research done by others to uncover these stories, compiling them in a map that is accessible and can be incrementally expanded. It presents five themes, each related to an underrepresented group on Cape Cod. You can look at the big picture of all sites on the regional map, or you can select one theme and follow the stories within that theme, or you can choose a single site to explore. The specific sites in each theme were compiled with assistance from people in these communities, and the information comes from historic inventory forms, museum archives, and local and regional research efforts.

CPUC_Fire-Threat_Map_Tier_2

Credit report of Elevate Industries Inc contains unique and detailed export import market intelligence with it's phone, email, Linkedin and details of each import and export shipment like product, quantity, price, buyer, supplier names, country and date of shipment.

Geolocet's Administrative Boundaries Spatial Data serves as the gateway to visualizing geographic distributions and patterns with precision. The comprehensive dataset covers all European countries, encompassing the boundaries of each country, as well as its political and statistical divisions. Tailoring data purchases to exact needs is possible, allowing for the selection of individual levels of geography or bundling all levels for a country with a discount. The seamless integration of administrative boundaries onto digital maps transforms raw data into actionable insights.

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New approaches to lineage tracking have allowed the study of differentiation in multicellular organisms over many generations of cells. Understanding the phenotypic variability observed in these lineage trees requires new statistical methods. Whereas an invariant cell lineage, such as that for the nematode Caenorhabditis elegans, can be described by a lineage map, defined as the pattern of phenotypes overlaid onto the binary tree, a traditional lineage map is static and does not describe the variability inherent in the cell lineages of higher organisms. Here, we introduce lineage variability maps which describe the pattern of second-order variation in lineage trees. These maps can be undirected graphs of the partial correlations between every lineal position, or directed graphs showing the dynamics of bifurcated patterns in each subtree. We show how to infer these graphical models for lineages of any depth from sample sizes of only a few pedigrees. This required developing the generalized spectral analysis for a binary tree, the natural framework for describing tree-structured variation. When tested on pedigrees from C. elegans expressing a marker for pharyngeal differentiation potential, the variability maps recover essential features of the known lineage map. When applied to highly-variable pedigrees monitoring cell size in T lymphocytes, the maps show that most of the phenotype is set by the founder naive T cell. Lineage variability maps thus elevate the concept of the lineage map to the population level, addressing questions about the potency and dynamics of cell lineages and providing a way to quantify the progressive restriction of cell fate with increasing depth in the tree.

A description of the methodology is available here: https://www.oregon.gov/oha/PH/HEALTHYENVIRONMENTS/HEALTHYNEIGHBORHOODS/RADONGAS/Documents/Radon%20Risk%20Level%20Assignment.pdf

New 1:24,000-scale geologic mapping in the Storm King Mountain 7.5' quadrangle, in support of the USGS Western Colorado I-70 Corridor Cooperative Geologic Mapping Project, provides new data on the structure on the south margin of the White River uplift and the Grand Hogback and on the nature, history, and distribution of surficial geologic units. Rocks ranging from Holocene to Proterozoic in age are shown on the map. The Canyon Creek Conglomerate, a unit presently known to only occur in this quadrangle, is interpreted to have been deposited in a very steep sided local basin formed by dissolution of Pennsylvanian evaporite late in Tertiary time. At the top of the Late Cretaceous Williams Fork Formation is a unit of sandstone, siltstone, and claystone from which Late Cretaceous palynomorphs were obtained in one locality. This interval has been mapped previously as Ohio Creek Conglomerate, but it does not fit the current interpretation of the origin of the Ohio Creek. Rocks previously mapped as Frontier Sandstone and Mowry Shale are here mapped as the lower member of the Mancos Shale and contain beds equivalent to the Juana Lopez Member of the Mancos Shale in northwestern New Mexico. The Pennsylvanian Eagle Valley Formation in this quadrangle grades into Eagle Valley Evaporite as mapped by Kirkham and others (1997) in the Glenwood Springs area. The Storm King Mountain quadrangle spans the south margin of the White River uplift and crosses the Grand Hogback monocline into the Piceance basin. Nearly flat lying Mississippian through Cambrian sedimentary rocks capping the White River uplift are bent into gentle south dips and broken by faults at the edge of the uplift. South of these faults the beds dip moderately to steeply to the south and are locally overturned. These dips are interrupted by a structural terrace on which are superposed numerous gentle minor folds and faults. This terrace has an east-west extent similar to that of the Canyon Creek Conglomerate to the north. We interpret that the terrace formed by movement of Eagle Evaporite from below in response to dissolution and diapirism in the area underlain by the conglomerate. A low-angle normal fault dipping gently north near the north margin of the quadrangle may have formed also in response to diapirism and dissolution in the area of the Canyon Creek Conglomerate. Along the east edge of the quadrangle Miocene basalt flows are offset by faults along bedding planes in underlying south-dipping Cretaceous rocks, probably because of diapiric movement of evaporite into the Cattle Creek anticline (Kirkham and Widmann, 1997). Steep topography and weak rocks combine to produce a variety of geologic hazards in the quadrangle.

This publication is a preliminary map and geodatabase of the coseismic surface rupture and other coseismic features generated from the August 9, 2020, Mw 5.1 earthquake near Sparta, North Carolina. Geologic mapping facilitated by analysis of post-earthquake quality level 0 to 1 lidar, document the coseismic surface rupture, named the Little River fault, and other coseismic features. The Little River fault is traced for approximately 4 kilometers and cuts the regional Paleozoic fabric (mean foliation, 063°/57°), and the dominant strike of joint sets are 0°–10°, 130°–150° and 320°–340°. Individual fault strands occur in an en echelon pattern within an approximately 10-meter-wide zone. Trenches across the Little River fault document a thrust fault oriented 110°/45° with at least 10 centimeters (cm) of displacement. The Little River fault is marked by a flexure or scarp with a height of 5-30 cm and a local maximum height of 50 cm. Southwest-side-up displacement is consistent along the ...

IntroductionClimate Central’s Surging Seas: Risk Zone map shows areas vulnerable to near-term flooding from different combinations of sea level rise, storm surge, tides, and tsunamis, or to permanent submersion by long-term sea level rise. Within the U.S., it incorporates the latest, high-resolution, high-accuracy lidar elevation data supplied by NOAA (exceptions: see Sources), displays points of interest, and contains layers displaying social vulnerability, population density, and property value. Outside the U.S., it utilizes satellite-based elevation data from NASA in some locations, and Climate Central’s more accurate CoastalDEM in others (see Methods and Qualifiers). It provides the ability to search by location name or postal code.The accompanying Risk Finder is an interactive data toolkit available for some countries that provides local projections and assessments of exposure to sea level rise and coastal flooding tabulated for many sub-national districts, down to cities and postal codes in the U.S. Exposure assessments always include land and population, and in the U.S. extend to over 100 demographic, economic, infrastructure and environmental variables using data drawn mainly from federal sources, including NOAA, USGS, FEMA, DOT, DOE, DOI, EPA, FCC and the Census.This web tool was highlighted at the launch of The White House's Climate Data Initiative in March 2014. Climate Central's original Surging Seas was featured on NBC, CBS, and PBS U.S. national news, the cover of The New York Times, in hundreds of other stories, and in testimony for the U.S. Senate. The Atlantic Cities named it the most important map of 2012. Both the Risk Zone map and the Risk Finder are grounded in peer-reviewed science.Back to topMethods and QualifiersThis map is based on analysis of digital elevation models mosaicked together for near-total coverage of the global coast. Details and sources for U.S. and international data are below. Elevations are transformed so they are expressed relative to local high tide lines (Mean Higher High Water, or MHHW). A simple elevation threshold-based “bathtub method” is then applied to determine areas below different water levels, relative to MHHW. Within the U.S., areas below the selected water level but apparently not connected to the ocean at that level are shown in a stippled green (as opposed to solid blue) on the map. Outside the U.S., due to data quality issues and data limitations, all areas below the selected level are shown as solid blue, unless separated from the ocean by a ridge at least 20 meters (66 feet) above MHHW, in which case they are shown as not affected (no blue).Areas using lidar-based elevation data: U.S. coastal states except AlaskaElevation data used for parts of this map within the U.S. come almost entirely from ~5-meter horizontal resolution digital elevation models curated and distributed by NOAA in its Coastal Lidar collection, derived from high-accuracy laser-rangefinding measurements. The same data are used in NOAA’s Sea Level Rise Viewer. (High-resolution elevation data for Louisiana, southeast Virginia, and limited other areas comes from the U.S. Geological Survey (USGS)). Areas using CoastalDEM™ elevation data: Antigua and Barbuda, Barbados, Corn Island (Nicaragua), Dominica, Dominican Republic, Grenada, Guyana, Haiti, Jamaica, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, San Blas (Panama), Suriname, The Bahamas, Trinidad and Tobago. CoastalDEM™ is a proprietary high-accuracy bare earth elevation dataset developed especially for low-lying coastal areas by Climate Central. Use our contact form to request more information.Warning for areas using other elevation data (all other areas)Areas of this map not listed above use elevation data on a roughly 90-meter horizontal resolution grid derived from NASA’s Shuttle Radar Topography Mission (SRTM). SRTM provides surface elevations, not bare earth elevations, causing it to commonly overestimate elevations, especially in areas with dense and tall buildings or vegetation. Therefore, the map under-portrays areas that could be submerged at each water level, and exposure is greater than shown (Kulp and Strauss, 2016). However, SRTM includes error in both directions, so some areas showing exposure may not be at risk.SRTM data do not cover latitudes farther north than 60 degrees or farther south than 56 degrees, meaning that sparsely populated parts of Arctic Circle nations are not mapped here, and may show visual artifacts.Areas of this map in Alaska use elevation data on a roughly 60-meter horizontal resolution grid supplied by the U.S. Geological Survey (USGS). This data is referenced to a vertical reference frame from 1929, based on historic sea levels, and with no established conversion to modern reference frames. The data also do not take into account subsequent land uplift and subsidence, widespread in the state. As a consequence, low confidence should be placed in Alaska map portions.Flood control structures (U.S.)Levees, walls, dams or other features may protect some areas, especially at lower elevations. Levees and other flood control structures are included in this map within but not outside of the U.S., due to poor and missing data. Within the U.S., data limitations, such as an incomplete inventory of levees, and a lack of levee height data, still make assessing protection difficult. For this map, levees are assumed high and strong enough for flood protection. However, it is important to note that only 8% of monitored levees in the U.S. are rated in “Acceptable” condition (ASCE). Also note that the map implicitly includes unmapped levees and their heights, if broad enough to be effectively captured directly by the elevation data.For more information on how Surging Seas incorporates levees and elevation data in Louisiana, view our Louisiana levees and DEMs methods PDF. For more information on how Surging Seas incorporates dams in Massachusetts, view the Surging Seas column of the web tools comparison matrix for Massachusetts.ErrorErrors or omissions in elevation or levee data may lead to areas being misclassified. Furthermore, this analysis does not account for future erosion, marsh migration, or construction. As is general best practice, local detail should be verified with a site visit. Sites located in zones below a given water level may or may not be subject to flooding at that level, and sites shown as isolated may or may not be be so. Areas may be connected to water via porous bedrock geology, and also may also be connected via channels, holes, or passages for drainage that the elevation data fails to or cannot pick up. In addition, sea level rise may cause problems even in isolated low zones during rainstorms by inhibiting drainage.ConnectivityAt any water height, there will be isolated, low-lying areas whose elevation falls below the water level, but are protected from coastal flooding by either man-made flood control structures (such as levees), or the natural topography of the surrounding land. In areas using lidar-based elevation data or CoastalDEM (see above), elevation data is accurate enough that non-connected areas can be clearly identified and treated separately in analysis (these areas are colored green on the map). In the U.S., levee data are complete enough to factor levees into determining connectivity as well.However, in other areas, elevation data is much less accurate, and noisy error often produces “speckled” artifacts in the flood maps, commonly in areas that should show complete inundation. Removing non-connected areas in these places could greatly underestimate the potential for flood exposure. For this reason, in these regions, the only areas removed from the map and excluded from analysis are separated from the ocean by a ridge of at least 20 meters (66 feet) above the local high tide line, according to the data, so coastal flooding would almost certainly be impossible (e.g., the Caspian Sea region).Back to topData LayersWater Level | Projections | Legend | Social Vulnerability | Population | Ethnicity | Income | Property | LandmarksWater LevelWater level means feet or meters above the local high tide line (“Mean Higher High Water”) instead of standard elevation. Methods described above explain how each map is generated based on a selected water level. Water can reach different levels in different time frames through combinations of sea level rise, tide and storm surge. Tide gauges shown on the map show related projections (see just below).The highest water levels on this map (10, 20 and 30 meters) provide reference points for possible flood risk from tsunamis, in regions prone to them.

This dataset is one of eight datasets produced by this study. Four of the datasets predict the probability of detecting atrazine and(or) desethyl-atrazine (a breakdown product of atrazine) in ground water in Colorado; the other four predict the probability of detecting elevated concentrations of nitrate in ground water in Colorado. The four datasets that predict the probability of atrazine and(or) desethyl-atrazine (atrazine/DEA) are differentiated by whether or not they incorporated atrazine use and whether or not they incorporated hydrogeomorphic regions. The four datasets that predict the probability of elevated concentrations of nitrate are differentiated by whether or not they incorporated fertilizer use and whether or not they incorporated hydrogeomorphic regions. Each of the eight datasets has its own unique strengths and weaknesses. The user is cautioned to read Rupert (2003, Probability of detecting atrazine/desethyl-atrazine and elevated concentrations of nitrate in ground water in Colorado: U.S. Geological Survey Water-Resources Investigations Report 02-4269, 35 p., https://water.usgs.gov/pubs/wri/wri02-4269/) to determine if he(she) is using the most appropriate dataset for his(her) particular needs. This dataset specifically predicts the probability of detecting elevated concentrations of nitrate in ground water in Colorado with hydrogeomorphic regions included and fertilizer use not included. The following text was extracted from Rupert (2003). Draft Federal regulations may require that each State develop a State Pesticide Management Plan for the herbicides atrazine, alachlor, metolachlor, and simazine. Maps were developed that the State of Colorado could use to predict the probability of detecting atrazine/DEA in ground water in Colorado. These maps can be incorporated into the State Pesticide Management Plan and can help provide a sound hydrogeologic basis for atrazine management in Colorado. Maps showing the probability of detecting elevated nitrite plus nitrate as nitrogen (nitrate) concentrations in ground water in Colorado also were developed because nitrate is a contaminant of concern in many areas of Colorado. Maps showing the probability of detecting atrazine/DEA at or greater than concentrations of 0.1 microgram per liter and nitrate concentrations in ground water greater than 5 milligrams per liter were developed as follows: (1) Ground-water quality data were overlaid with anthropogenic and hydrogeologic data by using a geographic information system (GIS) to produce a dataset in which each well had corresponding data on atrazine use, fertilizer use, geology, hydrogeomorphic regions, land cover, precipitation, soils, and well construction. These data then were downloaded to a statistical software package for analysis by logistic regression. (2) Relations were observed between ground-water quality and the percentage of land-cover categories within circular regions (buffers) around wells. Several buffer sizes were evaluated; the buffer size that provided the strongest relation was selected for use in the logistic regression models. (3) Relations between concentrations of atrazine/DEA and nitrate in ground water and atrazine use, fertilizer use, geology, hydrogeomorphic regions, land cover, precipitation, soils, and well-construction data were evaluated, and several preliminary multivariate models with various combinations of independent variables were constructed. (4) The multivariate models that best predicted the presence of atrazine/DEA and elevated concentrations of nitrate in ground water were selected. (5) The accuracy of the multivariate models was confirmed by validating the models with an independent set of ground-water quality data. (6) The multivariate models were entered into a geographic information system and the probability GRIDS were constructed.

The digital map database, compiled from previously published and unpublished data, and new mapping by the authors, represents the general distribution of bedrock and surficial deposits in the House Rock Spring area. Together with the accompanying text, it provides current information on the geologic structure and stratigraphy of the area covered. The database delineates map units that are identified by general age, lithology, and geomorphology following the spatial resolution (scale) of the database to 1:24,000. The content and character of the database, as well as three methods of obtaining the database, are described below.

This digital map database is compiled from unpublished data and new mapping by the authors, represents the general distribution of surficial and bedrock geology in the mapped area. Together with the accompanying pamphlet, it provides current information on the geologic structure and stratigraphy of the area. The database delineate map units that are identified by age and lithology following the stratigraphic nomenclature of the U.S. Geological Survey. The scale of the source maps limits the spatial resolution of the database to 1:24,000 or smaller.

This report consists of a set of geologic map database files (ARC/ INFO coverages) and supporting text and plot files. In addition, the report includes two sets of plot files(Post Script and PDF format) that will generate map sheets and pamphlets similar to a traditional USGS Miscellaneous Field Studies Report. These files are described in the explanatory pamphlets (hrsgeo.doc, hrsgeo. pdf, or hrsgeo.txt). The base layer used in the preparation of the geologic map plot files was derived from a Digital Raster Graphic version of a standard USGS 7.5' quadrangle. This raster image was converted to Grid format in ARC/INFO, trimmed and converted to a GeoTIFF image. The resultant TIFF image was combined with geologic data to produce the final map image in Illustrator 8.0.

This archive contains the input data for the conceptual well locations for the logistic mapping. Data were computed for either the well location or within a buffer area of the well location, as specified in the parameter definition.

This indicator reflects the total number of children aged 0-6 who are tested for the presence of blood lead in a calendar year. Source: Maryland Department of the Environment, Lead Poisoning Prevention Program Years Available: 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019

ADMMR map collection: Old Reliable Copper Mine Devlopment on 100 Foot Level, Stope Assays and Assays for Vertical Raise; 1 in. to 20 feet; 22 x 17 in.

This part of DS 781 presents data for the geologic and geomorphic map of the Offshore of Point Reyes map area, California. The vector data file is included in "Geology_OffshorePointReyes.zip," which is accessible from http://pubs.usgs.gov/ds/781/OffshorePointReyes/data_catalog_OffshorePointReyes.html.

Marine geology and geomorphology was mapped in the Offshore of Point Reyes map area from approximate Mean High Water (MHW) to the 3-nautical-mile limit of California’s State Waters. MHW is defined at an elevation of 1.46 m above the North American Vertical Datum of 1988 (NAVD 88) (Weber and others, 2005). Offshore geologic units were delineated on the basis of integrated analyses of adjacent onshore geology with multibeam bathymetry and backscatter imagery, seafloor-sediment and rock samples (Reid and others, 2006), digital camera and video imagery, and high-resolution seismic-reflection profiles.

The onshore bedrock mapping was compiled from Galloway (1977), Clark and Brabb (1997), and Wagner and Gutierrez (2010). Quaternary mapping was compiled from Witter and others (2006) and Wagner and Gutierrez (2010), with unit contacts modified based on analysis of 2012 LiDAR imagery; and additional Quaternary mapping by M.W. Manson.

The morphology and the geology of the Offshore of Point Reyes map area result from the interplay between tectonics, sea-level rise, local sedimentary processes, and oceanography. The Point Reyes Fault Zone runs through the map area and is an offshore curvilinear reverse Fault Zone (Hoskins and Griffiths, 1971; McCulloch, 1987; Heck and others, 1990; Stozek, 2012) that likely connects with the western San Gregorio fault further to the south (Ryan and others, 2008), making it part of the San Andreas Fault System. The Point Reyes Fault Zone is characterized by a 5 to 11 km-wide zone that is associated with two main fault structures, the Point Reyes Fault and the Western Point Reyes Fault (fig. 1).

Tectonic influences impacting shelf morphology and geology are related to local faulting, folding, uplift, and subsidence. Granitic basement rocks are offset about 1.4 km on the Point Reyes thrust fault offshore of the Point Reyes headland (McCulloch, 1987), and this uplift combined with west-side-up offset of the San Andreas Fault (Grove and Niemi, 2005) resulted in uplift of the Point Reyes Peninsula, including the adjacent Bodega and Tomales shelf. The Western Point Reyes Fault is defined by a broad anticlinal structure visible in both industry and high-resolution seismic datasets and exhibits that same sense of vergence as the Point Reyes Fault. The deformation associated with north-side-up motion across the Point Reyes Fault Zone has resulted in a distinct bathymetric gradient across the Point Reyes Fault, with a shallow bedrock platform to the north and east, and a deeper bedrock platform to the south.

Late Pleistocene uplift of marine terraces on the southern Point Reyes Peninsula suggests active deformation west of the San Andreas Fault (Grove and others, 2010) on offshore structures. The Point Reyes Fault and related structures may be responsible for this recent uplift of the Point Reyes Peninsula, however, the distribution and age control of Pleistocene strata in the Offshore of Point Reyes map area is not well constrained and therefore it is difficult to directly link the uplift onshore with the offshore Point Reyes Fault structures. Pervasive stratal thinning within inferred uppermost Pliocene and Pleistocene (post-Purisima) units above the Western Point Reyes Fault anticline suggests Quaternary active shortening above a curvilinear northeast to north-dipping Point Reyes Fault zone. Lack of clear deformation within the uppermost Pleistocene and Holocene unit suggests activity along the Point Reyes Fault zone has diminished or slowed since 21,000 years ago. In this map area the cumulative (post-Miocene) slip-rate on the Point Reyes Fault Zone is poorly constrained, but is estimated to be 0.3 mm/yr based on vertical offset of granitic basement rocks (McCulloch, 1987; Wills and others, 2008).

With the exception of the bathymetric gradient across the Point Reyes Fault, the offshore part of this map area is largely characterized by a relatively flat (<0.8°) bedrock platform. The continental shelf is quite wide in this area, with the shelfbreak located west of the Farallon high , about 35 km offshore. Sea level has risen about 125 to 130 m over about the last 21,000 years (for example, Lambeck and Chappell, 2001; Peltier and Fairbanks, 2005), leading to broadening of the continental shelf, progressive eastward migration of the shoreline and wave-cut platform, and associated transgressive erosion and deposition (for example, Catuneanu, 2006). Land-derived sediment was carried into this dynamic setting, and then subjected to full Pacific Ocean wave energy and strong curr... Visit https://dataone.org/datasets/3bdc07a6-75ea-44cd-a877-8f5a89f16312 for complete metadata about this dataset.

Surficial geology (geo7_2ag).. Visit https://dataone.org/datasets/69c5892e-94d8-49f5-8f64-892d3b4f7e43 for complete metadata about this dataset.

description: This part of DS 781 presents data for folds for the geologic and geomorphic map of the Offshore of Tomales Point map area, California. The vector data file is included in "Folds_OffshoreTomalesPoint.zip," which is accessible from http://pubs.usgs.gov/ds/781/OffshoreTomalesPoint/data_catalog_OffshoreTomalesPoint.html. The Point Reyes Peninsula is bounded to the south and west in the offshore by the north- and east-dipping Point Reyes Thrust Fault (McCulloch, 1987; Heck and others, 1990), which lies about 20 km west of Tomales Point. Granitic basement rocks are offset about 1.4 km on this thrust fault offshore of Point Reyes (McCulloch, 1987), and this uplift combined with west-side-up offset on the San Andreas Fault (Grove and Niemi, 2005) resulted in uplift of the Point Reyes Peninsula, including Tomales Point and the adjacent continental shelf. Grove and others (2010) reported uplift rates of as much as 1 mm/yr for the south flank of the Point Reyes Peninsula based on marine terraces, but reported no datable terrace surfaces that could constrain uplift for the flight of 4-5 terraces exposed farther north along Tomales Point. Folds were primarily mapped by interpretation of seismic reflection profile data (see field activity S-15-10-NC). The seismic reflection profiles were collected between 2007 and 2010. References Cited Grove, K., and Niemi, T.M., 2005, Late Quaternary deformation and slip rates in the northern San Andreas fault zone at Olema Valley, Marin County, California: Tectonophysics, v. 401, p. 231-250. Grove, K, Sklar, L.S., Scherer, A.M., Lee, G., and Davis, J., 2010, Accelerating and spatially-varying crustal uplift and its geomorphic expression, San Andreas fault zone north of San Francisco, California: Tectonophysics, v. 495, p. 256-268. Heck, R.G., Edwards, E.B., Kronen, J.D., Jr., and Willingham, C.R., 1990, Petroleum potential of the offshore outer Santa Cruz and Bodega basins, California, in Garrison, R.E., Greene, H.G., Hicks, K.R., Weber, G.E., and Wright, T.L., eds. Geology and tectonics of the central California coastal region, San Francisco to Monterey: Pacific Section, American Association of Petroleum Geologists Bulletin GB67, p. 143-164. McCulloch, D.S., 1987, Regional geology and hydrocarbon potential of offshore central California, in Scholl, D.W., Grantz, A., and Vedder, J.G., eds., Geology and Resource Potential of the Continental Margin of Western North America and Adjacent Oceans Beaufort Sea to Baja California: Houston, Texas, Circum-Pacific Council for Energy and Mineral Resources, Earth Science Series, v. 6., p. 353-401.; abstract: This part of DS 781 presents data for folds for the geologic and geomorphic map of the Offshore of Tomales Point map area, California. The vector data file is included in "Folds_OffshoreTomalesPoint.zip," which is accessible from http://pubs.usgs.gov/ds/781/OffshoreTomalesPoint/data_catalog_OffshoreTomalesPoint.html. The Point Reyes Peninsula is bounded to the south and west in the offshore by the north- and east-dipping Point Reyes Thrust Fault (McCulloch, 1987; Heck and others, 1990), which lies about 20 km west of Tomales Point. Granitic basement rocks are offset about 1.4 km on this thrust fault offshore of Point Reyes (McCulloch, 1987), and this uplift combined with west-side-up offset on the San Andreas Fault (Grove and Niemi, 2005) resulted in uplift of the Point Reyes Peninsula, including Tomales Point and the adjacent continental shelf. Grove and others (2010) reported uplift rates of as much as 1 mm/yr for the south flank of the Point Reyes Peninsula based on marine terraces, but reported no datable terrace surfaces that could constrain uplift for the flight of 4-5 terraces exposed farther north along Tomales Point. Folds were primarily mapped by interpretation of seismic reflection profile data (see field activity S-15-10-NC). The seismic reflection profiles were collected between 2007 and 2010. References Cited Grove, K., and Niemi, T.M., 2005, Late Quaternary deformation and slip rates in the northern San Andreas fault zone at Olema Valley, Marin County, California: Tectonophysics, v. 401, p. 231-250. Grove, K, Sklar, L.S., Scherer, A.M., Lee, G., and Davis, J., 2010, Accelerating and spatially-varying crustal uplift and its geomorphic expression, San Andreas fault zone north of San Francisco, California: Tectonophysics, v. 495, p. 256-268. Heck, R.G., Edwards, E.B., Kronen, J.D., Jr., and Willingham, C.R., 1990, Petroleum potential of the offshore outer Santa Cruz and Bodega basins, California, in Garrison, R.E., Greene, H.G., Hicks, K.R., Weber, G.E., and Wright, T.L., eds. Geology and tectonics of the central California coastal region, San Francisco to Monterey: Pacific Section, American Association of Petroleum Geologists Bulletin GB67, p. 143-164. McCulloch, D.S., 1987, Regional geology and hydrocarbon potential of offshore central California, in Scholl, D.W., Grantz, A., and Vedder, J.G., eds., Geology and Resource Potential of the Continental Margin of Western North America and Adjacent Oceans Beaufort Sea to Baja California: Houston, Texas, Circum-Pacific Council for Energy and Mineral Resources, Earth Science Series, v. 6., p. 353-401.

description: This part of DS 781 presents data for faults for the geologic and geomorphic map of the Offshore of Tomales Point map area, California. The vector data file is included in "Faults_OffshoreTomalesPoint.zip," which is accessible from http://pubs.usgs.gov/ds/781/OffshoreTomalesPoint/data_catalog_OffshoreTomalesPoint.html. The Point Reyes Peninsula is bounded to the south and west in the offshore by the north- and east-dipping Point Reyes Thrust Fault (McCulloch, 1987; Heck and others, 1990), which lies about 20 km west of Tomales Point. Granitic basement rocks are offset about 1.4 km on this thrust fault offshore of Point Reyes (McCulloch, 1987), and this uplift combined with west-side-up offset on the San Andreas Fault (Grove and Niemi, 2005) resulted in uplift of the Point Reyes Peninsula, including Tomales Point and the adjacent continental shelf. Grove and others (2010) reported uplift rates of as much as 1 mm/yr for the south flank of the Point Reyes Peninsula based on marine terraces, but reported no datable terrace surfaces that could constrain uplift for the flight of 4-5 terraces exposed farther north along Tomales Point. Faults were primarily mapped by interpretation of seismic reflection profile data (see field activity S-15-10-NC). The seismic reflection profiles were collected between 2007 and 2010. References Cited Grove, K., and Niemi, T.M., 2005, Late Quaternary deformation and slip rates in the northern San Andreas fault zone at Olema Valley, Marin County, California: Tectonophysics, v. 401, p. 231-250. Grove, K, Sklar, L.S., Scherer, A.M., Lee, G., and Davis, J., 2010, Accelerating and spatially-varying crustal uplift and its geomorphic expression, San Andreas fault zone north of San Francisco, California: Tectonophysics, v. 495, p. 256-268. Heck, R.G., Edwards, E.B., Kronen, J.D., Jr., and Willingham, C.R., 1990, Petroleum potential of the offshore outer Santa Cruz and Bodega basins, California, in Garrison, R.E., Greene, H.G., Hicks, K.R., Weber, G.E., and Wright, T.L., eds. Geology and tectonics of the central California coastal region, San Francisco to Monterey: Pacific Section, American Association of Petroleum Geologists Bulletin GB67, p. 143-164. McCulloch, D.S., 1987, Regional geology and hydrocarbon potential of offshore central California, in Scholl, D.W., Grantz, A., and Vedder, J.G., eds., Geology and Resource Potential of the Continental Margin of Western North America and Adjacent Oceans Beaufort Sea to Baja California: Houston, Texas, Circum-Pacific Council for Energy and Mineral Resources, Earth Science Series, v. 6., p. 353-401.; abstract: This part of DS 781 presents data for faults for the geologic and geomorphic map of the Offshore of Tomales Point map area, California. The vector data file is included in "Faults_OffshoreTomalesPoint.zip," which is accessible from http://pubs.usgs.gov/ds/781/OffshoreTomalesPoint/data_catalog_OffshoreTomalesPoint.html. The Point Reyes Peninsula is bounded to the south and west in the offshore by the north- and east-dipping Point Reyes Thrust Fault (McCulloch, 1987; Heck and others, 1990), which lies about 20 km west of Tomales Point. Granitic basement rocks are offset about 1.4 km on this thrust fault offshore of Point Reyes (McCulloch, 1987), and this uplift combined with west-side-up offset on the San Andreas Fault (Grove and Niemi, 2005) resulted in uplift of the Point Reyes Peninsula, including Tomales Point and the adjacent continental shelf. Grove and others (2010) reported uplift rates of as much as 1 mm/yr for the south flank of the Point Reyes Peninsula based on marine terraces, but reported no datable terrace surfaces that could constrain uplift for the flight of 4-5 terraces exposed farther north along Tomales Point. Faults were primarily mapped by interpretation of seismic reflection profile data (see field activity S-15-10-NC). The seismic reflection profiles were collected between 2007 and 2010. References Cited Grove, K., and Niemi, T.M., 2005, Late Quaternary deformation and slip rates in the northern San Andreas fault zone at Olema Valley, Marin County, California: Tectonophysics, v. 401, p. 231-250. Grove, K, Sklar, L.S., Scherer, A.M., Lee, G., and Davis, J., 2010, Accelerating and spatially-varying crustal uplift and its geomorphic expression, San Andreas fault zone north of San Francisco, California: Tectonophysics, v. 495, p. 256-268. Heck, R.G., Edwards, E.B., Kronen, J.D., Jr., and Willingham, C.R., 1990, Petroleum potential of the offshore outer Santa Cruz and Bodega basins, California, in Garrison, R.E., Greene, H.G., Hicks, K.R., Weber, G.E., and Wright, T.L., eds. Geology and tectonics of the central California coastal region, San Francisco to Monterey: Pacific Section, American Association of Petroleum Geologists Bulletin GB67, p. 143-164. McCulloch, D.S., 1987, Regional geology and hydrocarbon potential of offshore central California, in Scholl, D.W., Grantz, A., and Vedder, J.G., eds., Geology and Resource Potential of the Continental Margin of Western North America and Adjacent Oceans Beaufort Sea to Baja California: Houston, Texas, Circum-Pacific Council for Energy and Mineral Resources, Earth Science Series, v. 6., p. 353-401.

Used below layers to create this Map.https://gis.dallascityhall.com/wwwgis/rest/services/Mva_public/MarketValueAnalysis/MapServerhttps://dallasgis.maps.arcgis.com/home/item.html?id=c2cc6422e7964f3a9be1fbbcba5d0a05https://dallasgis.maps.arcgis.com/home/item.html?id=e3b042eb54974b348c8e39d45e40bf7e#overview'Percentage Households with No Internet Access' value is calculated. Sum(Households with No Computer, Households with Computer and No Internet Subscription fields) / (Total Households)MVA Clusters:Reinvestment Fund’s cluster analysis revealed nine market types, characterized as follows:Regional Choice “A”: Highest home values, largest level of new construction, high owner occupancy levels, and little housing distress (such as residential vacancy and foreclosure).Regional Choice “B”: Elevated home values, highest amounts of rehab. permits, highest levels of owner occupancy, and little housing distress.Regional Choice “C”: Elevated home values, above average levels of new construction, high levels of renter occupancy, and little housing distress.Steady “D”: Double average home values, high levels of rehab. permits, more owners than renters, and low levels of foreclosure and residential vacancy.Steady “E”: About average home values, highest household density, highest levels of renter occupancy, some residential vacancy and foreclosure.Steady “F”: Home values slightly below the citywide average, little new construction, more owners than renters, and about average levels of foreclosure and residential vacancy.Transitional “G”: Below average home values, little new construction, more renters than owners, and highest levels of subsidized rentals.Transitional “H”: Home values well below the citywide average, little new construction, more owners than renters, elevated levels of residential vacancy and foreclosure.Distressed “I”: Lowest home values in Dallas, slightly below average levels of new construction, about an even share of owners and renters, the highest levels of residential code violation liens, vacancy, and foreclosure.