Historical maps contain a wealth of information not generally available, but they must be referenced to well-known coordinate systems for maximum use in spatial analysis. Existing georeferencing tools are essentially manual, requiring considerable data entry, much panning and zooming, and precise on-screen digitizing. Here we present alternative approaches based on pattern-matching and spatial computing intended to overcome the inefficiencies of standard tools. We also describe and make available two computer programs implementing the methods discussed. The first, designed for large-scale quadrangles, locates map boundaries, finds ground control points, and produces georeferenced images without operator assistance. Experiments show that quadrangle georeferencing can be reliably automated (88% success rate in our tests). A second program, developed for general maps at any scale, uses self-learning and other approaches to overcome most of the manual aspects of georeferencing. Both programs find control points with single-pixel accuracy, yield transform errors on the order of map linewidth, and can produce warped or unwarped images as desired.

This map displays points representing projects receiving funding through the Multimodal Transportation Fund or Transportation Alternatives Program that were approved in 2014-2016. Each point tells the project's sponsor, funding source, and funding amount in addition to showing whether it includes attributes of streetscape additions, sidewalk improvements, ADA-compliant curb ramps, off-road trail, shared-use path, on-road bike facilities, or stormwater management. The map is implemented for more effective viewing in this application.There is no update cycle for this map.

The Wilkinson Microwave Anisotropy Probe (WMAP) is designed to produce all-sky maps of the cosmic microwave background (CMB) anisotropy. The WMAP 9-Year CMB-Free Point Source Catalog contained herein has information on 502 point sources in three frequency bands (41, 61 and 94 GHz, also known as the Q, V, and W bands, respectively) based on data from the entire 9 years of the WMAP sky survey from 10 Aug 2001 0:00 UT to 10 Aug 2010 0:00 UT, inclusive. The CMB-free method of point source identification was originally applied to one-year and three-year V- and W-band maps by Chen & Wright (2008, ApJ, 681, 747) and to five-year V- and W-band maps by Wright et al. (2009, ApJS, 180, 283). The method used here is that applied to five-year Q-, V-, and W-band maps by Chen & Wright (2009, ApJ, 694, 222) and to seven-year Q-, V-, and W-band maps by Gold et al. (2011, ApJS, 192, 15). The V- and W-band maps are smoothed to Q-band resolution. An internal linear combination (ILC) map (see Section 5.3.3 of the reference paper) is then formed from the three maps using weights such that CMB fluctuations are removed, flat-spectrum point sources are retained with fluxes normalized to Q-band, and the variance of the ILC map is minimized. The ILC map is filtered to reduce noise and suppress large angular scale structure. Peaks in the filtered map that are > 5 sigma and outside of the nine-year point source catalog mask are identified as point sources, and source positions are obtained by fitting the beam profile plus a baseline to the filtered map for each source. For the nine- year analysis, the position of the brightest pixel is adopted instead of the fit position in rare instances where they differ by > 0.1 degrees. Source fluxes are estimated by integrating the Q, V, and W temperature maps within 1.25 degrees of each source position, with a weighting function to enhance the contrast of the point source relative to background fluctuations, and applying a correction for Eddington bias due to noise (sometimes called "deboosting"). The authors identify possible 5-GHz counterparts to the WMAP sources found by cross-correlating with the GB6 (Gregory et al. 1996, ApJS, 103, 427), PMN (Griffith et al. 1994, ApJS, 90, 179; Griffith et al. 1995, ApJS, 97, 347; Wright et al. 1994, ApJS, 94, 111; Wright et al. 1996, ApJS, 103, 145), Kuehr et al. (1981, A&AS, 45, 367), and Healey et al. (2009, AJ, 138, 1032) catalogs. A 5-GHz source is identified as a counterpart if it lies within 11 arcminutes of the WMAP source position (the mean WMAP source position uncertainty is 4 arcminutes). When two or more 5 GHz sources are within 11 arcminutes, the brightest is assumed to be the counterpart and a multiple identification flag is entered in the catalog. A separate 9-year Point Source Catalog (available in Browse as the WMAPPTSRC table) has information on 501 point sources in five frequency bands from 23 to 94 GHz that were found using an alternative method. The two catalogs have 387 sources in common. As noted by Gold et al. (2011, ApJS, 192, 15), differences in the source populations detected by the two search methods are largely caused by Eddington bias in the five-band source detections due to CMB fluctuations and noise. At low flux levels, the five-band method tends to detect point sources located on positive CMB fluctuations and to overestimate their fluxes, and it tends to miss sources located in negative CMB fluctuations. Other point source detection methods have been applied to WMAP data and have identified sources not found by our methods (e.g., Scodeller et al. (2012, ApJ, 753, 27); Lanz (2012, ADASS 7); Ramos et al. (2011, A&A, 528, A75), and references therein). For more details of how the point source catalogs were constructed, see Section 5.2.2 of the reference paper. This table was last updated by the HEASARC in January 2013 based on an electronic version of Table 19 from the reference paper which was obtained from the LAMBDA web site, the file http://lambda.gsfc.nasa.gov/data/map/dr5/dfp/ptsrc/wmap_ptsrc_catalog_cmb_free_9yr_v5.txt. The source_flag values of 'M' in this file were changed to the 'a' values that were used in the printed version of this table. This is a service provided by NASA HEASARC .

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 Californiaâ  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 (<0.8à °) 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 currents before deposition or offshore transport. Much of the inner shelf bedrock platform is composed of Tertiary marine sedimentary rocks, which are underlain by Salinian granitic and metamorphic basement rocks, including the Late Cretaceous porphyritic granite (unit Kgg), which outcrops on the seafloor south of the Point Reyes headland. Unit Kgg appears complexly fractured, similar to onshore exposures, with a distinct massive, bulbous texture in multibeam imagery. The Tertiary strata overlying the granite form the core of the Point Reyes syncline (Weaver, 1949) and include the early Eocene Point Reyes Conglomerate (unit Tpr), mid- to late Miocene Monterey Formation (unit Tm), late Miocene Santa Margarita Formation (unit Tsm), late Miocene Santa Cruz Mudstone (unit Tsc), and late Miocene to early Pliocene Purisima Formation (unit Tp). The Point Reyes Conglomerate is exposed on the seafloor adjacent to onshore outcrops on the Point Reyes headland and has a distinct massive texture with some bedding planes visible, but the strata are highly fractured. Based on stratigraphic correlations from seismic reflection data and onshore wells, combined with multibeam imagery, we infer rocks of the early Eocene Point Reyes Conglomerate extend at least 6 km northwest from onshore exposures at Point Reyes headland. The absence of unit Tsc in onshore wells (Clark and Brabb, 1997) suggests these rocks are unlikely to occur within the Tertiary section of this map area, north of the Point Reyes Fault. In this map area, unit Tu represents seafloor outcrops of a middle Miocene to upper Pliocene sequence overlying unit Tpr, that may include units Tm, Tsm, and Tp. Seafloor exposures of unit Tu are characterized by distinct rhythmic bedding where beds are dipping and by a mottled texture where those beds become flat-lying. Modern nearshore sediments are mostly sand (unit Qms and Qsw) and a mix of sand, gravel, and cobbles (units Qmsc and Qmsd). The more coarse-grained sands and gravels (units Qmsc and Qmsd) are primarily recognized on the basis of bathymetry and high backscatter. The emergent bedrock platform north and west of the Point Reyes headland is heavily scoured, resulting in large areas of unit Qmsc and associated Qmsd. Both Qmsc and Qmsd typically have abrupt landward contacts with bedrock and form irregular to lenticular exposures that are commonly elongate in the shore-normal direction. Contacts between units Qmsc and Qms are typically gradational. Unit Qmsd forms erosional lags in scoured depressions that are bounded by relatively sharp and less commonly diffuse contacts with unit Qms horizontal sand sheets. These depressions are typically a few tens of centimeters deep and range in size from a few 10's of meters to more than 1 km2. There is an area of high-backscatter, and rough seafloor southeast of the Point Reyes headland that is notable in that it includes several small, irregular "lumps", with as much as 1 m of positive relief above the seafloor (unit Qsr). Unit Qsr occurs in water depths between 50 and 60 meters, with individual lumps randomly distributed to west-trending. This area on seismic-reflection data shows this lumpy material rests on several meters of latest Pleistocene to Holocene sediment and is thus not bedrock outcrop. Rather, it seems likely that this lumpy material is marine debris, possibly derived from one (or more) of the more than 60 shipwrecks offshore of the Point Reyes Peninsula between 1849 and 1940 (National Park Service, 2012). It is also conceivable that this lumpy terrane consists of biological "hardgrounds". Video transect data crossing unit Qsr near the Point Reyes headland was of insufficient quality to distinguish between these above alternatives. A transition to more fine-grained marine sediments (unit Qmsf) occurs around 50â  60 m depth within most of the map area, however, directly south and east of Drakes Estero, backscatter and seafloor sediment samples (Chin and others, 1997) suggest fine-grained sediments extend into water depths as shallow as 30 m. Unit Qmsf is commonly extensively bioturbated and consists primarily of mud and muddy sand. These fine-grained sediments are inferred to have been derived from the Drakes Estero estuary or from the San Francisco Bay to the south, via predominantly northwest flow at the seafloor (Noble and Gelfenbaum, 1990). References Cited Catuneanu, O., 2006, Principles of Sequence Stratigraphy: Amsterdam, Elsevier, 375 p. Chin, J.L., Karl, H.A., and Maher, N.M., 1997, Shallow subsurface geology of the continental shelf, Gulf of the Farallones, California, and its relationship to surficial seafloor characteristics: Marine Geology, v. 137, p. 251-269. Clark, J.C., and Brabb, E.E., 1997, Geology of the Point Reyes National Seashore and vicinity: U.S. Geological Survey Open-File Report 97-456, scale 1:48,000. Galloway, A.J., 1977, Geology of the Point Reyes Peninsula Marin County, California: California Geological Survey Bulletin 202, scale 1:24,000. Grove, K. and Niemi, T., 2005, Late Quaternary deformation and slip rates in the northern San

Go to https://afdc.energy.gov/stations/#/find/nearest to access the full database of alternative fuel station locations nationwide, collected and maintained by the U.S. Department of Energy National Renewable Energy Laboratory. A station appears as one point in the data and on the map, regardless of the number of fuel dispensers or charging outlets at that location. For EV charging stations for example, the data includes the number of number of charging ports available at the specific station.

How does your organization use this dataset? What other NYSERDA or energy-related datasets would you like to see on Open NY? Let us know by emailing OpenNY@nyserda.ny.gov.

Urban greenery has been shown to impact the quality of life in our urbanizing societies. While greenery is traditionally mapped top-down, alternative computational approaches have emerged for mapping greenery from the street level to mimic human sight. Despite the variety of these novel mapping approaches, it has remained unclear how well they reflect human perception in reality. We compared a range of both novel and traditional mapping methods with the self-reported perception of urban greenery at randomly selected study sites across Helsinki, the capital of Finland. The mapping methods included both image segmentation and point cloud-based methods to capture human perspective as well as traditional approaches taking the top-down perspective, i.e., land cover and remote sensing-based mapping methods. The results suggest that all the methods tested are strongly associated with the human perception of greenery at the street-level. However, mapped greenery values were consistently lower than the perceived values. Our results support the use of semantic image segmentation methods over color segmentation methods for greenery extraction to be closer to human perception. Point cloud-based approaches and top-down methods can be used as alternatives to image segmentation in case data coverage for the latter is limited. The results highlight a further research need for a comprehensive evaluation on how human perspective should be mimicked in different temporal and spatial conditions.

Inventory survey on Kirwin National Wildlife Refuge to develop a current baseline vegetation map. The completed vegetation map will aid in facilitating evaluation of management alternatives, aid in the prioritization of management activities, and contribute to monitoring progress toward achieving Comprehensive Conservation Plan (CCP) objectives. This reference houses the final vegetation shapefiles, as well as the accuracy assessment point shapefiles, as a single zipped folder.

Mapping of environmental variables often relies on map accuracy assessment through cross-validation with the data used for calibrating the underlying mapping model. When the data points are spatially clustered, conventional cross-validation leads to optimistically biased estimates of map accuracy. Several papers have promoted spatial cross-validation as a means to tackle this over-optimism. Many of these papers blame spatial autocorrelation as the cause of the bias and propagate the widespread misconception that spatial proximity of calibration points to validation points invalidates classical statistical validation of maps. In the paper related to these data, we present and evaluate alternative cross-validation approaches for assessing map accuracy from clustered sample data.

The study area is western Europe, constrained in the north at 52° latitude and at -10° and 24° longitude The projection is IGNF:ETRS89LAEA (Lambert azimuthal equal area projection).

Files:

agb.tif = above ground biomass (AGB) map from version 3 of the 2017 CCI-Biomass product (https://catalogue.ceda.ac.uk/uuid/5f331c418e9f4935b8eb1b836f8a91b8) AGBstack.tif = covariates used for predicting AGB aggArea.tif = coarse grid used for simulation in the model-based methods ocs.tif = soil organic carbon stock (OCS) map (0-30 cm) from Soilgrids (https://www.isric.org/explore/soilgrids) OCSstack.tif = covariates used for predicting OCS strata.xxx = 100 compact geo-strata (ESRI shape) created with the spcosa package; used for generating clustered samples TOTmask.tif = mask of the area covered by the covariates

Details and data sources of the covariates in AGBstack.tif and OCSstack.tif:

Name

Description

Source

Note

ai

Aridity Index

https://chelsa-climate.org/downloads/

    Version 2.1

bio1

Mean annual air temperature [°C]

    https://chelsa-climate.org/downloads/
    Version 2.1

bio5

Mean daily maximum air temperature of the warmest month [°C]

    https://chelsa-climate.org/downloads/
    Version 2.1

bio7

Annual range of air temperature [°C]

    https://chelsa-climate.org/downloads/
    Version 2.1

bio12

Annual precipitation [kg/m2]

    https://chelsa-climate.org/downloads/
    Version 2.1

bio15

Precipitation seasonality [kg/m2]

    https://chelsa-climate.org/downloads/
    Version 2.1

gdd10

Growing degree days heat sum above 10°C

    https://chelsa-climate.org/downloads/
    Version 2.1

clay

Clay content [g/kg] of the 0-5cm layer

https://soilgrids.org/

Only used for AGB

sand

Sand content [g/kg] of the 0-5cm layer

    https://soilgrids.org/
    as above

pH

Acidity (Ph(water)) of the 0-5cm layer

    https://soilgrids.org/
    as above

glc2017

Landcover 2017

https://land.copernicus.eu/global/products/lc, reclassified to: closed forest, open forest, natural non-forest veg., bare & sparse veg. cropland, built-up, water

Categorical variable

dem

Elevation

https://www.eea.europa.eu/data-and-maps/data/copernicus-land-monitoring-service-eu-dem

cosasp

Cosine of slope aspect

Computed with the terra package from elevation

    Computed @25m resolution; next aggregated to 0.5km

sinasp

Sine of slope aspect

    Computed with the terra package from elevation
    as above

slope

Slope

    Computed with the terra package from elevation
    as above

TPI

Topographic position index

    Computed with the terra package from elevation
    as above

TRI

Terrain ruggedness index

    Computed with the terra package from elevation
    as above

TWI

Topographic wetness index

Computed with SAGA from 500m resolution (aggregated) dem

gedi

Forest height

https://glad.umd.edu/dataset/gedi

Zone: NAFR

xcoord

X coordinate

Using a mask created from the other covariates

ycoord

Y coordinate

    Using a mask created from the other covariates

Dcoast

Distance from coast

Using a land mask created from the other covariates

This website contains the mapping sequence of poultry. The ArkDB database system aims to provide a comprehensive public repository for genome mapping data from farmed and other animal species. In doing so, it aims to provide a route in to genomic and other sequence from the initial viewpoint of linkage mapping, RH mapping, physical mapping or - possibly more importantly - QTL mapping data. It's supported, in part, by the USDA-CSREES National Animal Genome Research Program in order to serve the poultry genome mapping community. This system represents a complete rewrite of the original version with the code migrated to java and the underlying database targeted at postgres (although any standards-compliant database engine should suffice). The initial release records details of maps and the markers that they contain. There are alternative entry points that target either a chromosome or a specific mapping analysis as the starting point. Limited relationships between markers are recorded and displayed. As with the previous version, all maps are drawn using data extracted from the database on the fly.

San Joaquin Valley Subsidence Analysis README. Written: Joel Dudas, 3/12/2017. Amended: Ben Brezing, 4/2/2019. DWR’s Division of Engineering Geodetic Branch received a request in 1/2017 from Jeanine Jones to produce a graphic of historic subsidence in the entirety of the San Joaquin Valley. The task was assigned to the Mapping & Photogrammetry Office and the Geospatial Data Support Section to complete by early February. After reviewing the alternatives, the decision was made to produce contours from the oldest available set of quad maps for which there was reasonable certainty about quality and datum, and to compare that to the most current Valley-wide DEM. For the first requirement, research indicated that the 1950’s vintage quad maps for the Valley were the best alternative. Prior quad map editions are uneven in quality and vintage, and the actual control used for the contour lines was extremely suspect. The 1950’s quads, by contrast, were produced primarily on the basis of 1948-1949 aerial photography, along with control corresponding to that period, and referenced to the National Geodetic Vertical Datum of 1929. For the current set, the most recent Valley-wide dataset that was freely available, in the public domain, and of reasonable accuracy was the 2005 NextMap SAR acquisition (referenced to NAVD88). The primary bulk of the work focused on digitizing the 1950’s contours. First, all of the necessary quads were downloaded from the online USGS quad source https://ngmdb.usgs.gov/maps/Topoview/viewer/#4/41.13/-107.51. Then the entire staff of the Mapping & Photogrammetry Lab (including both the Mapping Office and GDDS staff) proceeded to digitize the contours. Given the short turnaround time constraint and limited budget, certain shortcuts occurred in contour development. While efforts were made to digitize accurately, speed really was important. Contours were primarily focused only on agricultural and other lowland areas, and so highlands were by and large skipped. The tight details of contours along rivers, levees, and hillsides was skipped and/or simplified. In some cases, only major contours were digitized. The mapping on the source quads itself varied….in a few cases on spot elevations on benchmarks were available in quads. The contour interval sometimes varied, even within the quad sheet itself. In addition, because 8 different people were creating the contours, variability exists in the style and attention to detail. It should be understood that given the purpose of the project (display regional subsidence patterns), that literal and precise development of the historic contour sets leaves some things to be desired. These caveats being said, the linework is reasonably accurate for what it is (particularly given that the contours of that era themselves were mapped at an unknown and varying actual quality). The digitizers tagged the lines with Z values manually entered after linework that corresponded to the mapped elevation contours. Joel Dudas then did what could be called a “rough” QA/QC of the contours. The individual lines were stitched together into a single contour set, and exported to an elevation raster (using TopoToRaster in ArcGIS 10.4). Gross blunders in Z values were corrected. Gaps in the coverage were filled. The elevation grid was then adjusted to NAVD88 using a single adjustment for the entire coverage area (2.5’, which is a pretty close average of values in this region). The NextMap data was extracted for the area, and converted into feet. The two raster sets were fixed to the same origin point. The subsidence grid was then created by subtracting the old contour-derived grid from the NextMAP DEM. The subsidence grid that includes all of the values has the suffix “ALL”. Then, to improve the display fidelity, some of the extreme values (above +5’ and below -20’*) were filtered out of the dataset, and the subsidence grid was regenerated for these areas and suffixed with “cut.” The purpose of this cut was to extract some of the riverine and hilly areas that produced more extreme values and other artifacts purely due to the analysis approach (i.e. not actual real elevation change). * - some of the areas with more than 20 feet of subsidence were omitted from this clipping, because they were in heavily subsided areas and may be “real subsidence.”The resulting subsidence product should be perceived in light of the above. Some of the collar of the San Joaquin Valley shows large changes, but that is simply due to the analysis method. Also, individual grid cells may or may not be comparing the same real features. Errors are baked into both comparison datasets. However, it is important to note that the large areas of subsidence in the primary agriculture area agree fairly well with a cruder USGS subsidence map of the Valley based on extensometer data. We have confidence that the big picture story these results show us is largely correct, and that the magnitudes of subsidence are somewhat reasonable. The contour set can serve as the baseline to support future comparisons using more recent or future data as it becomes available. It should be noted there are two key versions of the data. The “Final Deliverables” from 2/2017 were delivered to support the initial Public Affairs press release. Subsequent improvements were made in coverage and blunder correction as time permitted (it should be noted this occurred in the midst of the Oroville Dam emergency) to produce the final as of 3/12/2017. Further improvements in overall quality and filtering could occur in the future if time and needs demand it. Update (4/3/2019, Ben Brezing): The raster was further smoothed to remove artifacts that result from comparing the high resolution NextMAP DEM to the lower resolution DEM that was derived from the 1950’s quad map contours. The smoothing was accomplished by removing raster cells with values that are more than 0.5 feet different than adjacent cells (25 meter cell size), as well as the adjacent cells. The resulting raster was then resampled to a raster with 100 meter cell size using cubic resampling technique and was then converted to a point feature class. The point feature class was then interpolated to a raster with 250 meter cell size using the IDW technique, a fixed search radius of 1250 meters and power=2. The resulting raster was clipped to a smaller extent to remove noisier areas around the edges of the Central Valley while retaining coverage for the main area of interest.

Areas in cities typically denoted as 'Vacant and Derelict Land', are frequently presented in policy documents as absent of meaning and awaiting development. However, visits to many of these sites offer evidence of abundant citizen activity occurring outside of planning policy. Dog walkers, DIY skatepark builders, pigeon fanciers and reminiscing former factory workers, for example, can all be found inscribing their own narratives, in palimpsest like fashion, upon these landscapes. This spatio-temporally bound and layered mix of contested meanings extends beyond representational capacity offered by traditional cartographic methods as employed in policy decision making. Such a failure to represent these ecologies of citizen-led practices often result in their erasure at the point of formal redevelopment. We explore how one alternative approach may respond to these challenges of representation through a case study project in Glasgow, Scotland. Deep mapping is an ethnographically informed, arts research practice, drawing Cifford Geertz's notion of 'thick description' into a visual-performative realm and seeking to extend beyond the thin map by creating multi-faceted and open-ended descriptions of place. As such, deep maps are not only investigations into place but of equal concern are the processes by which representations of place are generated. Implicit in this are questions about the role of the researcher as initiator, gatherer, archivist or artist and the intertwining between the place and the self. As a methodological approach that embraces multiplicity and favours the 'politicized, passionate, and partisan' over the totalising objectivity of traditional maps, deep mapping offers a potential to give voice to marginalised, micro-narratives existing in tension with one another and within dominant meta-narratives but also triggers new questions over inclusivity. This methodologically focussed chapter explores the ways in which an ethnographically informed, arts research practice may offer alternative insight into spaces of non-aligned narratives. The results from this investigation will offer new framings of spaces within the urban landscape conventionally represented as vacant or empty and generate perspectives on how art research methods may provide valuable investigative tools for decision makers working in such contexts.

Web map for use with the R2 Mobile App. Focuses on the the Rocky Mountain Region (R2) of the USDA Forest Service. Depicts National Forest and Grasslands both as boundaries and with points, and state boundaries. When zoomed out, there are single points for each administrative unit, while when zoomed in closer to a larger scale, there is a point for each National Forest and for each National Grassland within the Rocky Mountain Region.

This part of DS 781 presents data for the geologic and geomorphic map of the Drakes Bay and Vicinity map area, California. The polygon shapefile is included in "Geology_DrakesBay.zip," which is accessible from http://pubs.usgs.gov/ds/781/DrakesBay/data_catalog_DrakesBay.html. Marine geology and geomorphology was mapped in the Drakes Bay and Vicinity map area from approximate Mean High Water (MHW) to the 3-nautical-mile limit of Californiaâ  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. San Andreas Fault traces are compiled from California Geological Survey (1974) and Wagner and Gutierrez (2010). The offshore part of the map area includes the large embayment known as Drakes Bay and extends from the shoreline to water depths of about 40 to 60 m. The continental shelf is quite wide in this area, with the shelfbreak located west of the Farallon High, about 35 km offshore. This map area is largely characterized by a relatively flat (<0.8à °) bedrock platform that is locally overlain by thin sediment cover. 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, 2006), 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 currents before deposition or offshore transport. Tectonic influences impacting shelf morphology and geology are related to local faulting, folding, uplift, and subsidence. 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. Late Pleistocene uplift of marine terraces on the Point Reyes Peninsula suggests active deformation west of the San Andreas Fault (Grove and others, 2010). Offshore Double Point, the Point Reyes Fault is associated with warping and folding of Neogene strata visible on high-resolution seismic data. 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). Salinian granitic basement rocks (unit Kgg) are exposed on the Point Reyes headland and offshore in the northwest corner of the map area. The granitic rocks are mapped on the basis of massive, bulbous texture and extensive fracturing in multibeam imagery, and high backscatter. Much of the inner shelf is underlain by Neogene marine sedimentary rocks that form the core of the Point Reyes syncline (Weaver, 1949), and include the mid- to late Miocene Monterey Formation (unit Tm), late Miocene Santa Margarita Formation (unit Tsm), late Miocene Santa Cruz Mudstone (unit Tsc), and late Miocene to early Pliocene Purisima Formation (unit Tp; Clark and Brabb, 1997; Powell and others, 2007). At Millers Point, the Monterey Formation is exposed onshore and on the seafloor in the nearshore and appears highly fractured with bedding planes difficult to identify. Seafloor exposures of the younger Tsc and Tp units are characterized by distinct rhythmic bedding and are often gently folded and fractured. Unit Tu refers to seafloor outcrops that may include unit Tm, unit Tsm, or unit Tsc. The Santa Cruz Mudstone and underlying Santa Margarita Sandstone at Double Point are more than 450 m thick in an oil test well (Clark and Brabb, 1997), and these units form coastal bluffs and tidal zone exposures that extend onto the adjacent bedrock shelf. The Santa Cruz Mudstone thins markedly to the northwest and disappears from the section about 10 km to the northwest where Purisima Formation unconformably overlies Santa Margarita Sandstone. We infer the offshore contact between the Santa Cruz Mudstone and Purisima Formation based on an angular unconformity visible in seismic data just southeast of the map area. This angular unconformity becomes conformable to the northwest in the Drakes Bay and Vicinity map area. We suggest this contact bends northward in the subsurface and comes onshore near U-Ranch (Galloway, 1977; Clark and Brabb, 1997). Given the lack of lithological evidence for this contact offshore Double Point, this interpretation is speculative, and an alternative interpretation is that the noted unconformity occurs within the Santa Cruz Mudstone. For this reason, we have queried unit Tp here to indicate this uncertainty. Modern nearshore sediments are mostly sand (unit Qms) and a mix of sand, gravel, and cobbles (units Qmsc and Qmsd). The more coarse-grained sands and gravels (units Qmsc and Qmsd) are primarily recognized on the basis of bathymetry and high backscatter (see Bathymetry--Drakes Bay, California and Backscattter A to C--Drakes Bay, California, DS 781, for more information). Both Qmsc and Qmsd typically have abrupt landward contacts with bedrock and form irregular to lenticular exposures that are commonly elongate in the shore-normal direction. Contacts between units Qmsc and Qms are typically gradational. Unit Qmsd forms erosional lags in scoured depressions that are bounded by relatively sharp and less commonly diffuse contacts with unit Qms horizontal sand sheets. These depressions are typically a few tens of centimeters deep and range in size from a few 10's of meters to more than 1 km2. There are two areas of high-backscatter, and rough seafloor that are notable in that each includes several small (less than about 20,000 m2), irregular "lumps", with as much as 1 m of positive relief above the seafloor (unit Qsr). Southeast of the Point Reyes headland, unit Qsr occurs in water depths between 50 and 60 meters, with individual lumps randomly distributed to west-trending. Southwest of Double Point, unit Qsr occurs in water depths between 30 and 40 meters, with individual lumps having a more northwest trend. Seismic-reflection data (see field activity S-8-09-NC) reveal this lumpy material rests on several meters of latest Pleistocene to Holocene sediment and is thus not bedrock outcrop. Rather, it seems likely that this lumpy material is marine debris, possibly derived from one (or more) of the more than 60 shipwrecks offshore of the Point Reyes Peninsula between 1849 and 1940 (National Park Service, 2012). It is also conceivable that this lumpy terrane consists of biological "hardgrounds". Video transect data crossing unit Qsr near the Point Reyes headland was of insufficient quality to distinguish between these above alternatives. A transition to more fine-grained marine sediments (unit Qmsf) occurs around 50-60 m depth south of the Point Reyes headland and west of Double Point, however, directly south and east of Drakes Estero estuary, backscatter and seafloor sediment samples (Chin and others, 1997) suggest fine-grained sediments extend into water depths as shallow as 30 m. Unit Qmsf is commonly extensively bioturbated and consists primarily of mud and muddy sand. These fine-grained sediments are inferred to have been derived from the Drakes and Limantour Esteros or from the San Francisco Bay to the south, via predominantly northwest flow at the seafloor (Noble and Gelfenbaum, 1990). References Cited Catuneanu, O., 2006, Principles of Sequence Stratigraphy: Amsterdam, Elsevier, 375 p. Chin, J.L., Karl, H.A., and Maher, N.M., 1997, Shallow subsurface geology of the continental shelf, Gulf of the Farallones, California, and its relationship to surficial seafloor characteristics: Marine Geology, v. 137, p. 251-269. Clark, J.C., and Brabb, E.E., 1997, Geology of the Point Reyes National Seashore and vicinity: U.S. Geological Survey Open-File Report 97-456, scale 1:48,000. 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. Hoskins E.G., Griffiths, J.R., 1971, Hydrocarbon potential of northern and central California offshore: American Association of Petroleum Geologists Memoir 15, p. 212-228. Lambeck, K., and Chappell, J., 2001, Sea level change through the last glacial cycle: Science, v. 292, p. 679-686, doi: 10.1126/science.1059549. 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 ocean basins-Beaufort Sea to Baja California: Circum-Pacific Council for Energy and Mineral Resources Earth Science Series, v. 6, p. 353-401. National Park Service, 2012, Shipwrecks at Point Reyes, available at:

The National Land Cover Database (NLCD) is a land cover monitoring program providing land cover information for the United States. NLCD2016 extended temporal coverage to 15 years (2001–2016). We collected land cover reference data for the 2011 and 2016 nominal dates to report land cover accuracy for the NLCD2016 database 2011 and 2016 land cover components. We measured land cover accuracy at Level II and Level I, and change accuracy at Level I. For both the 2011 and 2016 land cover components, single-date Level II overall accuracies (OA) were 72% (standard error of ±0.9%) when agreement was defined as match between the map label and primary reference label only and 86% (± 0.7%) when agreement also included the alternate reference label. The corresponding level I OA for both dates were 79% (± 0.9%) and 91% (± 1.0%). For land cover change, the 2011–2016 user’s and producer’s accuracies (UA and PA) were ~ 75% for forest loss. PA for water loss, grassland loss, and grass gain were > 70% when agreement included a match between the map label and either the primary or alternate reference label. Depending on agreement definition and level of the classification hierarchy, OA for the 2011 land cover component of the NLCD2016 database was about 4% to 7% higher than OA for the 2011 land cover component of the NLCD2011 database, suggesting that the changes in mapping methodologies initiated for production of the NLCD2016 database have led to improved product quality.

Molecularly controlled combustion systems (MCCSs) combine the advantages of compression-ignition and spark-ignition engines by employing both a low reactivity fuel and a high reactivity fuel (HRF). To optimize the MCCS, fuels must be tailored to the engine requirements with respect to fuel reactivity. We aim at deriving requirements for HRFs and identification of suitable HRF candidates. Single-cylinder experiments are performed to assess the suitability of conventional reactivity indicators for MCCS. Fuel ignition delay time (IDT) maps are proposed as alternative reactivity indicators conveying more information. The maps are constructed through five representative IDT measurements at varying temperatures and pressures within the constant volume combustion chamber of the advanced fuel ignition delay analyzer (AFIDA). Specifically, the IDT maps cover the temperature and pressure range of 500–700 °C and 10–35 bar, respectively; and the IDT is measured at the four corner points of that range and the center point. We present measured IDT maps for more than 50 oxygenated and nonoxygenated hydrocarbon species and analyze suitability for MCCSs, e.g., 1,3-dioxane and 1-heptanol are found as possible HRF. The measurement data are further utilized to develop a graph neural network (GNN) model that can predict IDT maps directly from the molecular structure with high accuracy, constituting a first step toward in-silico screening of HRFs for MCCSs.

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This map is one of a series of soil landscape maps that are intended for all of central and eastern NSW, based on standard 1:100,000 and 1:250,000 topographic sheets. The map provides an inventory of soil and landscape properties of the area and identifies major soil and landscape qualities and constraints. It integrates soil and topographic features into single units with relatively uniform land management requirements. Soils are described in terms of soil materials in addition to the Australian Soil Classification and the Great Soil Group systems.

Related Datasets: The dataset area is also covered by the mapping of Acid Sulphate Soil Risk Mapping.

Online Maps: This and related datasets can be viewed using eSPADE (NSW’s soil spatial viewer), which contains a suite of soil and landscape information including soil profile data. Many of these datasets have hot-linked soil reports. An alternative viewer is the SEED Map; an ideal way to see what other natural resources datasets (e.g. vegetation) are available for this map area.

Reference: Tulau, M.J. 1998. Soil Landscapes of the Bega - Goalen Point 1:100,000 Sheets map edition 2, NSW Department of Land and Water Conservation, Sydney.

Tulau, M.J. 1997. Soil Landscapes of the Bega - Goalen Point 1:100,000 Sheets report edition 1, NSW Department of Land and Water Conservation, Sydney

Part of the Vicmap Features of Interest dataset series. This layer is derived from the Register of Geographic Names. Named locations desribed in this layer include town names, buildings/structures and place names in general.These locations are stored as named points. The layers primary function is to support production of map annotation and as a general reference for localities. The Register is the primary reference for official names and their applications. The Register holds the status of names (e.g. official; official alternative; official historical; etc). To provide the official legal name of a place or feature or asset as in section 18 of the Geographic Place Names Act 1998.

Mapping-by-sequencing combines Next Generation Sequencing (NGS) with classical genetic mapping by linkage analysis to establish gene-to-phenotype relationships. Although numerous tools have been developed to analyze NGS datasets, only a few are available for mapping-by-sequencing. One such tool is Easymap, a versatile, easy-to-use package that performs automated mapping of point mutations and large DNA insertions. Here, we describe Easymap v.2, which also maps small insertion/deletions (InDels), and includes workflows to perform QTL-seq and variant density mapping analyses. Each mapping workflow can accommodate different experimental designs, including outcrossing and backcrossing, F2, M2, and M3 mapping populations, chemically induced mutation and natural variant mapping, input files containing single-end or paired-end reads of genomic or complementary DNA sequences, and alternative control sample files in FASTQ and VCF formats. Easymap v.2 can also be used as a variant analyzer in the absence of a mapping algorithm and includes a multi-threading option.

This map is one of a series of soil landscape maps that are intended for all of central and eastern NSW, based on standard 1:100,000 and 1:250,000 topographic sheets. The map provides an inventory of soil and landscape properties of the area and identifies major soil and landscape qualities and constraints. It integrates soil and topographic features into single units with relatively uniform land management requirements. Soils are described in terms of soil materials in addition to the Australian Soil Classification and the Great Soil Group systems.

Related Datasets: The dataset area is also covered by the mapping of Acid Sulphate Soil Risk Mapping.

Online Maps: This and related datasets can be viewed using eSPADE (NSW’s soil spatial viewer), which contains a suite of soil and landscape information including soil profile data. Many of these datasets have hot-linked soil reports. An alternative viewer is the SEED Map; an ideal way to see what other natural resources datasets (e.g. vegetation) are available for this map area.

Reference: Atkinson G, 1999, Soil Landscapes of the Kempsey-Korogoro Point 1:100,000 Sheets) map and report, NSW Department of Land and Water Conservation, Sydney.