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These are two land cover datasets derived from Landsat Thematic Mapper and Operational Land Imager (spatial resolution 30-m)Path 014 and Rows 032 and 033 surface reflectance data collected on July 14, 2011 and July 19, 2013, before and after Hurricane Sandy made landfall near Brigantine, New Jersey on October 29, 2012. The two land cover data sets provide a means of evaluating the effect of Hurricane Sandy of data sets collected at times that represent or approach peak vegetation growth. The most accurate results of the land cover classification are based on twelve classes, some of which occur adjacent to the marshes but not on the New Jersey intracoastal marshes. Twelve classes were used in the supervised maximum...
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This part of DS 781 presents data for the shaded-relief map of Offshore of Aptos map area, California. Shaded-relief data are provided as two separate grids depending on mapping agency and processing method. This metadata file refers to the data included in "BathymetryBHS_CSUMB_OffshoreAptos.zip," which is accessible from https://doi.org/10.5066/F7K35RQB. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D, Dieter, B.E., Golden, N.E., Hartwell, S.R., Ritchie, A.C., Kvitek, r.G., Maier, K.L., Endris, C.A., Davenport, C.W., Watt, J.T., Sliter, R.W., Finlayson, D.P., and Krigsman, L.M., (G.R. Cochrane and S.A. Cochran, eds.), 2016, California State...
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This part of DS 781 presents data for the bathymetry map of Offshore of Aptos map area, California. Bathymetry data are provided as two separate grids depending on mapping agency and processing method. This metadata file refers to the data included in "BathymetryA_USGS_OffshoreAptos.zip" which are accessible from https://doi.org/10.5066/F7K35RQB. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D, Dieter, B.E., Golden, N.E., Hartwell, S.R., Ritchie, A.C., Kvitek, r.G., Maier, K.L., Endris, C.A., Davenport, C.W., Watt, J.T., Sliter, R.W., Finlayson, D.P., and Krigsman, L.M., (G.R. Cochrane and S.A. Cochran, eds.), 2016, California State Waters...
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The dataset provides a near real time estimation of 2020 herbaceous mostly annual fractional cover predicted on July 1st with an emphasis on annual exotic grasses Historically, similar maps were produced at a spatial resolution of 250m (Boyte et al. 2019 https://doi.org/10.5066/P96PVZIF., Boyte et al. 2018 https://doi.org/10.5066/P9RIV03D.), but starting this year we are mapping at a 30m resolution (Pastick et al. 2020 doi:10.3390/rs12040725). This dataset was generated using in situ observations from Bureau of Land Management’s (BLM) Assessment, Inventory, and Monitoring data (AIM) plots; weekly composites of harmonized Landsat and Sentinel-2 (HLS) data (https://hls.gsfc.nasa.gov/); relevant environmental, vegetation,...
The U.S. Geological Survey (USGS) calculated multiple basin characteristics as part of preparing the Upper Colorado & Gunnison Rivers Pilot StreamStats application. These datasets are raster representations of various environmental, geological, and land use attributes within the Upper Colorado & Gunnison Rivers study area (also known as the Next-Generation Water Observing System, or NGWOS), and will be served in the National StreamStats application (https://streamstats.usgs.gov) to describe delineated watersheds. The StreamStats application provides access to spatial analysis tools that are useful for water-resources planning and management, and for engineering and design purposes. The map-based user interface can...
The U.S. Geological Survey (USGS), in cooperation with the Puerto Rico Environmental Quality Board, has compiled a series of geospatial datasets for Puerto Rico to be implemented into the USGS StreamStats application (https://streamstats.usgs.gov/ss/). These geospatial datasets, along with basin characteristics datasets for Puerto Rico published as a separate USGS data release (https://doi.org/10.5066/P9HK9SSQ), were used to delineate watersheds and develop the peak-flow and low-flow regression equations used by StreamStats. The geospatial dataset described herein are the flow direction rasters at a 10-m resolution, which indicates the direction in which water is predicted to flow out of a given pixel (8 compass...
The U.S. Geological Survey (USGS), in cooperation with the Puerto Rico Environmental Quality Board, has compiled a series of geospatial datasets for Puerto Rico to be implemented into the USGS StreamStats application (https://streamstats.usgs.gov/ss/). These geospatial datasets, along with basin characteristics datasets for Puerto Rico published as a separate USGS data release (https://doi.org/10.5066/P9HK9SSQ), were used to delineate watersheds and develop the peak-flow and low-flow regression equations used by StreamStats. The geospatial dataset described herein are the rasters of flow accumulation, which is the number of pixels upstream of a given pixel. Data are partitioned into four TIFF files, one for each...
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This part of DS 781 presents 2-m-resolution data collected by the U.S. Geological Survey in 2008 for the acoustic-backscatter map of the Offshore of Gaviota Map Area, California. The GeoTiff is included in "Backscatter_[USGS08]_OffshoreGaviota.zip," which is accessible from https://doi.org/10.5066/F7TH8JWJ. The acoustic-backscatter map of the Offshore of Gaviota map area in southern California was generated from acoustic-backscatter data collected by the U.S. Geological Survey (USGS) and by Fugro Pelagos Inc. Acoustic mapping was completed between 2007 and 2008 using a combination of 400-kHz Reson 7125, 240-kHz Reson 8101, and 100-kHz Reson 8111 multibeam echosounders, as well as a 234-kHz SEA SWATHplus bathymetric...
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This part of DS 781 presents data for the acoustic-backscatter map of Offshore of Pigeon Point map area, California. Backscatter data are provided as three separate grids depending on mapping system. The raster data files are included in "BackscatterB_7125_OffshorePigeonPoint.zip," which is accessible from http://dx.doi.org/10.5066/F7513W80.The acoustic-backscatter map of the Offshore of Pigeon Point, California was generated from backscatter data collected by California State University, Monterey Bay (CSUMB), by Fugro Pelagos, and by the U.S. Geological Survey (USGS). Mapping was completed between 2006 and 2009, using a combination of 400-kHz Reson 7125 and 244-kHz Reson 8101 multibeam echosounders, as well as...
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Seafloor character was derived from interpretations of air photo derived kelp distribution data available for the Santa Cruz Island (Kushner and others 2013). The number of substrate classes was reduced because rugosity could not be derived for all areas. References Cited: Kushner DJ, Rassweiler A, McLaughlin JP, Lafferty KD (2013) A multi-decade time series of kelp forest community structure at the California channel islands: Ecology 94:2655.
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Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
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Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
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Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
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Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
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Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
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Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
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Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
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Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
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Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
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Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...


map background search result map search result map BackscatterB [7125]--Offshore Pigeon Point, California BathymetryA [USGS]--Offshore Aptos, California BathymetryB Hillshade [CSUMB]--Offshore Aptos, California Air-photo seafloor character Santa Barbara Channel Geohab Land cover classification dataset Backscatter [USGS08]--Offshore of Gaviota Map Area, California Precipitation (Mean: Annual) - 2020-2050 - RCP8.5 - Min Precipitation (Proportion July - Sep) - 2020-2050 - RCP8.5 - Max Temperature (Mean: Annual) - 2070-2100 - RCP8.5 - Mean Temperature (Mean: Annual) - 2020-2050 - RCP8.5 - Mean Precipitation (Proportion May - Oct) - 2070-2100 - RCP4.5 - Mean Temperature (Maximum: July) - 2070-2100 - RCP8.5 - Mean Temperature (Mean: Apr - June) - 2070-2100 - RCP4.5 - Max Temperature (Mean: July - Sep) - 2070-2100 - RCP4.5 - Max Temperature (Minimum: January) - 2020-2050 - RCP4.5 - Mean Temperature (Minimum: January) - 2020-2050 - RCP8.5 - Max Flow accumulation rasters for Puerto Rico StreamStats Flow direction rasters for Puerto Rico StreamStats Near real time estimation of annual exotic herbaceous fractional cover in the sagebrush ecosystem 30m, USA, July 2020 Basin Characteristic Layers for the Upper Colorado & Gunnison Rivers Pilot Project for StreamStats 2020 BathymetryB Hillshade [CSUMB]--Offshore Aptos, California Flow accumulation rasters for Puerto Rico StreamStats Flow direction rasters for Puerto Rico StreamStats Land cover classification dataset Basin Characteristic Layers for the Upper Colorado & Gunnison Rivers Pilot Project for StreamStats 2020 Near real time estimation of annual exotic herbaceous fractional cover in the sagebrush ecosystem 30m, USA, July 2020 Precipitation (Mean: Annual) - 2020-2050 - RCP8.5 - Min Precipitation (Proportion July - Sep) - 2020-2050 - RCP8.5 - Max Temperature (Mean: Annual) - 2070-2100 - RCP8.5 - Mean Temperature (Mean: Annual) - 2020-2050 - RCP8.5 - Mean Precipitation (Proportion May - Oct) - 2070-2100 - RCP4.5 - Mean Temperature (Maximum: July) - 2070-2100 - RCP8.5 - Mean Temperature (Mean: Apr - June) - 2070-2100 - RCP4.5 - Max Temperature (Mean: July - Sep) - 2070-2100 - RCP4.5 - Max Temperature (Minimum: January) - 2020-2050 - RCP4.5 - Mean Temperature (Minimum: January) - 2020-2050 - RCP8.5 - Max