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Members from the U.S. Geological Survey (USGS) Patterns in the Landscape - Analyses of Cause and Effect (PLACE) team are releasing monthly surface water maps for the conterminous United States (U.S.) from 2003 through 2019 as 250-meter resolution geoTIFF files. The maps were produced using the Dynamic Surface Water Extent (DSWE) algorithm applied to daily Moderate Resolution Imaging Spectroradiometer (MODIS) imagery (DSWEmod) (Soulard et al., 2021) - see associated items. The DSWEmod model classifies the landscape (i.e., each MODIS pixel) into different classes of surface water based on quantified levels of confidence, including, i) high-confidence surface water (class 1), ii) moderate-confidence surface water (class...
Members from the U.S. Geological Survey (USGS) Patterns in the Landscape - Analyses of Cause and Effect (PLACE) team are releasing monthly surface water maps for the conterminous United States (U.S.) from 2003 through 2019 as 250-meter resolution geoTIFF files. The maps were produced using the Dynamic Surface Water Extent (DSWE) algorithm applied to daily Moderate Resolution Imaging Spectroradiometer (MODIS) imagery (DSWEmod) (Soulard et al., 2021) - see associated items. The DSWEmod model classifies the landscape (i.e., each MODIS pixel) into different classes of surface water based on quantified levels of confidence, including, i) high-confidence surface water (class 1), ii) moderate-confidence surface water (class...
Members from the U.S. Geological Survey (USGS) Patterns in the Landscape - Analyses of Cause and Effect (PLACE) team are releasing monthly surface water maps for the conterminous United States (U.S.) from 2003 through 2019 as 250-meter resolution geoTIFF files. The maps were produced using the Dynamic Surface Water Extent (DSWE) algorithm applied to daily Moderate Resolution Imaging Spectroradiometer (MODIS) imagery (DSWEmod) (Soulard et al., 2021) - see associated items. The DSWEmod model classifies the landscape (i.e., each MODIS pixel) into different classes of surface water based on quantified levels of confidence, including, i) high-confidence surface water (class 1), ii) moderate-confidence surface water (class...
Total Nitrogen (TN) rloadest models were developed to compute TN flux at School Branch at three USGS monitoring stations: School Branch at Maloney Road near Brownsburg, Indiana (03353415); School Branch at CR750N at Brownsburg, Indiana (03353420); and School Branch at Noble Drive at Brownsburg, Indiana (03353430). Frequently, TN models developed in rloadest regress discrete TN concentrations against concurrent daily mean streamflow values. However, due to the flashy nature of streamflows on School Branch, the developed TN models regressed discrete TN concentrations against the closest unit-value (15-minute) streamflows. Once TN flux models were calibrated, unit-value streamflows were used to estimate average TN...
The purpose of this field data collection was to test and compare the OceanInsight HDX Mini Spectrometer as an accessible alternative against the more expensive ASD Fieldspec for collecting ground-based hyperspectral reflectance profiles for landcover analysis. The data collection took place in Dog Head Marsh and South Cape Beach within the Waquoit Bay National Estuarine Research Reserve (WBNERR). The hyperspectral profiles were collected side-by-side with both field-spectrometers using comparable sensor collection settings for various ground cover samples. The terrain and vegetation type of these sample were described as well as surveyed using Real Time Kinematic Global Positioning System (RTK-GPS). This data...
Categories: Data;
Tags: 3DR Solo Quadcopter,
CMHRP,
Coastal and Marine Hazards and Resources Program,
Dog Head Marsh,
Field activity 2021-033-FA,
Members from the U.S. Geological Survey (USGS) Patterns in the Landscape - Analyses of Cause and Effect (PLACE) team are releasing monthly surface water maps for the conterminous United States (U.S.) from 2003 through 2019 as 250-meter resolution geoTIFF files. The maps were produced using the Dynamic Surface Water Extent (DSWE) algorithm applied to daily Moderate Resolution Imaging Spectroradiometer (MODIS) imagery (DSWEmod) (Soulard et al., 2021) - see associated items. The DSWEmod model classifies the landscape (i.e., each MODIS pixel) into different classes of surface water based on quantified levels of confidence, including, i) high-confidence surface water (class 1), ii) moderate-confidence surface water (class...
This data release contains the calibration data set and R code used to create regression models for estimating daily loads of suspended sediment, total nitrogen, and total phosphorus at the Iroquois River near Foresman, Indiana streamgage (05524500). The USGS R software package, rloadest, was used to develop the regression models and estimate loads. The models were developed using discrete water-quality data and concurrent daily streamflow data measured/determined at the streamgage for the period April 2015 through July 2018. Also included in this data release is the input data set of daily streamflow data and the daily load output data sets that were produced by the regression models. Summary information for the...
The purpose of this field data collection was to test and compare the OceanInsight HDX Mini Spectrometer as an accessible alternative against the more expensive ASD Fieldspec for collecting ground-based hyperspectral reflectance profiles for landcover analysis. The data collection took place in Dog Head Marsh and South Cape Beach within the Waquoit Bay National Estuarine Research Reserve (WBNERR). The hyperspectral profiles were collected side-by-side with both field-spectrometers using comparable sensor collection settings for various ground cover samples. The terrain and vegetation type of these sample were described as well as surveyed using Real Time Kinematic Global Positioning System (RTK-GPS). This data...
Categories: Data;
Tags: Agisoft Metashape,
Altum-PT,
CMHRP,
Coastal and Marine Hazards and Resources Program,
Dog Head Marsh,
The purpose of this field data collection was to test and compare the OceanInsight HDX Mini Spectrometer as an accessible alternative against the more expensive ASD Fieldspec for collecting ground-based hyperspectral reflectance profiles for landcover analysis. The data collection took place in Dog Head Marsh and South Cape Beach within the Waquoit Bay National Estuarine Research Reserve (WBNERR). The hyperspectral profiles were collected side-by-side with both field-spectrometers using comparable sensor collection settings for various ground cover samples. The terrain and vegetation type of these sample were described as well as surveyed using Real Time Kinematic Global Positioning System (RTK-GPS). This data...
Categories: Data;
Tags: CMHRP,
Coastal and Marine Hazards and Resources Program,
Dog Head Marsh,
Field activity 2021-033-FA,
GPS measurement,
Members from the U.S. Geological Survey (USGS) Patterns in the Landscape - Analyses of Cause and Effect (PLACE) team are releasing monthly surface water maps for the conterminous United States (U.S.) from 2003 through 2019 as 250-meter resolution geoTIFF files. The maps were produced using the Dynamic Surface Water Extent (DSWE) algorithm applied to daily Moderate Resolution Imaging Spectroradiometer (MODIS) imagery (DSWEmod) (Soulard et al., 2021) - see associated items. The DSWEmod model classifies the landscape (i.e., each MODIS pixel) into different classes of surface water based on quantified levels of confidence, including, i) high-confidence surface water (class 1), ii) moderate-confidence surface water (class...
Members from the U.S. Geological Survey (USGS) Patterns in the Landscape - Analyses of Cause and Effect (PLACE) team are releasing monthly surface water maps for the conterminous United States (U.S.) from 2003 through 2019 as 250-meter resolution geoTIFF files. The maps were produced using the Dynamic Surface Water Extent (DSWE) algorithm applied to daily Moderate Resolution Imaging Spectroradiometer (MODIS) imagery (DSWEmod) (Soulard et al., 2021) - see associated items. The DSWEmod model classifies the landscape (i.e., each MODIS pixel) into different classes of surface water based on quantified levels of confidence, including, i) high-confidence surface water (class 1), ii) moderate-confidence surface water (class...
This dataset is one of many used in the development of the manuscript 'Advancing Cave Detection using Terrain Analysis Techniques and Thermal Imagery' by Wynne et al. 2021. Manuscript Abstract: Since the initial experiments nearly 50 years ago, techniques for detecting caves using airborne and spacecraft acquired thermal imagery have improved markedly. These advances are largely due to a combination of higher instrument sensitivity, modern computing systems, and processor-intensive analytical techniques. Through applying these advancements, our goals were to: (1) determine the utility of methods designed for terrain analysis and applied to thermal imagery; (2) analyze the usefulness of predawn and midday imagery...
Members from the U.S. Geological Survey (USGS) Patterns in the Landscape - Analyses of Cause and Effect (PLACE) team are releasing monthly surface water maps for the conterminous United States (U.S.) from 2003 through 2019 as 250-meter resolution geoTIFF files. The maps were produced using the Dynamic Surface Water Extent (DSWE) algorithm applied to daily Moderate Resolution Imaging Spectroradiometer (MODIS) imagery (DSWEmod) (Soulard et al., 2021) - see associated items. The DSWEmod model classifies the landscape (i.e., each MODIS pixel) into different classes of surface water based on quantified levels of confidence, including, i) high-confidence surface water (class 1), ii) moderate-confidence surface water (class...
Members from the U.S. Geological Survey (USGS) Patterns in the Landscape - Analyses of Cause and Effect (PLACE) team are releasing monthly surface water maps for the conterminous United States (U.S.) from 2003 through 2019 as 250-meter resolution geoTIFF files. The maps were produced using the Dynamic Surface Water Extent (DSWE) algorithm applied to daily Moderate Resolution Imaging Spectroradiometer (MODIS) imagery (DSWEmod) (Soulard et al., 2021) - see associated items. The DSWEmod model classifies the landscape (i.e., each MODIS pixel) into different classes of surface water based on quantified levels of confidence, including, i) high-confidence surface water (class 1), ii) moderate-confidence surface water (class...
Defining site potential for an area establishes its possible long-term vegetation growth productivity in a relatively undisturbed state, providing a realistic reference point for ecosystem performance. Modeling and mapping site potential helps to measure and identify naturally occurring variations on the landscape as opposed to variations caused by land management activities or disturbances (Rigge et al. 2020). We integrated remotely sensed data (250-m enhanced Moderate Resolution Imaging Spectroradiometer (eMODIS) Normalized Difference Vegetation Index (NDVI) (https://earthexplorer.usgs.gov/)) with land cover, biogeophysical (i.e., soils, topography) and climate data into regression-tree software (Cubist®). We...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arid,
Arizona,
Colorado,
Ecology,
Geography,
Members from the U.S. Geological Survey (USGS) Patterns in the Landscape - Analyses of Cause and Effect (PLACE) team are releasing monthly surface water maps for the conterminous United States (U.S.) from 2003 through 2019 as 250-meter resolution geoTIFF files. The maps were produced using the Dynamic Surface Water Extent (DSWE) algorithm applied to daily Moderate Resolution Imaging Spectroradiometer (MODIS) imagery (DSWEmod) (Soulard et al., 2021) - see associated items. The DSWEmod model classifies the landscape (i.e., each MODIS pixel) into different classes of surface water based on quantified levels of confidence, including, i) high-confidence surface water (class 1), ii) moderate-confidence surface water (class...
This product summarizes the collection and analysis of bed material sample grain size distribution collected from the Iron Gate, Copco, and J.C. Boyle Reservoirs located in Northern California and Southern Oregon on the Klamath River. Samples were collected on June 16, 2020 from cores (less than 1m depth) and processed for the full size distribution.
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Bed material,
Bed sediment,
California,
Copco Reservoir,
Geomorphology,
This dataset is one of many used in the development of the manuscript 'Advancing Cave Detection using Terrain Analysis Techniques and Thermal Imagery' by Wynne et al. 2021. Manuscript Abstract: Since the initial experiments nearly 50 years ago, techniques for detecting caves using airborne and spacecraft acquired thermal imagery have improved markedly. These advances are largely due to a combination of higher instrument sensitivity, modern computing systems, and processor-intensive analytical techniques. Through applying these advancements, our goals were to: (1) determine the utility of methods designed for terrain analysis and applied to thermal imagery; (2) analyze the usefulness of predawn and midday imagery...
Members from the U.S. Geological Survey (USGS) Patterns in the Landscape - Analyses of Cause and Effect (PLACE) team are releasing monthly surface water maps for the conterminous United States (U.S.) from 2003 through 2019 as 250-meter resolution geoTIFF files. The maps were produced using the Dynamic Surface Water Extent (DSWE) algorithm applied to daily Moderate Resolution Imaging Spectroradiometer (MODIS) imagery (DSWEmod) (Soulard et al., 2021) - see associated items. The DSWEmod model classifies the landscape (i.e., each MODIS pixel) into different classes of surface water based on quantified levels of confidence, including, i) high-confidence surface water (class 1), ii) moderate-confidence surface water (class...
Members from the U.S. Geological Survey (USGS) Patterns in the Landscape - Analyses of Cause and Effect (PLACE) team are releasing monthly surface water maps for the conterminous United States (U.S.) from 2003 through 2019 as 250-meter resolution geoTIFF files. The maps were produced using the Dynamic Surface Water Extent (DSWE) algorithm applied to daily Moderate Resolution Imaging Spectroradiometer (MODIS) imagery (DSWEmod) (Soulard et al., 2021) - see associated items. The DSWEmod model classifies the landscape (i.e., each MODIS pixel) into different classes of surface water based on quantified levels of confidence, including, i) high-confidence surface water (class 1), ii) moderate-confidence surface water (class...
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