Digital shaded-relief map of Venezuela

USGS Publications Warehouse

Garrity, Christopher P.; Hackley, Paul C.; Urbani, Franco

2004-01-01

The Digital Shaded-Relief Map of Venezuela is a composite of more than 20 tiles of 90 meter (3 arc second) pixel resolution elevation data, captured during the Shuttle Radar Topography Mission (SRTM) in February 2000. The SRTM, a joint project between the National Geospatial-Intelligence Agency (NGA) and the National Aeronautics and Space Administration (NASA), provides the most accurate and comprehensive international digital elevation dataset ever assembled. The 10-day flight mission aboard the U.S. Space Shuttle Endeavour obtained elevation data for about 80% of the world's landmass at 3-5 meter pixel resolution through the use of synthetic aperture radar (SAR) technology. SAR is desirable because it acquires data along continuous swaths, maintaining data consistency across large areas, independent of cloud cover. Swaths were captured at an altitude of 230 km, and are approximately 225 km wide with varying lengths. Rendering of the shaded-relief image required editing of the raw elevation data to remove numerous holes and anomalously high and low values inherent in the dataset. Customized ArcInfo Arc Macro Language (AML) scripts were written to interpolate areas of null values and generalize irregular elevation spikes and wells. Coastlines and major water bodies used as a clipping mask were extracted from 1:500,000-scale geologic maps of Venezuela (Bellizzia and others, 1976). The shaded-relief image was rendered with an illumination azimuth of 315? and an altitude of 65?. A vertical exaggeration of 2X was applied to the image to enhance land-surface features. Image post-processing techniques were accomplished using conventional desktop imaging software.

Digital Elevation Models of the Earth derived from space-based observations: Advances and potential for geomorphological studies

NASA Astrophysics Data System (ADS)

Mouratidis, Antonios

2013-04-01

Digital Elevation Models (DEMs) are an inherently interdisciplinary topic, both due to their production and validation methods, as well as their significance for numerous disciplines. The most utilized contemporary topographic datasets worldwide are those of global DEMs. Several space-based sources have been used for the production of (almost) global DEMs, namely satellite Synthetic Aperture Radar (SAR) Interferometry/InSAR, stereoscopy of multispectral satellite images and altimetry, producing several versions of autonomous or mixed products (i.e. SRTM, ACE, ASTER-GDEM). Complementary space-based observations, such as those of Global Navigation Satellite Systems (GNSS), are also used, mainly for validation purposes. The apparent positive impact of these elevation datasets so far has been consolidated by the plethora of related scientific, civil and military applications. Topography is a prominent element for almost all Earth sciences, but in Geomorphology it is even more fundamental. In geomorphological studies, elevation data and thus DEMs can be extensively used for the extraction of both qualitative and quantitative information, such as relief classification, determination of slope and slope orientation, delineation of drainage basins, extraction of drainage networks and much more. Global DEMs are constantly becoming finer, i.e. of higher spatial resolution and more "sensitive" to elevation changes, i.e. of higher vertical accuracy and these progresses are undoubtedly considered as a major breakthrough, each time a new improved global DEM is released. Nevertheless, for Geomorphology in particular, if not already there, we are close to the point in time, where the need for discrimination between DSM (Digital Surface Model) and DTM (Digital Terrain Model) is becoming critical; if the distinction between vegetation and man-made structures on one side (DSM), and actual terrain elevation on the other side (DTM) cannot be made, then, in many cases, any further increase of elevation accuracy in DEMs will have little impact on geomorphological studies. After shortly reviewing the evolution of satellite-based global DEMs, the purpose of this paper is to address their current limitations and challenges from the perspective of a geomorphologist. Subsequently, the implications for geomorphological studies are discussed, with respect to the expected near-future advances in the field, such as the TanDEM-X Global Digital Elevation Model ("WorldDEM", 2014), as well as spaceborne LIDAR (Light Detection and Ranging) approaches (e.g. Lidar Surface Topography/LIST mission, 2016-2020).

Introduction: Special issue on advances in topobathymetric mapping, models, and applications

USGS Publications Warehouse

Gesch, Dean B.; Brock, John C.; Parrish, Christopher E.; Rogers, Jeffrey N.; Wright, C. Wayne

2016-01-01

Detailed knowledge of near-shore topography and bathymetry is required for many geospatial data applications in the coastal environment. New data sources and processing methods are facilitating development of seamless, regional-scale topobathymetric digital elevation models. These elevation models integrate disparate multi-sensor, multi-temporal topographic and bathymetric datasets to provide a coherent base layer for coastal science applications such as wetlands mapping and monitoring, sea-level rise assessment, benthic habitat mapping, erosion monitoring, and storm impact assessment. The focus of this special issue is on recent advances in the source data, data processing and integration methods, and applications of topobathymetric datasets.

The effects of wavelet compression on Digital Elevation Models (DEMs)

USGS Publications Warehouse

Oimoen, M.J.

2004-01-01

This paper investigates the effects of lossy compression on floating-point digital elevation models using the discrete wavelet transform. The compression of elevation data poses a different set of problems and concerns than does the compression of images. Most notably, the usefulness of DEMs depends largely in the quality of their derivatives, such as slope and aspect. Three areas extracted from the U.S. Geological Survey's National Elevation Dataset were transformed to the wavelet domain using the third order filters of the Daubechies family (DAUB6), and were made sparse by setting 95 percent of the smallest wavelet coefficients to zero. The resulting raster is compressible to a corresponding degree. The effects of the nulled coefficients on the reconstructed DEM are noted as residuals in elevation, derived slope and aspect, and delineation of drainage basins and streamlines. A simple masking technique also is presented, that maintains the integrity and flatness of water bodies in the reconstructed DEM.

Comparison of Surface Flow Features from Lidar-Derived Digital Elevation Models with Historical Elevation and Hydrography Data for Minnehaha County, South Dakota

USGS Publications Warehouse

Poppenga, Sandra K.; Worstell, Bruce B.; Stoker, Jason M.; Greenlee, Susan K.

2009-01-01

The U.S. Geological Survey (USGS) has taken the lead in the creation of a valuable remote sensing product by incorporating digital elevation models (DEMs) derived from Light Detection and Ranging (lidar) into the National Elevation Dataset (NED), the elevation layer of 'The National Map'. High-resolution lidar-derived DEMs provide the accuracy needed to systematically quantify and fully integrate surface flow including flow direction, flow accumulation, sinks, slope, and a dense drainage network. In 2008, 1-meter resolution lidar data were acquired in Minnehaha County, South Dakota. The acquisition was a collaborative effort between Minnehaha County, the city of Sioux Falls, and the USGS Earth Resources Observation and Science (EROS) Center. With the newly acquired lidar data, USGS scientists generated high-resolution DEMs and surface flow features. This report compares lidar-derived surface flow features in Minnehaha County to 30- and 10-meter elevation data previously incorporated in the NED and ancillary hydrography datasets. Surface flow features generated from lidar-derived DEMs are consistently integrated with elevation and are important in understanding surface-water movement to better detect surface-water runoff, flood inundation, and erosion. Many topographic and hydrologic applications will benefit from the increased availability of accurate, high-quality, and high-resolution surface-water data. The remotely sensed data provide topographic information and data integration capabilities needed for meeting current and future human and environmental needs.

Influence of Elevation Data Source on 2D Hydraulic Modelling

NASA Astrophysics Data System (ADS)

Bakuła, Krzysztof; StĘpnik, Mateusz; Kurczyński, Zdzisław

2016-08-01

The aim of this paper is to analyse the influence of the source of various elevation data on hydraulic modelling in open channels. In the research, digital terrain models from different datasets were evaluated and used in two-dimensional hydraulic models. The following aerial and satellite elevation data were used to create the representation of terrain-digital terrain model: airborne laser scanning, image matching, elevation data collected in the LPIS, EuroDEM, and ASTER GDEM. From the results of five 2D hydrodynamic models with different input elevation data, the maximum depth and flow velocity of water were derived and compared with the results of the most accurate ALS data. For such an analysis a statistical evaluation and differences between hydraulic modelling results were prepared. The presented research proved the importance of the quality of elevation data in hydraulic modelling and showed that only ALS and photogrammetric data can be the most reliable elevation data source in accurate 2D hydraulic modelling.

Release of a 10-m-resolution DEM for the whole Italian territory: a new, freely available resource for research purposes

NASA Astrophysics Data System (ADS)

Tarquini, S.; Nannipieri, L.; Favalli, M.; Fornaciai, A.; Vinci, S.; Doumaz, F.

2012-04-01

Digital elevation models (DEMs) are fundamental in any kind of environmental or morphological study. DEMs are obtained from a variety of sources and generated in several ways. Nowadays, a few global-coverage elevation datasets are available for free (e.g., SRTM, http://www.jpl.nasa.gov/srtm; ASTER, http://asterweb.jpl.nasa.gov/). When the matrix of a DEM is used also for computational purposes, the choice of the elevation dataset which better suits the target of the study is crucial. Recently, the increasing use of DEM-based numerical simulation tools (e.g. for gravity driven mass flows), would largely benefit from the use of a higher resolution/higher accuracy topography than those available at planetary scale. Similar elevation datasets are neither easily nor freely available for all countries worldwide. Here we introduce a new web resource which made available for free (for research purposes only) a 10 m-resolution DEM for the whole Italian territory. The creation of this elevation dataset was presented by Tarquini et al. (2007). This DEM was obtained in triangular irregular network (TIN) format starting from heterogeneous vector datasets, mostly consisting in elevation contour lines and elevation points derived from several sources. The input vector database was carefully cleaned up to obtain an improved seamless TIN refined by using the DEST algorithm, thus improving the Delaunay tessellation. The whole TINITALY/01 DEM was converted in grid format (10-m cell size) according to a tiled structure composed of 193, 50-km side square elements. The grid database consists of more than 3 billions of cells and occupies almost 12 GB of disk memory. A web-GIS has been created (http://tinitaly.pi.ingv.it/ ) where a seamless layer of images in full resolution (10 m) obtained from the whole DEM (both in color-shaded and anaglyph mode) is open for browsing. Accredited navigators are allowed to download the elevation dataset.

Characterization of ASTER GDEM Elevation Data over Vegetated Area Compared with Lidar Data

NASA Technical Reports Server (NTRS)

Ni, Wenjian; Sun, Guoqing; Ranson, Kenneth J.

2013-01-01

Current researches based on areal or spaceborne stereo images with very high resolutions (less than 1 meter) have demonstrated that it is possible to derive vegetation height from stereo images. The second version of the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) is a state-of-the-art global elevation data-set developed by stereo images. However, the resolution of ASTER stereo images (15 meters) is much coarser than areal stereo images, and the ASTER GDEM is compiled products from stereo images acquired over 10 years. The forest disturbances as well as forest growth are inevitable in 10 years time span. In this study, the features of ASTER GDEM over vegetated areas under both flat and mountainous conditions were investigated by comparisons with lidar data. The factors possibly affecting the extraction of vegetation canopy height considered include (1) co-registration of DEMs; (2) spatial resolution of digital elevation models (DEMs); (3) spatial vegetation structure; and (4) terrain slope. The results show that accurate co-registration between ASTER GDEM and the National Elevation Dataset (NED) is necessary over mountainous areas. The correlation between ASTER GDEM minus NED and vegetation canopy height is improved from 0.328 to 0.43 by degrading resolutions from 1 arc-second to 5 arc-seconds and further improved to 0.6 if only homogenous vegetated areas were considered.

Digital floodplain mapping and an analysis of errors involved

USGS Publications Warehouse

Hamblen, C.S.; Soong, D.T.; Cai, X.

2007-01-01

Mapping floodplain boundaries using geographical information system (GIS) and digital elevation models (DEMs) was completed in a recent study. However convenient this method may appear at first, the resulting maps potentially can have unaccounted errors. Mapping the floodplain using GIS is faster than mapping manually, and digital mapping is expected to be more common in the future. When mapping is done manually, the experience and judgment of the engineer or geographer completing the mapping and the contour resolution of the surface topography are critical in determining the flood-plain and floodway boundaries between cross sections. When mapping is done digitally, discrepancies can result from the use of the computing algorithm and digital topographic datasets. Understanding the possible sources of error and how the error accumulates through these processes is necessary for the validation of automated digital mapping. This study will evaluate the procedure of floodplain mapping using GIS and a 3 m by 3 m resolution DEM with a focus on the accumulated errors involved in the process. Within the GIS environment of this mapping method, the procedural steps of most interest, initially, include: (1) the accurate spatial representation of the stream centerline and cross sections, (2) properly using a triangulated irregular network (TIN) model for the flood elevations of the studied cross sections, the interpolated elevations between them and the extrapolated flood elevations beyond the cross sections, and (3) the comparison of the flood elevation TIN with the ground elevation DEM, from which the appropriate inundation boundaries are delineated. The study area involved is of relatively low topographic relief; thereby, making it representative of common suburban development and a prime setting for the need of accurately mapped floodplains. This paper emphasizes the impacts of integrating supplemental digital terrain data between cross sections on floodplain delineation. ?? 2007 ASCE.

New Geologic Map of the Scandia Region of Mars

NASA Technical Reports Server (NTRS)

Tanaka, K. L.; Rodriquez, J. A. P.; Skinner, J. A., Jr.; Hayward, R. K.; Fortezzo, C.; Edmundson, K.; Rosiek, M.

2009-01-01

We have begun work on a sophisti-cated digital geologic map of the Scandia region (Fig. 1) at 1:3,000,000 scale based on post-Viking image and to-pographic datasets. Through application of GIS tools, we will produce a map product that will consist of (1) a printed photogeologic map displaying geologic units and relevant modificational landforms produced by tectonism, erosion, and collapse/mass wasting; (2) a landform geoda-tabase including sublayers of key landform types, attributed with direct measurements of their planform and to-pography using Mars Orbiter Laser Altimeter (MOLA) altimetry data and High-Resolution Stereo Camera (HRSC) digital elevation models (DEMs) and various image datasets; and (3) a series of digital, reconstructed paleostratigraphic and paleotopographic maps showing the inferred distribution and topographic form of materi-als and features during past ages

NASA's Earth Science Use of Commercially Availiable Remote Sensing Datasets: Cover Image

NASA Technical Reports Server (NTRS)

Underwood, Lauren W.; Goward, Samuel N.; Fearon, Matthew G.; Fletcher, Rose; Garvin, Jim; Hurtt, George

2008-01-01

The cover image incorporates high resolution stereo pairs acquired from the DigitalGlobe(R) QuickBird sensor. It shows a digital elevation model of Meteor Crater, Arizona at approximately 1.3 meter point-spacing. Image analysts used the Leica Photogrammetry Suite to produce the DEM. The outside portion was computed from two QuickBird panchromatic scenes acquired October 2006, while an Optech laser scan dataset was used for the crater s interior elevations. The crater s terrain model and image drape were created in a NASA Constellation Program project focused on simulating lunar surface environments for prototyping and testing lunar surface mission analysis and planning tools. This work exemplifies NASA s Scientific Data Purchase legacy and commercial high resolution imagery applications, as scientists use commercial high resolution data to examine lunar analog Earth landscapes for advanced planning and trade studies for future lunar surface activities. Other applications include landscape dynamics related to volcanism, hydrologic events, climate change, and ice movement.

Estimation of average annual streamflows and power potentials for Alaska and Hawaii

DOE Office of Scientific and Technical Information (OSTI.GOV)

Verdin, Kristine L.

2004-05-01

This paper describes the work done to develop average annual streamflow estimates and power potential for the states of Alaska and Hawaii. The Elevation Derivatives for National Applications (EDNA) database was used, along with climatic datasets, to develop flow and power estimates for every stream reach in the EDNA database. Estimates of average annual streamflows were derived using state-specific regression equations, which were functions of average annual precipitation, precipitation intensity, drainage area, and other elevation-derived parameters. Power potential was calculated through the use of the average annual streamflow and the hydraulic head of each reach, which is calculated from themore » EDNA digital elevation model. In all, estimates of streamflow and power potential were calculated for over 170,000 stream segments in the Alaskan and Hawaiian datasets.« less

TopoLens: Building a cyberGIS community data service for enhancing the usability of high-resolution National Topographic datasets

USGS Publications Warehouse

Hu, Hao; Hong, Xingchen; Terstriep, Jeff; Liu, Yan; Finn, Michael P.; Rush, Johnathan; Wendel, Jeffrey; Wang, Shaowen

2016-01-01

Geospatial data, often embedded with geographic references, are important to many application and science domains, and represent a major type of big data. The increased volume and diversity of geospatial data have caused serious usability issues for researchers in various scientific domains, which call for innovative cyberGIS solutions. To address these issues, this paper describes a cyberGIS community data service framework to facilitate geospatial big data access, processing, and sharing based on a hybrid supercomputer architecture. Through the collaboration between the CyberGIS Center at the University of Illinois at Urbana-Champaign (UIUC) and the U.S. Geological Survey (USGS), a community data service for accessing, customizing, and sharing digital elevation model (DEM) and its derived datasets from the 10-meter national elevation dataset, namely TopoLens, is created to demonstrate the workflow integration of geospatial big data sources, computation, analysis needed for customizing the original dataset for end user needs, and a friendly online user environment. TopoLens provides online access to precomputed and on-demand computed high-resolution elevation data by exploiting the ROGER supercomputer. The usability of this prototype service has been acknowledged in community evaluation.

ISED: Constructing a high-resolution elevation road dataset from massive, low-quality in-situ observations derived from geosocial fitness tracking data.

PubMed

McKenzie, Grant; Janowicz, Krzysztof

2017-01-01

Gaining access to inexpensive, high-resolution, up-to-date, three-dimensional road network data is a top priority beyond research, as such data would fuel applications in industry, governments, and the broader public alike. Road network data are openly available via user-generated content such as OpenStreetMap (OSM) but lack the resolution required for many tasks, e.g., emergency management. More importantly, however, few publicly available data offer information on elevation and slope. For most parts of the world, up-to-date digital elevation products with a resolution of less than 10 meters are a distant dream and, if available, those datasets have to be matched to the road network through an error-prone process. In this paper we present a radically different approach by deriving road network elevation data from massive amounts of in-situ observations extracted from user-contributed data from an online social fitness tracking application. While each individual observation may be of low-quality in terms of resolution and accuracy, taken together they form an accurate, high-resolution, up-to-date, three-dimensional road network that excels where other technologies such as LiDAR fail, e.g., in case of overpasses, overhangs, and so forth. In fact, the 1m spatial resolution dataset created in this research based on 350 million individual 3D location fixes has an RMSE of approximately 3.11m compared to a LiDAR-based ground-truth and can be used to enhance existing road network datasets where individual elevation fixes differ by up to 60m. In contrast, using interpolated data from the National Elevation Dataset (NED) results in 4.75m RMSE compared to the base line. We utilize Linked Data technologies to integrate the proposed high-resolution dataset with OpenStreetMap road geometries without requiring any changes to the OSM data model.

A Seamless, High-Resolution, Coastal Digital Elevation Model (DEM) for Southern California

USGS Publications Warehouse

Barnard, Patrick L.; Hoover, Daniel

2010-01-01

A seamless, 3-meter digital elevation model (DEM) was constructed for the entire Southern California coastal zone, extending 473 km from Point Conception to the Mexican border. The goal was to integrate the most recent, high-resolution datasets available (for example, Light Detection and Ranging (Lidar) topography, multibeam and single beam sonar bathymetry, and Interferometric Synthetic Aperture Radar (IfSAR) topography) into a continuous surface from at least the 20-m isobath to the 20-m elevation contour. This dataset was produced to provide critical boundary conditions (bathymetry and topography) for a modeling effort designed to predict the impacts of severe winter storms on the Southern California coast (Barnard and others, 2009). The hazards model, run in real-time or with prescribed scenarios, incorporates atmospheric information (wind and pressure fields) with a suite of state-of-the-art physical process models (tide, surge, and wave) to enable detailed prediction of water levels, run-up, wave heights, and currents. Research-grade predictions of coastal flooding, inundation, erosion, and cliff failure are also included. The DEM was constructed to define the general shape of nearshore, beach and cliff surfaces as accurately as possible, with less emphasis on the detailed variations in elevation inland of the coast and on bathymetry inside harbors. As a result this DEM should not be used for navigation purposes.

Hydrologic Derivatives for Modeling and Analysis—A new global high-resolution database

USGS Publications Warehouse

Verdin, Kristine L.

2017-07-17

The U.S. Geological Survey has developed a new global high-resolution hydrologic derivative database. Loosely modeled on the HYDRO1k database, this new database, entitled Hydrologic Derivatives for Modeling and Analysis, provides comprehensive and consistent global coverage of topographically derived raster layers (digital elevation model data, flow direction, flow accumulation, slope, and compound topographic index) and vector layers (streams and catchment boundaries). The coverage of the data is global, and the underlying digital elevation model is a hybrid of three datasets: HydroSHEDS (Hydrological data and maps based on SHuttle Elevation Derivatives at multiple Scales), GMTED2010 (Global Multi-resolution Terrain Elevation Data 2010), and the SRTM (Shuttle Radar Topography Mission). For most of the globe south of 60°N., the raster resolution of the data is 3 arc-seconds, corresponding to the resolution of the SRTM. For the areas north of 60°N., the resolution is 7.5 arc-seconds (the highest resolution of the GMTED2010 dataset) except for Greenland, where the resolution is 30 arc-seconds. The streams and catchments are attributed with Pfafstetter codes, based on a hierarchical numbering system, that carry important topological information. This database is appropriate for use in continental-scale modeling efforts. The work described in this report was conducted by the U.S. Geological Survey in cooperation with the National Aeronautics and Space Administration Goddard Space Flight Center.

Glacier-specific elevation changes in western Alaska

NASA Astrophysics Data System (ADS)

Paul, Frank; Le Bris, Raymond

2013-04-01

Deriving glacier-specific elevation changes from DEM differencing and digital glacier outlines is rather straight-forward if the required datasets are available. Calculating such changes over large regions and including glaciers selected for mass balance measurements in the field, provides a possibility to determine the representativeness of the changes observed at these glaciers for the entire region. The related comparison of DEM-derived values for these glaciers with the overall mean avoids the rather error-prone conversion of volume to mass changes (e.g. due to unknown densities) and gives unit-less correction factors for upscaling the field measurements to a larger region. However, several issues have to be carefully considered, such as proper co-registration of the two DEMs, date and accuracy of the datasets compared, as well as source data used for DEM creation and potential artefacts (e.g. voids). In this contribution we present an assessment of the representativeness of the two mass balance glaciers Gulkana and Wolverine for the overall changes of nearly 3200 glaciers in western Alaska over a ca. 50-year time period. We use an elevation change dataset from a study by Berthier et al. (2010) that was derived from the USGS DEM of the 1960s (NED) and a more recent DEM derived from SPOT5 data for the SPIRIT project. Additionally, the ASTER GDEM was used as a more recent DEM. Historic glacier outlines were taken from the USGS digital line graph (DLG) dataset, corrected with the digital raster graph (DRG) maps from USGS. Mean glacier specific elevation changes were derived based on drainage divides from a recently created inventory. Land-terminating, lake-calving and tidewater glaciers were marked in the attribute table to determine their changes separately. We also investigated the impact of handling potential DEM artifacts in three different ways and compared elevation changes with altitude. The mean elevation changes of Gulkana and Wolverine glaciers (about -0.65 m / year) are very similar to the mean of the lake-calving and tidewater glaciers (about -0.6 m / year), but much more negative than for the land-terminating glaciers (about -0.24 m / year). The two mass balance glaciers are thus well representative for the entire region, but not for their own class. The different ways of considering positive elevation changes (e.g. setting them to zero or no data) influence the total values, but has otherwise little impact on the results (e.g. the correction factors are similar). The massive elevation loss of Columbia Glacier (-2.8 m / year) is exceptional and strongly influences the statistics when area-weighting is used to determine the regional mean. For the entire region this method yields more negative values for land-terminating and tidewater glaciers than the arithmetically averaged values, but for the lake-calving glaciers both are about the same.

Terrestrial-based lidar beach topography of Fire Island, New York, June 2014

USGS Publications Warehouse

Brenner, Owen T.; Hapke, Cheryl J.; Lee, Kathryn G.; Kimbrow, Dustin R.

2016-02-19

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) in Florida and the USGS Lower Mississippi-Gulf Water Science Center (LMG WSC) in Montgomery, Alabama, collaborated to gather alongshore terrestrial-based lidar beach elevation data at Fire Island, New York. This high-resolution elevation dataset was collected on June 11, 2014, to characterize beach topography and document ongoing beach evolution and recovery, and is part of the ongoing beach monitoring within the Hurricane Sandy Supplemental Project GS2-2B. This USGS data series includes the resulting processed elevation point data (xyz) and an interpolated digital elevation model (DEM).

Developing a new global network of river reaches from merged satellite-derived datasets

NASA Astrophysics Data System (ADS)

Lion, C.; Allen, G. H.; Beighley, E.; Pavelsky, T.

2015-12-01

In 2020, the Surface Water and Ocean Topography satellite (SWOT), a joint mission of NASA/CNES/CSA/UK will be launched. One of its major products will be the measurements of continental water extent, including the width, height, and slope of rivers and the surface area and elevations of lakes. The mission will improve the monitoring of continental water and also our understanding of the interactions between different hydrologic reservoirs. For rivers, SWOT measurements of slope must be carried out over predefined river reaches. As such, an a priori dataset for rivers is needed in order to facilitate analysis of the raw SWOT data. The information required to produce this dataset includes measurements of river width, elevation, slope, planform, river network topology, and flow accumulation. To produce this product, we have linked two existing global datasets: the Global River Widths from Landsat (GRWL) database, which contains river centerline locations, widths, and a braiding index derived from Landsat imagery, and a modified version of the HydroSHEDS hydrologically corrected digital elevation product, which contains heights and flow accumulation measurements for streams at 3 arcsecond spatial resolution. Merging these two datasets requires considerable care. The difficulties, among others, lie in the difference of resolution: 30m versus 3 arseconds, and the age of the datasets: 2000 versus ~2010 (some rivers have moved, the braided sections are different). As such, we have developed custom software to merge the two datasets, taking into account the spatial proximity of river channels in the two datasets and ensuring that flow accumulation in the final dataset always increases downstream. Here, we present our preliminary results for a portion of South America and demonstrate the strengths and weaknesses of the method.

A New Era in Geodesy and Cartography: Implications for Landing Site Operations

NASA Technical Reports Server (NTRS)

Duxbury, T. C.

2001-01-01

The Mars Global Surveyor (MGS) Mars Orbiter Laser Altimeter (MOLA) global dataset has ushered in a new era for Mars local and global geodesy and cartography. These data include the global digital terrain model (Digital Terrain Model (DTM) radii), the global digital elevation model (Digital Elevation Model (DEM) elevation with respect to the geoid), and the higher spatial resolution individual MOLA ground tracks. Currently there are about 500,000,000 MOLA points and this number continues to grow as MOLA continues successful operations in orbit about Mars, the combined processing of radiometric X-band Doppler and ranging tracking of MGS together with millions of MOLA orbital crossover points has produced global geodetic and cartographic control having a spatial (latitude/longitude) accuracy of a few meters and a topographic accuracy of less than 1 meter. This means that the position of an individual MOLA point with respect to the center-of-mass of Mars is know to an absolute accuracy of a few meters. The positional accuracy of this point in inertial space over time is controlled by the spin rate uncertainty of Mars which is less than 1 km over 10 years that will be improved significantly with the next landed mission.

Geocoding and stereo display of tropical forest multisensor datasets

NASA Technical Reports Server (NTRS)

Welch, R.; Jordan, T. R.; Luvall, J. C.

1990-01-01

Concern about the future of tropical forests has led to a demand for geocoded multisensor databases that can be used to assess forest structure, deforestation, thermal response, evapotranspiration, and other parameters linked to climate change. In response to studies being conducted at the Braulino Carrillo National Park, Costa Rica, digital satellite and aircraft images recorded by Landsat TM, SPOT HRV, Thermal Infrared Multispectral Scanner, and Calibrated Airborne Multispectral Scanner sensors were placed in register using the Landsat TM image as the reference map. Despite problems caused by relief, multitemporal datasets, and geometric distortions in the aircraft images, registration was accomplished to within + or - 20 m (+ or - 1 data pixel). A digital elevation model constructed from a multisensor Landsat TM/SPOT stereopair proved useful for generating perspective views of the rugged, forested terrain.

National Hydrography Dataset Plus (NHDPlus)

EPA Pesticide Factsheets

The NHDPlus Version 1.0 is an integrated suite of application-ready geospatial data sets that incorporate many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,000-scale NHD), improved networking, naming, and value-added attributes (VAA's). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainageenforcement technique first broadly applied in New England, and thus dubbed The New-England Method. This technique involves burning-in the 1:100,000-scale NHD and when available building walls using the national WatershedBoundary Dataset (WBD). The resulting modified digital elevation model(HydroDEM) is used to produce hydrologic derivatives that agree with the NHDand WBD. An interdisciplinary team from the U. S. Geological Survey (USGS), U.S. Environmental Protection Agency (USEPA), and contractors, over the lasttwo years has found this method to produce the best quality NHD catchments using an automated process.The VAAs include greatly enhanced capabilities for upstream and downstream navigation, analysis and modeling. Examples include: retrieve all flowlines (predominantly confluence-to-confluence stream segments) and catchments upstream of a given flowline using queries rather than by slower flowline-by flowline navigation; retrieve flowlines by stream order; subset a stream level path sorted in hydrologic order for st

Developing a Global Network of River Reaches in Preparation of SWOT

NASA Astrophysics Data System (ADS)

Lion, C.; Pavelsky, T.; Allen, G. H.; Beighley, E.; Schumann, G.; Durand, M. T.

2016-12-01

In 2020, the Surface Water and Ocean Topography satellite (SWOT), a joint mission of NASA/CNES/CSA/UK will be launched. One of its major products will be the measurements of continental water surfaces, including the width, height, and slope of rivers and the surface area and elevations of lakes. The mission will improve the monitoring of continental water and also our understanding of the interactions between different hydrologic reservoirs. For rivers, SWOT measurements of slope will be carried out over predefined river reaches. As such, an a priori dataset for rivers is needed in order to facilitate analysis of the raw SWOT data. The information required to produce this dataset includes measurements of river width, elevation, slope, planform, river network topology, and flow accumulation. To produce this product, we have linked two existing global datasets: the Global River Widths from Landsat (GRWL) database, which contains river centerline locations, widths, and a braiding index derived from Landsat imagery, and a modified version of the HydroSHEDS hydrologically corrected digital elevation product, which contains heights and flow accumulation measurements for streams at 3 arcseconds spatial resolution. Merging these two datasets requires considerable care. The difficulties, among others, lie in the difference of resolution: 30m versus 3 arseconds, and the age of the datasets: 2000 versus 2010 (some rivers have moved, the braided sections are different). As such, we have developed custom software to merge the two datasets, taking into account the spatial proximity of river channels in the two datasets and ensuring that flow accumulation in the final dataset always increases downstream. Here, we present our results for the globe.

Back to the Future: Have Remotely Sensed Digital Elevation Models Improved Hydrological Parameter Extraction?

NASA Astrophysics Data System (ADS)

Jarihani, B.

2015-12-01

Digital Elevation Models (DEMs) that accurately replicate both landscape form and processes are critical to support modeling of environmental processes. Pre-processing analysis of DEMs and extracting characteristics of the watershed (e.g., stream networks, catchment delineation, surface and subsurface flow paths) is essential for hydrological and geomorphic analysis and sediment transport. This study investigates the status of the current remotely-sensed DEMs in providing advanced morphometric information of drainage basins particularly in data sparse regions. Here we assess the accuracy of three available DEMs: (i) hydrologically corrected "H-DEM" of Geoscience Australia derived from the Shuttle Radar Topography Mission (SRTM) data; (ii) the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) version2 1-arc-second (~30 m) data; and (iii) the 9-arc-second national GEODATA DEM-9S ver3 from Geoscience Australia and the Australian National University. We used ESRI's geospatial data model, Arc Hydro and HEC-GeoHMS, designed for building hydrologic information systems to synthesize geospatial and temporal water resources data that support hydrologic modeling and analysis. A coastal catchment in northeast Australia was selected as the study site where very high resolution LiDAR data are available for parts of the area as reference data to assess the accuracy of other lower resolution datasets. This study provides morphometric information for drainage basins as part of the broad research on sediment flux from coastal basins to Great Barrier Reef, Australia. After applying geo-referencing and elevation corrections, stream and sub basins were delineated for each DEM. Then physical characteristics for streams (i.e., length, upstream and downstream elevation, and slope) and sub-basins (i.e., longest flow lengths, area, relief and slopes) were extracted and compared with reference datasets from LiDAR. Results showed that, in the absence of high-precision and high resolution DEM data, ASTER GDEM or SRTM DEM can be used to extract common morphometric relationship which are widely used for hydrological and geomorphological modelling.

Ground-based lidar beach topography of Fire Island, New York, April 2013

USGS Publications Warehouse

Brenner, Owen T.; Hapke, Cheryl J.; Spore, Nicholas J.; Brodie, Katherine L.; McNinch, Jesse E.

2015-01-01

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center in Florida and the U.S. Army Corps of Engineers Field Research Facility in Duck, North Carolina, collaborated to gather alongshore ground-based lidar beach elevation data at Fire Island, New York. This high-resolution elevation dataset was collected on April 10, 2013, to characterize beach topography following substantial erosion that occurred during Hurricane Sandy, which made landfall on October 29, 2012, and multiple, strong winter storms. The ongoing beach monitoring is part of the Hurricane Sandy Supplemental Project GS2-2B. This USGS data series includes the resulting processed elevation point data (xyz) and an interpolated digital elevation model (DEM).

Comparison of different landform classification methods for digital landform and soil mapping of the Iranian loess plateau

NASA Astrophysics Data System (ADS)

Hoffmeister, Dirk; Kramm, Tanja; Curdt, Constanze; Maleki, Sedigheh; Khormali, Farhad; Kehl, Martin

2016-04-01

The Iranian loess plateau is covered by loess deposits, up to 70 m thick. Tectonic uplift triggered deep erosion and valley incision into the loess and underlying marine deposits. Soil development strongly relates to the aspect of these incised slopes, because on northern slopes vegetation protects the soil surface against erosion and facilitates formation and preservation of a Cambisol, whereas on south-facing slopes soils were probably eroded and weakly developed Entisols formed. While the whole area is intensively stocked with sheep and goat, rain-fed cropping of winter wheat is practiced on the valley floors. Most time of the year, the soil surface is unprotected against rainfall, which is one of the factors promoting soil erosion and serious flooding. However, little information is available on soil distribution, plant cover and the geomorphological evolution of the plateau, as well as on potentials and problems in land use. Thus, digital landform and soil mapping is needed. As a requirement of digital landform and soil mapping, four different landform classification methods were compared and evaluated. These geomorphometric classifications were run on two different scales. On the whole area an ASTER GDEM and SRTM dataset (30 m pixel resolution) was used. Likewise, two high-resolution digital elevation models were derived from Pléiades satellite stereo-imagery (< 1m pixel resolution, 10 by 10 km). The high-resolution information of this dataset was aggregated to datasets of 5 and 10 m scale. The applied classification methods are the Geomorphons approach, an object-based image approach, the topographical position index and a mainly slope based approach. The accuracy of the classification was checked with a location related image dataset obtained in a field survey (n ~ 150) in September 2015. The accuracy of the DEMs was compared to measured DGPS trenches and map-based elevation data. The overall derived accuracy of the landform classification based on the high-resolution DEM with a resolution of 5 m is approximately 70% and on a 10 m resolution >58%. For the 30 m resolution datasets is the achieved accuracy approximately 40%, as several small scale features are not recognizable in this resolution. Thus, for an accurate differentiation between different important landform types, high-resolution datasets are necessary for this strongly shaped area. One major problem of this approach are the different classes derived by each method and the various class annotations. The result of this evaluation will be regarded for the derivation of landform and soil maps.

User's Guide for the Agricultural Non-Point Source (AGNPS) Pollution Model Data Generator

USGS Publications Warehouse

Finn, Michael P.; Scheidt, Douglas J.; Jaromack, Gregory M.

2003-01-01

BACKGROUND Throughout this user guide, we refer to datasets that we used in conjunction with developing of this software for supporting cartographic research and producing the datasets to conduct research. However, this software can be used with these datasets or with more 'generic' versions of data of the appropriate type. For example, throughout the guide, we refer to national land cover data (NLCD) and digital elevation model (DEM) data from the U.S. Geological Survey (USGS) at a 30-m resolution, but any digital terrain model or land cover data at any appropriate resolution will produce results. Another key point to keep in mind is to use a consistent data resolution for all the datasets per model run. The U.S. Department of Agriculture (USDA) developed the Agricultural Nonpoint Source (AGNPS) pollution model of watershed hydrology in response to the complex problem of managing nonpoint sources of pollution. AGNPS simulates the behavior of runoff, sediment, and nutrient transport from watersheds that have agriculture as their prime use. The model operates on a cell basis and is a distributed parameter, event-based model. The model requires 22 input parameters. Output parameters are grouped primarily by hydrology, sediment, and chemical output (Young and others, 1995.) Elevation, land cover, and soil are the base data from which to extract the 22 input parameters required by the AGNPS. For automatic parameter extraction, follow the general process described in this guide of extraction from the geospatial data through the AGNPS Data Generator to generate input parameters required by the pollution model (Finn and others, 2002.)

Spatial analysis of fluvial terraces in GRASS GIS accessing R functionality

NASA Astrophysics Data System (ADS)

Józsa, Edina

2017-04-01

Terrace research along the Danube is a major topic of Hungarian traditional geomorphology because of the socio-economic role of terrace surfaces and their importance in paleo-environmental reconstructions. Semi-automated mapping of fluvial landforms from a coherent digital elevation dataset allow objective analysis of hydrogeomorphic characteristics with low time and cost requirements. New results obtained with unified GIS-based algorithms can be integrated with previous findings regarding landscape evolution. The complementary functionality of GRASS GIS and R provides the possibility to develop a flexible terrain analysing tool for the delineation and quantifiable analysis of terrace remnants. Using R as an intermediate analytical environment and visualisation tool gives great added value to the algorithm, while GRASS GIS is capable of handling the large digital elevation datasets and perform the demanding computations to prepare necessary raster derivatives (Bivand, R.S. et al. 2008). The proposed terrace mapping algorithm is based on the work of Demoulin, A. et al. (2007), but it is further improved in the form of GRASS GIS script tool accessing R functionality. In the first step the hydrogeomorphic signatures of the given study site are explored and the area is divided along clearly recognizable structural-morphological boundaries.The algorithm then cuts up the subregions into parallel sections in the flow direction and determines cells potentially belonging to terrace surfaces based on local slope characteristics and a minimum area size threshold. As a result an output report is created that contains a histogram of altitudes, a swath-profile of the landscape, scatter plots to represent the relation of the relative elevations and slope values in the analysed sections and a final plot showing the longitudinal profile of the river with the determined height ranges of terrace levels. The algorithm also produces a raster map of extracted terrace remnants. From this dataset it is possible to interpolate a new digital elevation model approximating the former terraced valley surface using the Ordinary Kriging method (Troiani, F. and Della Seta, M. 2011). The applicability of the algorithm was tested on the northern foreland of Gerecse Mountains, an antecedent valley section of the Danube, with terrace remnants expected in 6 to 8 altitude ranges. Methodological issues arising from determining the optimal threshold values were explored using an artificial hillslope model, while the terrace profiles and terrace-top surfaces raster generated from the digital elevation model were validated with the previous findings of traditional geomorphological surveys. This research was supported by the Human Capacities Grant Management Office and the Hungarian Ministry of Human Capacities in the framework of the NTP-NFTÖ-16 project. References: Bivand, R.S. et al. (2008). Applied Spatial Data Analysis with R. New York: Springer. 378 p. Demoulin, A. et al. (2007). An automated method to extract fluvial terraces from digital elevation models: The Vesdre valley, a case study in eastern Belgium. - Geomorphology 91 (1-2): 51-64. Troiani, E. and Della Seta, M. (2011). Geomorphological response of fluvial and coastal terraces to Quaternary tectonics and climate as revealed by geostatistical topographic analysis. - Earth Surface Processes and Landforms 36: 1193-1208.

One-meter topobathymetric digital elevation model for Majuro Atoll, Republic of the Marshall Islands, 1944 to 2016

USGS Publications Warehouse

Palaseanu-Lovejoy, Monica; Poppenga, Sandra K.; Danielson, Jeffrey J.; Tyler, Dean J.; Gesch, Dean B.; Kottermair, Maria; Jalandoni, Andrea; Carlson, Edward; Thatcher, Cindy A.; Barbee, Matthew M.

2018-03-30

Atoll and island coastal communities are highly exposed to sea-level rise, tsunamis, storm surges, rogue waves, king tides, and the occasional combination of multiple factors, such as high regional sea levels, extreme high local tides, and unusually strong wave set-up. The elevation of most of these atolls averages just under 3 meters (m), with many areas roughly at sea level. The lack of high-resolution topographic data has been identified as a critical data gap for hazard vulnerability and adaptation efforts and for high-resolution inundation modeling for atoll nations. Modern topographic survey equipment and airborne lidar surveys can be very difficult and costly to deploy. Therefore, unmanned aircraft systems (UAS) were investigated for collecting overlapping imagery to generate topographic digital elevation models (DEMs). Medium- and high-resolution satellite imagery (Landsat 8 and WorldView-3) was investigated to derive nearshore bathymetry.The Republic of the Marshall Islands is associated with the United States through a Compact of Free Association, and Majuro Atoll is home to the capital city of Majuro and the largest population of the Republic of the Marshall Islands. The only elevation datasets currently available for the entire Majuro Atoll are the Shuttle Radar Topography Mission and the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model Version 2 elevation data, which have a 30-m grid-cell spacing and a 8-m vertical root mean square error (RMSE). Both these datasets have inadequate spatial resolution and vertical accuracy for inundation modeling.The final topobathymetric DEM (TBDEM) developed for Majuro Atoll is derived from various data sources including charts, soundings, acoustic sonar, and UAS and satellite imagery spanning over 70 years of data collection (1944 to 2016) on different sections of the atoll. The RMSE of the TBDEM over the land area is 0.197 m using over 70,000 Global Navigation Satellite System real-time kinematic survey points for validation, and 1.066 m for Landsat 8 and 1.112 m for WorldView-3 derived bathymetry using over 16,000 and 9,000 lidar bathymetry points, respectively.

Topogrid Derived 10 Meter Resolution Digital Elevation Model of Charleston, and Parts of Berkeley, Colleton, Dorchester and Georgetown Counties, South Carolina

USGS Publications Warehouse

Chirico, Peter G.

2005-01-01

EXPLANATION The purpose of developing a new 10m resolution digital elevation model (DEM) of the Charleston Region was to more accurately depict geologic structure, surfical geology, and landforms of the Charleston County Region. Previously, many areas northeast and southwest of Charleston were originally mapped with a 20 foot contour interval. As a result, large areas within the National Elevation Dataset (NED) depict flat terraced topography where there was a lack of higher resolution elevation data. To overcome these data voids, the new DEM is supplemented with additional elevation data and break-lines derived from aerial photography and topographic maps. The resultant DEM is stored as a raster grid at uniform 10m horizontal resolution. The elevation model contained in this publication was prodcued utilizing the ANUDEM algorthim. ANUDEM allows for the inclusion of contours, streams, rivers, lake and water body polygons as well as spot height data to control the development of the elevation model. A preliminary statistical analysis using over 788 vertical elevation check points, primarily located in the northeastern part of the study area, derived from USGS 7.5 Minute Topographic maps reveals that the final DEM, has a vertical accuracy of ?3.27 meters. A table listing the elevation comparison between the elevation check points and the final DEM is provided.

Extraction and Validation of Geomorphological Features from EU-DEM in The Vicinity of the Mygdonia Basin, Northern Greece

NASA Astrophysics Data System (ADS)

Mouratidis, Antonios; Karadimou, Georgia; Ampatzidis, Dimitrios

2017-12-01

The European Union Digital Elevation Model (EU-DEM) is a relatively new, hybrid elevation product, principally based on SRTM DEM and ASTER GDEM data, but also on publically available Russian topographic maps for regions north of 60° N. More specifically, EU-DEM is a Digital Surface Model (DSM) over Europe from the Global Monitoring for Environment and Security (GMES) Reference Data Access (RDA) project - a realisation of the Copernicus (former GMES) programme, managed by the European Commission/DG Enterprise and Industry. Even if EU-DEM is indeed more reliable in terms of elevation accuracy than its constituents, it ought to be noted that it is not representative of the original elevation measurements, but is rather a secondary (mathematical) product. Therefore, for specific applications, such as those of geomorphological interest, artefacts may be induced. To this end, the purpose of this paper is to investigate the performance of EU-DEM for geomorphological applications and compare it against other available datasets, i.e. topographic maps and (almost) global DEMs such as SRTM, ASTER-GDEM and WorldDEM™. This initial investigation is carried out in Central Macedonia, Northern Greece, in the vicinity of the Mygdonia basin, which corresponds to an area of particular interest for several geoscience applications. This area has also been serving as a test site for the systematic validation of DEMs for more than a decade. Consequently, extensive elevation datasets and experience have been accumulated over the years, rendering the evaluation of new elevation products a coherent and useful exercise on a local to regional scale. In this context, relief classification, drainage basin delineation, slope and slope aspect, as well as extraction and classification of drainage network are performed and validated among the aforementioned elevation sources. The achieved results focus on qualitative and quantitative aspects of automatic geomorphological feature extraction from EU-DEM at a water basin level, with the use of Geographical Information Systems (GIS).

Rapid, semi-automatic fracture and contact mapping for point clouds, images and geophysical data

NASA Astrophysics Data System (ADS)

Thiele, Samuel T.; Grose, Lachlan; Samsu, Anindita; Micklethwaite, Steven; Vollgger, Stefan A.; Cruden, Alexander R.

2017-12-01

The advent of large digital datasets from unmanned aerial vehicle (UAV) and satellite platforms now challenges our ability to extract information across multiple scales in a timely manner, often meaning that the full value of the data is not realised. Here we adapt a least-cost-path solver and specially tailored cost functions to rapidly interpolate structural features between manually defined control points in point cloud and raster datasets. We implement the method in the geographic information system QGIS and the point cloud and mesh processing software CloudCompare. Using these implementations, the method can be applied to a variety of three-dimensional (3-D) and two-dimensional (2-D) datasets, including high-resolution aerial imagery, digital outcrop models, digital elevation models (DEMs) and geophysical grids. We demonstrate the algorithm with four diverse applications in which we extract (1) joint and contact patterns in high-resolution orthophotographs, (2) fracture patterns in a dense 3-D point cloud, (3) earthquake surface ruptures of the Greendale Fault associated with the Mw7.1 Darfield earthquake (New Zealand) from high-resolution light detection and ranging (lidar) data, and (4) oceanic fracture zones from bathymetric data of the North Atlantic. The approach improves the consistency of the interpretation process while retaining expert guidance and achieves significant improvements (35-65 %) in digitisation time compared to traditional methods. Furthermore, it opens up new possibilities for data synthesis and can quantify the agreement between datasets and an interpretation.

Initial Everglades Depth Estimation Network (EDEN) Digital Elevation Model Research and Development

USGS Publications Warehouse

Jones, John W.; Price, Susan D.

2007-01-01

Introduction The Everglades Depth Estimation Network (EDEN) offers a consistent and documented dataset that can be used to guide large-scale field operations, to integrate hydrologic and ecological responses, and to support biological and ecological assessments that measure ecosystem responses to the Comprehensive Everglades Restoration Plan (Telis, 2006). To produce historic and near-real time maps of water depths, the EDEN requires a system-wide digital elevation model (DEM) of the ground surface. Accurate Everglades wetland ground surface elevation data were non-existent before the U.S. Geological Survey (USGS) undertook the collection of highly accurate surface elevations at the regional scale. These form the foundation for EDEN DEM development. This development process is iterative as additional high accuracy elevation data (HAED) are collected, water surfacing algorithms improve, and additional ground-based ancillary data become available. Models are tested using withheld HAED and independently measured water depth data, and by using DEM data in EDEN adaptive management applications. Here the collection of HAED is briefly described before the approach to DEM development and the current EDEN DEM are detailed. Finally future research directions for continued model development, testing, and refinement are provided.

Initialization and Setup of the Coastal Model Test Bed: STWAVE

DTIC Science & Technology

2017-01-01

Laboratory (CHL) Field Research Facility (FRF) in Duck , NC. The improved evaluation methodology will promote rapid enhancement of model capability and focus...Blanton 2008) study . This regional digital elevation model (DEM), with a cell size of 10 m, was generated from numerous datasets collected at different...INFORMATION: For additional information, contact Spicer Bak, Coastal Observation and Analysis Branch, Coastal and Hydraulics Laboratory, 1261 Duck Road

MOLA-Based Landing Site Characterization

NASA Technical Reports Server (NTRS)

Duxbury, T. C.; Ivanov, A. B.

2001-01-01

The Mars Global Surveyor (MGS) Mars Orbiter Laser Altimeter (MOLA) data provide the basis for site characterization and selection never before possible. The basic MOLA information includes absolute radii, elevation and 1 micrometer albedo with derived datasets including digital image models (DIM's illuminated elevation data), slopes maps and slope statistics and small scale surface roughness maps and statistics. These quantities are useful in downsizing potential sites from descent engineering constraints and landing/roving hazard and mobility assessments. Slope baselines at the few hundred meter level and surface roughness at the 10 meter level are possible. Additionally, the MOLA-derived Mars surface offers the possibility to precisely register and map project other instrument datasets (images, ultraviolet, infrared, radar, etc.) taken at different resolution, viewing and lighting geometry, building multiple layers of an information cube for site characterization and selection. Examples of direct MOLA data, data derived from MOLA and other instruments data registered to MOLA arc given for the Hematite area.

Validation of "AW3D" Global Dsm Generated from Alos Prism

NASA Astrophysics Data System (ADS)

Takaku, Junichi; Tadono, Takeo; Tsutsui, Ken; Ichikawa, Mayumi

2016-06-01

Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM), one of onboard sensors carried by Advanced Land Observing Satellite (ALOS), was designed to generate worldwide topographic data with its optical stereoscopic observation. It has an exclusive ability to perform a triplet stereo observation which views forward, nadir, and backward along the satellite track in 2.5 m ground resolution, and collected its derived images all over the world during the mission life of the satellite from 2006 through 2011. A new project, which generates global elevation datasets with the image archives, was started in 2014. The data is processed in unprecedented 5 m grid spacing utilizing the original triplet stereo images in 2.5 m resolution. As the number of processed data is growing steadily so that the global land areas are almost covered, a trend of global data qualities became apparent. This paper reports on up-to-date results of the validations for the accuracy of data products as well as the status of data coverage in global areas. The accuracies and error characteristics of datasets are analyzed by the comparison with existing global datasets such as Ice, Cloud, and land Elevation Satellite (ICESat) data, as well as ground control points (GCPs) and the reference Digital Elevation Model (DEM) derived from the airborne Light Detection and Ranging (LiDAR).

Global relationships in river hydromorphology

NASA Astrophysics Data System (ADS)

Pavelsky, T.; Lion, C.; Allen, G. H.; Durand, M. T.; Schumann, G.; Beighley, E.; Yang, X.

2017-12-01

Since the widespread adoption of digital elevation models (DEMs) in the 1980s, most global and continental-scale analysis of river flow characteristics has been focused on measurements derived from DEMs such as drainage area, elevation, and slope. These variables (especially drainage area) have been related to other quantities of interest such as river width, depth, and velocity via empirical relationships that often take the form of power laws. More recently, a number of groups have developed more direct measurements of river location and some aspects of planform geometry from optical satellite imagery on regional, continental, and global scales. However, these satellite-derived datasets often lack many of the qualities that make DEM=derived datasets attractive, including robust network topology. Here, we present analysis of a dataset that combines the Global River Widths from Landsat (GRWL) database of river location, width, and braiding index with a river database extracted from the Shuttle Radar Topography Mission DEM and the HydroSHEDS dataset. Using these combined tools, we present a dataset that includes measurements of river width, slope, braiding index, upstream drainage area, and other variables. The dataset is available everywhere that both datasets are available, which includes all continental areas south of 60N with rivers sufficiently large to be observed with Landsat imagery. We use the dataset to examine patterns and frequencies of river form across continental and global scales as well as global relationships among variables including width, slope, and drainage area. The results demonstrate the complex relationships among different dimensions of river hydromorphology at the global scale.

A digital map of the high center (HC) and low center (LC) polygon boundaries delineated from high resolution LiDAR data for Barrow, Alaska

DOE Data Explorer

Gangodagamage, Chandana; Wullschleger, Stan

2014-07-03

This dataset represent a map of the high center (HC) and low center (LC) polygon boundaries delineated from high resolution LiDAR data for the arctic coastal plain at Barrow, Alaska. The polygon troughs are considered as the surface expression of the ice-wedges. The troughs are in lower elevations than the interior polygon. The trough widths were initially identified from LiDAR data, and the boundary between two polygons assumed to be located along the lowest elevations on trough widths between them.

A semi-automated tool for reducing the creation of false closed depressions from a filled LIDAR-derived digital elevation model

USGS Publications Warehouse

Waller, John S.; Doctor, Daniel H.; Terziotti, Silvia

2015-01-01

Closed depressions on the land surface can be identified by ‘filling’ a digital elevation model (DEM) and subtracting the filled model from the original DEM. However, automated methods suffer from artificial ‘dams’ where surface streams cross under bridges and through culverts. Removal of these false depressions from an elevation model is difficult due to the lack of bridge and culvert inventories; thus, another method is needed to breach these artificial dams. Here, we present a semi-automated workflow and toolbox to remove falsely detected closed depressions created by artificial dams in a DEM. The approach finds the intersections between transportation routes (e.g., roads) and streams, and then lowers the elevation surface across the roads to stream level allowing flow to be routed under the road. Once the surface is corrected to match the approximate location of the National Hydrologic Dataset stream lines, the procedure is repeated with sequentially smaller flow accumulation thresholds in order to generate stream lines with less contributing area within the watershed. Through multiple iterations, artificial depressions that may arise due to ephemeral flow paths can also be removed. Preliminary results reveal that this new technique provides significant improvements for flow routing across a DEM and minimizes artifacts within the elevation surface. Slight changes in the stream flow lines generally improve the quality of flow routes; however some artificial dams may persist. Problematic areas include extensive road ditches, particularly along divided highways, and where surface flow crosses beneath road intersections. Limitations do exist, and the results partially depend on the quality of data being input. Of 166 manually identified culverts from a previous study by Doctor and Young in 2013, 125 are within 25 m of culverts identified by this tool. After three iterations, 1,735 culverts were identified and cataloged. The result is a reconditioned elevation dataset, which retains the karst topography for further analysis, and a culvert catalog.

The pyramid system for multiscale raster analysis

USGS Publications Warehouse

De Cola, L.; Montagne, N.

1993-01-01

Geographical research requires the management and analysis of spatial data at multiple scales. As part of the U.S. Geological Survey's global change research program a software system has been developed that reads raster data (such as an image or digital elevation model) and produces a pyramid of aggregated lattices as well as various measurements of spatial complexity. For a given raster dataset the system uses the pyramid to report: (1) mean, (2) variance, (3) a spatial autocorrelation parameter based on multiscale analysis of variance, and (4) a monofractal scaling parameter based on the analysis of isoline lengths. The system is applied to 1-km digital elevation model (DEM) data for a 256-km2 region of central California, as well as to 64 partitions of the region. PYRAMID, which offers robust descriptions of data complexity, also is used to describe the behavior of topographic aspect with scale. ?? 1993.

Attributes for NHDPlus catchments (version 1.1) for the conterminous United States: surficial geology

USGS Publications Warehouse

Wieczorek, Michael; LaMotte, Andrew E.

2010-01-01

This data set represents the area of surficial geology types in square meters compiled for every catchment of NHDPlus for the conterminous United States. The source data set is the "Digital data set describing surficial geology in the conterminous US" (Clawges and Price, 1999). The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

4D very high-resolution topography monitoring of surface deformation using UAV-SfM framework.

NASA Astrophysics Data System (ADS)

Clapuyt, François; Vanacker, Veerle; Schlunegger, Fritz; Van Oost, Kristof

2016-04-01

During the last years, exploratory research has shown that UAV-based image acquisition is suitable for environmental remote sensing and monitoring. Image acquisition with cameras mounted on an UAV can be performed at very-high spatial resolution and high temporal frequency in the most dynamic environments. Combined with Structure-from-Motion algorithm, the UAV-SfM framework is capable of providing digital surface models (DSM) which are highly accurate when compared to other very-high resolution topographic datasets and highly reproducible for repeated measurements over the same study area. In this study, we aim at assessing (1) differential movement of the Earth's surface and (2) the sediment budget of a complex earthflow located in the Central Swiss Alps based on three topographic datasets acquired over a period of 2 years. For three time steps, we acquired aerial photographs with a standard reflex camera mounted on a low-cost and lightweight UAV. Image datasets were then processed with the Structure-from-Motion algorithm in order to reconstruct a 3D dense point cloud representing the topography. Georeferencing of outputs has been achieved based on the ground control point (GCP) extraction method, previously surveyed on the field with a RTK GPS. Finally, digital elevation model of differences (DOD) has been computed to assess the topographic changes between the three acquisition dates while surface displacements have been quantified by using image correlation techniques. Our results show that the digital elevation model of topographic differences is able to capture surface deformation at cm-scale resolution. The mean annual displacement of the earthflow is about 3.6 m while the forefront of the landslide has advanced by ca. 30 meters over a period of 18 months. The 4D analysis permits to identify the direction and velocity of Earth movement. Stable topographic ridges condition the direction of the flow with highest downslope movement on steep slopes, and diffuse movement due to lateral sediment flux in the central part of the earthflow.

Digital elevation model and orthophotographs of Greenland based on aerial photographs from 1978-1987.

PubMed

Korsgaard, Niels J; Nuth, Christopher; Khan, Shfaqat A; Kjeldsen, Kristian K; Bjørk, Anders A; Schomacker, Anders; Kjær, Kurt H

2016-05-10

Digital Elevation Models (DEMs) play a prominent role in glaciological studies for the mass balance of glaciers and ice sheets. By providing a time snapshot of glacier geometry, DEMs are crucial for most glacier evolution modelling studies, but are also important for cryospheric modelling in general. We present a historical medium-resolution DEM and orthophotographs that consistently cover the entire surroundings and margins of the Greenland Ice Sheet 1978-1987. About 3,500 aerial photographs of Greenland are combined with field surveyed geodetic ground control to produce a 25 m gridded DEM and a 2 m black-and-white digital orthophotograph. Supporting data consist of a reliability mask and a photo footprint coverage with recording dates. Through one internal and two external validation tests, this DEM shows an accuracy better than 10 m horizontally and 6 m vertically while the precision is better than 4 m. This dataset proved successful for topographical mapping and geodetic mass balance. Other uses include control and calibration of remotely sensed data such as imagery or InSAR velocity maps.

Digital elevation model and orthophotographs of Greenland based on aerial photographs from 1978-1987

NASA Astrophysics Data System (ADS)

Korsgaard, Niels J.; Nuth, Christopher; Khan, Shfaqat A.; Kjeldsen, Kristian K.; Bjørk, Anders A.; Schomacker, Anders; Kjær, Kurt H.

2016-05-01

Digital Elevation Models (DEMs) play a prominent role in glaciological studies for the mass balance of glaciers and ice sheets. By providing a time snapshot of glacier geometry, DEMs are crucial for most glacier evolution modelling studies, but are also important for cryospheric modelling in general. We present a historical medium-resolution DEM and orthophotographs that consistently cover the entire surroundings and margins of the Greenland Ice Sheet 1978-1987. About 3,500 aerial photographs of Greenland are combined with field surveyed geodetic ground control to produce a 25 m gridded DEM and a 2 m black-and-white digital orthophotograph. Supporting data consist of a reliability mask and a photo footprint coverage with recording dates. Through one internal and two external validation tests, this DEM shows an accuracy better than 10 m horizontally and 6 m vertically while the precision is better than 4 m. This dataset proved successful for topographical mapping and geodetic mass balance. Other uses include control and calibration of remotely sensed data such as imagery or InSAR velocity maps.

Statistical correction of lidar-derived digital elevation models with multispectral airborne imagery in tidal marshes

USGS Publications Warehouse

Buffington, Kevin J.; Dugger, Bruce D.; Thorne, Karen M.; Takekawa, John Y.

2016-01-01

Airborne light detection and ranging (lidar) is a valuable tool for collecting large amounts of elevation data across large areas; however, the limited ability to penetrate dense vegetation with lidar hinders its usefulness for measuring tidal marsh platforms. Methods to correct lidar elevation data are available, but a reliable method that requires limited field work and maintains spatial resolution is lacking. We present a novel method, the Lidar Elevation Adjustment with NDVI (LEAN), to correct lidar digital elevation models (DEMs) with vegetation indices from readily available multispectral airborne imagery (NAIP) and RTK-GPS surveys. Using 17 study sites along the Pacific coast of the U.S., we achieved an average root mean squared error (RMSE) of 0.072 m, with a 40–75% improvement in accuracy from the lidar bare earth DEM. Results from our method compared favorably with results from three other methods (minimum-bin gridding, mean error correction, and vegetation correction factors), and a power analysis applying our extensive RTK-GPS dataset showed that on average 118 points were necessary to calibrate a site-specific correction model for tidal marshes along the Pacific coast. By using available imagery and with minimal field surveys, we showed that lidar-derived DEMs can be adjusted for greater accuracy while maintaining high (1 m) resolution.

Hydrography change detection: the usefulness of surface channels derived From LiDAR DEMs for updating mapped hydrography

USGS Publications Warehouse

Poppenga, Sandra K.; Gesch, Dean B.; Worstell, Bruce B.

2013-01-01

The 1:24,000-scale high-resolution National Hydrography Dataset (NHD) mapped hydrography flow lines require regular updating because land surface conditions that affect surface channel drainage change over time. Historically, NHD flow lines were created by digitizing surface water information from aerial photography and paper maps. Using these same methods to update nationwide NHD flow lines is costly and inefficient; furthermore, these methods result in hydrography that lacks the horizontal and vertical accuracy needed for fully integrated datasets useful for mapping and scientific investigations. Effective methods for improving mapped hydrography employ change detection analysis of surface channels derived from light detection and ranging (LiDAR) digital elevation models (DEMs) and NHD flow lines. In this article, we describe the usefulness of surface channels derived from LiDAR DEMs for hydrography change detection to derive spatially accurate and time-relevant mapped hydrography. The methods employ analyses of horizontal and vertical differences between LiDAR-derived surface channels and NHD flow lines to define candidate locations of hydrography change. These methods alleviate the need to analyze and update the nationwide NHD for time relevant hydrography, and provide an avenue for updating the dataset where change has occurred.

Datasets2Tools, repository and search engine for bioinformatics datasets, tools and canned analyses

PubMed Central

Torre, Denis; Krawczuk, Patrycja; Jagodnik, Kathleen M.; Lachmann, Alexander; Wang, Zichen; Wang, Lily; Kuleshov, Maxim V.; Ma’ayan, Avi

2018-01-01

Biomedical data repositories such as the Gene Expression Omnibus (GEO) enable the search and discovery of relevant biomedical digital data objects. Similarly, resources such as OMICtools, index bioinformatics tools that can extract knowledge from these digital data objects. However, systematic access to pre-generated ‘canned’ analyses applied by bioinformatics tools to biomedical digital data objects is currently not available. Datasets2Tools is a repository indexing 31,473 canned bioinformatics analyses applied to 6,431 datasets. The Datasets2Tools repository also contains the indexing of 4,901 published bioinformatics software tools, and all the analyzed datasets. Datasets2Tools enables users to rapidly find datasets, tools, and canned analyses through an intuitive web interface, a Google Chrome extension, and an API. Furthermore, Datasets2Tools provides a platform for contributing canned analyses, datasets, and tools, as well as evaluating these digital objects according to their compliance with the findable, accessible, interoperable, and reusable (FAIR) principles. By incorporating community engagement, Datasets2Tools promotes sharing of digital resources to stimulate the extraction of knowledge from biomedical research data. Datasets2Tools is freely available from: http://amp.pharm.mssm.edu/datasets2tools. PMID:29485625

Datasets2Tools, repository and search engine for bioinformatics datasets, tools and canned analyses.

PubMed

Torre, Denis; Krawczuk, Patrycja; Jagodnik, Kathleen M; Lachmann, Alexander; Wang, Zichen; Wang, Lily; Kuleshov, Maxim V; Ma'ayan, Avi

2018-02-27

Biomedical data repositories such as the Gene Expression Omnibus (GEO) enable the search and discovery of relevant biomedical digital data objects. Similarly, resources such as OMICtools, index bioinformatics tools that can extract knowledge from these digital data objects. However, systematic access to pre-generated 'canned' analyses applied by bioinformatics tools to biomedical digital data objects is currently not available. Datasets2Tools is a repository indexing 31,473 canned bioinformatics analyses applied to 6,431 datasets. The Datasets2Tools repository also contains the indexing of 4,901 published bioinformatics software tools, and all the analyzed datasets. Datasets2Tools enables users to rapidly find datasets, tools, and canned analyses through an intuitive web interface, a Google Chrome extension, and an API. Furthermore, Datasets2Tools provides a platform for contributing canned analyses, datasets, and tools, as well as evaluating these digital objects according to their compliance with the findable, accessible, interoperable, and reusable (FAIR) principles. By incorporating community engagement, Datasets2Tools promotes sharing of digital resources to stimulate the extraction of knowledge from biomedical research data. Datasets2Tools is freely available from: http://amp.pharm.mssm.edu/datasets2tools.

The National Map - Elevation

USGS Publications Warehouse

Gesch, Dean; Evans, Gayla; Mauck, James; Hutchinson, John; Carswell, William J.

2009-01-01

The National Elevation Dataset (NED) is the primary elevation data product produced and distributed by the USGS. The NED provides seamless raster elevation data of the conterminous United States, Alaska, Hawaii, and the island territories. The NED is derived from diverse source data sets that are processed to a specification with a consistent resolution, coordinate system, elevation units, and horizontal and vertical datums. The NED is the logical result of the maturation of the long-standing USGS elevation program, which for many years concentrated on production of topographic map quadrangle-based digital elevation models. The NED serves as the elevation layer of The National Map, and provides basic elevation information for earth science studies and mapping applications in the United States. The NED is a multi-resolution dataset that is updated bimonthly to integrate newly available, improved elevation source data. NED data are available nationally at grid spacings of 1 arc-second (approximately 30 meters) for the conterminous United States, and at 1/3 and 1/9 arc-seconds (approximately 10 and 3 meters, respectively) for parts of the United States. Most of the NED for Alaska is available at 2-arc-second (about 60 meters) grid spacing, where only lower resolution source data exist. Part of Alaska is available at the 1/3-arc-second resolution, and plans are in development for a significant upgrade in elevation data coverage of the State over the next 5 years. Specifications for the NED include the following: *Coordinate system: Geographic (decimal degrees of latitude and longitude), *Horizontal datum: North American Datum of 1983 (NAD 83), *Vertical datum: North American Vertical Datum of 1988 (NAVD 88) over the conterminous United States and varies in other areas, and *Elevation units: Decimal meters.

UAS-SfM for coastal research: Geomorphic feature extraction and land cover classification from high-resolution elevation and optical imagery

USGS Publications Warehouse

Sturdivant, Emily; Lentz, Erika; Thieler, E. Robert; Farris, Amy; Weber, Kathryn; Remsen, David P.; Miner, Simon; Henderson, Rachel

2017-01-01

The vulnerability of coastal systems to hazards such as storms and sea-level rise is typically characterized using a combination of ground and manned airborne systems that have limited spatial or temporal scales. Structure-from-motion (SfM) photogrammetry applied to imagery acquired by unmanned aerial systems (UAS) offers a rapid and inexpensive means to produce high-resolution topographic and visual reflectance datasets that rival existing lidar and imagery standards. Here, we use SfM to produce an elevation point cloud, an orthomosaic, and a digital elevation model (DEM) from data collected by UAS at a beach and wetland site in Massachusetts, USA. We apply existing methods to (a) determine the position of shorelines and foredunes using a feature extraction routine developed for lidar point clouds and (b) map land cover from the rasterized surfaces using a supervised classification routine. In both analyses, we experimentally vary the input datasets to understand the benefits and limitations of UAS-SfM for coastal vulnerability assessment. We find that (a) geomorphic features are extracted from the SfM point cloud with near-continuous coverage and sub-meter precision, better than was possible from a recent lidar dataset covering the same area; and (b) land cover classification is greatly improved by including topographic data with visual reflectance, but changes to resolution (when <50 cm) have little influence on the classification accuracy.

Online, On Demand Access to Coastal Digital Elevation Models

NASA Astrophysics Data System (ADS)

Long, J.; Bristol, S.; Long, D.; Thompson, S.

2014-12-01

Process-based numerical models for coastal waves, water levels, and sediment transport are initialized with digital elevation models (DEM) constructed by interpolating and merging bathymetric and topographic elevation data. These gridded surfaces must seamlessly span the land-water interface and may cover large regions where the individual raw data sources are collected at widely different spatial and temporal resolutions. In addition, the datasets are collected from different instrument platforms with varying accuracy and may or may not overlap in coverage. The lack of available tools and difficulties in constructing these DEMs lead scientists to 1) rely on previously merged, outdated, or over-smoothed DEMs; 2) discard more recent data that covers only a portion of the DEM domain; and 3) use inconsistent methodologies to generate DEMs. The objective of this work is to address the immediate need of integrating land and water-based elevation data sources and streamline the generation of a seamless data surface that spans the terrestrial-marine boundary. To achieve this, the U.S. Geological Survey (USGS) is developing a web processing service to format and initialize geoprocessing tasks designed to create coastal DEMs. The web processing service is maintained within the USGS ScienceBase data management system and has an associated user interface. Through the map-based interface, users define a geographic region that identifies the bounds of the desired DEM and a time period of interest. This initiates a query for elevation datasets within federal science agency data repositories. A geoprocessing service is then triggered to interpolate, merge, and smooth the data sources creating a DEM based on user-defined configuration parameters. Uncertainty and error estimates for the DEM are also returned by the geoprocessing service. Upon completion, the information management platform provides access to the final gridded data derivative and saves the configuration parameters for future reference. The resulting products and tools developed here could be adapted to future data sources and projects beyond the coastal environment.

Z-Earth: 4D topography from space combining short-baseline stereo and lidar

NASA Astrophysics Data System (ADS)

Dewez, T. J.; Akkari, H.; Kaab, A. M.; Lamare, M. L.; Doyon, G.; Costeraste, J.

2013-12-01

The advent of free-of-charge global topographic data sets SRTM and Aster GDEM have enabled testing a host of geoscience hypotheses. Availability of such data is now considered standard, and though resolved at 30-m to 90-m pixel size, they are today regarded as obsolete and inappropriate given the regularly updated sub-meter imagery coming through web services like Google Earth. Two features will thus help meet the current topographic data needs of the Geoscience communities: field-scale-compatible elevation datasets (i.e. meter-scale digital models and sub-meter elevation precision) and provision for regularly updated topography to tackle earth surface changes in 4D, while retaining the key for success: data availability at no charge. A new space borne instrumental concept called Z-Earth has undergone phase 0 study at CNES, the French space agency to fulfill these aims. The scientific communities backing this proposal are that of natural hazards, glaciology and biomass. The system under study combines a short-baseline native stereo imager and a lidar profiler. This combination provides spatially resolved elevation swaths together with absolute along-track elevation control point profiles. Acquisition is designed for revisit time better than a year. Intended products not only target single pass digital surface models, color orthoimages and small footprint full-wave-form lidar profiles to update existing topographic coverage, but also time series of them. 3D change detection targets centimetre-scale horizontal precision and metric vertical precision, in complement of -now traditional- spectral change detection. To assess the actual concept value, two real-size experiments were carried out. We used sub-meter-scale Pleiades panchromatic stereo-images to generate digital surface models and check them against dense airborne lidar coverages, one heliborne set purposely flown in Corsica (50-100pts/sq.m) and a second one retrieved from OpenTopography.org (~10pts/sq.m.). In Corsica, over a challenging 45-degree-grade tree-covered mountain side, the Pleiades 2-m-grid-posting digital surface model described the topography with a median error of -4.75m +/-2.59m (NMAD). A planimetric bias between both datasets was found to be about 7m to the South. This planimetric misregistration, though well within Pleiades specifications, partly explains the dramatic effect on elevation difference. In the Redmond area (eastern Oregon), a very gentle desert landscape, elevation differences also contained a vertical median bias of -4.02m+/-1.22m (NMAD). Though here, sub-pixel planimetric registration between stereo DSM and lidar coverage was enforced. This real-size experiment hints that sub-meter accuracy for 2-m-grid-posting DSM is an achievable goal when combining stereoimaging and lidar.

The Greenwich Photo-heliographic Results (1874 - 1976): Summary of the Observations, Applications, Datasets, Definitions and Errors

NASA Astrophysics Data System (ADS)

Willis, D. M.; Coffey, H. E.; Henwood, R.; Erwin, E. H.; Hoyt, D. V.; Wild, M. N.; Denig, W. F.

2013-11-01

The measurements of sunspot positions and areas that were published initially by the Royal Observatory, Greenwich, and subsequently by the Royal Greenwich Observatory (RGO), as the Greenwich Photo-heliographic Results ( GPR), 1874 - 1976, exist in both printed and digital forms. These printed and digital sunspot datasets have been archived in various libraries and data centres. Unfortunately, however, typographic, systematic and isolated errors can be found in the various datasets. The purpose of the present paper is to begin the task of identifying and correcting these errors. In particular, the intention is to provide in one foundational paper all the necessary background information on the original solar observations, their various applications in scientific research, the format of the different digital datasets, the necessary definitions of the quantities measured, and the initial identification of errors in both the printed publications and the digital datasets. Two companion papers address the question of specific identifiable errors; namely, typographic errors in the printed publications, and both isolated and systematic errors in the digital datasets. The existence of two independently prepared digital datasets, which both contain information on sunspot positions and areas, makes it possible to outline a preliminary strategy for the development of an even more accurate digital dataset. Further work is in progress to generate an extremely reliable sunspot digital dataset, based on the programme of solar observations supported for more than a century by the Royal Observatory, Greenwich, and the Royal Greenwich Observatory. This improved dataset should be of value in many future scientific investigations.

Object-oriented classification of drumlins from digital elevation models

NASA Astrophysics Data System (ADS)

Saha, Kakoli

Drumlins are common elements of glaciated landscapes which are easily identified by their distinct morphometric characteristics including shape, length/width ratio, elongation ratio, and uniform direction. To date, most researchers have mapped drumlins by tracing contours on maps, or through on-screen digitization directly on top of hillshaded digital elevation models (DEMs). This paper seeks to utilize the unique morphometric characteristics of drumlins and investigates automated extraction of the landforms as objects from DEMs by Definiens Developer software (V.7), using the 30 m United States Geological Survey National Elevation Dataset DEM as input. The Chautauqua drumlin field in Pennsylvania and upstate New York, USA was chosen as a study area. As the study area is huge (approximately covers 2500 sq.km. of area), small test areas were selected for initial testing of the method. Individual polygons representing the drumlins were extracted from the elevation data set by automated recognition, using Definiens' Multiresolution Segmentation tool, followed by rule-based classification. Subsequently parameters such as length, width and length-width ratio, perimeter and area were measured automatically. To test the accuracy of the method, a second base map was produced by manual on-screen digitization of drumlins from topographic maps and the same morphometric parameters were extracted from the mapped landforms using Definiens Developer. Statistical comparison showed a high agreement between the two methods confirming that object-oriented classification for extraction of drumlins can be used for mapping these landforms. The proposed method represents an attempt to solve the problem by providing a generalized rule-set for mass extraction of drumlins. To check that the automated extraction process was next applied to a larger area. Results showed that the proposed method is as successful for the bigger area as it was for the smaller test areas.

EAARL-B coastal topography: eastern New Jersey, Hurricane Sandy, 2012: first surface

USGS Publications Warehouse

Wright, C. Wayne; Fredericks, Xan; Troche, Rodolfo J.; Klipp, Emily S.; Kranenburg, Christine J.; Nagle, David B.

2014-01-01

These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography datasets were produced by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, Florida. This project provides highly detailed and accurate datasets for a portion of the New Jersey coastline beachface, acquired pre-Hurricane Sandy on October 26, and post-Hurricane Sandy on November 1 and November 5, 2012. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar system, known as the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), was used during data acquisition. The EAARL-B system is a raster-scanning, waveform-resolving, green-wavelength (532-nm) lidar designed to map nearshore bathymetry, topography, and vegetation structure simultaneously. The EAARL-B sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, down-looking red-green-blue (RGB) and infrared (IR) digital cameras, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL-B platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL-B system. The resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the "bare earth" under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Lidar for Science and Resource Management Web site.

EAARL Coastal Topography--Cape Canaveral, Florida, 2009: First Surface

USGS Publications Warehouse

Bonisteel-Cormier, J.M.; Nayegandhi, Amar; Plant, Nathaniel; Wright, C.W.; Nagle, D.B.; Serafin, K.S.; Klipp, E.S.

2011-01-01

These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Kennedy Space Center, FL. This project provides highly detailed and accurate datasets of a portion of the eastern Florida coastline beachface, acquired on May 28, 2009. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color-infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine aircraft, but the instrument was deployed on a Pilatus PC-6. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the "bare earth" under vegetation from a point cloud of last return elevations.

Evaluation of the differences between the SRTM and satellite radar altimetry height measurements and the approach taken for the ACE2 GDEM in areas of large disagreement.

PubMed

Smith, Richard Gavin; Berry, Philippa A M

2011-06-01

The new ACE2 (Altimeter Corrected Elevations 2) Global Digital Elevation Model (GDEM) which has recently been released aims to provide the most accurate GDEM to date. ACE2 was created by synergistically merging the SRTM and altimetry datasets. The comprehensive comparison carried out between the two datasets yielded a myriad of information, with the areas of disagreement providing as much valuable information as the areas of agreement. Analysis of the comparison dataset revealed that certain topographic features displayed consistent differences between the two datasets. The largest differences globally are present over the rainforests, particularly the two largest, around the Amazon and the Congo. The differences range between 10 m and 40 m; these differences can be attributed to the height of the rainforest canopy, as the SRTM returned height values from somewhere within the uppermost reaches of the vegetation whereas the altimeter was able to penetrate through and return true ground heights. The second major class of terrain feature to demonstrate coherent differences are desert regions; here, different deserts present different characteristics. The final area of interest is that of Wetlands; these are areas of special significance because even a slight misrepresentation of the heights can have wide ranging effects in modelling wetland areas. These examples illustrate the valuable additional information content gleaned from the synergistic global combination of the two datasets.

Digital surfaces and hydrogeologic data for the Floridan aquifer system in Florida and in parts of Georgia, Alabama, and South Carolina

USGS Publications Warehouse

Bellino, Jason C.

2011-01-01

A digital dataset for the Floridan aquifer system in Florida and in parts of Georgia, Alabama, and South Carolina was developed from selected reports published as part of the Regional Aquifer-System Analysis (RASA) Program of the U.S. Geological Survey (USGS) in the 1980s. These reports contain maps and data depicting the extent and elevation of both time-stratigraphic and hydrogeologic units of which the aquifer system is composed, as well as data on hydrology, meteorology, and aquifer properties. The three primary reports used for this dataset compilation were USGS Professional Paper 1403-B (Miller, 1986), Professional Paper 1403-C (Bush and Johnston, 1988), and USGS Open-File Report 88-86 (Miller, 1988). Paper maps from Professional Papers 1403-B and 1403-C were scanned and georeferenced to the North American Datum of 1927 (NAD27) using the Lambert Conformal Conic projection (standard parallels 33 and 45 degrees, central longitude -96 degrees, central latitude 39 degrees). Once georeferenced, tracing of pertinent line features contained in each image (for example, contours and faults) was facilitated by specialized software using algorithms that automated much of the process. Resulting digital line features were then processed using standard geographic information system (GIS) software to remove artifacts from the digitization process and to verify and update attribute tables. The digitization process for polygonal features (for example, outcrop areas and unit extents) was completed by hand using GIS software.

Do pre-trained deep learning models improve computer-aided classification of digital mammograms?

NASA Astrophysics Data System (ADS)

Aboutalib, Sarah S.; Mohamed, Aly A.; Zuley, Margarita L.; Berg, Wendie A.; Luo, Yahong; Wu, Shandong

2018-02-01

Digital mammography screening is an important exam for the early detection of breast cancer and reduction in mortality. False positives leading to high recall rates, however, results in unnecessary negative consequences to patients and health care systems. In order to better aid radiologists, computer-aided tools can be utilized to improve distinction between image classifications and thus potentially reduce false recalls. The emergence of deep learning has shown promising results in the area of biomedical imaging data analysis. This study aimed to investigate deep learning and transfer learning methods that can improve digital mammography classification performance. In particular, we evaluated the effect of pre-training deep learning models with other imaging datasets in order to boost classification performance on a digital mammography dataset. Two types of datasets were used for pre-training: (1) a digitized film mammography dataset, and (2) a very large non-medical imaging dataset. By using either of these datasets to pre-train the network initially, and then fine-tuning with the digital mammography dataset, we found an increase in overall classification performance in comparison to a model without pre-training, with the very large non-medical dataset performing the best in improving the classification accuracy.

Development and application of GIS-based PRISM integration through a plugin approach

NASA Astrophysics Data System (ADS)

Lee, Woo-Seop; Chun, Jong Ahn; Kang, Kwangmin

2014-05-01

A PRISM (Parameter-elevation Regressions on Independent Slopes Model) QGIS-plugin was developed on Quantum GIS platform in this study. This Quantum GIS plugin system provides user-friendly graphic user interfaces (GUIs) so that users can obtain gridded meteorological data of high resolutions (1 km × 1 km). Also, this software is designed to run on a personal computer so that it does not require an internet access or a sophisticated computer system. This module is a user-friendly system that a user can generate PRISM data with ease. The proposed PRISM QGIS-plugin is a hybrid statistical-geographic model system that uses coarse resolution datasets (APHRODITE datasets in this study) with digital elevation data to generate the fine-resolution gridded precipitation. To validate the performance of the software, Prek Thnot River Basin in Kandal, Cambodia is selected for application. Overall statistical analysis shows promising outputs generated by the proposed plugin. Error measures such as RMSE (Root Mean Square Error) and MAPE (Mean Absolute Percentage Error) were used to evaluate the performance of the developed PRISM QGIS-plugin. Evaluation results using RMSE and MAPE were 2.76 mm and 4.2%, respectively. This study suggested that the plugin can be used to generate high resolution precipitation datasets for hydrological and climatological studies at a watershed where observed weather datasets are limited.

Evaluation of different digital elevation models for analyzing drainage morphometric parameters in a mountainous terrain: a case study of the Supin-Upper Tons Basin, Indian Himalayas.

PubMed

Das, Sayantan; Patel, Priyank Pravin; Sengupta, Somasis

2016-01-01

With myriad geospatial datasets now available for terrain information extraction and particularly streamline demarcation, there arises questions regarding the scale, accuracy and sensitivity of the initial dataset from which these aspects are derived, as they influence all other parameters computed subsequently. In this study, digital elevation models (DEM) derived from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER V2), Shuttle Radar Topography Mission (SRTM V4, C-Band, 3 arc-second), Cartosat -1 (CartoDEM 1.0) and topographical maps (R.F. 1:250,000 and 1:50,000), have been used to individually extract and analyze the relief, surface, size, shape and texture properties of a mountainous drainage basin. Nestled inside a mountainous setting, the basin is a semi-elongated one with high relief ratio (>90), steep slopes (25°-30°) and high drainage density (>3.5 km/sq km), as computed from the different DEMs. The basin terrain and stream network is extracted from each DEM, whose morphometric attributes are compared with the surveyed stream networks present in the topographical maps, with resampling of finer DEM datasets to coarser resolutions, to reduce scale-implications during the delineation process. Ground truth verifications for altitudinal accuracy have also been done by a GPS survey. DEMs derived from the 1:50,000 topographical map and ASTER GDEM V2 data are found to be more accurate and consistent in terms of absolute accuracy, than the other generated or available DEM data products, on basis of the morphometric parameters extracted from each. They also exhibit a certain degree of proximity to the surveyed topographical map.

Comparing the Performance of Commonly Available Digital Elevation Models in GIS-based Flood Simulation

NASA Astrophysics Data System (ADS)

Ybanez, R. L.; Lagmay, A. M. A.; David, C. P.

2016-12-01

With climatological hazards increasing globally, the Philippines is listed as one of the most vulnerable countries in the world due to its location in the Western Pacific. Flood hazards mapping and modelling is one of the responses by local government and research institutions to help prepare for and mitigate the effects of flood hazards that constantly threaten towns and cities in floodplains during the 6-month rainy season. Available digital elevation maps, which serve as the most important dataset used in 2D flood modelling, are limited in the Philippines and testing is needed to determine which of the few would work best for flood hazards mapping and modelling. Two-dimensional GIS-based flood modelling with the flood-routing software FLO-2D was conducted using three different available DEMs from the ASTER GDEM, the SRTM GDEM, and the locally available IfSAR DTM. All other parameters kept uniform, such as resolution, soil parameters, rainfall amount, and surface roughness, the three models were run over a 129-sq. kilometer watershed with only the basemap varying. The output flood hazard maps were compared on the basis of their flood distribution, extent, and depth. The ASTER and SRTM GDEMs contained too much error and noise which manifested as dissipated and dissolved hazard areas in the lower watershed where clearly delineated flood hazards should be present. Noise on the two datasets are clearly visible as erratic mounds in the floodplain. The dataset which produced the only feasible flood hazard map is the IfSAR DTM which delineates flood hazard areas clearly and properly. Despite the use of ASTER and SRTM with their published resolution and accuracy, their use in GIS-based flood modelling would be unreliable. Although not as accessible, only IfSAR or better datasets should be used for creating secondary products from these base DEM datasets. For developing countries which are most prone to hazards, but with limited choices for basemaps used in hazards studies, the caution must be taken in the use of globally available GDEMs and higher-resolution DEMs must always be sought.

Combined High-Resolution LIDAR Topography and Multibeam Bathymetry for Northern Resurrection Bay, Seward, Alaska

USGS Publications Warehouse

Labay, Keith A.; Haeussler, Peter J.

2008-01-01

A new Digital Elevation Model was created using the best available high-resolution topography and multibeam bathymetry surrounding the area of Seward, Alaska. Datasets of (1) LIDAR topography collected for the Kenai Watershed Forum, (2) Seward harbor soundings from the U.S. Army Corp of Engineers, and (3) multibeam bathymetry from the National Oceanic and Atmospheric Administration contributed to the final combined product. These datasets were placed into a common coordinate system, horizontal datum, vertical datum, and data format prior to being combined. The projected coordinate system of Universal Transverse Mercator Zone 6 North American Datum of 1927 was used for the horizontal coordinates. Z-values in meters were referenced to the tidal datum of Mean High Water. Gaps between the datasets were interpolated to create the final seamless 5-meter grid covering the area of interest around Seward, Alaska.

Analysis of ArcticDEM orthorectification for polar navigational traverses

NASA Astrophysics Data System (ADS)

Menio, E. C.; Deeb, E. J.; Weale, J.; Courville, Z.; Tracy, B.; Cloutier, M. D.; Cothren, J. D.; Liu, J.

2017-12-01

The availability and accessibility of high-resolution satellite imagery allows operational support teams to visually assess physical risks along traverse routes before and during the field season. In support of operations along the Greenland Inland Traverse (GrIT), DigitalGlobe's WorldView 0.5m resolution panchromatic imagery is analyzed to identify and digitize crevasse features along the route from Thule Air Force Base to Summit Station, Greenland. In the spring of 2016, field teams reported up to 150 meters of offset between the location of crevasse features on the ground and the location of the same feature on the imagery provided. Investigation into this issue identified the need to orthorectify imagery—use digital elevation models (DEMs) to correct viewing geometry distortions—to improve navigational accuracy in the field. It was previously thought that orthorectification was not necessary for applications in relatively flat terrain such as ice sheets. However, the surface elevations on the margins of the Greenland Ice Sheet vary enough to cause distortions in imagery, if taken obliquely. As is standard for requests, the Polar Geospatial Center (PGC) provides orthorectified imagery using the MEaSUREs Greenland Ice Mapping Project (GIMP) 30m digital elevation model. Current, higher-resolution elevation datasets, such as the ArcticDEM (2-5m resolution) and WorldView stereopair DEMs (2-3m resolution), are available for use in orthorectification. This study examines three heavily crevassed areas along the GrIT traverse, as identified in 2015 and 2016 imagery. We extracted elevation profiles along the GrIT route from each of the three DEMs: GIMP, ArcticDEM, and WorldView stereopair mosaic. Results show the courser GIMP data deviating significantly from the ArcticDEM and WorldView data, at points by up to 80m, which is seen as offset of features in plan view. In-situ Ground Penetrating Radar (GPR) surveys of crevasse crossings allow for evaluation of geopositional accuracy of each resulting orthorectified photo and a quantitative analysis of plan view offset.

State of Texas - Highlighting low-lying areas derived from USGS Digital Elevation Data

USGS Publications Warehouse

Kosovich, John J.

2008-01-01

In support of U.S. Geological Survey (USGS) disaster preparedness efforts, this map depicts a color shaded relief representation of Texas and a grayscale relief of the surrounding areas. The first 30 feet of relief above mean sea level are displayed as brightly colored 5-foot elevation bands, which highlight low-elevation areas at a coarse spatial resolution. Standard USGS National Elevation Dataset (NED) 1 arc-second (nominally 30-meter) digital elevation model (DEM) data are the basis for the map, which is designed to be used at a broad scale and for informational purposes only. The NED data were derived from the original 1:24,000-scale USGS topographic map bare-earth contours, which were converted into gridded quadrangle-based DEM tiles at a constant post spacing (grid cell size) of either 30 meters (data before the mid-1990s) or 10 meters (mid-1990s and later data). These individual-quadrangle DEMs were then converted to spherical coordinates (latitude/longitude decimal degrees) and edge-matched to ensure seamlessness. The NED source data for this map consists of a mixture of 30-meter- and 10-meter-resolution DEMs. State and county boundary, hydrography, city, and road layers were modified from USGS National Atlas data downloaded in 2003. The NED data were downloaded in 2002. Shaded relief over Mexico was obtained from the USGS National Atlas.

Landscape unit based digital elevation model development for the freshwater wetlands within the Arthur C. Marshall Loxahatchee National Wildlife Refuge, Southeastern Florida

USGS Publications Warehouse

Xie, Zhixiao; Liu, Zhongwei; Jones, John W.; Higer, Aaron L.; Telis, Pamela A.

2011-01-01

The hydrologic regime is a critical limiting factor in the delicate ecosystem of the greater Everglades freshwater wetlands in south Florida that has been severely altered by management activities in the past several decades. "Getting the water right" is regarded as the key to successful restoration of this unique wetland ecosystem. An essential component to represent and model its hydrologic regime, specifically water depth, is an accurate ground Digital Elevation Model (DEM). The Everglades Depth Estimation Network (EDEN) supplies important hydrologic data, and its products (including a ground DEM) have been well received by scientists and resource managers involved in Everglades restoration. This study improves the EDEN DEMs of the Loxahatchee National Wildlife Refuge, also known as Water Conservation Area 1 (WCA1), by adopting a landscape unit (LU) based interpolation approach. The study first filtered the input elevation data based on newly available vegetation data, and then created a separate geostatistical model (universal kriging) for each LU. The resultant DEMs have encouraging cross-validation and validation results, especially since the validation is based on an independent elevation dataset (derived by subtracting water depth measurements from EDEN water surface elevations). The DEM product of this study will directly benefit hydrologic and ecological studies as well as restoration efforts. The study will also be valuable for a broad range of wetland studies.

Investigation of potential sea level rise impact on the Nile Delta, Egypt using digital elevation models.

PubMed

Hasan, Emad; Khan, Sadiq Ibrahim; Hong, Yang

2015-10-01

In this study, the future impact of Sea Level Rise (SLR) on the Nile Delta region in Egypt is assessed by evaluating the elevations of two freely available Digital Elevation Models (DEMs): the SRTM and the ASTER-GDEM-V2. The SLR is a significant worldwide dilemma that has been triggered by recent climatic changes. In Egypt, the Nile Delta is projected to face SLR of 1 m by the end of the 21th century. In order to provide a more accurate assessment of the future SLR impact on Nile Delta's land and population, this study corrected the DEM's elevations by using linear regression model with ground elevations from GPS survey. The information for the land cover types and future population numbers were derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) land cover and the Gridded Population of the Worlds (GPWv3) datasets respectively. The DEM's vertical accuracies were assessed using GPS measurements and the uncertainty analysis revealed that the SRTM-DEM has positive bias of 2.5 m, while the ASTER-GDEM-V2 showed a positive bias of 0.8 m. The future inundated land cover areas and the affected population were illustrated based on two SLR scenarios of 0.5 m and 1 m. The SRTM DEM data indicated that 1 m SLR will affect about 3900 km(2) of cropland, 1280 km(2) of vegetation, 205 km(2) of wetland, 146 km(2) of urban areas and cause more than 6 million people to lose their houses. The overall vulnerability assessment using ASTER-GDEM-V2 indicated that the influence of SLR will be intense and confined along the coastal areas. For instance, the data indicated that 1 m SLR will inundate about 580 Km(2) (6%) of the total land cover areas and approximately 887 thousand people will be relocated. Accordingly, the uncertainty analysis of the DEM's elevations revealed that the ASTER-GDEM-V2 dataset product was considered the best to determine the future impact of SLR on the Nile Delta region.

Combining structure-from-motion derived point clouds from satellites and unmanned aircraft systems images with ground-truth data to create high-resolution digital elevation models

NASA Astrophysics Data System (ADS)

Palaseanu, M.; Thatcher, C.; Danielson, J.; Gesch, D. B.; Poppenga, S.; Kottermair, M.; Jalandoni, A.; Carlson, E.

2016-12-01

Coastal topographic and bathymetric (topobathymetric) data with high spatial resolution (1-meter or better) and high vertical accuracy are needed to assess the vulnerability of Pacific Islands to climate change impacts, including sea level rise. According to the Intergovernmental Panel on Climate Change reports, low-lying atolls in the Pacific Ocean are extremely vulnerable to king tide events, storm surge, tsunamis, and sea-level rise. The lack of coastal topobathymetric data has been identified as a critical data gap for climate vulnerability and adaptation efforts in the Republic of the Marshall Islands (RMI). For Majuro Atoll, home to the largest city of RMI, the only elevation dataset currently available is the Shuttle Radar Topography Mission data which has a 30-meter spatial resolution and 16-meter vertical accuracy (expressed as linear error at 90%). To generate high-resolution digital elevation models (DEMs) in the RMI, elevation information and photographic imagery have been collected from field surveys using GNSS/total station and unmanned aerial vehicles for Structure-from-Motion (SfM) point cloud generation. Digital Globe WorldView II imagery was processed to create SfM point clouds to fill in gaps in the point cloud derived from the higher resolution UAS photos. The combined point cloud data is filtered and classified to bare-earth and georeferenced using the GNSS data acquired on roads and along survey transects perpendicular to the coast. A total station was used to collect elevation data under tree canopies where heavy vegetation cover blocked the view of GNSS satellites. A subset of the GPS / total station data was set aside for error assessment of the resulting DEM.

Attributes for NHDPlus Catchments (Version 1.1) in the Conterminous United States: Bedrock Geology

USGS Publications Warehouse

Wieczorek, Michael; LaMotte, Andrew E.

2010-01-01

This data set represents the area of bedrock geology types in square meters compiled for every catchment of NHDPlus for the conterminous United States. The source data set is the "Geology of the Conterminous United States at 1:2,500,000 Scale--A Digital Representation of the 1974 P.B. King and H.M. Beikman Map" (Schuben and others, 1994). The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18

A hierarchical network-based algorithm for multi-scale watershed delineation

NASA Astrophysics Data System (ADS)

Castronova, Anthony M.; Goodall, Jonathan L.

2014-11-01

Watershed delineation is a process for defining a land area that contributes surface water flow to a single outlet point. It is a commonly used in water resources analysis to define the domain in which hydrologic process calculations are applied. There has been a growing effort over the past decade to improve surface elevation measurements in the U.S., which has had a significant impact on the accuracy of hydrologic calculations. Traditional watershed processing on these elevation rasters, however, becomes more burdensome as data resolution increases. As a result, processing of these datasets can be troublesome on standard desktop computers. This challenge has resulted in numerous works that aim to provide high performance computing solutions to large data, high resolution data, or both. This work proposes an efficient watershed delineation algorithm for use in desktop computing environments that leverages existing data, U.S. Geological Survey (USGS) National Hydrography Dataset Plus (NHD+), and open source software tools to construct watershed boundaries. This approach makes use of U.S. national-level hydrography data that has been precomputed using raster processing algorithms coupled with quality control routines. Our approach uses carefully arranged data and mathematical graph theory to traverse river networks and identify catchment boundaries. We demonstrate this new watershed delineation technique, compare its accuracy with traditional algorithms that derive watershed solely from digital elevation models, and then extend our approach to address subwatershed delineation. Our findings suggest that the open-source hierarchical network-based delineation procedure presented in the work is a promising approach to watershed delineation that can be used summarize publicly available datasets for hydrologic model input pre-processing. Through our analysis, we explore the benefits of reusing the NHD+ datasets for watershed delineation, and find that the our technique offers greater flexibility and extendability than traditional raster algorithms.

Development of Land Segmentation, Stream-Reach Network, and Watersheds in Support of Hydrological Simulation Program-Fortran (HSPF) Modeling, Chesapeake Bay Watershed, and Adjacent Parts of Maryland, Delaware, and Virginia

USGS Publications Warehouse

Martucci, Sarah K.; Krstolic, Jennifer L.; Raffensperger, Jeff P.; Hopkins, Katherine J.

2006-01-01

The U.S. Geological Survey, U.S. Environmental Protection Agency Chesapeake Bay Program Office, Interstate Commission on the Potomac River Basin, Maryland Department of the Environment, Virginia Department of Conservation and Recreation, Virginia Department of Environmental Quality, and the University of Maryland Center for Environmental Science are collaborating on the Chesapeake Bay Regional Watershed Model, using Hydrological Simulation Program - FORTRAN to simulate streamflow and concentrations and loads of nutrients and sediment to Chesapeake Bay. The model will be used to provide information for resource managers. In order to establish a framework for model simulation, digital spatial datasets were created defining the discretization of the model region (including the Chesapeake Bay watershed, as well as the adjacent parts of Maryland, Delaware, and Virginia outside the watershed) into land segments, a stream-reach network, and associated watersheds. Land segmentation was based on county boundaries represented by a 1:100,000-scale digital dataset. Fifty of the 254 counties and incorporated cities in the model region were divided on the basis of physiography and topography, producing a total of 309 land segments. The stream-reach network for the Chesapeake Bay watershed part of the model region was based on the U.S. Geological Survey Chesapeake Bay SPARROW (SPAtially Referenced Regressions On Watershed attributes) model stream-reach network. Because that network was created only for the Chesapeake Bay watershed, the rest of the model region uses a 1:500,000-scale stream-reach network. Streams with mean annual streamflow of less than 100 cubic feet per second were excluded based on attributes from the dataset. Additional changes were made to enhance the data and to allow for inclusion of stream reaches with monitoring data that were not part of the original network. Thirty-meter-resolution Digital Elevation Model data were used to delineate watersheds for each stream reach. State watershed boundaries replaced the Digital Elevation Model-derived watersheds where coincident. After a number of corrections, the watersheds were coded to indicate major and minor basin, mean annual streamflow, and each watershed's unique identifier as well as that of the downstream watershed. Land segments and watersheds were intersected to create land-watershed segments for the model.

U.S. Geological Survey spatial data access

USGS Publications Warehouse

Faundeen, John L.; Kanengieter, Ronald L.; Buswell, Michael D.

2002-01-01

The U.S. Geological Survey (USGS) has done a progress review on improving access to its spatial data holdings over the Web. The USGS EROS Data Center has created three major Web-based interfaces to deliver spatial data to the general public; they are Earth Explorer, the Seamless Data Distribution System (SDDS), and the USGS Web Mapping Portal. Lessons were learned in developing these systems, and various resources were needed for their implementation. The USGS serves as a fact-finding agency in the U.S. Government that collects, monitors, analyzes, and provides scientific information about natural resource conditions and issues. To carry out its mission, the USGS has created and managed spatial data since its inception. Originally relying on paper maps, the USGS now uses advanced technology to produce digital representations of the Earth’s features. The spatial products of the USGS include both source and derivative data. Derivative datasets include Digital Orthophoto Quadrangles (DOQ), Digital Elevation Models, Digital Line Graphs, land-cover Digital Raster Graphics, and the seamless National Elevation Dataset. These products, created with automated processes, use aerial photographs, satellite images, or other cartographic information such as scanned paper maps as source data. With Earth Explorer, users can search multiple inventories through metadata queries and can browse satellite and DOQ imagery. They can place orders and make payment through secure credit card transactions. Some USGS spatial data can be accessed with SDDS. The SDDS uses an ArcIMS map service interface to identify the user’s areas of interest and determine the output format; it allows the user to either download the actual spatial data directly for small areas or place orders for larger areas to be delivered on media. The USGS Web Mapping Portal provides views of national and international datasets through an ArcIMS map service interface. In addition, the map portal posts news about new map services available from the USGS, many simultaneously published on the Environmental Systems Research Institute Geography Network. These three information systems use new software tools and expanded hardware to meet the requirements of the users. The systems are designed to handle the required workload and are relatively easy to enhance and maintain. The software tools give users a high level of functionality and help the system conform to industry standards. The hardware and software architecture is designed to handle the large amounts of spatial data and Internet traffic required by the information systems. Last, customer support was needed to answer questions, monitor e-mail, and report customer problems.

Applying modern measurements of Pleistocene loads to model lithospheric rheology

NASA Astrophysics Data System (ADS)

Beard, E. P.; Hoggan, J. R.; Lowry, A. R.

2011-12-01

The remnant shorelines of Pleistocene Lake Bonneville provide a unique opportunity for building a dataset from which to infer rheological properties of the lower crust and upper mantle. Multiple lakeshores developed over a period of around 30 kyr which record the lithosphere's isostatic response to a well-constrained load history. Bills et al. (1994) utilized a shoreline elevation dataset compiled by Currey (1982) in an attempt to model linear (Maxwell) viscosity as a function of depth beneath the basin. They estimated an effective elastic thickness (Te) for the basin of 20-25 km which differs significantly from the 5-15 km estimates derived from models of loading on geologic timescales (e.g., Lowry and Pérez-Gussinyé, 2011). We propose that the discrepancy in Te modeled by these two approaches may be resolved with dynamical modeling of a common rheology, using a more complete shoreline elevation dataset applied to a spherical Earth model. Where Currey's (1982) dataset was compiled largely from observations of depositional shoreline features, we are developing an algorithm for estimating elevation variations in erosional shorelines based on cross-correlation and stacking techniques similar to those used to automate picking of seismic phase arrival times. Application of this method to digital elevation models (DEMs) will increase the size and accuracy of the shoreline elevation dataset, enabling more robust modeling of the rheological properties driving isostatic response to unloading of Lake Bonneville. Our plan is to model these data and invert for a relatively small number of parameters describing depth- and temperature-dependent power-law rheology of the lower crust and upper mantle. These same parameters also will be used to model topographic and Moho response to estimates of regional mass variation on the longer loading timescales to test for inconsistencies. Bills, B.G., D.R. Currey, and G.A. Marshall, 1994, Viscosity estimates for the crust and upper mantle from patterns of lacustrine shoreline deformation in the Eastern Great Basin, Journal of Geophysical Research, 99, B11, 22,059-22,086. Currey, D.R., 1982, Lake Bonneville: Selected features of relevance to neotectonic analysis, U.S. Geological Survey Open File Report, 82-1070, 31pp. Lowry, A.R., and M. Pérez-Gussinyé, 2011, The role of crustal quartz in controlling Cordilleran deformation, Nature, 471, pp. 353-357.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fielding, E.J.; Barazangi, M.; Isacks, B.L.

Topography and heterogeneous crustal structure have major effects on the propagation of regional seismic phases. We are collecting topographical, geological, and geophysical datasets for Eurasia into an information system that can be accessed via Internet connections. Now available are digital topography, satellite imagery, and data on sedimentary basins and crustal structure thicknesses. New datasets for Eurasia include maps of depth to Moho beneath Europe and Scandinavia. We have created regularly spaced grids of the crustal thickness values from these maps that can be used to create profiles of crustal structure. These profiles can be compared by an analyst or anmore » automatic program with the crustal seismic phases received along the propagation path to better understand and predict the path effects on phase amplitudes, a key to estimating magnitudes and yields, and for understanding variations in travel-time delays for phases such as Pn, important for improving regional event locations. The gridded data could also be used to model propagation of crustal phases in three dimensions. Digital elevation models, Satellite imagery, Geographic information systems, Lg Propagation, Moho, Geology, Crustal structure, Topographic relief.« less

Global GIS database; digital atlas of Central and South America

USGS Publications Warehouse

Hearn,, Paul P.; Hare, T.; Schruben, P.; Sherrill, D.; LaMar, C.; Tsushima, P.

2000-01-01

This CD-ROM contains a digital atlas of the countries of Central and South America. This atlas is part of a global database compiled from USGS and other data sources at the nominal scale of 1:1 million and is intended to be used as a regional-scale reference and analytical tool by government officials, researchers, the private sector, and the general public. The atlas includes free GIS software or may also be used with ESRI's ArcView software. Customized ArcView tools, specifically designed to make the atlas easier to use, are also included. The atlas contains the following datasets: country political boundaries, digital shaded relief map, elevation, slope, hydrology, locations of cities and towns, airfields, roads, railroads, utility lines, population density, geology, ecological regions, historical seismicity, volcanoes, ore deposits, oil and gas fields, climate data, landcover, vegetation index, and lights at night.

Geospatial datasets for watershed delineation and characterization used in the Hawaii StreamStats web application

USGS Publications Warehouse

Rea, Alan; Skinner, Kenneth D.

2012-01-01

The U.S. Geological Survey Hawaii StreamStats application uses an integrated suite of raster and vector geospatial datasets to delineate and characterize watersheds. The geospatial datasets used to delineate and characterize watersheds on the StreamStats website, and the methods used to develop the datasets are described in this report. The datasets for Hawaii were derived primarily from 10 meter resolution National Elevation Dataset (NED) elevation models, and the National Hydrography Dataset (NHD), using a set of procedures designed to enforce the drainage pattern from the NHD into the NED, resulting in an integrated suite of elevation-derived datasets. Additional sources of data used for computing basin characteristics include precipitation, land cover, soil permeability, and elevation-derivative datasets. The report also includes links for metadata and downloads of the geospatial datasets.

Optimization of the resolution of remotely sensed digital elevation model to facilitate the simulation and spatial propagation of flood events in flat areas

NASA Astrophysics Data System (ADS)

Karapetsas, Nikolaos; Skoulikaris, Charalampos; Katsogiannos, Fotis; Zalidis, George; Alexandridis, Thomas

2013-04-01

The use of satellite remote sensing products, such as Digital Elevation Models (DEMs), under specific computational interfaces of Geographic Information Systems (GIS) has fostered and facilitated the acquisition of data on specific hydrologic features, such as slope, flow direction and flow accumulation, which are crucial inputs to hydrology or hydraulic models at the river basin scale. However, even though DEMs of different resolution varying from a few km up to 20m are freely available for the European continent, these remotely sensed elevation data are rather coarse in cases where large flat areas are dominant inside a watershed, resulting in an unsatisfactory representation of the terrain characteristics. This scientific work aims at implementing a combing interpolation technique for the amelioration of the analysis of a DEM in order to be used as the input ground model to a hydraulic model for the assessment of potential flood events propagation in plains. More specifically, the second version of the ASTER Global Digital Elevation Model (GDEM2), which has an overall accuracy of around 20 meters, was interpolated with a vast number of aerial control points available from the Hellenic Mapping and Cadastral Organization (HMCO). The uncertainty that was inherent in both the available datasets (ASTER & HMCO) and the appearance of uncorrelated errors and artifacts was minimized by incorporating geostatistical filtering. The resolution of the produced DEM was approximately 10 meters and its validation was conducted with the use of an external dataset of 220 geodetic survey points. The derived DEM was then used as an input to the hydraulic model InfoWorks RS, whose operation is based on the relief characteristics contained in the ground model, for defining, in an automated way, the cross section parameters and simulating the flood spatial distribution. The plain of Serres, which is located in the downstream part of the Struma/Strymon transboundary river basin shared by Bulgaria and Greece, was selected as the case study area, because of its importance to the regional and national economy of Greece and because of the numerous flood events recorded in the past. The results of the simulation processing demonstrated the importance of high resolution relief models for estimating the potential flood hazard zones in order to mitigate the catastrophe caused, both in economic and environmental terms, by this type of extreme event.

Accuracy assessment of the U.S. Geological Survey National Elevation Dataset, and comparison with other large-area elevation datasets: SRTM and ASTER

USGS Publications Warehouse

Gesch, Dean B.; Oimoen, Michael J.; Evans, Gayla A.

2014-01-01

The National Elevation Dataset (NED) is the primary elevation data product produced and distributed by the U.S. Geological Survey. The NED provides seamless raster elevation data of the conterminous United States, Alaska, Hawaii, U.S. island territories, Mexico, and Canada. The NED is derived from diverse source datasets that are processed to a specification with consistent resolutions, coordinate system, elevation units, and horizontal and vertical datums. The NED serves as the elevation layer of The National Map, and it provides basic elevation information for earth science studies and mapping applications in the United States and most of North America. An important part of supporting scientific and operational use of the NED is provision of thorough dataset documentation including data quality and accuracy metrics. The focus of this report is on the vertical accuracy of the NED and on comparison of the NED with other similar large-area elevation datasets, namely data from the Shuttle Radar Topography Mission (SRTM) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER).

EAARL-B submerged topography: Barnegat Bay, New Jersey, post-Hurricane Sandy, 2012-2013

USGS Publications Warehouse

Wright, C. Wayne; Troche, Rodolfo J.; Kranenburg, Christine J.; Klipp, Emily S.; Fredericks, Xan; Nagle, David B.

2014-01-01

These remotely sensed, geographically referenced elevation measurements of lidar-derived submerged topography datasets were produced by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, Florida. This project provides highly detailed and accurate datasets for part of Barnegat Bay, New Jersey, acquired post-Hurricane Sandy on November 1, 5, 16, 20, and 30, 2012; December 5, 6, and 21, 2012; and January 10, 2013. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar system, known as the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), was used during data acquisition. The EAARL-B system is a raster-scanning, waveform-resolving, green-wavelength (532-nm) lidar designed to map nearshore bathymetry, topography, and vegetation structure simultaneously. The EAARL-B sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, down-looking red-green-blue (RGB) and infrared (IR) digital cameras, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL-B platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL-B system. The resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed originally in a NASA-USGS collaboration. The exploration and processing of lidar data in an interactive or batch mode is supported using ALPS. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. The Airborne Lidar Processing System (ALPS) is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the "bare earth" under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Lidar for Science and Resource Management Web site.

EAARL Coastal Topography-Cape Hatteras National Seashore, North Carolina, Post-Nor'Ida, 2009: Bare Earth

USGS Publications Warehouse

Bonisteel-Cormier, J.M.; Nayegandhi, Amar; Fredericks, Xan; Brock, J.C.; Wright, C.W.; Nagle, D.B.; Stevens, Sara

2011-01-01

These remotely sensed, geographically referenced elevation measurements of lidar-derived bare-earth (BE) topography datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL, and the National Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI. This project provides highly detailed and accurate datasets of a portion of the National Park Service Southeast Coast Network's Cape Hatteras National Seashore in North Carolina, acquired post-Nor'Ida (November 2009 nor'easter) on November 27 and 29 and December 1, 2009. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color-infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine aircraft, but the instrument was deployed on a Pilatus PC-6. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.

EAARL coastal topography and imagery–Western Louisiana, post-Hurricane Rita, 2005: First surface

USGS Publications Warehouse

Bonisteel-Cormier, Jamie M.; Wright, Wayne C.; Fredericks, Alexandra M.; Klipp, Emily S.; Nagle, Doug B.; Sallenger, Asbury H.; Brock, John C.

2013-01-01

These remotely sensed, geographically referenced color-infrared (CIR) imagery and elevation measurements of lidar-derived first-surface (FS) topography datasets were produced by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, Florida, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, Virginia. This project provides highly detailed and accurate datasets of a portion of the Louisiana coastline beachface, acquired post-Hurricane Rita on September 27-28 and October 2, 2005. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the National Aeronautics and Space Administration (NASA) Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color-infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the "bare earth" under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Lidar for Science and Resource Management Website.

EAARL Coastal Topography-Maryland and Delaware, Post-Nor'Ida, 2009

USGS Publications Warehouse

Bonisteel-Cormier, J.M.; Vivekanandan, Saisudha; Nayegandhi, Amar; Sallenger, A.H.; Wright, C.W.; Brock, J.C.; Nagle, D.B.; Klipp, E.S.

2010-01-01

These remotely sensed, geographically referenced elevation measurements of lidar-derived bare-earth (BE) and first-surface (FS) topography datasets were produced by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL. This project provides highly detailed and accurate datasets of a portion of the eastern Maryland and Delaware coastline beachface, acquired post-Nor'Ida (November 2009 nor'easter) on November 28 and 30, 2009. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color-infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine aircraft, but the instrument was deployed on a Pilatus PC-6. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website.

EAARL Coastal Topography-Eastern Louisiana Barrier Islands, Post-Hurricane Gustav, 2008: First Surface

USGS Publications Warehouse

Bonisteel-Cormier, J.M.; Nayegandhi, Amar; Wright, C.W.; Sallenger, A.H.; Brock, J.C.; Nagle, D.B.; Vivekanandan, Saisudha; Fredericks, Xan

2010-01-01

These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the eastern Louisiana barrier islands, acquired post-Hurricane Gustav (September 2008 hurricane) on September 6 and 7, 2008. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website.

EAARL coastal topography-Cape Hatteras National Seashore, North Carolina, post-Nor'Ida, 2009: first surface

USGS Publications Warehouse

Bonisteel-Cormier, J.M.; Nayegandhi, Amar; Brock, J.C.; Wright, C.W.; Nagle, D.B.; Fredericks, Xan; Stevens, Sara

2010-01-01

These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL, and the National Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI. This project provides highly detailed and accurate datasets of a portion of the National Park Service Southeast Coast Network's Cape Hatteras National Seashore in North Carolina, acquired post-Nor'Ida (November 2009 nor'easter) on November 27 and 29 and December 1, 2009. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color-infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine aircraft, but the instrument was deployed on a Pilatus PC-6. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website.

EAARL Coastal Topography-Mississippi and Alabama Barrier Islands, Post-Hurricane Gustav, 2008

USGS Publications Warehouse

Bonisteel-Cormier, J.M.; Nayegandhi, Amar; Wright, C.W.; Sallenger, A.H.; Brock, J.C.; Nagle, D.B.; Klipp, E.S.; Vivekanandan, Saisudha; Fredericks, Xan; Segura, Martha

2010-01-01

These remotely sensed, geographically referenced elevation measurements of lidar-derived bare-earth (BE) and first-surface (FS) topography datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL; the National Park Service (NPS), Gulf Coast Network, Lafayette, LA; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the Mississippi and Alabama barrier islands, acquired post-Hurricane Gustav (September 2008 hurricane) on September 8, 2008. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website.

EAARL Coastal Topography and Imagery-Assateague Island National Seashore, Maryland and Virginia, Post-Nor'Ida, 2009

USGS Publications Warehouse

Bonisteel-Cormier, J.M.; Nayegandhi, Amar; Brock, J.C.; Wright, C.W.; Nagle, D.B.; Klipp, E.S.; Vivekanandan, Saisudha; Fredericks, Xan; Stevens, Sara

2010-01-01

These remotely sensed, geographically referenced color-infrared (CIR) imagery and elevation measurements of lidar-derived bare-earth (BE) and first-surface (FS) topography datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL, and the National Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI. This project provides highly detailed and accurate datasets of a portion of the Assateague Island National Seashore in Maryland and Virginia, acquired post-Nor'Ida (November 2009 nor'easter) on November 28 and 30, 2009. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar(EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color-infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine aircraft, but the instrument was deployed on a Pilatus PC-6. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website.

EAARL Coastal Topography-Fire Island National Seashore, New York, Post-Nor'Ida, 2009

USGS Publications Warehouse

Nayegandhi, Amar; Vivekanandan, Saisudha; Brock, J.C.; Wright, C.W.; Nagle, D.B.; Bonisteel-Cormier, J.M.; Fredericks, Xan; Stevens, Sara

2010-01-01

These remotely sensed, geographically referenced elevation measurements of lidar-derived bare-earth (BE) and first-surface (FS) topography datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL, and the National Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI. This project provides highly detailed and accurate datasets of a portion of the Fire Island National Seashore in New York, acquired post-Nor'Ida (November 2009 nor'easter) on December 4, 2009. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color-infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine aircraft, but the instrument was deployed on a Pilatus PC-6. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website.

EAARL coastal topography and imagery-Fire Island National Seashore, New York, 2009

USGS Publications Warehouse

Vivekanandan, Saisudha; Klipp, E.S.; Nayegandhi, Amar; Bonisteel-Cormier, J.M.; Brock, J.C.; Wright, C.W.; Nagle, D.B.; Fredericks, Xan; Stevens, Sara

2010-01-01

These remotely sensed, geographically referenced color-infrared (CIR) imagery and elevation measurements of lidar-derived bare-earth (BE) and first-surface (FS) topography datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL, and the National Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI. This project provides highly detailed and accurate datasets of a portion of the Fire Island National Seashore in New York, acquired on July 9 and August 3, 2009. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral CIR camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument was deployed on a Pilatus PC-6. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website.

EAARL Coastal Topography-Chandeleur Islands, Louisiana, 2010: Bare Earth

USGS Publications Warehouse

Nayegandhi, Amar; Bonisteel-Cormier, Jamie M.; Brock, John C.; Sallenger, A.H.; Wright, C. Wayne; Nagle, David B.; Vivekanandan, Saisudha; Yates, Xan; Klipp, Emily S.

2010-01-01

These remotely sensed, geographically referenced elevation measurements of lidar-derived bare-earth (BE) and submerged topography datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the Chandeleur Islands, acquired March 3, 2010. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color-infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website.

EAARL Coastal Topography-Eastern Florida, Post-Hurricane Jeanne, 2004: First Surface

USGS Publications Warehouse

Fredericks, Xan; Nayegandhi, Amar; Bonisteel-Cormier, J.M.; Wright, C.W.; Sallenger, A.H.; Brock, J.C.; Klipp, E.S.; Nagle, D.B.

2010-01-01

These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the eastern Florida coastline beachface, acquired post-Hurricane Jeanne (September 2004 hurricane) on October 1, 2004. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color-infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website.

EAARL Coastal Topography-Sandy Hook Unit, Gateway National Recreation Area, New Jersey, Post-Nor'Ida, 2009

USGS Publications Warehouse

Nayegandhi, Amar; Vivekanandan, Saisudha; Brock, J.C.; Wright, C.W.; Bonisteel-Cormier, J.M.; Nagle, D.B.; Klipp, E.S.; Stevens, Sara

2010-01-01

These remotely sensed, geographically referenced elevation measurements of lidar-derived bare-earth (BE) and first-surface (FS) topography datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL, and the National Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI. This project provides highly detailed and accurate datasets of a portion of the Sandy Hook Unit of Gateway National Recreation Area in New Jersey, acquired post-Nor'Ida (November 2009 nor'easter) on December 4, 2009. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine aircraft, but the instrument was deployed on a Pilatus PC-6. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website.

EAARL Coastal Topography and Imagery-Naval Live Oaks Area, Gulf Islands National Seashore, Florida, 2007

USGS Publications Warehouse

Nagle, David B.; Nayegandhi, Amar; Yates, Xan; Brock, John C.; Wright, C. Wayne; Bonisteel, Jamie M.; Klipp, Emily S.; Segura, Martha

2010-01-01

These remotely sensed, geographically referenced color-infrared (CIR) imagery and elevation measurements of lidar-derived bare-earth (BE) topography, first-surface (FS) topography, and canopy-height (CH) datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Science Center, St. Petersburg, FL; the National Park Service (NPS), Gulf Coast Network, Lafayette, LA; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of the Naval Live Oaks Area in Florida's Gulf Islands National Seashore, acquired June 30, 2007. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral CIR camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website.

Building block extraction and classification by means of aerial images fused with super-resolution reconstructed elevation data

NASA Astrophysics Data System (ADS)

Panagiotopoulou, Antigoni; Bratsolis, Emmanuel; Charou, Eleni; Perantonis, Stavros

2017-10-01

The detailed three-dimensional modeling of buildings utilizing elevation data, such as those provided by light detection and ranging (LiDAR) airborne scanners, is increasingly demanded today. There are certain application requirements and available datasets to which any research effort has to be adapted. Our dataset includes aerial orthophotos, with a spatial resolution 20 cm, and a digital surface model generated from LiDAR, with a spatial resolution 1 m and an elevation resolution 20 cm, from an area of Athens, Greece. The aerial images are fused with LiDAR, and we classify these data with a multilayer feedforward neural network for building block extraction. The innovation of our approach lies in the preprocessing step in which the original LiDAR data are super-resolution (SR) reconstructed by means of a stochastic regularized technique before their fusion with the aerial images takes place. The Lorentzian estimator combined with the bilateral total variation regularization performs the SR reconstruction. We evaluate the performance of our approach against that of fusing unprocessed LiDAR data with aerial images. We present the classified images and the statistical measures confusion matrix, kappa coefficient, and overall accuracy. The results demonstrate that our approach predominates over that of fusing unprocessed LiDAR data with aerial images.

Gulf of Mexico region - Highlighting low-lying areas derived from USGS Digital Elevation Data

USGS Publications Warehouse

Kosovich, John J.

2008-01-01

In support of U.S. Geological Survey (USGS) disaster preparedness efforts, this map depicts a color shaded relief representation of the area surrounding the Gulf of Mexico. The first 30 feet of relief above mean sea level are displayed as brightly colored 5-foot elevation bands, which highlight low-elevation areas at a coarse spatial resolution. Standard USGS National Elevation Dataset (NED) 1 arc-second (nominally 30-meter) digital elevation model (DEM) data are the basis for the map, which is designed to be used at a broad scale and for informational purposes only. The NED data were derived from the original 1:24,000-scale USGS topographic map bare-earth contours, which were converted into gridded quadrangle-based DEM tiles at a constant post spacing (grid cell size) of either 30 meters (data before the mid-1990s data) or 10 meters (mid-1990s and later data). These individual-quadrangle DEMs were then converted to spherical coordinates (latitude/longitude decimal degrees) and edge-matched to ensure seamlessness. Approximately one-half of the area shown on this map has DEM source data at a 30-meter resolution, with the remaining half consisting of 10-meter contour-derived DEM data or higher-resolution LIDAR data. Areas below sea level typically are surrounded by levees or some other type of flood-control structures. State and county boundary, hydrography, city, and road layers were modified from USGS National Atlas data downloaded in 2003. The NED data were downloaded in 2005.

Geometric correction and digital elevation extraction using multiple MTI datasets

USGS Publications Warehouse

Mercier, Jeffrey A.; Schowengerdt, Robert A.; Storey, James C.; Smith, Jody L.

2007-01-01

Digital Elevation Models (DEMs) are traditionally acquired from a stereo pair of aerial photographs sequentially captured by an airborne metric camera. Standard DEM extraction techniques can be naturally extended to satellite imagery, but the particular characteristics of satellite imaging can cause difficulties. The spacecraft ephemeris with respect to the ground site during image collects is the most important factor in the elevation extraction process. When the angle of separation between the stereo images is small, the extraction process typically produces measurements with low accuracy, while a large angle of separation can cause an excessive number of erroneous points in the DEM from occlusion of ground areas. The use of three or more images registered to the same ground area can potentially reduce these problems and improve the accuracy of the extracted DEM. The pointing capability of some sensors, such as the Multispectral Thermal Imager (MTI), allows for multiple collects of the same area from different perspectives. This functionality of MTI makes it a good candidate for the implementation of a DEM extraction algorithm using multiple images for improved accuracy. Evaluation of this capability and development of algorithms to geometrically model the MTI sensor and extract DEMs from multi-look MTI imagery are described in this paper. An RMS elevation error of 6.3-meters is achieved using 11 ground test points, while the MTI band has a 5-meter ground sample distance.

a New High-Resolution Elevation Model of Greenland Derived from Tandem-X

NASA Astrophysics Data System (ADS)

Wessel, B.; Bertram, A.; Gruber, A.; Bemm, S.; Dech, S.

2016-06-01

In this paper we present for the first time the new digital elevation model (DEM) for Greenland produced by the TanDEM-X (TerraSAR add-on for digital elevation measurement) mission. The new, full coverage DEM of Greenland has a resolution of 0.4 arc seconds corresponding to 12 m. It is composed of more than 7.000 interferometric synthetic aperture radar (InSAR) DEM scenes. X-Band SAR penetrates the snow and ice pack by several meters depending on the structures within the snow, the acquisition parameters, and the dielectricity constant of the medium. Hence, the resulting SAR measurements do not represent the surface but the elevation of the mean phase center of the backscattered signal. Special adaptations on the nominal TanDEM-X DEM generation are conducted to maintain these characteristics and not to raise or even deform the DEM to surface reference data. For the block adjustment, only on the outer coastal regions ICESat (Ice, Cloud, and land Elevation Satellite) elevations as ground control points (GCPs) are used where mostly rock and surface scattering predominates. Comparisons with ICESat data and snow facies are performed. In the inner ice and snow pack, the final X-Band InSAR DEM of Greenland lies up to 10 m below the ICESat measurements. At the outer coastal regions it corresponds well with the GCPs. The resulting DEM is outstanding due to its resolution, accuracy and full coverage. It provides a high resolution dataset as basis for research on climate change in the arctic.

Topobathymetric model of Mobile Bay, Alabama

USGS Publications Warehouse

Danielson, Jeffrey J.; Brock, John C.; Howard, Daniel M.; Gesch, Dean B.; Bonisteel-Cormier, Jamie M.; Travers, Laurinda J.

2013-01-01

Topobathymetric Digital Elevation Models (DEMs) are a merged rendering of both topography (land elevation) and bathymetry (water depth) that provides a seamless elevation product useful for inundation mapping, as well as for other earth science applications, such as the development of sediment-transport, sea-level rise, and storm-surge models. This 1/9-arc-second (approximately 3 meters) resolution model of Mobile Bay, Alabama was developed using multiple topographic and bathymetric datasets, collected on different dates. The topographic data were obtained primarily from the U.S. Geological Survey (USGS) National Elevation Dataset (NED) (http://ned.usgs.gov/) at 1/9-arc-second resolution; USGS Experimental Advanced Airborne Research Lidar (EAARL) data (2 meters) (http://pubs.usgs.gov/ds/400/); and topographic lidar data (2 meters) and Compact Hydrographic Airborne Rapid Total Survey (CHARTS) lidar data (2 meters) from the U.S. Army Corps of Engineers (USACE) (http://www.csc.noaa.gov/digitalcoast/data/coastallidar/). Bathymetry was derived from digital soundings obtained from the National Oceanic and Atmospheric Administration’s (NOAA) National Geophysical Data Center (NGDC) (http://www.ngdc.noaa.gov/mgg/geodas/geodas.html) and from water-penetrating lidar sources, such as EAARL and CHARTS. Mobile Bay is ecologically important as it is the fourth largest estuary in the United States. The Mobile and Tensaw Rivers drain into the bay at the northern end with the bay emptying into the Gulf of Mexico at the southern end. Dauphin Island (a barrier island) and the Fort Morgan Peninsula form the mouth of Mobile Bay. Mobile Bay is 31 miles (50 kilometers) long by a maximum width of 24 miles (39 kilometers) with a total area of 413 square miles (1,070 square kilometers). The vertical datum of the Mobile Bay topobathymetric model is the North American Vertical Datum of 1988 (NAVD 88). All the topographic datasets were originally referenced to NAVD 88 and no transformations were made to these input data. The NGDC hydrographic, multibeam, and trackline surveys were transformed from mean low water (MLW) or mean lower low water (MLLW) to NAVD 88 using VDatum (http://vdatum.noaa.gov). VDatum is a tool developed by the National Geodetic Survey (NGS) that performs transformations among tidal, ellipsoid-based, geoid-based, and orthometric datums using calibrated hydrodynamic models. The vertical accuracy of the input topographic data varied depending on the input source. Because the input elevation data were derived primarily from lidar, the vertical accuracy ranges from 6 to 20 centimeters in root mean square error (RMSE). he horizontal datum of the Mobile Bay topobathymetric model is the North American Datum of 1983 (NAD 83), geographic coordinates. All the topographic and bathymetric datasets were originally referenced to NAD 83, and no transformations were made to the input data. The bathymetric surveys were downloaded referenced to NAD 83 geographic, and therefore no horizontal transformations were required. The topbathymetric model of Mobile Bay and detailed metadata can be obtained from the USGS Web sites: http://nationalmap.gov/.

Framework for National Flood Risk Assessment for Canada

NASA Astrophysics Data System (ADS)

Elshorbagy, A. A.; Raja, B.; Lakhanpal, A.; Razavi, S.; Ceola, S.; Montanari, A.

2016-12-01

Worldwide, floods have been identified as a standout amongst the most widely recognized catastrophic events, resulting in the loss of life and property. These natural hazards cannot be avoided, but their consequences can certainly be reduced by having prior knowledge of their occurrence and impact. In the context of floods, the terms occurrence and impact are substituted by flood hazard and flood vulnerability, respectively, which collectively define the flood risk. There is a high need for identifying the flood-prone areas and to quantify the risk associated with them. The present study aims at delivering flood risk maps, which prioritize the potential flood risk areas in Canada. The methodology adopted in this study involves integrating various available spatial datasets such as nightlights satellite imagery, land use, population and the digital elevation model, to build a flexible framework for national flood risk assessment for Canada. The flood risk framework assists in identifying the flood-prone areas and evaluating the associated risk. All these spatial datasets were brought to a common GIS platform for flood risk analysis. The spatial datasets deliver the socioeconomic and topographical information that is required for evaluating the flood vulnerability and flood hazard, respectively. Nightlights have been investigated as a tool to be used as a proxy for the human activities to identify areas with regard to economic investment. However, other datasets, including existing flood protection measures, we added to identify a realistic flood assessment framework. Furthermore, the city of Calgary was used as an example to investigate the effect of using Digital Elevation Models (DEMs) of varying resolutions on risk maps. Along with this, the risk map for the city was further enhanced by including the population data to give a social dimension to the risk map. Flood protection measures play a major role by significantly reducing the flood risk of events with a specific return period. An analysis to update the risk maps when information on protection measures is available was carried out for the city of Winnipeg, Canada. The proposed framework is a promising approach to identify and prioritize flood-prone areas, which are in need of intervention or detailed studies.

Validation of digital elevation models (DEMs) and comparison of geomorphic metrics on the southern Central Andean Plateau

NASA Astrophysics Data System (ADS)

Purinton, Benjamin; Bookhagen, Bodo

2017-04-01

In this study, we validate and compare elevation accuracy and geomorphic metrics of satellite-derived digital elevation models (DEMs) on the southern Central Andean Plateau. The plateau has an average elevation of 3.7 km and is characterized by diverse topography and relief, lack of vegetation, and clear skies that create ideal conditions for remote sensing. At 30 m resolution, SRTM-C, ASTER GDEM2, stacked ASTER L1A stereopair DEM, ALOS World 3D, and TanDEM-X have been analyzed. The higher-resolution datasets include 12 m TanDEM-X, 10 m single-CoSSC TerraSAR-X/TanDEM-X DEMs, and 5 m ALOS World 3D. These DEMs are state of the art for optical (ASTER and ALOS) and radar (SRTM-C and TanDEM-X) spaceborne sensors. We assessed vertical accuracy by comparing standard deviations of the DEM elevation versus 307 509 differential GPS measurements across 4000 m of elevation. For the 30 m DEMs, the ASTER datasets had the highest vertical standard deviation at > 6.5 m, whereas the SRTM-C, ALOS World 3D, and TanDEM-X were all < 3.5 m. Higher-resolution DEMs generally had lower uncertainty, with both the 12 m TanDEM-X and 5 m ALOS World 3D having < 2 m vertical standard deviation. Analysis of vertical uncertainty with respect to terrain elevation, slope, and aspect revealed the low uncertainty across these attributes for SRTM-C (30 m), TanDEM-X (12-30 m), and ALOS World 3D (5-30 m). Single-CoSSC TerraSAR-X/TanDEM-X 10 m DEMs and the 30 m ASTER GDEM2 displayed slight aspect biases, which were removed in their stacked counterparts (TanDEM-X and ASTER Stack). Based on low vertical standard deviations and visual inspection alongside optical satellite data, we selected the 30 m SRTM-C, 12-30 m TanDEM-X, 10 m single-CoSSC TerraSAR-X/TanDEM-X, and 5 m ALOS World 3D for geomorphic metric comparison in a 66 km2 catchment with a distinct river knickpoint. Consistent m/n values were found using chi plot channel profile analysis, regardless of DEM type and spatial resolution. Slope, curvature, and drainage area were calculated and plotting schemes were used to assess basin-wide differences in the hillslope-to-valley transition related to the knickpoint. While slope and hillslope length measurements vary little between datasets, curvature displays higher magnitude measurements with fining resolution. This is especially true for the optical 5 m ALOS World 3D DEM, which demonstrated high-frequency noise in 2-8 pixel steps through a Fourier frequency analysis. The improvements in accurate space-radar DEMs (e.g., TanDEM-X) for geomorphometry are promising, but airborne or terrestrial data are still necessary for meter-scale analysis.

Etna_NETVIS: A dedicated tool for automatically pre-processing high frequency data useful to extract geometrical parameters and track the evolution of the lava field

NASA Astrophysics Data System (ADS)

Marsella, Maria; Junior Valentino D'Aranno, Peppe; De Bonis, Roberto; Nardinocchi, Carla; Scifoni, Silvia; Scutti, Marianna; Sonnessa, Alberico; Wahbeh, Wissam; Biale, Emilio; Coltelli, Mauro; Pecora, Emilio; Prestifilippo, Michele; Proietti, Cristina

2016-04-01

In volcanic areas, where it could be difficult to gain access to the most critical zones for carrying out direct surveys, digital photogrammetry techniques are rarely experimented, although in many cases they proved to have remarkable potentialities, as the possibility to follow the evolution of volcanic (fracturing, vent positions, lava fields, lava front positions) and deformation processes (inflation/deflation and instability phenomena induced by volcanic activity). These results can be obtained, in the framework of standard surveillance activities, by acquiring multi-temporal datasets including Digital Orthophotos (DO) and Digital Elevation Models (DEM) to be used for implementing a quantitative and comparative analysis. The frequency of the surveys can be intensified during emergency phases to implement a quasi real-time monitoring for supporting civil protection actions. The high level of accuracy and the short time required for image processing make digital photogrammetry a suitable tool for controlling the evolution of volcanic processes which are usually characterized by large and rapid mass displacements. In order to optimize and extend the existing permanent ground NEtwork of Thermal and VIsible Sensors located on Mt. Etna (Etna_NETVIS) and to improve the observation of the most active areas, an approach for monitoring surface sin-eruptive processes was implemented. A dedicated tool for automatically pre-processing high frequency data, useful to extract geometrical parameters as well as to track the evolution of the lava field, was developed and tested both in simulated and real scenarios. The tool allows to extract a coherent multi-temporal dataset of orthophotos useful to evaluate active flow area and to estimate effusion rates. Furthermore, Etna_NETVIS data were used to downscale the information derived from satellite data and/or to integrate the satellite datasets in case of incomplete coverage or missing acquisitions. This work was developed in the framework of the EU-FP7 project "MED-SUV" (MEDiterranean SUpersite Volcanoes).

Appending High-Resolution Elevation Data to GPS Speed Traces for Vehicle Energy Modeling and Simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wood, E.; Burton, E.; Duran, A.

Accurate and reliable global positioning system (GPS)-based vehicle use data are highly valuable for many transportation, analysis, and automotive considerations. Model-based design, real-world fuel economy analysis, and the growing field of autonomous and connected technologies (including predictive powertrain control and self-driving cars) all have a vested interest in high-fidelity estimation of powertrain loads and vehicle usage profiles. Unfortunately, road grade can be a difficult property to extract from GPS data with consistency. In this report, we present a methodology for appending high-resolution elevation data to GPS speed traces via a static digital elevation model. Anomalous data points in the digitalmore » elevation model are addressed during a filtration/smoothing routine, resulting in an elevation profile that can be used to calculate road grade. This process is evaluated against a large, commercially available height/slope dataset from the Navteq/Nokia/HERE Advanced Driver Assistance Systems product. Results will show good agreement with the Advanced Driver Assistance Systems data in the ability to estimate road grade between any two consecutive points in the contiguous United States.« less

Validation Study on Alos Prism Dsm Mosaic and Aster Gdem 2

NASA Astrophysics Data System (ADS)

Tadono, T.; Takaku, J.; Shimada, M.

2012-07-01

This study aims to evaluate height accuracy of two datasets obtained by spaceborne optical instruments of a digital elevation data for a large-scale area. The digital surface model (DSM) was generated by the Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) onboard the Advanced Land Observing Satellite (ALOS, nicknamed 'Daichi'), and the global digital elevation model (DEM) version 2 (GDEM-2) was derived from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) onboard NASA's TERRA satellite. The test site of this study was the entire country of Bhutan, which is located on the southern slopes of the eastern Himalayas. Bhutan is not a large country, covering about 330 km from east to west, and 170 km from north to south; however, it has large height variation from 200 m to more than 7,000 m. This therefore makes it very interesting for validating digital topographic information in terms of national scale generation as well as wide height range. Regarding the reference data, field surveys were conducted in 2010 and 2011, and collected ground control points by a global positioning system were used for evaluating precise height accuracies in point scale as check points (CPs), with a 3 arc-sec DEM created by the Shuttle Radar Topography Mission (SRTM-3) used to validate the wide region. The results confirmed a root mean square error of 8.1 m for PRISM DSM and 29.4 m for GDEM-2 by CPs.

High-quality seamless DEM generation blending SRTM-1, ASTER GDEM v2 and ICESat/GLAS observations

NASA Astrophysics Data System (ADS)

Yue, Linwei; Shen, Huanfeng; Zhang, Liangpei; Zheng, Xianwei; Zhang, Fan; Yuan, Qiangqiang

2017-01-01

The absence of a high-quality seamless global digital elevation model (DEM) dataset has been a challenge for the Earth-related research fields. Recently, the 1-arc-second Shuttle Radar Topography Mission (SRTM-1) data have been released globally, covering over 80% of the Earth's land surface (60°N-56°S). However, voids and anomalies still exist in some tiles, which has prevented the SRTM-1 dataset from being directly used without further processing. In this paper, we propose a method to generate a seamless DEM dataset blending SRTM-1, ASTER GDEM v2, and ICESat laser altimetry data. The ASTER GDEM v2 data are used as the elevation source for the SRTM void filling. To get a reliable filling source, ICESat GLAS points are incorporated to enhance the accuracy of the ASTER data within the void regions, using an artificial neural network (ANN) model. After correction, the voids in the SRTM-1 data are filled with the corrected ASTER GDEM values. The triangular irregular network based delta surface fill (DSF) method is then employed to eliminate the vertical bias between them. Finally, an adaptive outlier filter is applied to all the data tiles. The final result is a seamless global DEM dataset. ICESat points collected from 2003 to 2009 were used to validate the effectiveness of the proposed method, and to assess the vertical accuracy of the global DEM products in China. Furthermore, channel networks in the Yangtze River Basin were also extracted for the data assessment.

Nearshore coastal bathymetry data collected in 2016 from West Ship Island to Horn Island, Gulf Islands National Seashore, Mississippi

USGS Publications Warehouse

DeWitt, Nancy T.; Stalk, Chelsea A.; Fredericks, Jake J.; Flocks, James G.; Kelso, Kyle W.; Farmer, Andrew S.; Tuten, Thomas M.; Buster, Noreen A.

2018-04-13

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center, in cooperation with the U.S. Army Corps of Engineers, Mobile District, conducted bathymetric surveys of the nearshore waters surrounding Ship and Horn Islands, Gulf Islands National Seashore, Mississippi. The objective of this study was to establish base-level elevation conditions around West Ship, East Ship, and Horn Islands and their associated active littoral system prior to restoration activities. These activities include the closure of Camille Cut and the placement of sediment in the littoral zone of East Ship Island. These surveys can be compared with future surveys to monitor sediment migration patterns post-restoration and can also be measured against historic bathymetric datasets to further our understanding of island evolution.The USGS collected 667 line-kilometers (km) of single-beam bathymetry data and 844 line-km of interferometric swath bathymetry data in July 2016 under Field Activity Number 2016-347-FA. Data are provided in three datums: (1) the International Terrestrial Reference Frame of 2000 (ellipsoid height); (2) the North American Datum of 1983 (NAD83) CORS96 realization and the North American Vertical Datum of 1988 with respect to the GEOID12B model (orthometric height); and (3) NAD83 (CORS96) and Mean Lower Low Water (tidal datum). Data products, including x,y,zpoint datasets, trackline shapefiles, digital and handwritten Field Activity Collection Systems logs, 50-meter digital elevation model, and formal Federal Geographic Data Committee metadata, are available for download.

Topographic and hydrographic GIS datasets for the Afghan Geological Survey and U.S. Geological Survey 2013 mineral areas of interest

USGS Publications Warehouse

Casey, Brittany N.; Chirico, Peter G.

2013-01-01

Afghanistan is endowed with a vast amount of mineral resources, and it is believed that the current economic state of the country could be greatly improved through investment in the extraction and production of these resources. In 2007, the “Preliminary Non-Fuel Resource Assessment of Afghanistan 2007” was completed by members of the U.S. Geological Survey and Afghan Geological Survey (Peters and others, 2007). The assessment delineated 20 mineralized areas for further study using a geologic-based methodology. In 2011, a follow-on data product, “Summaries and Data Packages of Important Areas for Mineral Investment and Production Opportunities of Nonfuel Minerals in Afghanistan,” was released (Peters and others, 2011). As part of this more recent work, geologic, geohydrologic, and hyperspectral studies were carried out in the areas of interest (AOIs) to assess the location and characteristics of the mineral resources. The 2011 publication included a dataset of 24 identified AOIs containing subareas, a corresponding digital elevation model (DEM), elevation contours, areal extent, and hydrography for each AOI. In 2012, project scientists identified five new AOIs and two subareas in Afghanistan. These new areas are Ahankashan, Kandahar, Parwan, North Bamyan, and South Bamyan. The two identified subareas include Obatu-Shela and Sekhab-ZamtoKalay, both located within the larger Kandahar AOI. In addition, an extended Kandahar AOI is included in the project for water resource modeling purposes. The dataset presented in this publication consists of the areal extent of the five new AOIs, two subareas, and the extended Kandahar AOI, elevation contours at 100-, 50-, and 25-meter intervals, an enhanced DEM, and a hydrographic dataset covering the extent of the new study area. The resulting raster and vector layers are intended for use by government agencies, developmental organizations, and private companies in Afghanistan to assist with mineral assessments, monitoring, management, and investment.

Topographic changes and their driving factors after 2008 Wenchuan earthquake

NASA Astrophysics Data System (ADS)

Li, Congrong; Wang, Ming; Liu, Kai; Xie, Jun

2018-06-01

The 2008 Wenchuan Earthquake caused topographic change in the stricken areas because of the occurrence of numerous coseismic landslides. The emergence of new landslides and debris flows and movement of loose materials under the driving force of high rainfall could further shape the local topography. Currently, little attention has been paid to continuously monitoring and assessing topographic changes after the major earthquake. In this research, we obtained an elevation dataset (2002, 2010, 2013 and 2015) based on digital elevation model (DEM) data and a DEM extracted from ZY-3 stereo paired images with validation by field measurement. We quantitatively assessed elevation changes in different years and qualitatively analyzed spatiotemporal variation of the terrain and mass movement across the study area. The results show that the earthquake affected area experienced substantial elevation changes caused by seismic forces and subsequent rainfalls. High rainfall after the earthquake have become the biggest driver of elevation reduction, which overwhelmed elevation increase caused by the major earthquake. Increased post-earthquake erosion intensity has caused large amounts of loose materials to accumulate in river channels, and gullies and on upper-middle mountain slopes, which increases the risk of flooding and geo-hazards in the area.

State of Louisiana - Highlighting low-lying areas derived from USGS Digital Elevation Data

USGS Publications Warehouse

Kosovich, John J.

2008-01-01

In support of U.S. Geological Survey (USGS) disaster preparedness efforts, this map depicts a color shaded relief representation highlighting the State of Louisiana and depicts the surrounding areas using muted elevation colors. The first 30 feet of relief above mean sea level are displayed as brightly colored 5-foot elevation bands, which highlight low-elevation areas at a coarse spatial resolution. Areas below sea level typically are surrounded by levees or some other type of flood-control structures. Standard USGS National Elevation Dataset (NED) 1 arc-second (nominally 30-meter) digital elevation model (DEM) data are the basis for the map, which is designed to be used at a broad scale and for informational purposes only. The NED data are a mixture of data and were derived from the original 1:24,000-scale USGS topographic map bare-earth contours, which were converted into gridded quadrangle-based DEM tiles at a constant post spacing (grid cell size) of either 30 meters (data before the mid-1990s) or 10 meters (mid-1990s and later data). These individual-quadrangle DEMs were then converted to spherical coordinates (latitude/longitude decimal degrees) and edge-matched to ensure seamlessness. Approximately one-half of the area shown on this map has DEM source data at a 30-meter resolution, with the remaining half consisting of mostly 10-meter contour-derived DEM data and some small areas of higher-resolution LIght Detection And Ranging (LIDAR) data along parts of the coastline. Areas below sea level typically are surrounded by levees or some other type of flood-control structures. State and parish boundary, hydrography, city, and road layers were modified from USGS National Atlas data downloaded in 2003. The NED data were downloaded in 2007.

1-Meter Digital Elevation Model specification

USGS Publications Warehouse

Arundel, Samantha T.; Archuleta, Christy-Ann M.; Phillips, Lori A.; Roche, Brittany L.; Constance, Eric W.

2015-10-21

In January 2015, the U.S. Geological Survey National Geospatial Technical Operations Center began producing the 1-Meter Digital Elevation Model data product. This new product was developed to provide high resolution bare-earth digital elevation models from light detection and ranging (lidar) elevation data and other elevation data collected over the conterminous United States (lower 48 States), Hawaii, and potentially Alaska and the U.S. territories. The 1-Meter Digital Elevation Model consists of hydroflattened, topographic bare-earth raster digital elevation models, with a 1-meter x 1-meter cell size, and is available in 10,000-meter x 10,000-meter square blocks with a 6-meter overlap. This report details the specifications required for the production of the 1-Meter Digital Elevation Model.

Finding Mount Everest and handling voids.

PubMed

Storch, Tobias

2011-01-01

Evolutionary algorithms (EAs) are randomized search heuristics that solve problems successfully in many cases. Their behavior is often described in terms of strategies to find a high location on Earth's surface. Unfortunately, many digital elevation models describing it contain void elements. These are elements not assigned an elevation. Therefore, we design and analyze simple EAs with different strategies to handle such partially defined functions. They are experimentally investigated on a dataset describing the elevation of Earth's surface. The largest value found by an EA within a certain runtime is measured, and the median over a few runs is computed and compared for the different EAs. For the dataset, the distribution of void elements seems to be neither random nor adversarial. They are so-called semirandomly distributed. To deepen our understanding of the behavior of the different EAs, they are theoretically considered on well-known pseudo-Boolean functions transferred to partially defined ones. These modifications are also performed in a semirandom way. The typical runtime until an optimum is found by an EA is analyzed, namely bounded from above and below, and compared for the different EAs. We figure out that for the random model it is a good strategy to assume that a void element has a worse function value than all previous elements. Whereas for the adversary model it is a good strategy to assume that a void element has the best function value of all previous elements.

TerraSAR-X/TanDEM-X data for natural hazards research in mountainous regions of Uzbekistan

NASA Astrophysics Data System (ADS)

Semakova, Eleonora; Bühler, Yves

2017-07-01

Accurate and up-to-date digital elevation models (DEMs) are important tools for studying mountain hazards. We considered natural hazards related to glacier retreat, debris flows, and snow avalanches in two study areas of the Western Tien-Shan mountains, Uzbekistan. High-resolution DEMs were generated using single TerraSAR-X/TanDEM-X datasets. The high quality and actuality of the DEMs were proved through a comparison with Shuttle Radar Topography Mission, Advanced Spaceborne Emission and Reflection Radiometer, and Topo DEMs, using Ice, Cloud, and Land Elevation Satellite data as the reference dataset. For the first study area, which had high levels of economic activity, we applied the generated TanDEM-X DEM to an avalanche dynamics simulation using RAMMS software. Verification of the output results showed good agreement with field observations. For the second study area, with a wide spatial distribution of glaciers, we applied the TanDEM-X DEM to an assessment of glacier surface elevation changes. The results can be used to calculate the local mass balance in glacier ablation zones in other areas. Models were applied to estimate the probability of moraine-dammed lake formation and the affected area of a possible debris flow resulting from glacial lake outburst. The natural hazard research methods considered here will minimize costly ground observations in poorly accessible mountains and mitigate the impacts of hazards on the environment of Uzbekistan.

Validation of the Aster Global Digital Elevation Model Version 3 Over the Conterminous United States

NASA Astrophysics Data System (ADS)

Gesch, D.; Oimoen, M.; Danielson, J.; Meyer, D.

2016-06-01

The ASTER Global Digital Elevation Model Version 3 (GDEM v3) was evaluated over the conterminous United States in a manner similar to the validation conducted for the original GDEM Version 1 (v1) in 2009 and GDEM Version 2 (v2) in 2011. The absolute vertical accuracy of GDEM v3 was calculated by comparison with more than 23,000 independent reference geodetic ground control points from the U.S. National Geodetic Survey. The root mean square error (RMSE) measured for GDEM v3 is 8.52 meters. This compares with the RMSE of 8.68 meters for GDEM v2. Another important descriptor of vertical accuracy is the mean error, or bias, which indicates if a DEM has an overall vertical offset from true ground level. The GDEM v3 mean error of -1.20 meters reflects an overall negative bias in GDEM v3. The absolute vertical accuracy assessment results, both mean error and RMSE, were segmented by land cover type to provide insight into how GDEM v3 performs in various land surface conditions. While the RMSE varies little across cover types (6.92 to 9.25 meters), the mean error (bias) does appear to be affected by land cover type, ranging from -2.99 to +4.16 meters across 14 land cover classes. These results indicate that in areas where built or natural aboveground features are present, GDEM v3 is measuring elevations above the ground level, a condition noted in assessments of previous GDEM versions (v1 and v2) and an expected condition given the type of stereo-optical image data collected by ASTER. GDEM v3 was also evaluated by differencing with the Shuttle Radar Topography Mission (SRTM) dataset. In many forested areas, GDEM v3 has elevations that are higher in the canopy than SRTM. The overall validation effort also included an evaluation of the GDEM v3 water mask. In general, the number of distinct water polygons in GDEM v3 is much lower than the number in a reference land cover dataset, but the total areas compare much more closely.

Validation of the ASTER Global Digital Elevation Model version 3 over the conterminous United States

USGS Publications Warehouse

Gesch, Dean B.; Oimoen, Michael J.; Danielson, Jeffrey J.; Meyer, David; Halounova, L; Šafář, V.; Jiang, J.; Olešovská, H.; Dvořáček, P.; Holland, D.; Seredovich, V.A.; Muller, J.P.; Pattabhi Rama Rao, E.; Veenendaal, B.; Mu, L.; Zlatanova, S.; Oberst, J.; Yang, C.P.; Ban, Y.; Stylianidis, S.; Voženílek, V.; Vondráková, A.; Gartner, G.; Remondino, F.; Doytsher, Y.; Percivall, George; Schreier, G.; Dowman, I.; Streilein, A.; Ernst, J.

2016-01-01

The ASTER Global Digital Elevation Model Version 3 (GDEM v3) was evaluated over the conterminous United States in a manner similar to the validation conducted for the original GDEM Version 1 (v1) in 2009 and GDEM Version 2 (v2) in 2011. The absolute vertical accuracy of GDEM v3 was calculated by comparison with more than 23,000 independent reference geodetic ground control points from the U.S. National Geodetic Survey. The root mean square error (RMSE) measured for GDEM v3 is 8.52 meters. This compares with the RMSE of 8.68 meters for GDEM v2. Another important descriptor of vertical accuracy is the mean error, or bias, which indicates if a DEM has an overall vertical offset from true ground level. The GDEM v3 mean error of −1.20 meters reflects an overall negative bias in GDEM v3. The absolute vertical accuracy assessment results, both mean error and RMSE, were segmented by land cover type to provide insight into how GDEM v3 performs in various land surface conditions. While the RMSE varies little across cover types (6.92 to 9.25 meters), the mean error (bias) does appear to be affected by land cover type, ranging from −2.99 to +4.16 meters across 14 land cover classes. These results indicate that in areas where built or natural aboveground features are present, GDEM v3 is measuring elevations above the ground level, a condition noted in assessments of previous GDEM versions (v1 and v2) and an expected condition given the type of stereo-optical image data collected by ASTER. GDEM v3 was also evaluated by differencing with the Shuttle Radar Topography Mission (SRTM) dataset. In many forested areas, GDEM v3 has elevations that are higher in the canopy than SRTM. The overall validation effort also included an evaluation of the GDEM v3 water mask. In general, the number of distinct water polygons in GDEM v3 is much lower than the number in a reference land cover dataset, but the total areas compare much more closely.

Watershed boundaries and digital elevation model of Oklahoma derived from 1:100,000-scale digital topographic maps

USGS Publications Warehouse

Cederstrand, J.R.; Rea, A.H.

1995-01-01

This document provides a general description of the procedures used to develop the data sets included on this compact disc. This compact disc contains watershed boundaries for Oklahoma, a digital elevation model, and other data sets derived from the digital elevation model. The digital elevation model was produced using the ANUDEM software package, written by Michael Hutchinson and licensed from the Centre for Resource and Environmental Studies at The Australian National University. Elevation data (hypsography) and streams (hydrography) from digital versions of the U.S. Geological Survey 1:100,000-scale topographic maps were used by the ANUDEM package to produce a hydrologically conditioned digital elevation model with a 60-meter cell size. This digital elevation model is well suited for drainage-basin delineation using automated techniques. Additional data sets include flow-direction, flow-accumulation, and shaded-relief grids, all derived from the digital elevation model, and the hydrography data set used in producing the digital elevation model. The watershed boundaries derived from the digital elevation model have been edited to be consistent with contours and streams from the U.S. Geological Survey 1:100,000-scale topographic maps. The watershed data set includes boundaries for 11-digit Hydrologic Unit Codes (watersheds) within Oklahoma, and 8-digit Hydrologic Unit Codes (cataloging units) outside Oklahoma. Cataloging-unit boundaries based on 1:250,000-scale maps outside Oklahoma for the Arkansas, Red, and White River basins are included. The other data sets cover Oklahoma, and where available, portions of 1:100,000-scale quadrangles adjoining Oklahoma.

EAARL Coastal Topography - Northern Gulf of Mexico, 2007: First Surface

USGS Publications Warehouse

Smith, Kathryn E.L.; Nayegandhi, Amar; Wright, C. Wayne; Bonisteel, Jamie M.; Brock, John C.

2009-01-01

These remotely sensed, geographically referenced elevation measurements of Lidar-derived first surface (FS) elevation data were produced as a collaborative effort between the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL; the National Park Service (NPS), Gulf Coast Network, Lafayette, LA; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. The project provides highly detailed and accurate datasets of select barrier islands and peninsular regions of Louisiana, Mississippi, Alabama, and Florida, acquired June 27-30, 2007. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative airborne Lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) Lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive Lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit which provide for submeter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a Lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for presurvey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.

The use of karst geomorphology for planning, hazard avoidance and development in Great Britain

NASA Astrophysics Data System (ADS)

Cooper, Anthony H.; Farrant, Andrew R.; Price, Simon J.

2011-11-01

Within Great Britain five main types of karstic rocks - dolomite, limestone, chalk, gypsum and salt - are present. Each presents a different type and severity of karstic geohazard which are related to the rock solubility and geological setting. Typical karstic features associated with these rocks have been databased by the British Geological Survey (BGS) with records of sinkholes, cave entrances, stream sinks, resurgences and building damage; data for more than half of the country has been gathered. BGS has manipulated digital map data, for bedrock and superficial deposits, with digital elevation slope models, superficial deposit thickness models, the karst data and expertly interpreted areas, to generate a derived dataset assessing the likelihood of subsidence due to karst collapse. This dataset is informed and verified by the karst database and marketed as part of the BGS GeoSure suite. It is currently used by environmental regulators, the insurance and construction industries, and the BGS semi-automated enquiry system. The database and derived datasets can be further combined and manipulated using GIS to provide other datasets that deal with specific problems. Sustainable drainage systems, some of which use soak-aways into the ground, are being encouraged in Great Britain, but in karst areas they can cause ground stability problems. Similarly, open loop ground source heat or cooling pump systems may induce subsidence if installed in certain types of karstic environments such as in chalk with overlying sand deposits. Groundwater abstraction also has the potential to trigger subsidence in karst areas. GIS manipulation of the karst information is allowing Great Britain to be zoned into areas suitable, or unsuitable, for such uses; it has the potential to become part of a suite of planning management tools for local and National Government to assess the long term sustainable use of the ground.

Free internet datasets for streamflow modelling using SWAT in the Johor river basin, Malaysia

NASA Astrophysics Data System (ADS)

Tan, M. L.

2014-02-01

Streamflow modelling is a mathematical computational approach that represents terrestrial hydrology cycle digitally and is used for water resources assessment. However, such modelling endeavours require a large amount of data. Generally, governmental departments produce and maintain these data sets which make it difficult to obtain this data due to bureaucratic constraints. In some countries, the availability and quality of geospatial and climate datasets remain a critical issue due to many factors such as lacking of ground station, expertise, technology, financial support and war time. To overcome this problem, this research used public domain datasets from the Internet as "input" to a streamflow model. The intention is simulate daily and monthly streamflow of the Johor River Basin in Malaysia. The model used is the Soil and Water Assessment Tool (SWAT). As input free data including a digital elevation model (DEM), land use information, soil and climate data were used. The model was validated by in-situ streamflow information obtained from Rantau Panjang station for the year 2006. The coefficient of determination and Nash-Sutcliffe efficiency were 0.35/0.02 for daily simulated streamflow and 0.92/0.21 for monthly simulated streamflow, respectively. The results show that free data can provide a better simulation at a monthly scale compared to a daily basis in a tropical region. A sensitivity analysis and calibration procedure should be conducted in order to maximize the "goodness-of-fit" between simulated and observed streamflow. The application of Internet datasets promises an acceptable performance of streamflow modelling. This research demonstrates that public domain data is suitable for streamflow modelling in a tropical river basin within acceptable accuracy.

Search for the 700,000-year-old source crater of the Australasian tektite strewn field

NASA Technical Reports Server (NTRS)

Schnetzler, C. C.; Garvin, J. B.

1992-01-01

Many tektite investigations have hypothesized that the impact crater that was the source of the extensive Australasian strewn field lies somewhere in or near Indochina. This is due to variations in abundance and size of tektites across the strewn field, variation of thickness of microtektite layers in ocean cores, nature and ablation characteristics across the field, and, above all, the occurrence of the large, blocky, layered Muong Nong-type tektites in Indochina. A recent study of the location and chemistry of Muong Nong-type and splash-form tektites suggests that the source region can be further narrowed to a limited area in eastern Thailand and southern Loas. Satellite multispectral imagery, a digital elevation dataset, and maps showing drainage patterns were used to search within this area for possible anomalous features that may be large degraded impact craters. Four interesting structures were identified from these datasets, and they are presented.

The 3D elevation program - Precision agriculture and other farm practices

USGS Publications Warehouse

Sugarbaker, Larry J.; Carswell, Jr., William J.

2016-12-27

A founding motto of the Natural Resources Conservation Service (NRCS), originally the Soil Conservation Service (SCS), explains that “If we take care of the land, it will take care of us.” Digital elevation models (DEMs; see fig. 1) are derived from light detection and ranging (lidar) data and can be processed to derive values such as slope angle, aspect, and topographic curvature. These three measurements are the principal parameters of the NRCS LidarEnhanced Soil Survey (LESS) model, which improves the precision of soil surveys, by more accurately displaying the slopes and soils patterns, while increasing the objectivity and science in line placement. As combined resources, DEMs, LESS model outputs, and similar derived datasets are essential for conserving soil, wetlands, and other natural resources managed and overseen by the NRCS and other Federal and State agencies.

The 10 m-resolution TINITALY DEM as a trans-disciplinary basis for the analysis of the Italian territory: Current trends and new perspectives

NASA Astrophysics Data System (ADS)

Tarquini, Simone; Nannipieri, Luca

2017-03-01

The increasing availability of high resolution digital elevation models (DEMs) is changing our viewpoint towards Earth surface landforms. Nevertheless, large-coverage, intermediate-resolution DEMs are still largely used, and can be the ideal choice in several applications based on the processing of spatially-integrated information. In 2012 the Istituto Nazionale di Geofisica e Vulcanologia opened a website for the free download of the "TINTALY" Digital Elevation Model (DEM), which covers the whole Italian territory. Since then, about 700 users from 28 different countries have been accredited for data download, and a report of 4 years of data dissemination and use is presented. The analysis of the intended use reveals that the 10 m-resolution, seamless TINITALY DEM is of use for an extremely assorted research community. Accredited users are working in virtually any branch of the Earth Sciences (e.g. Volcanology, Seismology, and Geomorphology), in spatially integrated humanities (e.g. History and Archaeology), and in other thematic areas such as in applied Physics and Zoology. Many users are also working in local administrations (e.g. Regions and Municipalities) for civil protection or land use planning purposes. In summary, the documented activity shows that the dissemination of seamless, large coverage elevation datasets can fertilize the technological progress of the whole society providing a significant benefit to stakeholders.

A multitemporal (1979-2009) land-use/land-cover dataset of the binational Santa Cruz Watershed

USGS Publications Warehouse

2011-01-01

Trends derived from multitemporal land-cover data can be used to make informed land management decisions and to help managers model future change scenarios. We developed a multitemporal land-use/land-cover dataset for the binational Santa Cruz watershed of southern Arizona, United States, and northern Sonora, Mexico by creating a series of land-cover maps at decadal intervals (1979, 1989, 1999, and 2009) using Landsat Multispectral Scanner and Thematic Mapper data and a classification and regression tree classifier. The classification model exploited phenological changes of different land-cover spectral signatures through the use of biseasonal imagery collected during the (dry) early summer and (wet) late summer following rains from the North American monsoon. Landsat images were corrected to remove atmospheric influences, and the data were converted from raw digital numbers to surface reflectance values. The 14-class land-cover classification scheme is based on the 2001 National Land Cover Database with a focus on "Developed" land-use classes and riverine "Forest" and "Wetlands" cover classes required for specific watershed models. The classification procedure included the creation of several image-derived and topographic variables, including digital elevation model derivatives, image variance, and multitemporal Kauth-Thomas transformations. The accuracy of the land-cover maps was assessed using a random-stratified sampling design, reference aerial photography, and digital imagery. This showed high accuracy results, with kappa values (the statistical measure of agreement between map and reference data) ranging from 0.80 to 0.85.

EAARL Coastal Topography - Northeast Barrier Islands 2007: Bare Earth

USGS Publications Warehouse

Nayegandhi, Amar; Brock, John C.; Sallenger, A.H.; Wright, C. Wayne; Yates, Xan; Bonisteel, Jamie M.

2008-01-01

These remotely sensed, geographically referenced elevation measurements of Lidar-derived bare earth (BE) topography were produced collaboratively by the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of the northeast coastal barrier islands in New York and New Jersey, acquired April 29-30 and May 15-16, 2007. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative airborne Lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) Lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive Lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers and an integrated miniature digital inertial measurement unit, which provide for submeter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a Lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for presurvey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is routinely used to create maps that represent submerged or first surface topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.

EAARL Topography - Natchez Trace Parkway 2007: First Surface

USGS Publications Warehouse

Nayegandhi, Amar; Brock, John C.; Wright, C. Wayne; Segura, Martha; Yates, Xan

2008-01-01

These remotely sensed, geographically referenced elevation measurements of Lidar-derived first surface (FS) topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL; the National Park Service (NPS), Gulf Coast Network, Lafayette, LA; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the Natchez Trace Parkway in Mississippi, acquired on September 14, 2007. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative airborne Lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) Lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive Lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for submeter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a Lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for presurvey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or first surface topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.

EAARL Topography - Vicksburg National Military Park 2008: Bare Earth

USGS Publications Warehouse

Nayegandhi, Amar; Brock, John C.; Wright, C. Wayne; Segura, Martha; Yates, Xan

2008-01-01

These remotely sensed, geographically referenced elevation measurements of Lidar-derived bare earth (BE) topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL; the National Park Service (NPS), Gulf Coast Network, Lafayette, LA; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of the Vicksburg National Military Park in Mississippi, acquired on March 6, 2008. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative airborne Lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) Lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive Lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for submeter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a Lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for presurvey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or first surface topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.

EAARL Coastal Topography - Northeast Barrier Islands 2007: First Surface

USGS Publications Warehouse

Nayegandhi, Amar; Brock, John C.; Sallenger, A.H.; Wright, C. Wayne; Yates, Xan; Bonisteel, Jamie M.

2009-01-01

These remotely sensed, geographically referenced elevation measurements of Lidar-derived first surface (FS) topography were produced collaboratively by the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of the northeast coastal barrier islands in New York and New Jersey, acquired April 29-30 and May 15-16, 2007. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative airborne Lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) Lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive Lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for submeter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a Lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for presurvey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is routinely used to create maps that represent submerged or first surface topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.

EAARL Topography-Vicksburg National Military Park 2007: First Surface

USGS Publications Warehouse

Nayegandhi, Amar; Brock, John C.; Wright, C. Wayne; Segura, Martha; Yates, Xan

2009-01-01

These remotely sensed, geographically referenced elevation measurements of Lidar-derived first-surface (FS) topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL; the National Park Service (NPS), Gulf Coast Network, Lafayette, LA; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of the Vicksburg National Military Park in Mississippi, acquired on September 12, 2007. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative airborne Lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) Lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive Lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for submeter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a Lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for presurvey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or first surface topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.

EAARL Coastal Topography - Sandy Hook 2007

USGS Publications Warehouse

Nayegandhi, Amar; Brock, John C.; Wright, C. Wayne; Stevens, Sara; Yates, Xan; Bonisteel, Jamie M.

2008-01-01

These remotely sensed, geographically referenced elevation measurements of Lidar-derived topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL; the National Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of Gateway National Recreation Area's Sandy Hook Unit in New Jersey, acquired on May 16, 2007. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative airborne Lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL) was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) Lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive Lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers and an integrated miniature digital inertial measurement unit, which provide for submeter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a Lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for pre-survey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is routinely used to create maps that represent submerged or first surface topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.

Accuracy of five intraoral scanners compared to indirect digitalization.

PubMed

Güth, Jan-Frederik; Runkel, Cornelius; Beuer, Florian; Stimmelmayr, Michael; Edelhoff, Daniel; Keul, Christine

2017-06-01

Direct and indirect digitalization offer two options for computer-aided design (CAD)/ computer-aided manufacturing (CAM)-generated restorations. The aim of this study was to evaluate the accuracy of different intraoral scanners and compare them to the process of indirect digitalization. A titanium testing model was directly digitized 12 times with each intraoral scanner: (1) CS 3500 (CS), (2) Zfx Intrascan (ZFX), (3) CEREC AC Bluecam (BLU), (4) CEREC AC Omnicam (OC) and (5) True Definition (TD). As control, 12 polyether impressions were taken and the referring plaster casts were digitized indirectly with the D-810 laboratory scanner (CON). The accuracy (trueness/precision) of the datasets was evaluated by an analysing software (Geomagic Qualify 12.1) using a "best fit alignment" of the datasets with a highly accurate reference dataset of the testing model, received from industrial computed tomography. Direct digitalization using the TD showed the significant highest overall "trueness", followed by CS. Both performed better than CON. BLU, ZFX and OC showed higher differences from the reference dataset than CON. Regarding the overall "precision", the CS 3500 intraoral scanner and the True Definition showed the best performance. CON, BLU and OC resulted in significantly higher precision than ZFX did. Within the limitations of this in vitro study, the accuracy of the ascertained datasets was dependent on the scanning system. The direct digitalization was not superior to indirect digitalization for all tested systems. Regarding the accuracy, all tested intraoral scanning technologies seem to be able to reproduce a single quadrant within clinical acceptable accuracy. However, differences were detected between the tested systems.

Rockfall hazard analysis using LiDAR and spatial modeling

NASA Astrophysics Data System (ADS)

Lan, Hengxing; Martin, C. Derek; Zhou, Chenghu; Lim, Chang Ho

2010-05-01

Rockfalls have been significant geohazards along the Canadian Class 1 Railways (CN Rail and CP Rail) since their construction in the late 1800s. These rockfalls cause damage to infrastructure, interruption of business, and environmental impacts, and their occurrence varies both spatially and temporally. The proactive management of these rockfall hazards requires enabling technologies. This paper discusses a hazard assessment strategy for rockfalls along a section of a Canadian railway using LiDAR and spatial modeling. LiDAR provides accurate topographical information of the source area of rockfalls and along their paths. Spatial modeling was conducted using Rockfall Analyst, a three dimensional extension to GIS, to determine the characteristics of the rockfalls in terms of travel distance, velocity and energy. Historical rockfall records were used to calibrate the physical characteristics of the rockfall processes. The results based on a high-resolution digital elevation model from a LiDAR dataset were compared with those based on a coarse digital elevation model. A comprehensive methodology for rockfall hazard assessment is proposed which takes into account the characteristics of source areas, the physical processes of rockfalls and the spatial attribution of their frequency and energy.

Spatial Resolution Effects of Digital Terrain Models on Landslide Susceptibility Analysis

NASA Astrophysics Data System (ADS)

Chang, K. T.; Dou, J.; Chang, Y.; Kuo, C. P.; Xu, K. M.; Liu, J. K.

2016-06-01

The purposes of this study are to identify the maximum number of correlated factors for landslide susceptibility mapping and to evaluate landslide susceptibility at Sihjhong river catchment in the southern Taiwan, integrating two techniques, namely certainty factor (CF) and artificial neural network (ANN). The landslide inventory data of the Central Geological Survey (CGS, MOEA) in 2004-2014 and two digital elevation model (DEM) datasets including a 5-meter LiDAR DEM and a 30-meter Aster DEM were prepared. We collected thirteen possible landslide-conditioning factors. Considering the multi-collinearity and factor redundancy, we applied the CF approach to optimize these thirteen conditioning factors. We hypothesize that if the CF values of the thematic factor layers are positive, it implies that these conditioning factors have a positive relationship with the landslide occurrence. Therefore, based on this assumption and positive CF values, seven conditioning factors including slope angle, slope aspect, elevation, terrain roughness index (TRI), terrain position index (TPI), total curvature, and lithology have been selected for further analysis. The results showed that the optimized-factors model provides a better accuracy for predicting landslide susceptibility in the study area. In conclusion, the optimized-factors model is suggested for selecting relative factors of landslide occurrence.

The Need for Careful Data Collection for Pattern Recognition in Digital Pathology.

PubMed

Marée, Raphaël

2017-01-01

Effective pattern recognition requires carefully designed ground-truth datasets. In this technical note, we first summarize potential data collection issues in digital pathology and then propose guidelines to build more realistic ground-truth datasets and to control their quality. We hope our comments will foster the effective application of pattern recognition approaches in digital pathology.

Assessment of Photogrammetry Structure-from-Motion Compared to Terrestrial LiDAR Scanning for Generating Digital Elevation Models. Application to the Austre Lovéenbreen Polar Glacier Basin, Spitsbergen 79°N

NASA Astrophysics Data System (ADS)

Tolle, F.; Friedt, J. M.; Bernard, É.; Prokop, A.; Griselin, M.

2014-12-01

Digital Elevation Model (DEM) is a key tool for analyzing spatially dependent processes including snow accumulation on slopes or glacier mass balance. Acquiring DEM within short time intervals provides new opportunities to evaluate such phenomena at the daily to seasonal rates.DEMs are usually generated from satellite imagery, aerial photography, airborne and ground-based LiDAR, and GPS surveys. In addition to these classical methods, we consider another alternative for periodic DEM acquisition with lower logistics requirements: digital processing of ground based, oblique view digital photography. Such a dataset, acquired using commercial off the shelf cameras, provides the source for generating elevation models using Structure from Motion (SfM) algorithms. Sets of pictures of a same structure but taken from various points of view are acquired. Selected features are identified on the images and allow for the reconstruction of the three-dimensional (3D) point cloud after computing the camera positions and optical properties. This cloud point, generated in an arbitrary coordinate system, is converted to an absolute coordinate system either by adding constraints of Ground Control Points (GCP), or including the (GPS) position of the cameras in the processing chain. We selected the opensource digital signal processing library provided by the French Geographic Institute (IGN) called Micmac for its fine processing granularity and the ability to assess the quality of each processing step.Although operating in snow covered environments appears challenging due to the lack of relevant features, we observed that enough reference points could be identified for 3D reconstruction. Despite poor climatic environment of the Arctic region considered (Ny Alesund area, 79oN) is not a problem for SfM, the low lying spring sun and the cast shadows appear as a limitation because of the lack of color dynamics in the digital cameras we used. A detailed understanding of the processing steps is mandatory during the image acquisition phase: compliance with acquisition rules reducing digital processing errors helps minimizing the uncertainty on the point cloud absolute position in its coordinate system. 3D models from SfM are compared with terrestrial LiDAR acquisitions for resolution assesment.

Using LiDAR datasets to improve HSPF water quality modeling in the Red River of the North Basin

NASA Astrophysics Data System (ADS)

Burke, M. P.; Foreman, C. S.

2013-12-01

The Red River of the North Basin (RRB), located in the lakebed of ancient glacial Lake Agassiz, comprises one of the flattest landscapes in North America. The topography of the basin, coupled with the Red River's direction of flow from south to north results in a system that is highly susceptible to flooding. The magnitude and frequency of flood events in the RRB has prompted several multijurisdictional projects and mitigation efforts. In response to the devastating 1997 flood, an International Joint Commission sponsored task force established the need for accurate elevation data to help improve flood forecasting and better understand risks. This led to the International Water Institute's Red River Basin Mapping Initiative, and the acquisition LiDAR Data for the entire US portion of the RRB. The resulting 1 meter bare earth digital elevation models have been used to improve hydraulic and hydrologic modeling within the RRB, with focus on flood prediction and mitigation. More recently, these LiDAR datasets have been incorporated into Hydrological Simulation Program-FORTRAN (HSPF) model applications to improve water quality predictions in the MN portion of the RRB. RESPEC is currently building HSPF model applications for five of MN's 8-digit HUC watersheds draining to the Red River, including: the Red Lake River, Clearwater River, Sandhill River, Two Rivers, and Tamarac River watersheds. This work is being conducted for the Minnesota Pollution Control Agency (MPCA) as part of MN's statewide watershed approach to restoring and protecting water. The HSPF model applications simulate hydrology (discharge, stage), as well as a number of water quality constituents (sediment, temperature, organic and inorganic nitrogen, total ammonia, organic and inorganic phosphorus, dissolved oxygen and biochemical oxygen demand, and algae) continuously for the period 1995-2009 and are formulated to provide predictions at points of interest within the watersheds, such as observation gages, management boundaries, compliance points, and impaired water body endpoints. Incorporation of the LiDAR datasets has been critical to representing the topographic characteristics that impact hydrologic and water quality processes in the extremely flat, heavily drained sub-basins of the RRB. Beyond providing more detailed elevation and slope measurements, the high resolution LiDAR datasets have helped to identify drainage alterations due to agricultural practices, as well as improve representation of channel geometry. Additionally, when available, LiDAR based hydraulic models completed as part of the RRB flood mitigation efforts, are incorporated to further improve flow routing. The MPCA will ultimately use these HSPF models to aid in Total Maximum Daily Load (TMDL) development, permit development/compliance, analysis of Best Management Practice (BMP) implementation scenarios, and other watershed planning and management objectives. LiDAR datasets are an essential component of the water quality models build for the watersheds within the RRB and would greatly benefit water quality modeling efforts in similarly characterized areas.

Development of Global 30m Resolution Water Body Map with Permanent/Temporal Water Body Separation Using Satellite Acquired Images of Landsat GLS Datasets

NASA Astrophysics Data System (ADS)

Ikeshima, D.; Yamazaki, D.; Yoshikawa, S.; Kanae, S.

2015-12-01

The specification of worldwide water body distribution is important for discovering hydrological cycle. Global 3-second Water Body Map (G3WBM) is a global scale map, which indicates the distribution of water body in 90m resolutions (http://hydro.iis.u-tokyo.ac.jp/~yamadai/G3WBM/index.html). This dataset was mainly built to identify the width of river channels, which is one of major uncertainties of continental-scale river hydrodynamics models. To survey the true width of the river channel, this water body map distinguish Permanent Water Body from Temporary Water Body, which means separating river channel and flood plain. However, rivers with narrower width, which is a major case in usual river, could not be observed in this map. To overcome this problem, updating the algorithm of G3WBM and enhancing the resolutions to 30m is the goal of this research. Although this 30m-resolution water body map uses similar algorithm as G3WBM, there are many technical issues attributed to relatively high resolutions. Those are such as lack of same high-resolution digital elevation map, or contamination problem of sub-pixel scale object on satellite acquired image, or invisibility of well-vegetated water body such as swamp. To manage those issues, this research used more than 30,000 satellite images of Landsat Global Land Survey (GLS), and lately distributed topography data of Shuttle Rader Topography Mission (SRTM) 1 arc-second (30m) digital elevation map. Also the effect of aerosol, which would scatter the sun reflectance and disturb the acquired result image, was considered. Due to these revises, the global water body distribution was established in more precise resolution.

Online Farsi digit recognition using their upper half structure

NASA Astrophysics Data System (ADS)

Ghods, Vahid; Sohrabi, Mohammad Karim

2015-03-01

In this paper, we investigated the efficiency of upper half Farsi numerical digit structure. In other words, half of data (upper half of the digit shapes) was exploited for the recognition of Farsi numerical digits. This method can be used for both offline and online recognition. Half of data is more effective in speed process, data transfer and in this application accuracy. Hidden Markov model (HMM) was used to classify online Farsi digits. Evaluation was performed by TMU dataset. This dataset contains more than 1200 samples of online handwritten Farsi digits. The proposed method yielded more accuracy in recognition rate.

State of Florida 1:24,000- and 1:100,000-scale quadrangle index map - Highlighting low-lying areas derived from USGS Digital Elevation Models

USGS Publications Warehouse

Kosovich, John J.

2008-01-01

In support of U.S. Geological Survey (USGS) disaster preparedness efforts, this map depicts 1:24,000- and 1:100,000-scale quadrangle footprints over a color shaded relief representation of the State of Florida. The first 30 feet of relief above mean sea level are displayed as brightly colored 5-foot elevation bands, which highlight low-elevation areas at a coarse spatial resolution. Standard USGS National Elevation Dataset (NED) 1 arc-second (nominally 30-meter) digital elevation model (DEM) data are the basis for the map, which is designed to be used at a broad scale and for informational purposes only. The NED source data for this map consists of a mixture of 30-meter- and 10-meter-resolution DEMs. The NED data were derived from the original 1:24,000-scale USGS topographic map bare-earth contours, which were converted into gridded quadrangle-based DEM tiles at a constant post spacing (grid cell size) of either 30 meters (data before the mid-1990s) or 10 meters (mid-1990s and later data). These individual-quadrangle DEMs were then converted to spherical coordinates (latitude/longitude decimal degrees) and edge-matched to ensure seamlessness. Figure 1 shows a similar representation for the entire U.S. Gulf Coast, using coarsened 30-meter NED data. Areas below sea level typically are surrounded by levees or some other type of flood-control structures. State and county boundary, hydrography, city, and road layers were modified from USGS National Atlas data downloaded in 2003. Quadrangle names, dated April, 2006, were obtained from the Federal Geographic Names Information System. The NED data were downloaded in 2004.

Modelling vertical error in LiDAR-derived digital elevation models

NASA Astrophysics Data System (ADS)

Aguilar, Fernando J.; Mills, Jon P.; Delgado, Jorge; Aguilar, Manuel A.; Negreiros, J. G.; Pérez, José L.

2010-01-01

A hybrid theoretical-empirical model has been developed for modelling the error in LiDAR-derived digital elevation models (DEMs) of non-open terrain. The theoretical component seeks to model the propagation of the sample data error (SDE), i.e. the error from light detection and ranging (LiDAR) data capture of ground sampled points in open terrain, towards interpolated points. The interpolation methods used for infilling gaps may produce a non-negligible error that is referred to as gridding error. In this case, interpolation is performed using an inverse distance weighting (IDW) method with the local support of the five closest neighbours, although it would be possible to utilize other interpolation methods. The empirical component refers to what is known as "information loss". This is the error purely due to modelling the continuous terrain surface from only a discrete number of points plus the error arising from the interpolation process. The SDE must be previously calculated from a suitable number of check points located in open terrain and assumes that the LiDAR point density was sufficiently high to neglect the gridding error. For model calibration, data for 29 study sites, 200×200 m in size, belonging to different areas around Almeria province, south-east Spain, were acquired by means of stereo photogrammetric methods. The developed methodology was validated against two different LiDAR datasets. The first dataset used was an Ordnance Survey (OS) LiDAR survey carried out over a region of Bristol in the UK. The second dataset was an area located at Gador mountain range, south of Almería province, Spain. Both terrain slope and sampling density were incorporated in the empirical component through the calibration phase, resulting in a very good agreement between predicted and observed data (R2 = 0.9856 ; p < 0.001). In validation, Bristol observed vertical errors, corresponding to different LiDAR point densities, offered a reasonably good fit to the predicted errors. Even better results were achieved in the more rugged morphology of the Gador mountain range dataset. The findings presented in this article could be used as a guide for the selection of appropriate operational parameters (essentially point density in order to optimize survey cost), in projects related to LiDAR survey in non-open terrain, for instance those projects dealing with forestry applications.

Southern Alaska Coastal Relief Model

NASA Astrophysics Data System (ADS)

Lim, E.; Eakins, B.; Wigley, R.

2009-12-01

The National Geophysical Data Center (NGDC), an office of the National Oceanic and Atmospheric Administration (NOAA), in conjunction with the Cooperative Institute for Research in Environmental Sciences (CIRES) at the University of Colorado at Boulder, has developed a 24 arc-second integrated bathymetric-topographic digital elevation model of Southern Alaska. This Coastal Relief Model (CRM) was generated from diverse digital datasets that were obtained from NGDC, the United States Geological Survey, and other U.S. and international agencies. The CRM spans 170° to 230° E and 48.5° to 66.5° N, including the Gulf of Alaska, Bering Sea, Aleutian Islands, and Alaska’s largest communities: Anchorage, Fairbanks, and Juneau. The CRM provides a framework for enabling scientists to refine tsunami propagation and ocean circulation modeling through increased resolution of geomorphologic features. It may also be useful for benthic habitat research, weather forecasting, and environmental stewardship. Shaded-relief image of the Southern Alaska Coastal Relief Model.

Creation of digital contours that approach the characteristics of cartographic contours

USGS Publications Warehouse

Tyler, Dean J.; Greenlee, Susan K.

2012-01-01

The capability to easily create digital contours using commercial off-the-shelf (COTS) software has existed for decades. Out-of-the-box raw contours are suitable for many scientific applications without pre- or post-processing; however, cartographic applications typically require additional improvements. For example, raw contours generally require smoothing before placement on a map. Cartographic contours must also conform to certain spatial/logical rules; for example, contours may not cross waterbodies. The objective was to create contours that match as closely as possible the cartographic contours produced by manual methods on the 1:24,000-scale, 7.5-minute Topographic Map series. This report outlines the basic approach, describes a variety of problems that were encountered, and discusses solutions. Many of the challenges described herein were the result of imperfect input raster elevation data and the requirement to have the contours integrated with hydrographic features from the National Hydrography Dataset (NHD).

Digital elevations and extents of regional hydrogeologic units in the Northern Atlantic Coastal Plain aquifer system from Long Island, New York, to North Carolina

USGS Publications Warehouse

Pope, Jason P.; Andreasen, David C.; Mcfarland, E. Randolph; Watt, Martha K.

2016-08-31

Digital geospatial datasets of the extents and top elevations of the regional hydrogeologic units of the Northern Atlantic Coastal Plain aquifer system from Long Island, New York, to northeastern North Carolina were developed to provide an updated hydrogeologic framework to support analysis of groundwater resources. The 19 regional hydrogeologic units were delineated by elevation grids and extent polygons for 20 layers: the land and bathymetric surface at the top of the unconfined surficial aquifer, the upper surfaces of 9 confined aquifers and 9 confining units, and the bedrock surface that defines the base of all Northern Atlantic Coastal Plain sediments. The delineation of the regional hydrogeologic units relied on the interpretive work from source reports for New York, New Jersey, Delaware and Maryland, Virginia, and North Carolina rather than from re-analysis of fundamental hydrogeologic data. This model of regional hydrogeologic unit geometries represents interpolation, extrapolation, and generalization of the earlier interpretive work. Regional units were constructed from available digital data layers from the source studies in order to extend units consistently across political boundaries and approximate units in offshore areas.Though many of the Northern Atlantic Coastal Plain hydrogeologic units may extend eastward as far as the edge of the Atlantic Continental Shelf, the modeled boundaries of all regional hydrogeologic units in this study were clipped to an area approximately defined by the furthest offshore extent of fresh to brackish water in any part of the aquifer system, as indicated by chloride concentrations of 10,000 milligrams per liter. Elevations and extents of units that do not exist onshore in Long Island, New York, were not included north of New Jersey. Hydrogeologic units in North Carolina were included primarily to provide continuity across the Virginia-North Carolina State boundary, which was important for defining the southern edge of the Northern Atlantic Coastal Plain study area.

Attributes for NHDPlus Catchments (Version 1.1): Basin Characteristics, 2002

USGS Publications Warehouse

Wieczorek, Michael; LaMotte, Andrew E.

2010-01-01

This data set represents basin characteristics, compiled for every catchment in NHDPlus for the conterminous United States. These characteristics are basin shape index, stream density, sinuosity, mean elevation, mean slope, and number of road-stream crossings. The source data sets are the U.S. Environmental Protection Agency's NHDPlus and the U.S. Census Bureau's TIGER/Line Files. The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

Eastern Denali Fault surface trace map, eastern Alaska and Yukon, Canada

USGS Publications Warehouse

Bender, Adrian M.; Haeussler, Peter J.

2017-05-04

We map the 385-kilometer (km) long surface trace of the right-lateral, strike-slip Denali Fault between the Totschunda-Denali Fault intersection in Alaska, United States and the village of Haines Junction, Yukon, Canada. In Alaska, digital elevation models based on light detection and ranging and interferometric synthetic aperture radar data enabled our fault mapping at scales of 1:2,000 and 1:10,000, respectively. Lacking such resources in Yukon, we developed new structure-from-motion digital photogrammetry products from legacy aerial photos to map the fault surface trace at a scale of 1:10,000 east of the international border. The section of the fault that we map, referred to as the Eastern Denali Fault, did not rupture during the 2002 Denali Fault earthquake (moment magnitude 7.9). Seismologic, geodetic, and geomorphic evidence, along with a paleoseismic record of past ground-rupturing earthquakes, demonstrate Holocene and contemporary activity on the fault, however. This map of the Eastern Denali Fault surface trace complements other data sets by providing an openly accessible digital interpretation of the location, length, and continuity of the fault’s surface trace based on the accompanying digital topography dataset. Additionally, the digitized fault trace may provide geometric constraints useful for modeling earthquake scenarios and related seismic hazard.

Generation of High Resolution Global DSM from ALOS PRISM

NASA Astrophysics Data System (ADS)

Takaku, J.; Tadono, T.; Tsutsui, K.

2014-04-01

Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM), one of onboard sensors carried on the Advanced Land Observing Satellite (ALOS), was designed to generate worldwide topographic data with its optical stereoscopic observation. The sensor consists of three independent panchromatic radiometers for viewing forward, nadir, and backward in 2.5 m ground resolution producing a triplet stereoscopic image along its track. The sensor had observed huge amount of stereo images all over the world during the mission life of the satellite from 2006 through 2011. We have semi-automatically processed Digital Surface Model (DSM) data with the image archives in some limited areas. The height accuracy of the dataset was estimated at less than 5 m (rms) from the evaluation with ground control points (GCPs) or reference DSMs derived from the Light Detection and Ranging (LiDAR). Then, we decided to process the global DSM datasets from all available archives of PRISM stereo images by the end of March 2016. This paper briefly reports on the latest processing algorithms for the global DSM datasets as well as their preliminary results on some test sites. The accuracies and error characteristics of datasets are analyzed and discussed on various fields by the comparison with existing global datasets such as Ice, Cloud, and land Elevation Satellite (ICESat) data and Shuttle Radar Topography Mission (SRTM) data, as well as the GCPs and the reference airborne LiDAR/DSM.

GLOBATO: An enhanced global relief model at 30 arc-seconds resolution

NASA Astrophysics Data System (ADS)

O'Leary, V.; Amante, C.

2017-12-01

The National Centers for Environmental Information (NCEI), an office of the National Oceanic and Atmospheric Administration (NOAA), first developed a digital bathymetric and elevation model, ETOPO5, from publicly available data in 1993. For nearly 25 years, NCEI's ETOPO family of global relief models have supported research at a planetary scale, including tsunami forecasting, ocean circulation modeling, visualization of the seafloor, understanding geological phenomena, and aiding the development of other global and regional elevation models. GLOBATO (GLObal BAThymetry and TOpography) is now the most detailed version released by NCEI with a horizontal resolution of 30 arc-seconds and succeeds ETOPO1 with the inclusion of several new or updated data-sets for the seafloor as well as land areas. GLOBATO is a compilation of data derived from models of satellite measurements, ship depth soundings, and multibeam surveys, as well as regional models developed for Greenland and Antarctica. These data were converted from different formats, resolutions, spatial distributions, and projections into a single global model using GDAL v2.2 and MB-System v5.5. As with previous NCEI models, GLOBATO is available in two formats, "bedrock elevation" (measured as the base of major ice sheets) and "ice surface elevation" (measured as the surface of major ice sheets) which provides comprehensive topographic and bathymetric coverage between +- 90 degrees latitude and +- 180 degrees longitude. Adhering to best practices, GLOBATO, all related digital products, and any supporting documentation are available online through the NCEI data portal. These new, high resolution models will better support the variety of research ETOPO1 has made possible.

Validation of the ASTER Global Digital Elevation Model Version 2 over the conterminous United States

USGS Publications Warehouse

Gesch, Dean B.; Oimoen, Michael J.; Zhang, Zheng; Meyer, David J.; Danielson, Jeffrey J.

2012-01-01

The ASTER Global Digital Elevation Model Version 2 (GDEM v2) was evaluated over the conterminous United States in a manner similar to the validation conducted for the original GDEM Version 1 (v1) in 2009. The absolute vertical accuracy of GDEM v2 was calculated by comparison with more than 18,000 independent reference geodetic ground control points from the National Geodetic Survey. The root mean square error (RMSE) measured for GDEM v2 is 8.68 meters. This compares with the RMSE of 9.34 meters for GDEM v1. Another important descriptor of vertical accuracy is the mean error, or bias, which indicates if a DEM has an overall vertical offset from true ground level. The GDEM v2 mean error of -0.20 meters is a significant improvement over the GDEM v1 mean error of -3.69 meters. The absolute vertical accuracy assessment results, both mean error and RMSE, were segmented by land cover to examine the effects of cover types on measured errors. The GDEM v2 mean errors by land cover class verify that the presence of aboveground features (tree canopies and built structures) cause a positive elevation bias, as would be expected for an imaging system like ASTER. In open ground classes (little or no vegetation with significant aboveground height), GDEM v2 exhibits a negative bias on the order of 1 meter. GDEM v2 was also evaluated by differencing with the Shuttle Radar Topography Mission (SRTM) dataset. In many forested areas, GDEM v2 has elevations that are higher in the canopy than SRTM.

Brokering technologies to realize the hydrology scenario in NSF BCube

NASA Astrophysics Data System (ADS)

Boldrini, Enrico; Easton, Zachary; Fuka, Daniel; Pearlman, Jay; Nativi, Stefano

2015-04-01

In the National Science Foundation (NSF) BCube project an international team composed of cyber infrastructure experts, geoscientists, social scientists and educators are working together to explore the use of brokering technologies, initially focusing on four domains: hydrology, oceans, polar, and weather. In the hydrology domain, environmental models are fundamental to understand the behaviour of hydrological systems. A specific model usually requires datasets coming from different disciplines for its initialization (e.g. elevation models from Earth observation, weather data from Atmospheric sciences, etc.). Scientific datasets are usually available on heterogeneous publishing services, such as inventory and access services (e.g. OGC Web Coverage Service, THREDDS Data Server, etc.). Indeed, datasets are published according to different protocols, moreover they usually come in different formats, resolutions, Coordinate Reference Systems (CRSs): in short different grid environments depending on the original data and the publishing service processing capabilities. Scientists can thus be impeded by the burden of discovery, access and normalize the desired datasets to the grid environment required by the model. These technological tasks of course divert scientists from their main, scientific goals. The use of GI-axe brokering framework has been experimented in a hydrology scenario where scientists needed to compare a particular hydrological model with two different input datasets (digital elevation models): - the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) dataset, v.2. - the Shuttle Radar Topography Mission (SRTM) dataset, v.3. These datasets were published by means of Hyrax Server technology, which can provide NetCDF files at their original resolution and CRS. Scientists had their model running on ArcGIS, so the main goal was to import the datasets using the available ArcPy library and have EPSG:4326 with the same resolution grid as the reference system, so that model outputs could be compared. ArcPy however is able to access only GeoTIff datasets that are published by a OGC Web Coverage Service (WCS). The GI-axe broker has then been deployed between the client application and the data providers. It has been configured to broker the two different Hyrax service endpoints and republish the data content through a WCS interface for the use of the ArcPy library. Finally, scientists were able to easily run the model, and to concentrate on the comparison of the different results obtained according to the selected input dataset. The use of a third party broker to perform such technological tasks has also shown to have the potential advantage of increasing the repeatability of a study among different researchers.

A comparison of U.S. geological survey seamless elevation models with shuttle radar topography mission data

USGS Publications Warehouse

Gesch, D.; Williams, J.; Miller, W.

2001-01-01

Elevation models produced from Shuttle Radar Topography Mission (SRTM) data will be the most comprehensive, consistently processed, highest resolution topographic dataset ever produced for the Earth's land surface. Many applications that currently use elevation data will benefit from the increased availability of data with higher accuracy, quality, and resolution, especially in poorly mapped areas of the globe. SRTM data will be produced as seamless data, thereby avoiding many of the problems inherent in existing multi-source topographic databases. Serving as precursors to SRTM datasets, the U.S. Geological Survey (USGS) has produced and is distributing seamless elevation datasets that facilitate scientific use of elevation data over large areas. GTOPO30 is a global elevation model with a 30 arc-second resolution (approximately 1-kilometer). The National Elevation Dataset (NED) covers the United States at a resolution of 1 arc-second (approximately 30-meters). Due to their seamless format and broad area coverage, both GTOPO30 and NED represent an advance in the usability of elevation data, but each still includes artifacts from the highly variable source data used to produce them. The consistent source data and processing approach for SRTM data will result in elevation products that will be a significant addition to the current availability of seamless datasets, specifically for many areas outside the U.S. One application that demonstrates some advantages that may be realized with SRTM data is delineation of land surface drainage features (watersheds and stream channels). Seamless distribution of elevation data in which a user interactively specifies the area of interest and order parameters via a map server is already being successfully demonstrated with existing USGS datasets. Such an approach for distributing SRTM data is ideal for a dataset that undoubtedly will be of very high interest to the spatial data user community.

Digital Geospatial Datasets in Support of Hydrologic Investigations of the Colorado Front Range Infrastructure Resources Project

USGS Publications Warehouse

Rafferty, Sharon A.; Arnold, L.R.; Char, Stephen J.

2002-01-01

The U.S. Geological Survey developed this dataset as part of the Colorado Front Range Infrastructure Resources Project (FRIRP). One goal of the FRIRP was to provide information on the availability of those hydrogeologic resources that are either critical to maintaining infrastructure along the northern Front Range or that may become less available because of urban expansion in the northern Front Range. This dataset extends from the Boulder-Jefferson County line on the south, to the middle of Larimer and Weld Counties on the North. On the west, this dataset is bounded by the approximate mountain front of the Front Range of the Rocky Mountains; on the east, by an arbitrary north-south line extending through a point about 6.5 kilometers east of Greeley. This digital geospatial dataset consists of digitized contours of unconsolidated-sediment thickness (depth to bedrock).

Rapid, low-cost photogrammetry to monitor volcanic eruptions: an example from Mount St. Helens, Washington, USA

USGS Publications Warehouse

Diefenbach, Angela K.; Crider, Juliet G.; Schilling, Steve P.; Dzurisin, Daniel

2012-01-01

We describe a low-cost application of digital photogrammetry using commercially available photogrammetric software and oblique photographs taken with an off-the-shelf digital camera to create sequential digital elevation models (DEMs) of a lava dome that grew during the 2004–2008 eruption of Mount St. Helens (MSH) volcano. Renewed activity at MSH provided an opportunity to devise and test this method, because it could be validated against other observations of this well-monitored volcano. The datasets consist of oblique aerial photographs (snapshots) taken from a helicopter using a digital single-lens reflex camera. Twelve sets of overlapping digital images of the dome taken during 2004–2007 were used to produce DEMs and to calculate lava dome volumes and extrusion rates. Analyses of the digital images were carried out using photogrammetric software to produce three-dimensional coordinates of points identified in multiple photos. The evolving morphology of the dome was modeled by comparing successive DEMs. Results were validated by comparison to volume measurements derived from traditional vertical photogrammetric surveys by the US Geological Survey Cascades Volcano Observatory. Our technique was significantly less expensive and required less time than traditional vertical photogrammetric techniques; yet, it consistently yielded volume estimates within 5% of the traditional method. This technique provides an inexpensive, rapid assessment tool for tracking lava dome growth or other topographic changes at restless volcanoes.

Soil organic carbon content assessment in a heterogeneous landscape: comparison of digital soil mapping and visible and near Infrared spectroscopy approaches

NASA Astrophysics Data System (ADS)

Michot, Didier; Fouad, Youssef; Pascal, Pichelin; Viaud, Valérie; Soltani, Inès; Walter, Christian

2017-04-01

This study aims are: i) to assess SOC content distribution according to the global soil map (GSM) project recommendations in a heterogeneous landscape ; ii) to compare the prediction performance of digital soil mapping (DSM) and visible-near infrared (Vis-NIR) spectroscopy approaches. The study area of 140 ha, located at Plancoët, surrounds the unique mineral spring water of Brittany (Western France). It's a hillock characterized by a heterogeneous landscape mosaic with different types of forest, permanent pastures and wetlands along a small coastal river. We acquired two independent datasets: j) 50 points selected using a conditioned Latin hypercube sampling (cLHS); jj) 254 points corresponding to the GSM grid. Soil samples were collected in three layers (0-5, 20-25 and 40-50cm) for both sampling strategies. SOC content was only measured in cLHS soil samples, while Vis-NIR spectra were measured on all the collected samples. For the DSM approach, a machine-learning algorithm (Cubist) was applied on the cLHS calibration data to build rule-based models linking soil carbon content in the different layers with environmental covariates, derived from digital elevation model, geological variables, land use data and existing large scale soil maps. For the spectroscopy approach, we used two calibration datasets: k) the local cLHS ; kk) a subset selected from the regional spectral database of Brittany after a PCA with a hierarchical clustering analysis and spiked by local cLHS spectra. The PLS regression algorithm with "leave-one-out" cross validation was performed for both calibration datasets. SOC contents for the 3 layers of the GSM grid were predicted using the different approaches and were compared with each other. Their prediction performance was evaluated by the following parameters: R2, RMSE and RPD. Both approaches led to satisfactory predictions for SOC content with an advantage for the spectral approach, particularly as regards the pertinence of the variation range.

Correction of elevation offsets in multiple co-located lidar datasets

USGS Publications Warehouse

Thompson, David M.; Dalyander, P. Soupy; Long, Joseph W.; Plant, Nathaniel G.

2017-04-07

IntroductionTopographic elevation data collected with airborne light detection and ranging (lidar) can be used to analyze short- and long-term changes to beach and dune systems. Analysis of multiple lidar datasets at Dauphin Island, Alabama, revealed systematic, island-wide elevation differences on the order of 10s of centimeters (cm) that were not attributable to real-world change and, therefore, were likely to represent systematic sampling offsets. These offsets vary between the datasets, but appear spatially consistent within a given survey. This report describes a method that was developed to identify and correct offsets between lidar datasets collected over the same site at different times so that true elevation changes over time, associated with sediment accumulation or erosion, can be analyzed.

National Elevation Dataset

USGS Publications Warehouse

,

1999-01-01

The National Elevation Dataset (NED) is a new raster product assembled by the U.S. Geological Survey (USGS). The NED is designed to provide national elevation data in a seamless form with a consistent datum, elevation unit, and projection. Data corrections were made in the NED assembly process to minimize artifacts, permit edge matching, and fill sliver areas of missing data.

UAV and SfM in Detailed Geomorphological Mapping of Granite Tors: An Example of Starościńskie Skały (Sudetes, SW Poland)

NASA Astrophysics Data System (ADS)

Kasprzak, Marek; Jancewicz, Kacper; Michniewicz, Aleksandra

2017-11-01

The paper presents an example of using photographs taken by unmanned aerial vehicles (UAV) and processed using the structure from motion (SfM) procedure in a geomorphological study of rock relief. Subject to analysis is a small rock city in the West Sudetes (SW Poland), known as Starościńskie Skały and developed in coarse granite bedrock. The aims of this paper were, first, to compare UAV/SfM-derived data with the cartographical image based on the traditional geomorphological field-mapping methods and the digital elevation model derived from airborne laser scanning (ALS). Second, to test if the proposed combination of UAV and SfM methods may be helpful in recognizing the detailed structure of granite tors. As a result of conducted UAV flights and digital image post-processing in AgiSoft software, it was possible to obtain datasets (dense point cloud, texture model, orthophotomap, bare-ground-type digital terrain model—DTM) which allowed to visualize in detail the surface of the study area. In consequence, it was possible to distinguish even the very small forms of rock surface microrelief: joints, aplite veins, rills and karren, weathering pits, etc., otherwise difficult to map and measure. The study includes also valorization of particular datasets concerning microtopography and allows to discuss indisputable advantages of using the UAV/SfM-based DTM in geomorphic studies of tors and rock cities, even those located within forest as in the presented case study.

Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: Physiographic Provinces

USGS Publications Warehouse

Wieczorek, Michael; LaMotte, Andrew E.

2010-01-01

This dataset represents the area of each physiographic province (Fenneman and Johnson, 1946) in square meters, compiled for every catchment of NHDPlus for the conterminous United States. The source data are from Fenneman and Johnson's Physiographic Provinces of the United States, which is based on 8 major divisions, 25 provinces, and 86 sections representing distinctive areas having common topography, rock type and structure, and geologic and geomorphic history (Fenneman and Johnson, 1946). The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

Attributes for NHDPlus catchments (version 1.1) for the conterminous United States: 30-year average annual maximum temperature, 1971-2000

USGS Publications Warehouse

Wieczorek, Michael; LaMotte, Andrew E.

2010-01-01

This data set represents the 30-year (1971-2000) average annual maximum temperature in Celsius multiplied by 100 compiled for every catchment of NHDPlus for the conterminous United States. The source data were the United States Average Monthly or Annual Minimum Temperature, 1971 - 2000 raster dataset produced by the PRISM Group at Oregon State University. The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: Average Annual Daily Minimum Temperature, 2002

USGS Publications Warehouse

Wieczorek, Michael; LaMotte, Andrew E.

2010-01-01

This data set represents the average monthly minimum temperature in Celsius multiplied by 100 for 2002 compiled for every catchment of NHDPlus for the conterminous United States. The source data were the Near-Real-Time High-Resolution Monthly Average Maximum/Minimum Temperature for the Conterminous United States for 2002 raster dataset produced by the Spatial Climate Analysis Service at Oregon State University. The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: 30-Year Average Annual Precipitation, 1971-2000

USGS Publications Warehouse

Wieczorek, Michael; LaMotte, Andrew E.

2010-01-01

This data set represents the 30-year (1971-2000) average annual precipitation in millimeters multiplied by 100 compiled for every catchment of NHDPlus for the conterminous United States. The source data were the "United States Average Monthly or Annual Precipitation, 1971 - 2000" raster dataset produced by the PRISM Group at Oregon State University. The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: 30-Year Average Annual Minimum Temperature, 1971-2000

USGS Publications Warehouse

Wieczorek, Michael; LaMotte, Andrew E.

2010-01-01

This data set represents the 30-year (1971-2000) average annual minimum temperature in Celsius multiplied by 100 compiled for every catchment of NHDPlus for the conterminous United States. The source data were the "United States Average Monthly or Annual Minimum Temperature, 1971 - 2000" raster dataset produced by the PRISM Group at Oregon State University. The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

Attributes for NHDPlus catchments (version 1.1) for the conterminous United States: Average Annual Daily Maximum Temperature, 2002

USGS Publications Warehouse

Wieczorek, Michael; LaMotte, Andrew E.

2010-01-01

This data set represents the average monthly maximum temperature in Celsius multiplied by 100 for 2002 compiled for every catchment of NHDPlus for the conterminous United States. The source data were the Near-Real-Time High-Resolution Monthly Average Maximum/Minimum Temperature for the Conterminous United States for 2002 raster dataset produced by the Spatial Climate Analysis Service at Oregon State University. The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: Average Monthly Precipitation, 2002

USGS Publications Warehouse

Wieczorek, Michael; LaMotte, Andrew E.

2010-01-01

This data set represents the average monthly precipitation in millimeters multiplied by 100 for 2002 compiled for every catchment of NHDPlus for the conterminous United States. The source data were the Near-Real-Time Monthly High-Resolution Precipitation Climate Data Set for the Conterminous United States (2002) raster dataset produced by the Spatial Climate Analysis Service at Oregon State University. The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

Internet-Based Software Tools for Analysis and Processing of LIDAR Point Cloud Data via the OpenTopography Portal

NASA Astrophysics Data System (ADS)

Nandigam, V.; Crosby, C. J.; Baru, C.; Arrowsmith, R.

2009-12-01

LIDAR is an excellent example of the new generation of powerful remote sensing data now available to Earth science researchers. Capable of producing digital elevation models (DEMs) more than an order of magnitude higher resolution than those currently available, LIDAR data allows earth scientists to study the processes that contribute to landscape evolution at resolutions not previously possible, yet essential for their appropriate representation. Along with these high-resolution datasets comes an increase in the volume and complexity of data that the user must efficiently manage and process in order for it to be scientifically useful. Although there are expensive commercial LIDAR software applications available, processing and analysis of these datasets are typically computationally inefficient on the conventional hardware and software that is currently available to most of the Earth science community. We have designed and implemented an Internet-based system, the OpenTopography Portal, that provides integrated access to high-resolution LIDAR data as well as web-based tools for processing of these datasets. By using remote data storage and high performance compute resources, the OpenTopography Portal attempts to simplify data access and standard LIDAR processing tasks for the Earth Science community. The OpenTopography Portal allows users to access massive amounts of raw point cloud LIDAR data as well as a suite of DEM generation tools to enable users to generate custom digital elevation models to best fit their science applications. The Cyberinfrastructure software tools for processing the data are freely available via the portal and conveniently integrated with the data selection in a single user-friendly interface. The ability to run these tools on powerful Cyberinfrastructure resources instead of their own labs provides a huge advantage in terms of performance and compute power. The system also encourages users to explore data processing methods and the variations in algorithm parameters since all of the processing is done remotely and numerous jobs can be submitted in sequence. The web-based software also eliminates the need for users to deal with the hassles and costs associated with software installation and licensing while providing adequate disk space for storage and personal job archival capability. Although currently limited to data access and DEM generation tasks, the OpenTopography system is modular in design and can be modified to accommodate new processing tools as they become available. We are currently exploring implementation of higher-level DEM analysis tasks in OpenTopography, since such processing is often computationally intensive and thus lends itself to utilization of cyberinfrastructure. Products derived from OpenTopography processing are available in a variety of formats ranging from simple Google Earth visualizations of LIDAR-derived hillshades to various GIS-compatible grid formats. To serve community users less interested in data processing, OpenTopography also hosts 1 km^2 digital elevation model tiles as well as Google Earth image overlays for a synoptic view of the data.

EAARL coastal topography--Alligator Point, Louisiana, 2010

USGS Publications Warehouse

Nayegandhi, Amar; Bonisteel-Cormier, J.M.; Wright, C.W.; Brock, J.C.; Nagle, D.B.; Vivekanandan, Saisudha; Fredericks, Xan; Barras, J.A.

2012-01-01

This project provides highly detailed and accurate datasets of a portion of Alligator Point, Louisiana, acquired on March 5 and 6, 2010. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the National Aeronautics and Space Administration (NASA) Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color-infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine aircraft, but the instrument was deployed on a Pilatus PC-6. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the "bare earth" under vegetation from a point cloud of last return elevations.

The Greenwich Photo-heliographic Results (1874 - 1976): Initial Corrections to the Printed Publications

NASA Astrophysics Data System (ADS)

Erwin, E. H.; Coffey, H. E.; Denig, W. F.; Willis, D. M.; Henwood, R.; Wild, M. N.

2013-11-01

A new sunspot and faculae digital dataset for the interval 1874 - 1955 has been prepared under the auspices of the NOAA National Geophysical Data Center (NGDC). This digital dataset contains measurements of the positions and areas of both sunspots and faculae published initially by the Royal Observatory, Greenwich, and subsequently by the Royal Greenwich Observatory (RGO), under the title Greenwich Photo-heliographic Results ( GPR) , 1874 - 1976. Quality control (QC) procedures based on logical consistency have been used to identify the more obvious errors in the RGO publications. Typical examples of identifiable errors are North versus South errors in specifying heliographic latitude, errors in specifying heliographic (Carrington) longitude, errors in the dates and times, errors in sunspot group numbers, arithmetic errors in the summation process, and the occasional omission of solar ephemerides. Although the number of errors in the RGO publications is remarkably small, an initial table of necessary corrections is provided for the interval 1874 - 1917. Moreover, as noted in the preceding companion papers, the existence of two independently prepared digital datasets, which both contain information on sunspot positions and areas, makes it possible to outline a preliminary strategy for the development of an even more accurate digital dataset. Further work is in progress to generate an extremely reliable sunspot digital dataset, based on the long programme of solar observations supported first by the Royal Observatory, Greenwich, and then by the Royal Greenwich Observatory.

Evaluation Digital Elevation Model Generated by Synthetic Aperture Radar Data

NASA Astrophysics Data System (ADS)

Makineci, H. B.; Karabörk, H.

2016-06-01

Digital elevation model, showing the physical and topographical situation of the earth, is defined a tree-dimensional digital model obtained from the elevation of the surface by using of selected an appropriate interpolation method. DEMs are used in many areas such as management of natural resources, engineering and infrastructure projects, disaster and risk analysis, archaeology, security, aviation, forestry, energy, topographic mapping, landslide and flood analysis, Geographic Information Systems (GIS). Digital elevation models, which are the fundamental components of cartography, is calculated by many methods. Digital elevation models can be obtained terrestrial methods or data obtained by digitization of maps by processing the digital platform in general. Today, Digital elevation model data is generated by the processing of stereo optical satellite images, radar images (radargrammetry, interferometry) and lidar data using remote sensing and photogrammetric techniques with the help of improving technology. One of the fundamental components of remote sensing radar technology is very advanced nowadays. In response to this progress it began to be used more frequently in various fields. Determining the shape of topography and creating digital elevation model comes the beginning topics of these areas. It is aimed in this work , the differences of evaluation of quality between Sentinel-1A SAR image ,which is sent by European Space Agency ESA and Interferometry Wide Swath imaging mode and C band type , and DTED-2 (Digital Terrain Elevation Data) and application between them. The application includes RMS static method for detecting precision of data. Results show us to variance of points make a high decrease from mountain area to plane area.

[Scientific significance and prospective application of digitized virtual human].

PubMed

Zhong, Shi-zhen

2003-03-01

As a cutting-edge research project, digitization of human anatomical information combines conventional medicine with information technology, computer technology, and virtual reality technology. Recent years have seen the establishment of, or the ongoing effort to establish various virtual human models in many countries, on the basis of continuous sections of human body that are digitized by means of computational medicine incorporating information technology to quantitatively simulate human physiological and pathological conditions, and to provide wide prospective applications in the fields of medicine and other disciplines. This article addresses 4 issues concerning the progress in virtual human model researches as the following: (1) Worldwide survey of sectioning and modeling of visible human. American visible human database was completed in 1994, which contains both a male and a female datasets, and has found wide application internationally. South Korea also finished the data collection for a male visible Korean human dataset in 2000. (2) Application of the dataset of Visible Human Project (VHP). This dataset has yielded plentiful fruits in medical education and clinical research, and further plans are proposed and practiced to construct a Physical Human and Physiological Human . (3) Scientific significance and prospect of virtual human studies. Digitized human dataset may eventually contribute to the development of many new high-tech industries. (4) Progress of virtual Chinese human project. The 174th session of Xiangshang Science Conferences held in 2001 marked the initiation of digitized virtual human project in China, and some key techniques have been explored. By now the data-collection process for 4 Chinese virtual human datasets have been successfully completed.

Monitoring fluvial erosion of the Oso landslide, Washington, using repeat Structure-from-Motion photogrammetry

NASA Astrophysics Data System (ADS)

Anderson, S. W.; Magirl, C. S.; Keith, M. K.

2015-12-01

On March 22, 2014, the Oso landslide, located in northwestern Washington State, catastrophically mobilized about 8 million m3 of mixed glacial sediment, creating a valley-wide blockage that impounded the North Fork Stillaguamish River to a height of 8 m. The river overtopped the landslide blockage within several days and incised a new channel through predominately fine-grained, cohesive glaciolacustrine sediment in the center of the deposit. Our research focuses on the evolution of this new channel. Using a consumer-grade digital camera mounted on a fixed wing-aircraft, we used structure-from-motion (SfM) photogrammetry to produce 25 cm digital elevation models (DEMs) of the channel at one-month intervals between November 2014 and July 2015. A large RTK GPS validation dataset and inter-survey comparisons documents sub-decimeter vertical and horizontal accuracies. In combination with aerial lidar surveys acquired in March and April 2014, this dataset provides a uniquely resolved look at the erosion of a landslide dam. The newly-formed channel incised rapidly, lowering to within a meter of its pre-slide elevation by May 2014 despite modest flows. During high flows of the 2014-2015 winter flood season, erosion was dominated by channel widening of tens of meters with an overall stable planform. Incision fully returned the channel to pre-slide elevations by December 2014. A total of 510,000 +/- 50,000 m3 of material was eroded between March 2014 and July 2015, split evenly between the initial period of incision and the later period of widening. Sediment yield and channel morphology showed asymptotic trends towards stability. Measurements of deposit bulk density and grain size allowed conversion of volumetric sediment yields to mass yields by size classes. Over the 16 months after the slide, the river eroded about 0.82 +/- 0.1 Mt of sediment, of which 0.78 Mt was finer than 2mm. This yield agrees within 15% of an independent estimate based on concurrent sediment gaging in the reach, and represents about 400% of the background sediment yield over that same period.

ASTER-Derived 30-Meter-Resolution Digital Elevation Models of Afghanistan

USGS Publications Warehouse

Chirico, Peter G.; Warner, Michael B.

2007-01-01

INTRODUCTION The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is an imaging instrument aboard the Terra satellite, launched on December 19, 1999, as part of the National Aeronautics and Space Administration's (NASA) Earth Observing System (EOS). The ASTER sensor consists of three subsystems: the visible and near infrared (VNIR), the shortwave infrared (SWIR), and the thermal infrared (TIR), each with a different spatial resolution (VNIR, 15 meters; SWIR, 30 meters, TIR 90 meters). The VNIR system has the capability to generate along-track stereo images that can be used to create digital elevation models (DEMs) at 30-meter resolution. Currently, the only available DEM dataset for Afghanistan is the 90-meter-resolution Shuttle Radar Topography Mission (SRTM) data. This dataset is appropriate for macroscale DEM analysis and mapping. However, ASTER provides a low cost opportunity to generate higher resolution data. For this publication, study areas were identified around populated areas and areas where higher resolution elevation data were desired to assist in natural resource assessments. The higher resolution fidelity of these DEMs can also be used for other terrain analysis including landform classification and geologic structure analysis. For this publication, ASTER scenes were processed and mosaicked to generate 36 DEMs which were created and extracted using PCI Geomatics' OrthoEngine 3D Stereo software. The ASTER images were geographically registered to Landsat data with at least 15 accurate and well distributed ground control points with a root mean square error (RMSE) of less that one pixel (15 meters). An elevation value was then assigned to each ground control point by extracting the elevation from the 90-meter SRTM data. The 36 derived DEMs demonstrate that the software correlated on nearly flat surfaces and smooth slopes accurately. Larger errors occur in cloudy and snow-covered areas, lakes, areas with steep slopes, and southeastern-facing slopes. In these areas, holes, large pits, and spikes were generated by the software during the correlation process and the automatic interpolation method. To eliminate these problems, overlapping DEMs were generated and filtered using a progressive morphologic filter. The quadrangles used to delineate the DEMs in the publication were derived from the Afghan Geodesy and Cartography Head Office's (AGCHO) 1:100,000-scale maps series quadrangles. Each DEM was clipped and assigned a name according to the associated AGCHO quadrangle name. The geospatial data included in this publication are intended to be used with any GIS software packages including, but not limited to, ESRI's ArcGIS and ERDAS IMAGINE.

A New Lunar Digital Elevation Model from the Lunar Orbiter Laser Altimeter and SELENE Terrain Camera

NASA Technical Reports Server (NTRS)

Barker, M. K.; Mazarico, E.; Neumann, G. A.; Zuber, M. T.; Haruyama, J.; Smith, D. E.

2015-01-01

We present an improved lunar digital elevation model (DEM) covering latitudes within +/-60 deg, at a horizontal resolution of 512 pixels per degree ( approx.60 m at the equator) and a typical vertical accuracy approx.3 to 4 m. This DEM is constructed from approx.4.5 ×10(exp 9) geodetically-accurate topographic heights from the Lunar Orbiter Laser Altimeter (LOLA) onboard the Lunar Reconnaissance Orbiter, to which we co-registered 43,200 stereo-derived DEMs (each 1 deg×1 deg) from the SELENE Terrain Camera (TC) ( approx.10(exp 10) pixels total). After co-registration, approximately 90% of the TC DEMs show root-mean-square vertical residuals with the LOLA data of < 5 m compared to approx.50% prior to co-registration. We use the co-registered TC data to estimate and correct orbital and pointing geolocation errors from the LOLA altimetric profiles (typically amounting to < 10 m horizontally and < 1 m vertically). By combining both co-registered datasets, we obtain a near-global DEM with high geodetic accuracy, and without the need for surface interpolation. We evaluate the resulting LOLA + TC merged DEM (designated as "SLDEM2015") with particular attention to quantifying seams and crossover errors.

A Large-Scale, High-Resolution Hydrological Model Parameter Data Set for Climate Change Impact Assessment for the Conterminous US

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oubeidillah, Abdoul A; Kao, Shih-Chieh; Ashfaq, Moetasim

2014-01-01

To extend geographical coverage, refine spatial resolution, and improve modeling efficiency, a computation- and data-intensive effort was conducted to organize a comprehensive hydrologic dataset with post-calibrated model parameters for hydro-climate impact assessment. Several key inputs for hydrologic simulation including meteorologic forcings, soil, land class, vegetation, and elevation were collected from multiple best-available data sources and organized for 2107 hydrologic subbasins (8-digit hydrologic units, HUC8s) in the conterminous United States at refined 1/24 (~4 km) spatial resolution. Using high-performance computing for intensive model calibration, a high-resolution parameter dataset was prepared for the macro-scale Variable Infiltration Capacity (VIC) hydrologic model. The VICmore » simulation was driven by DAYMET daily meteorological forcing and was calibrated against USGS WaterWatch monthly runoff observations for each HUC8. The results showed that this new parameter dataset may help reasonably simulate runoff at most US HUC8 subbasins. Based on this exhaustive calibration effort, it is now possible to accurately estimate the resources required for further model improvement across the entire conterminous United States. We anticipate that through this hydrologic parameter dataset, the repeated effort of fundamental data processing can be lessened, so that research efforts can emphasize the more challenging task of assessing climate change impacts. The pre-organized model parameter dataset will be provided to interested parties to support further hydro-climate impact assessment.« less

Area and Elevation Changes of a Debris-Covered Glacier and a Clean-Ice Glacier Between 1952-2013 Using Aerial Images and Structure-from-Motion

NASA Astrophysics Data System (ADS)

Lardeux, P.; Glasser, N. F.; Holt, T.; Irvine-Fynn, T. D.; Hubbard, B. P.

2015-12-01

Since 1952, the clean-ice Glacier Blanc has retreated twice as fast as the adjacent debris-covered Glacier Noir. Located in the French Alps and separated by only 1 km, both glaciers experience the same climatic conditions, making them ideal to evaluate the impact of debris cover on glacier evolution. We used aerial photographs from 16 acquisitions from 1952 to 2013 to reconstruct and analyze glacier elevation changes using Structure-from-Motion (SfM) techniques. Here, we present the process of developing sub-metric resolution digital elevation models (DEMs) from these aerial photographs. By combining 16 DEMs, we produced a dataset of elevation changes of Glacier Noir and Glacier Blanc, including time-series analysis of lateral and longitudinal profiles, glacier hypsometry and mass balance variation. Our preliminary results indicate that Glacier Noir and Glacier Blanc have both thinned to a similar magnitude, ≤ 20 m, despite a 1 km retreat for Glacier Blanc and only 500 m for Glacier Noir. However, these elevation change reconstructions are hampered by large uncertainties, principally due to the lack of independent camera calibration on the historical imagery. Initial attempts using posteriori correction grids have proven to significantly increase the accuracy of these data. We will present some of the uncertainties and solutions linked to the use of SfM on such a large scale and on such an old dataset. This study demonstrates how SfM can be used to investigate long-term trends in environmental change, allowing glacier monitoring to be up-scaled. It also highlights the need for on-going validation of methods to increase the accuracy and precision of SfM in glaciology. This work is not only advancing our understanding of the role of the debris layer, but will also aid glacial geology more generally with, for example, detailed geomorphological analysis of proglacial terrain and Quaternary sciences with quick and accurate reconstruction of a glacial paleo-environment.

EAARL Topography - George Washington Birthplace National Monument 2008

USGS Publications Warehouse

Brock, John C.; Nayegandhi, Amar; Wright, C. Wayne; Stevens, Sara; Yates, Xan

2009-01-01

These remotely sensed, geographically referenced elevation measurements of Lidar-derived bare earth (BE) and first surface (FS) topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL; the National Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of the George Washington Birthplace National Monument in Virginia, acquired on March 26, 2008. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative airborne Lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL) was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) Lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive Lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for submeter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a Lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for presurvey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is routinely used to create maps that represent submerged or first surface topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.

EAARL Coastal Topography-Pearl River Delta 2008: Bare Earth

USGS Publications Warehouse

Nayegandhi, Amar; Brock, John C.; Wright, C. Wayne; Miner, Michael D.; Yates, Xan; Bonisteel, Jamie M.

2009-01-01

These remotely sensed, geographically referenced elevation measurements of Lidar-derived bare earth (BE) topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL; the University of New Orleans (UNO), Pontchartrain Institute for Environmental Sciences (PIES), New Orleans, LA; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the Pearl River Delta in Louisiana and Mississippi, acquired March 9-11, 2008. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative airborne Lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) Lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive Lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for submeter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a Lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for presurvey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or first surface topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.

EAARL Coastal Topography-Pearl River Delta 2008: First Surface

USGS Publications Warehouse

Nayegandhi, Amar; Brock, John C.; Wright, C. Wayne; Miner, Michael D.; Michael, D.; Yates, Xan; Bonisteel, Jamie M.

2009-01-01

These remotely sensed, geographically referenced elevation measurements of Lidar-derived first surface (FS) topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL; the University of New Orleans (UNO), Pontchartrain Institute for Environmental Sciences (PIES), New Orleans, LA; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the Pearl River Delta in Louisiana and Mississippi, acquired March 9-11, 2008. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative airborne Lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) Lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive Lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for submeter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a Lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for presurvey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or first surface topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.

EAARL Topography - Jean Lafitte National Historical Park and Preserve 2006

USGS Publications Warehouse

Nayegandhi, Amar; Brock, John C.; Wright, C. Wayne; Segura, Martha; Yates, Xan

2008-01-01

These remotely sensed, geographically referenced elevation measurements of Lidar-derived first surface (FS) and bare earth (BE) topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL; the National Park Service (NPS), Gulf Coast Network, Lafayette, LA; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of the Jean Lafitte National Historical Park and Preserve in Louisiana, acquired on September 22, 2006. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative airborne Lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) Lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive Lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for submeter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a Lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for presurvey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or first surface topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.

EAARL Coastal Topography - Northern Gulf of Mexico, 2007: Bare Earth

USGS Publications Warehouse

Smith, Kathryn E.L.; Nayegandhi, Amar; Wright, C. Wayne; Bonisteel, Jamie M.; Brock, John C.

2009-01-01

These remotely sensed, geographically referenced elevation measurements of Lidar-derived bare earth (BE) topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL; the National Park Service (NPS), Gulf Coast Network, Lafayette, LA; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. The purpose of this project is to provide highly detailed and accurate datasets of select barrier islands and peninsular regions of Louisiana, Mississippi, Alabama, and Florida, acquired on June 27-30, 2007. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative airborne Lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) Lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive Lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit which provide for submeter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a Lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for presurvey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.

EAARL Submerged Topography - U.S. Virgin Islands 2003

USGS Publications Warehouse

Nayegandhi, Amar; Brock, John C.; Wright, C. Wayne; Stevens, Sara; Yates, Xan; Bonisteel, Jamie M.

2008-01-01

These remotely sensed, geographically referenced elevation measurements of Lidar-derived submerged topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL; the National Park Service (NPS), South Florida-Caribbean Network, Miami, FL; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate bathymetric datasets of a portion of the U.S. Virgin Islands, acquired on April 21, 23, and 30, May 2, and June 14 and 17, 2003. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative airborne Lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) Lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive Lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for submeter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a Lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for presurvey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or first surface topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.

EAARL Coastal Topography - Fire Island National Seashore 2007

USGS Publications Warehouse

Nayegandhi, Amar; Brock, John C.; Wright, C. Wayne; Stevens, Sara; Yates, Xan; Bonisteel, Jamie M.

2008-01-01

These remotely sensed, geographically referenced elevation measurements of Lidar-derived first surface (FS) and bare earth (BE) topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL; the National Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of Fire Island National Seashore in New York, acquired on April 29-30 and May 15-16, 2007. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative airborne Lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL) was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) Lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive Lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers and an integrated miniature digital inertial measurement unit, which provide for submeter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a Lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for pre-survey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is routinely used to create maps that represent submerged or first surface topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.

EAARL Coastal Topography-Assateague Island National Seashore, 2008: Bare Earth

USGS Publications Warehouse

Bonisteel, Jamie M.; Nayegandhi, Amar; Brock, John C.; Wright, C. Wayne; Stevens, Sara; Yates, Xan; Klipp, Emily S.

2009-01-01

These remotely sensed, geographically referenced elevation measurements of lidar-derived bare-earth (BE) topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL; the National Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of the Assateague Island National Seashore in Maryland and Virginia, acquired March 24-25, 2008. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL) was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for pre-survey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.

EAARL Coastal Topography-Assateague Island National Seashore, 2008: First Surface

USGS Publications Warehouse

Bonisteel, Jamie M.; Nayegandhi, Amar; Brock, John C.; Wright, C. Wayne; Stevens, Sara; Yates, Xan; Klipp, Emily S.

2009-01-01

These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL; the National Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of the Assateague Island National Seashore in Maryland and Virginia, acquired March 24-25, 2008. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for pre-survey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.

Accuracy of Digital vs. Conventional Implant Impressions

PubMed Central

Lee, Sang J.; Betensky, Rebecca A.; Gianneschi, Grace E.; Gallucci, German O.

2015-01-01

The accuracy of digital impressions greatly influences the clinical viability in implant restorations. The aim of this study is to compare the accuracy of gypsum models acquired from the conventional implant impression to digitally milled models created from direct digitalization by three-dimensional analysis. Thirty gypsum and 30 digitally milled models impressed directly from a reference model were prepared. The models were scanned by a laboratory scanner and 30 STL datasets from each group were imported to an inspection software. The datasets were aligned to the reference dataset by a repeated best fit algorithm and 10 specified contact locations of interest were measured in mean volumetric deviations. The areas were pooled by cusps, fossae, interproximal contacts, horizontal and vertical axes of implant position and angulation. The pooled areas were statistically analysed by comparing each group to the reference model to investigate the mean volumetric deviations accounting for accuracy and standard deviations for precision. Milled models from digital impressions had comparable accuracy to gypsum models from conventional impressions. However, differences in fossae and vertical displacement of the implant position from the gypsum and digitally milled models compared to the reference model, exhibited statistical significance (p<0.001, p=0.020 respectively). PMID:24720423

High-Resolution Forest Canopy Height Estimation in an African Blue Carbon Ecosystem

NASA Technical Reports Server (NTRS)

Lagomasino, David; Fatoyinbo, Temilola; Lee, Seung-Kuk; Simard, Marc

2015-01-01

Mangrove forests are one of the most productive and carbon dense ecosystems that are only found at tidally inundated coastal areas. Forest canopy height is an important measure for modeling carbon and biomass dynamics, as well as land cover change. By taking advantage of the flat terrain and dense canopy cover, the present study derived digital surface models (DSMs) using stereophotogrammetric techniques on high-resolution spaceborne imagery (HRSI) for southern Mozambique. A mean-weighted ground surface elevation factor was subtracted from the HRSI DSM to accurately estimate the canopy height in mangrove forests in southern Mozambique. The mean and H100 tree height measured in both the field and with the digital canopy model provided the most accurate results with a vertical error of 1.18-1.84 m, respectively. Distinct patterns were identified in the HRSI canopy height map that could not be discerned from coarse shuttle radar topography mission canopy maps even though the mode and distribution of canopy heights were similar over the same area. Through further investigation, HRSI DSMs have the potential of providing a new type of three-dimensional dataset that could serve as calibration/validation data for other DSMs generated from spaceborne datasets with much larger global coverage. HSRI DSMs could be used in lieu of Lidar acquisitions for canopy height and forest biomass estimation, and be combined with passive optical data to improve land cover classifications.

Revisiting Frazier's subdeltas: enhancing datasets with dimensionality, better to understand geologic systems

USGS Publications Warehouse

Flocks, James

2006-01-01

Scientific knowledge from the past century is commonly represented by two-dimensional figures and graphs, as presented in manuscripts and maps. Using today's computer technology, this information can be extracted and projected into three- and four-dimensional perspectives. Computer models can be applied to datasets to provide additional insight into complex spatial and temporal systems. This process can be demonstrated by applying digitizing and modeling techniques to valuable information within widely used publications. The seminal paper by D. Frazier, published in 1967, identified 16 separate delta lobes formed by the Mississippi River during the past 6,000 yrs. The paper includes stratigraphic descriptions through geologic cross-sections, and provides distribution and chronologies of the delta lobes. The data from Frazier's publication are extensively referenced in the literature. Additional information can be extracted from the data through computer modeling. Digitizing and geo-rectifying Frazier's geologic cross-sections produce a three-dimensional perspective of the delta lobes. Adding the chronological data included in the report provides the fourth-dimension of the delta cycles, which can be visualized through computer-generated animation. Supplemental information can be added to the model, such as post-abandonment subsidence of the delta-lobe surface. Analyzing the regional, net surface-elevation balance between delta progradations and land subsidence is computationally intensive. By visualizing this process during the past 4,500 yrs through multi-dimensional animation, the importance of sediment compaction in influencing both the shape and direction of subsequent delta progradations becomes apparent. Visualization enhances a classic dataset, and can be further refined using additional data, as well as provide a guide for identifying future areas of study.

Delineation of marsh types and marsh-type change in coastal Louisiana for 2007 and 2013

USGS Publications Warehouse

Hartley, Stephen B.; Couvillion, Brady R.; Enwright, Nicholas M.

2017-05-30

The Bureau of Ocean Energy Management researchers often require detailed information regarding emergent marsh vegetation types (such as fresh, intermediate, brackish, and saline) for modeling habitat capacities and mitigation. In response, the U.S. Geological Survey in cooperation with the Bureau of Ocean Energy Management produced a detailed change classification of emergent marsh vegetation types in coastal Louisiana from 2007 and 2013. This study incorporates two existing vegetation surveys and independent variables such as Landsat Thematic Mapper multispectral satellite imagery, high-resolution airborne imagery from 2007 and 2013, bare-earth digital elevation models based on airborne light detection and ranging, alternative contemporary land-cover classifications, and other spatially explicit variables. An image classification based on image objects was created from 2007 and 2013 National Agriculture Imagery Program color-infrared aerial photography. The final products consisted of two 10-meter raster datasets. Each image object from the 2007 and 2013 spatial datasets was assigned a vegetation classification by using a simple majority filter. In addition to those spatial datasets, we also conducted a change analysis between the datasets to produce a 10-meter change raster product. This analysis identified how much change has taken place and where change has occurred. The spatial data products show dynamic areas where marsh loss is occurring or where marsh type is changing. This information can be used to assist and advance conservation efforts for priority natural resources.

Rescuing biogeographic legacy data: The "Thor" Expedition, a historical oceanographic expedition to the Mediterranean Sea

PubMed Central

Mavraki, Dimitra; Fanini, Lucia; Tsompanou, Marilena; Gerovasileiou, Vasilis; Nikolopoulou, Stamatina; Chatzinikolaou, Eva; Plaitis, Wanda

2016-01-01

Abstract Background This article describes the digitization of a series of historical datasets based οn the reports of the 1908–1910 Danish Oceanographical Expeditions to the Mediterranean and adjacent seas. All station and sampling metadata as well as biodiversity data regarding calcareous rhodophytes, pelagic polychaetes, and fish (families Engraulidae and Clupeidae) obtained during these expeditions were digitized within the activities of the LifeWatchGreece Research Ιnfrastructure project and presented in the present paper. The aim was to safeguard public data availability by using an open access infrastructure, and to prevent potential loss of valuable historical data on the Mediterranean marine biodiversity. New information The datasets digitized here cover 2,043 samples taken at 567 stations during a time period from 1904 to 1930 in the Mediterranean and adjacent seas. The samples resulted in 1,588 occurrence records of pelagic polychaetes, fish (Clupeiformes) and calcareous algae (Rhodophyta). In addition, basic environmental data (e.g. sea surface temperature, salinity) as well as meterological conditions are included for most sampling events. In addition to the description of the digitized datasets, a detailed description of the problems encountered during the digitization of this historical dataset and a discussion on the value of such data are provided. PMID:28174510

3D Analysis of Human Embryos and Fetuses Using Digitized Datasets From the Kyoto Collection.

PubMed

Takakuwa, Tetsuya

2018-06-01

Three-dimensional (3D) analysis of the human embryonic and early-fetal period has been performed using digitized datasets obtained from the Kyoto Collection, in which the digital datasets play a primary role in research. Datasets include magnetic resonance imaging (MRI) acquired with 1.5 T, 2.35 T, and 7 T magnet systems, phase-contrast X-ray computed tomography (CT), and digitized histological serial sections. Large, high-resolution datasets covering a broad range of developmental periods obtained with various methods of acquisition are key elements for the studies. The digital data have gross merits that enabled us to develop various analysis. Digital data analysis accelerated the speed of morphological observations using precise and improved methods by providing a suitable plane for a morphometric analysis from staged human embryos. Morphometric data are useful for quantitatively evaluating and demonstrating the features of development and for screening abnormal samples, which may be suggestive in the pathogenesis of congenital malformations. Morphometric data are also valuable for comparing sonographic data in a process known as "sonoembryology." The 3D coordinates of anatomical landmarks may be useful tools for analyzing the positional change of interesting landmarks and their relationships during development. Several dynamic events could be explained by differential growth using 3D coordinates. Moreover, 3D coordinates can be utilized in mathematical analysis as well as statistical analysis. The 3D analysis in our study may serve to provide accurate morphologic data, including the dynamics of embryonic structures related to developmental stages, which is required for insights into the dynamic and complex processes occurring during organogenesis. Anat Rec, 301:960-969, 2018. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

Attributes for NHDPlus Catchments (Version 1.1) in the Conterminous United States: Artificial Drainage (1992) and Irrigation Types (1997)

USGS Publications Warehouse

Wieczorek, Michael; LaMotte, Andrew E.

2010-01-01

This tabular dataset represents the estimated area of artificial drainage for the year 1992 and irrigation types for the year 1997 compiled for every catchment of NHDPlus for the conterminous United States. The source datasets were derived from tabular National Resource Inventory (NRI) datasets created by the National Resources Conservation Service (NRCS, U.S. Department of Agriculture, 1995, 1997). Artificial drainage is defined as subsurface drains and ditches. Irrigation types are defined as gravity and pressure. Subsurface drains are described as conduits, such as corrugated plastic tubing, tile, or pipe, installed beneath the ground surface to collect and/or convey drainage. Surface drainage field ditches are described as graded ditches for collecting excess water. Gravity irrigation source is described as irrigation delivered to the farm and/or field by canals or pipelines open to the atmosphere; and water is distributed by the force of gravity down the field by: (1) A surface irrigation system (border, basin, furrow, corrugation, wild flooding, etc.) or (2) Sub-surface irrigation pipelines or ditches. Pressure irrigation source is described as irrigation delivered to the farm and/or field in pump or elevation-induced pressure pipelines, and water is distributed across the field by: (1) Sprinkle irrigation (center pivot, linear move, traveling gun, side roll, hand move, big gun, or fixed set sprinklers), or (2) Micro irrigation (drip emitters, continuous tube bubblers, micro spray or micro sprinklers). NRI data do not include Federal lands and are thus excluded from this dataset. The tabular data for drainage were spatially apportioned to the National Land Cover Dataset (NLCD, Kerie Hitt, written commun., 2005) and the tabular data for irrigation were spatially apportioned to an enhanced version of the National Land Cover Dataset (NLCDe, Nakagaki and others 2007) The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geological Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

Improving the discoverability, accessibility, and citability of omics datasets: a case report.

PubMed

Darlington, Yolanda F; Naumov, Alexey; McOwiti, Apollo; Kankanamge, Wasula H; Becnel, Lauren B; McKenna, Neil J

2017-03-01

Although omics datasets represent valuable assets for hypothesis generation, model testing, and data validation, the infrastructure supporting their reuse lacks organization and consistency. Using nuclear receptor signaling transcriptomic datasets as proof of principle, we developed a model to improve the discoverability, accessibility, and citability of published omics datasets. Primary datasets were retrieved from archives, processed to extract data points, then subjected to metadata enrichment and gap filling. The resulting secondary datasets were exposed on responsive web pages to support mining of gene lists, discovery of related datasets, and single-click citation integration with popular reference managers. Automated processes were established to embed digital object identifier-driven links to the secondary datasets in associated journal articles, small molecule and gene-centric databases, and a dataset search engine. Our model creates multiple points of access to reprocessed and reannotated derivative datasets across the digital biomedical research ecosystem, promoting their visibility and usability across disparate research communities. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Scoping of Flood Hazard Mapping Needs for Coos County, New Hampshire

DTIC Science & Technology

2006-01-01

Technical Partner DEM Digital Elevation Model DFIRM Digital Flood Insurance Rate Map DOQ Digital Orthophoto Quadrangle DOQQ Digital Ortho Quarter Quadrangle...color Digital Orthophoto Quadrangles (DOQs)). Remote sensing, base map information, GIS data (for example, contour data, E911 data, Digital Elevation...the feature types found on USGS topographic maps. More recently developed data were derived from digital orthophotos providing improved base map

Comparison of High and Low Density Airborne LIDAR Data for Forest Road Quality Assessment

NASA Astrophysics Data System (ADS)

Kiss, K.; Malinen, J.; Tokola, T.

2016-06-01

Good quality forest roads are important for forest management. Airborne laser scanning data can help create automatized road quality detection, thus avoiding field visits. Two different pulse density datasets have been used to assess road quality: high-density airborne laser scanning data from Kiihtelysvaara and low-density data from Tuusniemi, Finland. The field inventory mainly focused on the surface wear condition, structural condition, flatness, road side vegetation and drying of the road. Observations were divided into poor, satisfactory and good categories based on the current Finnish quality standards used for forest roads. Digital Elevation Models were derived from the laser point cloud, and indices were calculated to determine road quality. The calculated indices assessed the topographic differences on the road surface and road sides. The topographic position index works well in flat terrain only, while the standardized elevation index described the road surface better if the differences are bigger. Both indices require at least a 1 metre resolution. High-density data is necessary for analysis of the road surface, and the indices relate mostly to the surface wear and flatness. The classification was more precise (31-92%) than on low-density data (25-40%). However, ditch detection and classification can be carried out using the sparse dataset as well (with a success rate of 69%). The use of airborne laser scanning data can provide quality information on forest roads.

A 3D visualization of spatial relationship between geological structure and groundwater chemical profile around Iwate volcano, Japan: based on the ARCGIS 3D Analyst

NASA Astrophysics Data System (ADS)

Shibahara, A.; Ohwada, M.; Itoh, J.; Kazahaya, K.; Tsukamoto, H.; Takahashi, M.; Morikawa, N.; Takahashi, H.; Yasuhara, M.; Inamura, A.; Oyama, Y.

2009-12-01

We established 3D geological and hydrological model around Iwate volcano to visualize 3D relationships between subsurface structure and groundwater profile. Iwate volcano is a typical polygenetic volcano located in NE Japan, and its body is composed of two stratovolcanoes which have experienced sector collapses several times. Because of this complex structure, groundwater flow around Iwate volcano is strongly restricted by subsurface construction. For example, Kazahaya and Yasuhara (1999) clarified that shallow groundwater in north and east flanks of Iwate volcano are recharged at the mountaintop, and these flow systems are restricted in north and east area because of the structure of younger volcanic body collapse. In addition, Ohwada et al. (2006) found that these shallow groundwater in north and east flanks have relatively high concentration of major chemical components and high 3He/4He ratios. In this study, we succeeded to visualize the spatial relationship between subsurface structure and chemical profile of shallow and deep groundwater system using 3D model on the GIS. In the study region, a number of geological and hydrological datasets, such as boring log data and groundwater chemical profile, were reported. All these paper data are digitized and converted to meshed data on the GIS, and plotted in the three dimensional space to visualize spatial distribution. We also inputted digital elevation model (DEM) around Iwate volcano issued by the Geographical Survey Institute of Japan, and digital geological maps issued by Geological Survey of Japan, AIST. All 3D models are converted into VRML format, and can be used as a versatile dataset on personal computer.

Integration of Digital Dental Casts in Cone-Beam Computed Tomography Scans

PubMed Central

Rangel, Frits A.; Maal, Thomas J. J.; Bergé, Stefaan J.; Kuijpers-Jagtman, Anne Marie

2012-01-01

Cone-beam computed tomography (CBCT) is widely used in maxillofacial surgery. The CBCT image of the dental arches, however, is of insufficient quality to use in digital planning of orthognathic surgery. Several authors have described methods to integrate digital dental casts into CBCT scans, but all reported methods have drawbacks. The aim of this feasibility study is to present a new simplified method to integrate digital dental casts into CBCT scans. In a patient scheduled for orthognathic surgery, titanium markers were glued to the gingiva. Next, a CBCT scan and dental impressions were made. During the impression-taking procedure, the titanium markers were transferred to the impression. The impressions were scanned, and all CBCT datasets were exported in DICOM format. The two datasets were matched, and the dentition derived from the scanned impressions was transferred to the CBCT of the patient. After matching the two datasets, the average distance between the corresponding markers was 0.1 mm. This novel method allows for the integration of digital dental casts into CBCT scans, overcoming problems such as unwanted extra radiation exposure, distortion of soft tissues due to the use of bite jigs, and time-consuming digital data handling. PMID:23050159

Topographic soil wetness index derived from combined Alaska-British Columbia datasets for the Gulf of Alaska region

NASA Astrophysics Data System (ADS)

D'Amore, D. V.; Biles, F. E.

2016-12-01

The flow of water is often highlighted as a priority in land management planning and assessments related to climate change. Improved measurement and modeling of soil moisture is required to develop predictive estimates for plant distributions, soil moisture, and snowpack, which all play important roles in ecosystem planning in the face of climate change. Drainage indexes are commonly derived from GIS tools with digital elevation models. Soil moisture classes derived from these tools are useful digital proxies for ecosystem functions associated with the concentration of water on the landscape. We developed a spatially explicit topographically derived soil wetness index (TWI) across the perhumid coastal temperate rainforest (PCTR) of Alaska and British Columbia. Developing applicable drainage indexes in complex terrain and across broad areas required careful application of the appropriate DEM, caution with artifacts in GIS covers and mapping realistic zones of wetlands with the indicator. The large spatial extent of the model has facilitated the mapping of forest habitat and the development of water table depth mapping in the region. A key element of the TWI is the merging of elevation datasets across the US-Canada border where major rivers transect the international boundary. The unified TWI allows for seemless mapping across the international border and unified ecological applications. A python program combined with the unified DEM allows end users to quickly apply the TWI to all areas of the PCTR. This common platform can facilitate model comparison and improvements to local soil moisture conditions, generation of streamflow, and ecological site conditions. In this presentation we highlight the application of the TWI for mapping risk factors related to forest decline and the development of a regional water table depth map. Improved soil moisture maps are critical for deriving spatial models of changes in soil moisture for both plant growth and streamflow across future climate conditions.

Comparison of Terrestrial Laser Scanning (TLS) and Structure from Motion (SfM) photogrammetry from unmanned aerial systems (UAS) for geomorphic change detection in beach-dune systems.

NASA Astrophysics Data System (ADS)

Heathfield, D.; Walker, I. J.; Grilliot, M. J.

2016-12-01

The recent emergence of terrestrial laser scanning (TLS) and unmanned aerial systems (UAS) as mapping platforms in geomorphology research has allowed for expedited acquisition of high spatial and temporal resolution, three-dimensional topographic datasets. TLS provides dense 3D `point cloud' datasets that require careful acquisition strategies and appreciable post-processing to produce accurate digital elevation models (DEMs). UAS provide overlapping nadir and oblique imagery that can be analysed using Structure from Motion (SfM) photogrammetry software to provide accurate, high-resolution orthophoto mosaics and accurate digital surface models (DSMs). Both methods yield centimeter to decimeter scale accuracy, depending on various hardware and field acquisition considerations (e.g., camera resolution, flight height, on-site GNSS control, etc.). Combined, the UAS-SfM workflow provides a comparable and more affordable solution to the more expensive TLS or aerial LiDAR methods. This paper compares and contrasts SfM and TLS survey methodologies and related workflow costs and benefits as used to quantify and examine seasonal beach-dune erosion and recovery processes at a site (Calvert Island) on British Columbia's central coast in western Canada. Seasonal SfM- and TLS-derived DEMs were used to quantify spatial patterns of surface elevation change, geomorphic responses, and related significant sediment volume changes. Cluster maps of positive (depositional) and negative (erosional) change are analysed to detect and interpret the geomorphic and sediment budget responses following an erosive water level event during winter 2016 season (Oct. 2015 - Apr. 2016). Vantage cameras also provided qualitative data on the frequency and magnitude of environmental drivers (e.g., tide, wave, wind forcing) of erosion and deposition events during the observation period. In addition, we evaluate the costs, time expenditures, and accuracy considerations for both SfM and TLS methodologies.

Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: Level 3 Ecoregions

USGS Publications Warehouse

Wieczorek, Michael; LaMotte, Andrew E.

2010-01-01

This data set represents the estimated area of level 3 ecological landscape regions (ecoregions), as defined by Omernik (1987), compiled for every catchment of NHDPlus for the conterminous United States. The source data set is Level III Ecoregions of the Continental United States (U.S. Environmental Protection Agency, 2003). The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: Hydrologic Landscape Regions

USGS Publications Warehouse

Wieczorek, Michael; LaMotte, Andrew E.

2010-01-01

This data set represents the area of Hydrologic Landscape Regions (HLR) compiled for every catchment of NHDPlus for the conterminous United States. The source data set is a 100-meter version of Hydrologic Landscape Regions of the United States (Wolock, 2003). HLR groups watersheds on the basis of similarities in land-surface form, geologic texture, and climate characteristics. The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

Attributes for NHDPlus Catchments (Version 1.1): Level 3 Nutrient Ecoregions, 2002

USGS Publications Warehouse

Wieczorek, Michael; LaMotte, Andrew E.

2010-01-01

This data set represents the area of each level 3 nutrient ecoregion in square meters, compiled for every catchment of NHDPlus for the conterminous United States. The source data are from the 2002 version of the U.S. Environmental Protection Agency's (USEPA) Aggregations of Level III Ecoregions for National Nutrient Assessment & Management Strategy (USEPA, 2002). The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: Base-Flow Index

USGS Publications Warehouse

Wieczorek, Michael; LaMotte, Andrew E.

2010-01-01

This tabular data set represents the mean base-flow index expressed as a percent, compiled for every catchment in NHDPlus for the conterminous United States. Base flow is the component of streamflow that can be attributed to ground-water discharge into streams. The source data set is Base-Flow Index for the Conterminous United States (Wolock, 2003). The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: Mean Annual R-factor, 1971-2000

USGS Publications Warehouse

Wieczorek, Michael; LaMotte, Andrew E.

2010-01-01

This data set represents the average annual R-factor, rainfall-runoff erosivity measure, compiled for every catchment of NHDPlus for the conterminous United States. The source data are from Christopher Daly of the Spatial Climate Analysis Service, Oregon State University, and George Taylor of the Oregon Climate Service, Oregon State University (2002), who developed spatially distributed estimates of R-factor for the period 1971-2000 for the conterminous United States. The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: Average Atmospheric (Wet) Deposition of Inorganic Nitrogen, 2002

USGS Publications Warehouse

Wieczorek, Michael; LaMotte, Andrew E.

2010-01-01

This data set represents the average atmospheric (wet) deposition, in kilograms per square kilometer, of inorganic nitrogen for the year 2002 compiled for every catchment of NHDPlus for the conterminous United States. The source data set for wet deposition was from the USGS's raster data set atmospheric (wet) deposition of inorganic nitrogen for 2002 (Gronberg, 2005). The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years (2007-2008), an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: Nutrient Inputs from Fertilizer and Manure, Nitrogen and Phosphorus (N&P), 2002

USGS Publications Warehouse

Wieczorek, Michael; LaMotte, Andrew E.

2010-01-01

This data set represents the estimated amount of nitrogen and phosphorus in kilograms for the year 2002, compiled for every catchment of NHDPlus for the conterminous United States. The source data set is County-Level Estimates of Nutrient Inputs to the Land Surface of the Conterminous United States, 1982-2001 (Ruddy and others, 2006). The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

Attributes for NHDPlus catchments (Version 1.1) for the conterminous United States: STATSGO soil characteristics

USGS Publications Warehouse

Wieczorek, Michael; LaMotte, Andrew E.

2010-01-01

This data set represents estimated soil variables compiled for every catchment of NHDPlus for the conterminous United States. The variables included are cation exchange capacity, percent calcium carbonate, slope, water-table depth, soil thickness, hydrologic soil group, soil erodibility (k-factor), permeability, average water capacity, bulk density, percent organic material, percent clay, percent sand, and percent silt. The source data set is the State Soil ( STATSGO ) Geographic Database (Wolock, 1997). The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: Estimated Mean Annual Natural Groundwater Recharge, 2002

USGS Publications Warehouse

Wieczorek, Michael; LaMotte, Andrew E.

2010-01-01

This data set represents the mean annual natural groundwater recharge, in millimeters, compiled for every catchment of NHDPlus for the conterminous United States. The source data set is Estimated Mean Annual Natural Ground-Water Recharge in the Conterminous United States (Wolock, 2003). The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, containing NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

Attributes for NHDplus Catchments (Version 1.1) for the Conterminous United States: Population Density, 2000

USGS Publications Warehouse

Wieczorek, Michael; LaMottem, Andrew E.

2010-01-01

This data set represents the average population density, in number of people per square kilometer multiplied by 10 for the year 2000, compiled for every catchment of NHDPlus for the conterminous United States. The source data set is the 2000 Population Density by Block Group for the Conterminous United States (Hitt, 2003). The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: Nutrient Application (Phosphorus and Nitrogen ) for Fertilizer and Manure Applied to Crops (Cropsplit), 2002

USGS Publications Warehouse

Wieczorek, Michael; LaMotte, Andrew E.

2010-01-01

This data set represents the estimated amount of phosphorus and nitrogen fertilizers applied to selected crops for the year 2002, compiled for every catchment of NHDPlus for the conterminous United States. The source data set is based on 2002 fertilizer data (Ruddy and others, 2006) and tabulated by crop type per county (Alexander and others, 2007). The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

Development of a Watershed Boundary Dataset for Mississippi

USGS Publications Warehouse

Van Wilson, K.; Clair, Michael G.; Turnipseed, D. Phil; Rebich, Richard A.

2009-01-01

The U.S. Geological Survey, in cooperation with the Mississippi Department of Environmental Quality, U.S. Department of Agriculture-Natural Resources Conservation Service, Mississippi Department of Transportation, U.S. Department of Agriculture-Forest Service, and the Mississippi Automated Resource Information System, developed a 1:24,000-scale Watershed Boundary Dataset for Mississippi including watershed and subwatershed boundaries, codes, names, and drainage areas. The Watershed Boundary Dataset for Mississippi provides a standard geographical framework for water-resources and selected land-resources planning. The original 8-digit subbasins (hydrologic unit codes) were further subdivided into 10-digit watersheds and 12-digit subwatersheds - the exceptions are the Lower Mississippi River Alluvial Plain (known locally as the Delta) and the Mississippi River inside levees, which were only subdivided into 10-digit watersheds. Also, large water bodies in the Mississippi Sound along the coast were not delineated as small as a typical 12-digit subwatershed. All of the data - including watershed and subwatershed boundaries, hydrologic unit codes and names, and drainage-area data - are stored in a Geographic Information System database.

Mapping hydrological environments in central Amazonia: ground validation and surface model based on SRTM DEM data corrected for deforestation

NASA Astrophysics Data System (ADS)

Moulatlet, G. M.; Rennó, C. D.; Costa, F. R. C.; Emilio, T.; Schietti, J.

2014-07-01

One of the most important freely available digital elevation models (DEMs) for Amazonia is the one obtained by the Shuttle Radar Topography Mission (SRTM). However, since SRTM tends to represent the vegetation surface instead of the ground surface, the broad use of SRTM DEM as a framework for terrain description in Amazonia is hampered by the presence of deforested areas. We present here two datasets: (1) a deforestation-corrected SRTM DEM for the interfluve between the Purus and Madeira rivers, in central Amazonia, which passed through a careful identification of different environments and has deforestation features corrected by a new method of increasing pixel values of the DEM; and (2) a set of eighteen hydrological-topographic descriptors based on the corrected SRTM DEM. The hydrological-topographic description was generated by the Height Above the Nearest Drainage (HAND) algorithm, which normalizes the terrain elevation (a.s.l.) by the elevation of the nearest hydrologically connected drainage. The validation of the HAND dataset was done by in situ hydrological description of 110 km of walking trails also available in this dataset. The new SRTM DEM expands the applicability of SRTM data for landscape modelling; and the datasets of hydrological features based on topographic modelling is undoubtedly appropriate for ecological modelling and an important contribution for environmental mapping of Amazonia. The deforestation-corrected SRTM DEM is available at http://ppbio.inpa.gov.br/knb/metacat/naman.318.3/ppbio; the polygons selected for deforestation correction are available at http://ppbio.inpa.gov.br/knb/metacat/naman.317.3/ppbio; the set of hydrological-topographic descriptors is available at http://ppbio.inpa.gov.br/knb/metacat/naman.544.2/ppbio; and the environmental description of access trails is available at http://ppbio.inpa.gov.br/knb/metacat/naman.541.2/ppbio.

A critical source area phosphorus index with topographic transport factors using high resolution LiDAR digital elevation models

NASA Astrophysics Data System (ADS)

Thomas, Ian; Murphy, Paul; Fenton, Owen; Shine, Oliver; Mellander, Per-Erik; Dunlop, Paul; Jordan, Phil

2015-04-01

A new phosphorus index (PI) tool is presented which aims to improve the identification of critical source areas (CSAs) of phosphorus (P) losses from agricultural land to surface waters. In a novel approach, the PI incorporates topographic indices rather than watercourse proximity as proxies for runoff risk, to account for the dominant control of topography on runoff-generating areas and P transport pathways. Runoff propensity and hydrological connectivity are modelled using the Topographic Wetness Index (TWI) and Network Index (NI) respectively, utilising high resolution digital elevation models (DEMs) derived from Light Detection and Ranging (LiDAR) to capture the influence of micro-topographic features on runoff pathways. Additionally, the PI attempts to improve risk estimates of particulate P losses by incorporating an erosion factor that accounts for fine-scale topographic variability within fields. Erosion risk is modelled using the Unit Stream Power Erosion Deposition (USPED) model, which integrates DEM-derived upslope contributing area and Universal Soil Loss Equation (USLE) factors. The PI was developed using field, sub-field and sub-catchment scale datasets of P source, mobilisation and transport factors, for four intensive agricultural catchments in Ireland representing different agri-environmental conditions. Datasets included soil test P concentrations, degree of P saturation, soil attributes, land use, artificial subsurface drainage locations, and 2 m resolution LiDAR DEMs resampled from 0.25 m resolution data. All factor datasets were integrated within a Geographical Information System (GIS) and rasterised to 2 m resolution. For each factor, values were categorised and assigned relative risk scores which ranked P loss potential. Total risk scores were calculated for each grid cell using a component formulation, which summed the products of weighted factor risk scores for runoff and erosion pathways. Results showed that the new PI was able to predict in-field risk variability and hence was able to identify CSAs at the sub-field scale. PI risk estimates and component scores were analysed at catchment and subcatchment scales, and validated using measured dissolved, particulate and total P losses at subcatchment snapshot sites and gauging stations at catchment outlets. The new PI provides CSA delineations at higher precision compared to conventional PIs, and more robust P transport risk estimates. The tool can be used to target cost-effective mitigation measures for P management within single farm units and wider catchments.

Towards large-scale mapping of urban three-dimensional structure using Landsat imagery and global elevation datasets

NASA Astrophysics Data System (ADS)

Wang, P.; Huang, C.

2017-12-01

The three-dimensional (3D) structure of buildings and infrastructures is fundamental to understanding and modelling of the impacts and challenges of urbanization in terms of energy use, carbon emissions, and earthquake vulnerabilities. However, spatially detailed maps of urban 3D structure have been scarce, particularly in fast-changing developing countries. We present here a novel methodology to map the volume of buildings and infrastructures at 30 meter resolution using a synergy of Landsat imagery and openly available global digital surface models (DSMs), including the Shuttle Radar Topography Mission (SRTM), ASTER Global Digital Elevation Map (GDEM), ALOS World 3D - 30m (AW3D30), and the recently released global DSM from the TanDEM-X mission. Our method builds on the concept of object-based height profile to extract height metrics from the DSMs and use a machine learning algorithm to predict height and volume from the height metrics. We have tested this algorithm in the entire England and assessed our result using Lidar measurements in 25 England cities. Our initial assessments achieved a RMSE of 1.4 m (R2 = 0.72) for building height and a RMSE of 1208.7 m3 (R2 = 0.69) for building volume, demonstrating the potential of large-scale applications and fully automated mapping of urban structure.

Distinctive fingerprints of erosional regimes in terrestrial channel networks

NASA Astrophysics Data System (ADS)

Grau Galofre, A.; Jellinek, M.

2017-12-01

Satellite imagery and digital elevation maps capture the large scale morphology of channel networks attributed to long term erosional processes, such as fluvial, glacial, groundwater sapping and subglacial erosion. Characteristic morphologies associated with each of these styles of erosion have been studied in detail, but there exists a knowledge gap related to their parameterization and quantification. This knowledge gap prevents a rigorous analysis of the dominant processes that shaped a particular landscape, and a comparison across styles of erosion. To address this gap, we use previous morphological descriptions of glaciers, rivers, sapping valleys and tunnel valleys to identify and measure quantitative metrics diagnostic of these distinctive styles of erosion. From digital elevation models, we identify four geometric metrics: The minimum channel width, channel aspect ratio (longest length to channel width at the outlet), presence of undulating longitudinal profiles, and tributary junction angle. We also parameterize channel network complexity in terms of its stream order and fractal dimension. We then perform a statistical classification of the channel networks using a Principal Component Analysis on measurements of these six metrics on a dataset of 70 channelized systems. We show that rivers, glaciers, groundwater seepage and subglacial meltwater erode the landscape in rigorously distinguishable ways. Our methodology can more generally be applied to identify the contributions of different processes involved in carving a channel network. In particular, we are able to identify transitions from fluvial to glaciated landscapes or vice-versa.

Topographic changes and their driving factors after 2008 Wenchuan Earthquake

NASA Astrophysics Data System (ADS)

Li, C.; Wang, M.; Xie, J.; Liu, K.

2017-12-01

The Wenchuan Ms 8.0 Earthquake caused topographic change in the stricken areas because of the formation of numerous coseismic landslides. The emergence of new landslides and debris flows and movement of loose materials under the driving force of heavy rainfall could further shape the local topography. Dynamic topographic changes in mountainous areas stricken by major earthquakes have a strong linkage to the development and occurrence of secondary disasters. However, little attention has been paid to continuously monitoring mountain environment change after such earthquakes. A digital elevation model (DEM) is the main feature of the terrain surface, in our research, we extracted DEM in 2013 and 2015 of a typical mountainous area severely impacted by the 2008 Wenchuan earthquake from the ZY-3 stereo pair images with validation by field measurement. Combined with the elevation dataset in 2002 and 2010, we quantitatively assessed elevation changes in different years and qualitatively analyzed spatiotemporal variation of the terrain and mass movement across the study area. The results show that the earthquake stricken area experienced substantial elevation changes caused by seismic forces and subsequent rainfalls. Meanwhile, deposits after the earthquake are mainly accumulated on the river-channels and mountain ridges and deep gullies which increase the risk of other geo-hazards. And the heavy rainfalls after the earthquake have become the biggest driver of elevation reduction, which overwhelmed elevation increase during the major earthquake. Our study provided a better understanding of subsequent hazards and risks faced by residents and communities stricken by major earthquakes.

Benford's Law for Quality Assurance of Manner of Death Counts in Small and Large Databases.

PubMed

Daniels, Jeremy; Caetano, Samantha-Jo; Huyer, Dirk; Stephen, Andrew; Fernandes, John; Lytwyn, Alice; Hoppe, Fred M

2017-09-01

To assess if Benford's law, a mathematical law used for quality assurance in accounting, can be applied as a quality assurance measure for the manner of death determination. We examined a regional forensic pathology service's monthly manner of death counts (N = 2352) from 2011 to 2013, and provincial monthly and weekly death counts from 2009 to 2013 (N = 81,831). We tested whether each dataset's leading digit followed Benford's law via the chi-square test. For each database, we assessed whether number 1 was the most common leading digit. The manner of death counts first digit followed Benford's law in all the three datasets. Two of the three datasets had 1 as the most frequent leading digit. The manner of death data in this study showed qualities consistent with Benford's law. The law has potential as a quality assurance metric in the manner of death determination for both small and large databases. © 2017 American Academy of Forensic Sciences.

Integration of SRTM and TRMM date into the GIS-based hydrological model for the purpose of flood modelling

NASA Astrophysics Data System (ADS)

Akbari, A.; Abu Samah, A.; Othman, F.

2012-04-01

Due to land use and climate changes, more severe and frequent floods occur worldwide. Flood simulation as the first step in flood risk management can be robustly conducted with integration of GIS, RS and flood modeling tools. The primary goal of this research is to examine the practical use of public domain satellite data and GIS-based hydrologic model. Firstly, database development process is described. GIS tools and techniques were used in the light of relevant literature to achieve the appropriate database. Watershed delineation and parameterizations were carried out using cartographic DEM derived from digital topography at a scale of 1:25 000 with 30 m cell size and SRTM elevation data at 30 m cell size. The SRTM elevation dataset is evaluated and compared with cartographic DEM. With the assistance of statistical measures such as Correlation coefficient (r), Nash-Sutcliffe efficiency (NSE), Percent Bias (PBias) or Percent of Error (PE). According to NSE index, SRTM-DEM can be used for watershed delineation and parameterization with 87% similarity with Topo-DEM in a complex and underdeveloped terrains. Primary TRMM (V6) data was used as satellite based hytograph for rainfall-runoff simulation. The SCS-CN approach was used for losses and kinematic routing method employed for hydrograph transformation through the reaches. It is concluded that TRMM estimates do not give adequate information about the storms as it can be drawn from the rain gauges. Event-based flood modeling using HEC-HMS proved that SRTM elevation dataset has the ability to obviate the lack of terrain data for hydrologic modeling where appropriate data for terrain modeling and simulation of hydrological processes is unavailable. However, TRMM precipitation estimates failed to explain the behavior of rainfall events and its resultant peak discharge and time of peak.

Identifying opportune landing sites in degraded visual environments with terrain and cultural databases

NASA Astrophysics Data System (ADS)

Moody, Marc; Fisher, Robert; Little, J. Kristin

2014-06-01

Boeing has developed a degraded visual environment navigational aid that is flying on the Boeing AH-6 light attack helicopter. The navigational aid is a two dimensional software digital map underlay generated by the Boeing™ Geospatial Embedded Mapping Software (GEMS) and fully integrated with the operational flight program. The page format on the aircraft's multi function displays (MFD) is termed the Approach page. The existing work utilizes Digital Terrain Elevation Data (DTED) and OpenGL ES 2.0 graphics capabilities to compute the pertinent graphics underlay entirely on the graphics processor unit (GPU) within the AH-6 mission computer. The next release will incorporate cultural databases containing Digital Vertical Obstructions (DVO) to warn the crew of towers, buildings, and power lines when choosing an opportune landing site. Future IRAD will include Light Detection and Ranging (LIDAR) point cloud generating sensors to provide 2D and 3D synthetic vision on the final approach to the landing zone. Collision detection with respect to terrain, cultural, and point cloud datasets may be used to further augment the crew warning system. The techniques for creating the digital map underlay leverage the GPU almost entirely, making this solution viable on most embedded mission computing systems with an OpenGL ES 2.0 capable GPU. This paper focuses on the AH-6 crew interface process for determining a landing zone and flying the aircraft to it.

Multi-sensor fusion over the World Trade Center disaster site

NASA Astrophysics Data System (ADS)

Rodarmel, Craig; Scott, Lawrence; Simerlink, Deborah A.; Walker, Jeffrey

2002-09-01

The immense size and scope of the rescue and clean-up of the World Trade Center site created a need for data that would provide a total overview of the disaster area. To fulfill this need, the New York State Office for Technology (NYSOFT) contracted with EarthData International to collect airborne remote sensing data over Ground Zero with an airborne light detection and ranging (LIDAR) sensor, a high-resolution digital camera, and a thermal camera. The LIDAR data provided a three-dimensional elevation model of the ground surface that was used for volumetric calculations and also in the orthorectification of the digital images. The digital camera provided high-resolution imagery over the site to aide the rescuers in placement of equipment and other assets. In addition, the digital imagery was used to georeference the thermal imagery and also provided the visual background for the thermal data. The thermal camera aided in the location and tracking of underground fires. The combination of data from these three sensors provided the emergency crews with a timely, accurate overview containing a wealth of information of the rapidly changing disaster site. Because of the dynamic nature of the site, the data was acquired on a daily basis, processed, and turned over to NYSOFT within twelve hours of the collection. During processing, the three datasets were combined and georeferenced to allow them to be inserted into the client's geographic information systems.

Historical glacier outlines from digitized topographic maps of the Swiss Alps

NASA Astrophysics Data System (ADS)

Freudiger, Daphné; Mennekes, David; Seibert, Jan; Weiler, Markus

2018-04-01

Since the end of the Little Ice Age around 1850, the total glacier area of the central European Alps has considerably decreased. In order to understand the changes in glacier coverage at various scales and to model past and future streamflow accurately, long-term and large-scale datasets of glacier outlines are needed. To fill the gap between the morphologically reconstructed glacier outlines from the moraine extent corresponding to the time period around 1850 and the first complete dataset of glacier areas in the Swiss Alps from aerial photographs in 1973, glacier areas from 80 sheets of a historical topographic map (the Siegfried map) were manually digitized for the publication years 1878-1918 (further called first period, with most sheets being published around 1900) and 1917-1944 (further called second period, with most sheets being published around 1935). The accuracy of the digitized glacier areas was then assessed through a two-step validation process: the data were (1) visually and (2) quantitatively compared to glacier area datasets of the years 1850, 1973, 2003, and 2010, which were derived from different sources, at the large scale, basin scale, and locally. The validation showed that at least 70 % of the digitized glaciers were comparable to the outlines from the other datasets and were therefore plausible. Furthermore, the inaccuracy of the manual digitization was found to be less than 5 %. The presented datasets of glacier outlines for the first and second periods are a valuable source of information for long-term glacier mass balance or hydrological modelling in glacierized basins. The uncertainty of the historical topographic maps should be considered during the interpretation of the results. The datasets can be downloaded from the FreiDok plus data repository (https://freidok.uni-freiburg.de/data/15008, https://doi.org/10.6094/UNIFR/15008).

Ground-Truthing of Airborne LiDAR Using RTK-GPS Surveyed Data in Coastal Louisiana's Wetlands

NASA Astrophysics Data System (ADS)

Lauve, R. M.; Alizad, K.; Hagen, S. C.

2017-12-01

Airborne LiDAR (Light Detection and Ranging) data are used by engineers and scientists to create bare earth digital elevation models (DEM), which are essential to modeling complex coastal, ecological, and hydrological systems. However, acquiring accurate bare earth elevations in coastal wetlands is difficult due to the density of marsh grasses that prevent the sensors reflection off the true ground surface. Previous work by Medeiros et al. [2015] developed a technique to assess LiDAR error and adjust elevations according to marsh vegetation density and index. The aim of this study is the collection of ground truth points and the investigation on the range of potential errors found in existing LiDAR datasets within coastal Louisiana's wetlands. Survey grids were mapped out in an area dominated by Spartina alterniflora and a survey-grade Trimble Real Time Kinematic (RTK) GPS device was employed to measure bare earth ground elevations in the marsh system adjacent to Terrebonne Bay, LA. Elevations were obtained for 20 meter-spaced surveyed grid points and were used to generate a DEM. The comparison between LiDAR derived and surveyed data DEMs yield an average difference of 23 cm with a maximum difference of 68 cm. Considering the local tidal range of 45 cm, these differences can introduce substantial error when the DEM is used for ecological modeling [Alizad et al., 2016]. Results from this study will be further analyzed and implemented in order to adjust LiDAR-derived DEMs closer to their true elevation across Louisiana's coastal wetlands. ReferencesAlizad, K., S. C. Hagen, J. T. Morris, S. C. Medeiros, M. V. Bilskie, and J. F. Weishampel (2016), Coastal wetland response to sea-level rise in a fluvial estuarine system, Earth's Future, 4(11), 483-497, 10.1002/2016EF000385. Medeiros, S., S. Hagen, J. Weishampel, and J. Angelo (2015), Adjusting Lidar-Derived Digital Terrain Models in Coastal Marshes Based on Estimated Aboveground Biomass Density, Remote Sensing, 7(4), 3507-3525, 10.3390/rs70403507.

Automating the implementation of an equilibrium profile model for glacier reconstruction in a GIS environment

NASA Astrophysics Data System (ADS)

Frew, Craig R.; Pellitero, Ramón; Rea, Brice R.; Spagnolo, Matteo; Bakke, Jostein; Hughes, Philip D.; Ivy-Ochs, Susan; Lukas, Sven; Renssen, Hans; Ribolini, Adriano

2014-05-01

Reconstruction of glacier equilibrium line altitudes (ELAs) associated with advance stages of former ice masses is widely used as a tool for palaeoclimatic reconstruction. This requires an accurate reconstruction of palaeo-glacier surface hypsometry, based on mapping of available ice-marginal landform evidence. Classically, the approach used to define ice-surface elevations, using such evidence, follows the 'cartographic method', whereby contours are estimated based on an 'understanding' of the typical surface form of contemporary ice masses. This method introduces inherent uncertainties in the palaeoclimatic interpretation of reconstructed ELAs, especially where the upper limits of glaciation are less well constrained and/or the age of such features in relation to terminal moraine sequences is unknown. An alternative approach is to use equilibrium profile models to define ice surface elevations. Such models are tuned, generally using basal shear stress, in order to generate an ice surface that reaches 'target elevations' defined by geomorphology. In areas where there are no geomorphological constraints for the former ice surface, the reconstruction is undertaken using glaciologiaclly representative values for basal shear stress. Numerical reconstructions have been shown to produce glaciologically "realistic" ice surface geometries, allowing for more objective and robust comparative studies at local to regional scales. User-friendly tools for the calculation of equilibrium profiles are presently available in the literature. Despite this, their use is not yet widespread, perhaps owing to the difficult and time consuming nature of acquiring the necessary inputs from contour maps or digital elevation models. Here we describe a tool for automatically reconstructing palaeo-glacier surface geometry using an equilibrium profile equation implemented in ArcGIS. The only necessary inputs for this tool are 1) a suitable digital elevation model and 2) mapped outlines of the former glacier terminus position (usually a frontal moraine system) and any relevant geomorphological constraints on ice surface elevation (e.g. lateral moraines, trimlines etc.). This provides a standardised method for glacier reconstruction that can be applied rapidly and systematically to large geomorphological datasets.

Filling the voids in the SRTM elevation model — A TIN-based delta surface approach

NASA Astrophysics Data System (ADS)

Luedeling, Eike; Siebert, Stefan; Buerkert, Andreas

The Digital Elevation Model (DEM) derived from NASA's Shuttle Radar Topography Mission is the most accurate near-global elevation model that is publicly available. However, it contains many data voids, mostly in mountainous terrain. This problem is particularly severe in the rugged Oman Mountains. This study presents a method to fill these voids using a fill surface derived from Russian military maps. For this we developed a new method, which is based on Triangular Irregular Networks (TINs). For each void, we extracted points around the edge of the void from the SRTM DEM and the fill surface. TINs were calculated from these points and converted to a base surface for each dataset. The fill base surface was subtracted from the fill surface, and the result added to the SRTM base surface. The fill surface could then seamlessly be merged with the SRTM DEM. For validation, we compared the resulting DEM to the original SRTM surface, to the fill DEM and to a surface calculated by the International Center for Tropical Agriculture (CIAT) from the SRTM data. We calculated the differences between measured GPS positions and the respective surfaces for 187,500 points throughout the mountain range (ΔGPS). Comparison of the means and standard deviations of these values showed that for the void areas, the fill surface was most accurate, with a standard deviation of the ΔGPS from the mean ΔGPS of 69 m, and only little accuracy was lost by merging it to the SRTM surface (standard deviation of 76 m). The CIAT model was much less accurate in these areas (standard deviation of 128 m). The results show that our method is capable of transferring the relative vertical accuracy of a fill surface to the void areas in the SRTM model, without introducing uncertainties about the absolute elevation of the fill surface. It is well suited for datasets with varying altitude biases, which is a common problem of older topographic information.

A new bed elevation model for the Weddell Sea sector of the West Antarctic Ice Sheet

NASA Astrophysics Data System (ADS)

Jeofry, Hafeez; Ross, Neil; Corr, Hugh F. J.; Li, Jilu; Morlighem, Mathieu; Gogineni, Prasad; Siegert, Martin J.

2018-04-01

We present a new digital elevation model (DEM) of the bed, with a 1 km gridding, of the Weddell Sea (WS) sector of the West Antarctic Ice Sheet (WAIS). The DEM has a total area of ˜ 125 000 km2 covering the Institute, Möller and Foundation ice streams, as well as the Bungenstock ice rise. In comparison with the Bedmap2 product, our DEM includes new aerogeophysical datasets acquired by the Center for Remote Sensing of Ice Sheets (CReSIS) through the NASA Operation IceBridge (OIB) program in 2012, 2014 and 2016. We also improve bed elevation information from the single largest existing dataset in the region, collected by the British Antarctic Survey (BAS) Polarimetric radar Airborne Science Instrument (PASIN) in 2010-2011, from the relatively crude measurements determined in the field for quality control purposes used in Bedmap2. While the gross form of the new DEM is similar to Bedmap2, there are some notable differences. For example, the position and size of a deep subglacial trough (˜ 2 km below sea level) between the ice-sheet interior and the grounding line of the Foundation Ice Stream have been redefined. From the revised DEM, we are able to better derive the expected routing of basal water and, by comparison with that calculated using Bedmap2, we are able to assess regions where hydraulic flow is sensitive to change. Given the potential vulnerability of this sector to ocean-induced melting at the grounding line, especially in light of the improved definition of the Foundation Ice Stream trough, our revised DEM will be of value to ice-sheet modelling in efforts to quantify future glaciological changes in the region and, from this, the potential impact on global sea level. The new 1 km bed elevation product of the WS sector can be found at https://doi.org/10.5281/zenodo.1035488.

Watershed Boundary Dataset for Mississippi

USGS Publications Warehouse

Wilson, K. Van; Clair, Michael G.; Turnipseed, D. Phil; Rebich, Richard A.

2009-01-01

The U.S. Geological Survey, in cooperation with the Mississippi Department of Environmental Quality, U.S. Department of Agriculture-Natural Resources Conservation Service, Mississippi Department of Transportation, U.S. Department of Agriculture-Forest Service, and the Mississippi Automated Resource Information System developed a 1:24,000-scale Watershed Boundary Dataset for Mississippi including watershed and subwatershed boundaries, codes, names, and areas. The Watershed Boundary Dataset for Mississippi provides a standard geographical framework for water-resources and selected land-resources planning. The original 8-digit subbasins (Hydrologic Unit Codes) were further subdivided into 10-digit watersheds (62.5 to 391 square miles (mi2)) and 12-digit subwatersheds (15.6 to 62.5 mi2) - the exceptions being the Delta part of Mississippi and the Mississippi River inside levees, which were subdivided into 10-digit watersheds only. Also, large water bodies in the Mississippi Sound along the coast were not delineated as small as a typical 12-digit subwatershed. All of the data - including watershed and subwatershed boundaries, subdivision codes and names, and drainage-area data - are stored in a Geographic Information System database, which are available at: http://ms.water.usgs.gov/. This map shows information on drainage and hydrography in the form of U.S. Geological Survey hydrologic unit boundaries for water-resource 2-digit regions, 4-digit subregions, 6-digit basins (formerly called accounting units), 8-digit subbasins (formerly called cataloging units), 10-digit watershed, and 12-digit subwatersheds in Mississippi. A description of the project study area, methods used in the development of watershed and subwatershed boundaries for Mississippi, and results are presented in Wilson and others (2008). The data presented in this map and by Wilson and others (2008) supersede the data presented for Mississippi by Seaber and others (1987) and U.S. Geological Survey (1977).

Mapping and Visualization of Storm-Surge Dynamics for Hurricane Katrina and Hurricane Rita

USGS Publications Warehouse

Gesch, Dean B.

2009-01-01

The damages caused by the storm surges from Hurricane Katrina and Hurricane Rita were significant and occurred over broad areas. Storm-surge maps are among the most useful geospatial datasets for hurricane recovery, impact assessments, and mitigation planning for future storms. Surveyed high-water marks were used to generate a maximum storm-surge surface for Hurricane Katrina extending from eastern Louisiana to Mobile Bay, Alabama. The interpolated surface was intersected with high-resolution lidar elevation data covering the study area to produce a highly detailed digital storm-surge inundation map. The storm-surge dataset and related data are available for display and query in a Web-based viewer application. A unique water-level dataset from a network of portable pressure sensors deployed in the days just prior to Hurricane Rita's landfall captured the hurricane's storm surge. The recorded sensor data provided water-level measurements with a very high temporal resolution at surveyed point locations. The resulting dataset was used to generate a time series of storm-surge surfaces that documents the surge dynamics in a new, spatially explicit way. The temporal information contained in the multiple storm-surge surfaces can be visualized in a number of ways to portray how the surge interacted with and was affected by land surface features. Spatially explicit storm-surge products can be useful for a variety of hurricane impact assessments, especially studies of wetland and land changes where knowledge of the extent and magnitude of storm-surge flooding is critical.

Application of spatial technology in malaria research & control: some new insights.

PubMed

Saxena, Rekha; Nagpal, B N; Srivastava, Aruna; Gupta, S K; Dash, A P

2009-08-01

Geographical information System (GIS) has emerged as the core of the spatial technology which integrates wide range of dataset available from different sources including Remote Sensing (RS) and Global Positioning System (GPS). Literature published during the decade (1998-2007) has been compiled and grouped into six categories according to the usage of the technology in malaria epidemiology. Different GIS modules like spatial data sources, mapping and geo-processing tools, distance calculation, digital elevation model (DEM), buffer zone and geo-statistical analysis have been investigated in detail, illustrated with examples as per the derived results. These GIS tools have contributed immensely in understanding the epidemiological processes of malaria and examples drawn have shown that GIS is now widely used for research and decision making in malaria control. Statistical data analysis currently is the most consistent and established set of tools to analyze spatial datasets. The desired future development of GIS is in line with the utilization of geo-statistical tools which combined with high quality data has capability to provide new insight into malaria epidemiology and the complexity of its transmission potential in endemic areas.

Evaluation of the U.S. Geological Survey standard elevation products in a two-dimensional hydraulic modeling application for a low relief coastal floodplain

USGS Publications Warehouse

Witt, Emitt C.

2015-01-01

Growing use of two-dimensional (2-D) hydraulic models has created a need for high resolution data to support flood volume estimates, floodplain specific engineering data, and accurate flood inundation scenarios. Elevation data are a critical input to these models that guide the flood-wave across the landscape allowing the computation of valuable engineering specific data that provides a better understanding of flooding impacts on structures, debris movement, bed scour, and direction. High resolution elevation data are becoming publicly available that can benefit the 2-D flood modeling community. Comparison of these newly available data with legacy data suggests that better modeling outcomes are achieved by using 3D Elevation Program (3DEP) lidar point data and the derived 1 m Digital Elevation Model (DEM) product relative to the legacy 3 m, 10 m, or 30 m products currently available in the U.S. Geological Survey (USGS) National Elevation Dataset. Within the low topographic relief of a coastal floodplain, the newer 3DEP data better resolved elevations within the forested and swampy areas achieving simulations that compared well with a historic flooding event. Results show that the 1 m DEM derived from 3DEP lidar source provides a more conservative estimate of specific energy, static pressure, and impact pressure for grid elements at maximum flow relative to the legacy DEM data. Better flood simulations are critically important in coastal floodplains where climate change driven storm frequency and sea level rise will contribute to more frequent flooding events.

Attributes for NHDPlus Catchments (Version 1.1)for the Conterminous United States: Contact Time, 2002

USGS Publications Warehouse

Wieczorek, Michael; LaMotte, Andrew E.

2010-01-01

This data set represents the average contact time, in units of days, compiled for every catchment of NHDPlus for the conterminous United States. Contact time, as described in Wolock and others (1989), is the baseflow residence time in the subsurface. The source data set was the U.S. Geological Survey's (USGS) 1-kilometer grid for the conterminous United States (D.M. Wolock, U.S. Geological Survey, written commun., 2008). The grid was created using a method described by Wolock and others (1997a; see equation 3). In the source data set, the contact time was estimated from 1-kilometer resolution elevation data (Verdin and Greenlee, 1996 ) and STATSGO soil characteristics (Wolock, 1997b). The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

Extraction of Urban Trees from Integrated Airborne Based Digital Image and LIDAR Point Cloud Datasets - Initial Results

NASA Astrophysics Data System (ADS)

Dogon-yaro, M. A.; Kumar, P.; Rahman, A. Abdul; Buyuksalih, G.

2016-10-01

Timely and accurate acquisition of information on the condition and structural changes of urban trees serves as a tool for decision makers to better appreciate urban ecosystems and their numerous values which are critical to building up strategies for sustainable development. The conventional techniques used for extracting tree features include; ground surveying and interpretation of the aerial photography. However, these techniques are associated with some constraint, such as labour intensive field work, a lot of financial requirement, influences by weather condition and topographical covers which can be overcome by means of integrated airborne based LiDAR and very high resolution digital image datasets. This study presented a semi-automated approach for extracting urban trees from integrated airborne based LIDAR and multispectral digital image datasets over Istanbul city of Turkey. The above scheme includes detection and extraction of shadow free vegetation features based on spectral properties of digital images using shadow index and NDVI techniques and automated extraction of 3D information about vegetation features from the integrated processing of shadow free vegetation image and LiDAR point cloud datasets. The ability of the developed algorithms shows a promising result as an automated and cost effective approach to estimating and delineated 3D information of urban trees. The research also proved that integrated datasets is a suitable technology and a viable source of information for city managers to be used in urban trees management.

EnviroAtlas - NHDPlus V2 WBD Snapshot, EnviroAtlas version - Conterminous United States

EPA Pesticide Factsheets

This EnviroAtlas dataset is a digital hydrologic unit boundary layer to the Subwatershed (12-digit) 6th level for the conterminous United States, based on the January 6, 2015 NHDPlus V2 WBD (Watershed Boundary Dataset) Snapshot (NHDPlusV21_NationalData_WBDSnapshot_FileGDB_05). The feature class has been edited for use in for EPA ORD's EnviroAtlas. Features in Canada and Mexico have been removed, the boundaries of three 12-digit HUCs have been edited to eliminate gaps and overlaps, the dataset has been dissolved on HUC_12 to create multipart polygons, and information on the percent land area has been added. Hawaii, Puerto Rico, and the U.S. Virgin Islands have been removed, and can be downloaded separately. Other than these modifications, the dataset is the same as the WBD Snapshot included in NHDPlus V2.This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

Which DEM is the best for glaciology? -Evaluation of global-scale DEM products-

NASA Astrophysics Data System (ADS)

Nagai, Hiroto; Tadono, Takeo

2017-04-01

Digital elevation models (DEMs) are fundamental geospatial data to study glacier distribution, changes, dynamics, mass balance and various geomorphological conditions. This study evaluates latest global-scale free DEMs in order to clarify their superiority and inferiority in glaciological uses. Three DEMs are now available; the 1-arcsec. product obtained from the Shuttle Radar Topographic Mission (SRTM1), the second version of Global Digital Elevation Model of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER GDEM2), and the first resampled dataset acquired by the Advanced Land observing Satellite, namely ALOS World 3D-30m (AW3D30). These DEMs have common specifications of global coverage (<60°S/N for SRTM1), freely downloadable via internet, and 1-arcsec. ( 30 m) pixel spacing. We carried out quantitative accuracy evaluation and spatial analysis of missing data (i.e. "void") distribution for these DEMs. Elevation values of the three DEMs are validated at check points (CPs), where elevation was measured by Geospatial Information Authority of Japan, in (A) the Japan Alps (as steep mountains with glaciation), in (B) Mt. Fuji (as monotonous hillslope), and in (C) the Tone river basin (as an flat plain). In all study sites, AW3D30 has the smallest errors against the CP elevation values (A: -6.1±8.6 m, B: +0.1±3.9 m, C: +0.1±2.5 m as the mean value and standard deviation of elevation differences). SRTM1 is secondly accurate (A: -17.8±16.3 m, B: +1.3±6.4 m, C: +0.1±3.1 m,), followed by ASTER GDEM2 (A: -13.9±20.8 m, B: -3.9±10.0 m, C: +4.3±3.8 m,). This accuracy differences among the DEMs are greater in steeper terrains (A>B>C). In the Tone river basin, SRTM1 has equivalent accuracy to AW3D30. High resolution (2.5 m) of the original stereo-pair images for AW3D30 (i.e. ALOS PRISM imagery) contributes for the best absolute accuracy. Glaciers on rather flat terrains are usually distributed in higher latitude (e.g. Antarctica and Greenland), where SRTM1 is unable. Glaciers at mid-to-low latitudes glaciers are usually distributed in high and steep mountains, where SRTM1 has lower accuracy than AW3D30. AW3D30 would contributes as a preferable option for glaciology in a global scale. At the tops of high mountains in the Nepal Himalaya, however, AW3D30 has a large area of data missing due to snow cover. This inferiority should be improved by filling with other datasets in the next version. ASTER GDEM2 has less area of data missing in the Nepal Himalaya, which would contribute for coarse uses such as generation of river basin, brief drawing of a topographic map, etc.

Data-driven simulations of the Landsat Data Continuity Mission (LDCM) platform

NASA Astrophysics Data System (ADS)

Gerace, Aaron; Gartley, Mike; Schott, John; Raqueño, Nina; Raqueño, Rolando

2011-06-01

The Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) are two new sensors being developed by the Landsat Data Continuity Mission (LDCM) that will extend over 35 years of archived Landsat data. In a departure from the whiskbroom design used by all previous generations of Landsat, the LDCM system will employ a pushbroom technology. Although the newly adopted modular array, pushbroom architecture has several advantages over the previous whiskbroom design, registration of the multi-spectral data products is a concern. In this paper, the Digital Imaging and Remote Sensing Image Generation (DIRSIG) tool was used to simulate an LDCM collection, which gives the team access to data that would not otherwise be available prior to launch. The DIRSIG model was used to simulate the two-instrument LDCM payload in order to study the geometric and radiometric impacts of the sensor design on the proposed processing chain. The Lake Tahoe area located in eastern California was chosen for this work because of its dramatic change in elevation, which was ideal for studying the geometric effects of the new Landsat sensor design. Multi-modal datasets were used to create the Lake Tahoe site model for use in DIRSIG. National Elevation Dataset (NED) data were used to create the digital elevation map (DEM) required by DIRSIG, QuickBird data were used to identify different material classes in the scene, and ASTER and Hyperion spectral data were used to assign radiometric properties to those classes. In order to model a realistic Landsat orbit in these simulations, orbital parameters were obtained from a Landsat 7 two-line element set and propagated with the SGP4 orbital position model. Line-of-sight vectors defining how the individual detector elements of the OLI and TIRS instruments project through the optics were measured and provided by NASA. Additionally, the relative spectral response functions for the 9 bands of OLI and the 2 bands of TIRS were measured and provided by NASA. The instruments were offset on the virtual satellite and data recorders used to generate ephemeris data for downstream processing. Finally, potential platform jitter spectra were measured and provided by NASA and incorporated into the simulations. Simulated imagery generated by the model was incrementally provided to the rest of the LDCM team in a spiral development cycle to constantly refine the simulations.

Coastal Digital Elevation Models (DEMs) for tsunami hazard assessment on the French coasts

NASA Astrophysics Data System (ADS)

Maspataud, Aurélie; Biscara, Laurie; Hébert, Hélène; Schmitt, Thierry; Créach, Ronan

2015-04-01

Building precise and up-to-date coastal DEMs is a prerequisite for accurate modeling and forecasting of hydrodynamic processes at local scale. Marine flooding, originating from tsunamis, storm surges or waves, is one of them. Some high resolution DEMs are being generated for multiple coast configurations (gulf, embayment, strait, estuary, harbor approaches, low-lying areas…) along French Atlantic and Channel coasts. This work is undertaken within the framework of the TANDEM project (Tsunamis in the Atlantic and the English ChaNnel: Definition of the Effects through numerical Modeling) (2014-2017). DEMs boundaries were defined considering the vicinity of French civil nuclear facilities, site effects considerations and potential tsunamigenic sources. Those were identified from available historical observations. Seamless integrated topographic and bathymetric coastal DEMs will be used by institutions taking part in the study to simulate expected wave height at regional and local scale on the French coasts, for a set of defined scenarii. The main tasks were (1) the development of a new capacity of production of DEM, (2) aiming at the release of high resolution and precision digital field models referred to vertical reference frameworks, that require (3) horizontal and vertical datum conversions (all source elevation data need to be transformed to a common datum), on the basis of (4) the building of (national and/or local) conversion grids of datum relationships based on known measurements. Challenges in coastal DEMs development deal with good practices throughout model development that can help minimizing uncertainties. This is particularly true as scattered elevation data with variable density, from multiple sources (national hydrographic services, state and local government agencies, research organizations and private engineering companies) and from many different types (paper fieldsheets to be digitized, single beam echo sounder, multibeam sonar, airborne laser bathymetric and topographic data, …) were gathered. Consequently, datasets were first assessed internally for both quality and accuracy and then externally with other to ensure consistency and gradual topographic/bathymetric transitioning along limits of the datasets. The heterogeneous ages of the input data also stress the importance of taking into account the temporal variability of bathymetric features, especially in the active areas (sandbanks, estuaries, channels). Locally, gaps between marine (hydrographic surveys) and terrestrial (topographic LIDAR) data have required the introduction of new methods and tools to solve interpolation. Through these activities the goal is to improve the production line and to enhance tools and procedures used for the improvement of processing, validation and qualification algorithms of bathymetric data, data collection work, automation of processing and integration process for conception of improved both bathymetric and topographic DEMs, merging data collected. This work is supported by a French ANR program in the frame of "Investissements d'Avenir", under the grant ANR-11-RSNR-00023-01.

Digital terrain tapes: user guide

USGS Publications Warehouse

,

1980-01-01

DMATC's digital terrain tapes are a by-product of the agency's efforts to streamline the production of raised-relief maps. In the early 1960's DMATC developed the Digital Graphics Recorder (DGR) system that introduced new digitizing techniques and processing methods into the field of three-dimensional mapping. The DGR system consisted of an automatic digitizing table and a computer system that recorded a grid of terrain elevations from traces of the contour lines on standard topographic maps. A sequence of computer accuracy checks was performed and then the elevations of grid points not intersected by contour lines were interpolated. The DGR system produced computer magnetic tapes which controlled the carving of plaster forms used to mold raised-relief maps. It was realized almost immediately that this relatively simple tool for carving plaster molds had enormous potential for storing, manipulating, and selectively displaying (either graphically or numerically) a vast number of terrain elevations. As the demand for the digital terrain tapes increased, DMATC began developing increasingly advanced digitizing systems and now operates the Digital Topographic Data Collection System (DTDCS). With DTDCS, two types of data elevations as contour lines and points, and stream and ridge lines are sorted, matched, and resorted to obtain a grid of elevation values for every 0.01 inch on each map (approximately 200 feet on the ground). Undefined points on the grid are found by either linear or or planar interpolation.

Geodatabase of sites, basin boundaries, and topology rules used to store drainage basin boundaries for the U.S. Geological Survey, Colorado Water Science Center

USGS Publications Warehouse

Dupree, Jean A.; Crowfoot, Richard M.

2012-01-01

This geodatabase and its component datasets are part of U.S. Geological Survey Digital Data Series 650 and were generated to store basin boundaries for U.S. Geological Survey streamgages and other sites in Colorado. The geodatabase and its components were created by the U.S. Geological Survey, Colorado Water Science Center, and are used to derive the numeric drainage areas for Colorado that are input into the U.S. Geological Survey's National Water Information System (NWIS) database and also published in the Annual Water Data Report and on NWISWeb. The foundational dataset used to create the basin boundaries in this geodatabase was the National Watershed Boundary Dataset. This geodatabase accompanies a U.S. Geological Survey Techniques and Methods report (Book 11, Section C, Chapter 6) entitled "Digital Database Architecture and Delineation Methodology for Deriving Drainage Basins, and Comparison of Digitally and Non-Digitally Derived Numeric Drainage Areas." The Techniques and Methods report details the geodatabase architecture, describes the delineation methodology and workflows used to develop these basin boundaries, and compares digitally derived numeric drainage areas in this geodatabase to non-digitally derived areas. 1. COBasins.gdb: This geodatabase contains site locations and basin boundaries for Colorado. It includes a single feature dataset, called BasinsFD, which groups the component feature classes and topology rules. 2. BasinsFD: This feature dataset in the "COBasins.gdb" geodatabase is a digital container that holds the feature classes used to archive site locations and basin boundaries as well as the topology rules that govern spatial relations within and among component feature classes. This feature dataset includes three feature classes: the sites for which basins have been delineated (the "Sites" feature class), basin bounding lines (the "BasinLines" feature class), and polygonal basin areas (the "BasinPolys" feature class). The feature dataset also stores the topology rules (the "BasinsFD_Topology") that constrain the relations within and among component feature classes. The feature dataset also forces any feature classes inside it to have a consistent projection system, which is, in this case, an Albers-Equal-Area projection system. 3. BasinsFD_Topology: This topology contains four persistent topology rules that constrain the spatial relations within the "BasinLines" feature class and between the "BasinLines" feature class and the "BasinPolys" feature classes. 4. Sites: This point feature class contains the digital representations of the site locations for which Colorado Water Science Center basin boundaries have been delineated. This feature class includes point locations for Colorado Water Science Center active (as of September 30, 2009) gages and for other sites. 5. BasinLines: This line feature class contains the perimeters of basins delineated for features in the "Sites" feature class, and it also contains information regarding the sources of lines used for the basin boundaries. 6. BasinPolys: This polygon feature class contains the polygonal basin areas delineated for features in the "Sites" feature class, and it is used to derive the numeric drainage areas published by the Colorado Water Science Center.

Reconstruction of time-varying tidal flat topography using optical remote sensing imageries

NASA Astrophysics Data System (ADS)

Tseng, Kuo-Hsin; Kuo, Chung-Yen; Lin, Tang-Huang; Huang, Zhi-Cheng; Lin, Yu-Ching; Liao, Wen-Hung; Chen, Chi-Farn

2017-09-01

Tidal flats (TFs) occupy approximately 7% of the total coastal shelf areas worldwide. However, TFs are unavailable in most global digital elevation models (DEMs) due to water-impermeable nature of existing remote sensing approaches (e.g., radar used for WorldDEM™ and Shuttle Radar Topography Mission DEM and optical stereo-pairs used for ASTER Global Digital Elevation Map Version 2). However, this problem can be circumvented using remote sensing imageries to observe land exposure at different tidal heights during each revisit. This work exploits Landsat-4/-5/-7/-8 Thematic Mapper (TM)/Enhanced TM Plus/Operational Land Imager imageries to reconstruct topography of a TF, namely, Hsiang-Shan Wetland in Taiwan, to unveil its formation and temporal changes since the 1980s. We first classify water areas by applying modified normalized difference water index to each Landsat image and normalize chances of water exposure to create an inundation probability map. This map is then scaled by tidal amplitudes extracted from DTU10 tide model to convert the probabilities into actual elevations. After building DEM at intertidal zone, a water level-area curve is established, and accuracy of DEM is validated by sea level (SL) at the timing of each Landsat snapshot. A 22-year (1992-2013) dataset composed of 227 Landsat scenes are analyzed and compared with tide gauge data. Root-mean-square differences of SL reaches 48 cm with a correlation coefficient of 0.93, indicating that the present technique is useful for constructing accurate coastal DEMs, and that products can be utilized for estimating instant SL. This study shows the possibility of exploring evolution of intertidal zones using an archive of optical remote sensing imageries. The technique developed in the present study potentially helps in quantifying SL from the start of optical remote sensing era.

Improving Frozen Precipitation Density Estimation in Land Surface Modeling

NASA Astrophysics Data System (ADS)

Sparrow, K.; Fall, G. M.

2017-12-01

The Office of Water Prediction (OWP) produces high-value water supply and flood risk planning information through the use of operational land surface modeling. Improvements in diagnosing frozen precipitation density will benefit the NWS's meteorological and hydrological services by refining estimates of a significant and vital input into land surface models. A current common practice for handling the density of snow accumulation in a land surface model is to use a standard 10:1 snow-to-liquid-equivalent ratio (SLR). Our research findings suggest the possibility of a more skillful approach for assessing the spatial variability of precipitation density. We developed a 30-year SLR climatology for the coterminous US from version 3.22 of the Daily Global Historical Climatology Network - Daily (GHCN-D) dataset. Our methods followed the approach described by Baxter (2005) to estimate mean climatological SLR values at GHCN-D sites in the US, Canada, and Mexico for the years 1986-2015. In addition to the Baxter criteria, the following refinements were made: tests were performed to eliminate SLR outliers and frequent reports of SLR = 10, a linear SLR vs. elevation trend was fitted to station SLR mean values to remove the elevation trend from the data, and detrended SLR residuals were interpolated using ordinary kriging with a spherical semivariogram model. The elevation values of each station were based on the GMTED 2010 digital elevation model and the elevation trend in the data was established via linear least squares approximation. The ordinary kriging procedure was used to interpolate the data into gridded climatological SLR estimates for each calendar month at a 0.125 degree resolution. To assess the skill of this climatology, we compared estimates from our SLR climatology with observations from the GHCN-D dataset to consider the potential use of this climatology as a first guess of frozen precipitation density in an operational land surface model. The difference in model derived estimates and GHCN-D observations were assessed using time-series graphs of 2016-2017 winter season SLR observations and climatological estimates, as well as calculating RMSE and variance between estimated and observed values.

A geospatial framework for improving the vertical accuracy of elevation models in Florida's coastal Everglades

NASA Astrophysics Data System (ADS)

Cooper, H.; Zhang, C.; Sirianni, M.

2016-12-01

South Florida relies upon the health of the Everglades, the largest subtropical wetland in North America, as a vital source of water. Since the late 1800's, this imperiled ecosystem has been highly engineered to meet human needs of flood control and water use. The Comprehensive Everglades Restoration Plan (CERP) was initiated in 2000 to restore original water flows to the Everglades and improve overall ecosystem health, while also aiming to achieve balance with human water usage. Due to subtle changes in the Everglades terrain, better vertical accuracy elevation data are needed to model groundwater and surface water levels that are integral to monitoring the effects of restoration under impacts such as sea-level rise. The current best available elevation datasets for the coastal Everglades include High Accuracy Elevation Data (HAED) and Florida Department of Emergency Management (FDEM) Light Detection and Ranging (LiDAR). However, the horizontal resolution of the HAED data is too coarse ( 400 m) for fine scale mapping, and the LiDAR data does not contain an accuracy assessment for coastal Everglades' vegetation communities. The purpose of this study is to develop a framework for generating better vertical accuracy and horizontal resolution Digital Elevation Models in the Flamingo District of Everglades National Park. In the framework, field work is conducted to collect RTK GPS and total station elevation measurements for mangrove swamp, coastal prairies, and freshwater marsh, and the proposed accuracy assessment and elevation modeling methodology is integrated with a Geographical Information System (GIS). It is anticipated that this study will provide more accurate models of the soil substrate elevation that can be used by restoration planners to better predict the future state of the Everglades ecosystem.

Information measures for terrain visualization

NASA Astrophysics Data System (ADS)

Bonaventura, Xavier; Sima, Aleksandra A.; Feixas, Miquel; Buckley, Simon J.; Sbert, Mateu; Howell, John A.

2017-02-01

Many quantitative and qualitative studies in geoscience research are based on digital elevation models (DEMs) and 3D surfaces to aid understanding of natural and anthropogenically-influenced topography. As well as their quantitative uses, the visual representation of DEMs can add valuable information for identifying and interpreting topographic features. However, choice of viewpoints and rendering styles may not always be intuitive, especially when terrain data are augmented with digital image texture. In this paper, an information-theoretic framework for object understanding is applied to terrain visualization and terrain view selection. From a visibility channel between a set of viewpoints and the component polygons of a 3D terrain model, we obtain three polygonal information measures. These measures are used to visualize the information associated with each polygon of the terrain model. In order to enhance the perception of the terrain's shape, we explore the effect of combining the calculated information measures with the supplementary digital image texture. From polygonal information, we also introduce a method to select a set of representative views of the terrain model. Finally, we evaluate the behaviour of the proposed techniques using example datasets. A publicly available framework for both the visualization and the view selection of a terrain has been created in order to provide the possibility to analyse any terrain model.

An evaluation of onshore digital elevation models for tsunami inundation modelling

NASA Astrophysics Data System (ADS)

Griffin, J.; Latief, H.; Kongko, W.; Harig, S.; Horspool, N.; Hanung, R.; Rojali, A.; Maher, N.; Fountain, L.; Fuchs, A.; Hossen, J.; Upi, S.; Dewanto, S. E.; Cummins, P. R.

2012-12-01

Tsunami inundation models provide fundamental information about coastal areas that may be inundated in the event of a tsunami along with additional parameters such as flow depth and velocity. This can inform disaster management activities including evacuation planning, impact and risk assessment and coastal engineering. A fundamental input to tsunami inundation models is adigital elevation model (DEM). Onshore DEMs vary widely in resolution, accuracy, availability and cost. A proper assessment of how the accuracy and resolution of DEMs translates into uncertainties in modelled inundation is needed to ensure results are appropriately interpreted and used. This assessment can in turn informdata acquisition strategies depending on the purpose of the inundation model. For example, lower accuracy elevation data may give inundation results that are sufficiently accurate to plan a community's evacuation route but not sufficient to inform engineering of a vertical evacuation shelters. A sensitivity study is undertaken to assess the utility of different available onshore digital elevation models for tsunami inundation modelling. We compare airborne interferometric synthetic aperture radar (IFSAR), ASTER and SRTM against high resolution (<1 m horizontal resolution, < 0.15 m vertical accuracy) LiDAR or stereo-camera data in three Indonesian locations with different coastal morphologies (Padang, West Sumatra; Palu, Central Sulawesi; and Maumere, Flores), using three different computational codes (ANUGA, TUNAMI-N3 and TsunAWI). Tsunami inundation extents modelled with IFSAR are comparable with those modelled with the high resolution datasets and with historical tsunami run-up data. Large vertical errors (> 10 m) and poor resolution of the coastline in the ASTER and SRTM elevation models cause modelled inundation to be much less compared with models using better data and with observations. Therefore we recommend that ASTER and SRTM should not be used for modelling tsunami inundation in order to determine tsunami extent or any other measure of onshore tsunami hazard. We suggest that for certain disaster management applications where the important factor is the extent of inundation, such as evacuation planning, airborne IFSAR provides a good compromise between cost and accuracy; however the representation of flow parameters such as depth and velocity is not sufficient to inform detailed engineering of structures. Differences in modelled inundation extent between digital terrain models (DTM) and digital surface models (DSM) for LiDAR, high resolution stereo-camera and airborne IFSAR data are greater than differences between the data types. The presence of trees and buildings as solid elevation in the DSM leads to underestimated inundation extents compared with observations, while removal of these features in the DTM causes more extensive inundation. Further work is needed to resolve whether DTM or DSM should be used and, in particular for DTM, how and at what spatial scale roughness should be parameterized to appropriately account for the presence of buildings and vegetation. We also test model mesh resolutions up to 0.8 m but find that there are only negligible changes in inundation extent between 0.8 and 25 m mesh resolution, even using the highest resolution elevation data.

Three-dimensional information extraction from GaoFen-1 satellite images for landslide monitoring

NASA Astrophysics Data System (ADS)

Wang, Shixin; Yang, Baolin; Zhou, Yi; Wang, Futao; Zhang, Rui; Zhao, Qing

2018-05-01

To more efficiently use GaoFen-1 (GF-1) satellite images for landslide emergency monitoring, a Digital Surface Model (DSM) can be generated from GF-1 across-track stereo image pairs to build a terrain dataset. This study proposes a landslide 3D information extraction method based on the terrain changes of slope objects. The slope objects are mergences of segmented image objects which have similar aspects; and the terrain changes are calculated from the post-disaster Digital Elevation Model (DEM) from GF-1 and the pre-disaster DEM from GDEM V2. A high mountain landslide that occurred in Wenchuan County, Sichuan Province is used to conduct a 3D information extraction test. The extracted total area of the landslide is 22.58 ha; the displaced earth volume is 652,100 m3; and the average sliding direction is 263.83°. The accuracies of them are 0.89, 0.87 and 0.95, respectively. Thus, the proposed method expands the application of GF-1 satellite images to the field of landslide emergency monitoring.

Data layer integration for the national map of the united states

USGS Publications Warehouse

Usery, E.L.; Finn, M.P.; Starbuck, M.

2009-01-01

The integration of geographic data layers in multiple raster and vector formats, from many different organizations and at a variety of resolutions and scales, is a significant problem for The National Map of the United States being developed by the U.S. Geological Survey. Our research has examined data integration from a layer-based approach for five of The National Map data layers: digital orthoimages, elevation, land cover, hydrography, and transportation. An empirical approach has included visual assessment by a set of respondents with statistical analysis to establish the meaning of various types of integration. A separate theoretical approach with established hypotheses tested against actual data sets has resulted in an automated procedure for integration of specific layers and is being tested. The empirical analysis has established resolution bounds on meanings of integration with raster datasets and distance bounds for vector data. The theoretical approach has used a combination of theories on cartographic transformation and generalization, such as T??pfer's radical law, and additional research concerning optimum viewing scales for digital images to establish a set of guiding principles for integrating data of different resolutions.

The influence of data characteristics on detecting wetland/stream surface-water connections in the Delmarva Peninsula, Maryland and Delaware

USGS Publications Warehouse

Vanderhoof, Melanie; Distler, Hayley; Lang, Megan W.; Alexander, Laurie C.

2018-01-01

The dependence of downstream waters on upstream ecosystems necessitates an improved understanding of watershed-scale hydrological interactions including connections between wetlands and streams. An evaluation of such connections is challenging when, (1) accurate and complete datasets of wetland and stream locations are often not available and (2) natural variability in surface-water extent influences the frequency and duration of wetland/stream connectivity. The Upper Choptank River watershed on the Delmarva Peninsula in eastern Maryland and Delaware is dominated by a high density of small, forested wetlands. In this analysis, wetland/stream surface water connections were quantified using multiple wetland and stream datasets, including headwater streams and depressions mapped from a lidar-derived digital elevation model. Surface-water extent was mapped across the watershed for spring 2015 using Landsat-8, Radarsat-2 and Worldview-3 imagery. The frequency of wetland/stream connections increased as a more complete and accurate stream dataset was used and surface-water extent was included, in particular when the spatial resolution of the imagery was finer (i.e., <10 m). Depending on the datasets used, 12–60% of wetlands by count (21–93% of wetlands by area) experienced surface-water interactions with streams during spring 2015. This translated into a range of 50–94% of the watershed contributing direct surface water runoff to streamflow. This finding suggests that our interpretation of the frequency and duration of wetland/stream connections will be influenced not only by the spatial and temporal characteristics of wetlands, streams and potential flowpaths, but also by the completeness, accuracy and resolution of input datasets.

Status report for the 3D Elevation Program, 2013-2014

USGS Publications Warehouse

Lukas, Vicki; Eldridge, Diane F.; Jason, Allyson L.; Saghy, David L.; Steigerwald, Pamela R.; Stoker, Jason M.; Sugarbaker, Larry J.; Thunen, Diana R.

2015-09-25

The 3D Elevation Program (3DEP) goal is to acquire, manage, and distribute enhanced three-dimensional elevation data for the Nation and U.S. territories by 2023. This status report covers implementation activities during 2013–2014 to include meeting funding objectives, developing a management structure, modernizing systems, and collecting and producing initial 3DEP data and products. The Nation will not have complete coverage of 3DEP quality data until 2023 assuming that sufficient funding is available. In spite of the overall condition of government budgets, the 3DEP initiative has gained widespread support and had incremental budget success to include supplemental funding resulting from natural disasters. The 3DEP Executive Forum and a wide range of professional organizations are actively working to maintain support for the program. The systems that have been developed to support increasing acquisition and processing levels are largely in place. The first 3DEP quality datasets were released to the public in late 2014. In addition, light detection and ranging (lidar), interferometric synthetic aperture radar (ifsar), and digital elevation models (DEMs) acquired before 2014 are all supported within the new infrastructure and available for download. Research is ongoing to expand the suite of products and services, and to increase overall throughput and data management efficiency. Emerging technologies may result in lower acquisition costs in the future. Elevation data acquired by 3DEP partnerships will be available through The National Map representing one of the largest and most comprehensive databases publicly available for the United States. 

Topographic Structure from Motion

NASA Astrophysics Data System (ADS)

Fonstad, M. A.; Dietrich, J. T.; Courville, B. C.; Jensen, J.; Carbonneau, P.

2011-12-01

The production of high-resolution topographic datasets is of increasing concern and application throughout the geomorphic sciences, and river science is no exception. Consequently, a wide range of topographic measurement methods have evolved. Despite the range of available methods, the production of high resolution, high quality digital elevation models (DEMs) generally requires a significant investment in personnel time, hardware and/or software. However, image-based methods such as digital photogrammetry have steadily been decreasing in costs. Initially developed for the purpose of rapid, inexpensive and easy three dimensional surveys of buildings or small objects, the "structure from motion" photogrammetric approach (SfM) is a purely image based method which could deliver a step-change if transferred to river remote sensing, and requires very little training and is extremely inexpensive. Using the online SfM program Microsoft Photosynth, we have created high-resolution digital elevation models (DEM) of rivers from ordinary photographs produced from a multi-step workflow that takes advantage of free and open source software. This process reconstructs real world scenes from SfM algorithms based on the derived positions of the photographs in three-dimensional space. One of the products of the SfM process is a three-dimensional point cloud of features present in the input photographs. This point cloud can be georeferenced from a small number of ground control points collected via GPS in the field. The georeferenced point cloud can then be used to create a variety of digital elevation model products. Among several study sites, we examine the applicability of SfM in the Pedernales River in Texas (USA), where several hundred images taken from a hand-held helikite are used to produce DEMs of the fluvial topographic environment. This test shows that SfM and low-altitude platforms can produce point clouds with point densities considerably better than airborne LiDAR, with horizontal and vertical precision in the centimeter range, and with very low capital and labor costs and low expertise levels. Advanced structure from motion software (such as Bundler and OpenSynther) are currently under development and should increase the density of topographic points rivaling those of terrestrial laser scanning when using images shot from low altitude platforms such as helikites, poles, remote-controlled aircraft and rotocraft, and low-flying manned aircraft. Clearly, the development of this set of inexpensive and low-required-expertise tools has the potential to fundamentally shift the production of digital fluvial topography from a capital-intensive enterprise of a low number of researchers to a low-cost exercise of many river researchers.

A method for normalizing pathology images to improve feature extraction for quantitative pathology.

PubMed

Tam, Allison; Barker, Jocelyn; Rubin, Daniel

2016-01-01

With the advent of digital slide scanning technologies and the potential proliferation of large repositories of digital pathology images, many research studies can leverage these data for biomedical discovery and to develop clinical applications. However, quantitative analysis of digital pathology images is impeded by batch effects generated by varied staining protocols and staining conditions of pathological slides. To overcome this problem, this paper proposes a novel, fully automated stain normalization method to reduce batch effects and thus aid research in digital pathology applications. Their method, intensity centering and histogram equalization (ICHE), normalizes a diverse set of pathology images by first scaling the centroids of the intensity histograms to a common point and then applying a modified version of contrast-limited adaptive histogram equalization. Normalization was performed on two datasets of digitized hematoxylin and eosin (H&E) slides of different tissue slices from the same lung tumor, and one immunohistochemistry dataset of digitized slides created by restaining one of the H&E datasets. The ICHE method was evaluated based on image intensity values, quantitative features, and the effect on downstream applications, such as a computer aided diagnosis. For comparison, three methods from the literature were reimplemented and evaluated using the same criteria. The authors found that ICHE not only improved performance compared with un-normalized images, but in most cases showed improvement compared with previous methods for correcting batch effects in the literature. ICHE may be a useful preprocessing step a digital pathology image processing pipeline.

Development of large scale riverine terrain-bathymetry dataset by integrating NHDPlus HR with NED,CoNED and HAND data

NASA Astrophysics Data System (ADS)

Li, Z.; Clark, E. P.

2017-12-01

Large scale and fine resolution riverine bathymetry data is critical for flood inundation modelingbut not available over the continental United States (CONUS). Previously we implementedbankfull hydraulic geometry based approaches to simulate bathymetry for individual riversusing NHDPlus v2.1 data and 10 m National Elevation Dataset (NED). USGS has recentlydeveloped High Resolution NHD data (NHDPlus HR Beta) (USGS, 2017), and thisenhanced dataset has a significant improvement on its spatial correspondence with 10 m DEM.In this study, we used this high resolution data, specifically NHDFlowline and NHDArea,to create bathymetry/terrain for CONUS river channels and floodplains. A software packageNHDPlus Inundation Modeler v5.0 Beta was developed for this project as an Esri ArcGIShydrological analysis extension. With the updated tools, raw 10 m DEM was first hydrologicallytreated to remove artificial blockages (e.g., overpasses, bridges and eve roadways, etc.) usinglow pass moving window filters. Cross sections were then automatically constructed along eachflowline to extract elevation from the hydrologically treated DEM. In this study, river channelshapes were approximated using quadratic curves to reduce uncertainties from commonly usedtrapezoids. We calculated underneath water channel elevation at each cross section samplingpoint using bankfull channel dimensions that were estimated from physiographicprovince/division based regression equations (Bieger et al. 2015). These elevation points werethen interpolated to generate bathymetry raster. The simulated bathymetry raster wasintegrated with USGS NED and Coastal National Elevation Database (CoNED) (whereveravailable) to make seamless terrain-bathymetry dataset. Channel bathymetry was alsointegrated to the HAND (Height above Nearest Drainage) dataset to improve large scaleinundation modeling. The generated terrain-bathymetry was processed at WatershedBoundary Dataset Hydrologic Unit 4 (WBDHU4) level.

National requirements for improved elevation data

USGS Publications Warehouse

Snyder, Gregory I.; Sugarbaker, Larry J.; Jason, Allyson L.; Maune, David F.

2014-01-01

This report presents the results of surveys, structured interviews, and workshops conducted to identify key national requirements for improved elevation data for the United States and its territories, including coastlines. Organizations also identified and reported the expected economic benefits that would be realized if their requirements for improved elevation were met (appendixes 1–3). This report describes the data collection methodology and summarizes the findings. Participating organizations included 34 Federal agencies, 50 States and two territories, and a sampling of local governments, tribes, and nongovernmental orgnizations. The nongovernmental organizations included The Nature Conservancy and a sampling of private sector businesses. These data were collected in 2010-2011 as part of the National Enhanced Elevation Assessment (NEEA), a study to identify program alternatives for better meeting the Nation’s elevation data needs. NEEA tasks included the collection of national elevation requirements; analysis of the benefits and costs of meeting these requirements; assessment of emerging elevation technologies, lifecycle data management needs, and costs for managing and distributing a national-scale dataset and derived products; and candidate national elevation program alternatives that balance costs and benefits in meeting the Nation’s elevation requirements. The NEEA was sponsored by the National Digital Elevation Program (NDEP), a government coordination body with the U.S. Geological Survey (USGS) as managing partner that includes the National Geospatial-Intelligence Agency (NGA), the Federal Emergency Management Agency (FEMA), the Natural Resources Conservation Service (NRCS), the U.S. Army Corps of Engineers (USACE), and the National Oceanic and Atmospheric Administration (NOAA), among the more than a dozen agencies and organizations. The term enhanced elevation data as used in this report refers broadly to three-dimensional measurements of land or submerged topography, built features, vegetation structure, and other landscape detail. Additional information about NEEA and its later use in the development of a 3D Elevation Program (3DEP) can be found at http://nationalmap.gov/3DEP/index.html.

Creating Digital Elevation Model Using a Mobile Device

NASA Astrophysics Data System (ADS)

Durmaz, A. İ.

2017-11-01

DEM (Digital Elevation Models) is the best way to interpret topography on the ground. In recent years, lidar technology allows to create more accurate elevation models. However, the problem is this technology is not common all over the world. Also if Lidar data are not provided by government agencies freely, people have to pay lots of money to reach these point clouds. In this article, we will discuss how we can create digital elevation model from less accurate mobile devices' GPS data. Moreover, we will evaluate these data on the same mobile device which we collected data to reduce cost of this modeling.

Calculation and Error Analysis of a Digital Elevation Model of Hofsjokull, Iceland from SAR Interferometry

NASA Technical Reports Server (NTRS)

Barton, Jonathan S.; Hall, Dorothy K.; Sigurosson, Oddur; Williams, Richard S., Jr.; Smith, Laurence C.; Garvin, James B.

1999-01-01

Two ascending European Space Agency (ESA) Earth Resources Satellites (ERS)-1/-2 tandem-mode, synthetic aperture radar (SAR) pairs are used to calculate the surface elevation of Hofsjokull, an ice cap in central Iceland. The motion component of the interferometric phase is calculated using the 30 arc-second resolution USGS GTOPO30 global digital elevation product and one of the ERS tandem pairs. The topography is then derived by subtracting the motion component from the other tandem pair. In order to assess the accuracy of the resultant digital elevation model (DEM), a geodetic airborne laser-altimetry swath is compared with the elevations derived from the interferometry. The DEM is also compared with elevations derived from a digitized topographic map of the ice cap from the University of Iceland Science Institute. Results show that low temporal correlation is a significant problem for the application of interferometry to small, low-elevation ice caps, even over a one-day repeat interval, and especially at the higher elevations. Results also show that an uncompensated error in the phase, ramping from northwest to southeast, present after tying the DEM to ground-control points, has resulted in a systematic error across the DEM.

Calculation and error analysis of a digital elevation model of Hofsjokull, Iceland, from SAR interferometry

USGS Publications Warehouse

Barton, Jonathan S.; Hall, Dorothy K.; Sigurðsson, Oddur; Williams, Richard S.; Smith, Laurence C.; Garvin, James B.; Taylor, Susan; Hardy, Janet

1999-01-01

Two ascending European Space Agency (ESA) Earth Resources Satellites (ERS)-1/-2 tandem-mode, synthetic aperture radar (SAR) pairs are used to calculate the surface elevation of Hofsjokull, an ice cap in central Iceland. The motion component of the interferometric phase is calculated using the 30 arc-second resolution USGS GTOPO30 global digital elevation product and one of the ERS tandem pairs. The topography is then derived by subtracting the motion component from the other tandem pair. In order to assess the accuracy of the resultant digital elevation model (DEM), a geodetic airborne laser-altimetry swath is compared with the elevations derived from the interferometry. The DEM is also compared with elevations derived from a digitized topographic map of the ice cap from the University of Iceland Science Institute. Results show that low temporal correlation is a significant problem for the application of interferometry to small, low-elevation ice caps, even over a one-day repeat interval, and especially at the higher elevations. Results also show that an uncompensated error in the phase, ramping from northwest to southeast, present after tying the DEM to ground-control points, has resulted in a systematic error across the DEM.

Digital elevation modeling via curvature interpolation for lidar data

USDA-ARS?s Scientific Manuscript database

Digital elevation model (DEM) is a three-dimensional (3D) representation of a terrain's surface - for a planet (including Earth), moon, or asteroid - created from point cloud data which measure terrain elevation. Its modeling requires surface reconstruction for the scattered data, which is an ill-p...

Blood Lead Concentrations of Children in the United States: A Comparison of States Using Two Very Large Databases.

PubMed

Shah, Keneil K; Oleske, James M; Gomez, Hernan F; Davidow, Amy L; Bogden, John D

2017-06-01

To determine whether there are substantial differences by state between 2 large datasets in the proportion of children with elevated blood lead levels (BLLs); to identify states in which the percentage of elevated BLLs is high in either or both datasets; and to compare the percentage of elevated BLLs in individual states with those of children living in Flint, Michigan, during the months when these children were exposed to lead-contaminated drinking water. Tables of BLLs for individual states from the Quest Diagnostics and the Centers for Disease Control and Prevention datasets for 2014-2015, containing more than 3 million BLLs of young children?

Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: Mean Infiltration-Excess Overland Flow, 2002

USGS Publications Warehouse

Wieczorek, Michael; LaMotte, Andrew E.

2010-01-01

This tabular data set represents the mean value for infiltration-excess overland flow as estimated by the watershed model TOPMODEL, compiled for every catchment of NHDPlus for the conterminous United States. Infiltration-excess overland flow, expressed as a percent of total overland flow, is simulated in TOPMODEL as precipitation that exceeds the infiltration capacity of the soil and enters the stream channel. The source data set is Infiltration-Excess Overland Flow Estimated by TOPMODEL for the Conterminous United States (Wolock, 2003). The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

Attributes for NHDPlus catchments (version 1.1) for the conterminous United States: normalized atmospheric deposition for 2002, Total Inorganic Nitrogen

USGS Publications Warehouse

Wieczorek, Michael; LaMotte, Andrew E.

2010-01-01

This data set represents the average normalized atmospheric (wet) deposition, in kilograms, of Total Inorganic Nitrogen for the year 2002 compiled for every catchment of NHDPlus for the conterminous United States. Estimates of Total Inorganic Nitrogen deposition are based on National Atmospheric Deposition Program (NADP) measurements (B. Larsen, U.S. Geological Survey, written commun., 2007). De-trending methods applied to the year 2002 are described in Alexander and others, 2001. NADP site selection met the following criteria: stations must have records from 1995 to 2002 and have a minimum of 30 observations. The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: Normalized Atmospheric Deposition for 2002, Ammonium (NH4)

USGS Publications Warehouse

Wieczorek, Michael; LaMotte, Andrew E.

2010-01-01

This data set represents the average normalized atmospheric (wet) deposition, in kilograms, of Ammonium (NH4) for the year 2002 compiled for every catchment of NHDPlus for the conterminous United States. Estimates of NH4 deposition are based on National Atmospheric Deposition Program (NADP) measurements (B. Larsen, U.S. Geological Survey, written commun., 2007). De-trending methods applied to the year 2002 are described in Alexander and others, 2001. NADP site selection met the following criteria: stations must have records from 1995 to 2002 and have a minimum of 30 observations. The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: Normalized Atmospheric Deposition for 2002, Nitrate (NO3)

USGS Publications Warehouse

Wieczorek, Michael; LaMotte, Andrew E.

2010-01-01

This data set represents the average normalized atmospheric (wet) deposition, in kilograms, of Nitrate (NO3) for the year 2002 compiled for every catchment of NHDPlus for the conterminous United States. Estimates of NO3 deposition are based on National Atmospheric Deposition Program (NADP) measurements (B. Larsen, U.S. Geological Survey, written commun., 2007). De-trending methods applied to the year 2002 are described in Alexander and others, 2001. NADP site selection met the following criteria: stations must have records from 1995 to 2002 and have a minimum of 30 observations. The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

Dynamic Floodplain representation in hydrologic flood forecasting using WRF-Hydro modeling framework

NASA Astrophysics Data System (ADS)

Gangodagamage, C.; Li, Z.; Maitaria, K.; Islam, M.; Ito, T.; Dhondia, J.

2016-12-01

Floods claim more lives and damage more property than any other category of natural disaster in the Continental United States. A system that can demarcate local flood boundaries dynamically could help flood prone communities prepare for and even prevent from catastrophic flood events. Lateral distance from the centerline of the river to the right and left floodplains for the water levels coming out of the models at each grid location have not been properly integrated with the national hydrography dataset (NHDPlus). The NHDPlus dataset represents the stream network with feature classes such as rivers, tributaries, canals, lakes, ponds, dams, coastlines, and stream gages. The NHDPlus dataset consists of approximately 2.7 million river reaches defining how surface water drains to the ocean. These river reaches have upstream and downstream nodes and basic parameters such as flow direction, drainage area, reach slope etc. We modified an existing algorithm (Gangodagamage et al., 2007) to provide lateral distance from the centerline of the river to the right and left floodplains for the flows simulated by models. Previous work produced floodplain boundaries for static river stages (i.e. 3D metric: distance along the main stem, flow depth, lateral distance from river center line). Our new approach introduces the floodplain boundary for variable water levels at each reach with the fourth dimension, time. We use modeled flows from WRF-Hydro and demarcate the right and left lateral boundaries of inundation dynamically by appropriately mapping discharges into hydraulically corrected stages. Backwater effects from the mainstem to tributaries are considered and proper corrections are applied for the tributary inundations. We obtained river stages by optimizing reach level channel parameters using newly developed stream flow routing algorithm. Non uniform inundations are mapped at each NHDplus reach (upstream and downstream nodes) and spatial interpolation is carried out on a normalized digital elevation model (always streams are at zero elevations) to obtain the smooth flood boundaries between adjacent reaches. The validation of the dynamic inundation boundaries is performed using multi-temporal satellite datasets as well as HEC-RAS hydrodynamic model results for selected streams for previous flood events.

Avulsion research using flume experiments and highly accurate and temporal-rich SfM datasets

NASA Astrophysics Data System (ADS)

Javernick, L.; Bertoldi, W.; Vitti, A.

2017-12-01

SfM's ability to produce high-quality, large-scale digital elevation models (DEMs) of complicated and rapidly evolving systems has made it a valuable technique for low-budget researchers and practitioners. While SfM has provided valuable datasets that capture single-flood event DEMs, there is an increasing scientific need to capture higher temporal resolution datasets that can quantify the evolutionary processes instead of pre- and post-flood snapshots. However, flood events' dangerous field conditions and image matching challenges (e.g. wind, rain) prevent quality SfM-image acquisition. Conversely, flume experiments offer opportunities to document flood events, but achieving consistent and accurate DEMs to detect subtle changes in dry and inundated areas remains a challenge for SfM (e.g. parabolic error signatures).This research aimed at investigating the impact of naturally occurring and manipulated avulsions on braided river morphology and on the encroachment of floodplain vegetation, using laboratory experiments. This required DEMs with millimeter accuracy and precision and at a temporal resolution to capture the processes. SfM was chosen as it offered the most practical method. Through redundant local network design and a meticulous ground control point (GCP) survey with a Leica Total Station in red laser configuration (reported 2 mm accuracy), the SfM residual errors compared to separate ground truthing data produced mean errors of 1.5 mm (accuracy) and standard deviations of 1.4 mm (precision) without parabolic error signatures. Lighting conditions in the flume were limited to uniform, oblique, and filtered LED strips, which removed glint and thus improved bed elevation mean errors to 4 mm, but errors were further reduced by means of an open source software for refraction correction. The obtained datasets have provided the ability to quantify how small flood events with avulsion can have similar morphologic and vegetation impacts as large flood events without avulsion. Further, this research highlights the potential application of SfM in the laboratory and ability to document physical and biological processes at greater spatial and temporal resolution. Marie Sklodowska-Curie Individual Fellowship: River-HMV, 656917

Spatial downscaling algorithm of TRMM precipitation based on multiple high-resolution satellite data for Inner Mongolia, China

NASA Astrophysics Data System (ADS)

Duan, Limin; Fan, Keke; Li, Wei; Liu, Tingxi

2017-12-01

Daily precipitation data from 42 stations in Inner Mongolia, China for the 10 years period from 1 January 2001 to 31 December 2010 was utilized along with downscaled data from the Tropical Rainfall Measuring Mission (TRMM) with a spatial resolution of 0.25° × 0.25° for the same period based on the statistical relationships between the normalized difference vegetation index (NDVI), meteorological variables, and digital elevation models (https://en.wikipedia.org/wiki/Digital_elevation_model) (DEM) using the leave-one-out (LOO) cross validation method and multivariate step regression. The results indicate that (1) TRMM data can indeed be used to estimate annual precipitation in Inner Mongolia and there is a linear relationship between annual TRMM and observed precipitation; (2) there is a significant relationship between TRMM-based precipitation and predicted precipitation, with a spatial resolution of 0.50° × 0.50°; (3) NDVI and temperature are important factors influencing the downscaling of TRMM precipitation data for DEM and the slope is not the most significant factor affecting the downscaled TRMM data; and (4) the downscaled TRMM data reflects spatial patterns in annual precipitation reasonably well, showing less precipitation falling in west Inner Mongolia and more in the south and southeast. The new approach proposed here provides a useful alternative for evaluating spatial patterns in precipitation and can thus be applied to generate a more accurate precipitation dataset to support both irrigation management and the conservation of this fragile grassland ecosystem.

A fast and robust bulk-loading algorithm for indexing very large digital elevation datasets II. Experimental results

NASA Astrophysics Data System (ADS)

Rodríguez, Félix R.; Barrena, Manuel

2011-07-01

The spatial indexing of eventually all the available topographic information of Earth is a highly valuable tool for different geoscientific application domains. The Shuttle Radar Topography Mission (SRTM) collected and made available to the public one of the world's largest digital elevation models (DEMs). With the aim of providing on easier and faster access to these data by improving their further analysis and processing, we have indexed the SRTM DEM by means of a spatial index based on the kd-tree data structure, called the Q-tree. This paper is the second in a two-part series that includes a thorough performance analysis to validate the bulk-load algorithm efficiency of the Q-tree. We investigate performance measuring elapsed time in different contexts, analyzing disk space usage, testing response time with typical queries, and validating the final index structure balance. In addition, the paper includes performance comparisons with Oracle 11g that helps to understand the real cost of our proposal. Our tests prove that the proposed algorithm outperforms Oracle 11g using around a 9% of the elapsed time, taking six times less storage with more than 96% of page utilization, and getting faster response times to spatial queries issued on 4.5 million points. In addition to this, the behavior of the spatial index has been successfully tested on both an open GIS (VT Builder) and a visualizer tool derived from the previous one.

Bathymetry and digital elevation models of Coyote Creek and Alviso Slough, South San Francisco Bay, California

USGS Publications Warehouse

Foxgrover, Amy C.; Finlayson, David P.; Jaffe, Bruce E.; Fregoso, Theresa A.

2012-01-05

In 2010 the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center completed three cruises to map the bathymetry of the main channel and shallow intertidal mudflats in the southernmost part of south San Francisco Bay. The three surveys were merged to generate comprehensive maps of Coyote Creek (from Calaveras Point east to the railroad bridge) and Alviso Slough (from the bay to the town of Alviso) to establish baseline bathymetry prior to the breaching of levees adjacent to Alviso and Guadalupe Sloughs as part of the South Bay Salt Pond Restoration Project (http://www.southbayrestoration.org). Since 2010 the USGS has conducted twelve additional surveys to monitor bathymetric change in this region as restoration progresses.The bathymetry surveys were conducted using the state-of-the-art research vessel R/V Parke Snavely outfitted with an interferometric sidescan sonar for swath mapping in extremely shallow water. This publication provides high-resolution bathymetric data collected by the USGS. For the 2010 baseline survey we have merged the bathymetry with aerial lidar data that were collected for the USGS during the same time period to create a seamless, high-resolution digital elevation model (DEM) of the study area. The series of bathymetry datasets are provided at 1 m resolution and the 2010 bathymetric/topographic DEM at 2 m resolution. The data are formatted as both X, Y, Z text files and ESRI Arc ASCII files that are accompanied by Federal Geographic Data Committee (FGDC) compliant metadata.

Multi-source Geospatial Data Analysis with Google Earth Engine

NASA Astrophysics Data System (ADS)

Erickson, T.

2014-12-01

The Google Earth Engine platform is a cloud computing environment for data analysis that combines a public data catalog with a large-scale computational facility optimized for parallel processing of geospatial data. The data catalog is a multi-petabyte archive of georeferenced datasets that include images from Earth observing satellite and airborne sensors (examples: USGS Landsat, NASA MODIS, USDA NAIP), weather and climate datasets, and digital elevation models. Earth Engine supports both a just-in-time computation model that enables real-time preview and debugging during algorithm development for open-ended data exploration, and a batch computation mode for applying algorithms over large spatial and temporal extents. The platform automatically handles many traditionally-onerous data management tasks, such as data format conversion, reprojection, and resampling, which facilitates writing algorithms that combine data from multiple sensors and/or models. Although the primary use of Earth Engine, to date, has been the analysis of large Earth observing satellite datasets, the computational platform is generally applicable to a wide variety of use cases that require large-scale geospatial data analyses. This presentation will focus on how Earth Engine facilitates the analysis of geospatial data streams that originate from multiple separate sources (and often communities) and how it enables collaboration during algorithm development and data exploration. The talk will highlight current projects/analyses that are enabled by this functionality.https://earthengine.google.org

Deep learning in breast cancer risk assessment: evaluation of convolutional neural networks on a clinical dataset of full-field digital mammograms.

PubMed

Li, Hui; Giger, Maryellen L; Huynh, Benjamin Q; Antropova, Natalia O

2017-10-01

To evaluate deep learning in the assessment of breast cancer risk in which convolutional neural networks (CNNs) with transfer learning are used to extract parenchymal characteristics directly from full-field digital mammographic (FFDM) images instead of using computerized radiographic texture analysis (RTA), 456 clinical FFDM cases were included: a "high-risk" BRCA1/2 gene-mutation carriers dataset (53 cases), a "high-risk" unilateral cancer patients dataset (75 cases), and a "low-risk dataset" (328 cases). Deep learning was compared to the use of features from RTA, as well as to a combination of both in the task of distinguishing between high- and low-risk subjects. Similar classification performances were obtained using CNN [area under the curve [Formula: see text]; standard error [Formula: see text

Setting up a hydrological model based on global data for the Ayeyarwady basin in Myanmar

NASA Astrophysics Data System (ADS)

ten Velden, Corine; Sloff, Kees; Nauta, Tjitte

2017-04-01

The use of global datasets in local hydrological modelling can be of great value. It opens up the possibility to include data for areas where local data is not or only sparsely available. In hydrological modelling the existence of both static physical data such as elevation and land use, and dynamic meteorological data such as precipitation and temperature, is essential for setting up a hydrological model, but often such data is difficult to obtain at the local level. For the Ayeyarwady catchment in Myanmar a distributed hydrological model (Wflow: https://github.com/openstreams/wflow) was set up with only global datasets, as part of a water resources study. Myanmar is an emerging economy, which has only recently become more receptive to foreign influences. It has a very limited hydrometeorological measurement network, with large spatial and temporal gaps, and data that are of uncertain quality and difficult to obtain. The hydrological model was thus set up based on resampled versions of the SRTM digital elevation model, the GlobCover land cover dataset and the HWSD soil dataset. Three global meteorological datasets were assessed and compared for use in the hydrological model: TRMM, WFDEI and MSWEP. The meteorological datasets were assessed based on their conformity with several precipitation station measurements, and the overall model performance was assessed by calculating the NSE and RVE based on discharge measurements of several gauging stations. The model was run for the period 1979-2012 on a daily time step, and the results show an acceptable applicability of the used global datasets in the hydrological model. The WFDEI forcing dataset gave the best results, with a NSE of 0.55 at the outlet of the model and a RVE of 8.5%, calculated over the calibration period 2006-2012. As a general trend the modelled discharge at the upstream stations tends to be underestimated, and at the downstream stations slightly overestimated. The quality of the discharge measurements that form the basis for the performance calculations is uncertain; data analysis suggests that rating curves are not frequently updated. The modelling results are not perfect and there is ample room for improvement, but the results are reasonable given the notion that setting up a hydrological model for this area would not have been possible without the use of global datasets due to the lack of available local data. The resulting hydrological model then enabled the set-up of the RIBASIM water allocation model for the Ayeyarwady basin in order to assess its water resources. The study discussed here is a first step; ideally this is followed up by a more thorough calibration and validation with the limited local measurements available, e.g. a precipitation correction based on the available rainfall measurements, to ensure the integration of global and local data.

Integrating terrestrial LiDAR and stereo photogrammetry to map the Tolay lakebed in northern San Francisco Bay

USGS Publications Warehouse

Woo, Isa; Storesund,; Takekawa, John Y.; Gardiner, Rachel J.; Ehret,

2009-01-01

The Tolay Creek Watershed drains approximately 3,520 ha along the northern edge of San Francisco Bay. Surrounded by a mosaic of open space conservation easements and public wildlife areas, it is one of the only watersheds in this urbanized estuary that is protected from its headwaters to the bay. Tolay Lake is a seasonal, spring-fed lake found in the upper watershed that historically extended over 120 ha. Although the lakebed was farmed since the early 1860s, the majority of the lakebed was recently acquired by the Sonoma County Regional Parks Department to restore its natural habitat values. As part of the restoration planning process, we produced a digital elevation model (DEM) of the historic extent of Tolay Lake by integrating terrestrial LiDAR (light detection and ranging) and stereo photogrammetry datasets, and real-time kinematic (RTK) global positioning system (GPS) surveys. We integrated the data, generated a DEM of the lakebed and upland areas, and analyzed errors. The accuracy of the composite DEM was verified using spot elevations obtained from the RTK GPS. Thus, we found that by combining photogrammetry, terrestrial LiDAR, and RTK GPS, we created an accurate baseline elevation map to use in watershed restoration planning and design.

Bathymetric and underwater video survey of Lower Granite Reservoir and vicinity, Washington and Idaho, 2009-10

USGS Publications Warehouse

Williams, Marshall L.; Fosness, Ryan L.; Weakland, Rhonda J.

2012-01-01

The U.S. Geological Survey conducted a bathymetric survey of the Lower Granite Reservoir, Washington, using a multibeam echosounder, and an underwater video mapping survey during autumn 2009 and winter 2010. The surveys were conducted as part of the U.S. Army Corps of Engineer's study on sediment deposition and control in the reservoir. The multibeam echosounder survey was performed in 1-mile increments between river mile (RM) 130 and 142 on the Snake River, and between RM 0 and 2 on the Clearwater River. The result of the survey is a digital elevation dataset in ASCII coordinate positioning data (easting, northing, and elevation) useful in rendering a 3×3-foot point grid showing bed elevation and reservoir geomorphology. The underwater video mapping survey was conducted from RM 107.73 to 141.78 on the Snake River and RM 0 to 1.66 on the Clearwater River, along 61 U.S. Army Corps of Engineers established cross sections, and dredge material deposit transects. More than 900 videos and 90 bank photographs were used to characterize the sediment facies and ground-truth the multibeam echosounder data. Combined, the surveys were used to create a surficial sediment facies map that displays type of substrate, level of embeddedness, and presence of silt.

ASTER Global Digital Elevation Model GDEM

NASA Image and Video Library

2009-06-29

NASA and Japan Ministry of Economy, Trade and Industry METI released the Advanced Spaceborne Thermal Emission and Reflection Radiometer ASTER Global Digital Elevation Model GDEM to the worldwide public on June 29, 2009.

Explain the CERES file naming convention

Atmospheric Science Data Center

2014-12-08

... using the dataset name, configuration code and date information which make each file name unique. A Dataset name consists ... 6-digit file and software version management code number - 120145 Date in the form YYYYMMDDHH ...

Topographic Map of Quadrangle 3568, Polekhomri (503) and Charikar (504) Quadrangles, Afghanistan

USGS Publications Warehouse

Bohannon, Robert G.

2006-01-01

This map was produced from several larger digital datasets. Topography was derived from Shuttle Radar Topography Mission (SRTM) 85-meter digital data. Gaps in the original dataset were filled with data digitized from contours on 1:200,000-scale Soviet General Staff Sheets (1978-1997). Contours were generated by cubic convolution averaged over four pixels using TNTmips surface-modeling capabilities. Minor artifacts resulting from the auto-contouring technique are present. Streams were auto-generated from the SRTM data in TNTmips as flow paths. Flow paths were limited in number by their Horton value on a quadrangle-by-quadrangle basis. Peak elevations were averaged over an area measuring 85 m by 85 m (represented by one pixel), and they are slightly lower than the highest corresponding point on the ground. Cultural data were extracted from files downloaded from the Afghanistan Information Management Service (AIMS) Web site (http://www.aims.org.af). The AIMS files were originally derived from maps produced by the Afghanistan Geodesy and Cartography Head Office (AGCHO). Because cultural features were not derived from the SRTM base, they do not match it precisely. Province boundaries are not exactly located. This map is part of a series that includes a geologic map, a topographic map, a Landsat natural-color-image map, and a Landsat false-color-image map for the USGS/AGS (Afghan Geological Survey) quadrangles covering Afghanistan. The maps for any given quadrangle have the same open-file number but a different letter suffix, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively. The open-file report (OFR) numbers for each quadrangle range in sequence from 1092 - 1123. The present map series is to be followed by a second series, in which the geology is reinterpreted on the basis of analysis of remote-sensing data, limited fieldwork, and library research. The second series is to be produced by the USGS in cooperation with the AGS and AGCHO.

Topographic Map of Quadrangle 3468, Chak Wardak Syahgerd (509) and Kabul (510) Quadrangles, Afghanistan

USGS Publications Warehouse

Bohannon, Robert G.

2006-01-01

This map was produced from several larger digital datasets. Topography was derived from Shuttle Radar Topography Mission (SRTM) 85-meter digital data. Gaps in the original dataset were filled with data digitized from contours on 1:200,000-scale Soviet General Staff Sheets (1978-1997). Contours were generated by cubic convolution averaged over four pixels using TNTmips surface-modeling capabilities. Minor artifacts resulting from the auto-contouring technique are present. Streams were auto-generated from the SRTM data in TNTmips as flow paths. Flow paths were limited in number by their Horton value on a quadrangle-by-quadrangle basis. Peak elevations were averaged over an area measuring 85 m by 85 m (represented by one pixel), and they are slightly lower than the highest corresponding point on the ground. Cultural data were extracted from files downloaded from the Afghanistan Information Management Service (AIMS) Web site (http://www.aims.org.af). The AIMS files were originally derived from maps produced by the Afghanistan Geodesy and Cartography Head Office (AGCHO). Because cultural features were not derived from the SRTM base, they do not match it precisely. Province boundaries are not exactly located. This map is part of a series that includes a geologic map, a topographic map, a Landsat natural-color-image map, and a Landsat false-color-image map for the USGS/AGS (Afghan Geological Survey) quadrangles covering Afghanistan. The maps for any given quadrangle have the same open-file number but a different letter suffix, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively. The open-file report (OFR) numbers for each quadrangle range in sequence from 1092 - 1123. The present map series is to be followed by a second series, in which the geology is reinterpreted on the basis of analysis of remote-sensing data, limited fieldwork, and library research. The second series is to be produced by the USGS in cooperation with the AGS and AGCHO.

Topographic Map of Quadrangle 3464, Shahrak (411) and Kasi (412) Quadrangles, Afghanistan

USGS Publications Warehouse

Bohannon, Robert G.

2006-01-01

This map was produced from several larger digital datasets. Topography was derived from Shuttle Radar Topography Mission (SRTM) 85-meter digital data. Gaps in the original dataset were filled with data digitized from contours on 1:200,000-scale Soviet General Staff Sheets (1978-1997). Contours were generated by cubic convolution averaged over four pixels using TNTmips surface-modeling capabilities. Minor artifacts resulting from the auto-contouring technique are present. Streams were auto-generated from the SRTM data in TNTmips as flow paths. Flow paths were limited in number by their Horton value on a quadrangle-by-quadrangle basis. Peak elevations were averaged over an area measuring 85 m by 85 m (represented by one pixel), and they are slightly lower than the highest corresponding point on the ground. Cultural data were extracted from files downloaded from the Afghanistan Information Management Service (AIMS) Web site (http://www.aims.org.af). The AIMS files were originally derived from maps produced by the Afghanistan Geodesy and Cartography Head Office (AGCHO). Because cultural features were not derived from the SRTM base, they do not match it precisely. Province boundaries are not exactly located. This map is part of a series that includes a geologic map, a topographic map, a Landsat natural-color-image map, and a Landsat false-color-image map for the USGS/AGS (Afghan Geological Survey) quadrangles covering Afghanistan. The maps for any given quadrangle have the same open-file number but a different letter suffix, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively. The open-file report (OFR) numbers for each quadrangle range in sequence from 1092 - 1123. The present map series is to be followed by a second series, in which the geology is reinterpreted on the basis of analysis of remote-sensing data, limited fieldwork, and library research. The second series is to be produced by the USGS in cooperation with the AGS and AGCHO.

Topographic Map of Quadrangle 3570, Tagab-E-Munjan (505) and Asmar-Kamdesh (506) Quadrangles, Afghanistan

USGS Publications Warehouse

Bohannon, Robert G.

2006-01-01

This map was produced from several larger digital datasets. Topography was derived from Shuttle Radar Topography Mission (SRTM) 85-meter digital data. Gaps in the original dataset were filled with data digitized from contours on 1:200,000-scale Soviet General Staff Sheets (1978-1997). Contours were generated by cubic convolution averaged over four pixels using TNTmips surface-modeling capabilities. Minor artifacts resulting from the auto-contouring technique are present. Streams were auto-generated from the SRTM data in TNTmips as flow paths. Flow paths were limited in number by their Horton value on a quadrangle-by-quadrangle basis. Peak elevations were averaged over an area measuring 85 m by 85 m (represented by one pixel), and they are slightly lower than the highest corresponding point on the ground. Cultural data were extracted from files downloaded from the Afghanistan Information Management Service (AIMS) Web site (http://www.aims.org.af). The AIMS files were originally derived from maps produced by the Afghanistan Geodesy and Cartography Head Office (AGCHO). Because cultural features were not derived from the SRTM base, they do not match it precisely. Province boundaries are not exactly located. This map is part of a series that includes a geologic map, a topographic map, a Landsat natural-color-image map, and a Landsat false-color-image map for the USGS/AGS (Afghan Geological Survey) quadrangles covering Afghanistan. The maps for any given quadrangle have the same open-file number but a different letter suffix, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively. The open-file report (OFR) numbers for each quadrangle range in sequence from 1092 - 1123. The present map series is to be followed by a second series, in which the geology is reinterpreted on the basis of analysis of remote-sensing data, limited fieldwork, and library research. The second series is to be produced by the USGS in cooperation with the AGS and AGCHO.

Topographic Map of Quadrangle 3564, Chahriaq (Joand) (405) and Gurziwan (406) Quadrangles, Afghanistan

USGS Publications Warehouse

Bohannon, Robert G.

2006-01-01

This map was produced from several larger digital datasets. Topography was derived from Shuttle Radar Topography Mission (SRTM) 85-meter digital data. Gaps in the original dataset were filled with data digitized from contours on 1:200,000-scale Soviet General Staff Sheets (1978-1997). Contours were generated by cubic convolution averaged over four pixels using TNTmips surface-modeling capabilities. Minor artifacts resulting from the auto-contouring technique are present. Streams were auto-generated from the SRTM data in TNTmips as flow paths. Flow paths were limited in number by their Horton value on a quadrangle-by-quadrangle basis. Peak elevations were averaged over an area measuring 85 m by 85 m (represented by one pixel), and they are slightly lower than the highest corresponding point on the ground. Cultural data were extracted from files downloaded from the Afghanistan Information Management Service (AIMS) Web site (http://www.aims.org.af). The AIMS files were originally derived from maps produced by the Afghanistan Geodesy and Cartography Head Office (AGCHO). Because cultural features were not derived from the SRTM base, they do not match it precisely. Province boundaries are not exactly located. This map is part of a series that includes a geologic map, a topographic map, a Landsat natural-color-image map, and a Landsat false-color-image map for the USGS/AGS (Afghan Geological Survey) quadrangles covering Afghanistan. The maps for any given quadrangle have the same open-file number but a different letter suffix, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively. The open-file report (OFR) numbers for each quadrangle range in sequence from 1092 - 1123. The present map series is to be followed by a second series, in which the geology is reinterpreted on the basis of analysis of remote-sensing data, limited fieldwork, and library research. The second series is to be produced by the USGS in cooperation with the AGS and AGCHO.

Topographic Map of Quadrangle 3364, Pasa-Band (417) and Kejran (418) Quadrangles, Afghanistan

USGS Publications Warehouse

Bohannon, Robert G.

2006-01-01

This map was produced from several larger digital datasets. Topography was derived from Shuttle Radar Topography Mission (SRTM) 85-meter digital data. Gaps in the original dataset were filled with data digitized from contours on 1:200,000-scale Soviet General Staff Sheets (1978-1997). Contours were generated by cubic convolution averaged over four pixels using TNTmips surface-modeling capabilities. Minor artifacts resulting from the auto-contouring technique are present. Streams were auto-generated from the SRTM data in TNTmips as flow paths. Flow paths were limited in number by their Horton value on a quadrangle-by-quadrangle basis. Peak elevations were averaged over an area measuring 85 m by 85 m (represented by one pixel), and they are slightly lower than the highest corresponding point on the ground. Cultural data were extracted from files downloaded from the Afghanistan Information Management Service (AIMS) Web site (http://www.aims.org.af). The AIMS files were originally derived from maps produced by the Afghanistan Geodesy and Cartography Head Office (AGCHO). Because cultural features were not derived from the SRTM base, they do not match it precisely. Province boundaries are not exactly located. This map is part of a series that includes a geologic map, a topographic map, a Landsat natural-color-image map, and a Landsat false-color-image map for the USGS/AGS (Afghan Geological Survey) quadrangles covering Afghanistan. The maps for any given quadrangle have the same open-file number but a different letter suffix, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively. The open-file report (OFR) numbers for each quadrangle range in sequence from 1092 - 1123. The present map series is to be followed by a second series, in which the geology is reinterpreted on the basis of analysis of remote-sensing data, limited fieldwork, and library research. The second series is to be produced by the USGS in cooperation with the AGS and AGCHO.

Topographic Map of Quadrangle 3366, Gizab (513) and Nawer (514) Quadrangles, Afghanistan

USGS Publications Warehouse

Bohannon, Robert G.

2006-01-01

This map was produced from several larger digital datasets. Topography was derived from Shuttle Radar Topography Mission (SRTM) 85-meter digital data. Gaps in the original dataset were filled with data digitized from contours on 1:200,000-scale Soviet General Staff Sheets (1978-1997). Contours were generated by cubic convolution averaged over four pixels using TNTmips surface-modeling capabilities. Minor artifacts resulting from the auto-contouring technique are present. Streams were auto-generated from the SRTM data in TNTmips as flow paths. Flow paths were limited in number by their Horton value on a quadrangle-by-quadrangle basis. Peak elevations were averaged over an area measuring 85 m by 85 m (represented by one pixel), and they are slightly lower than the highest corresponding point on the ground. Cultural data were extracted from files downloaded from the Afghanistan Information Management Service (AIMS) Web site (http://www.aims.org.af). The AIMS files were originally derived from maps produced by the Afghanistan Geodesy and Cartography Head Office (AGCHO). Because cultural features were not derived from the SRTM base, they do not match it precisely. Province boundaries are not exactly located. This map is part of a series that includes a geologic map, a topographic map, a Landsat natural-color-image map, and a Landsat false-color-image map for the USGS/AGS (Afghan Geological Survey) quadrangles covering Afghanistan. The maps for any given quadrangle have the same open-file number but a different letter suffix, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively. The open-file report (OFR) numbers for each quadrangle range in sequence from 1092 - 1123. The present map series is to be followed by a second series, in which the geology is reinterpreted on the basis of analysis of remote-sensing data, limited fieldwork, and library research. The second series is to be produced by the USGS in cooperation with the AGS and AGCHO.

Topographic Map of Quadrangle 3462, Herat (409) and Chesht-Sharif (410) Quadrangles, Afghanistan

USGS Publications Warehouse

Bohannon, Robert G.

2006-01-01

This map was produced from several larger digital datasets. Topography was derived from Shuttle Radar Topography Mission (SRTM) 85-meter digital data. Gaps in the original dataset were filled with data digitized from contours on 1:200,000-scale Soviet General Staff Sheets (1978-1997). Contours were generated by cubic convolution averaged over four pixels using TNTmips surface-modeling capabilities. Minor artifacts resulting from the auto-contouring technique are present. Streams were auto-generated from the SRTM data in TNTmips as flow paths. Flow paths were limited in number by their Horton value on a quadrangle-by-quadrangle basis. Peak elevations were averaged over an area measuring 85 m by 85 m (represented by one pixel), and they are slightly lower than the highest corresponding point on the ground. Cultural data were extracted from files downloaded from the Afghanistan Information Management Service (AIMS) Web site (http://www.aims.org.af). The AIMS files were originally derived from maps produced by the Afghanistan Geodesy and Cartography Head Office (AGCHO). Because cultural features were not derived from the SRTM base, they do not match it precisely. Province boundaries are not exactly located. This map is part of a series that includes a geologic map, a topographic map, a Landsat natural-color-image map, and a Landsat false-color-image map for the USGS/AGS (Afghan Geological Survey) quadrangles covering Afghanistan. The maps for any given quadrangle have the same open-file number but a different letter suffix, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively. The open-file report (OFR) numbers for each quadrangle range in sequence from 1092 - 1123. The present map series is to be followed by a second series, in which the geology is reinterpreted on the basis of analysis of remote-sensing data, limited fieldwork, and library research. The second series is to be produced by the USGS in cooperation with the AGS and AGCHO.

Topographic Map of Quadrangle 3262, Farah (421) and Hokumat-E-Pur-Chaman (422) Quadrangles, Afghanistan

USGS Publications Warehouse

Bohannon, Robert G.

2006-01-01

This map was produced from several larger digital datasets. Topography was derived from Shuttle Radar Topography Mission (SRTM) 85-meter digital data. Gaps in the original dataset were filled with data digitized from contours on 1:200,000-scale Soviet General Staff Sheets (1978-1997). Contours were generated by cubic convolution averaged over four pixels using TNTmips surface-modeling capabilities. Minor artifacts resulting from the auto-contouring technique are present. Streams were auto-generated from the SRTM data in TNTmips as flow paths. Flow paths were limited in number by their Horton value on a quadrangle-by-quadrangle basis. Peak elevations were averaged over an area measuring 85 m by 85 m (represented by one pixel), and they are slightly lower than the highest corresponding point on the ground. Cultural data were extracted from files downloaded from the Afghanistan Information Management Service (AIMS) Web site (http://www.aims.org.af). The AIMS files were originally derived from maps produced by the Afghanistan Geodesy and Cartography Head Office (AGCHO). Because cultural features were not derived from the SRTM base, they do not match it precisely. Province boundaries are not exactly located. This map is part of a series that includes a geologic map, a topographic map, a Landsat natural-color-image map, and a Landsat false-color-image map for the USGS/AGS (Afghan Geological Survey) quadrangles covering Afghanistan. The maps for any given quadrangle have the same open-file number but a different letter suffix, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively. The open-file report (OFR) numbers for each quadrangle range in sequence from 1092 - 1123. The present map series is to be followed by a second series, in which the geology is reinterpreted on the basis of analysis of remote-sensing data, limited fieldwork, and library research. The second series is to be produced by the USGS in cooperation with the AGS and AGCHO.

Topographic Map of Quadrangle 3362, Shin-Dand (415) and Tulak (416) Quadrangles, Afghanistan

USGS Publications Warehouse

Bohannon, Robert G.

2006-01-01

This map was produced from several larger digital datasets. Topography was derived from Shuttle Radar Topography Mission (SRTM) 85-meter digital data. Gaps in the original dataset were filled with data digitized from contours on 1:200,000-scale Soviet General Staff Sheets (1978-1997). Contours were generated by cubic convolution averaged over four pixels using TNTmips surface-modeling capabilities. Minor artifacts resulting from the auto-contouring technique are present. Streams were auto-generated from the SRTM data in TNTmips as flow paths. Flow paths were limited in number by their Horton value on a quadrangle-by-quadrangle basis. Peak elevations were averaged over an area measuring 85 m by 85 m (represented by one pixel), and they are slightly lower than the highest corresponding point on the ground. Cultural data were extracted from files downloaded from the Afghanistan Information Management Service (AIMS) Web site (http://www.aims.org.af). The AIMS files were originally derived from maps produced by the Afghanistan Geodesy and Cartography Head Office (AGCHO). Because cultural features were not derived from the SRTM base, they do not match it precisely. Province boundaries are not exactly located. This map is part of a series that includes a geologic map, a topographic map, a Landsat natural-color-image map, and a Landsat false-color-image map for the USGS/AGS (Afghan Geological Survey) quadrangles covering Afghanistan. The maps for any given quadrangle have the same open-file number but a different letter suffix, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively. The open-file report (OFR) numbers for each quadrangle range in sequence from 1092 - 1123. The present map series is to be followed by a second series, in which the geology is reinterpreted on the basis of analysis of remote-sensing data, limited fieldwork, and library research. The second series is to be produced by the USGS in cooperation with the AGS and AGCHO.

Topographic Map of Quadrangle 3670, Jam-Kashem (223) and Zebak (224) Quadrangles, Afghanistan

USGS Publications Warehouse

Bohannon, Robert G.

2006-01-01

This map was produced from several larger digital datasets. Topography was derived from Shuttle Radar Topography Mission (SRTM) 85-meter digital data. Gaps in the original dataset were filled with data digitized from contours on 1:200,000-scale Soviet General Staff Sheets (1978-1997). Contours were generated by cubic convolution averaged over four pixels using TNTmips surface-modeling capabilities. Minor artifacts resulting from the auto-contouring technique are present. Streams were auto-generated from the SRTM data in TNTmips as flow paths. Flow paths were limited in number by their Horton value on a quadrangle-by-quadrangle basis. Peak elevations were averaged over an area measuring 85 m by 85 m (represented by one pixel), and they are slightly lower than the highest corresponding point on the ground. Cultural data were extracted from files downloaded from the Afghanistan Information Management Service (AIMS) Web site (http://www.aims.org.af). The AIMS files were originally derived from maps produced by the Afghanistan Geodesy and Cartography Head Office (AGCHO). Because cultural features were not derived from the SRTM base, they do not match it precisely. Province boundaries are not exactly located. This map is part of a series that includes a geologic map, a topographic map, a Landsat natural-color-image map, and a Landsat false-color-image map for the USGS/AGS (Afghan Geological Survey) quadrangles covering Afghanistan. The maps for any given quadrangle have the same open-file number but a different letter suffix, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively. The open-file report (OFR) numbers for each quadrangle range in sequence from 1092 - 1123. The present map series is to be followed by a second series, in which the geology is reinterpreted on the basis of analysis of remote-sensing data, limited fieldwork, and library research. The second series is to be produced by the USGS in cooperation with the AGS and AGCHO.

Topographic Map of Quadrangle 3466, Lal-Sarjangal (507) and Bamyan (508) Quadrangles, Afghanistan

USGS Publications Warehouse

Bohannon, Robert G.

2006-01-01

This map was produced from several larger digital datasets. Topography was derived from Shuttle Radar Topography Mission (SRTM) 85-meter digital data. Gaps in the original dataset were filled with data digitized from contours on 1:200,000-scale Soviet General Staff Sheets (1978-1997). Contours were generated by cubic convolution averaged over four pixels using TNTmips surface-modeling capabilities. Minor artifacts resulting from the auto-contouring technique are present. Streams were auto-generated from the SRTM data in TNTmips as flow paths. Flow paths were limited in number by their Horton value on a quadrangle-by-quadrangle basis. Peak elevations were averaged over an area measuring 85 m by 85 m (represented by one pixel), and they are slightly lower than the highest corresponding point on the ground. Cultural data were extracted from files downloaded from the Afghanistan Information Management Service (AIMS) Web site (http://www.aims.org.af). The AIMS files were originally derived from maps produced by the Afghanistan Geodesy and Cartography Head Office (AGCHO). Because cultural features were not derived from the SRTM base, they do not match it precisely. Province boundaries are not exactly located. This map is part of a series that includes a geologic map, a topographic map, a Landsat natural-color-image map, and a Landsat false-color-image map for the USGS/AGS (Afghan Geological Survey) quadrangles covering Afghanistan. The maps for any given quadrangle have the same open-file number but a different letter suffix, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively. The open-file report (OFR) numbers for each quadrangle range in sequence from 1092 - 1123. The present map series is to be followed by a second series, in which the geology is reinterpreted on the basis of analysis of remote-sensing data, limited fieldwork, and library research. The second series is to be produced by the USGS in cooperation with the AGS and AGCHO.

Topographic Map of Quadrangle 3566, Sang-Charak (501) and Sayghan-O-Kamard (502) Quadrangles, Afghanistan

USGS Publications Warehouse

Bohannon, Robert G.

2006-01-01

This map was produced from several larger digital datasets. Topography was derived from Shuttle Radar Topography Mission (SRTM) 85-meter digital data. Gaps in the original dataset were filled with data digitized from contours on 1:200,000-scale Soviet General Staff Sheets (1978-1997). Contours were generated by cubic convolution averaged over four pixels using TNTmips surface-modeling capabilities. Minor artifacts resulting from the auto-contouring technique are present. Streams were auto-generated from the SRTM data in TNTmips as flow paths. Flow paths were limited in number by their Horton value on a quadrangle-by-quadrangle basis. Peak elevations were averaged over an area measuring 85 m by 85 m (represented by one pixel), and they are slightly lower than the highest corresponding point on the ground. Cultural data were extracted from files downloaded from the Afghanistan Information Management Service (AIMS) Web site (http://www.aims.org.af). The AIMS files were originally derived from maps produced by the Afghanistan Geodesy and Cartography Head Office (AGCHO). Because cultural features were not derived from the SRTM base, they do not match it precisely. Province boundaries are not exactly located. This map is part of a series that includes a geologic map, a topographic map, a Landsat natural-color-image map, and a Landsat false-color-image map for the USGS/AGS (Afghan Geological Survey) quadrangles covering Afghanistan. The maps for any given quadrangle have the same open-file number but a different letter suffix, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively. The open-file report (OFR) numbers for each quadrangle range in sequence from 1092 - 1123. The present map series is to be followed by a second series, in which the geology is reinterpreted on the basis of analysis of remote-sensing data, limited fieldwork, and library research. The second series is to be produced by the USGS in cooperation with the AGS and AGCHO.

Topographic Map of Quadrangle 3164, Lashkargah (605) and Kandahar (606) Quadrangles, Afghanistan

USGS Publications Warehouse

Bohannon, Robert G.

2006-01-01

This map was produced from several larger digital datasets. Topography was derived from Shuttle Radar Topography Mission (SRTM) 85-meter digital data. Gaps in the original dataset were filled with data digitized from contours on 1:200,000-scale Soviet General Staff Sheets (1978-1997). Contours were generated by cubic convolution averaged over four pixels using TNTmips surface-modeling capabilities. Minor artifacts resulting from the auto-contouring technique are present. Streams were auto-generated from the SRTM data in TNTmips as flow paths. Flow paths were limited in number by their Horton value on a quadrangle-by-quadrangle basis. Peak elevations were averaged over an area measuring 85 m by 85 m (represented by one pixel), and they are slightly lower than the highest corresponding point on the ground. Cultural data were extracted from files downloaded from the Afghanistan Information Management Service (AIMS) Web site (http://www.aims.org.af). The AIMS files were originally derived from maps produced by the Afghanistan Geodesy and Cartography Head Office (AGCHO). Because cultural features were not derived from the SRTM base, they do not match it precisely. Province boundaries are not exactly located. This map is part of a series that includes a geologic map, a topographic map, a Landsat natural-color-image map, and a Landsat false-color-image map for the USGS/AGS (Afghan Geological Survey) quadrangles covering Afghanistan. The maps for any given quadrangle have the same open-file number but a different letter suffix, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively. The open-file report (OFR) numbers for each quadrangle range in sequence from 1092 - 1123. The present map series is to be followed by a second series, in which the geology is reinterpreted on the basis of analysis of remote-sensing data, limited fieldwork, and library research. The second series is to be produced by the USGS in cooperation with the AGS and AGCHO.

Topographic Map of Quadrangle 3162, Chakhansur (603) and Kotalak (604) Quadrangles, Afghanistan

USGS Publications Warehouse

Bohannon, Robert G.

2006-01-01

This map was produced from several larger digital datasets. Topography was derived from Shuttle Radar Topography Mission (SRTM) 85-meter digital data. Gaps in the original dataset were filled with data digitized from contours on 1:200,000-scale Soviet General Staff Sheets (1978-1997). Contours were generated by cubic convolution averaged over four pixels using TNTmips surface-modeling capabilities. Minor artifacts resulting from the auto-contouring technique are present. Streams were auto-generated from the SRTM data in TNTmips as flow paths. Flow paths were limited in number by their Horton value on a quadrangle-by-quadrangle basis. Peak elevations were averaged over an area measuring 85 m by 85 m (represented by one pixel), and they are slightly lower than the highest corresponding point on the ground. Cultural data were extracted from files downloaded from the Afghanistan Information Management Service (AIMS) Web site (http://www.aims.org.af). The AIMS files were originally derived from maps produced by the Afghanistan Geodesy and Cartography Head Office (AGCHO). Because cultural features were not derived from the SRTM base, they do not match it precisely. Province boundaries are not exactly located. This map is part of a series that includes a geologic map, a topographic map, a Landsat natural-color-image map, and a Landsat false-color-image map for the USGS/AGS (Afghan Geological Survey) quadrangles covering Afghanistan. The maps for any given quadrangle have the same open-file number but a different letter suffix, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively. The open-file report (OFR) numbers for each quadrangle range in sequence from 1092 - 1123. The present map series is to be followed by a second series, in which the geology is reinterpreted on the basis of analysis of remote-sensing data, limited fieldwork, and library research. The second series is to be produced by the USGS in cooperation with the AGS and AGCHO.

Topographic Map of Quadrangle 3166, Jaldak (701) and Maruf-Nawa (702) Quadrangles, Afghanistan

USGS Publications Warehouse

Bohannon, Robert G.

2006-01-01

This map was produced from several larger digital datasets. Topography was derived from Shuttle Radar Topography Mission (SRTM) 85-meter digital data. Gaps in the original dataset were filled with data digitized from contours on 1:200,000-scale Soviet General Staff Sheets (1978-1997). Contours were generated by cubic convolution averaged over four pixels using TNTmips surface-modeling capabilities. Minor artifacts resulting from the auto-contouring technique are present. Streams were auto-generated from the SRTM data in TNTmips as flow paths. Flow paths were limited in number by their Horton value on a quadrangle-by-quadrangle basis. Peak elevations were averaged over an area measuring 85 m by 85 m (represented by one pixel), and they are slightly lower than the highest corresponding point on the ground. Cultural data were extracted from files downloaded from the Afghanistan Information Management Service (AIMS) Web site (http://www.aims.org.af). The AIMS files were originally derived from maps produced by the Afghanistan Geodesy and Cartography Head Office (AGCHO). Because cultural features were not derived from the SRTM base, they do not match it precisely. Province boundaries are not exactly located. This map is part of a series that includes a geologic map, a topographic map, a Landsat natural-color-image map, and a Landsat false-color-image map for the USGS/AGS (Afghan Geological Survey) quadrangles covering Afghanistan. The maps for any given quadrangle have the same open-file number but a different letter suffix, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively. The open-file report (OFR) numbers for each quadrangle range in sequence from 1092 - 1123. The present map series is to be followed by a second series, in which the geology is reinterpreted on the basis of analysis of remote-sensing data, limited fieldwork, and library research. The second series is to be produced by the USGS in cooperation with the AGS and AGCHO.

Topographic Map of Quadrangle 3266, Ourzgan (519) and Moqur (520) Quadrangles, Afghanistan

USGS Publications Warehouse

Bohannon, Robert G.

2006-01-01

This map was produced from several larger digital datasets. Topography was derived from Shuttle Radar Topography Mission (SRTM) 85-meter digital data. Gaps in the original dataset were filled with data digitized from contours on 1:200,000-scale Soviet General Staff Sheets (1978-1997). Contours were generated by cubic convolution averaged over four pixels using TNTmips surface-modeling capabilities. Minor artifacts resulting from the auto-contouring technique are present. Streams were auto-generated from the SRTM data in TNTmips as flow paths. Flow paths were limited in number by their Horton value on a quadrangle-by-quadrangle basis. Peak elevations were averaged over an area measuring 85 m by 85 m (represented by one pixel), and they are slightly lower than the highest corresponding point on the ground. Cultural data were extracted from files downloaded from the Afghanistan Information Management Service (AIMS) Web site (http://www.aims.org.af). The AIMS files were originally derived from maps produced by the Afghanistan Geodesy and Cartography Head Office (AGCHO). Because cultural features were not derived from the SRTM base, they do not match it precisely. Province boundaries are not exactly located. This map is part of a series that includes a geologic map, a topographic map, a Landsat natural-color-image map, and a Landsat false-color-image map for the USGS/AGS (Afghan Geological Survey) quadrangles covering Afghanistan. The maps for any given quadrangle have the same open-file number but a different letter suffix, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively. The open-file report (OFR) numbers for each quadrangle range in sequence from 1092 - 1123. The present map series is to be followed by a second series, in which the geology is reinterpreted on the basis of analysis of remote-sensing data, limited fieldwork, and library research. The second series is to be produced by the USGS in cooperation with the AGS and AGCHO.

Topographic Map of Quadrangle 3264, Nawzad-Musa-Qala (423) and Dehrawat (424) Quadrangles, Afghanistan

USGS Publications Warehouse

Bohannon, Robert G.

2006-01-01

This map was produced from several larger digital datasets. Topography was derived from Shuttle Radar Topography Mission (SRTM) 85-meter digital data. Gaps in the original dataset were filled with data digitized from contours on 1:200,000-scale Soviet General Staff Sheets (1978-1997). Contours were generated by cubic convolution averaged over four pixels using TNTmips surface-modeling capabilities. Minor artifacts resulting from the auto-contouring technique are present. Streams were auto-generated from the SRTM data in TNTmips as flow paths. Flow paths were limited in number by their Horton value on a quadrangle-by-quadrangle basis. Peak elevations were averaged over an area measuring 85 m by 85 m (represented by one pixel), and they are slightly lower than the highest corresponding point on the ground. Cultural data were extracted from files downloaded from the Afghanistan Information Management Service (AIMS) Web site (http://www.aims.org.af). The AIMS files were originally derived from maps produced by the Afghanistan Geodesy and Cartography Head Office (AGCHO). Because cultural features were not derived from the SRTM base, they do not match it precisely. Province boundaries are not exactly located. This map is part of a series that includes a geologic map, a topographic map, a Landsat natural-color-image map, and a Landsat false-color-image map for the USGS/AGS (Afghan Geological Survey) quadrangles covering Afghanistan. The maps for any given quadrangle have the same open-file number but a different letter suffix, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively. The open-file report (OFR) numbers for each quadrangle range in sequence from 1092 - 1123. The present map series is to be followed by a second series, in which the geology is reinterpreted on the basis of analysis of remote-sensing data, limited fieldwork, and library research. The second series is to be produced by the USGS in cooperation with the AGS and AGCHO.

Acquisition of thin coronal sectional dataset of cadaveric liver.

PubMed

Lou, Li; Liu, Shu Wei; Zhao, Zhen Mei; Tang, Yu Chun; Lin, Xiang Tao

2014-04-01

To obtain the thin coronal sectional anatomic dataset of the liver by using digital freezing milling technique. The upper abdomen of one Chinese adult cadaver was selected as the specimen. After CT and MRI examinations verification of absent liver lesions, the specimen was embedded with gelatin in stand erect position and frozen under profound hypothermia, and the specimen was then serially sectioned from anterior to posterior layer by layer with digital milling machine in the freezing chamber. The sequential images were captured by means of a digital camera and the dataset was imported to imaging workstation. The thin serial section of the liver added up to 699 layers with each layer being 0.2 mm in thickness. The shape, location, structure, intrahepatic vessels and adjacent structures of the liver was displayed clearly on each layer of the coronal sectional slice. CT and MR images through the body were obtained at 1.0 and 3.0 mm intervals, respectively. The methodology reported here is an adaptation of the milling methods previously described, which is a new data acquisition method for sectional anatomy. The thin coronal sectional anatomic dataset of the liver obtained by this technique is of high precision and good quality.

A method for normalizing pathology images to improve feature extraction for quantitative pathology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tam, Allison; Barker, Jocelyn; Rubin, Daniel

Purpose: With the advent of digital slide scanning technologies and the potential proliferation of large repositories of digital pathology images, many research studies can leverage these data for biomedical discovery and to develop clinical applications. However, quantitative analysis of digital pathology images is impeded by batch effects generated by varied staining protocols and staining conditions of pathological slides. Methods: To overcome this problem, this paper proposes a novel, fully automated stain normalization method to reduce batch effects and thus aid research in digital pathology applications. Their method, intensity centering and histogram equalization (ICHE), normalizes a diverse set of pathology imagesmore » by first scaling the centroids of the intensity histograms to a common point and then applying a modified version of contrast-limited adaptive histogram equalization. Normalization was performed on two datasets of digitized hematoxylin and eosin (H&E) slides of different tissue slices from the same lung tumor, and one immunohistochemistry dataset of digitized slides created by restaining one of the H&E datasets. Results: The ICHE method was evaluated based on image intensity values, quantitative features, and the effect on downstream applications, such as a computer aided diagnosis. For comparison, three methods from the literature were reimplemented and evaluated using the same criteria. The authors found that ICHE not only improved performance compared with un-normalized images, but in most cases showed improvement compared with previous methods for correcting batch effects in the literature. Conclusions: ICHE may be a useful preprocessing step a digital pathology image processing pipeline.« less

A Digital Solar Aspect Sensor

NASA Technical Reports Server (NTRS)

Albus, James S.

1961-01-01

The solar aspect sensor described herein performs the analog-to-digital conversion of data optically. To accomplish this, it uses a binary "Gray code" light mask to produce a digital indication, in vehicle-fixed coordinates, of the elevation and azimuth angles of incident light from the sun. This digital solar aspect sensor system, in Explorer X, provided measurements of both elevation and azimuth angles to +/- 2 degrees at a distance of over 140,000 statute miles.

Geologic Communications | Alaska Division of Geological & Geophysical

Science.gov Websites

improves a database for the Division's digital and map-based geological, geophysical, and geochemical data interfaces DGGS metadata and digital data distribution - Geospatial datasets published by DGGS are designed to be compatible with a broad variety of digital mapping software, to present DGGS's geospatial data

High-resolution digital elevation dataset for Crater Lake National Park and vicinity, Oregon, based on LiDAR survey of August-September 2010 and bathymetric survey of July 2000

USGS Publications Warehouse

Robinson, Joel E.

2012-01-01

Crater Lake partially fills the caldera that formed approximately 7,700 years ago during the eruption of a 12,000-foot volcano known as Mount Mazama. The caldera-forming or climactic eruption of Mount Mazama devastated the surrounding landscape, left a thick deposit of pumice and ash in adjacent valleys, and spread a blanket of volcanic ash as far away as southern Canada. Because the Crater Lake region is potentially volcanically active, knowledge of past events is important to understanding hazards from future eruptions. Similarly, because the area is seismically active, documenting and evaluating geologic faults is critical to assessing hazards from earthquakes. As part of the American Recovery and Reinvestment Act (ARRA) of 2009, the U.S. Geological Survey was awarded funding for high-precision airborne LiDAR (Light Detection And Ranging) data collection at several volcanoes in the Cascade Range through the Oregon LiDAR Consortium, administered by the Oregon Department of Geology and Mineral Industries (DOGAMI). The Oregon LiDAR Consortium contracted with Watershed Sciences, Inc., to conduct the data collection surveys. Collaborating agencies participating with the Oregon LiDAR Consortium for data collection in the Crater Lake region include Crater Lake National Park (National Park Service) and the Federal Highway Administration. In the immediate vicinity of Crater Lake National Park, 798 square kilometers of LiDAR data were collected, providing a digital elevation dataset of the ground surface beneath forest cover with an average resolution of 1.6 laser returns/m2 and both vertical and horizontal accuracies of ±5 cm. The LiDAR data were mosaicked in this report with bathymetry of the lake floor of Crater Lake, collected in 2000 using high-resolution multibeam sonar in a collaborative effort between the U.S. Geological Survey, Crater Lake National Park, and the Center for Coastal and Ocean Mapping at the University of New Hampshire. The bathymetric survey collected 16 million soundings with a spatial resolution of 2 meters using an EM1002 system owned and operated by C&C Technologies, Inc. The combined LiDAR and bathymetric dataset has a cell size of 1 meter and will contribute to understanding past volcanic events and their deposits, recognizing of faults and volcanic landforms, and quantifying landscape modification during and after the next volcanic eruption at Crater Lake.

Using Digital Globes to Explore the Deep Sea and Advance Public Literacy in Earth System Science

ERIC Educational Resources Information Center

Beaulieu, Stace E.; Emery, Emery; Brickley, Annette; Spargo, Abbey; Patterson, Kathleen; Joyce, Katherine; Silva, Tim; Madin, Katherine

2015-01-01

Digital globes are new technologies increasingly used in informal and formal education to display global datasets and show connections among Earth systems. But how effective are digital globes in advancing public literacy in Earth system science? We addressed this question by developing new content for digital globes with the intent to educate and…

A new Glacier Inventory of the Antarctic Peninsula as compiled from pre-existing Datasets

NASA Astrophysics Data System (ADS)

Huber, J.; Cook, A. J.; Paul, F.; Zemp, M.

2016-12-01

The glaciers on the Antarctic Peninsula (AP) potentially make a large contribution to sea level rise. However, this contribution was difficult to estimate, as no complete glacier inventory (outlines, attributes, separation from the ice sheet) was available so far. This work fills the gap and presents a new glacier inventory of the AP north of 70° S based on digitally combining pre-existing datasets with GIS techniques. Rock outcrops are removed from the glacier basin outlines of Cook et al. (2014) by digital intersection with the latest layer of the Antarctic Digital Database (Burton-Johnson et al. 2016). Glacier-specific topographic parameters (e.g. mean elevation, slope and aspect) as well as hypsometry have been calculated from the DEM of Cook et al. (2012). We also assigned connectivity levels to all glaciers following the concept by Rastner et al. (2012). Moreover, the bedrock dataset of Huss and Farinotti (2014) enabled us to add ice thickness and volume for each glacier. The new inventory is available from the GLIMS database and consists of 1589 glaciers covering an area of 95273 km2, slightly more than the 90000 km2 covered by glaciers surrounding the Greenland Ice Sheet. The total ice volume is 34590 km3 of which 1/3 is below sea level. The hypsometric curve has a bimodal shape due to the special topography of the AP consisting mainly of ice caps with outlet glaciers. Most of the glacierized area is located at 200-500 m a.s.l. with a secondary maximum at 1500-1900 m. About 63% of the area is drained by marine-terminating glaciers and ice shelf tributary glaciers cover 35% of the area. This combination results in a high sensitivity of the glaciers to climate change for several reasons: (1) only slightly rising equilibrium line altitudes would expose huge additional areas to ablation, (2) rising ocean temperatures increase melting of marine terminating glaciers, and (3) ice shelves have a buttressing effect on their feeding glaciers and their collapse would alter glacier dynamics and strongly enhance ice loss (Rott et al. 2011). The new inventory should facilitate modeling of the related effects using approaches tailored to glaciers for a more accurate determination of their future evolution and contribution to sea level rise.

Monitoring Water Resources in Pastoral Areas of East Africa Using Satellite Data and Hydrologic Modeling

NASA Astrophysics Data System (ADS)

Alemu, H.; Senay, G. B.; Velpuri, N.; Asante, K. O.

2008-12-01

The nomadic pastoral communities in East Africa heavily depend on small water bodies and artificial lakes for domestic and livestock uses. The shortage of water in the region has made these water resources of great importance to them and sometimes even the reason for conflicts amongst rival communities in the region. Satellite-based data has significantly transformed the way we track and estimate hydrological processes such as precipitation and evapotranspiration. This approach has been particularly useful in remote places where conventional station-based weather networks are scarce. Tropical Rainfall Measuring Mission (TRMM) satellite data were extracted for the study region. National Oceanic and Atmospheric Administration's (NOAA) Global Data Assimilation System (GDAS) data were used to extract the climatic parameters needed to calculate reference evapotranspiration. The elevation data needed to delineate the watersheds were extracted from the Shuttle Radar Topography Mission (SRTM) with spatial resolution of 90m. The waterholes (most of which have average surface area less than a hectare) were identified using Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) images with a spatial resolution of 15 m. As part of National Aeronautics and Space Administration's (NASA) funded enhancement to a livestock early warning decision support system, a simple hydrologic water balance model was developed to estimate daily waterhole depth variations. The model was run for over 10 years from 1998 till 2008 for 10 representative waterholes in the region. Although there were no independent datasets to validate the results, the temporal patterns captured both the seasonal and inter-annual variations, depicting known drought and flood years. Future research includes the installation of staff-gauges for model calibration and validation. The simple modeling approach demonstrated the effectiveness of integrating dynamic coarse resolution datasets such as TRMM with high resolution static datasets such as ASTER and SRTM DEM (Digital Elevation Model) to monitor water resources for drought early warning applications.

What's the Point of a Raster ? Advantages of 3D Point Cloud Processing over Raster Based Methods for Accurate Geomorphic Analysis of High Resolution Topography.

NASA Astrophysics Data System (ADS)

Lague, D.

2014-12-01

High Resolution Topographic (HRT) datasets are predominantly stored and analyzed as 2D raster grids of elevations (i.e., Digital Elevation Models). Raster grid processing is common in GIS software and benefits from a large library of fast algorithms dedicated to geometrical analysis, drainage network computation and topographic change measurement. Yet, all instruments or methods currently generating HRT datasets (e.g., ALS, TLS, SFM, stereo satellite imagery) output natively 3D unstructured point clouds that are (i) non-regularly sampled, (ii) incomplete (e.g., submerged parts of river channels are rarely measured), and (iii) include 3D elements (e.g., vegetation, vertical features such as river banks or cliffs) that cannot be accurately described in a DEM. Interpolating the raw point cloud onto a 2D grid generally results in a loss of position accuracy, spatial resolution and in more or less controlled interpolation. Here I demonstrate how studying earth surface topography and processes directly on native 3D point cloud datasets offers several advantages over raster based methods: point cloud methods preserve the accuracy of the original data, can better handle the evaluation of uncertainty associated to topographic change measurements and are more suitable to study vegetation characteristics and steep features of the landscape. In this presentation, I will illustrate and compare Point Cloud based and Raster based workflows with various examples involving ALS, TLS and SFM for the analysis of bank erosion processes in bedrock and alluvial rivers, rockfall statistics (including rockfall volume estimate directly from point clouds) and the interaction of vegetation/hydraulics and sedimentation in salt marshes. These workflows use 2 recently published algorithms for point cloud classification (CANUPO) and point cloud comparison (M3C2) now implemented in the open source software CloudCompare.

Inter-comparison of multiple statistically downscaled climate datasets for the Pacific Northwest, USA

PubMed Central

Jiang, Yueyang; Kim, John B.; Still, Christopher J.; Kerns, Becky K.; Kline, Jeffrey D.; Cunningham, Patrick G.

2018-01-01

Statistically downscaled climate data have been widely used to explore possible impacts of climate change in various fields of study. Although many studies have focused on characterizing differences in the downscaling methods, few studies have evaluated actual downscaled datasets being distributed publicly. Spatially focusing on the Pacific Northwest, we compare five statistically downscaled climate datasets distributed publicly in the US: ClimateNA, NASA NEX-DCP30, MACAv2-METDATA, MACAv2-LIVNEH and WorldClim. We compare the downscaled projections of climate change, and the associated observational data used as training data for downscaling. We map and quantify the variability among the datasets and characterize the spatio-temporal patterns of agreement and disagreement among the datasets. Pair-wise comparisons of datasets identify the coast and high-elevation areas as areas of disagreement for temperature. For precipitation, high-elevation areas, rainshadows and the dry, eastern portion of the study area have high dissimilarity among the datasets. By spatially aggregating the variability measures into watersheds, we develop guidance for selecting datasets within the Pacific Northwest climate change impact studies. PMID:29461513

Inter-comparison of multiple statistically downscaled climate datasets for the Pacific Northwest, USA.

PubMed

Jiang, Yueyang; Kim, John B; Still, Christopher J; Kerns, Becky K; Kline, Jeffrey D; Cunningham, Patrick G

2018-02-20

Statistically downscaled climate data have been widely used to explore possible impacts of climate change in various fields of study. Although many studies have focused on characterizing differences in the downscaling methods, few studies have evaluated actual downscaled datasets being distributed publicly. Spatially focusing on the Pacific Northwest, we compare five statistically downscaled climate datasets distributed publicly in the US: ClimateNA, NASA NEX-DCP30, MACAv2-METDATA, MACAv2-LIVNEH and WorldClim. We compare the downscaled projections of climate change, and the associated observational data used as training data for downscaling. We map and quantify the variability among the datasets and characterize the spatio-temporal patterns of agreement and disagreement among the datasets. Pair-wise comparisons of datasets identify the coast and high-elevation areas as areas of disagreement for temperature. For precipitation, high-elevation areas, rainshadows and the dry, eastern portion of the study area have high dissimilarity among the datasets. By spatially aggregating the variability measures into watersheds, we develop guidance for selecting datasets within the Pacific Northwest climate change impact studies.

Digital Elevation Models

USGS Publications Warehouse

,

1993-01-01

The Earth Science Information Center (ESIC) distributes digital cartographic/geographic data files produced by the U.S. Geological Survey (USGS) as part of the National Mapping Program. Digital cartographic data files may be grouped into four basic types. The first of these, called a Digital Line Graph (DLG), is the line map information in digital form. These data files include information on base data categories, such as transportation, hypsography, hydrography, and boundaries. The second type, called a Digital Elevation Model (DEM), consists of a sampled array of elevations for a number of ground positions at regularly spaced intervals. The third type is Land Use and Land Cover digital data which provides information on nine major classes of land use such as urban, agricultural, or forest as well as associated map data such as political units and Federal land ownership. The fourth type, the Geographic Names Information System, provides primary information for all known places, features, and areas in the United States identified by a proper name.

Estimating the magnitude and frequency of floods in urban basins in Missouri

USGS Publications Warehouse

Southard, Rodney E.

2010-01-01

Streamgage flood-frequency analyses were done for 35 streamgages on urban streams in and adjacent to Missouri for estimation of the magnitude and frequency of floods in urban areas of Missouri. A log-Pearson Type-III distribution was fitted to the annual series of peak flow data retrieved from the U.S. Geological Survey National Water Information System. For this report, the flood frequency estimates are expressed in terms of percent annual exceedance probabilities of 50, 20, 10, 4, 2, 1, and 0.2. Of the 35 streamgages, 30 are located in Missouri. The remaining five non-Missouri streamgages were added to the dataset to improve the range and applicability of the regression analyses from the streamgage frequency analyses. Ordinary least-squares was used to determine the best set of independent variables for the regression equations. Basin characteristics selected for independent variables into the ordinary least-squares regression analyses were based on theoretical relation to flood flows, literature review of possible basin characteristics, and the ability to measure the basin characteristics using digital datasets and geographic information system technology. Results of the ordinary least-squares were evaluated on the basis of Mallow's Cp statistic, the adjusted coefficient of determination, and the statistical significance of the independent variables. The independent variables of drainage area and percent impervious area were determined to be statistically significant and readily determined from existing digital datasets. The drainage area variable was computed using the best elevation data available, either from a statewide 10-meter grid or high-resolution elevation data from urban areas. The impervious area variable was computed from the National Land Cover Dataset 2001 impervious area dataset. The National Land Cover Dataset 2001 impervious area data for each basin was compared to historical imagery and 7.5-minute topographic maps to verify the national dataset represented the urbanization of the basin at the time streamgage data were collected. Eight streamgages had less urbanization during the period of time streamflow data were collected than was shown on the 2001 dataset. The impervious area values for these eight urban basins were adjusted downward as much as 23 percent to account for the additional urbanization since the streamflow data were collected. Weighted least-squares regression techniques were used to determine the final regression equations for the statewide urban flood-frequency equations. Weighted least-squares techniques improve regression equations by adjusting for different and varying lengths in streamflow records. The final flood-frequency equations for the 50-, 20-, 10-, 4-, 2-, 1-, and 0.2-percent annual exceedance probability floods for Missouri provide a technique for estimating peak flows on urban streams at gaged and ungaged sites. The applicability of the equations is limited by the range in basin characteristics used to develop the regression equations. The range in drainage area is 0.28 to 189 square miles; range in impervious area is 2.3 to 46.0 percent. Seven of the 35 selected streamgages were used to compare the results of the existing rural and urban equations to the urban equations presented in this report for the 1-percent annual exceedance probability. Results of the comparison indicate that the estimated peak flows for the urban equation in this report ranged from 3 to 52 percent higher than the results from the rural equations. Comparing the estimated urban peak flows from this report to the existing urban equation developed in 1986 indicated the range was 255 percent lower to 10 percent higher. The overall comparison between the current (2010) and 1986 urban equations indicates a reduction in estimated peak flow values for the 1-percent annual exceedance probability flood.

A conceptual prototype for the next-generation national elevation dataset

USGS Publications Warehouse

Stoker, Jason M.; Heidemann, Hans Karl; Evans, Gayla A.; Greenlee, Susan K.

2013-01-01

In 2012 the U.S. Geological Survey's (USGS) National Geospatial Program (NGP) funded a study to develop a conceptual prototype for a new National Elevation Dataset (NED) design with expanded capabilities to generate and deliver a suite of bare earth and above ground feature information over the United States. This report details the research on identifying operational requirements based on prior research, evaluation of what is needed for the USGS to meet these requirements, and development of a possible conceptual framework that could potentially deliver the kinds of information that are needed to support NGP's partners and constituents. This report provides an initial proof-of-concept demonstration using an existing dataset, and recommendations for the future, to inform NGP's ongoing and future elevation program planning and management decisions. The demonstration shows that this type of functional process can robustly create derivatives from lidar point cloud data; however, more research needs to be done to see how well it extends to multiple datasets.

High spatial resolution mapping of folds and fractures using Unmanned Aerial Vehicle (UAV) photogrammetry

NASA Astrophysics Data System (ADS)

Cruden, A. R.; Vollgger, S.

2016-12-01

The emerging capability of UAV photogrammetry combines a simple and cost-effective method to acquire digital aerial images with advanced computer vision algorithms that compute spatial datasets from a sequence of overlapping digital photographs from various viewpoints. Depending on flight altitude and camera setup, sub-centimeter spatial resolution orthophotographs and textured dense point clouds can be achieved. Orientation data can be collected for detailed structural analysis by digitally mapping such high-resolution spatial datasets in a fraction of time and with higher fidelity compared to traditional mapping techniques. Here we describe a photogrammetric workflow applied to a structural study of folds and fractures within alternating layers of sandstone and mudstone at a coastal outcrop in SE Australia. We surveyed this location using a downward looking digital camera mounted on commercially available multi-rotor UAV that autonomously followed waypoints at a set altitude and speed to ensure sufficient image overlap, minimum motion blur and an appropriate resolution. The use of surveyed ground control points allowed us to produce a geo-referenced 3D point cloud and an orthophotograph from hundreds of digital images at a spatial resolution < 10 mm per pixel, and cm-scale location accuracy. Orientation data of brittle and ductile structures were semi-automatically extracted from these high-resolution datasets using open-source software. This resulted in an extensive and statistically relevant orientation dataset that was used to 1) interpret the progressive development of folds and faults in the region, and 2) to generate a 3D structural model that underlines the complex internal structure of the outcrop and quantifies spatial variations in fold geometries. Overall, our work highlights how UAV photogrammetry can contribute to new insights in structural analysis.

Method for crater detection from digital topography data: interpolation based improvement and application to Lunar SELENE LALT data

NASA Astrophysics Data System (ADS)

Salamunićcar, Goran; Lončarić, Sven

Crater detection algorithms (CDAs) are an important subject of recent scientific research, as evident from the numerous recent publications in the field [ASR, 42 (1), 6-19]. In our previous work: (1) all the craters from the major currently available manually assembled catalogues have been merged into the catalogue with 57633 known Martian impact-craters [PSS, 56 (15), 1992-2008]; and (2) the CDA (developed to search for still uncatalogued impact-craters using 1/128° MOLA data) has been used to extend GT-57633 catalogue with 57592 additional craters resulting in GT-115225 catalog [GRS, 48 (5), in press, doi:10.1109/TGRS.2009.2037750]. On the other hand, the most complete catalog for Moon is the Morphological catalog of Lunar craters [edited by V. V. Shevchenko], which includes information on 14923 craters larger than 10km, visible on the lunar nearside and farside. This was the main motivation for application of our CDA to newly available Lunar SELENE LALT data. However, one of the main differences between MOLA and LALT data is the highest available resolution, wherein MOLA is available in 1/128° and LALT in 1/16° . The consequence is that only the largest craters can be detected using LALT dataset. However, this is still an excellent opportunity for further work on CDA in order to prepare it for forthcoming LRO LOLA data (which is expected to be in even better resolution than MOLA). The importance is in the fact that morphologically Martian and Lunar craters are not the same. Therefore, it is important to use the dataset for Moon in order to work on the CDA which is meant for detection of Lunar craters as well. In order to overcome the problem of currently available topography data in low resolution only, we particularly concentrated our work on the CDA's capability to detect very small craters relative to available dataset (up to the extreme case wherein the radius is as small as only two pixels). For this purpose, we improved the previous CDA with a new algorithm for sub-pixel interpolation of elevation samples, before subsequent computations. For elevation samples on larger distances from the crater's center, linear interpolation was used in order to speed-up the computations. For samples closer to the crater's center, the elevation value at the crater's center and relative sub-pixel distance to the selected elevation sample is additionally taken into account. The purpose is to compute the most realistic values for estimated elevation at a selected point. The results are, according to the initial visual evaluation, that numerous craters were successfully detected using SELENE LALT data.

Comparison of 7.5-minute and 1-degree digital elevation models

NASA Technical Reports Server (NTRS)

Isaacson, Dennis L.; Ripple, William J.

1995-01-01

We compared two digital elevation models (DEM's) for the Echo Mountain SE quadrangle in the Cascade Mountains of Oregon. Comparisons were made between 7.5-minute (1:24,000-scale) and 1-degree (1:250,000-scale) images using the variables of elevation, slope aspect, and slope gradient. Both visual and statistical differences are presented.

Comparison of 7.5-minute and 1-degree digital elevation models

NASA Technical Reports Server (NTRS)

Isaacson, Dennis L.; Ripple, William J.

1990-01-01

Two digital elevation models are compared for the Echo Mountain SE quadrangle in the Cascade Mountains of Oregon. Comparisons were made between 7.5-minute (1:24,000-scale) and 1-degree (1:250,000-scale) images using the variables of elevation, slope aspect, and slope gradient. Both visual and statistical differences are presented.

Where’s the Ground Surface? – Elevation Bias in LIDAR-derived Digital Elevation Models Due to Dense Vegetation in Oregon Tidal Marshes

EPA Science Inventory

Light Detection and Ranging (LIDAR) is a powerful resource for coastal and wetland managers and its use is increasing. Vegetation density and other land cover characteristics influence the accuracy of LIDAR-derived ground surface digital elevation models; however the degree to wh...

A Comparison of Mangrove Canopy Height Using Multiple Independent Measurements from Land, Air, and Space.

PubMed

Lagomasino, David; Fatoyinbo, Temilola; Lee, SeungKuk; Feliciano, Emanuelle; Trettin, Carl; Simard, Marc

2016-04-01

Canopy height is one of the strongest predictors of biomass and carbon in forested ecosystems. Additionally, mangrove ecosystems represent one of the most concentrated carbon reservoirs that are rapidly degrading as a result of deforestation, development, and hydrologic manipulation. Therefore, the accuracy of Canopy Height Models (CHM) over mangrove forest can provide crucial information for monitoring and verification protocols. We compared four CHMs derived from independent remotely sensed imagery and identified potential errors and bias between measurement types. CHMs were derived from three spaceborne datasets; Very-High Resolution (VHR) stereophotogrammetry, TerraSAR-X add-on for Digital Elevation Measurement, and Shuttle Radar Topography Mission (TanDEM-X), and lidar data which was acquired from an airborne platform. Each dataset exhibited different error characteristics that were related to spatial resolution, sensitivities of the sensors, and reference frames. Canopies over 10 m were accurately predicted by all CHMs while the distributions of canopy height were best predicted by the VHR CHM. Depending on the guidelines and strategies needed for monitoring and verification activities, coarse resolution CHMs could be used to track canopy height at regional and global scales with finer resolution imagery used to validate and monitor critical areas undergoing rapid changes.

Impact of recent Global Digital Bathymetry and Topography Models on geoid modelling: Results from two case studies in Balearic and Aegean Seas

NASA Astrophysics Data System (ADS)

Delikaraoglou, D.; Mintourakis, I.; Kallianou, F.

2009-04-01

With the realization of the Shuttle Radar Topographic Mission (SRTM) and the free distribution of its global elevation dataset with 3 arcsec (90 m) resolution and less than 16 m vertical accuracy, together with the availability of the higher resolution (30 m) and accuracy (10 m) Digital Terrain Models (DTM) from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), these two valuable sources of uniform DEM data represent a revolution in the world of terrain modelling. DEMs are an important source of data for the generation of high resolution geoids since they provide the high-frequency content of the gravity field spectrum and are suitable for the computation of terrain effects to gravity and indirect effects to the geoid, thus allowing the combination of global geopotential models, local gravity anomalies and information about the earth's topography (represented by a given DEM). However, although such models are available for land, there are no readily accessible Digital Bathymetry Models (DBMs) of equivalent quality for the coastal and oceanic regions. Most of the global DBM's (e.g. ETOPO1, SRTM30, and GEBCO global bathymetric grid) are compilations of heterogeneous data with medium resolution and accuracy. This prevents to exploit the potential of the recent high resolution (1 arcmin) marine free-air gravity anomalies datasets derived from satellite altimetry (such as the DNSC08, and the Sandwell & Smith v18.1 (S&Sv18.1) global solutions) in conjunction with such global DBM's. Fortunately, for some regions, recently have become available DBM's of much better accuracy and resolution, such as the DBM of 1 km resolution for many regions of the Mediterranean Sea which is distributed by IFREMER, the French Research Institute for Exploitation of the Sea. The scope of this study is to use this latest regional DBM in combination with the newly available DNSC08 and SSV18.1 global marine free-air gravity anomalies datasets for marine and near shore geoid modelling of archipelagic (island) areas. We have concentrated in two test regions: (a) the Catalano-Balearic Sea (South of Spain in the NW Meditteranean), where adequate marine and land gravity data allow a detailed evaluation of our processing methodologies and their results and, (b) the Aegean Sea where the presence of many islands in varying distances from the mainland Greece and located on the continental shelf and/or divided by steep sea floor topography present some unique challenges for any high resolution geoid modelling efforts. For both test regions, we generated a combined DEM (C-DEM) using the IFREMER and SRTM 30 arcsec bathymetric data for the sea areas and SRTM 3 arcsec data for the surrounding land areas. In this contribution, we discuss various computational aspects relating to the so-called "Direct Topographical Effect" (DTE) and the "Indirect Topographical Effect" (ITE), the two most significant topographical effects that have to be evaluated when a precise geoid is being compiled. In addition, we outline the evaluation and the impact of the results obtained, especially with regard to the differences in the geoid models when different elevation data are used, and point out the main limitations and possibilities for further improvements in the use of the aforementioned satellite and terrestrial data for regional and local geoid mapping in coastal and island regions. Keywords: IFREMER, SRTM, terrain effects, free-air gravity anomalies, geoid modelling,Digital Bathymetry Models.

Integrating depth functions and hyper-scale terrain analysis for 3D soil organic carbon modeling in agricultural fields at regional scale

NASA Astrophysics Data System (ADS)

Ramirez-Lopez, L.; van Wesemael, B.; Stevens, A.; Doetterl, S.; Van Oost, K.; Behrens, T.; Schmidt, K.

2012-04-01

Soil Organic Carbon (SOC) represents a key component in the global C cycle and has an important influence on the global CO2 fluxes between terrestrial biosphere and atmosphere. In the context of agricultural landscapes, SOC inventories are important since soil management practices have a strong influence on CO2 fluxes and SOC stocks. However, there is lack of accurate and cost-effective methods for producing high spatial resolution of SOC information. In this respect, our work is focused on the development of a three dimensional modeling approach for SOC monitoring in agricultural fields. The study area comprises ~420 km2 and includes 4 of the 5 agro-geological regions of the Grand-Duchy of Luxembourg. The soil dataset consist of 172 profiles (1033 samples) which were not sampled specifically for this study. This dataset is a combination of profile samples collected in previous soil surveys and soil profiles sampled for other research purposes. The proposed strategy comprises two main steps. In the first step the SOC distribution within each profile (vertical distribution) is modeled. Depth functions for are fitted in order to summarize the information content in the profile. By using these functions the SOC can be interpolated at any depth within the profiles. The second step involves the use of contextual terrain (ConMap) features (Behrens et al., 2010). These features are based on the differences in elevation between a given point location in the landscape and its circular neighbourhoods at a given set of different radius. One of the main advantages of this approach is that it allows the integration of several spatial scales (eg. local and regional) for soil spatial analysis. In this work the ConMap features are derived from a digital elevation model of the area and are used as predictors for spatial modeling of the parameters of the depth functions fitted in the previous step. In this poster we present some preliminary results in which we analyze: i. The use of different depth functions, ii. The use of different machine learning approaches for modeling the parameters of the fitted depth functions using the ConMap features and iii. The influence of different spatial scales on the SOC profile distribution variability. Keywords: 3D modeling, Digital soil mapping, Depth functions, Terrain analysis. Reference Behrens, T., K. Schmidt, K., Zhu, A.X. Scholten, T. 2010. The ConMap approach for terrain-based digital soil mapping. European Journal of Soil Science, v. 61, p.133-143.

NATIONAL HYDROGRAPHY DATASET

EPA Science Inventory

Resource Purpose:The National Hydrography Dataset (NHD) is a comprehensive set of digital spatial data that contains information about surface water features such as lakes, ponds, streams, rivers, springs and wells. Within the NHD, surface water features are combined to fo...

The Impact of Digital Skills on Educational Outcomes: Evidence from Performance Tests

ERIC Educational Resources Information Center

Pagani, Laura; Argentin, Gianluca; Gui, Marco; Stanca, Luca

2016-01-01

Digital skills are increasingly important for labour market outcomes and social participation. Do they also matter for academic performance? This paper investigates the effects of digital literacy on educational outcomes by merging data from the Italian National Assessment in secondary schools with an original data-set on performance tests of…

Using Selective Drainage Methods to Extract Continuous Surface Flow from 1-Meter Lidar-Derived Digital Elevation Data

USGS Publications Warehouse

Poppenga, Sandra K.; Worstell, Bruce B.; Stoker, Jason M.; Greenlee, Susan K.

2010-01-01

Digital elevation data commonly are used to extract surface flow features. One source for high-resolution elevation data is light detection and ranging (lidar). Lidar can capture a vast amount of topographic detail because of its fine-scale ability to digitally capture the surface of the earth. Because elevation is a key factor in extracting surface flow features, high-resolution lidar-derived digital elevation models (DEMs) provide the detail needed to consistently integrate hydrography with elevation, land cover, structures, and other geospatial features. The U.S. Geological Survey has developed selective drainage methods to extract continuous surface flow from high-resolution lidar-derived digital elevation data. The lidar-derived continuous surface flow network contains valuable information for water resource management involving flood hazard mapping, flood inundation, and coastal erosion. DEMs used in hydrologic applications typically are processed to remove depressions by filling them. High-resolution DEMs derived from lidar can capture much more detail of the land surface than courser elevation data. Therefore, high-resolution DEMs contain more depressions because of obstructions such as roads, railroads, and other elevated structures. The filling of these depressions can significantly affect the DEM-derived surface flow routing and terrain characteristics in an adverse way. In this report, selective draining methods that modify the elevation surface to drain a depression through an obstruction are presented. If such obstructions are not removed from the elevation data, the filling of depressions to create continuous surface flow can cause the flow to spill over an obstruction in the wrong location. Using this modified elevation surface improves the quality of derived surface flow and retains more of the true surface characteristics by correcting large filled depressions. A reliable flow surface is necessary for deriving a consistently connected drainage network, which is important in understanding surface water movement and developing applications for surface water runoff, flood inundation, and erosion. Improved methods are needed to extract continuous surface flow features from high-resolution elevation data based on lidar.

Digital geologic map and GIS database of Venezuela

USGS Publications Warehouse

Garrity, Christopher P.; Hackley, Paul C.; Urbani, Franco

2006-01-01

The digital geologic map and GIS database of Venezuela captures GIS compatible geologic and hydrologic data from the 'Geologic Shaded Relief Map of Venezuela,' which was released online as U.S. Geological Survey Open-File Report 2005-1038. Digital datasets and corresponding metadata files are stored in ESRI geodatabase format; accessible via ArcGIS 9.X. Feature classes in the geodatabase include geologic unit polygons, open water polygons, coincident geologic unit linework (contacts, faults, etc.) and non-coincident geologic unit linework (folds, drainage networks, etc.). Geologic unit polygon data were attributed for age, name, and lithologic type following the Lexico Estratigrafico de Venezuela. All digital datasets were captured from source data at 1:750,000. Although users may view and analyze data at varying scales, the authors make no guarantee as to the accuracy of the data at scales larger than 1:750,000.

A comparative appraisal of hydrological behavior of SRTM DEM at catchment level

NASA Astrophysics Data System (ADS)

Sharma, Arabinda; Tiwari, K. N.

2014-11-01

The Shuttle Radar Topography Mission (SRTM) data has emerged as a global elevation data in the past one decade because of its free availability, homogeneity and consistent accuracy compared to other global elevation dataset. The present study explores the consistency in hydrological behavior of the SRTM digital elevation model (DEM) with reference to easily available regional 20 m contour interpolated DEM (TOPO DEM). Analysis ranging from simple vertical accuracy assessment to hydrological simulation of the studied Maithon catchment, using empirical USLE model and semidistributed, physical SWAT model, were carried out. Moreover, terrain analysis involving hydrological indices was performed for comparative assessment of the SRTM DEM with respect to TOPO DEM. Results reveal that the vertical accuracy of SRTM DEM (±27.58 m) in the region is less than the specified standard (±16 m). Statistical analysis of hydrological indices such as topographic wetness index (TWI), stream power index (SPI), slope length factor (SLF) and geometry number (GN) shows a significant differences in hydrological properties of the two studied DEMs. Estimation of soil erosion potentials of the catchment and conservation priorities of microwatersheds of the catchment using SRTM DEM and TOPO DEM produce considerably different results. Prediction of soil erosion potential using SRTM DEM is far higher than that obtained using TOPO DEM. Similarly, conservation priorities determined using the two DEMs are found to be agreed for only 34% of microwatersheds of the catchment. ArcSWAT simulation reveals that runoff predictions are less sensitive to selection of the two DEMs as compared to sediment yield prediction. The results obtained in the present study are vital to hydrological analysis as it helps understanding the hydrological behavior of the DEM without being influenced by the model structural as well as parameter uncertainty. It also reemphasized that SRTM DEM can be a valuable dataset for hydrological analysis provided any error/uncertainty therein is being properly evaluated and characterized.

EnviroAtlas - NHDPlus V2 Hydrologic Unit Boundaries Web Service - Conterminous United States

EPA Pesticide Factsheets

This EnviroAtlas web service contains layers depicting hydrologic unit boundary layers and labels for the Subregion level (4-digit HUCs), Subbasin level (8-digit HUCs), and Subwatershed level (12-digit HUCs) for the conterminous United States. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

Maximizing Accessibility to Spatially Referenced Digital Data.

ERIC Educational Resources Information Center

Hunt, Li; Joselyn, Mark

1995-01-01

Discusses some widely available spatially referenced datasets, including raster and vector datasets. Strategies for improving accessibility include: acquisition of data in a software-dependent format; reorganization of data into logical geographic units; acquisition of intelligent retrieval software; improving computer hardware; and intelligent…

OpenTopography: Enabling Online Access to High-Resolution Lidar Topography Data and Processing Tools

NASA Astrophysics Data System (ADS)

Crosby, Christopher; Nandigam, Viswanath; Baru, Chaitan; Arrowsmith, J. Ramon

2013-04-01

High-resolution topography data acquired with lidar (light detection and ranging) technology are revolutionizing the way we study the Earth's surface and overlying vegetation. These data, collected from airborne, tripod, or mobile-mounted scanners have emerged as a fundamental tool for research on topics ranging from earthquake hazards to hillslope processes. Lidar data provide a digital representation of the earth's surface at a resolution sufficient to appropriately capture the processes that contribute to landscape evolution. The U.S. National Science Foundation-funded OpenTopography Facility (http://www.opentopography.org) is a web-based system designed to democratize access to earth science-oriented lidar topography data. OpenTopography provides free, online access to lidar data in a number of forms, including the raw point cloud and associated geospatial-processing tools for customized analysis. The point cloud data are co-located with on-demand processing tools to generate digital elevation models, and derived products and visualizations which allow users to quickly access data in a format appropriate for their scientific application. The OpenTopography system is built using a service-oriented architecture (SOA) that leverages cyberinfrastructure resources at the San Diego Supercomputer Center at the University of California San Diego to allow users, regardless of expertise level, to access these massive lidar datasets and derived products for use in research and teaching. OpenTopography hosts over 500 billion lidar returns covering 85,000 km2. These data are all in the public domain and are provided by a variety of partners under joint agreements and memoranda of understanding with OpenTopography. Partners include national facilities such as the NSF-funded National Center for Airborne Lidar Mapping (NCALM), as well as non-governmental organizations and local, state, and federal agencies. OpenTopography has become a hub for high-resolution topography resources. Datasets hosted by other organizations, as well as lidar-specific software, can be registered into the OpenTopography catalog, providing users a "one-stop shop" for such information. With several thousand active users, OpenTopography is an excellent example of a mature Spatial Data Infrastructure system that is enabling access to challenging data for research, education and outreach. Ongoing OpenTopography design and development work includes the archive and publication of datasets using digital object identifiers (DOIs); creation of a more flexible and scalable high-performance environment for processing of large datasets; expanded support for satellite and terrestrial lidar; and creation of a "pluggable" infrastructure for third-party programs and algorithms. OpenTopography has successfully created a facility for sharing lidar data. In the project's next phase, we are working to enable equally easy and successful sharing of services for processing and analysis of these data.

GTN-G, WGI, RGI, DCW, GLIMS, WGMS, GCOS - What's all this about? (Invited)

NASA Astrophysics Data System (ADS)

Paul, F.; Raup, B. H.; Zemp, M.

2013-12-01

In a large collaborative effort, the glaciological community has compiled a new and spa-tially complete global dataset of glacier outlines, the so-called Randolph Glacier Inventory or RGI. Despite its regional shortcomings in quality (e.g. in regard to geolocation, gener-alization, and interpretation), this dataset was heavily used for global-scale modelling ap-plications (e.g. determination of total glacier volume and glacier contribution to sea-level rise) in support of the forthcoming 5th Assessment Report (AR5) of Working Group I of the IPCC. The RGI is a merged dataset that is largely based on the GLIMS database and several new datasets provided by the community (both are mostly derived from satellite data), as well as the Digital Chart of the World (DCW) and glacier attribute information (location, size) from the World Glacier Inventory (WGI). There are now two key tasks to be performed, (1) improving the quality of the RGI in all regions where the outlines do not met the quality required for local scale applications, and (2) integrating the RGI in the GLIMS glacier database to improve its spatial completeness. While (1) requires again a huge effort but is already ongoing, (2) is mainly a technical issue that is nearly solved. Apart from this technical dimension, there is also a more political or structural one. While GLIMS is responsible for the remote sensing and glacier inventory part (Tier 5) of the Global Terrestrial Network for Glaciers (GTN-G) within the Global Climate Observing System (GCOS), the World Glacier Monitoring Service (WGMS) is collecting and dis-seminating the field observations. Along with new global products derived from satellite data (e.g. elevation changes and velocity fields) and the community wish to keep a snap-shot dataset such as the RGI available, how to make all these datasets available to the community without duplicating efforts and making best use of the very limited financial resources available must now be discussed. This overview presentation describes the cur-rently available datasets, clarifying the terminology and the international framework, and suggesting a way forward to serve the community at best.

Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: NLCD 2001 Imperviousness

USGS Publications Warehouse

Wieczorek, Michael; LaMotte, Andrew E.

2010-01-01

This data set represents the mean percent impervious surface from the Imperviousness Layer of the National Land Cover Dataset 2001 (LaMotte and Wieczorek, 2010), compiled for every catchment of NHDPlus for the conterminous United States. The source data set represents imperviousness for the conterminous United States for 2001. The Imperviousness Layer of the National Land Cover Data Set for 2001 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of Federal agencies (http://www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (USEPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (USFWS), the Bureau of Land Management (BLM), and the USDA Natural Resources Conservation Service (NRCS). The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: NLCD 2001 Land Use and Land Cover

USGS Publications Warehouse

Wieczorek, Michael; LaMotte, Andrew E.

2010-01-01

This data set represents the estimated area of land use and land cover from the National Land Cover Dataset 2001 (LaMotte, 2008), compiled for every catchment of NHDPlus for the conterminous United States. The source data set represents land use and land cover for the conterminous United States for 2001. The National Land Cover Data Set for 2001 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of Federal agencies (http://www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (USEPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (USFWS), the Bureau of Land Management (BLM), and the USDA Natural Resources Conservation Service (NRCS). The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

An assessment of differences in gridded precipitation datasets in complex terrain

NASA Astrophysics Data System (ADS)

Henn, Brian; Newman, Andrew J.; Livneh, Ben; Daly, Christopher; Lundquist, Jessica D.

2018-01-01

Hydrologic modeling and other geophysical applications are sensitive to precipitation forcing data quality, and there are known challenges in spatially distributing gauge-based precipitation over complex terrain. We conduct a comparison of six high-resolution, daily and monthly gridded precipitation datasets over the Western United States. We compare the long-term average spatial patterns, and interannual variability of water-year total precipitation, as well as multi-year trends in precipitation across the datasets. We find that the greatest absolute differences among datasets occur in high-elevation areas and in the maritime mountain ranges of the Western United States, while the greatest percent differences among datasets relative to annual total precipitation occur in arid and rain-shadowed areas. Differences between datasets in some high-elevation areas exceed 200 mm yr-1 on average, and relative differences range from 5 to 60% across the Western United States. In areas of high topographic relief, true uncertainties and biases are likely higher than the differences among the datasets; we present evidence of this based on streamflow observations. Precipitation trends in the datasets differ in magnitude and sign at smaller scales, and are sensitive to how temporal inhomogeneities in the underlying precipitation gauge data are handled.

Digital tissue and what it may reveal about the brain.

PubMed

Morgan, Josh L; Lichtman, Jeff W

2017-10-30

Imaging as a means of scientific data storage has evolved rapidly over the past century from hand drawings, to photography, to digital images. Only recently can sufficiently large datasets be acquired, stored, and processed such that tissue digitization can actually reveal more than direct observation of tissue. One field where this transformation is occurring is connectomics: the mapping of neural connections in large volumes of digitized brain tissue.

Three-dimensional reconstruction of Roman coins from photometric image sets

NASA Astrophysics Data System (ADS)

MacDonald, Lindsay; Moitinho de Almeida, Vera; Hess, Mona

2017-01-01

A method is presented for increasing the spatial resolution of the three-dimensional (3-D) digital representation of coins by combining fine photometric detail derived from a set of photographic images with accurate geometric data from a 3-D laser scanner. 3-D reconstructions were made of the obverse and reverse sides of two ancient Roman denarii by processing sets of images captured under directional lighting in an illumination dome. Surface normal vectors were calculated by a "bounded regression" technique, excluding both shadow and specular components of reflection from the metallic surface. Because of the known difficulty in achieving geometric accuracy when integrating photometric normals to produce a digital elevation model, the low spatial frequencies were replaced by those derived from the point cloud produced by a 3-D laser scanner. The two datasets were scaled and registered by matching the outlines and correlating the surface gradients. The final result was a realistic rendering of the coins at a spatial resolution of 75 pixels/mm (13-μm spacing), in which the fine detail modulated the underlying geometric form of the surface relief. The method opens the way to obtain high quality 3-D representations of coins in collections to enable interactive online viewing.

A 125 year history of topographic mapping and GIS in the U.S. Geological Survey 1884-2009, part 2: 1980-2009

USGS Publications Warehouse

Usery, E. Lynn; Varanka, Dalia; Finn, Michael P.

2009-01-01

The United States Geological Survey (USGS) entered the mainstream of developments in computer-assisted technology for mapping during the 1970s. The introduction by USGS of digital line graphs (DLGs), digital elevation models (DEMs), and land use data analysis (LUDA) nationwide land-cover data provided a base for the rapid expansion of the use of GIS in the 1980s. Whereas USGS had developed the topologically structured DLG data and the Geographic Information Retrieval and Analysis System (GIRAS) for land-cover data, the Map Overlay Statistical System (MOSS), a nontopologically structured GIS software package developed by Autometric, Inc., under contract to the U.S. Fish and Wildlife Service, dominated the use of GIS by federal agencies in the 1970s. Thus, USGS data was used in MOSS, but the topological structure, which later became a requirement for GIS vector datasets, was not used in early GIS applications. The introduction of Esri's ARC/INFO in 1982 changed that, and by the end of the 1980s, topological structure for vector data was essential, and ARC/INFO was the dominant GIS software package used by federal agencies.

Mineral and Vegetation Maps of the Bodie Hills, Sweetwater Mountains, and Wassuk Range, California/Nevada, Generated from ASTER Satellite Data

USGS Publications Warehouse

Rockwell, Barnaby W.

2010-01-01

Multispectral remote sensing data acquired by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) were analyzed to identify and map minerals, vegetation groups, and volatiles (water and snow) in support of geologic studies of the Bodie Hills, Sweetwater Mountains, and Wassuk Range, California/Nevada. Digital mineral and vegetation mapping results are presented in both portable document format (PDF) and ERDAS Imagine format (.img). The ERDAS-format files are suitable for integration with other geospatial data in Geographic Information Systems (GIS) such as ArcGIS. The ERDAS files showing occurrence of 1) iron-bearing minerals, vegetation, and water, and 2) clay, sulfate, mica, carbonate, Mg-OH, and hydrous quartz minerals have been attributed according to identified material, so that the material detected in a pixel can be queried with the interactive attribute identification tools of GIS and image processing software packages (for example, the Identify Tool of ArcMap and the Inquire Cursor Tool of ERDAS Imagine). All raster data have been orthorectified to the Universal Transverse Mercator (UTM) projection using a projective transform with ground-control points selected from orthorectified Landsat Thematic Mapper data and a digital elevation model from the U.S. Geological Survey (USGS) National Elevation Dataset (1/3 arc second, 10 m resolution). Metadata compliant with Federal Geographic Data Committee (FGDC) standards for all ERDAS-format files have been included, and contain important information regarding geographic coordinate systems, attributes, and cross-references. Documentation regarding spectral analysis methodologies employed to make the maps is included in these cross-references.

A robust interpolation method for constructing digital elevation models from remote sensing data

NASA Astrophysics Data System (ADS)

Chen, Chuanfa; Liu, Fengying; Li, Yanyan; Yan, Changqing; Liu, Guolin

2016-09-01

A digital elevation model (DEM) derived from remote sensing data often suffers from outliers due to various reasons such as the physical limitation of sensors and low contrast of terrain textures. In order to reduce the effect of outliers on DEM construction, a robust algorithm of multiquadric (MQ) methodology based on M-estimators (MQ-M) was proposed. MQ-M adopts an adaptive weight function with three-parts. The weight function is null for large errors, one for small errors and quadric for others. A mathematical surface was employed to comparatively analyze the robustness of MQ-M, and its performance was compared with those of the classical MQ and a recently developed robust MQ method based on least absolute deviation (MQ-L). Numerical tests show that MQ-M is comparative to the classical MQ and superior to MQ-L when sample points follow normal and Laplace distributions, and under the presence of outliers the former is more accurate than the latter. A real-world example of DEM construction using stereo images indicates that compared with the classical interpolation methods, such as natural neighbor (NN), ordinary kriging (OK), ANUDEM, MQ-L and MQ, MQ-M has a better ability of preserving subtle terrain features. MQ-M replaces thin plate spline for reference DEM construction to assess the contribution to our recently developed multiresolution hierarchical classification method (MHC). Classifying the 15 groups of benchmark datasets provided by the ISPRS Commission demonstrates that MQ-M-based MHC is more accurate than MQ-L-based and TPS-based MHCs. MQ-M has high potential for DEM construction.

Applicability of computer-aided comprehensive tool (LINDA: LINeament Detection and Analysis) and shaded digital elevation model for characterizing and interpreting morphotectonic features from lineaments

NASA Astrophysics Data System (ADS)

Masoud, Alaa; Koike, Katsuaki

2017-09-01

Detection and analysis of linear features related to surface and subsurface structures have been deemed necessary in natural resource exploration and earth surface instability assessment. Subjectivity in choosing control parameters required in conventional methods of lineament detection may cause unreliable results. To reduce this ambiguity, we developed LINDA (LINeament Detection and Analysis), an integrated tool with graphical user interface in Visual Basic. This tool automates processes of detection and analysis of linear features from grid data of topography (digital elevation model; DEM), gravity and magnetic surfaces, as well as data from remote sensing imagery. A simple interface with five display windows forms a user-friendly interactive environment. The interface facilitates grid data shading, detection and grouping of segments, lineament analyses for calculating strike and dip and estimating fault type, and interactive viewing of lineament geometry. Density maps of the center and intersection points of linear features (segments and lineaments) are also included. A systematic analysis of test DEMs and Landsat 7 ETM+ imagery datasets in the North and South Eastern Deserts of Egypt is implemented to demonstrate the capability of LINDA and correct use of its functions. Linear features from the DEM are superior to those from the imagery in terms of frequency, but both linear features agree with location and direction of V-shaped valleys and dykes and reference fault data. Through the case studies, LINDA applicability is demonstrated to highlight dominant structural trends, which can aid understanding of geodynamic frameworks in any region.

Developing a Resource for Implementing ArcSWAT Using Global Datasets

NASA Astrophysics Data System (ADS)

Taggart, M.; Caraballo Álvarez, I. O.; Mueller, C.; Palacios, S. L.; Schmidt, C.; Milesi, C.; Palmer-Moloney, L. J.

2015-12-01

This project developed a comprehensive user manual outlining methods for adapting and implementing global datasets for use within ArcSWAT for international and worldwide applications. The Soil and Water Assessment Tool (SWAT) is a hydrologic model that looks at a number of hydrologic variables including runoff and the chemical makeup of water at a given location on the Earth's surface using Digital Elevation Models (DEM), land cover, soil, and weather data. However, the application of ArcSWAT for projects outside of the United States is challenging as there is no standard framework for inputting global datasets into ArcSWAT. This project aims to remove this obstacle by outlining methods for adapting and implementing these global datasets via the user manual. The manual takes the user through the processes of data conditioning while providing solutions and suggestions for common errors. The efficacy of the manual was explored using examples from watersheds located in Puerto Rico, Mexico and Western Africa. Each run explored the various options for setting up a ArcSWAT project as well as a range of satellite data products and soil databases. Future work will incorporate in-situ data for validation and calibration of the model and outline additional resources to assist future users in efficiently implementing the model for worldwide applications. The capacity to manage and monitor freshwater availability is of critical importance in both developed and developing countries. As populations grow and climate changes, both the quality and quantity of freshwater are affected resulting in negative impacts on the health of the surrounding population. The use of hydrologic models such as ArcSWAT can help stakeholders and decision makers understand the future impacts of these changes enabling informed and substantiated decisions.

Low-head hydropower assessment of the Brazilian State of São Paulo

USGS Publications Warehouse

Artan, Guleid A.; Cushing, W. Matthew; Mathis, Melissa L.; Tieszen, Larry L.

2014-01-01

This study produced a comprehensive estimate of the magnitude of hydropower potential available in the streams that drain watersheds entirely within the State of São Paulo, Brazil. Because a large part of the contributing area is outside of São Paulo, the main stem of the Paraná River was excluded from the assessment. Potential head drops were calculated from the Digital Terrain Elevation Data,which has a 1-arc-second resolution (approximately 30-meter resolution at the equator). For the conditioning and validation of synthetic stream channels derived from the Digital Elevation Model datasets, hydrography data (in digital format) supplied by the São Paulo State Department of Energy and the Agência Nacional de Águas were used. Within the study area there were 1,424 rain gages and 123 streamgages with long-term data records. To estimate average yearly streamflow, a hydrologic regionalization system that divides the State into 21 homogeneous basins was used. Stream segments, upstream areas, and mean annual rainfall were estimated using geographic information systems techniques. The accuracy of the flows estimated with the regionalization models was validated. Overall, simulated streamflows were significantly correlated with the observed flows but with a consistent underestimation bias. When the annual mean flows from the regionalization models were adjusted upward by 10 percent, average streamflow estimation bias was reduced from -13 percent to -4 percent. The sum of all the validated stream reach mean annual hydropower potentials in the 21 basins is 7,000 megawatts (MW). Hydropower potential is mainly concentrated near the Serra do Mar mountain range and along the Tietê River. The power potential along the Tietê River is mainly at sites with medium and high potentials, sites where hydropower has already been harnessed. In addition to the annual mean hydropower estimates, potential hydropower estimates with flow rates with exceedance probabilities of 40 percent, 60 percent, and 90 percent were made.

Digital Astronaut Photography: A Discovery Dataset for Archaeology

NASA Technical Reports Server (NTRS)

Stefanov, William L.

2010-01-01

Astronaut photography acquired from the International Space Station (ISS) using commercial off-the-shelf cameras offers a freely-accessible source for high to very high resolution (4-20 m/pixel) visible-wavelength digital data of Earth. Since ISS Expedition 1 in 2000, over 373,000 images of the Earth-Moon system (including land surface, ocean, atmospheric, and lunar images) have been added to the Gateway to Astronaut Photography of Earth online database (http://eol.jsc.nasa.gov ). Handheld astronaut photographs vary in look angle, time of acquisition, solar illumination, and spatial resolution. These attributes of digital astronaut photography result from a unique combination of ISS orbital dynamics, mission operations, camera systems, and the individual skills of the astronaut. The variable nature of astronaut photography makes the dataset uniquely useful for archaeological applications in comparison with more traditional nadir-viewing multispectral datasets acquired from unmanned orbital platforms. For example, surface features such as trenches, walls, ruins, urban patterns, and vegetation clearing and regrowth patterns may be accentuated by low sun angles and oblique viewing conditions (Fig. 1). High spatial resolution digital astronaut photographs can also be used with sophisticated land cover classification and spatial analysis approaches like Object Based Image Analysis, increasing the potential for use in archaeological characterization of landscapes and specific sites.

Multi-scale Visualization of Remote Sensing and Topographic Data of the Amazon Rain Forest for Environmental Monitoring of the Petroleum Industry.

NASA Astrophysics Data System (ADS)

Fonseca, L.; Miranda, F. P.; Beisl, C. H.; Souza-Fonseca, J.

2002-12-01

PETROBRAS (the Brazilian national oil company) built a pipeline to transport crude oil from the Urucu River region to a terminal in the vicinities of Coari, a city located in the right margin of the Solimoes River. The oil is then shipped by tankers to another terminal in Manaus, capital city of the Amazonas state. At the city of Coari, changes in water level between dry and wet seasons reach up to 14 meters. This strong seasonal character of the Amazonian climate gives rise to four distinct scenarios in the annual hydrological cycle: low water, high water, receding water, and rising water. These scenarios constitute the main reference for the definition of oil spill response planning in the region, since flooded forests and flooded vegetation are the most sensitive fluvial environments to oil spills. This study focuses on improving information about oil spill environmental sensitivity in Western Amazon by using 3D visualization techniques to help the analysis and interpretation of remote sensing and digital topographic data, as follows: (a) 1995 low flood and 1996 high flood JERS-1 SAR mosaics, band LHH, 100m pixel; (b) 2000 low flood and 2001 high flood RADARSAT-1 W1 images, band CHH, 30m pixel; (c) 2002 high flood airborne SAR images from the SIVAM project (System for Surveillance of the Amazon), band LHH, 3m pixel and band XHH, 6m pixel; (d) GTOPO30 digital elevation model, 30' resolution; (e) Digital elevation model derived from topographic information acquired during seismic surveys, 25m resolution; (f) panoramic views obtained from low altitude helicopter flights. The methodology applied includes image processing, cartographic conversion and generation of value-added product using 3D visualization. A semivariogram textural classification was applied to the SAR images in order to identify areas of flooded forest and flooded vegetation. The digital elevation models were color shaded to highlight subtle topographic features. Both datasets were then converted to the same cartographic projection and inserted into the Fledermaus 3D visualization environment. 3D visualization proved to be an important aid in understanding the spatial distribution pattern of the environmentally sensitive vegetation cover. The dynamics of the hydrological cycle was depicted in a basin-wide scale, revealing new geomorphic information relevant to assess the environmental risk of oil spills. Results demonstrate that pipelines constitute an environmentally saver option for oil transportation in the region when compared to fluvial tanker routes.

High-resolution digital elevation model of Mount St. Helens crater and upper North Fork Toutle River basin, Washington, based on an airborne lidar survey of September 2009

USGS Publications Warehouse

Mosbrucker, Adam

2014-01-01

The lateral blast, debris avalanche, and lahars of the May 18th, 1980, eruption of Mount St. Helens, Washington, dramatically altered the surrounding landscape. Lava domes were extruded during the subsequent eruptive periods of 1980–1986 and 2004–2008. More than three decades after the emplacement of the 1980 debris avalanche, high sediment production persists in the North Fork Toutle River basin, which drains the northern flank of the volcano. Because this sediment increases the risk of flooding to downstream communities on the Toutle and Cowlitz Rivers, the U.S. Army Corps of Engineers (USACE), under the direction of Congress to maintain an authorized level of flood protection, built a sediment retention structure on the North Fork Toutle River in 1989 to help reduce this risk and to prevent sediment from clogging the shipping channel of the Columbia River. From September 16–20, 2009, Watershed Sciences, Inc., under contract to USACE, collected high-precision airborne lidar (light detection and ranging) data that cover 214 square kilometers (83 square miles) of Mount St. Helens and the upper North Fork Toutle River basin from the sediment retention structure to the volcano's crater. These data provide a digital dataset of the ground surface, including beneath forest cover. Such remotely sensed data can be used to develop sediment budgets and models of sediment erosion, transport, and deposition. The U.S. Geological Survey (USGS) used these lidar data to develop digital elevation models (DEMs) of the study area. DEMs are fundamental to monitoring natural hazards and studying volcanic landforms, fluvial and glacial geomorphology, and surface geology. Watershed Sciences, Inc., provided files in the LASer (LAS) format containing laser returns that had been filtered, classified, and georeferenced. The USGS produced a hydro-flattened DEM from ground-classified points at Castle, Coldwater, and Spirit Lakes. Final results averaged about five laser last-return points per square meter. As reported by Watershed Sciences, Inc., vertical accuracy is 10 centimeters (cm) at the 95-percent confidence interval on bare road surfaces; however, over natural terrain, USGS found vertical accuracy to be 10–50 cm. This USGS data series contains the bare-earth lidar data as 1- and 10-meter (m) resolution Esri grid files. Digital-elevation data can be downloaded (1m_DEM.zip and 10m_DEM.zip), as well as a 1-m resolution hillshade image with pyramids (1m_hillshade.zip). These geospatial data files require geographic information system (GIS) software for viewing.

Evaluation of Elevation, Slope and Stream Network Quality of SPOT Dems

NASA Astrophysics Data System (ADS)

El Hage, M.; Simonetto, E.; Faour, G.; Polidori, L.

2012-07-01

Digital elevation models are considered the most useful data for dealing with geomorphology. The quality of these models is an important issue for users. This quality concerns position and shape. Vertical accuracy is the most assessed in many studies and shape quality is often neglected. However, both of them have an impact on the quality of the final results for a particular application. For instance, the elevation accuracy is required for orthorectification and the shape quality for geomorphology and hydrology. In this study, we deal with photogrammetric DEMs and show the importance of the quality assessment of both elevation and shape. For this purpose, we produce several SPOT HRV DEMs with the same dataset but with different template size, that is one of the production parameters from optical images. Then, we evaluate both elevation and shape quality. The shape quality is assessed with in situ measurements and analysis of slopes as an elementary shape and stream networks as a complex shape. We use the fractal dimension and sinuosity to evaluate the stream network shape. The results show that the elevation accuracy as well as the slope accuracy are affected by the template size. Indeed, an improvement of 1 m in the elevation accuracy and of 5 degrees in the slope accuracy has been obtained while changing this parameter. The elevation RMSE ranges from 7.6 to 8.6 m, which is smaller than the pixel size (10 m). For slope, the RMSE depends on the sampling distance. With a distance of 10 m, the minimum slope RMSE is 11.4 degrees. The stream networks extracted from these DEMs present a higher fractal dimension than the reference river. Moreover, the fractal dimension of the extracted networks has a negligible change according to the template size. Finally, the sinuosity of the stream networks is slightly affected by the change of the template size.

Forest Fire Danger Rating (FFDR) Prediction over the Korean Peninsula

NASA Astrophysics Data System (ADS)

Song, B.; Won, M.; Jang, K.; Yoon, S.; Lim, J.

2016-12-01

Approximately five hundred forest fires occur and inflict the losses of both life and property each year in Korea during the forest fire seasons in the spring and autumn. Thus, an accurate prediction of forest fire is essential for effective forest fire prevention. The meteorology is one of important factors to predict and understand the fire occurrence as well as its behaviors and spread. In this study, we present the Forest Fire Danger Rating Systems (FFDRS) on the Korean Peninsula based on the Daily Weather Index (DWI) which represents the meteorological characteristics related to forest fire. The thematic maps including temperature, humidity, and wind speed produced from Korea Meteorology Administration (KMA) were applied to the forest fire occurrence probability model by logistic regression to analyze the DWI over the Korean Peninsula. The regional data assimilation and prediction system (RDAPS) and the improved digital forecast model were used to verify the sensitivity of DWI. The result of verification test revealed that the improved digital forecast model dataset showed better agreements with the real-time weather data. The forest fire danger rating index (FFDRI) calculated by the improved digital forecast model dataset showed a good agreement with the real-time weather dataset at the 233 administrative districts (R2=0.854). In addition, FFDRI were compared with observation-based FFDRI at 76 national weather stations. The mean difference was 0.5 at the site-level. The results produced in this study indicate that the improved digital forecast model dataset can be useful to predict the FFDRI in the Korean Peninsula successfully.

A geo-spatial data management system for potentially active volcanoes—GEOWARN project

NASA Astrophysics Data System (ADS)

Gogu, Radu C.; Dietrich, Volker J.; Jenny, Bernhard; Schwandner, Florian M.; Hurni, Lorenz

2006-02-01

Integrated studies of active volcanic systems for the purpose of long-term monitoring and forecast and short-term eruption prediction require large numbers of data-sets from various disciplines. A modern database concept has been developed for managing and analyzing multi-disciplinary volcanological data-sets. The GEOWARN project (choosing the "Kos-Yali-Nisyros-Tilos volcanic field, Greece" and the "Campi Flegrei, Italy" as test sites) is oriented toward potentially active volcanoes situated in regions of high geodynamic unrest. This article describes the volcanological database of the spatial and temporal data acquired within the GEOWARN project. As a first step, a spatial database embedded in a Geographic Information System (GIS) environment was created. Digital data of different spatial resolution, and time-series data collected at different intervals or periods, were unified in a common, four-dimensional representation of space and time. The database scheme comprises various information layers containing geographic data (e.g. seafloor and land digital elevation model, satellite imagery, anthropogenic structures, land-use), geophysical data (e.g. from active and passive seismicity, gravity, tomography, SAR interferometry, thermal imagery, differential GPS), geological data (e.g. lithology, structural geology, oceanography), and geochemical data (e.g. from hydrothermal fluid chemistry and diffuse degassing features). As a second step based on the presented database, spatial data analysis has been performed using custom-programmed interfaces that execute query scripts resulting in a graphical visualization of data. These query tools were designed and compiled following scenarios of known "behavior" patterns of dormant volcanoes and first candidate signs of potential unrest. The spatial database and query approach is intended to facilitate scientific research on volcanic processes and phenomena, and volcanic surveillance.

Measuring Erosion and Deposition During the World's Largest Dam Removal in Near-Real-Time: An Example of 4-Dimensional SfM from the Elwha River, Washington, USA

NASA Astrophysics Data System (ADS)

Ritchie, A.; Bountry, J.; Randle, T. J.; Warrick, J. A.

2016-12-01

The stepwise removal of two dams on the Elwha River beginning in September 2011 exposed 21 million cubic meters of sediment to fluvial erosion and created an unprecedented opportunity to monitor reservoir sediment erosion and river evolution during base level adjustment and a pulsed sediment release. We conduct repeat aerial surveys with a Cessna 172 using a simple custom wing-mount for consumer grade cameras and SfM photogrammetry to produce orthoimagery and digital elevation models in near-real-time at sub-weekly to monthly time intervals, depending on hydrology. Multiple lidar flights and ground survey campaigns provide estimates of both systematic and random error for this uniquely dense dataset. Co-registration of multiple SfM surveys during processing reduces systematic error and allows boot-strapping of ephemeral ground control points to earlier or later flights. Measurements of reservoir erosion volumes, delta growth, channel braiding, and bank erosion illustrate the reservoir and river channel responses to dam removal at resolutions comparable to hydrologic forcing events, allowing us to quantify reservoir sediment budgets on a per-storm basis. This allows for the analysis of sediment transported relative to rates of reservoir drawdown and river stream power for dozens of time intervals. Temporal decoupling of peak sediment flux and bank erosion rates is noted from these analyses. This dataset illustrates both challenges and opportunities emerging with the advent of big data in remote sensing of earth surface processes. Digital AbstractErosion and deposition by year in former Lake Mills reservoir measured using SfM-derived photogrammetry and LiDAR for WY2011 through 2016 (partial). Approximately 70% of available sediment has been eroded.

Three-dimensional displays for natural hazards analysis, using classified Landsat Thematic Mapper digital data and large-scale digital elevation models

NASA Technical Reports Server (NTRS)

Butler, David R.; Walsh, Stephen J.; Brown, Daniel G.

1991-01-01

Methods are described for using Landsat Thematic Mapper digital data and digital elevation models for the display of natural hazard sites in a mountainous region of northwestern Montana, USA. Hazard zones can be easily identified on the three-dimensional images. Proximity of facilities such as highways and building locations to hazard sites can also be easily displayed. A temporal sequence of Landsat TM (or similar) satellite data sets could also be used to display landscape changes associated with dynamic natural hazard processes.

EnviroAtlas - Historic Places by 12-digit HUC for the Conterminous United States

EPA Pesticide Factsheets

This EnviroAtlas dataset portrays the total number of historic places located within each 12-digit Hydrologic Unit (HUC). The historic places data were compiled from the National Park Service's National Register of Historic Places (NRHP), which provides official federal lists of districts, sites, buildings, structures and objects significant to American history, architecture, archeology, engineering, and culture. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

Comparing Methods to Assess Intraobserver Measurement Error of 3D Craniofacial Landmarks Using Geometric Morphometrics Through a Digitizer Arm.

PubMed

Menéndez, Lumila Paula

2017-05-01

Intraobserver error (INTRA-OE) is the difference between repeated measurements of the same variable made by the same observer. The objective of this work was to evaluate INTRA-OE from 3D landmarks registered with a Microscribe, in different datasets: (A) the 3D coordinates, (B) linear measurements calculated from A, and (C) the six-first principal component axes. INTRA-OE was analyzed by digitizing 42 landmarks from 23 skulls in three events two weeks apart from each other. Systematic error was tested through repeated measures ANOVA (ANOVA-RM), while random error through intraclass correlation coefficient. Results showed that the largest differences between the three observations were found in the first dataset. Some anatomical points like nasion, ectoconchion, temporosphenoparietal, asterion, and temporomandibular presented the highest INTRA-OE. In the second dataset, local distances had higher INTRA-OE than global distances while the third dataset showed the lowest INTRA-OE. © 2016 American Academy of Forensic Sciences.

Evaluation of catchment delineation methods for the medium-resolution National Hydrography Dataset

USGS Publications Warehouse

Johnston, Craig M.; Dewald, Thomas G.; Bondelid, Timothy R.; Worstell, Bruce B.; McKay, Lucinda D.; Rea, Alan; Moore, Richard B.; Goodall, Jonathan L.

2009-01-01

Different methods for determining catchments (incremental drainage areas) for stream segments of the medium-resolution (1:100,000-scale) National Hydrography Dataset (NHD) were evaluated by the U.S. Geological Survey (USGS), in cooperation with the U.S. Environmental Protection Agency (USEPA). The NHD is a comprehensive set of digital spatial data that contains information about surface-water features (such as lakes, ponds, streams, and rivers) of the United States. The need for NHD catchments was driven primarily by the goal to estimate NHD streamflow and velocity to support water-quality modeling. The application of catchments for this purpose also demonstrates the broader value of NHD catchments for supporting landscape characterization and analysis. Five catchment delineation methods were evaluated. Four of the methods use topographic information for the delineation of the NHD catchments. These methods include the Raster Seeding Method; two variants of a method first used in a USGS New England study-one used the Watershed Boundary Dataset (WBD) and the other did not-termed the 'New England Methods'; and the Outlet Matching Method. For these topographically based methods, the elevation data source was the 30-meter (m) resolution National Elevation Dataset (NED), as this was the highest resolution available for the conterminous United States and Hawaii. The fifth method evaluated, the Thiessen Polygon Method, uses distance to the nearest NHD stream segments to determine catchment boundaries. Catchments were generated using each method for NHD stream segments within six hydrologically and geographically distinct Subbasins to evaluate the applicability of the method across the United States. The five methods were evaluated by comparing the resulting catchments with the boundaries and the computed area measurements available from several verification datasets that were developed independently using manual methods. The results of the evaluation indicated that the two New England Methods provided the most accurate catchment boundaries. The New England Method with the WBD provided the most accurate results. The time and cost to implement and apply these automated methods were also considered in ultimately selecting the methods used to produce NHD catchments for the conterminous United States and Hawaii. This study was conducted by a joint USGS-USEPA team during the 2-year period that ended in September 2004. During the following 2-year period ending in the fall of 2006, the New England Methods were used to produce NHD catchments as part of a multiagency effort to generate the NHD streamflow and velocity estimates for a suite of integrated geospatial products known as 'NHDPlus.'

Topography- and nightlight-based national flood risk assessment in Canada

NASA Astrophysics Data System (ADS)

Elshorbagy, Amin; Bharath, Raja; Lakhanpal, Anchit; Ceola, Serena; Montanari, Alberto; Lindenschmidt, Karl-Erich

2017-04-01

In Canada, flood analysis and water resource management, in general, are tasks conducted at the provincial level; therefore, unified national-scale approaches to water-related problems are uncommon. In this study, a national-scale flood risk assessment approach is proposed and developed. The study focuses on using global and national datasets available with various resolutions to create flood risk maps. First, a flood hazard map of Canada is developed using topography-based parameters derived from digital elevation models, namely, elevation above nearest drainage (EAND) and distance from nearest drainage (DFND). This flood hazard mapping method is tested on a smaller area around the city of Calgary, Alberta, against a flood inundation map produced by the city using hydraulic modelling. Second, a flood exposure map of Canada is developed using a land-use map and the satellite-based nightlight luminosity data as two exposure parameters. Third, an economic flood risk map is produced, and subsequently overlaid with population density information to produce a socioeconomic flood risk map for Canada. All three maps of hazard, exposure, and risk are classified into five classes, ranging from very low to severe. A simple way to include flood protection measures in hazard estimation is also demonstrated using the example of the city of Winnipeg, Manitoba. This could be done for the entire country if information on flood protection across Canada were available. The evaluation of the flood hazard map shows that the topography-based method adopted in this study is both practical and reliable for large-scale analysis. Sensitivity analysis regarding the resolution of the digital elevation model is needed to identify the resolution that is fine enough for reliable hazard mapping, but coarse enough for computational tractability. The nightlight data are found to be useful for exposure and risk mapping in Canada; however, uncertainty analysis should be conducted to investigate the effect of the overglow phenomenon on flood risk mapping.

Sparsity based terahertz reflective off-axis digital holography

NASA Astrophysics Data System (ADS)

Wan, Min; Muniraj, Inbarasan; Malallah, Ra'ed; Zhao, Liang; Ryle, James P.; Rong, Lu; Healy, John J.; Wang, Dayong; Sheridan, John T.

2017-05-01

Terahertz radiation lies between the microwave and infrared regions in the electromagnetic spectrum. Emitted frequencies range from 0.1 to 10 THz with corresponding wavelengths ranging from 30 μm to 3 mm. In this paper, a continuous-wave Terahertz off-axis digital holographic system is described. A Gaussian fitting method and image normalisation techniques were employed on the recorded hologram to improve the image resolution. A synthesised contrast enhanced hologram is then digitally constructed. Numerical reconstruction is achieved using the angular spectrum method of the filtered off-axis hologram. A sparsity based compression technique is introduced before numerical data reconstruction in order to reduce the dataset required for hologram reconstruction. Results prove that a tiny amount of sparse dataset is sufficient in order to reconstruct the hologram with good image quality.

A suite of global, cross-scale topographic variables for environmental and biodiversity modeling

NASA Astrophysics Data System (ADS)

Amatulli, Giuseppe; Domisch, Sami; Tuanmu, Mao-Ning; Parmentier, Benoit; Ranipeta, Ajay; Malczyk, Jeremy; Jetz, Walter

2018-03-01

Topographic variation underpins a myriad of patterns and processes in hydrology, climatology, geography and ecology and is key to understanding the variation of life on the planet. A fully standardized and global multivariate product of different terrain features has the potential to support many large-scale research applications, however to date, such datasets are unavailable. Here we used the digital elevation model products of global 250 m GMTED2010 and near-global 90 m SRTM4.1dev to derive a suite of topographic variables: elevation, slope, aspect, eastness, northness, roughness, terrain roughness index, topographic position index, vector ruggedness measure, profile/tangential curvature, first/second order partial derivative, and 10 geomorphological landform classes. We aggregated each variable to 1, 5, 10, 50 and 100 km spatial grains using several aggregation approaches. While a cross-correlation underlines the high similarity of many variables, a more detailed view in four mountain regions reveals local differences, as well as scale variations in the aggregated variables at different spatial grains. All newly-developed variables are available for download at Data Citation 1 and for download and visualization at http://www.earthenv.org/topography.

Characterization of Lunar Polar Illumination from a Power System Perspective

NASA Technical Reports Server (NTRS)

Fincannon, James

2008-01-01

This paper presents the results of illumination analyses for the lunar south and north pole regions obtained using an independently developed analytical tool and two types of digital elevation models (DEM). One DEM was based on radar height data from Earth observations of the lunar surface and the other was a combination of the radar data with a separate dataset generated using Clementine spacecraft stereo imagery. The analysis tool enables the assessment of illumination at most locations in the lunar polar regions for any time and any year. Maps are presented for both lunar poles for the worst case winter period (the critical power system design and planning bottleneck) and for the more favorable best case summer period. Average illumination maps are presented to help understand general topographic trends over the regions. Energy storage duration maps are presented to assist in power system design. Average illumination fraction, energy storage duration, solar/horizon terrain elevation profiles and illumination fraction profiles are presented for favorable lunar north and south pole sites which have the potential for manned or unmanned spacecraft operations. The format of the data is oriented for use by power system designers to develop mass optimized solar and energy storage systems.

An algorithm for treating flat areas and depressions in digital elevation models using linear interpolation

EPA Science Inventory

Digital elevation model (DEM) data are essential to hydrological applications and have been widely used to calculate a variety of useful topographic characteristics, e.g., slope, flow direction, flow accumulation area, stream channel network, topographic index, and others. Excep...

NHDPlusHR: A national geospatial framework for surface-water information

USGS Publications Warehouse

Viger, Roland; Rea, Alan H.; Simley, Jeffrey D.; Hanson, Karen M.

2016-01-01

The U.S. Geological Survey is developing a new geospatial hydrographic framework for the United States, called the National Hydrography Dataset Plus High Resolution (NHDPlusHR), that integrates a diversity of the best-available information, robustly supports ongoing dataset improvements, enables hydrographic generalization to derive alternate representations of the network while maintaining feature identity, and supports modern scientific computing and Internet accessibility needs. This framework is based on the High Resolution National Hydrography Dataset, the Watershed Boundaries Dataset, and elevation from the 3-D Elevation Program, and will provide an authoritative, high precision, and attribute-rich geospatial framework for surface-water information for the United States. Using this common geospatial framework will provide a consistent basis for indexing water information in the United States, eliminate redundancy, and harmonize access to, and exchange of water information.

UAV-based photogrammetry combination of the elevational outcrop and digital surface models: an example of Sanyi active fault in western Taiwan

NASA Astrophysics Data System (ADS)

Hsieh, Cheng-En; Huang, Wen-Jeng; Chang, Ping-Yu; Lo, Wei

2016-04-01

An unmanned aerial vehicle (UAV) with a digital camera is an efficient tool for geologists to investigate structure patterns in the field. By setting ground control points (GCPs), UAV-based photogrammetry provides high-quality and quantitative results such as a digital surface model (DSM) and orthomosaic and elevational images. We combine the elevational outcrop 3D model and a digital surface model together to analyze the structural characteristics of Sanyi active fault in Houli-Fengyuan area, western Taiwan. Furthermore, we collect resistivity survey profiles and drilling core data in the Fengyuan District in order to build the subsurface fault geometry. The ground sample distance (GSD) of an elevational outcrop 3D model is 3.64 cm/pixel in this study. Our preliminary result shows that 5 fault branches are distributed 500 meters wide on the elevational outcrop and the width of Sanyi fault zone is likely much great than this value. Together with our field observations, we propose a structural evolution model to demonstrate how the 5 fault branches developed. The resistivity survey profiles show that Holocene gravel was disturbed by the Sanyi fault in Fengyuan area.

ATM Coastal Topography-Alabama 2001

USGS Publications Warehouse

Nayegandhi, Amar; Yates, Xan; Brock, John C.; Sallenger, A.H.; Bonisteel, Jamie M.; Klipp, Emily S.; Wright, C. Wayne

2009-01-01

These remotely sensed, geographically referenced elevation measurements of Lidar-derived first surface (FS) topography were produced collaboratively by the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of the Alabama coastline, acquired October 3-4, 2001. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative scanning Lidar instrument originally developed by NASA, and known as the Airborne Topographic Mapper (ATM), was used during data acquisition. The ATM system is a scanning Lidar system that measures high-resolution topography of the land surface, and incorporates a green-wavelength laser operating at pulse rates of 2 to 10 kilohertz. Measurements from the laser ranging device are coupled with data acquired from inertial navigation system (INS) attitude sensors and differentially corrected global positioning system (GPS) receivers to measure topography of the surface at accuracies of +/-15 centimeters. The nominal ATM platform is a Twin Otter or P-3 Orion aircraft, but the instrument may be deployed on a range of light aircraft. Elevation measurements were collected over the survey area using the ATM system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for pre-survey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is routinely used to create maps that represent submerged or first surface topography.

ATM Coastal Topography-Florida 2001: Eastern Panhandle

USGS Publications Warehouse

Yates, Xan; Nayegandhi, Amar; Brock, John C.; Sallenger, A.H.; Bonisteel, Jamie M.; Klipp, Emily S.; Wright, C. Wayne

2009-01-01

These remotely sensed, geographically referenced elevation measurements of Lidar-derived first surface (FS) topography were produced collaboratively by the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of the eastern Florida panhandle coastline, acquired October 2, 2001. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative scanning Lidar instrument originally developed by NASA, and known as the Airborne Topographic Mapper (ATM), was used during data acquisition. The ATM system is a scanning Lidar system that measures high-resolution topography of the land surface and incorporates a green-wavelength laser operating at pulse rates of 2 to 10 kilohertz. Measurements from the laser-ranging device are coupled with data acquired from inertial navigation system (INS) attitude sensors and differentially corrected global positioning system (GPS) receivers to measure topography of the surface at accuracies of +/-15 centimeters. The nominal ATM platform is a Twin Otter or P-3 Orion aircraft, but the instrument may be deployed on a range of light aircraft. Elevation measurements were collected over the survey area using the ATM system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for presurvey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is routinely used to create maps that represent submerged or first surface topography.

Historical analysis and visualization of the retreat of Findelengletscher, Switzerland, 1859-2010

NASA Astrophysics Data System (ADS)

Rastner, P.; Joerg, P. C.; Huss, M.; Zemp, M.

2016-10-01

Since the end of the Little Ice Age around 1850, glaciers in Europe have strongly retreated. Thanks to early topographic surveys in Switzerland, accurate maps are available, which enable us to trace glacier changes back in time. The earliest map for all of Switzerland that is usable for a detailed analysis is the Dufour map from around 1850 with subsequent topographic maps on a 20 year interval. Despite the large public and scientific interest in glacier changes through time, this historic dataset has not yet been fully utilized for topographic change assessment or visualization of historic glacier extents. In this study, we use eleven historical topographic maps and more recent digital datasets for the region of Zermatt to analyze geometric changes (length, area and volume) of Findelengletscher as well as for creating animations of glacier evolution through time for use in public communication. All maps were georeferenced, the contour lines digitized, and digital elevation models (DEMs) created and co-registered. Additional digital data like the SRTM X-band DEM and high resolution laser scanning data were used to extend the analysis until 2010. Moreover, one independent DEM from aerial photogrammetry was used for comparison. During the period 1859-2010, Findelengletscher lost 3.5 km of its length (6.9 km in 2010), 4.42 ± 0.13 km2 of its area (15.05 ± 0.45 km2 in 2010) and 1.32 ± 0.52 km3 of its volume. The average rate of thickness loss is 0.45 ± 0.042 m yr- 1 for the 151 years period. Four periods with high thickness change from - 0.56 m ± 0.28 yr- 1 (1859-1881), - 0.40 ± 0.08 m yr- 1 (1937-1965), - 0.90 ± 0.31 m yr- 1 (1995-2000) and - 1.18 ± 0.02 m yr- 1 (2000-2005) have been identified. Small positive thickness changes were found for the periods 1890-1909 (+ 0.09 ± 0.46 m yr- 1) and 1988-1995 (+ 0.05 ± 0.24 m yr- 1). During its retreat with intermittent periods of advance, the glacier separated into three parts. The above changes are demonstrated through an animation (available from the supplementary material), which has been created to inform the general public.

Digital spatial data for observed, predicted, and misclassification errors for observations in the training dataset for nitrate and arsenic concentrations in basin-fill aquifers in the Southwest Principal Aquifers study area

USGS Publications Warehouse

McKinney, Tim S.; Anning, David W.

2012-01-01

This product "Digital spatial data for observed, predicted, and misclassification errors for observations in the training dataset for nitrate and arsenic concentrations in basin-fill aquifers in the Southwest Principal Aquifers study area" is a 1:250,000-scale point spatial dataset developed as part of a regional Southwest Principal Aquifers (SWPA) study (Anning and others, 2012). The study examined the vulnerability of basin-fill aquifers in the southwestern United States to nitrate contamination and arsenic enrichment. Statistical models were developed by using the random forest classifier algorithm to predict concentrations of nitrate and arsenic across a model grid that represents local- and basin-scale measures of source, aquifer susceptibility, and geochemical conditions.

Distribution patterns in the native vascular flora of Iceland.

PubMed

Wasowicz, Pawel; Pasierbiński, Andrzej; Przedpelska-Wasowicz, Ewa Maria; Kristinsson, Hörður

2014-01-01

The aim of our study was to reveal biogeographical patterns in the native vascular flora of Iceland and to define ecological factors responsible for these patterns. We analysed dataset of more than 500,000 records containing information on the occurrence of vascular plants. Analysis of ecological factors included climatic (derived from WORLDCLIM data), topographic (calculated from digital elevation model) and geological (bedrock characteristics) variables. Spherical k-means clustering and principal component analysis were used to detect biogeographical patterns and to study the factors responsible for them. We defined 10 biotic elements exhibiting different biogeographical patterns. We showed that climatic (temperature-related) and topographic variables were the most important factors contributing to the spatial patterns within the Icelandic vascular flora and that these patterns are almost completely independent of edaphic factors (bedrock type). Our study is the first one to analyse the biogeographical differentiation of the native vascular flora of Iceland.

BanglaLekha-Isolated: A multi-purpose comprehensive dataset of Handwritten Bangla Isolated characters.

PubMed

Biswas, Mithun; Islam, Rafiqul; Shom, Gautam Kumar; Shopon, Md; Mohammed, Nabeel; Momen, Sifat; Abedin, Anowarul

2017-06-01

BanglaLekha-Isolated, a Bangla handwritten isolated character dataset is presented in this article. This dataset contains 84 different characters comprising of 50 Bangla basic characters, 10 Bangla numerals and 24 selected compound characters. 2000 handwriting samples for each of the 84 characters were collected, digitized and pre-processed. After discarding mistakes and scribbles, 1,66,105 handwritten character images were included in the final dataset. The dataset also includes labels indicating the age and the gender of the subjects from whom the samples were collected. This dataset could be used not only for optical handwriting recognition research but also to explore the influence of gender and age on handwriting. The dataset is publicly available at https://data.mendeley.com/datasets/hf6sf8zrkc/2.

EnviroAtlas - Average Annual Precipitation 1981-2010 by HUC12 for the Conterminous United States

EPA Pesticide Factsheets

This EnviroAtlas dataset provides the average annual precipitation by 12-digit Hydrologic Unit (HUC). The values were estimated from maps produced by the PRISM Climate Group, Oregon State University. The original data was at the scale of 800 m grid cells representing average precipitation from 1981-2010 in mm. The data was converted to inches of precipitation and then zonal statistics were estimated for a final value of average annual precipitation for each 12 digit HUC. For more information about the original dataset please refer to the PRISM website at http://www.prism.oregonstate.edu/. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

Database for the geologic map of Upper Geyser Basin, Yellowstone National Park, Wyoming

USGS Publications Warehouse

Abendini, Atosa A.; Robinson, Joel E.; Muffler, L. J. Patrick; White, D. E.; Beeson, Melvin H.; Truesdell, A. H.

2015-01-01

This dataset contains contacts, geologic units, and map boundaries from Miscellaneous Investigations Series Map I-1371, "The Geologic map of upper Geyser Basin, Yellowstone, National Park, Wyoming". This dataset was constructed to produce a digital geologic map as a basis for ongoing studies of hydrothermal processes.

Recording, monitoring and managing the conservation of historic sites: a new application for BGS·SIGMA

NASA Astrophysics Data System (ADS)

Tracey, Emily; Smith, Nichola; Lawrie, Ken

2017-04-01

The principles behind, and the methods of, digital data capture can be applied across many scientific, and other, disciplines, as can be demonstrated by the use of a custom modified version of the British Geological Survey's System for Integrated Geoscience Mapping, (BGS·SIGMA), for the capture of data for use in the conservation of Scottish built heritage. Historic Environment Scotland (HES), an executive agency of the Scottish Government charged with safeguarding the nation's historic environment, is directly responsible for 345 sites of national significance, most of which are built from stone. In common with many other heritage organisations, HES needs a system that can capture, store and present conservation, maintenance and condition indicator information for single or multiple historic sites; this system would then be used to better target and plan effective programmes of maintenance and repair. To meet this need, the British Geological Survey (BGS) has worked with HES to develop an integrated digital site assessment system that provides a refined survey process for stone-built (and other) historic sites. Based on BGS·SIGMA—an integrated workflow underpinned by a geo-spatial platform for data capture and interpretation—the new system is built on top of ESRI's ArcGIS software, and underpinned by a relational database. Users can, in the field or in the office, populate custom-built data entry forms to record maintenance issues and repair specifications for architectural elements ranging from individual blocks of stone to entire building elevations. Photographs, sketches, and digital documents can be linked to architectural elements to enhance the usability of the data. Predetermined data fields and supporting dictionaries constrain the input parameters, ensuring a high degree of standardisation in the datasets and, therefore, enabling highly consistent data extraction and querying. The GIS presentation of the data provides a powerful and versatile planning tool for scheduling works, specifying materials, identifying the skills needed for repairs, and allocating resources more effectively and efficiently. Physical alterations and changes in the overall condition of a single site, or a group of sites can be monitored accurately over time by repeating the original survey (e.g. every 5 years). Other datasets can be linked to the database and other geospatially referenced datasets can be superimposed in GIS, adding considerably to the scope and utility of the system. The system can be applied to any geospatially referenced object in a wide range of situations thus providing many potential applications in conservation, archaeology and other related fields.

Gsflow-py: An integrated hydrologic model development tool

NASA Astrophysics Data System (ADS)

Gardner, M.; Niswonger, R. G.; Morton, C.; Henson, W.; Huntington, J. L.

2017-12-01

Integrated hydrologic modeling encompasses a vast number of processes and specifications, variable in time and space, and development of model datasets can be arduous. Model input construction techniques have not been formalized or made easily reproducible. Creating the input files for integrated hydrologic models (IHM) requires complex GIS processing of raster and vector datasets from various sources. Developing stream network topology that is consistent with the model resolution digital elevation model is important for robust simulation of surface water and groundwater exchanges. Distribution of meteorologic parameters over the model domain is difficult in complex terrain at the model resolution scale, but is necessary to drive realistic simulations. Historically, development of input data for IHM models has required extensive GIS and computer programming expertise which has restricted the use of IHMs to research groups with available financial, human, and technical resources. Here we present a series of Python scripts that provide a formalized technique for the parameterization and development of integrated hydrologic model inputs for GSFLOW. With some modifications, this process could be applied to any regular grid hydrologic model. This Python toolkit automates many of the necessary and laborious processes of parameterization, including stream network development and cascade routing, land coverages, and meteorological distribution over the model domain.

Everglades Depth Estimation Network (EDEN)—A decade of serving hydrologic information to scientists and resource managers

USGS Publications Warehouse

Patino, Eduardo; Conrads, Paul; Swain, Eric; Beerens, James M.

2017-10-30

IntroductionThe Everglades Depth Estimation Network (EDEN) provides scientists and resource managers with regional maps of daily water levels and depths in the freshwater part of the Greater Everglades landscape. The EDEN domain includes all or parts of five Water Conservation Areas, Big Cypress National Preserve, Pennsuco Wetlands, and Everglades National Park. Daily water-level maps are interpolated from water-level data at monitoring gages, and depth is estimated by using a digital elevation model of the land surface. Online datasets provide time series of daily water levels at gages and rainfall and evapotranspiration data (https://sofia.usgs.gov/eden/). These datasets are used by scientists and resource managers to guide large-scale field operations, describe hydrologic changes, and support biological and ecological assessments that measure ecosystem response to the implementation of the Comprehensive Everglades Restoration Plan. EDEN water-level data have been used in a variety of biological and ecological studies including (1) the health of American alligators as a function of water depth, (2) the variability of post-fire landscape dynamics in relation to water depth, (3) the habitat quality for wading birds with dynamic habitat selection, and (4) an evaluation of the habitat of the Cape Sable seaside sparrow.

Spectral Topography Generation for Arbitrary Grids

NASA Astrophysics Data System (ADS)

Oh, T. J.

2015-12-01

A new topography generation tool utilizing spectral transformation technique for both structured and unstructured grids is presented. For the source global digital elevation data, the NASA Shuttle Radar Topography Mission (SRTM) 15 arc-second dataset (gap-filling by Jonathan de Ferranti) is used and for land/water mask source, the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) 30 arc-second land water mask dataset v5 is used. The original source data is coarsened to a intermediate global 2 minute lat-lon mesh. Then, spectral transformation to the wave space and inverse transformation with wavenumber truncation is performed for isotropic topography smoothness control. Target grid topography mapping is done by bivariate cubic spline interpolation from the truncated 2 minute lat-lon topography. Gibbs phenomenon in the water region can be removed by overwriting ocean masked target coordinate grids with interpolated values from the intermediate 2 minute grid. Finally, a weak smoothing operator is applied on the target grid to minimize the land/water surface height discontinuity that might have been introduced by the Gibbs oscillation removal procedure. Overall, the new topography generation approach provides spectrally-derived, smooth topography with isotropic resolution and minimum damping, enabling realistic topography forcing in the numerical model. Topography is generated for the cubed-sphere grid and tested on the KIAPS Integrated Model (KIM).

A Comparison of Mangrove Canopy Height Using Multiple Independent Measurements from Land, Air, and Space

NASA Technical Reports Server (NTRS)

Lagomasino, David; Fatoyinbo, Temilola; Lee, SeungKuk; Feliciano, Emanuelle; Trettin, Carl; Simard, Marc

2016-01-01

Canopy height is one of the strongest predictors of biomass and carbon in forested ecosystems. Additionally, mangrove ecosystems represent one of the most concentrated carbon reservoirs that are rapidly degrading as a result of deforestation, development, and hydrologic manipulation. Therefore, the accuracy of Canopy Height Models (CHM) over mangrove forest can provide crucial information for monitoring and verification protocols. We compared four CHMs derived from independent remotely sensed imagery and identified potential errors and bias between measurement types. CHMs were derived from three spaceborne datasets; Very-High Resolution (VHR) stereophotogrammetry, TerraSAR-X add-on for Digital Elevation Measurement (DEM), and Shuttle Radar Topography Mission (TanDEM-X), and lidar data which was acquired from an airborne platform. Each dataset exhibited different error characteristics that were related to spatial resolution, sensitivities of the sensors, and reference frames. Canopies over 10 meters were accurately predicted by all CHMs while the distributions of canopy height were best predicted by the VHR CHM. Depending on the guidelines and strategies needed for monitoring and verification activities, coarse resolution CHMs could be used to track canopy height at regional and global scales with finer resolution imagery used to validate and monitor critical areas undergoing rapid changes.

A Comparison of Mangrove Canopy Height Using Multiple Independent Measurements from Land, Air, and Space

PubMed Central

Lagomasino, David; Fatoyinbo, Temilola; Lee, SeungKuk; Feliciano, Emanuelle; Trettin, Carl; Simard, Marc

2017-01-01

Canopy height is one of the strongest predictors of biomass and carbon in forested ecosystems. Additionally, mangrove ecosystems represent one of the most concentrated carbon reservoirs that are rapidly degrading as a result of deforestation, development, and hydrologic manipulation. Therefore, the accuracy of Canopy Height Models (CHM) over mangrove forest can provide crucial information for monitoring and verification protocols. We compared four CHMs derived from independent remotely sensed imagery and identified potential errors and bias between measurement types. CHMs were derived from three spaceborne datasets; Very-High Resolution (VHR) stereophotogrammetry, TerraSAR-X add-on for Digital Elevation Measurement, and Shuttle Radar Topography Mission (TanDEM-X), and lidar data which was acquired from an airborne platform. Each dataset exhibited different error characteristics that were related to spatial resolution, sensitivities of the sensors, and reference frames. Canopies over 10 m were accurately predicted by all CHMs while the distributions of canopy height were best predicted by the VHR CHM. Depending on the guidelines and strategies needed for monitoring and verification activities, coarse resolution CHMs could be used to track canopy height at regional and global scales with finer resolution imagery used to validate and monitor critical areas undergoing rapid changes. PMID:29629207

Handwritten mathematical symbols dataset.

PubMed

Chajri, Yassine; Bouikhalene, Belaid

2016-06-01

Due to the technological advances in recent years, paper scientific documents are used less and less. Thus, the trend in the scientific community to use digital documents has increased considerably. Among these documents, there are scientific documents and more specifically mathematics documents. In this context, we present our own dataset of handwritten mathematical symbols composed of 10,379 images. This dataset gathers Arabic characters, Latin characters, Arabic numerals, Latin numerals, arithmetic operators, set-symbols, comparison symbols, delimiters, etc.

Quantitative fractography by digital image processing: NIH Image macro tools for stereo pair analysis and 3-D reconstruction.

PubMed

Hein, L R

2001-10-01

A set of NIH Image macro programs was developed to make qualitative and quantitative analyses from digital stereo pictures produced by scanning electron microscopes. These tools were designed for image alignment, anaglyph representation, animation, reconstruction of true elevation surfaces, reconstruction of elevation profiles, true-scale elevation mapping and, for the quantitative approach, surface area and roughness calculations. Limitations on time processing, scanning techniques and programming concepts are also discussed.

Use of slope, aspect, and elevation maps derived from digital elevation model data in making soil surveys

USGS Publications Warehouse

Klingebiel, A.A.; Horvath, E.H.; Moore, D.G.; Reybold, W.U.

1987-01-01

Maps showing different classes of slope, aspect, and elevation were developed from U.S. Geological Survey digital elevation model data. The classes were displayed on clear Mylar at 1:24 000-scale and registered with topographic maps and orthophotos. The maps were used with aerial photographs, topographic maps, and other resource data to determine their value in making order-three soil surveys. They were tested on over 600 000 ha in Wyoming, Idaho, and Nevada under various climatic and topographic conditions. Field evaluations showed that the maps developed from digital elevation model data were accurate, except for slope class maps where slopes were <4%. The maps were useful to soil scientists, especially where (i) class boundaries coincided with soil changes, landform delineations, land use and management separations, and vegetation changes, and (ii) rough terrain and dense vegetation made it difficult to traverse the area. In hot, arid areas of sparse vegetation, the relationship of slope classes to kinds of soil and vegetation was less significant.

A downscaled 1 km dataset of daily Greenland ice sheet surface mass balance components (1958-2014)

NASA Astrophysics Data System (ADS)

Noel, B.; Van De Berg, W. J.; Fettweis, X.; Machguth, H.; Howat, I. M.; van den Broeke, M. R.

2015-12-01

The current spatial resolution in regional climate models (RCMs), typically around 5 to 20 km, remains too coarse to accurately reproduce the spatial variability in surface mass balance (SMB) components over the narrow ablation zones, marginal outlet glaciers and neighbouring ice caps of the Greenland ice sheet (GrIS). In these topographically rough terrains, the SMB components are highly dependent on local variations in topography. However, the relatively low-resolution elevation and ice mask prescribed in RCMs contribute to significantly underestimate melt and runoff in these regions due to unresolved valley glaciers and fjords. Therefore, near-km resolution topography is essential to better capture SMB variability in these spatially restricted regions. We present a 1 km resolution dataset of daily GrIS SMB covering the period 1958-2014, which is statistically downscaled from data of the polar regional climate model RACMO2.3 at 11 km, using an elevation dependence. The dataset includes all individual SMB components projected on the elevation and ice mask from the GIMP DEM, down-sampled to 1 km. Daily runoff and sublimation are interpolated to the 1 km topography using a local regression to elevation valid for each day specifically; daily precipitation is bi-linearly downscaled without elevation corrections. The daily SMB dataset is then reconstructed by summing downscaled precipitation, sublimation and runoff. High-resolution elevation and ice mask allow for properly resolving the narrow ablation zones and valley glaciers at the GrIS margins, leading to significant increase in runoff estimate. In these regions, and especially over narrow glaciers tongues, the downscaled products improve on the original RACMO2.3 outputs by better representing local SMB patterns through a gradual ablation increase towards the GrIS margins. We discuss the impact of downscaling on the SMB components in a case study for a spatially restricted region, where large elevation discrepancies are observed between both resolutions. Owing to generally enhanced runoff in the GrIS ablation zone, the evaluation of daily downscaled SMB against ablation measurements, collected at in-situ measuring sites derived from a newly compiled ablation dataset, shows a better agreement with observations relative to native RACMO2.3 SMB at 11 km.

Tillage practices in the conterminous United States, 1989-2004-Datasets Aggregated by Watershed

USGS Publications Warehouse

Baker, Nancy T.

2011-01-01

This report documents the methods used to aggregate county-level tillage practices to the 8-digit hydrologic unit (HU) watershed. The original county-level data were collected by the Conservation Technology Information Center (CTIC). The CTIC collects tillage data by conducting surveys about tillage systems for all counties in the United States. Tillage systems include three types of conservation tillage (no-till, ridge-till, and mulch-till), reduced tillage, and intensive tillage. Total planted acreage for each tillage practice for each crop grown is reported to the CTIC. The dataset includes total planted acreage by tillage type for selected crops (corn, cotton, grain sorghum, soybeans, fallow, forage, newly established permanent pasture, spring and fall seeded small grains, and 'other' crops) for 1989-2004. Two tabular datasets, based on the 1992 enhanced and 2001 National Land Cover Data (NLCD), are provided as part of this report and include the land-cover area-weighted interpolation and aggregation of acreage for each tillage practice in each 8-digit HU watershed in the conterminous United States for each crop. Watershed aggregations were done by overlying the 8-digit HU polygons with a raster of county boundaries and a raster of either the enhanced 1992 or the 2001 NLCD for cultivated land to derive a county/land-cover area weighting factor. The weighting factor then was applied to the county-level tillage data for the counties within each 8-digit HU and summed to yield the total acreage of each tillage type within each 8-digit HU watershed.

Development of a LiDAR derived digital elevation model (DEM) as Input to a METRANS geographic information system (GIS).

DOT National Transportation Integrated Search

2011-05-01

This report describes an assessment of digital elevation models (DEMs) derived from : LiDAR data for a subset of the Ports of Los Angeles and Long Beach. A methodology : based on Monte Carlo simulation was applied to investigate the accuracy of DEMs ...

EAARL Coastal Topography - Northern Gulf of Mexico

USGS Publications Warehouse

Nayegandhi, Amar; Brock, John C.; Sallenger, Abby; Wright, C. Wayne; Travers, Laurinda J.; Lebonitte, James

2008-01-01

These remotely sensed, geographically referenced elevation measurements of Lidar-derived coastal topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. One objective of this research is to create techniques to survey areas for the purposes of geomorphic change studies following major storm events. The USGS Coastal and Marine Geology Program's National Assessment of Coastal Change Hazards project is a multi-year undertaking to identify and quantify the vulnerability of U.S. shorelines to coastal change hazards such as effects of severe storms, sea-level rise, and shoreline erosion and retreat. Airborne Lidar surveys conducted during periods of calm weather are compared to surveys collected following extreme storms in order to quantify the resulting coastal change. Other applications of high-resolution topography include habitat mapping, ecological monitoring, volumetric change detection, and event assessment. The purpose of this project is to provide highly detailed and accurate datasets of the northern Gulf of Mexico coastal areas, acquired on September 19, 2004, immediately following Hurricane Ivan. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative airborne Lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Airborne Advanced Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532 nanometer) Lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive Lidar, a down-looking RGB (red-green-blue) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers and an integrated miniature digital inertial measurement unit which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a Lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system on September 19, 2004. The survey resulted in the acquisition of 3.2 gigabytes of data. The data were processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for pre-survey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is routinely used to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of 'last return' elevations.

The National Map seamless digital elevation model specifications

USGS Publications Warehouse

Archuleta, Christy-Ann M.; Constance, Eric W.; Arundel, Samantha T.; Lowe, Amanda J.; Mantey, Kimberly S.; Phillips, Lori A.

2017-08-02

This specification documents the requirements and standards used to produce the seamless elevation layers for The National Map of the United States. Seamless elevation data are available for the conterminous United States, Hawaii, Alaska, and the U.S. territories, in three different resolutions—1/3-arc-second, 1-arc-second, and 2-arc-second. These specifications include requirements and standards information about source data requirements, spatial reference system, distribution tiling schemes, horizontal resolution, vertical accuracy, digital elevation model surface treatment, georeferencing, data source and tile dates, distribution and supporting file formats, void areas, metadata, spatial metadata, and quality assurance and control.

New land surface digital elevation model covers the Earth

USGS Publications Warehouse

Gesch, Dean B.; Verdin, Kristine L.; Greenlee, Susan K.

1999-01-01

Land surface elevation around the world is reaching new heights—as far as its description and measurement goes. A new global digital elevation model (DEM) is being cited as a significant improvement in the quality of topographic data available for Earth science studies.Land surface elevation is one of the Earth's most fundamental geophysical properties, but the accuracy and detail with which it has been measured and described globally have been insufficient for many large-area studies. The new model, developed at the U.S. Geological Survey's (USGS) EROS Data Center (EDC), has changed all that.

Geomorphological mapping with a small unmanned aircraft system (sUAS): Feature detection and accuracy assessment of a photogrammetrically-derived digital terrain model

NASA Astrophysics Data System (ADS)

Hugenholtz, Chris H.; Whitehead, Ken; Brown, Owen W.; Barchyn, Thomas E.; Moorman, Brian J.; LeClair, Adam; Riddell, Kevin; Hamilton, Tayler

2013-07-01

Small unmanned aircraft systems (sUAS) are a relatively new type of aerial platform for acquiring high-resolution remote sensing measurements of Earth surface processes and landforms. However, despite growing application there has been little quantitative assessment of sUAS performance. Here we present results from a field experiment designed to evaluate the accuracy of a photogrammetrically-derived digital terrain model (DTM) developed from imagery acquired with a low-cost digital camera onboard an sUAS. We also show the utility of the high-resolution (0.1 m) sUAS imagery for resolving small-scale biogeomorphic features. The experiment was conducted in an area with active and stabilized aeolian landforms in the southern Canadian Prairies. Images were acquired with a Hawkeye RQ-84Z Areohawk fixed-wing sUAS. A total of 280 images were acquired along 14 flight lines, covering an area of 1.95 km2. The survey was completed in 4.5 h, including GPS surveying, sUAS setup and flight time. Standard image processing and photogrammetric techniques were used to produce a 1 m resolution DTM and a 0.1 m resolution orthorectified image mosaic. The latter revealed previously un-mapped bioturbation features. The vertical accuracy of the DTM was evaluated with 99 Real-Time Kinematic GPS points, while 20 of these points were used to quantify horizontal accuracy. The horizontal root mean squared error (RMSE) of the orthoimage was 0.18 m, while the vertical RMSE of the DTM was 0.29 m, which is equivalent to the RMSE of a bare earth LiDAR DTM for the same site. The combined error from both datasets was used to define a threshold of the minimum elevation difference that could be reliably attributed to erosion or deposition in the seven years separating the sUAS and LiDAR datasets. Overall, our results suggest that sUAS-acquired imagery may provide a low-cost, rapid, and flexible alternative to airborne LiDAR for geomorphological mapping.

Topographic Map of Quadrangle 3768 and 3668, Imam-Saheb (215), Rustaq (216), Baghlan (221), and Taloqan (222) Quadrangles, Afghanistan

USGS Publications Warehouse

Bohannon, Robert G.

2006-01-01

This map was produced from several larger digital datasets. Topography was derived from Shuttle Radar Topography Mission (SRTM) 85-meter digital data. Gaps in the original dataset were filled with data digitized from contours on 1:200,000-scale Soviet General Staff Sheets (1978-1997). Contours were generated by cubic convolution averaged over four pixels using TNTmips surface-modeling capabilities. Minor artifacts resulting from the auto-contouring technique are present. Streams were auto-generated from the SRTM data in TNTmips as flow paths. Flow paths were limited in number by their Horton value on a quadrangle-by-quadrangle basis. Peak elevations were averaged over an area measuring 85 m by 85 m (represented by one pixel), and they are slightly lower than the highest corresponding point on the ground. Cultural data were extracted from files downloaded from the Afghanistan Information Management Service (AIMS) Web site (http://www.aims.org.af). The AIMS files were originally derived from maps produced by the Afghanistan Geodesy and Cartography Head Office (AGCHO). Because cultural features were not derived from the SRTM base, they do not match it precisely. Province boundaries are not exactly located. This map is part of a series that includes a geologic map, a topographic map, a Landsat natural-color-image map, and a Landsat false-color-image map for the USGS/AGS (Afghan Geological Survey) quadrangles covering Afghanistan. The maps for any given quadrangle have the same open-file report (OFR) number but a different letter suffix, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively. The OFR numbers range in sequence from 1092 to 1123. The present map series is to be followed by a second series, in which the geology is reinterpreted on the basis of analysis of remote-sensing data, limited fieldwork, and library research. The second series is to be produced by the USGS in cooperation with the AGS and AGCHO.

Topographic Map of Quadrangle 3368 and Part of Quadrangle 3370, Ghazni (515), Gardez (516), and Jaji-Maydan (517) Quadrangles, Afghanistan

USGS Publications Warehouse

Bohannon, Robert G.

2006-01-01

This map was produced from several larger digital datasets. Topography was derived from Shuttle Radar Topography Mission (SRTM) 85-meter digital data. Gaps in the original dataset were filled with data digitized from contours on 1:200,000-scale Soviet General Staff Sheets (1978-1997). Contours were generated by cubic convolution averaged over four pixels using TNTmips surface-modeling capabilities. Minor artifacts resulting from the auto-contouring technique are present. Streams were auto-generated from the SRTM data in TNTmips as flow paths. Flow paths were limited in number by their Horton value on a quadrangle-by-quadrangle basis. Peak elevations were averaged over an area measuring 85 m by 85 m (represented by one pixel), and they are slightly lower than the highest corresponding point on the ground. Cultural data were extracted from files downloaded from the Afghanistan Information Management Service (AIMS) Web site (http://www.aims.org.af). The AIMS files were originally derived from maps produced by the Afghanistan Geodesy and Cartography Head Office (AGCHO). Because cultural features were not derived from the SRTM base, they do not match it precisely. Province boundaries are not exactly located. This map is part of a series that includes a geologic map, a topographic map, a Landsat natural-color-image map, and a Landsat false-color-image map for the USGS/AGS (Afghan Geological Survey) quadrangles covering Afghanistan. The maps for any given quadrangle have the same open-file number but a different letter suffix, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively. The open-file report (OFR) numbers for each quadrangle range in sequence from 1092 - 1123. The present map series is to be followed by a second series, in which the geology is reinterpreted on the basis of analysis of remote-sensing data, limited fieldwork, and library research. The second series is to be produced by the USGS in cooperation with the AGS and AGCHO.

Topographic Map of Quadrangles 3666 and 3766, Balkh (219), Mazar-I-Sharif (220), Qarqin (213), and Hazara Toghai (214) Quadrangles, Afghanistan

USGS Publications Warehouse

Bohannon, Robert G.

2006-01-01

This map was produced from several larger digital datasets. Topography was derived from Shuttle Radar Topography Mission (SRTM) 85-meter digital data. Gaps in the original dataset were filled with data digitized from contours on 1:200,000-scale Soviet General Staff Sheets (1978-1997). Contours were generated by cubic convolution averaged over four pixels using TNTmips surface-modeling capabilities. Minor artifacts resulting from the auto-contouring technique are present. Streams were auto-generated from the SRTM data in TNTmips as flow paths. Flow paths were limited in number by their Horton value on a quadrangle-by-quadrangle basis. Peak elevations were averaged over an area measuring 85 m by 85 m (represented by one pixel), and they are slightly lower than the highest corresponding point on the ground. Cultural data were extracted from files downloaded from the Afghanistan Information Management Service (AIMS) Web site (http://www.aims.org.af). The AIMS files were originally derived from maps produced by the Afghanistan Geodesy and Cartography Head Office (AGCHO). Because cultural features were not derived from the SRTM base, they do not match it precisely. Province boundaries are not exactly located. This map is part of a series that includes a geologic map, a topographic map, a Landsat natural-color-image map, and a Landsat false-color-image map for the USGS/AGS (Afghan Geological Survey) quadrangles covering Afghanistan. The maps for any given quadrangle have the same open-file number but a different letter suffix, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively. The open-file report (OFR) numbers for each quadrangle range in sequence from 1092 - 1123. The present map series is to be followed by a second series, in which the geology is reinterpreted on the basis of analysis of remote-sensing data, limited fieldwork, and library research. The second series is to be produced by the USGS in cooperation with the AGS and AGCHO.

Topographic Map of Quadrangles 3560 and 3562, Sir-Band (402), Khawja-Jir (403), and Bala-Murghab (404) Quadrangles, Afghanistan

USGS Publications Warehouse

Bohannon, Robert G.

2006-01-01

This map was produced from several larger digital datasets. Topography was derived from Shuttle Radar Topography Mission (SRTM) 85-meter digital data. Gaps in the original dataset were filled with data digitized from contours on 1:200,000-scale Soviet General Staff Sheets (1978-1997). Contours were generated by cubic convolution averaged over four pixels using TNTmips surface-modeling capabilities. Minor artifacts resulting from the auto-contouring technique are present. Streams were auto-generated from the SRTM data in TNTmips as flow paths. Flow paths were limited in number by their Horton value on a quadrangle-by-quadrangle basis. Peak elevations were averaged over an area measuring 85 m by 85 m (represented by one pixel), and they are slightly lower than the highest corresponding point on the ground. Cultural data were extracted from files downloaded from the Afghanistan Information Management Service (AIMS) Web site (http://www.aims.org.af). The AIMS files were originally derived from maps produced by the Afghanistan Geodesy and Cartography Head Office (AGCHO). Because cultural features were not derived from the SRTM base, they do not match it precisely. Province boundaries are not exactly located. This map is part of a series that includes a geologic map, a topographic map, a Landsat natural-color-image map, and a Landsat false-color-image map for the USGS/AGS (Afghan Geological Survey) quadrangles covering Afghanistan. The maps for any given quadrangle have the same open-file number but a different letter suffix, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively. The open-file report (OFR) numbers for each quadrangle range in sequence from 1092 - 1123. The present map series is to be followed by a second series, in which the geology is reinterpreted on the basis of analysis of remote-sensing data, limited fieldwork, and library research. The second series is to be produced by the USGS in cooperation with the AGS and AGCHO.

Topographic Map of Quadrangles 3770 and 3870, Maymayk (211), Jamarj-I-Bala (212), Faydz-Abad (217), and Parkhaw (218) Quadrangles, Afghanistan

USGS Publications Warehouse

Bohannon, Robert G.

2006-01-01

This map was produced from several larger digital datasets. Topography was derived from Shuttle Radar Topography Mission (SRTM) 85-meter digital data. Gaps in the original dataset were filled with data digitized from contours on 1:200,000-scale Soviet General Staff Sheets (1978-1997). Contours were generated by cubic convolution averaged over four pixels using TNTmips surface-modeling capabilities. Minor artifacts resulting from the auto-contouring technique are present. Streams were auto-generated from the SRTM data in TNTmips as flow paths. Flow paths were limited in number by their Horton value on a quadrangle-by-quadrangle basis. Peak elevations were averaged over an area measuring 85 m by 85 m (represented by one pixel), and they are slightly lower than the highest corresponding point on the ground. Cultural data were extracted from files downloaded from the Afghanistan Information Management Service (AIMS) Web site (http://www.aims.org.af). The AIMS files were originally derived from maps produced by the Afghanistan Geodesy and Cartography Head Office (AGCHO). Because cultural features were not derived from the SRTM base, they do not match it precisely. Province boundaries are not exactly located. This map is part of a series that includes a geologic map, a topographic map, a Landsat natural-color-image map, and a Landsat false-color-image map for the USGS/AGS (Afghan Geological Survey) quadrangles covering Afghanistan. The maps for any given quadrangle have the same open-file number but a different letter suffix, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively. The open-file report (OFR) numbers for each quadrangle range in sequence from 1092 - 1123. The present map series is to be followed by a second series, in which the geology is reinterpreted on the basis of analysis of remote-sensing data, limited fieldwork, and library research. The second series is to be produced by the USGS in cooperation with the AGS and AGCHO.

Topographic Map of Quadrangles 3764 and 3664, Jalajin (117), Kham-Ab (118), Char Shangho (123), and Sheberghan (124) Quadrangles, Afghanistan

USGS Publications Warehouse

Bohannon, Robert G.

2006-01-01

This map was produced from several larger digital datasets. Topography was derived from Shuttle Radar Topography Mission (SRTM) 85-meter digital data. Gaps in the original dataset were filled with data digitized from contours on 1:200,000-scale Soviet General Staff Sheets (1978-1997). Contours were generated by cubic convolution averaged over four pixels using TNTmips surface-modeling capabilities. Minor artifacts resulting from the auto-contouring technique are present. Streams were auto-generated from the SRTM data in TNTmips as flow paths. Flow paths were limited in number by their Horton value on a quadrangle-by-quadrangle basis. Peak elevations were averaged over an area measuring 85 m by 85 m (represented by one pixel), and they are slightly lower than the highest corresponding point on the ground. Cultural data were extracted from files downloaded from the Afghanistan Information Management Service (AIMS) Web site (http://www.aims.org.af). The AIMS files were originally derived from maps produced by the Afghanistan Geodesy and Cartography Head Office (AGCHO). Because cultural features were not derived from the SRTM base, they do not match it precisely. Province boundaries are not exactly located. This map is part of a series that includes a geologic map, a topographic map, a Landsat natural-color-image map, and a Landsat false-color-image map for the USGS/AGS (Afghan Geological Survey) quadrangles covering Afghanistan. The maps for any given quadrangle have the same open-file number but a different letter suffix, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively. The open-file report (OFR) numbers for each quadrangle range in sequence from 1092 - 1123. The present map series is to be followed by a second series, in which the geology is reinterpreted on the basis of analysis of remote-sensing data, limited fieldwork, and library research. The second series is to be produced by the USGS in cooperation with the AGS and AGCHO.

Topographic Map of Quadrangles 3260 and 3160, Dasht-E-Chahe-Mazar (419), Anardara (420), Asparan (601), and Kang (602) Quadrangles, Afghanistan

USGS Publications Warehouse

Bohannon, Robert G.

2006-01-01

This map was produced from several larger digital datasets. Topography was derived from Shuttle Radar Topography Mission (SRTM) 85-meter digital data. Gaps in the original dataset were filled with data digitized from contours on 1:200,000-scale Soviet General Staff Sheets (1978-1997). Contours were generated by cubic convolution averaged over four pixels using TNTmips surface-modeling capabilities. Minor artifacts resulting from the auto-contouring technique are present. Streams were auto-generated from the SRTM data in TNTmips as flow paths. Flow paths were limited in number by their Horton value on a quadrangle-by-quadrangle basis. Peak elevations were averaged over an area measuring 85 m by 85 m (represented by one pixel), and they are slightly lower than the highest corresponding point on the ground. Cultural data were extracted from files downloaded from the Afghanistan Information Management Service (AIMS) Web site (http://www.aims.org.af). The AIMS files were originally derived from maps produced by the Afghanistan Geodesy and Cartography Head Office (AGCHO). Because cultural features were not derived from the SRTM base, they do not match it precisely. Province boundaries are not exactly located. This map is part of a series that includes a geologic map, a topographic map, a Landsat natural-color-image map, and a Landsat false-color-image map for the USGS/AGS (Afghan Geological Survey) quadrangles covering Afghanistan. The maps for any given quadrangle have the same open-file number but a different letter suffix, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively. The open-file report (OFR) numbers for each quadrangle range in sequence from 1092 - 1123. The present map series is to be followed by a second series, in which the geology is reinterpreted on the basis of analysis of remote-sensing data, limited fieldwork, and library research. The second series is to be produced by the USGS in cooperation with the AGS and AGCHO.

Topographic Map of Quadrangle 3470 and the Northern Edge of 3370, Jalal-Abad (511), Chaghasaray (512), and Northernmost Jaji-Maydan (517) Quadrangles, Afg

USGS Publications Warehouse

Bohannon, Robert G.

2006-01-01

This map was produced from several larger digital datasets. Topography was derived from Shuttle Radar Topography Mission (SRTM) 85-meter digital data. Gaps in the original dataset were filled with data digitized from contours on 1:200,000-scale Soviet General Staff Sheets (1978-1997). Contours were generated by cubic convolution averaged over four pixels using TNTmips surface-modeling capabilities. Minor artifacts resulting from the auto-contouring technique are present. Streams were auto-generated from the SRTM data in TNTmips as flow paths. Flow paths were limited in number by their Horton value on a quadrangle-by-quadrangle basis. Peak elevations were averaged over an area measuring 85 m by 85 m (represented by one pixel), and they are slightly lower than the highest corresponding point on the ground. Cultural data were extracted from files downloaded from the Afghanistan Information Management Service (AIMS) Web site (http://www.aims.org.af). The AIMS files were originally derived from maps produced by the Afghanistan Geodesy and Cartography Head Office (AGCHO). Because cultural features were not derived from the SRTM base, they do not match it precisely. Province boundaries are not exactly located. This map is part of a series that includes a geologic map, a topographic map, a Landsat natural-color-image map, and a Landsat false-color-image map for the USGS/AGS (Afghan Geological Survey) quadrangles covering Afghanistan. The maps for any given quadrangle have the same open-file number but a different letter suffix, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively. The open-file report (OFR) numbers for each quadrangle range in sequence from 1092 - 1123. The present map series is to be followed by a second series, in which the geology is reinterpreted on the basis of analysis of remote-sensing data, limited fieldwork, and library research. The second series is to be produced by the USGS in cooperation with the AGS and AGCHO.

Topographic Map of Quadrangles 3772, 3774, 3672, and 3674, Gaz-Khan (313), Sarhad (314), Kol-I-Chaqmaqtin (315), Khandud (319), Deh-Ghulaman (320), and Erftah (321) Quadrangles, Afghanistan

USGS Publications Warehouse

Bohannon, Robert G.

2006-01-01

This map was produced from several larger digital datasets. Topography was derived from Shuttle Radar Topography Mission (SRTM) 85-meter digital data. Gaps in the original dataset were filled with data digitized from contours on 1:200,000-scale Soviet General Staff Sheets (1978-1997). Contours were generated by cubic convolution averaged over four pixels using TNTmips surface-modeling capabilities. Minor artifacts resulting from the auto-contouring technique are present. Streams were auto-generated from the SRTM data in TNTmips as flow paths. Flow paths were limited in number by their Horton value on a quadrangle-by-quadrangle basis. Peak elevations were averaged over an area measuring 85 m by 85 m (represented by one pixel), and they are slightly lower than the highest corresponding point on the ground. Cultural data were extracted from files downloaded from the Afghanistan Information Management Service (AIMS) Web site (http://www.aims.org.af). The AIMS files were originally derived from maps produced by the Afghanistan Geodesy and Cartography Head Office (AGCHO). Because cultural features were not derived from the SRTM base, they do not match it precisely. Province boundaries are not exactly located. This map is part of a series that includes a geologic map, a topographic map, a Landsat natural-color-image map, and a Landsat false-color-image map for the USGS/AGS (Afghan Geological Survey) quadrangles covering Afghanistan. The maps for any given quadrangle have the same open-file number but a different letter suffix, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively. The open-file report (OFR) numbers for each quadrangle range in sequence from 1092 - 1123. The present map series is to be followed by a second series, in which the geology is reinterpreted on the basis of analysis of remote-sensing data, limited fieldwork, and library research. The second series is to be produced by the USGS in cooperation with the AGS and AGCHO.

Topographic Map of Quadrangles 3062 and 2962, Charburjak (609), Khanneshin (610), Gawdezereh (615), and Galachah (616) Quadrangles, Afghanistan

USGS Publications Warehouse

Bohannon, Robert G.

2006-01-01

This map was produced from several larger digital datasets. Topography was derived from Shuttle Radar Topography Mission (SRTM) 85-meter digital data. Gaps in the original dataset were filled with data digitized from contours on 1:200,000-scale Soviet General Staff Sheets (1978-1997). Contours were generated by cubic convolution averaged over four pixels using TNTmips surface-modeling capabilities. Minor artifacts resulting from the auto-contouring technique are present. Streams were auto-generated from the SRTM data in TNTmips as flow paths. Flow paths were limited in number by their Horton value on a quadrangle-by-quadrangle basis. Peak elevations were averaged over an area measuring 85 m by 85 m (represented by one pixel), and they are slightly lower than the highest corresponding point on the ground. Cultural data were extracted from files downloaded from the Afghanistan Information Management Service (AIMS) Web site (http://www.aims.org.af). The AIMS files were originally derived from maps produced by the Afghanistan Geodesy and Cartography Head Office (AGCHO). Because cultural features were not derived from the SRTM base, they do not match it precisely. Province boundaries are not exactly located. This map is part of a series that includes a geologic map, a topographic map, a Landsat natural-color-image map, and a Landsat false-color-image map for the USGS/AGS (Afghan Geological Survey) quadrangles covering Afghanistan. The maps for any given quadrangle have the same open-file number but a different letter suffix, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively. The open-file report (OFR) numbers for each quadrangle range in sequence from 1092 - 1123. The present map series is to be followed by a second series, in which the geology is reinterpreted on the basis of analysis of remote-sensing data, limited fieldwork, and library research. The second series is to be produced by the USGS in cooperation with the AGS and AGCHO.

Topographic Map of Quadrangles 3168 and 3268, Yahya-Wona (703), Wersek (704), Khayr-Kot (521), and Urgon (522) Quadrangles, Afghanistan

USGS Publications Warehouse

Bohannon, Robert G.

2006-01-01

This map was produced from several larger digital datasets. Topography was derived from Shuttle Radar Topography Mission (SRTM) 85-meter digital data. Gaps in the original dataset were filled with data digitized from contours on 1:200,000-scale Soviet General Staff Sheets (1978-1997). Contours were generated by cubic convolution averaged over four pixels using TNTmips surface-modeling capabilities. Minor artifacts resulting from the auto-contouring technique are present. Streams were auto-generated from the SRTM data in TNTmips as flow paths. Flow paths were limited in number by their Horton value on a quadrangle-by-quadrangle basis. Peak elevations were averaged over an area measuring 85 m by 85 m (represented by one pixel), and they are slightly lower than the highest corresponding point on the ground. Cultural data were extracted from files downloaded from the Afghanistan Information Management Service (AIMS) Web site (http://www.aims.org.af). The AIMS files were originally derived from maps produced by the Afghanistan Geodesy and Cartography Head Office (AGCHO). Because cultural features were not derived from the SRTM base, they do not match it precisely. Province boundaries are not exactly located. This map is part of a series that includes a geologic map, a topographic map, a Landsat natural-color-image map, and a Landsat false-color-image map for the USGS/AGS (Afghan Geological Survey) quadrangles covering Afghanistan. The maps for any given quadrangle have the same open-file number but a different letter suffix, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively. The open-file report (OFR) numbers for each quadrangle range in sequence from 1092 - 1123. The present map series is to be followed by a second series, in which the geology is reinterpreted on the basis of analysis of remote-sensing data, limited fieldwork, and library research. The second series is to be produced by the USGS in cooperation with the AGS and AGCHO.

Topographic Map of Quadrangles 2964, 2966, 3064, and 3066, Shah-Esmail (617), Reg-Alaqadari (618), Samandkhan-Karez (713), Laki-Bander (611), Jahangir-Naweran (612), and Sreh-Chena (707) Quadrangles, Afghanistan

USGS Publications Warehouse

Bohannon, Robert G.

2006-01-01

This map was produced from several larger digital datasets. Topography was derived from Shuttle Radar Topography Mission (SRTM) 85-meter digital data. Gaps in the original dataset were filled with data digitized from contours on 1:200,000-scale Soviet General Staff Sheets (1978-1997). Contours were generated by cubic convolution averaged over four pixels using TNTmips surface-modeling capabilities. Minor artifacts resulting from the auto-contouring technique are present. Streams were auto-generated from the SRTM data in TNTmips as flow paths. Flow paths were limited in number by their Horton value on a quadrangle-by-quadrangle basis. Peak elevations were averaged over an area measuring 85 m by 85 m (represented by one pixel), and they are slightly lower than the highest corresponding point on the ground. Cultural data were extracted from files downloaded from the Afghanistan Information Management Service (AIMS) Web site (http://www.aims.org.af). The AIMS files were originally derived from maps produced by the Afghanistan Geodesy and Cartography Head Office (AGCHO). Because cultural features were not derived from the SRTM base, they do not match it precisely. Province boundaries are not exactly located. This map is part of a series that includes a geologic map, a topographic map, a Landsat natural-color-image map, and a Landsat false-color-image map for the USGS/AGS (Afghan Geological Survey) quadrangles covering Afghanistan. The maps for any given quadrangle have the same open-file number but a different letter suffix, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively. The open-file report (OFR) numbers for each quadrangle range in sequence from 1092 - 1123. The present map series is to be followed by a second series, in which the geology is reinterpreted on the basis of analysis of remote-sensing data, limited fieldwork, and library research. The second series is to be produced by the USGS in cooperation with the AGS and AGCHO.

Topographic Map of Quadrangles 3060 and 2960, Qala-I-Fath (608), Malek-Sayh-Koh (613), and Gozar-E-Sah (614) Quadrangles, Afghanistan

USGS Publications Warehouse

Bohannon, Robert G.

2006-01-01

This map was produced from several larger digital datasets. Topography was derived from Shuttle Radar Topography Mission (SRTM) 85-meter digital data. Gaps in the original dataset were filled with data digitized from contours on 1:200,000-scale Soviet General Staff Sheets (1978-1997). Contours were generated by cubic convolution averaged over four pixels using TNTmips surface-modeling capabilities. Minor artifacts resulting from the auto-contouring technique are present. Streams were auto-generated from the SRTM data in TNTmips as flow paths. Flow paths were limited in number by their Horton value on a quadrangle-by-quadrangle basis. Peak elevations were averaged over an area measuring 85 m by 85 m (represented by one pixel), and they are slightly lower than the highest corresponding point on the ground. Cultural data were extracted from files downloaded from the Afghanistan Information Management Service (AIMS) Web site (http://www.aims.org.af). The AIMS files were originally derived from maps produced by the Afghanistan Geodesy and Cartography Head Office (AGCHO). Because cultural features were not derived from the SRTM base, they do not match it precisely. Province boundaries are not exactly located. This map is part of a series that includes a geologic map, a topographic map, a Landsat natural-color-image map, and a Landsat false-color-image map for the USGS/AGS (Afghan Geological Survey) quadrangles covering Afghanistan. The maps for any given quadrangle have the same open-file number but a different letter suffix, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively. The open-file report (OFR) numbers for each quadrangle range in sequence from 1092 - 1123. The present map series is to be followed by a second series, in which the geology is reinterpreted on the basis of analysis of remote-sensing data, limited fieldwork, and library research. The second series is to be produced by the USGS in cooperation with the AGS and AGCHO.

Topographic Map of Quadrangles 3460 and 3360, Kol-I-Namaksar (407), Ghuryan (408), Kawir-I-Naizar (413), and Kohe-Mahmudo-Esmailjan (414) Quadrangles, Afghanistan

USGS Publications Warehouse

Bohannon, Robert G.

2006-01-01

This map was produced from several larger digital datasets. Topography was derived from Shuttle Radar Topography Mission (SRTM) 85-meter digital data. Gaps in the original dataset were filled with data digitized from contours on 1:200,000-scale Soviet General Staff Sheets (1978-1997). Contours were generated by cubic convolution averaged over four pixels using TNTmips surface-modeling capabilities. Minor artifacts resulting from the auto-contouring technique are present. Streams were auto-generated from the SRTM data in TNTmips as flow paths. Flow paths were limited in number by their Horton value on a quadrangle-by-quadrangle basis. Peak elevations were averaged over an area measuring 85 m by 85 m (represented by one pixel), and they are slightly lower than the highest corresponding point on the ground. Cultural data were extracted from files downloaded from the Afghanistan Information Management Service (AIMS) Web site (http://www.aims.org.af). The AIMS files were originally derived from maps produced by the Afghanistan Geodesy and Cartography Head Office (AGCHO). Because cultural features were not derived from the SRTM base, they do not match it precisely. Province boundaries are not exactly located. This map is part of a series that includes a geologic map, a topographic map, a Landsat natural-color-image map, and a Landsat false-color-image map for the USGS/AGS (Afghan Geological Survey) quadrangles covering Afghanistan. The maps for any given quadrangle have the same open-file number but a different letter suffix, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively. The open-file report (OFR) numbers for each quadrangle range in sequence from 1092 - 1123. The present map series is to be followed by a second series, in which the geology is reinterpreted on the basis of analysis of remote-sensing data, limited fieldwork, and library research. The second series is to be produced by the USGS in cooperation with the AGS and AGCHO.

Latin Hypercube Sampling (LHS) at variable resolutions for enhanced watershed scale Soil Sampling and Digital Soil Mapping.

NASA Astrophysics Data System (ADS)

Hamalainen, Sampsa; Geng, Xiaoyuan; He, Juanxia

2017-04-01

Latin Hypercube Sampling (LHS) at variable resolutions for enhanced watershed scale Soil Sampling and Digital Soil Mapping. Sampsa Hamalainen, Xiaoyuan Geng, and Juanxia, He. AAFC - Agriculture and Agr-Food Canada, Ottawa, Canada. The Latin Hypercube Sampling (LHS) approach to assist with Digital Soil Mapping has been developed for some time now, however the purpose of this work was to complement LHS with use of multiple spatial resolutions of covariate datasets and variability in the range of sampling points produced. This allowed for specific sets of LHS points to be produced to fulfil the needs of various partners from multiple projects working in the Ontario and Prince Edward Island provinces of Canada. Secondary soil and environmental attributes are critical inputs that are required in the development of sampling points by LHS. These include a required Digital Elevation Model (DEM) and subsequent covariate datasets produced as a result of a Digital Terrain Analysis performed on the DEM. These additional covariates often include but are not limited to Topographic Wetness Index (TWI), Length-Slope (LS) Factor, and Slope which are continuous data. The range of specific points created in LHS included 50 - 200 depending on the size of the watershed and more importantly the number of soil types found within. The spatial resolution of covariates included within the work ranged from 5 - 30 m. The iterations within the LHS sampling were run at an optimal level so the LHS model provided a good spatial representation of the environmental attributes within the watershed. Also, additional covariates were included in the Latin Hypercube Sampling approach which is categorical in nature such as external Surficial Geology data. Some initial results of the work include using a 1000 iteration variable within the LHS model. 1000 iterations was consistently a reasonable value used to produce sampling points that provided a good spatial representation of the environmental attributes. When working within the same spatial resolution for covariates, however only modifying the desired number of sampling points produced, the change of point location portrayed a strong geospatial relationship when using continuous data. Access to agricultural fields and adjacent land uses is often "pinned" as the greatest deterrent to performing soil sampling for both soil survey and soil attribute validation work. The lack of access can be a result of poor road access and/or difficult geographical conditions to navigate for field work individuals. This seems a simple yet continuous issue to overcome for the scientific community and in particular, soils professionals. The ability to assist with the ease of access to sampling points will be in the future a contribution to the Latin Hypercube Sampling (LHS) approach. By removing all locations in the initial instance from the DEM, the LHS model can be restricted to locations only with access from the adjacent road or trail. To further the approach, a road network geospatial dataset can be included within spatial Geographic Information Systems (GIS) applications to access already produced points using a shortest-distance network method.

A Digital Hydrologic Network Supporting NAWQA MRB SPARROW Modeling--MRB_E2RF1WS

USGS Publications Warehouse

Brakebill, J.W.; Terziotti, S.E.

2011-01-01

A digital hydrologic network was developed to support SPAtially Referenced Regression on Watershed attributes (SPARROW) models within selected regions of the United States. These regions correspond with the U.S. Geological Survey's National Water Quality Assessment (NAWQA) Program Major River Basin (MRB) study units 2, 3, 4, 5, and 7 (Preston and others, 2009). MRB2, covers the South Atlantic-Gulf and Tennessee River basins. MRB3, covers the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins. MRB4, covers the Missouri River basins. MRB5, covers the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins. MRB7, covers the Pacific Northwest River basins. The digital hydrologic network described here represents surface-water pathways (MRB_E2RF1) and associated catchments (MRB_E2RF1WS). It serves as the fundamental framework to spatially reference and summarize explanatory information supporting nutrient SPARROW models (Brakebill and others, 2011; Wieczorek and LaMotte, 2011). The principal geospatial dataset used to support this regional effort was based on an enhanced version of a 1:500,000 scale digital stream-reach network (ERF1_2) (Nolan et al., 2002). Enhancements included associating over 3,500 water-quality monitoring sites to the reach network, improving physical locations of stream reaches at or near monitoring locations, and generating drainage catchments based on 100m elevation data. A unique number (MRB_ID) identifies each reach as a single unit. This unique number is also shared by the catchment area drained by the reach, thus spatially linking the hydrologically connected streams and the respective drainage area characteristics. In addition, other relevant physical, environmental, and monitoring information can be associated to the common network and accessed using the unique identification number.

A Digital Hydrologic Network Supporting NAWQA MRB SPARROW Modeling--MRB_E2RF1

USGS Publications Warehouse

Brakebill, J.W.; Terziotti, S.E.

2011-01-01

A digital hydrologic network was developed to support SPAtially Referenced Regression on Watershed attributes (SPARROW) models within selected regions of the United States. These regions correspond with the U.S. Geological Survey's National Water Quality Assessment (NAWQA) Program Major River Basin (MRB) study units 2, 3, 4, 5, and 7 (Preston and others, 2009). MRB2, covers the South Atlantic-Gulf and Tennessee River basins. MRB3, covers the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins. MRB4, covers the Missouri River basins. MRB5, covers the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins. MRB7, covers the Pacific Northwest River basins. The digital hydrologic network described here represents surface-water pathways (MRB_E2RF1) and associated catchments (MRB_E2RF1WS). It serves as the fundamental framework to spatially reference and summarize explanatory information supporting nutrient SPARROW models (Brakebill and others, 2011; Wieczorek and LaMotte, 2011). The principal geospatial dataset used to support this regional effort was based on an enhanced version of a 1:500,000 scale digital stream-reach network (ERF1_2) (Nolan et al., 2002). Enhancements included associating over 3,500 water-quality monitoring sites to the reach network, improving physical locations of stream reaches at or near monitoring locations, and generating drainage catchments based on 100m elevation data. A unique number (MRB_ID) identifies each reach as a single unit. This unique number is also shared by the catchment area drained by the reach, thus spatially linking the hydrologically connected streams and the respective drainage area characteristics. In addition, other relevant physical, environmental, and monitoring information can be associated to the common network and accessed using the unique identification number.

Use of ALS data for digital terrain extraction and roughness parametrization in floodplain areas

NASA Astrophysics Data System (ADS)

Idda, B.; Nardinocchi, C.; Marsella, M.

2009-04-01

In order to undertake structural and land planning actions aimed at improving risk thresholds and vulnerability associated to floodplain inundation, the evaluation of the area concerning the channel overflowing from his natural embankments it is of essential importance. Floodplain models requires the analysis of historical floodplains extensions, ground's morphological structure and hydraulic measurements. Within this set of information, a more detailed characterization about the hydraulic roughness, which controls the velocity to the hydraulic flow, is a interesting challenge to achieve a 2D spatial distribution into the model. Remote sensing optical and radar sensors techniques can be applied to generate 2D and 3D map products useful to perimeter floodplains extension during the main event and extrapolate river cross-sections. Among these techniques, it is unquestionable the enhancement that the Airborne Laser Scanner (ALS) have brought for its capability to extract high resolution and accurate Digital Terrain Models. In hydraulic applications, a number of studies investigated the use of ALS for DTM generation and approached the quantitative estimations of the hydraulic roughness. The aim of this work is the generation of a digital terrain model and the estimation of hydraulic parameters useful for floodplains models from Airborne Laser Scanner data collected in a test area, which encloses a portion of a drainage basin of the Mela river (Sicily, Italy). From the Airborne Laser Scanner dataset, a high resolution Digital Elevation Model was first created, then after applying filtering and classification processes, a dedicated procedure was implemented to assess automatically a value for the hydraulic roughness coefficient (in Manning's formulation) per each point interested in the floodplain. The obtained results allowed to generate maps of equal roughness, hydraulic level depending, based on the application of empirical formulas for specific-type vegetation at each classified ALS point.

ArcticDEM Validation and Accuracy Assessment

NASA Astrophysics Data System (ADS)

Candela, S. G.; Howat, I.; Noh, M. J.; Porter, C. C.; Morin, P. J.

2017-12-01

ArcticDEM comprises a growing inventory Digital Elevation Models (DEMs) covering all land above 60°N. As of August, 2017, ArcticDEM had openly released 2-m resolution, individual DEM covering over 51 million km2, which includes areas of repeat coverage for change detection, as well as over 15 million km2 of 5-m resolution seamless mosaics. By the end of the project, over 80 million km2 of 2-m DEMs will be produced, averaging four repeats of the 20 million km2 Arctic landmass. ArcticDEM is produced from sub-meter resolution, stereoscopic imagery using open source software (SETSM) on the NCSA Blue Waters supercomputer. These DEMs have known biases of several meters due to errors in the sensor models generated from satellite positioning. These systematic errors are removed through three-dimensional registration to high-precision Lidar or other control datasets. ArcticDEM is registered to seasonally-subsetted ICESat elevations due its global coverage and high report accuracy ( 10 cm). The vertical accuracy of ArcticDEM is then obtained from the statistics of the fit to the ICESat point cloud, which averages -0.01 m ± 0.07 m. ICESat, however, has a relatively coarse measurement footprint ( 70 m) which may impact the precision of the registration. Further, the ICESat data predates the ArcticDEM imagery by a decade, so that temporal changes in the surface may also impact the registration. Finally, biases may exist between different the different sensors in the ArcticDEM constellation. Here we assess the accuracy of ArcticDEM and the ICESat registration through comparison to multiple high-resolution airborne lidar datasets that were acquired within one year of the imagery used in ArcticDEM. We find the ICESat dataset is performing as anticipated, introducing no systematic bias during the coregistration process, and reducing vertical errors to within the uncertainty of the airborne Lidars. Preliminary sensor comparisons show no significant difference post coregistration, suggesting that there is no sensor bias between platforms, and all data is suitable for analysis without further correction. Here we will present accuracy assessments, observations and comparisons over diverse terrain in parts of Alaska and Greenland.

Massively Open Online Course for Educators (MOOC-Ed) Network Dataset

ERIC Educational Resources Information Center

Kellogg, Shaun; Edelmann, Achim

2015-01-01

This paper presents the Massively Open Online Course for Educators (MOOC-Ed) network dataset. It entails information on two online communication networks resulting from two consecutive offerings of the MOOC called "The Digital Learning Transition in K-12 Schools" in spring and fall 2013. The courses were offered to educators from the USA…

Embracing the Future: Embedding Digital Repositories in the University of London. Technical Report

ERIC Educational Resources Information Center

Hoorens, Stijn; van Dijk, Lidia Villalba; van Stolk, Christian

2008-01-01

Digital repositories can help Higher Education Institutions (HEIs) to develop coherent and coordinated approaches to capture, identify, store and retrieve intellectual assets such as datasets, course material and research papers. With the advances of technology, an increasing number of Higher Education Institutions are implementing digital…

PhenoCam Dataset v1.0: Vegetation Phenology from Digital Camera Imagery, 2000-2015

USDA-ARS?s Scientific Manuscript database

This data set provides a time series of vegetation phenological observations for 133 sites across diverse ecosystems of North America and Europe from 2000-2015. The phenology data were derived from conventional visible-wavelength automated digital camera imagery collected through the PhenoCam Networ...

Handwritten mathematical symbols dataset

PubMed Central

Chajri, Yassine; Bouikhalene, Belaid

2016-01-01

Due to the technological advances in recent years, paper scientific documents are used less and less. Thus, the trend in the scientific community to use digital documents has increased considerably. Among these documents, there are scientific documents and more specifically mathematics documents. In this context, we present our own dataset of handwritten mathematical symbols composed of 10,379 images. This dataset gathers Arabic characters, Latin characters, Arabic numerals, Latin numerals, arithmetic operators, set-symbols, comparison symbols, delimiters, etc. PMID:27006975

Rescuing Paleomagnetic Data from Deep-Sea Cores Through the IEDA-CCNY Data Internship Program

NASA Astrophysics Data System (ADS)

Ismail, A.; Randel, C.; Palumbo, R. V.; Carter, M.; Cai, Y.; Kent, D. V.; Lehnert, K.; Block, K. A.

2016-12-01

Paleomagnetic data provides essential information for evaluating the chronostratigraphy of sedimentary cores. Lamont research vessels Vema and Robert Conrad collected over 10,000 deep-sea sediment cores around the world from 1953 to 1989. 10% of these cores have been sampled for paleomagnetic analyses at Lamont. Over the years, only 10% of these paleomagnetic records have been published. Moreover, data listings were only rarely made available in older publications because electronic appendices were not available and cyberinfrastructure was not in place for publishing and preserving these data. As a result, the majority of these datasets exist only as fading computer printouts in binders on the investigator's bookshelf. This summer, undergraduate students from the NSF-funded IEDA-CCNY Data Internship Program started digitizing this enormous dataset under the supervision of Dennis Kent, the current custodian of the data and one of the investigators who oversaw some of the data collection process, and an active leader in the field. Undergraduate students worked on digitizing paper records, proof-reading and organizing the data sheets for future integration into an appropriate repository. Through observing and plotting the data, the students learned about how sediment cores and paleomagnetic data are collected and used in research, and the best practices in data publishing and preservation from IEDA (Interdisciplinary Earth Data Alliance) team members. The students also compared different optical character recognition (OCR) softwares and established an efficient workflow to digitize these datasets. These datasets will eventually be incorporated in the Magnetics Information Consortium (MagIC), so that they can be easily compared with similar datasets and have the potential to generate new findings. Through this data rescue project, the students had the opportunity to learn about an important field of scientific research and interact with world-class scientists.

Comparison of digital elevation models for aquatic data development.

Treesearch

Sharon Clarke; Kelly Burnett

2003-01-01

Thirty-meter digital elevation models (DEMs) produced by the U.S. Geological Survey (USGS) are widely available and commonly used in analyzing aquatic systems. However, these DEMs are of relatively coarse resolution, were inconsistently produced (i.e., Level 1 versus Level 2 DEMs), and lack drainage enforcement. Such issues may hamper efforts to accurately model...

USING 30-METER RESOLUTION DIGITAL ELEVATION DATA FOR BASIN ANALYSIS-A PRACTICAL UTILIZATION OF USGS 24K DIGITAL ELEVATION DATA-COMPLICATIONS AND SOLUTIONS. (R826595)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

Slope histogram distribution-based parametrisation of Martian geomorphic features

NASA Astrophysics Data System (ADS)

Balint, Zita; Székely, Balázs; Kovács, Gábor

2014-05-01

The application of geomorphometric methods on the large Martian digital topographic datasets paves the way to analyse the Martian areomorphic processes in more detail. One of the numerous methods is the analysis is to analyse local slope distributions. To this implementation a visualization program code was developed that allows to calculate the local slope histograms and to compare them based on Kolmogorov distance criterion. As input data we used the digital elevation models (DTMs) derived from HRSC high-resolution stereo camera image from various Martian regions. The Kolmogorov-criterion based discrimination produces classes of slope histograms that displayed using coloration obtaining an image map. In this image map the distribution can be visualized by their different colours representing the various classes. Our goal is to create a local slope histogram based classification for large Martian areas in order to obtain information about general morphological characteristics of the region. This is a contribution of the TMIS.ascrea project, financed by the Austrian Research Promotion Agency (FFG). The present research is partly realized in the frames of TÁMOP 4.2.4.A/2-11-1-2012-0001 high priority "National Excellence Program - Elaborating and Operating an Inland Student and Researcher Personal Support System convergence program" project's scholarship support, using Hungarian state and European Union funds and cofinances from the European Social Fund.

EnviroAtlas - Percentage of stream and water body shoreline lengths within 30 meters of >= 5% or >= 15% impervious cover by 12-Digit HUC for the Conterminous United States

EPA Pesticide Factsheets

This EnviroAtlas dataset shows the percentages of stream and water body shoreline lengths within 30 meters of impervious cover by 12-digit Hydrologic Unit (HUC) subwatershed in the contiguous U.S. Impervious cover alters the hydrologic behavior of streams and water bodies, promoting increased storm water runoff and lower stream flow during periods in between rainfall events. Impervious cover also promotes increased pollutant loads in receiving waters and degraded streamside habitat. This dataset shows were impervious cover occurs close to streams and water bodies, where it is likely to have a greater adverse impact on receiving waters. This dataset was produced by the US EPA to support research and online mapping activities related to the EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

[Current problems in the data acquisition of digitized virtual human and the countermeasures].

PubMed

Zhong, Shi-zhen; Yuan, Lin

2003-06-01

As a relatively new field of medical science research that has attracted the attention from worldwide researchers, study of digitized virtual human still awaits long-term dedicated effort for its full development. In the full array of research projects of the integrated Virtual Chinese Human project, virtual visible human, virtual physical human, virtual physiome, and intellectualized virtual human must be included as the four essential constitutional opponents. The primary importance should be given to solving the problems concerning the data acquisition for the dataset of this immense project. Currently 9 virtual human datasets have been established worldwide, which are subjected to critical analyses in the paper with special attention given to the problems in the data storage and the techniques employed, for instance, in these datasets. On the basis of current research status of Virtual Chinese Human project, the authors propose some countermeasures for solving the problems in the data acquisition for the dataset, which include (1) giving the priority to the quality control instead of merely racing for quantity and speed, and (2) improving the setting up of the markers specific for the tissues and organs to meet the requirement from information technology, (3) with also attention to the development potential of the dataset which should have explicit pertinence to specific actual applications.

Adjusting lidar-derived digital terrain models in coastal marshes based on estimated aboveground biomass density

DOE PAGES

Medeiros, Stephen; Hagen, Scott; Weishampel, John; ...

2015-03-25

Digital elevation models (DEMs) derived from airborne lidar are traditionally unreliable in coastal salt marshes due to the inability of the laser to penetrate the dense grasses and reach the underlying soil. To that end, we present a novel processing methodology that uses ASTER Band 2 (visible red), an interferometric SAR (IfSAR) digital surface model, and lidar-derived canopy height to classify biomass density using both a three-class scheme (high, medium and low) and a two-class scheme (high and low). Elevation adjustments associated with these classes using both median and quartile approaches were applied to adjust lidar-derived elevation values closer tomore » true bare earth elevation. The performance of the method was tested on 229 elevation points in the lower Apalachicola River Marsh. The two-class quartile-based adjusted DEM produced the best results, reducing the RMS error in elevation from 0.65 m to 0.40 m, a 38% improvement. The raw mean errors for the lidar DEM and the adjusted DEM were 0.61 ± 0.24 m and 0.32 ± 0.24 m, respectively, thereby reducing the high bias by approximately 49%.« less

Conceptual Design of the Everglades Depth Estimation Network (EDEN) Grid

USGS Publications Warehouse

Jones, John W.; Price, Susan D.

2007-01-01

INTRODUCTION The Everglades Depth Estimation Network (EDEN) offers a consistent and documented dataset that can be used to guide large-scale field operations, to integrate hydrologic and ecological responses, and to support biological and ecological assessments that measure ecosystem responses to the Comprehensive Everglades Restoration Plan (Telis, 2006). Ground elevation data for the greater Everglades and the digital ground elevation models derived from them form the foundation for all EDEN water depth and associated ecologic/hydrologic modeling (Jones, 2004, Jones and Price, 2007). To use EDEN water depth and duration information most effectively, it is important to be able to view and manipulate information on elevation data quality and other land cover and habitat characteristics across the Everglades region. These requirements led to the development of the geographic data layer described in this techniques and methods report. Relying on extensive experience in GIS data development, distribution, and analysis, a great deal of forethought went into the design of the geographic data layer used to index elevation and other surface characteristics for the Greater Everglades region. To allow for simplicity of design and use, the EDEN area was broken into a large number of equal-sized rectangles ('Cells') that in total are referred to here as the 'grid'. Some characteristics of this grid, such as the size of its cells, its origin, the area of Florida it is designed to represent, and individual grid cell identifiers, could not be changed once the grid database was developed. Therefore, these characteristics were selected to design as robust a grid as possible and to ensure the grid's long-term utility. It is desirable to include all pertinent information known about elevation and elevation data collection as grid attributes. Also, it is very important to allow for efficient grid post-processing, sub-setting, analysis, and distribution. This document details the conceptual design of the EDEN grid spatial parameters and cell attribute-table content.

Identifying images of handwritten digits using deep learning in H2O

NASA Astrophysics Data System (ADS)

Sadhasivam, Jayakumar; Charanya, R.; Kumar, S. Harish; Srinivasan, A.

2017-11-01

Automatic digit recognition is of popular interest today. Deep learning techniques make it possible for object recognition in image data. Perceiving the digit has turned into a fundamental part as far as certifiable applications. Since, digits are composed in various styles in this way to distinguish the digit it is important to perceive and arrange it with the assistance of machine learning methods. This exploration depends on supervised learning vector quantization neural system arranged under counterfeit artificial neural network. The pictures of digits are perceived, prepared and tried. After the system is made digits are prepared utilizing preparing dataset vectors and testing is connected to the pictures of digits which are separated to each other by fragmenting the picture and resizing the digit picture as needs be for better precision.

High-resolution digital elevation model of lower Cowlitz and Toutle Rivers, adjacent to Mount St. Helens, Washington, based on an airborne lidar survey of October 2007

USGS Publications Warehouse

Mosbrucker, Adam

2015-01-01

The lateral blast, debris avalanche, and lahars of the May 18th, 1980, eruption of Mount St. Helens, Washington, dramatically altered the surrounding landscape. Lava domes were extruded during the subsequent eruptive periods of 1980–1986 and 2004–2008. More than three decades after the emplacement of the 1980 debris avalanche, high sediment production persists in the Toutle River basin, which drains the northern and western flanks of the volcano. Because this sediment increases the risk of flooding to downstream communities on the Toutle and lower Cowlitz Rivers, the U.S. Army Corps of Engineers (USACE), under the direction of Congress to maintain an authorized level of flood protection, continues to monitor and mitigate excess sediment in North and South Fork Toutle River basins to help reduce this risk and to prevent sediment from clogging the shipping channel of the Columbia River. From October 22–27, 2007, Watershed Sciences, Inc., under contract to USACE, collected high-precision airborne lidar (light detection and ranging) data that cover 273 square kilometers (105 square miles) of lower Cowlitz and Toutle River tributaries from the Columbia River at Kelso, Washington, to upper North Fork Toutle River (below the volcano's edifice), including lower South Fork Toutle River. These data provide a digital dataset of the ground surface, including beneath forest cover. Such remotely sensed data can be used to develop sediment budgets and models of sediment erosion, transport, and deposition. The U.S. Geological Survey (USGS) used these lidar data to develop digital elevation models (DEMs) of the study area. DEMs are fundamental to monitoring natural hazards and studying volcanic landforms, fluvial and glacial geomorphology, and surface geology. Watershed Sciences, Inc., provided files in the LASer (LAS) format containing laser returns that had been filtered, classified, and georeferenced. The USGS produced a hydro-flattened DEM from ground-classified points at Castle and Coldwater Lakes. Final results averaged about two laser last-return points per square meter. As reported by Watershed Sciences, Inc., vertical accuracy is 10 centimeters (cm) at the 95-percent confidence interval on bare road surfaces; however, over natural terrain, USGS found vertical accuracy to be 10–50 cm. This USGS data series contains the bare-earth lidar data as 1- and 10-meter (m) resolution Esri grid files. Digital-elevation data can be downloaded (1m_DEM.zip and 10m_DEM.zip), as well as a 1-m resolution hillshade image with pyramids (1m_hillshade.zip). These geospatial data files require geographic information system (GIS) software for viewing.

The national elevation data set

USGS Publications Warehouse

Gesch, Dean B.; Oimoen, Michael J.; Greenlee, Susan K.; Nelson, Charles A.; Steuck, Michael J.; Tyler, Dean J.

2002-01-01

The NED is a seamless raster dataset from the USGS that fulfills many of the concepts of framework geospatial data as envisioned for the NSDI, allowing users to focus on analysis rather than data preparation. It is regularly maintained and updated, and it provides basic elevation data for many GIS applications. The NED is one of several seamless datasets that the USGS is making available through the Web. The techniques and approaches developed for producing, maintaining, and distributing the NED are the type that will be used for implementing the USGS National Map (http://nationalmap.usgs.gov/).

Application of Virtual and Augmented reality to geoscientific teaching and research.

NASA Astrophysics Data System (ADS)

Hodgetts, David

2017-04-01

The geological sciences are the ideal candidate for the application of Virtual Reality (VR) and Augmented Reality (AR). Digital data collection techniques such as laser scanning, digital photogrammetry and the increasing use of Unmanned Aerial Vehicles (UAV) or Small Unmanned Aircraft (SUA) technology allow us to collect large datasets efficiently and evermore affordably. This linked with the recent resurgence in VR and AR technologies make these 3D digital datasets even more valuable. These advances in VR and AR have been further supported by rapid improvements in graphics card technologies, and by development of high performance software applications to support them. Visualising data in VR is more complex than normal 3D rendering, consideration needs to be given to latency, frame-rate and the comfort of the viewer to enable reasonably long immersion time. Each frame has to be rendered from 2 viewpoints (one for each eye) requiring twice the rendering than for normal monoscopic views. Any unnatural effects (e.g. incorrect lighting) can lead to an uncomfortable VR experience so these have to be minimised. With large digital outcrop datasets comprising 10's-100's of millions of triangles this is challenging but achievable. Apart from the obvious "wow factor" of VR there are some serious applications. It is often the case that users of digital outcrop data do not appreciate the size of features they are dealing with. This is not the case when using correctly scaled VR, and a true sense of scale can be achieved. In addition VR provides an excellent way of performing quality control on 3D models and interpretations and errors are much more easily visible. VR models can then be used to create content that can then be used in AR applications closing the loop and taking interpretations back into the field.

Channel Classification across Arid West Landscapes in Support of OHW Delineation

DTIC Science & Technology

2013-01-01

8 Figure 5. National Hydrography Dataset for Chinle Creek, AZ...the OHW boundary is determined by observing recent physical evidence subsequent to flow. Channel morphology and physical features associated with the...data from the National Hydrography Dataset (NHD) (USGS 2010). The NHD digital ERDC/CRREL TR-13-3 9 stream data were downloaded as a line

Options in virtual 3D, optical-impression-based planning of dental implants.

PubMed

Reich, Sven; Kern, Thomas; Ritter, Lutz

2014-01-01

If a 3D radiograph, which in today's dentistry often consists of a CBCT dataset, is available for computerized implant planning, the 3D planning should also consider functional prosthetic aspects. In a conventional workflow, the CBCT is done with a specially produced radiopaque prosthetic setup that makes the desired prosthetic situation visible during virtual implant planning. If an exclusively digital workflow is chosen, intraoral digital impressions are taken. On these digital models, the desired prosthetic suprastructures are designed. The entire datasets are virtually superimposed by a "registration" process on the corresponding structures (teeth) in the CBCTs. Thus, both the osseous and prosthetic structures are visible in one single 3D application and make it possible to consider surgical and prosthetic aspects. After having determined the implant positions on the computer screen, a drilling template is designed digitally. According to this design (CAD), a template is printed or milled in CAM process. This template is the first physically extant product in the entire workflow. The article discusses the options and limitations of this workflow.

Unveiling the geography of historical patents in the United States from 1836 to 1975

PubMed Central

Petralia, Sergio; Balland, Pierre-Alexandre; Rigby, David L.

2016-01-01

It is clear that technology is a key driver of economic growth. Much less clear is where new technologies are produced and how the geography of U.S. invention has changed over the last two hundred years. Patent data report the geography, history, and technological characteristics of invention. However, those data have only recently become available in digital form and at the present time there exists no comprehensive dataset on the geography of knowledge production in the United States prior to 1975. The database presented in this paper unveils the geography of historical patents granted by the United States Patent and Trademark Office (USPTO) from 1836 to 1975. This historical dataset, HistPat, is constructed using digitalized records of original patent documents that are publicly available. We describe a methodological procedure that allows recovery of geographical information on patents from the digital records. HistPat can be used in different disciplines ranging from geography, economics, history, network science, and science and technology studies. Additionally, it is easily merged with post-1975 USPTO digital patent data to extend it until today. PMID:27576103

A rigorous test of the accuracy of USGS digital elevation models in forested areas of Oregon and Washington.

Treesearch

Ward W. Carson; Stephen E. Reutebuch

1997-01-01

A procedure for performing a rigorous test of elevational accuracy of DEMs using independent ground coordinate data digitized photogrammetrically from aerial photography is presented. The accuracy of a sample set of 23 DEMs covering National Forests in Oregon and Washington was evaluated. Accuracy varied considerably between eastern and western parts of Oregon and...

An algorithm for treating flat areas and depressions in digital elevation models using linear interpolation

Treesearch

F. Pan; M. Stieglitz; R.B. McKane

2012-01-01

Digital elevation model (DEM) data are essential to hydrological applications and have been widely used to calculate a variety of useful topographic characteristics, e.g., slope, flow direction, flow accumulation area, stream channel network, topographic index, and others. Except for slope, none of the other topographic characteristics can be calculated until the flow...

Downscaling global precipitation for local applications - a case for the Rhine basin

NASA Astrophysics Data System (ADS)

Sperna Weiland, Frederiek; van Verseveld, Willem; Schellekens, Jaap

2017-04-01

Within the EU FP7 project eartH2Observe a global Water Resources Re-analysis (WRR) is being developed. This re-analysis consists of meteorological and hydrological water balance variables with global coverage, spanning the period 1979-2014 at 0.25 degrees resolution (Schellekens et al., 2016). The dataset can be of special interest in regions with limited in-situ data availability, yet for local scale analysis particularly in mountainous regions, a resolution of 0.25 degrees may be too coarse and downscaling the data to a higher resolution may be required. A downscaling toolbox has been made that includes spatial downscaling of precipitation based on the global WorldClim dataset that is available at 1 km resolution as a monthly climatology (Hijmans et al., 2005). The input of the down-scaling tool are either the global eartH2Observe WRR1 and WRR2 datasets based on the WFDEI correction methodology (Weedon et al., 2014) or the global Multi-Source Weighted-Ensemble Precipitation (MSWEP) dataset (Beck et al., 2016). Here we present a validation of the datasets over the Rhine catchment by means of a distributed hydrological model (wflow, Schellekens et al., 2014) using a number of precipitation scenarios. (1) We start by running the model using the local reference dataset derived by spatial interpolation of gauge observations. Furthermore we use (2) the MSWEP dataset at the native 0.25-degree resolution followed by (3) MSWEP downscaled with the WorldClim dataset and final (4) MSWEP downscaled with the local reference dataset. The validation will be based on comparison of the modeled river discharges as well as rainfall statistics. We expect that down-scaling the MSWEP dataset with the WorldClim data to higher resolution will increase its performance. To test the performance of the down-scaling routine we have added a run with MSWEP data down-scaled with the local dataset and compare this with the run based on the local dataset itself. - Beck, H. E. et al., 2016. MSWEP: 3-hourly 0.25° global gridded precipitation (1979-2015) by merging gauge, satellite, and reanalysis data, Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-236, accepted for final publication. - Hijmans, R.J. et al., 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965-1978. - Schellekens, J. et al., 2016. A global water resources ensemble of hydrological models: the eartH2Observe Tier-1 dataset, Earth Syst. Sci. Data Discuss., doi:10.5194/essd-2016-55, under review. - Schellekens, J. et al., 2014. Rapid setup of hydrological and hydraulic models using OpenStreetMap and the SRTM derived digital elevation model. Environmental Modelling&Software - Weedon, G.P. et al., 2014. The WFDEI meteorological forcing data set: WATCH Forcing Data methodology applied to ERA-Interim reanalysis data. Water Resources Research, 50, doi:10.1002/2014WR015638.

Scoping of Flood Hazard Mapping Needs for Belknap County, New Hampshire

DTIC Science & Technology

2006-01-01

DEM Digital Elevation Model DFIRM Digital Flood Insurance Rate Map DOQ Digital Orthophoto Quadrangle DOQQ Digital Ortho Quarter Quadrangle DTM...Agriculture Imag- ery Program (NAIP) color Digital Orthophoto Quadrangles (DOQs)). Remote sensing, base map information, GIS data (for example, contour data...found on USGS topographic maps. More recently developed data were derived from digital orthophotos providing improved base map accuracy. NH GRANIT is

Analysis of accuracy of digital elevation models created from captured data by digital photogrammetry method

NASA Astrophysics Data System (ADS)

Hudec, P.

2011-12-01

A digital elevation model (DEM) is an important part of many geoinformatic applications. For the creation of DEM, spatial data collected by geodetic measurements in the field, photogrammetric processing of aerial survey photographs, laser scanning and secondary sources (analogue maps) are used. It is very important from a user's point of view to know the vertical accuracy of a DEM. The article describes the verification of the vertical accuracy of a DEM for the region of Medzibodrožie, which was created using digital photogrammetry for the purposes of water resources management and modeling and resolving flood cases based on geodetic measurements in the field.

SU-G-JeP3-01: A Method to Quantify Lung SBRT Target Localization Accuracy Based On Digitally Reconstructed Fluoroscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lafata, K; Ren, L; Cai, J

2016-06-15

Purpose: To develop a methodology based on digitally-reconstructed-fluoroscopy (DRF) to quantitatively assess target localization accuracy of lung SBRT, and to evaluate using both a dynamic digital phantom and a patient dataset. Methods: For each treatment field, a 10-phase DRF is generated based on the planning 4DCT. Each frame is pre-processed with a morphological top-hat filter, and corresponding beam apertures are projected to each detector plane. A template-matching algorithm based on cross-correlation is used to detect the tumor location in each frame. Tumor motion relative beam aperture is extracted in the superior-inferior direction based on each frame’s impulse response to themore » template, and the mean tumor position (MTP) is calculated as the average tumor displacement. The DRF template coordinates are then transferred to the corresponding MV-cine dataset, which is retrospectively filtered as above. The treatment MTP is calculated within each field’s projection space, relative to the DRF-defined template. The field’s localization error is defined as the difference between the DRF-derived-MTP (planning) and the MV-cine-derived-MTP (delivery). A dynamic digital phantom was used to assess the algorithm’s ability to detect intra-fractional changes in patient alignment, by simulating different spatial variations in the MV-cine and calculating the corresponding change in MTP. Inter-and-intra-fractional variation, IGRT accuracy, and filtering effects were investigated on a patient dataset. Results: Phantom results demonstrated a high accuracy in detecting both translational and rotational variation. The lowest localization error of the patient dataset was achieved at each fraction’s first field (mean=0.38mm), with Fx3 demonstrating a particularly strong correlation between intra-fractional motion-caused localization error and treatment progress. Filtering significantly improved tracking visibility in both the DRF and MV-cine images. Conclusion: We have developed and evaluated a methodology to quantify lung SBRT target localization accuracy based on digitally-reconstructed-fluoroscopy. Our approach may be useful in potentially reducing treatment margins to optimize lung SBRT outcomes. R01-184173.« less

The use of UAV to document sloping landscapes to produce digital elevation models to examine environmental degradation

NASA Astrophysics Data System (ADS)

Themistocleous, K.; Agapiou, A.; Papadavid, G.; Christoforou, M.; Hadjimitsis, D. G.

2015-10-01

This paper focuses on the use of Unmanned Aerial Vehicles (UAVs) over the study area of Pissouri in Cyprus to document the sloping landscapes of the area. The study area has been affected by overgrazing, which has led to shifts in the vegetation patterns and changing microtopography of the soil. The UAV images were used to generate digital elevation models (DEMs) to examine the changes in microtopography. Next to that orthophotos were used to detect changes in vegetation patterns. The combined data of the digital elevation models and the orthophotos will be used to detect the occurrence of catastrophic shifts and mechanisms for desertification in the study area due to overgrazing. This study is part of the "CASCADE- Catastrophic shifts in dryland" project.

High-resolution mapping based on an Unmanned Aerial Vehicle (UAV) to capture paleoseismic offsets along the Altyn-Tagh fault, China.

PubMed

Gao, Mingxing; Xu, Xiwei; Klinger, Yann; van der Woerd, Jerome; Tapponnier, Paul

2017-08-15

The recent dramatic increase in millimeter- to centimeter- resolution topographic datasets obtained via multi-view photogrammetry raises the possibility of mapping detailed offset geomorphology and constraining the spatial characteristics of active faults. Here, for the first time, we applied this new method to acquire high-resolution imagery and generate topographic data along the Altyn Tagh fault, which is located in a remote high elevation area and shows preserved ancient earthquake surface ruptures. A digital elevation model (DEM) with a resolution of 0.065 m and an orthophoto with a resolution of 0.016 m were generated from these images. We identified piercing markers and reconstructed offsets based on both the orthoimage and the topography. The high-resolution UAV data were used to accurately measure the recent seismic offset. We obtained the recent offset of 7 ± 1 m. Combined with the high resolution satellite image, we measured cumulative offsets of 15 ± 2 m, 20 ± 2 m, 30 ± 2 m, which may be due to multiple paleo-earthquakes. Therefore, UAV mapping can provide fine-scale data for the assessment of the seismic hazards.

Accuracy assessment of TanDEM-X IDEM using airborne LiDAR on the area of Poland

NASA Astrophysics Data System (ADS)

Woroszkiewicz, Małgorzata; Ewiak, Ireneusz; Lulkowska, Paulina

2017-06-01

The TerraSAR-X add-on for Digital Elevation Measurement (TanDEM-X) mission launched in 2010 is another programme - after the Shuttle Radar Topography Mission (SRTM) in 2000 - that uses space-borne radar interferometry to build a global digital surface model. This article presents the accuracy assessment of the TanDEM-X intermediate Digital Elevation Model (IDEM) provided by the German Aerospace Center (DLR) under the project "Accuracy assessment of a Digital Elevation Model based on TanDEM-X data" for the southwestern territory of Poland. The study area included: open terrain, urban terrain and forested terrain. Based on a set of 17,498 reference points acquired by airborne laser scanning, the mean errors of average heights and standard deviations were calculated for areas with a terrain slope below 2 degrees, between 2 and 6 degrees and above 6 degrees. The absolute accuracy of the IDEM data for the analysed area, expressed as a root mean square error (Total RMSE), was 0.77 m.

Side-specific effect of yolk testosterone elevation on second-to-fourth digit ratio in a wild passerine

NASA Astrophysics Data System (ADS)

Nagy, Gergely; Blázi, György; Hegyi, Gergely; Török, János

2016-02-01

Second-to-fourth digit ratio is a widely investigated sexually dimorphic morphological trait in human studies and could reliably indicate the prenatal steroid environment. Conducting manipulative experiments to test this hypothesis comes up against ethical limits in humans. However, oviparous tetrapods may be excellent models to experimentally investigate the effects of prenatal steroids on offspring second-to-fourth digit ratio. In this field study, we injected collared flycatcher ( Ficedula albicollis) eggs with physiological doses of testosterone. Fledglings from eggs with elevated yolk testosterone, regardless of their sex, had longer second digits on their left feet than controls, while the fourth digit did not differ between groups. Therefore, second-to-fourth digit ratio was higher in the testosterone-injected group, but only on the left foot. This is the first study which shows experimentally that early testosterone exposure can affect second-to-fourth digit ratio in a wild population of a passerine bird.

Digital line graphs from 1:24,000-scale maps

USGS Publications Warehouse

,

1990-01-01

The Earth Science Information Centers (ESIC) distribute digital cartographic/geographic data files produced by the U.S. Geological Survey (USGS) as part of the National Mapping Program. Digital cartographic data flles are grouped into four basic types. The first of these, called a Digital Line . Graph (DLG), is line map information in digital form. These data files include information on planimetric base categories, such as transportation, hydrography, and boundaries. The second type, called a Digital Elevation Model (DEM), consists of a sampled array of elevations for a number of ground positions that are usually at regularly spaced intervals. The third type is Land Use and Land Cover digital data, which provides information on nine major classes of land use such as urban, agricultural, or forest as wen as associated map data such as political units and Federal land ownership. The fourth type, the Geographic Names Information System, provides primary information for all known places, features, and areas in the United States identified by a proper name.

Digital line graphs from 1:100,000-scale maps

USGS Publications Warehouse

,

1989-01-01

The National Cartographic Information Center (NCIC) distributes digital cartographic/geographic data files produced by the U.S. Geological Survey (USGS) as part of the National Mapping Program. Digital cartographic data files may be grouped into four basic types. The first of these, called a Digital Line Graph (DLG), is line map information in digital form. These data files include information on planimetric base categories, such as transportation, hydrography, and boundaries. The second form, called a Digital Elevation Model (OEM), consists of a sampled array of elevations for ground positions that are usually, but not always, at regularly spaced intervals. The third type is Land Use and Land Cover digital data, which provides information on nine major classes of land use such as urban, agricultural, or forest as well as associated map data such as political units and Federal land ownership. The fourth type, the Geographic Names Information System, provides primary information for known places, features, and areas in the United States identified by a proper name.

Land-use in Amazonia and the Cerrado of Brazil: State of Knowledge and GIS Database

NASA Technical Reports Server (NTRS)

Nepstad, Daniel C.

1997-01-01

We have assembled datasets to strengthen the LargeScale Biosphere Atmosphere Experiment in Amazonia (LBA). These datasets can now be accessed through the Woods Hole Research Center homepage (www.whrc.org), and will soon be linked to the Pre-LBA homepages of the Brazilian Space Research Institute's Center for Weather and Climate Prediction (Instituto de Pesquisas Espaciais, Centro de Previsao de Tempo e Estudos Climaticos, INPE/CPTEC) and through the Oak Ridge National Laboratory, Distributed Active Archive Center (ORNL/DMC). Some of the datasets that we are making available involved new field research and/or the digitization of data available in Brazilian government agencies. For example, during the grant period we conducted interviews at 1,100 sawmills across Amazonia to determine their production of sawn timber, and their harvest intensities. These data provide the basis for the first quantitative assessment of the area of forest affected each year by selective logging (Nepstad et al, submitted to Nature). We digitized the locations of all of the rural households in the State of Para that have been mapped by the Brazilian malaria combat agency (SUCAM). We also mapped and digitized areas of deforestation in the state of Tocantins, which is comprised largely of savanna (cerrado), an ecosystem that has been routinely excluded from deforestation mapping exercises.

Clearing your Desk! Software and Data Services for Collaborative Web Based GIS Analysis

NASA Astrophysics Data System (ADS)

Tarboton, D. G.; Idaszak, R.; Horsburgh, J. S.; Ames, D. P.; Goodall, J. L.; Band, L. E.; Merwade, V.; Couch, A.; Hooper, R. P.; Maidment, D. R.; Dash, P. K.; Stealey, M.; Yi, H.; Gan, T.; Gichamo, T.; Yildirim, A. A.; Liu, Y.

2015-12-01

Can your desktop computer crunch the large GIS datasets that are becoming increasingly common across the geosciences? Do you have access to or the know-how to take advantage of advanced high performance computing (HPC) capability? Web based cyberinfrastructure takes work off your desk or laptop computer and onto infrastructure or "cloud" based data and processing servers. This talk will describe the HydroShare collaborative environment and web based services being developed to support the sharing and processing of hydrologic data and models. HydroShare supports the upload, storage, and sharing of a broad class of hydrologic data including time series, geographic features and raster datasets, multidimensional space-time data, and other structured collections of data. Web service tools and a Python client library provide researchers with access to HPC resources without requiring them to become HPC experts. This reduces the time and effort spent in finding and organizing the data required to prepare the inputs for hydrologic models and facilitates the management of online data and execution of models on HPC systems. This presentation will illustrate the use of web based data and computation services from both the browser and desktop client software. These web-based services implement the Terrain Analysis Using Digital Elevation Model (TauDEM) tools for watershed delineation, generation of hydrology-based terrain information, and preparation of hydrologic model inputs. They allow users to develop scripts on their desktop computer that call analytical functions that are executed completely in the cloud, on HPC resources using input datasets stored in the cloud, without installing specialized software, learning how to use HPC, or transferring large datasets back to the user's desktop. These cases serve as examples for how this approach can be extended to other models to enhance the use of web and data services in the geosciences.

Next-Generation NATO Reference Mobility Model (NG-NRMM)

DTIC Science & Technology

2016-05-11

facilitate comparisons between vehicle design candidates and to assess the mobility of existing vehicles under specific scenarios. Although NRMM has...of different deployed platforms in different areas of operation and routes  Improved flexibility as a design and procurement support tool through...Element Method DEM Digital Elevation Model DIL Driver in the Loop DP Drawbar Pull Force DOE Design of Experiments DTED Digital Terrain Elevation Data

US GeoData Available Through the Internet

USGS Publications Warehouse

,

2000-01-01

The U.S. Geological Survey (USGS) offers certain US GeoData data sets through the Internet. They can be retrieved using the World Wide Web or anonymous File Transfer Protocol (FTP). The data bases and their directory paths are as follows: * 1:24,000-scale digital line graph data in SDTS format (/pub/data/DLG/24K) * 1:2,000,000-scale digital line graph data in SDTS format (/pub/data/DLG/2M) * 1:100,000-scale digital line graph data (/pub/data/DLG/100K) * 1:100,000-scale land use and land cover data (/pub/data/LULC/100K) * 1:250,000-scale land use and land cover data (/pub/data/LULC/250K) * 1:24,000-scale digital elevation data (/pub/data/DEM/7.5min) * 1-degree digital elevation model data (/pub/data/DEM/250)

A multi-directional and multi-scale roughness filter to detect lineament segments on digital elevation models - analyzing spatial objects in R

NASA Astrophysics Data System (ADS)

Baumann, Sebastian; Robl, Jörg; Wendt, Lorenz; Willingshofer, Ernst; Hilberg, Sylke

2016-04-01

Automated lineament analysis on remotely sensed data requires two general process steps: The identification of neighboring pixels showing high contrast and the conversion of these domains into lines. The target output is the lineaments' position, extent and orientation. We developed a lineament extraction tool programmed in R using digital elevation models as input data to generate morphological lineaments defined as follows: A morphological lineament represents a zone of high relief roughness, whose length significantly exceeds the width. As relief roughness any deviation from a flat plane, defined by a roughness threshold, is considered. In our novel approach a multi-directional and multi-scale roughness filter uses moving windows of different neighborhood sizes to identify threshold limited rough domains on digital elevation models. Surface roughness is calculated as the vertical elevation difference between the center cell and the different orientated straight lines connecting two edge cells of a neighborhood, divided by the horizontal distance of the edge cells. Thus multiple roughness values depending on the neighborhood sizes and orientations of the edge connecting lines are generated for each cell and their maximum and minimum values are extracted. Thereby negative signs of the roughness parameter represent concave relief structures as valleys, positive signs convex relief structures as ridges. A threshold defines domains of high relief roughness. These domains are thinned to a representative point pattern by a 3x3 neighborhood filter, highlighting maximum and minimum roughness peaks, and representing the center points of lineament segments. The orientation and extent of the lineament segments are calculated within the roughness domains, generating a straight line segment in the direction of least roughness differences. We tested our algorithm on digital elevation models of multiple sources and scales and compared the results visually with shaded relief map of these digital elevation models. The lineament segments trace the relief structure to a great extent and the calculated roughness parameter represents the physical geometry of the digital elevation model. Modifying the threshold for the surface roughness value highlights different distinct relief structures. Also the neighborhood size at which lineament segments are detected correspond with the width of the surface structure and may be a useful additional parameter for further analysis. The discrimination of concave and convex relief structures perfectly matches with valleys and ridges of the surface.

Creating a Coastal National Elevation Database (CoNED) for science and conservation applications

USGS Publications Warehouse

Thatcher, Cindy A.; Brock, John C.; Danielson, Jeffrey J.; Poppenga, Sandra K.; Gesch, Dean B.; Palaseanu-Lovejoy, Monica; Barras, John; Evans, Gayla A.; Gibbs, Ann

2016-01-01

The U.S. Geological Survey is creating the Coastal National Elevation Database, an expanding set of topobathymetric elevation models that extend seamlessly across coastal regions of high societal or ecological significance in the United States that are undergoing rapid change or are threatened by inundation hazards. Topobathymetric elevation models are raster datasets useful for inundation prediction and other earth science applications, such as the development of sediment-transport and storm surge models. These topobathymetric elevation models are being constructed by the broad regional assimilation of numerous topographic and bathymetric datasets, and are intended to fulfill the pressing needs of decision makers establishing policies for hazard mitigation and emergency preparedness, coastal managers tasked with coastal planning compatible with predictions of inundation due to sea-level rise, and scientists investigating processes of coastal geomorphic change. A key priority of this coastal elevation mapping effort is to foster collaborative lidar acquisitions that meet the standards of the USGS National Geospatial Program's 3D Elevation Program, a nationwide initiative to systematically collect high-quality elevation data. The focus regions are located in highly dynamic environments, for example in areas subject to shoreline change, rapid wetland loss, hurricane impacts such as overwash and wave scouring, and/or human-induced changes to coastal topography.

Digital Image Analysis System for Monitoring Crack Growth at Elevated Temperature

DTIC Science & Technology

1988-05-01

The objective of the research work reported here was to develop a new concept, based on Digital Image Analysis , for monitoring the crack-tip position...a 512 x 512 pixel frame. c) Digital Image Analysis software developed to locate and digitize the position of the crack-tip, on the observed image

A Digital Badging Dataset Focused on Performance, Engagement and Behavior-Related Variables from Observations in Web-Based University Courses

ERIC Educational Resources Information Center

McDaniel, Rudy; Fanfarelli, Joseph R.

2015-01-01

This dataset contains participant data related to the use of badging (achievement) feedback in pedagogical design. Two sections each of web-based graphic design and web design undergraduate courses were offered at the University of Central Florida. A badging system for achievements was included in one section of each. Performance, engagement and…

EnviroAtlas - Industrial Water Demand by 12-Digit HUC for the Conterminous United States

EPA Pesticide Factsheets

This EnviroAtlas dataset includes industrial water demand attributes which provide insight into the amount of water currently used for manufacturing and production of commodities in the contiguous United States. The values are based on 2005 water demand and Dun and Bradstreet's 2009/2010 source data, and have been summarized by watershed or 12-digit hydrologic unit code (HUC). For the purposes of this metric, industrial water use includes chemical, food, paper, wood, and metal production. The industrial water is for self-supplied only such as by private wells or reservoirs. Sources include either surface water or groundwater. This dataset was produced by the US EPA to support research and online mapping activities related to the EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

EnviroAtlas - Big Game Hunting Recreation Demand by 12-Digit HUC in the Conterminous United States

EPA Pesticide Factsheets

This EnviroAtlas dataset includes the total number of recreational days per year demanded by people ages 18 and over for big game hunting by location in the contiguous United States. Big game includes deer, elk, bear, and wild turkey. These values are based on 2010 population distribution, 2011 U.S. Fish and Wildlife Service (FWS) Fish, Hunting, and Wildlife-Associated Recreation (FHWAR) survey data, and 2011 U.S. Department of Agriculture (USDA) Forest Service National Visitor Use Monitoring program data, and have been summarized by 12-digit hydrologic unit code (HUC). This dataset was produced by the US EPA to support research and online mapping activities related to the EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

Digital hydrologic networks supporting applications related to spatially referenced regression modeling

USGS Publications Warehouse

Brakebill, John W.; Wolock, David M.; Terziotti, Silvia

2011-01-01

Digital hydrologic networks depicting surface-water pathways and their associated drainage catchments provide a key component to hydrologic analysis and modeling. Collectively, they form common spatial units that can be used to frame the descriptions of aquatic and watershed processes. In addition, they provide the ability to simulate and route the movement of water and associated constituents throughout the landscape. Digital hydrologic networks have evolved from derivatives of mapping products to detailed, interconnected, spatially referenced networks of water pathways, drainage areas, and stream and watershed characteristics. These properties are important because they enhance the ability to spatially evaluate factors that affect the sources and transport of water-quality constituents at various scales. SPAtially Referenced Regressions On Watershed attributes (SPARROW), a process-based ⁄ statistical model, relies on a digital hydrologic network in order to establish relations between quantities of monitored contaminant flux, contaminant sources, and the associated physical characteristics affecting contaminant transport. Digital hydrologic networks modified from the River Reach File (RF1) and National Hydrography Dataset (NHD) geospatial datasets provided frameworks for SPARROW in six regions of the conterminous United States. In addition, characteristics of the modified RF1 were used to update estimates of mean-annual streamflow. This produced more current flow estimates for use in SPARROW modeling.

Validation of a novel technique for creating simulated radiographs using computed tomography datasets.

PubMed

Mendoza, Patricia; d'Anjou, Marc-André; Carmel, Eric N; Fournier, Eric; Mai, Wilfried; Alexander, Kate; Winter, Matthew D; Zwingenberger, Allison L; Thrall, Donald E; Theoret, Christine

2014-01-01

Understanding radiographic anatomy and the effects of varying patient and radiographic tube positioning on image quality can be a challenge for students. The purposes of this study were to develop and validate a novel technique for creating simulated radiographs using computed tomography (CT) datasets. A DICOM viewer (ORS Visual) plug-in was developed with the ability to move and deform cuboidal volumetric CT datasets, and to produce images simulating the effects of tube-patient-detector distance and angulation. Computed tomographic datasets were acquired from two dogs, one cat, and one horse. Simulated radiographs of different body parts (n = 9) were produced using different angles to mimic conventional projections, before actual digital radiographs were obtained using the same projections. These studies (n = 18) were then submitted to 10 board-certified radiologists who were asked to score visualization of anatomical landmarks, depiction of patient positioning, realism of distortion/magnification, and image quality. No significant differences between simulated and actual radiographs were found for anatomic structure visualization and patient positioning in the majority of body parts. For the assessment of radiographic realism, no significant differences were found between simulated and digital radiographs for canine pelvis, equine tarsus, and feline abdomen body parts. Overall, image quality and contrast resolution of simulated radiographs were considered satisfactory. Findings from the current study indicated that radiographs simulated using this new technique are comparable to actual digital radiographs. Further studies are needed to apply this technique in developing interactive tools for teaching radiographic anatomy and the effects of varying patient and tube positioning. © 2013 American College of Veterinary Radiology.

Generation of topographic terrain models utilizing synthetic aperture radar and surface level data

NASA Technical Reports Server (NTRS)

Imhoff, Marc L. (Inventor)

1991-01-01

Topographical terrain models are generated by digitally delineating the boundary of the region under investigation from the data obtained from an airborne synthetic aperture radar image and surface elevation data concurrently acquired either from an airborne instrument or at ground level. A set of coregistered boundary maps thus generated are then digitally combined in three dimensional space with the acquired surface elevation data by means of image processing software stored in a digital computer. The method is particularly applicable for generating terrain models of flooded regions covered entirely or in part by foliage.

47 CFR 24.53 - Calculation of height above average terrain (HAAT).

Code of Federal Regulations, 2012 CFR

2012-10-01

... height above mean sea level. (b) Average terrain elevation shall be calculated using elevation data from... Digital Chart of the World (DCW) may be used. (c) Radial average terrain elevation is calculated as the...

47 CFR 24.53 - Calculation of height above average terrain (HAAT).

Code of Federal Regulations, 2011 CFR

2011-10-01

... height above mean sea level. (b) Average terrain elevation shall be calculated using elevation data from... Digital Chart of the World (DCW) may be used. (c) Radial average terrain elevation is calculated as the...

47 CFR 24.53 - Calculation of height above average terrain (HAAT).

Code of Federal Regulations, 2010 CFR

2010-10-01

... height above mean sea level. (b) Average terrain elevation shall be calculated using elevation data from... Digital Chart of the World (DCW) may be used. (c) Radial average terrain elevation is calculated as the...

47 CFR 24.53 - Calculation of height above average terrain (HAAT).

Code of Federal Regulations, 2014 CFR

2014-10-01

... height above mean sea level. (b) Average terrain elevation shall be calculated using elevation data from... Digital Chart of the World (DCW) may be used. (c) Radial average terrain elevation is calculated as the...

47 CFR 24.53 - Calculation of height above average terrain (HAAT).

Code of Federal Regulations, 2013 CFR

2013-10-01

... height above mean sea level. (b) Average terrain elevation shall be calculated using elevation data from... Digital Chart of the World (DCW) may be used. (c) Radial average terrain elevation is calculated as the...

Using Benford's law to investigate Natural Hazard dataset homogeneity.

PubMed

Joannes-Boyau, Renaud; Bodin, Thomas; Scheffers, Anja; Sambridge, Malcolm; May, Simon Matthias

2015-07-09

Working with a large temporal dataset spanning several decades often represents a challenging task, especially when the record is heterogeneous and incomplete. The use of statistical laws could potentially overcome these problems. Here we apply Benford's Law (also called the "First-Digit Law") to the traveled distances of tropical cyclones since 1842. The record of tropical cyclones has been extensively impacted by improvements in detection capabilities over the past decades. We have found that, while the first-digit distribution for the entire record follows Benford's Law prediction, specific changes such as satellite detection have had serious impacts on the dataset. The least-square misfit measure is used as a proxy to observe temporal variations, allowing us to assess data quality and homogeneity over the entire record, and at the same time over specific periods. Such information is crucial when running climatic models and Benford's Law could potentially be used to overcome and correct for data heterogeneity and/or to select the most appropriate part of the record for detailed studies.

Modeling turbulent flows in the atmospheric boundary layer of Mars: application to Gale crater, Mars, landing site of the Curiosity rover

NASA Astrophysics Data System (ADS)

Anderson, William; Day, Kenzie; Kocurek, Gary

2016-11-01

Mars is a dry planet with a thin atmosphere. Aeolian processes - wind-driven mobilization of sediment and dust - are the exclusive mode of landscape variability on Mars. Craters are common topographic features on the surface of Mars, and many craters on Mars contain a prominent central mound (NASA's Curiosity rover was landed in Gale crater). Using density-normalized large-eddy simulations, we have modeled turbulent flows over crater-like topographies that feature a central mound. We have also run one simulation of flow over a digital elevation map of Gale crater. Resultant datasets suggest a deflationary mechanism wherein vortices shed from the upwind crater rim are realigned to conform to the crater profile via stretching and tilting. This was accomplished using three-dimensional datasets (momentum and vorticity) retrieved from LES. As a result, helical vortices occupy the inner region of the crater and, therefore, are primarily responsible for aeolian morphodynamics in the crater. We have also used the immersed-boundary method body force distribution to compute the aerodynamic surface stress on the crater. These results suggest that secondary flows - originating from flow separation at the crater - have played an important role in shaping landscape features observed in craters (including the dune fields observed on Mars, many of which are actively evolving). None.

Modeling turbulent flows in the atmospheric boundary layer of Mars: application to Gale crater, Mars, landing site of the Curiosity rover

NASA Astrophysics Data System (ADS)

Anderson, William

2017-04-01

Mars is a dry planet with a thin atmosphere. Aeolian processes - wind-driven mobilization of sediment and dust - are the exclusive mode of landscape variability on Mars. Craters are common topographic features on the surface of Mars, and many craters on Mars contain a prominent central mound (NASA's Curiosity rover was landed in Gale crater). Using density-normalized large-eddy simulations, we have modeled turbulent flows over crater-like topographies that feature a central mound. We have also run one simulation of flow over a digital elevation map of Gale crater. Resultant datasets suggest a deflationary mechanism wherein vortices shed from the upwind crater rim are realigned to conform to the crater profile via stretching and tilting. This was accomplished using three-dimensional datasets (momentum and vorticity) retrieved from LES. As a result, helical vortices occupy the inner region of the crater and, therefore, are primarily responsible for aeolian morphodynamics in the crater. We have also used the immersed-boundary method body force distribution to compute the aerodynamic surface stress on the crater. These results suggest that secondary flows - originating from flow separation at the crater - have played an important role in shaping landscape features observed in craters (including the dune fields observed on Mars, many of which are actively evolving).

Quantifying the Uncertainty in Streamflow Predictions Using Swat for Brazos-Colorado Coastal Watershed, Texas

NASA Astrophysics Data System (ADS)

Mandal, D.; Bhatia, N.; Srivastav, R. K.

2016-12-01

Soil Water Assessment Tool (SWAT) is one of the most comprehensive hydrologic models to simulate streamflow for a watershed. The two major inputs for a SWAT model are: (i) Digital Elevation Models (DEM), and (ii) Land Use and Land Cover Maps (LULC). This study aims to quantify the uncertainty in streamflow predictions using SWAT for San Bernard River in Brazos-Colorado coastal watershed, Texas, by incorporating the respective datasets from different sources: (i) DEM data will be obtained from ASTER GDEM V2, GMTED2010, NHD DEM, and SRTM DEM datasets with ranging resolution from 1/3 arc-second to 30 arc-second, and (ii) LULC data will be obtained from GLCC V2, MRLC NLCD2011, NOAA's C-CAP, USGS GAP, and TCEQ databases. Weather variables (Precipitation and Max-Min Temperature at daily scale) will be obtained from National Climatic Data Centre (NCDC) and SWAT in-built STASGO tool will be used to obtain the soil maps. The SWAT model will be calibrated using SWAT-CUP SUFI-2 approach and its performance will be evaluated using the statistical indices of Nash-Sutcliffe efficiency (NSE), ratio of Root-Mean-Square-Error to standard deviation of observed streamflow (RSR), and Percent-Bias Error (PBIAS). The study will help understand the performance of SWAT model with varying data sources and eventually aid the regional state water boards in planning, designing, and managing hydrologic systems.

The Upper Mississippi River System—Topobathy

USGS Publications Warehouse

Stone, Jayme M.; Hanson, Jenny L.; Sattler, Stephanie R.

2017-03-23

The Upper Mississippi River System (UMRS), the navigable part of the Upper Mississippi and Illinois Rivers, is a diverse ecosystem that contains river channels, tributaries, shallow-water wetlands, backwater lakes, and flood-plain forests. Approximately 10,000 years of geologic and hydrographic history exist within the UMRS. Because it maintains crucial wildlife and fish habitats, the dynamic ecosystems of the Upper Mississippi River Basin and its tributaries are contingent on the adjacent flood plains and water-level fluctuations of the Mississippi River. Separate data for flood-plain elevation (lidar) and riverbed elevation (bathymetry) were collected on the UMRS by the U.S. Army Corps of Engineers’ (USACE) Upper Mississippi River Restoration (UMRR) Program. Using the two elevation datasets, the U.S. Geological Survey (USGS) Upper Midwest Environmental Sciences Center (UMESC) developed a systemic topobathy dataset.

Elevation and mass change of the Echaurren Norte Glacier (Central Andes, Chile) from 1955 to 2015.

NASA Astrophysics Data System (ADS)

Farías, David; Vivero, Sebastián; Casassa, Gino; Seehaus, Thorsten; Braun, Matthias H.

2017-04-01

The Echaurren Norte Glacier (33°34'S 70°07'W) is a small mountain glacier located at the upper Maipo basin, approximately 80 km to Santiago de Chile. The glacier has the longest surface mass balance record in South America (1975 to 2016). The measurements are carried out by DGA (water directory of Chile) using the direct glaciological method. The surface mass balance show continuous negative values, but exceptional positive mass balances were identified during ENSO periods. The aim of our study is complement the in-situ observations on Echaurren Norte Glacier with the geodetic mass balance measurements for the period 1955 to 2015. Our database comprises digital elevation models (DEM) from historical cartography based on aerial photographs (1955), SRTM (2000) and Lidar data. In addition, we mapped changes in glacier extent using aerial photography and multi-mission satellite data. TanDEM-X (2012-2015) and SRTM data will be used to investigate surrounding glaciers that have not such extensive and detailed coverage as Echaurren Norte Glacier. The aerial photographs from 1955 were scanned from the original negative using a photogrammetric scanner and processed on a digital photogrammetric workstation (DPW) and georeferenced with the aid of GCPs derived from the Lidar dataset. The TanDEM-X data was processed using differential interferometry using SRTM C-band DEM as reference. Differences resulting from X- and C-band penetration are considered comparing X- and C-band SRTM data. All DEMs were laterally and vertically co-registered to each other. Error assessment was done over stable ground. Our preliminary results indicate an elevation change of -42.2 m ± 4 m (1955-2015) for Echaurren Norte Glacier. The estimated averaged annual mass balance is -0.59 m water equivalent for the period 1955-2015 using a density of 0.85 kg/cm3 for volume to mass conversion. Significant changes of the surface cover were identified, with a considerable increase of the debris cover, in particular in the medial zone of the glacier with a layer approximately 0.35 m of thickness (2009-2015).

Analyzing remote sensing geobotanical trends in Quetico Provincial Park, Ontario, Canada, using digital elevation data

NASA Technical Reports Server (NTRS)

Warner, Timothy A.; Campagna, David J.; Levandowski, Don W.; Cetin, Haluk; Evans, Carla S.

1991-01-01

A 10 x 13-km area in Quetico Provincial Park, Canada has been studied using a digital elevation model to separate different drainage classes and to examine the influence of site factors and lithology on vegetation. Landsat Thematic Mapper data have been classified into six forest classes of varying deciduous-coniferous cover through nPDF, a procedure based on probability density functions. It is shown that forests growing on mafic lithologies are enriched in deciduous species, compared to those growing on granites. Of the forest classes found on mafics, the highest coniferous component was on north facing slopes, and the highest deciduous component on south facing slopes. Granites showed no substantial variation between site classes. The digital elevation derived site data is considered to be an important tool in geobotanical investigations.

Topographic Science

USGS Publications Warehouse

Poppenga, Sandra K.; Evans, Gayla; Gesch, Dean; Stoker, Jason M.; Queija, Vivian R.; Worstell, Bruce; Tyler, Dean J.; Danielson, Jeff; Bliss, Norman; Greenlee, Susan

2010-01-01

The mission of U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center Topographic Science is to establish partnerships and conduct research and applications that facilitate the development and use of integrated national and global topographic datasets. Topographic Science includes a wide range of research and applications that result in improved seamless topographic datasets, advanced elevation technology, data integration and terrain visualization, new and improved elevation derivatives, and development of Web-based tools. In cooperation with our partners, Topographic Science is developing integrated-science applications for mapping, national natural resource initiatives, hazards, and global change science. http://topotools.cr.usgs.gov/.

Measuring the effects of morphological changes to sea turtle nesting beaches over time with LiDAR data

NASA Astrophysics Data System (ADS)

Yamamoto, Kristina H.; Anderson, Sharolyn J.; Sutton, Paul C.

2015-10-01

Sea turtle nesting beaches in southeastern Florida were evaluated for changes from 1999 to 2005 using LiDAR datasets. Changes to beach volume were correlated with changes in several elevation-derived characteristics, such as elevation and slope. In addition, these changes to beach geomorphology were correlated to changes in nest success, illustrating that beach alterations may affect sea turtle nesting behavior. The ability to use LiDAR datasets to quickly and efficiently conduct beach comparisons for habitat use represents another benefit to this high spatial resolution data.

Upscaling of soil moisture measurements in NW Italy

NASA Astrophysics Data System (ADS)

Ferraris, Stefano; Canone, Davide; Previati, Maurizio; Brunod, Christian; Ratto, Sara; Cauduro, Marco

2015-04-01

There is large mismatch in spatial scale between the climate and meteorological model grid, and the scale of soil and vegetation measurements. Remote sensing data can help to fit the model scale, but they cannot provide rootzone data. In this work some soil moisture datasets are analysed for the sake of providing larger scale estimation of soil moisture and water and energy fluxes. The first dataset refers to a plain site near Torino, where measurements are taken since 1997 (Baudena et al., 2012), and a mountain site close to the town. The second one is a dataset in the mountains of Valle d'Aosta (Brocca et al., 2013), where 4 years of data are available. The use of digital elevation models and vegetation maps is shown in this work. Some soil processes (e.g. Whalley et al., 2012) are usually disregarded, but in this work their possible impact is considered. References L. Brocca, A. Tarpanelli, T. Moramarco, F. Melone, S.M. Ratto, M. Cauduro, S. Ferraris, N. Berni, F. Ponziani, W. Wagner, T. Melzer (2013). Soil Moisture Estimation in Alpine Catchments through Modeling and Satellite Observations VADOSE ZONE JOURNAL, vol. 8-2, p. 1-10, doi:10.2136/vzj2012.0102 M. Baudena, I. Bevilacqua, D. Canone, S. Ferraris, M. Previati, A. Provenzale (2012). Soil water dynamics at a midlatitude test site: Field measurements and box modeling approaches. JOURNAL OF HYDROLOGY, vol. 414-415, p. 329-340, ISSN: 0022-1694, doi: 10.1016/j.jhydrol.2011.11.009 W.R. Whalley, G.P. Matthews, S. Ferraris (2012). The effect of compaction and shear deformation of saturated soil on hydraulic conductivity. SOIL & TILLAGE RESEARCH, vol. 125, p. 23-29, ISSN: 0167-1987

Soil Erosion map of Europe based on high resolution input datasets

NASA Astrophysics Data System (ADS)

Panagos, Panos; Borrelli, Pasquale; Meusburger, Katrin; Ballabio, Cristiano; Alewell, Christine

2015-04-01

Modelling soil erosion in European Union is of major importance for agro-environmental policies. Soil erosion estimates are important inputs for the Common Agricultural Policy (CAP) and the implementation of the Soil Thematic Strategy. Using the findings of a recent pan-European data collection through the EIONET network, it was concluded that most Member States are applying the empirical Revised Universal Soil Loss Equation (RUSLE) for the modelling soil erosion at National level. This model was chosen for the pan-European soil erosion risk assessment and it is based on 6 input factors. Compared to past approaches, each of the factors is modelled using the latest pan-European datasets, expertise and data from Member states and high resolution remote sensing data. The soil erodibility (K-factor) is modelled using the recently published LUCAS topsoil database with 20,000 point measurements and incorporating the surface stone cover which can reduce K-factor by 15%. The rainfall erosivity dataset (R-factor) has been implemented using high temporal resolution rainfall data from more than 1,500 precipitation stations well distributed in Europe. The cover-management (C-factor) incorporates crop statistics and management practices such as cover crops, tillage practices and plant residuals. The slope length and steepness (combined LS-factor) is based on the first ever 25m Digital Elevation Model (DEM) of Europe. Finally, the support practices (P-factor) is modelled for first time at this scale taking into account the 270,000 LUCAS earth observations and the Good Agricultural and Environmental Condition (GAEC) that farmers have to follow in Europe. The high resolution input layers produce the final soil erosion risk map at 100m resolution and allow policy makers to run future land use, management and climate change scenarios.

Object-Oriented Image Clustering Method Using UAS Photogrammetric Imagery

NASA Astrophysics Data System (ADS)

Lin, Y.; Larson, A.; Schultz-Fellenz, E. S.; Sussman, A. J.; Swanson, E.; Coppersmith, R.

2016-12-01

Unmanned Aerial Systems (UAS) have been used widely as an imaging modality to obtain remotely sensed multi-band surface imagery, and are growing in popularity due to their efficiency, ease of use, and affordability. Los Alamos National Laboratory (LANL) has employed the use of UAS for geologic site characterization and change detection studies at a variety of field sites. The deployed UAS equipped with a standard visible band camera to collect imagery datasets. Based on the imagery collected, we use deep sparse algorithmic processing to detect and discriminate subtle topographic features created or impacted by subsurface activities. In this work, we develop an object-oriented remote sensing imagery clustering method for land cover classification. To improve the clustering and segmentation accuracy, instead of using conventional pixel-based clustering methods, we integrate the spatial information from neighboring regions to create super-pixels to avoid salt-and-pepper noise and subsequent over-segmentation. To further improve robustness of our clustering method, we also incorporate a custom digital elevation model (DEM) dataset generated using a structure-from-motion (SfM) algorithm together with the red, green, and blue (RGB) band data for clustering. In particular, we first employ an agglomerative clustering to create an initial segmentation map, from where every object is treated as a single (new) pixel. Based on the new pixels obtained, we generate new features to implement another level of clustering. We employ our clustering method to the RGB+DEM datasets collected at the field site. Through binary clustering and multi-object clustering tests, we verify that our method can accurately separate vegetation from non-vegetation regions, and are also able to differentiate object features on the surface.

Applying NASA Imaging Radar Datasets to Investigate the Geomorphology of the Amazon's Planalto

NASA Astrophysics Data System (ADS)

McDonald, K. C.; Campbell, K.; Islam, R.; Alexander, P. M.; Cracraft, J.

2016-12-01

The Amazon basin is a biodiversity rich biome and plays a significant role into shaping Earth's climate, ocean and atmospheric gases. Understanding the history of the formation of this basin is essential to our understanding of the region's biodiversity and its response to climate change. During March 2013, the NASA/JPL L-band polarimetric airborne imaging radar, UAVSAR, conducted airborne studies over regions of South America including portions of the western Amazon basin. We utilize UAVSAR imagery acquired during that time over the Planalto, in the Madre de Dios region of southeastern Peru in an assessment of the underlying geomorphology, its relationship to the current distribution of vegetation, and its relationship to geologic processes through deep time. We employ UAVSAR data collections to assess the utility of these high quality imaging radar data for use in identifying geomorphologic features and vegetation communities within the context of improving the understanding of evolutionary processes, and their utility in aiding interpretation of datasets from Earth-orbiting satellites to support a basin-wide characterization across the Amazon. We derive maps of landcover and river branching structure from UAVSAR imagery. We compare these maps to those derived using imaging radar datasets from the Japanese Space Agency's ALOS PALSAR and Digital Elevation Models (DEMs) from NASA's Shuttle Radar Topography Mission (SRTM). Results provide an understanding of the underlying geomorphology of the Amazon planalto as well as its relationship to geologic processes and will support interpretation of the evolutionary history of the Amazon Basin. Portions of this work have been carried out within the framework of the ALOS Kyoto & Carbon Initiative. PALSAR data were provided by JAXA/EORC and the Alaska Satellite Facility.This work is carried out with support from the NASA Biodiversity Program and the NSF DIMENSIONS of Biodiversity Program.

Effect of Variable Spatial Scales on USLE-GIS Computations

NASA Astrophysics Data System (ADS)

Patil, R. J.; Sharma, S. K.

2017-12-01

Use of appropriate spatial scale is very important in Universal Soil Loss Equation (USLE) based spatially distributed soil erosion modelling. This study aimed at assessment of annual rates of soil erosion at different spatial scales/grid sizes and analysing how changes in spatial scales affect USLE-GIS computations using simulation and statistical variabilities. Efforts have been made in this study to recommend an optimum spatial scale for further USLE-GIS computations for management and planning in the study area. The present research study was conducted in Shakkar River watershed, situated in Narsinghpur and Chhindwara districts of Madhya Pradesh, India. Remote Sensing and GIS techniques were integrated with Universal Soil Loss Equation (USLE) to predict spatial distribution of soil erosion in the study area at four different spatial scales viz; 30 m, 50 m, 100 m, and 200 m. Rainfall data, soil map, digital elevation model (DEM) and an executable C++ program, and satellite image of the area were used for preparation of the thematic maps for various USLE factors. Annual rates of soil erosion were estimated for 15 years (1992 to 2006) at four different grid sizes. The statistical analysis of four estimated datasets showed that sediment loss dataset at 30 m spatial scale has a minimum standard deviation (2.16), variance (4.68), percent deviation from observed values (2.68 - 18.91 %), and highest coefficient of determination (R2 = 0.874) among all the four datasets. Thus, it is recommended to adopt this spatial scale for USLE-GIS computations in the study area due to its minimum statistical variability and better agreement with the observed sediment loss data. This study also indicates large scope for use of finer spatial scales in spatially distributed soil erosion modelling.

Extraction of drainage networks from large terrain datasets using high throughput computing

NASA Astrophysics Data System (ADS)

Gong, Jianya; Xie, Jibo

2009-02-01

Advanced digital photogrammetry and remote sensing technology produces large terrain datasets (LTD). How to process and use these LTD has become a big challenge for GIS users. Extracting drainage networks, which are basic for hydrological applications, from LTD is one of the typical applications of digital terrain analysis (DTA) in geographical information applications. Existing serial drainage algorithms cannot deal with large data volumes in a timely fashion, and few GIS platforms can process LTD beyond the GB size. High throughput computing (HTC), a distributed parallel computing mode, is proposed to improve the efficiency of drainage networks extraction from LTD. Drainage network extraction using HTC involves two key issues: (1) how to decompose the large DEM datasets into independent computing units and (2) how to merge the separate outputs into a final result. A new decomposition method is presented in which the large datasets are partitioned into independent computing units using natural watershed boundaries instead of using regular 1-dimensional (strip-wise) and 2-dimensional (block-wise) decomposition. Because the distribution of drainage networks is strongly related to watershed boundaries, the new decomposition method is more effective and natural. The method to extract natural watershed boundaries was improved by using multi-scale DEMs instead of single-scale DEMs. A HTC environment is employed to test the proposed methods with real datasets.

NASADEM Global Elevation Model of Earth: Methods for the Refinement and Merger of SRTM and ASTER GDEM

NASA Astrophysics Data System (ADS)

Crippen, R. E.; Buckley, S.; Agram, P. S.; Belz, J. E.; Gurrola, E. M.; Hensley, S.; Kobrick, M.; Lavalle, M.; Martin, J. M.; Neumann, M.; Nguyen, Q.; Rosen, P. A.; Shimada, J.; Simard, M.; Tung, W.

2016-12-01

NASADEM is a near-global elevation model that is being produced primarily by completely reprocessing the Shuttle Radar Topography Mission (SRTM) radar data and then merging it with refined ASTER GDEM elevations. The new and improved SRTM elevations in NASADEM result from better vertical control of each SRTM data swath via reference to ICESat elevations and from SRTM void reductions using advanced interferometric unwrapping algorithms. Errors in SRTM (due to incorrect interferometric unwrapping) are rare but can be found and removed via a detector that relies upon pattern analysis within synergistic comparisons of SRTM and GDEM. Remnant voids in SRTM are filled primarily by GDEM3, but with removal of GDEM glitches that are mostly related to clouds. GDEM glitch removal uses a measure of curvature and then spatial filtering to detect, isolate, and delete anomalous spikes and pits that are uncharacteristic of natural topography. Water masking uses the original SRTM Water Body Dataset (SWBD), but with errors corrected via a new ASTER Water Body Database. The improved SRTM, GDEM, and water body databases will be made available individually in addition to our merged product, which is particularly important for the SRTM dataset, which stands as a February 2000 baseline for many topographic change studies. New and forthcoming freely available elevation data (at reduced resolutions) from the ALOS PRISM World 3D and TanDEM-X projects will contribute to the critical but not yet reached goal of a complete, high-quality elevation model of Earth, and they are expected to provide additional validation for NASADEM. Indeed, cross validation among all of these datasets is a vital part of reaching that goal. The value of elevation data is difficult to overstate. These data are used in nearly all types of geophysical study conducted at or near Earth's surface.

The Reference Elevation Model of Antarctica (REMA): A High Resolution, Time-Stamped Digital Elevation Model for the Antarctic Ice Sheet

NASA Astrophysics Data System (ADS)

Howat, I.; Noh, M. J.; Porter, C. C.; Smith, B. E.; Morin, P. J.

2017-12-01

We are creating the Reference Elevation Model of Antarctica (REMA), a continuous, high resolution (2-8 m), high precision (accuracy better than 1 m) reference surface for a wide range of glaciological and geodetic applications. REMA will be constructed from stereo-photogrammetric Digital Surface Models (DSM) extracted from pairs of submeter resolution DigitalGlobe satellite imagery and vertically registred to precise elevations from near-coincident airborne LiDAR, ground-based GPS surveys and Cryosat-2 radar altimetry. Both a seamless mosaic and individual, time-stamped DSM strips, collected primarily between 2012 and 2016, will be distributed to enable change measurement. These data will be used for mapping bed topography from ice thickness, measuring ice thickness changes, constraining ice flow and geodynamic models, mapping glacial geomorphology, terrain corrections and filtering of remote sensing observations, and many other science tasks. Is will also be critical for mapping ice traverse routes, landing sites and other field logistics planning. REMA will also provide a critical elevation benchmark for future satellite altimetry missions including ICESat-2. Here we report on REMA production progress, initial accuracy assessment and data availability.

Lunar Pole Illumination and Communications Maps Computed from GSSR Elevation Data

NASA Technical Reports Server (NTRS)

Bryant, Scott

2009-01-01

A Digital Elevation Model of the lunar south pole was produced using Goldstone Solar System RADAR (GSSR) data obtained in 2006.12 This model has 40-meter horizontal resolution and about 5-meter relative vertical accuracy. This Digital Elevation Model was used to compute average solar illumination and Earth visibility with 100 kilometers of the lunar south pole. The elevation data were converted into local terrain horizon masks, then converted into lunar-centric latitude and longitude coordinates. The horizon masks were compared to latitude, longitude regions bounding the maximum Sun and Earth motions relative to the moon. Estimates of Earth visibility were computed by integrating the area of the region bounding the Earth's motion that was below the horizon mask. Solar illumination and other metrics were computed similarly. Proposed lunar south pole base sites were examined in detail, with the best site showing yearly solar power availability of 92 percent and Direct-To-Earth (DTE) communication availability of about 50 percent. Similar analysis of the lunar south pole used an older GSSR Digital Elevation Model with 600-meter horizontal resolution. The paper also explores using a heliostat to reduce the photovoltaic power system mass and complexity.

Ikh Turgen Mountain Glacier Change and 3d Surface Extents Prediction Using Long Term Landsat Image and Climate Data

NASA Astrophysics Data System (ADS)

Nasanbat, Elbegjargal; Erdenebat, Erdenetogtokh; Chogsom, Bolorchuluun; Lkhamjav, Ochirkhuyag; Nanzad, Lkhagvadorj

2018-04-01

The glacier is most important the freshwater resources and indicator of the climate change. The researchers noted that during last decades the glacier is melting due to global warming. The study calculates a spatial distribution of protentional change of glacier coverage in the Ikh Turgen mountain of Western Mongolia, and it integrates long-term climate data and satellite datasets. Therefore, in this experiment has tried to estimation three-dimensional surface area of the glacier. For this purpose, Normalized difference snow index (NDSI) was applied to decision tree approach, using Landsat MSS, TM, ETM+ and LC8 imagery for 1975-2016, a surface and slope for digital elevation model, precipitation and air temperature historical data of meteorological station. The potential volume area significantly changed glacier cover of the Ikh Turgen Mountain, and the area affected by highly variable precipitation and air temperature regimes. Between 1972 and 2016, a potential area of glacier area has been decreased in Ikh Turgen mountain region.

Isostatic gravity map of the Monterey 30 x 60 minute quadrangle and adjacent areas, California

USGS Publications Warehouse

Langenheim, V.E.; Stiles, S.R.; Jachens, R.C.

2002-01-01

The digital dataset consists of one file (monterey_100k.iso) containing 2,385 gravity stations. The file, monterey_100k.iso, contains the principal facts of the gravity stations, with one point coded per line. The format of the data is described below. Each gravity station has a station name, location (latitude and longitude, NAD27 projection), elevation, and an observed gravity reading. The data are on the IGSN71 datum and the reference ellipsoid is the Geodetic Reference System 1967 (GRS67). The free-air gravity anomalies were calculated using standard formulas (Telford and others, 1976). The Bouguer, curvature, and terrain corrections were applied to the free-air anomaly at each station to determine the complete Bouguer gravity anomalies at a reduction density of 2.67 g/cc. An isostatic correction was then applied to remove the long-wavelength effect of deep crustal and/or upper mantle masses that isostatically support regional topography.

Bulk Insolation Models as Predictors for Locations for High Lunar Hydrogen Concentrations

NASA Technical Reports Server (NTRS)

Mcclanahan, T. P.; Mitrofanov, I.G.; Boynton, W. V.; Chin, G.; Starr, R. D.; Evans, L. G.; Sanin, A.; Livengood, T.; Sagdeev, R.; Milikh, G.

2013-01-01

In this study we consider the bulk effects of surface illumination on topography (insolation) and the possible thermodynamic effects on the Moon's hydrogen budget. Insolation is important as one of the dominant loss processes governing distributions of hydrogen volatiles on the Earth, Mars and most recently Mercury. We evaluated three types of high latitude > 65 deg., illumination models that were derived from the Lunar Observing Laser Altimetry (LOLA) digital elevation models (DEM)'s. These models reflect varying accounts of solar flux interactions with the Moon's near-surface. We correlate these models with orbital collimated epithermal neutron measurements made by the Lunar Exploration Neutron Detector (LEND). LEND's measurements derive the Moon's spatial distributions of hydrogen concentration. To perform this analysis we transformed the topographic model into an insolation model described by two variables as each pixels 1) slope and 2) slope angular orientation with respect to the pole. We then decomposed the illumination models and epithermal maps as a function of the insolation model and correlate the datasets.

Levee crest elevation profiles derived from airborne lidar-based high resolution digital elevation models in south Louisiana

USGS Publications Warehouse

Palaseanu-Lovejoy, Monica; Thatcher, Cindy A.; Barras, John A.

2014-01-01

This study explores the feasibility of using airborne lidar surveys to construct high-resolution digital elevation models (DEMs) and develop an automated procedure to extract levee longitudinal elevation profiles for both federal levees in Atchafalaya Basin and local levees in Lafourche Parish, south Lousiana. This approach can successfully accommodate a high degree of levee sinuosity and abrupt changes in levee orientation (direction) in planar coordinates, variations in levee geometries, and differing DEM resolutions. The federal levees investigated in Atchafalaya Basin have crest elevations between 5.3 and 12 m while the local counterparts in Lafourche Parish are between 0.76 and 2.3 m. The vertical uncertainty in the elevation data is considered when assessing federal crest elevation against the U.S. Army Corps of Engineers minimum height requirements to withstand the 100-year flood. Only approximately 5% of the crest points of the two federal levees investigated in the Atchafalaya Basin region met this requirement.

Cadastral Database Positional Accuracy Improvement

NASA Astrophysics Data System (ADS)

Hashim, N. M.; Omar, A. H.; Ramli, S. N. M.; Omar, K. M.; Din, N.

2017-10-01

Positional Accuracy Improvement (PAI) is the refining process of the geometry feature in a geospatial dataset to improve its actual position. This actual position relates to the absolute position in specific coordinate system and the relation to the neighborhood features. With the growth of spatial based technology especially Geographical Information System (GIS) and Global Navigation Satellite System (GNSS), the PAI campaign is inevitable especially to the legacy cadastral database. Integration of legacy dataset and higher accuracy dataset like GNSS observation is a potential solution for improving the legacy dataset. However, by merely integrating both datasets will lead to a distortion of the relative geometry. The improved dataset should be further treated to minimize inherent errors and fitting to the new accurate dataset. The main focus of this study is to describe a method of angular based Least Square Adjustment (LSA) for PAI process of legacy dataset. The existing high accuracy dataset known as National Digital Cadastral Database (NDCDB) is then used as bench mark to validate the results. It was found that the propose technique is highly possible for positional accuracy improvement of legacy spatial datasets.

Development of a seamless multisource topographic/bathymetric elevation model of Tampa Bay

USGS Publications Warehouse

Gesch, D.; Wilson, R.

2001-01-01

Many applications of geospatial data in coastal environments require knowledge of the nearshore topography and bathymetry. However, because existing topographic and bathymetric data have been collected independently for different purposes, it has been difficult to use them together at the land/water interface owing to differences in format, projection, resolution, accuracy, and datums. As a first step toward solving the problems of integrating diverse coastal datasets, the U.S. Geological Survey (USGS) and the National Oceanic and Atmospheric Administration (NOAA) are collaborating on a joint demonstration project to merge their data for the Tampa Bay region of Florida. The best available topographic and bathymetric data were extracted from the USGS National Elevation Dataset and the NOAA hydrographic survey database, respectively. Before being merged, the topographic and bathymetric datasets were processed with standard geographic information system tools to place them in a common horizontal reference frame. Also, a key part of the preprocessing was transformation to a common vertical reference through the use of VDatum, a new tool created by NOAA's National Geodetic Survey for vertical datum conversions. The final merged product is a seamless topographic/bathymetric model covering the Tampa Bay region at a grid spacing of 1 arc-second. Topographic LIDAR data were processed and merged with the bathymetry to demonstrate the incorporation of recent third party data sources for several test areas. A primary application of a merged topographic/bathymetric elevation model is for user-defined shoreline delineation, in which the user decides on the tidal condition (for example, low or high water) to be superimposed on the elevation data to determine the spatial position of the water line. Such a use of merged topographic/bathymetric data could lead to the development of a shoreline zone, which could reduce redundant mapping efforts by federal, state, and local agencies by allowing them to customize their portrayals of the shoreline using a standard baseline elevation dataset.

Land use and land cover digital data from 1:250,000- and 1:100,000- scale maps

USGS Publications Warehouse

,

1990-01-01

The Earth Science Information Centers (ESIC) distribute digital cartographic/geographic data files produced by the U.S. Geological Survey (USGS) as part of the National Mapping Program. The data files are grouped into four basic types. The first type, called a Digital Line Graph (DLG), is line map information in digital form. These data files include information on planimetric base categories, such as transportation, hydrography, and boundaries. The second type, called a Digital Elevation Model (DEM), consists of a sampled array of elevations for ground positions that are usually at regularly spaced intervals. The third type, Land Use and Land Cover digital data, provide information on nine major classes of land use such as urban, agricultural, or forest as well as associated map data such as political units and Federal land ownership. The fourth type, the Geographic Names Information System, provides primary information for known places, features, and areas in the United States identified by a proper name.

Creating Digital Environments for Multi-Agent Simulation

DTIC Science & Technology

2003-12-01

foliage on a polygon to represent a tree). Tile A spatial partition of a coverage that shares the same set of feature classes with the same... orthophoto datasets can be made from rectified grayscale aerial images. These datasets can support various weapon systems, Command, Control...Raster Product Format (RPF) Standard. This data consists of unclassified seamless orthophotos , made from rectified grayscale aerial images. DOI 10

Discovering the Past through Data: Promoting the Design and Analysis of Original Data-Sets in History Undergraduate Courses in Hong Kong

ERIC Educational Resources Information Center

Kim, Loretta; Wong, Shun Han Rebekah

2015-01-01

This article discusses the objectives and outcomes of a project to enhance digital humanities training at the undergraduate level in a Hong Kong university. The co-investigators re-designed a multi-source data-set as an example and then taught a multi-step curriculum about gathering, organizing, and presenting original data to an introductory…

Sediment erosion and delivery from Toutle River basin after the 1980 eruption of Mount St. Helens: A 30-year perspective

USGS Publications Warehouse

Major, Jon J.; Mosbrucker, Adam; Spicer, Kurt R.; Crisafulli, Charles; Dale, V.

2018-01-01

Exceptional sediment yields persist in Toutle River valley more than 30 years after the major 1980 eruption of Mount St. Helens. Differencing of decadal-scale digital elevation models shows the elevated load comes largely from persistent lateral channel erosion across the debris-avalanche deposit. Since the mid-1980s, rates of channel-bed-elevation change have diminished, and magnitudes of lateral erosion have outpaced those of channel incision. A digital elevation model of difference from 1999 to 2009 shows erosion across the debris-avalanche deposit is more spatially distributed compared to a model from 1987 to 1999, in which erosion was strongly focused along specific reaches of the channel.

Evaluating stability of histomorphometric features across scanner and staining variations: predicting biochemical recurrence from prostate cancer whole slide images

NASA Astrophysics Data System (ADS)

Leo, Patrick; Lee, George; Madabhushi, Anant

2016-03-01

Quantitative histomorphometry (QH) is the process of computerized extraction of features from digitized tissue slide images. Typically these features are used in machine learning classifiers to predict disease presence, behavior and outcome. Successful robust classifiers require features that both discriminate between classes of interest and are stable across data from multiple sites. Feature stability may be compromised by variation in slide staining and scanning procedures. These laboratory specific variables include dye batch, slice thickness and the whole slide scanner used to digitize the slide. The key therefore is to be able to identify features that are not only discriminating between the classes of interest (e.g. cancer and non-cancer or biochemical recurrence and non- recurrence) but also features that will not wildly fluctuate on slides representing the same tissue class but from across multiple different labs and sites. While there has been some recent efforts at understanding feature stability in the context of radiomics applications (i.e. feature analysis of radiographic images), relatively few attempts have been made at studying the trade-off between feature stability and discriminability for histomorphometric and digital pathology applications. In this paper we present two new measures, preparation-induced instability score (PI) and latent instability score (LI), to quantify feature instability across and within datasets. Dividing PI by LI yields a ratio for how often a feature for a specific tissue class (e.g. low grade prostate cancer) is different between datasets from different sites versus what would be expected from random chance alone. Using this ratio we seek to quantify feature vulnerability to variations in slide preparation and digitization. Since our goal is to identify stable QH features we evaluate these features for their stability and thus inclusion in machine learning based classifiers in a use case involving prostate cancer. Specifically we examine QH features which may predict 5 year biochemical recurrence for prostate cancer patients who have undergone radical prostatectomy from digital slide images of surgically excised tissue specimens, 5 year biochemical recurrence being a strong predictor of disease recurrence. In this study we evaluated the ability of our feature robustness indices to identify the most stable and predictive features of 5 year biochemical recurrence using digitized slide images of surgically excised prostate cancer specimens from 80 different patients across 4 different sites. A total of 242 features from 5 different feature families were investigated to identify the most stable QH features from our set. Our feature robustness indices (PI and LI) suggested that five feature families (graph, shape, co-occurring gland tensors, gland sub-graphs, texture) were susceptible to variations in slide preparation and digitization across various sites. The family least affected was shape features in which 19.3% of features varied across laboratories while the most vulnerable family, at 55.6%, was the gland disorder features. However the disorder features were the most stable within datasets being different between random halves of a dataset in an average of just 4.1% of comparisons while texture features were the most unstable being different at a rate of 4.7%. We also compared feature stability across two datasets before and after color normalization. Color normalization decreased feature stability with 8% and 34% of features different between the two datasets in two outcome groups prior to normalization and 49% and 51% different afterwards. Our results appear to suggest that evaluation of QH features across multiple sites needs to be undertaken to assess robustness and class discriminability alone should not represent the benchmark for selection of QH features to build diagnostic and prognostic digital pathology classifiers.

Feasibility and Accuracy of Digitizing Edentulous Maxillectomy Defects: A Comparative Study.

PubMed

Elbashti, Mahmoud E; Hattori, Mariko; Patzelt, Sebastian Bm; Schulze, Dirk; Sumita, Yuka I; Taniguchi, Hisashi

The aim of this study was to evaluate the feasibility and accuracy of using an intraoral scanner to digitize edentulous maxillectomy defects. A total of 20 maxillectomy models with two defect types were digitized using cone beam computed tomography. Conventional and digital impressions were made using silicone impression material and a laboratory optical scanner as well as a chairside intraoral scanner. The 3D datasets were analyzed using 3D evaluation software. Two-way analysis of variance revealed no interaction between defect types and impression methods, and the accuracy of the impression methods was significantly different (P = .0374). Digitizing edentulous maxillectomy defect models using a chairside intraoral scanner appears to be feasible and accurate.

Topogrid Derived 10 Meter Resolution Digital Elevation Model of the Shenandoah National Park and Surrounding Region, Virginia

USGS Publications Warehouse

Chirico, Peter G.; Tanner, Seth D.

2004-01-01

Explanation The purpose of developing a new 10m resolution DEM of the Shenandoah National Park Region was to more accurately depict geologic structure, surfical geology, and landforms of the Shenandoah National Park Region in preparation for automated landform classification. Previously, only a 30m resolution DEM was available through the National Elevation Dataset (NED). During production of the Shenandoah10m DEM of the Park the Geography Discipline of the USGS completed a revised 10m DEM to be included into the NED. However, different methodologies were used to produce the two similar DEMs. The ANUDEM algorithm was used to develop the Shenadoah DEM data. This algorithm allows for the inclusion of contours, streams, rivers, lake and water body polygons as well as spot height data to control the elevation model. A statistical analysis using over 800 National Geodetic Survey (NGS) first and second order vertical control points reveals that the Shenandoah10m DEM, produced as a part of the Appalachian Blue Ridge Landscape project, has a vertical accuracy of ?4.87 meters. The metadata for the 10m NED data reports a vertical accuracy of ?7m. A table listing the NGS control points, the elevation comparison, and the RMSE for the Shenandoah10m DEM is provided. The process of automated terrain classification involves developing statistical signatures from the DEM for each type of surficial deposit and landform type. The signature will be a measure of several characteristics derived from the elevation data including slope, aspect, planform curvature, and profile curvature. The quality of the DEM is of critical importance when extracting terrain signatures. The highest possible horizontal and vertical accuracy is required. The more accurate Shenandoah 10m DEM can now be analyzed and integrated with the geologic observations to yield statistical correlations between the two in the development of landform and surface geology mapping projects.

Earth Explorer

USGS Publications Warehouse

,

2000-01-01

The U.S. Geological Survey's (USGS) Earth Explorer Web site provides access to millions of land-related products, including the following: Satellite images from Landsat, advanced very high resolution radiometer (AVHRR), and Corona data sets. Aerial photographs from the National Aerial Photography Program, NASA, and USGS data sets.  Digital cartographic data from digital elevation models, digital line graphs, digital raster graphics, and digital orthophoto quadrangles. USGS paper maps Digital, film, and paper products are available, and many products can be previewed before ordering.

A History Update of the U. S. Army Engineer Topographic Laboratories Fort Belvoir, Virginia 1979-1983

DTIC Science & Technology

1988-01-01

these patterns had to be arranged in one of a number of spatial data formats. To a computer, electronic " noise " created by errant impulses in the...quality photographs can be deblurred using digital image manipulation techniques. The special congressional committee investigating the...capability. UNAMACE errors were of two kinds. Electronic noise recorded along with digital elevation data created false elevations . Also , UNAMACE could

Digital elevation data as an aid to land use and land cover classification

USGS Publications Warehouse

Colvocoresses, Alden P.

1981-01-01

In relatively well mapped areas such as the United States and Europe, digital data can be developed from topographic maps or from the stereo aerial photographic movie. For poorer mapped areas (which involved most of the world's land areas), a satellite designed to obtain stereo data offers the best hope for a digital elevation database. Such a satellite, known as Mapsat, has been defined by the U.S. Geological Survey. Utilizing modern solid state technology, there is no reason why such stereo data cannot be acquired simultaneously with the multispectral response, thus simplifying the overall problem of land use and land cover classification.

A method for the processing and analysis of digital terrain elevation data. [Shiprock and Gallup Quadrangles, Arizona and New Mexico

NASA Technical Reports Server (NTRS)

Junkin, B. G. (Principal Investigator)

1979-01-01

A method is presented for the processing and analysis of digital topography data that can subsequently be entered in an interactive data base in the form of slope, slope length, elevation, and aspect angle. A discussion of the data source and specific descriptions of the data processing software programs are included. In addition, the mathematical considerations involved in the registration of raw digitized coordinate points to the UTM coordinate system are presented. Scale factor considerations are also included. Results of the processing and analysis are illustrated using the Shiprock and Gallup Quadrangle test data.

Algorithms and methodology used in constructing high-resolution terrain databases

NASA Astrophysics Data System (ADS)

Williams, Bryan L.; Wilkosz, Aaron

1998-07-01

This paper presents a top-level description of methods used to generate high-resolution 3D IR digital terrain databases using soft photogrammetry. The 3D IR database is derived from aerial photography and is made up of digital ground plane elevation map, vegetation height elevation map, material classification map, object data (tanks, buildings, etc.), and temperature radiance map. Steps required to generate some of these elements are outlined. The use of metric photogrammetry is discussed in the context of elevation map development; and methods employed to generate the material classification maps are given. The developed databases are used by the US Army Aviation and Missile Command to evaluate the performance of various missile systems. A discussion is also presented on database certification which consists of validation, verification, and accreditation procedures followed to certify that the developed databases give a true representation of the area of interest, and are fully compatible with the targeted digital simulators.

Vertical Accuracy Evaluation of Aster GDEM2 Over a Mountainous Area Based on Uav Photogrammetry

NASA Astrophysics Data System (ADS)

Liang, Y.; Qu, Y.; Guo, D.; Cui, T.

2018-05-01

Global digital elevation models (GDEM) provide elementary information on heights of the Earth's surface and objects on the ground. GDEMs have become an important data source for a range of applications. The vertical accuracy of a GDEM is critical for its applications. Nowadays UAVs has been widely used for large-scale surveying and mapping. Compared with traditional surveying techniques, UAV photogrammetry are more convenient and more cost-effective. UAV photogrammetry produces the DEM of the survey area with high accuracy and high spatial resolution. As a result, DEMs resulted from UAV photogrammetry can be used for a more detailed and accurate evaluation of the GDEM product. This study investigates the vertical accuracy (in terms of elevation accuracy and systematic errors) of the ASTER GDEM Version 2 dataset over a complex terrain based on UAV photogrammetry. Experimental results show that the elevation errors of ASTER GDEM2 are in normal distribution and the systematic error is quite small. The accuracy of the ASTER GDEM2 coincides well with that reported by the ASTER validation team. The accuracy in the research area is negatively correlated to both the slope of the terrain and the number of stereo observations. This study also evaluates the vertical accuracy of the up-sampled ASTER GDEM2. Experimental results show that the accuracy of the up-sampled ASTER GDEM2 data in the research area is not significantly reduced by the complexity of the terrain. The fine-grained accuracy evaluation of the ASTER GDEM2 is informative for the GDEM-supported UAV photogrammetric applications.

The Characterization of a DIRSIG Simulation Environment to Support the Inter-Calibration of Spaceborne Sensors

NASA Technical Reports Server (NTRS)

Ambeau, Brittany L.; Gerace, Aaron D.; Montanaro, Matthew; McCorkel, Joel

2016-01-01

Climate change studies require long-term, continuous records that extend beyond the lifetime, and the temporal resolution, of a single remote sensing satellite sensor. The inter-calibration of spaceborne sensors is therefore desired to provide spatially, spectrally, and temporally homogeneous datasets. The Digital Imaging and Remote Sensing Image Generation (DIRSIG) tool is a first principle-based synthetic image generation model that has the potential to characterize the parameters that impact the accuracy of the inter-calibration of spaceborne sensors. To demonstrate the potential utility of the model, we compare the radiance observed in real image data to the radiance observed in simulated image from DIRSIG. In the present work, a synthetic landscape of the Algodones Sand Dunes System is created. The terrain is facetized using a 2-meter digital elevation model generated from NASA Goddard's LiDAR, Hyperspectral, and Thermal (G-LiHT) imager. The material spectra are assigned using hyperspectral measurements of sand collected from the Algodones Sand Dunes System. Lastly, the bidirectional reflectance distribution function (BRDF) properties are assigned to the modeled terrain using the Moderate Resolution Imaging Spectroradiometer (MODIS) BRDF product in conjunction with DIRSIG's Ross-Li capability. The results of this work indicate that DIRSIG is in good agreement with real image data. The potential sources of residual error are identified and the possibilities for future work are discussed..

The characterization of a DIRSIG simulation environment to support the inter-calibration of spaceborne sensors

NASA Astrophysics Data System (ADS)

Ambeau, Brittany L.; Gerace, Aaron D.; Montanaro, Matthew; McCorkel, Joel

2016-09-01

Climate change studies require long-term, continuous records that extend beyond the lifetime, and the temporal resolution, of a single remote sensing satellite sensor. The inter-calibration of spaceborne sensors is therefore desired to provide spatially, spectrally, and temporally homogeneous datasets. The Digital Imaging and Remote Sensing Image Generation (DIRSIG) tool is a first principle-based synthetic image generation model that has the potential to characterize the parameters that impact the accuracy of the inter-calibration of spaceborne sensors. To demonstrate the potential utility of the model, we compare the radiance observed in real image data to the radiance observed in simulated image from DIRSIG. In the present work, a synthetic landscape of the Algodones Sand Dunes System is created. The terrain is facetized using a 2-meter digital elevation model generated from NASA Goddard's LiDAR, Hyperspectral, and Thermal (G-LiHT) imager. The material spectra are assigned using hyperspectral measurements of sand collected from the Algodones Sand Dunes System. Lastly, the bidirectional reflectance distribution function (BRDF) properties are assigned to the modeled terrain using the Moderate Resolution Imaging Spectroradiometer (MODIS) BRDF product in conjunction with DIRSIG's Ross-Li capability. The results of this work indicate that DIRSIG is in good agreement with real image data. The potential sources of residual error are identified and the possibilities for future work are discussed.

ATM Coastal Topography - Louisiana, 2001: UTM Zone 16 (Part 2 of 2)

USGS Publications Warehouse

Yates, Xan; Nayegandhi, Amar; Brock, John C.; Sallenger, Asbury H.; Klipp, Emily S.; Wright, C. Wayne

2009-01-01

These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography were produced collaboratively by the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the Louisiana coastline beach face within UTM Zone 16, from Grand Isle to the Chandeleur Islands, acquired September 7 and 9, 2001. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative scanning lidar instrument originally developed by NASA, and known as the Airborne Topographic Mapper (ATM), was used during data acquisition. The ATM system is a scanning lidar system that measures high-resolution topography of the land surface and incorporates a green-wavelength laser operating at pulse rates of 2 to 10 kilohertz. Measurements from the laser-ranging device are coupled with data acquired from inertial navigation system (INS) attitude sensors and differentially corrected global positioning system (GPS) receivers to measure topography of the surface at accuracies of +/-15 centimeters. The nominal ATM platform is a Twin Otter or P-3 Orion aircraft, but the instrument may be deployed on a range of light aircraft. Elevation measurements were collected over the survey area using the ATM system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or first-surface topography.

ATM Coastal Topography-Louisiana, 2001: UTM Zone 15 (Part 1 of 2)

USGS Publications Warehouse

Yates, Xan; Nayegandhi, Amar; Brock, John C.; Sallenger, A.H.; Klipp, Emily S.; Wright, C. Wayne

2010-01-01

These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography were produced collaboratively by the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the Louisiana coastline beach face within UTM Zone 15, from Isles Dernieres to Grand Isle, acquired September 7 and 10, 2001. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative scanning lidar instrument originally developed by NASA, and known as the Airborne Topographic Mapper (ATM), was used during data acquisition. The ATM system is a scanning lidar system that measures high-resolution topography of the land surface and incorporates a green-wavelength laser operating at pulse rates of 2 to 10 kilohertz. Measurements from the laser-ranging device are coupled with data acquired from inertial navigation system (INS) attitude sensors and differentially corrected global positioning system (GPS) receivers to measure topography of the surface at accuracies of +/-15 centimeters. The nominal ATM platform is a Twin Otter or P-3 Orion aircraft, but the instrument may be deployed on a range of light aircraft. Elevation measurements were collected over the survey area using the ATM system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or first-surface topography.

ATM Coastal Topography-Texas, 2001: UTM Zone 14

USGS Publications Warehouse

Klipp, Emily S.; Nayegandhi, Amar; Brock, John C.; Sallenger, A.H.; Bonisteel, Jamie M.; Yates, Xan; Wright, C. Wayne

2009-01-01

These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography were produced collaboratively by the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the Texas coastline within UTM zone 14, acquired October 12-13, 2001. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative scanning lidar instrument originally developed by NASA, and known as the Airborne Topographic Mapper (ATM), was used during data acquisition. The ATM system is a scanning lidar system that measures high-resolution topography of the land surface and incorporates a green-wavelength laser operating at pulse rates of 2 to 10 kilohertz. Measurements from the laser-ranging device are coupled with data acquired from inertial navigation system (INS) attitude sensors and differentially corrected global positioning system (GPS) receivers to measure topography of the surface at accuracies of +/-15 centimeters. The nominal ATM platform is a Twin Otter or P-3 Orion aircraft, but the instrument may be deployed on a range of light aircraft. Elevation measurements were collected over the survey area using the ATM system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or first-surface topography.

ATM Coastal Topography-Texas, 2001: UTM Zone 15

USGS Publications Warehouse

Klipp, Emily S.; Nayegandhi, Amar; Brock, John C.; Sallenger, A.H.; Bonisteel, Jamie M.; Yates, Xan; Wright, C. Wayne

2009-01-01

These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography were produced collaboratively by the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the Texas coastline within UTM zone 15, from Matagorda Peninsula to Galveston Island, acquired October 12-13, 2001. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative scanning lidar instrument originally developed by NASA, and known as the Airborne Topographic Mapper (ATM), was used during data acquisition. The ATM system is a scanning lidar system that measures high-resolution topography of the land surface and incorporates a green-wavelength laser operating at pulse rates of 2 to 10 kilohertz. Measurements from the laser-ranging device are coupled with data acquired from inertial navigation system (INS) attitude sensors and differentially corrected global positioning system (GPS) receivers to measure topography of the surface at accuracies of +/-15 centimeters. The nominal ATM platform is a Twin Otter or P-3 Orion aircraft, but the instrument may be deployed on a range of light aircraft. Elevation measurements were collected over the survey area using the ATM system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or first-surface topography.

ATM Coastal Topography-Florida 2001: Western Panhandle

USGS Publications Warehouse

Yates, Xan; Nayegandhi, Amar; Brock, John C.; Sallenger, A.H.; Bonisteel, Jamie M.; Klipp, Emily S.; Wright, C. Wayne

2009-01-01

These remotely sensed, geographically referenced elevation measurements of Lidar-derived first surface (FS) topography were produced collaboratively by the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of the western Florida panhandle coastline, acquired October 2-4 and 7-10, 2001. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative scanning Lidar instrument originally developed by NASA, and known as the Airborne Topographic Mapper (ATM), was used during data acquisition. The ATM system is a scanning Lidar system that measures high-resolution topography of the land surface and incorporates a green-wavelength laser operating at pulse rates of 2 to 10 kilohertz. Measurements from the laser-ranging device are coupled with data acquired from inertial navigation system (INS) attitude sensors and differentially corrected global positioning system (GPS) receivers to measure topography of the surface at accuracies of +/-15 centimeters. The nominal ATM platform is a Twin Otter or P-3 Orion aircraft, but the instrument may be deployed on a range of light aircraft. Elevation measurements were collected over the survey area using the ATM system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for presurvey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is routinely used to create maps that represent submerged or first surface topography.

ATM Coastal Topography-Mississippi, 2001

USGS Publications Warehouse

Nayegandhi, Amar; Yates, Xan; Brock, John C.; Sallenger, A.H.; Klipp, Emily S.; Wright, C. Wayne

2009-01-01

These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography were produced collaboratively by the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of the Mississippi coastline, from Lakeshore to Petit Bois Island, acquired September 9-10, 2001. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative scanning lidar instrument originally developed by NASA, and known as the Airborne Topographic Mapper (ATM), was used during data acquisition. The ATM system is a scanning lidar system that measures high-resolution topography of the land surface and incorporates a green-wavelength laser operating at pulse rates of 2 to 10 kilohertz. Measurements from the laser-ranging device are coupled with data acquired from inertial navigation system (INS) attitude sensors and differentially corrected global positioning system (GPS) receivers to measure topography of the surface at accuracies of +/-15 centimeters. The nominal ATM platform is a Twin Otter or P-3 Orion aircraft, but the instrument may be deployed on a range of light aircraft. Elevation measurements were collected over the survey area using the ATM system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or first-surface topography.

Downscaling of inundation extents

NASA Astrophysics Data System (ADS)

Aires, Filipe; Prigent, Catherine; Papa, Fabrice

2014-05-01

The Global Inundation Extent from Multi-Satellite (GIEMS) provides multi-year monthly variations of the global surface water extent at about 25 kmx25 km resolution, from 1993 to 2007. It is derived from multiple satellite observations. Its spatial resolution is usually compatible with climate model outputs and with global land surface model grids but is clearly not adequate for local applications that require the characterization of small individual water bodies. There is today a strong demand for high-resolution inundation extent datasets, for a large variety of applications such as water management, regional hydrological modeling, or for the analysis of mosquitos-related diseases. This paper present three approaches to do downscale GIEMS: The first one is based on a image-processing technique using neighborhood constraints. The third approach uses a PCA representation to perform an algebraic inversion. The PCA-representation is also very convenient to perform temporal and spatial interpolation of complexe inundation fields. The third downscaling method uses topography information from Hydroshed Digital Elevation Model (DEM). Information such as the elevation, distance to river and flow accumulation are used to define a ``flood ability index'' that is used by the downscaling. Three basins will be considered for illustrative purposes: Amazon, Niger and Mekong. Aires, F., F. Papa, C. Prigent, J.-F. Cretaux and M. Berge-Nguyen, Characterization and downscaling of the inundation extent over the Inner Niger delta using a multi-wavelength retrievals and Modis data, J. of Hydrometeorology, in press, 2014. Aires, F., F. Papa and C. Prigent, A long-term, high-resolution wetland dataset over the Amazon basin, downscaled from a multi-wavelength retrieval using SAR, J. of Hydrometeorology, 14, 594-6007, 2013. Prigent, C., F. Papa, F. Aires, C. Jimenez, W.B. Rossow, and E. Matthews. Changes in land surface water dynamics since the 1990s and relation to population pressure. Geophys. Res. Lett., 39(L08403), 2012.