Validation and Analysis of SRTM and VCL Data Over Tropical Volcanoes

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Mouginis-Mark, Peter J.

2004-01-01

The focus of our investigation was on the application of digital topographic data in conducting first-order volcanological and structural studies of tropical volcanoes, focusing on the Java, the Philippines and the Galapagos Islands. Kilauea volcano, Hawaii, served as our test site for SRTM data validation. Volcanoes in humid tropical environments are frequently cloud covered, typically densely vegetated and erode rapidly, so that it was expected that new insights into the styles of eruption of these volcanoes could be obtained from analysis of topographic data. For instance, in certain parts of the world, such as Indonesia, even the regional structural context of volcanic centers is poorly known, and the distribution of volcanic products (e.g., lava flows, pyroclastic flows, and lahars) are not well mapped. SRTM and Vegetation Canopy Lidar (VCL) data were expected to provide new information on these volcanoes. Due to the cancellation of the VCL mission, we did not conduct any lidar studies during the duration of this project. Digital elevation models (DEMs) such as those collected by SRTM provide quantitative information about the time-integrated typical activity on a volcano and allow an assessment of the spatial and temporal contributions of various constructional and destructional processes to each volcano's present morphology. For basaltic volcanoes, P_c?w!m-d and Garbed (2000) have shown that gradual slopes (less than 5 deg.) occur where lava and tephra pond within calderas or in the saddles between adjacent volcanoes, as well as where lava deltas coalesce to form coastal plains. Vent concentration zones (axes of rift zones) have slopes ranging from 10 deg. to 12 deg. Differential vertical growth rates between vent concentration zones and adjacent mostly-lava flanks produce steep constructional slopes up to 40". The steepest slopes (locally approaching 90 deg.) are produced by fluvial erosion, caldera collapse, faulting, and catastrophic avalanches, all of

DERIVAÇÃO DE REDE DE DRENAGEM A PARTIR DE DADOS DO SRTM / DERIVING DRAINAGE NETWORK FROM SRTM DATA

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Walter Collischonn

2008-08-01

Full Text Available The development and improvement of Geographic Information Systems and geoprocessing algorithms,together with the increase in computational capacity and data availability from remote sensing, becamepossible to prepare information for hydrologic studies of large areas with relative low cost and incrediblespeed. This paper describes the use of SRTM data to derive drainage network and related products, suchas accumulated drainage areas and river lengths, with application to the Uruguay river basin. Six distinctDigital Elevation Models (DEMs were used, varying the spatial resolution and applying the stream burningpre-processing technique. The main limitations of the DEM-derived drainage network refer to the incapacityof representing river meanders that are smaller than the pixel size and the problem of artificial sinuosity thatoccurs when the width of the river is larger than pixel side.

REGIONAL GEOLGICAL MAPPING IN TROPICAL ENVIRONMENTS USING LANDSAT TM AND SRTM REMOTE SENSING DATA

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A. Beiranvand Pour

2015-10-01

Full Text Available Landsat Thematic Mapper (TM and Shuttle Radar Topography Mission (SRTM data were used to produce geological maps in tropical environments. Lineament, lithology and landform maps were produced for all states in peninsular Malaysia in this study. Kedah, Perak and Terengganu states have been selected as case studies to demonstrate the results of the data and techniques used. Directional filtering technique was applied to Landsat TM bands 4, 5 and 3 for lineament mapping. The lithology map was produced using Landsat TM bands combination consist of bands 4, 3 and 2. Digital elevation model and landform map were produced using SRTM data in 3 Dimension (3D and 2 Dimension (2D perspective views, respectively. The produced geological maps and the remote sensing data and methods applied in this study are mostly appropriate for hazard risk mapping applications and mineral exploration projects in the peninsular Malaysia and tropical environments.

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

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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.

VALIDATION OF THE ASTER GLOBAL DIGITAL ELEVATION MODEL VERSION 2 OVER THE CONTERMINOUS UNITED STATES

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D. Gesch

2012-07-01

Full Text Available 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.

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

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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.

Mapping boreal forest biomass from a SRTM and TanDEM-X based on canopy height model and Landsat spectral indices

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Sadeghi, Yaser; St-Onge, Benoît; Leblon, Brigitte; Prieur, Jean-François; Simard, Marc

2018-06-01

We propose a method for mapping above-ground biomass (AGB) (Mg ha-1) in boreal forests based predominantly on Landsat 8 images and on canopy height models (CHM) generated using interferometric synthetic aperture radar (InSAR) from the Shuttle Radar Topographic Mission (SRTM) and the TanDEM-X mission. The original SRTM digital elevation model (DEM) was corrected by modelling the respective effects of landform and land cover on its errors and then subtracted from a TanDEM-X DSM to produce a SAR CHM. Among all the landform factors, the terrain curvature had the largest effect on SRTM elevation errors, with a r2 of 0.29. The NDSI was the best predictor of the residual SRTM land cover error, with a r2 of 0.30. The final SAR CHM had a RMSE of 2.45 m, with a bias of 0.07 m, compared to a lidar-based CHM. An AGB prediction model was developed based on a combination of the SAR CHM, TanDEM-X coherence, Landsat 8 NDVI, and other vegetation indices of RVI, DVI, GRVI, EVI, LAI, GNDVI, SAVI, GVI, Brightness, Greenness, and Wetness. The best results were obtained using a Random forest regression algorithm, at the stand level, yielding a RMSE of 26 Mg ha-1 (34% of average biomass), with a r2 of 0.62. This method has the potential of creating spatially continuous biomass maps over entire biomes using only spaceborne sensors and requiring only low-intensity calibration.

SRTM Perspective View with Landsat Overlay: Mt. Pinos and San Joaquin Valley, California

Science.gov (United States)

2000-01-01

Ask any astronomer where the best stargazing site in Southern California is, and chances are they'll say Mt. Pinos. In this perspective view generated from SRTM elevation data the snow-capped peak is seen rising to an elevation of 2,692 meters (8,831 feet), in stark contrast to the flat agricultural fields of the San Joaquin valley seen in the foreground. Below the summit, but still well away from city lights, the Mt. Pinos parking lot at 2,468 meters (8,100 feet) is a popular viewing area for both amateur and professional astronomers and astro-photographers. For visualization purposes, topographic heights displayed in this image are exaggerated two times.The elevation data used in this image was acquired by SRTM aboard the Space Shuttle Endeavour, launched on February 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on Endeavour in 1994. SRTM was designed to collect three-dimensional measurements of Earth's land surface. To collect the 3-D SRTM data, engineers added a mast 60 meters (about 200 feet)long, installed additional C-band and X-band antennas, and improved tracking and navigation devices. The mission is a cooperative project between the NASA, the National Imagery and Mapping Agency (NIMA) of the U.S. Department of Defense, and the German and Italian space agencies. It is managed by NASA's Jet Propulsion Laboratory, Pasadena, Calif., for NASA's Earth Science Enterprise,Washington, D.C. JPL is a division of the California Institute of Technology in Pasadena.Distance to Horizon: 176 kilometers (109 miles) Location: 34.83 deg. North lat., 119.25 deg. West lon. View: Toward the Southwest Date Acquired: February 16, 2000 SRTM, December 14, 1984 Landsat

Karst Depression Detection Using ASTER, ALOS/PRISM and SRTM-Derived Digital Elevation Models in the Bambuí Group, Brazil

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Osmar Abílio de Carvalho

2013-12-01

Full Text Available Remote sensing has been used in karst studies to identify limestone terrain, describe exokarst features, analyze karst depressions, and detect geological structures important to karst development. The aim of this work is to investigate the use of ASTER-, SRTM- and ALOS/PRISM-derived digital elevation models (DEMs to detect and quantify natural karst depressions along the São Francisco River near Barreiras city, northeast Brazil. The study area is a karst landscape characterized by karst depressions (dolines, closed depressions in limestone, many of which contain standing water connected with the ground-water table. The base of dolines is typically sealed with an impermeable clay layer covered by standing water or herbaceous vegetation. We identify dolines by combining the extraction of sink depth from DEMs, morphometric analysis using GIS, and visual interpretation. Our methodology is a semi-automatic approach involving several steps: (a DEM acquisition; (b sink-depth calculation using the difference between the raw DEM and the corresponding DEM with sinks filled; and (c elimination of falsely identified karst depressions using morphometric attributes. The advantages and limitations of the applied methodology using different DEMs are examined by comparison with a sinkhole map generated from traditional geomorphological investigations based on visual interpretation of the high-resolution remote sensing images and field surveys. The threshold values of the depth, area size and circularity index appropriate for distinguishing dolines were identified from the maximum overall accuracy obtained by comparison with a true doline map. Our results indicate that the best performance of the proposed methodology for meso-scale karst feature detection was using ALOS/PRISM data with a threshold depth > 2 m; areas > 13,125 m2 and circularity indexes > 0.3 (overall accuracy of 0.53. The overall correct identification of around half of the true dolines suggests

SRTM Colored Height and Shaded Relief: Sredinnyy Khrebet, Kamchatka Peninsula, Russia

Science.gov (United States)

2001-01-01

The Kamchatka Peninsula in eastern Russia is shown in this scene created from a preliminary elevation model derived from the first data collected during the Shuttle Radar Topography Mission (SRTM) on February 12, 2000. Sredinnyy Khrebet, the mountain range that makes up the spine of the peninsula, is a chain of active volcanic peaks. Pleistocene and recent glaciers have carved the broad valleys and jagged ridges that are common here. The relative youth of the volcanism is revealed by the topography as infilling and smoothing of the otherwise rugged terrain by lava, ash, and pyroclastic flows, particularly surrounding the high peaks in the south central part of the image. Elevations here range from near sea level up to 2,618 meters (8,590 feet).Two visualization methods were combined to produce this image: shading and color coding of topographic height. The shade image was derived by computing topographic slope in the north-south direction. Northern slopes appear bright and southern slopes appear dark. Color coding is directly related to topographic height, with green at the lower elevations, rising through yellow, red, and magenta, to white at the highest elevations.Elevation data used in this image was acquired by the Shuttle Radar Topography Mission (SRTM) aboard Space Shuttle Endeavour, launched on February 11,2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on Space Shuttle Endeavour in 1994. SRTM was designed to collect three-dimensional measurements of Earth's surface. To collect the 3-D data, engineers added a 60-meter-long (200-foot) mast, installed additional C-band and X-band antennas, and improved tracking and navigation devices. The mission is a cooperative project between the National Aeronautics and Space Administration (NASA), the National Imagery and Mapping Agency (NIMA) of the U.S. Department of Defense, and the German and Italian space agencies

SRTM Radar Image, Wrapped Color as Height/EarthKam Optical Honolulu, Hawaii

Science.gov (United States)

2000-01-01

These two images of the eastern part of the island of Oahu, Hawaii provide information on regional topography and show the relationship between urban development and sensitive ecosystems. On the left is a topographic radar image collected by the Shuttle Radar Topography Mission (SRTM.) On the right is an optical image acquired by a digital camera on the Space Shuttle Endeavour, which carried SRTM. Features of interest in this scene include Diamond Head (an extinct volcano at the lower center), Waikiki Beach (just left of Diamond Head), the Punchbowl National Cemetery (another extinct volcano, at the foot of the Koolau Mountains), downtown Honolulu and Honolulu airport (lower left of center), and Pearl Harbor (at the left edge.)The topography shows the steep, high central part of the island surrounded by flatter coastal areas. The optical image shows the urban areas and a darker, forested region on the mountain slopes. The clouds in the optical image and the black areas on the topographic image are both a result of the steep topography. In this tropical region, high mountain peaks are usually covered in clouds. These steep peaks also cause shadows in the radar data, resulting in missing data 'holes.' A second pass over the island was obtained by SRTM and will be used to fill in the holes.The left image combines two types of SRTM data. Brightness corresponds to the strength of the radar signal reflected from the ground, while colors show the elevation. Each color cycle (from pink through blue and back to pink) represents 400 meters (1,300 feet) of elevation difference, like the contour lines on a topographic map. This image contains about 2,400 meters (8,000 feet) of total relief. The optical image was acquired by the Shuttle Electronic Still Camera with a lens focal length of 64 millimeters (2.5 inches) for the Earth Knowledge Acquired by Middle school students (EarthKAM) project. EarthKAM has flown on five space shuttle missions since 1996. Additional information

SRTM Colored Height and Shaded Relief: Pinon Canyon region, Colorado

Science.gov (United States)

2001-01-01

Erosional features are prominent in this view of southern Colorado taken by the Shuttle Radar Topography Mission (SRTM). The area covers about 20,000 square kilometers and is located about 50 kilometers south of Pueblo, Colorado. The prominent mountains near the left edge of the image are the Spanish Peaks, remnants of a 20 million year old volcano. Rising 2,100 meters (7,000 ft) above the plains to the east, these igneous rock formations with intrusions of eroded sedimentary rock historically served as guiding landmarks for travelers on the Mountain Branch of the Santa Fe Trail.Near the center of the image is the Pinon Canyon Maneuver Site, a training area for soldiers of the U.S. Army from nearby Fort Carson. The site supports a diverse ecosystem with large numbers of big and small game, fisheries, non-game wildlife, forest, range land and mineral resources. It is bounded on the east by the dramatic topography of the Purgatoire River Canyon, a 100 meter (328 foot) deep scenic red canyon with flowing streams, sandstone formations, and exposed geologic processes.Two visualization methods were combined to produce this image: shading and color coding of topographic height. The shade image was derived by computing topographic slope in the northwest-southeast direction. Southern slopes appear bright and northern slopes appear dark. Color coding is directly related to topographic height, with blue and green at the lower elevations, rising through yellow and brown to white at the highest elevations.Elevation data used in this image was acquired by the Shuttle Radar Topography Mission (SRTM) aboard the Space Shuttle Endeavour, launched on February 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR)that flew twice on the Space Shuttle Endeavour in 1994. SRTM was designed to collect three-dimensional measurements of the Earth's surface. To collect the 3-D data, engineers added a 60-meter

Morpho structural interpretation with SRTM data for helping the oil exploration: an example of Amazonas-Brazil sedimentary basin; Interpretacao morfoestrutural com dados SRTM no auxilio a exploracao petrolifera: um exemplo na bacia sedimentar do Amazonas

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Almeida-Filho, Raimundo; Ibanez, Delano M. [INPE, Sao Jose dos Campos, SP (Brazil)], E-mails: rai@ltid.inpe.br, dmi77@uol.com.br; Miranda, Fernando P. de [Petrobras-CENPES, Rio de Janeiro, RJ (Brazil)], E-mail: fmiranda@petrobras.com.br

2010-01-15

The availability of digital elevation models produced by the SRTM (Shuttle Radar Topographic Mission) opened new possibilities for studies of geological remote sensing in the Amazonia, since these models enhance subtle details of the terrain and drainage system, usually masked in conventional orbital images. Using as a case study an area located in the Amazonas sedimentary basin, this article discusses an approach to use these data as an aid to oil exploration in that region. The analysis of the drainage network automatically extracted from that product, combined with altitude information provided by the digital elevation model, revealed a number of drainage anomalies, which may indicate surface expression of buried geological features. One of these drainage anomalies is located exactly within the limits of the Azulao Gas Field, and may correspond to the surface expression of the hydrocarbon trapping structures in that area. The methodological approach discussed in this study can be replicated elsewhere in the Amazonas and Solimoes sedimentary basins, which together comprise about 1,000,000 km{sup 2} covered by rainforest. (author)

USO DE MODELOS DIGITAIS DE ELEVAÇÃO (MDE GERADOS A PARTIR DE IMAGENS DE RADAR INTERFEROMÉTRICO (SRTM NA ESTIMATIVA DE PERDAS DE SOLO

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Leonardo Franklin Fornelos

2007-12-01

Full Text Available Considering the advances in the generation of Remote Sensing products, this work proposes the utilization of DEM derived from Interferometric radar images (SRTM to generate one of the factors of USLE, the length-slope factor (LS. This factor considers the relation between the length of the hillside and its slope. Usually, it’s generated from the digitizing of topographic maps contours. The chosen area was Córrego Cachoeirinha watershed, located in the cities of Cáceres and Porto Estrela/MT. Maps of rainfall erosivity, soil erodibility, length-slope factor, land cover and conservation practices have been made. It generated two maps of LS factor, one from the hypsometry and another from the Digital Elevation Model (DEM obtained from the SRTM images. These maps were made and crossed in the software ArcGis, generating maps of soil losses, which were quantified and compared, according to the classification proposed by FAO, UNEP and UNESCO (1980. Analyzing the LS Maps, the model generated by SRTM showed larger details of the slope shape, that shows a bigger definition offered by that product and less time in the production of soil losses maps, since it avoids not only the job of the hypsometric digitizing, but also the DEM generation from the contours. This proposal of methodology changing aims the execution of environmental analyses in areas that do not own compatible systematic mappings up to 1:100.000 scale.

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

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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

Recent Elevation Changes on Bagley Ice Valley, Guyot and Yahtse Glaciers, Alaska, from ICESat Altimetry, Star-3i Airborne, and SRTM Spaceborne DEMs

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Muskett, R. R.; Sauber, J. M.; Lingle, C. S.; Rabus, B. T.; Tangborn, W. V.; Echelmeyer, K. A.

2005-12-01

Three- to 5-year surface elevation changes on Bagley Ice Valley, Guyot and Yahtse Glaciers, in the eastern Chugach and St. Elias Mtns of south-central Alaska, are estimated using ICESat-derived data and digital elevation models (DEMs) derived from interferometric synthetic aperture radar (InSAR) data. The surface elevations of these glaciers are influenced by climatic warming superimposed on surge dynamics (in the case of Bagley Ice Valley) and tidewater glacier dynamics (in the cases of Guyot and Yahtse Glaciers) in this coastal high-precipitation regime. Bagley Ice Valley / Bering Glacier last surged in 1993-95. Guyot and Yahtse Glaciers, as well as the nearby Tyndell Glacier, have experienced massive tidewater retreat during the past century, as well as during recent decades. The ICESat-derived elevation data we employ were acquired in early autumn in both 2003 and 2004. The NASA/NIMA Shuttle Radar Topography Mission (SRTM) DEM that we employ was derived from X-band InSAR data acquired during this 11-22 Feb. 2000 mission and processed by the German Aerospace Center. This DEM was corrected for estimated systematic error, and a mass balance model was employed to account for seasonal snow accumulation. The Star-3i airborne, X-band, InSAR-derived DEM that we employ was acquired 4-13 Sept. 2000 by Intermap Technologies, Inc., and was also processed by them. The ICESat-derived profiles crossing Bagley Ice Valley, differenced with Star-3i DEM elevations, indicate preliminary mean along-profile elevation increases of 5.6 ± 3.4 m at 1315 m altitude, 7.4 ± 2.7 m at 1448 m altitude, 4.7 ± 1.9 m at 1557 m altitude, 1.3 ± 1.4 m at 1774 m altitude, and 2.5 ± 1.5 m at 1781 m altitude. This is qualitatively consistent with the rising surface on Bagley Ice Valley observed by Muskett et al. [2003]. The ICESat-derived profiles crossing Yahtse Glacier, differenced with the SRTM DEM elevations, indicate preliminary mean elevation changes (negative implies decrease) of -0.9 ± 3

SRTM Colored Height and Shaded Relief: Corral de Piedra, Argentina

Science.gov (United States)

2001-01-01

Volcanism and erosion are prominently seen in this view of the eastern flank of the Andes Mountains taken by Shuttle Radar Topography Mission (SRTM). The area is southeast of San Martin de Los Andes, Argentina. Eroded peaks up to 2,210-meter-high (7,260-foot) are seen on the west (left), but much of the scene consists of lava plateaus that slope gently eastward. These lava flows were most likely derived from volcanic sources in the high mountains. However, younger and more localized volcanic activity is evident in the topographic data as a cone surrounding oval-shaped flow near the center of the scene.The plateaus are extensively eroded by the Rio Limay (bottom of the image) and the Rio Collon Cura and its tributaries (upper half). The larger stream channels have reached a stable level and are now cutting broad valleys. Few terraces between the levels of the high plateaus and lower valleys (bottom center and upper right of the volcanic cone) indicate that stream erosion had once temporarily reached a higher stable level before eroding down to its current level. In general, depositional surfaces like lava flows are progressively younger with increasing elevation, while erosional surfaces are progressively younger with decreasing elevation.Two visualization methods were combined to produce this image: shading and color coding of topographic height. The shade image was derived by computing topographic slope in the north-south direction. Northern slopes appear bright and southern slopes appear dark, as would be the case at noon at this latitude in the southern hemisphere. Color coding is directly related to topographic height, with green at the lower elevations, rising through yellow, red and magenta to white at the highest elevations.Elevation data used in this image was acquired by the Shuttle Radar Topography Mission (SRTM) aboard the Space Shuttle Endeavour, launched on February 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging

Digital Elevation Model (DEM) 24K

Data.gov (United States)

Kansas Data Access and Support Center — Digital Elevation Model (DEM) is the terminology adopted by the USGS to describe terrain elevation data sets in a digital raster form. The standard DEM consists of a...

SRTM Perspective View with Landsat Overlay: San Jose, Costa Rica

Science.gov (United States)

2001-01-01

This perspective view shows the capital city of San Jose, Costa Rica, in the right center of the image (gray area). Rising behind it are the volcanoes Irazu, 3402 meters high (11,161 feet) and Turrialba, 3330 meters high (10,925 feet.)Irazu is the highest volcano in Costa Rica and is located in the Irazu Volcano National Park, established in 1955. There have been at least 23 eruptions of Irazu since 1723, the most recent during 1963 to 1965. This activity sent tephra and secondary mudflows into cultivated areas, caused at least 40 deaths, and destroyed 400 houses and some factories.This image was generated in support of the Central American Commission for Environment and Development through an agreement with NASA. The Commission involves eight nations working to develop the Mesoamerican Biological Corridor, an effort to study and preserve some of the most biologically diverse regions of the planet.This three-dimensional perspective view was generated using topographic data from the Shuttle Radar Topography Mission (SRTM) and an enhanced false-color Landsat 7 satellite image. Colors are from Landsat bands 5, 4, and 2 as red, green and blue, respectively. Topographic expression is exaggerated 2X.Landsat has been providing visible and infrared views of the Earth since 1972. SRTM elevation data matches the 30-meter resolution of most Landsat images and will substantially help in analyses of the large and growing Landsat image archive. The Landsat 7 Thematic Mapper image used here was provided to the SRTM by the United States Geological Survey, Earth Resources Observation Systems (EROS) Data Center, Sioux Falls, South Dakota.Elevation data used in this image was acquired by the Shuttle Radar Topography Mission (SRTM) aboard the Space Shuttle Endeavour, launched on February 11,2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space Shuttle Endeavour in 1994. SRTM

SRTM Stereo Pair: Fiji Islands

Science.gov (United States)

2000-01-01

The Sovereign Democratic Republic of the Fiji Islands, commonly known as Fiji, is an independent nation consisting of some 332 islands surrounding the Koro Sea in the South Pacific Ocean. This topographic image shows Viti Levu, the largest island in the group. With an area of 10,429 square kilometers (about 4000 square miles), it comprises more than half the area of the Fiji Islands. Suva, the capital city, lies on the southeast shore. The Nakauvadra, the rugged mountain range running from north to south, has several peaks rising above 900 meters (about 3000 feet). Mount Tomanivi, in the upper center, is the highest peak at 1324 meters (4341 feet). The distinct circular feature on the north shore is the Tavua Caldera, the remnant of a large shield volcano that was active about 4 million years ago. Gold has been mined on the margin of the caldera since the 1930s. The Nadrau plateau is the low relief highland in the center of the mountain range. The coastal plains in the west, northwest and southeast account for only 15 percent of Viti Levu's area but are the main centers of agriculture and settlement.This stereoscopic view was generated using preliminary topographic data from the Shuttle Radar Topography Mission. A computer-generated artificial light source illuminates the elevation data from the top (north) to produce a pattern of light and shadows. Slopes facing the light appear bright, while those facing away are shaded. Also, colors show the elevation as measured by SRTM. Colors range from green at the lowest elevations to pink at the highest elevations. This image contains about 1300 meters (4300 feet) of total relief. The stereoscopic effect was created by first draping the shading and colors back over the topographic data and then generating two differing perspectives, one for each eye. The 3-D perception is achieved by viewing the left image with the right eye and the right image with the left eye (cross-eyed viewing), or by downloading and printing the

SRTM Colored Height and Shaded Relief: Laguna Mellquina, Andes Mountains, Argentina

Science.gov (United States)

2001-01-01

This depiction of an area south of San Martin de Los Andes, Argentina, is the first Shuttle Radar Topography Mission (SRTM) view of the Andes Mountains, the tallest mountain chain in the western hemisphere. This particular site does not include the higher Andes peaks, but it does include steep-sided valleys and other distinctive landforms carved by Pleistocene glaciers. Elevations here range from about 700 to 2,440 meters(2,300 to 8,000 feet). This region is very active tectonically and volcanically, and the landforms provide a record of the changes that have occurred over many thousands of years. Large lakes fill the broad mountain valleys, and the spectacular scenery here makes this area a popular resort destination for Argentinians.Two visualization methods were combined to produce this image: shading and color coding of topographic height. The shade image was derived by computing topographic slope in the north-south direction. Northern slopes appear bright and southern slopes appear dark, as would be the case at noon at this latitude in the southern hemisphere. Color coding is directly related to topographic height, with green at the lower elevations, rising through yellow, red, and magenta, to white at the highest elevations.Elevation data used in this image was acquired by the Shuttle Radar Topography Mission aboard Space Shuttle Endeavour, launched on February 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR)that flew twice on the Space Shuttle Endeavour in 1994. SRTM was designed to collect three-dimensional measurements of the Earth's surface. To collect the 3-D data, engineers added a 60-meter-long (200-foot) mast, installed additional C-band and X-band antennas, and improved tracking and navigation devices. The mission is a cooperative project between the National Aeronautics and Space Administration (NASA), the National Imagery and Mapping Agency (NIMA) of the U

Estimating Error in SRTM Derived Planform of a River in Data-poor Region and Subsequent Impact on Inundation Modeling

Science.gov (United States)

Bhuyian, M. N. M.; Kalyanapu, A. J.

2017-12-01

Accurate representation of river planform is critical for hydrodynamic modeling. Digital elevation models (DEM) often falls short in accurately representing river planform because they show the ground as it was during data acquisition. But, water bodies (i.e. rivers) change their size and shape over time. River planforms are more dynamic in undisturbed riverine systems (mostly located in data-poor regions) where remote sensing is the most convenient source of data. For many of such regions, Shuttle Radar Topographic Mission (SRTM) is the best available source of DEM. Therefore, the objective of this study is to estimate the error in SRTM derived planform of a river in a data-poor region and estimate the subsequent impact on inundation modeling. Analysis of Landsat image, SRTM DEM and remotely sensed soil data was used to classify the planform activity in an 185 km stretch of the Kushiyara River in Bangladesh. In last 15 years, the river eroded about 4.65 square km and deposited 7.55 square km area. Therefore, current (the year 2017) river planform is significantly different than the SRTM water body data which represents the time of SRTM data acquisition (the year 2000). The rate of planform shifting significantly increased as the river traveled to downstream. Therefore, the study area was divided into three reaches (R1, R2, and R3) from upstream to downstream. Channel slope and meandering ratio changed from 2x10-7 and 1.64 in R1 to 1x10-4 and 1.45 in R3. However, more than 60% erosion-deposition occurred in R3 where a high percentage of Fluvisols (98%) and coarse particles (21%) were present in the vicinity of the river. It indicates errors in SRTM water body data (due to planform shifting) could be correlated with the physical properties (i.e. slope, soil type, meandering ratio etc.) of the riverine system. The correlations would help in zoning activity of a riverine system and determine a timeline to update DEM for a given region. Additionally, to estimate the

Uncertainties in the Shuttle Radar Topography Mission (SRTM) Heights: Insights from the Indian Himalaya and Peninsula.

Science.gov (United States)

Mukul, Manas; Srivastava, Vinee; Jade, Sridevi; Mukul, Malay

2017-02-08

The Shuttle Radar Topography Mission (SRTM) Digital Terrain Elevation Data (DTED) are used with the consensus view that it has a minimum vertical accuracy of 16 m absolute error at 90% confidence (Root Mean Square Error (RMSE) of 9.73 m) world-wide. However, vertical accuracy of the data decreases with increase in slope and elevation due to presence of large outliers and voids. Therefore, studies using SRTM data "as is", especially in regions like the Himalaya, are not statistically meaningful. New data from ~200 high-precision static Global Position System (GPS) Independent Check Points (ICPs) in the Himalaya and Peninsular India indicate that only 1-arc X-Band data are usable "as is" in the Himalaya as it has height accuracy of 9.18 m (RMSE). In contrast, recently released (2014-2015) "as-is" 1-arc and widely used 3-arc C-Band data have a height accuracy of RMSE 23.53 m and 47.24 m and need to be corrected before use. Outlier and void filtering improves the height accuracy to RMSE 8 m, 10.14 m, 14.38 m for 1-arc X and C-Band and 3-arc C-Band data respectively. Our study indicates that the C-Band 90 m and 30 m DEMs are well-aligned and without any significant horizontal offset implying that area and length computations using both the datasets have identical values.

Davenport Ranges, Northern Territory, Australia, SRTM Shaded Relief and Colored Height

Science.gov (United States)

2005-01-01

The Davenport Ranges of central Australia have been inferred to be among the oldest persisting landforms on Earth, founded on the belief that the interior of Australia has been tectonically stable for at least 700 million years. New rock age dating techniques indicate that substantial erosion has probably occurred over that time period and that the landforms are not nearly that old, but landscape evolution certainly occurs much slower here (at least now) than is typical across Earth's surface. Regardless of their antiquity, the Davenport Ranges exhibit a striking landform pattern as shown in this display of elevation data from the Shuttle Radar Topography Mission (SRTM). Quartzites and other erosion resistant strata form ridges within anticlinal (arched up) and synclinal (arched down) ovals and zigzags. These structures, if not the landforms, likely date back at least hundreds of millions of years, to a time when tectonic forces were active. Maximum local relief is only about 60 meters (about 200 feet), which is enough to contrast greatly with the extremely low relief surrounding terrain. Two visualization methods were combined to produce this image: shading and color coding of topographic height. The shade image was derived by computing topographic slope in the northeast-southwest (image top to bottom) direction, so that northeast slopes appear bright and southwest slopes appear dark. Color coding is directly related to topographic height, with green at the lower elevations, rising through yellow and tan, to white at the highest elevations. Elevation data used in this image were acquired by the Shuttle Radar Topography Mission aboard the Space Shuttle Endeavour, launched on Feb. 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space Shuttle Endeavour in 1994. SRTM was designed to collect 3-D measurements of the Earth's surface. To collect the 3-D data

VALIDATION OF THE ASTER GLOBAL DIGITAL ELEVATION MODEL VERSION 3 OVER THE CONTERMINOUS UNITED STATES

Directory of Open Access Journals (Sweden)

D. Gesch

2016-06-01

Full Text Available 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

Science.gov (United States)

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.

Nabro and Mallahle Volcanoes, Eritrea and Ethiopia, SRTM Colored Height and Shaded Relief

Science.gov (United States)

2004-01-01

The area known as the Afar Triangle is located at the northern end of the East Africa Rift, where it approaches the southeastern end of the Red Sea and the southwestern end of the Gulf of Aden. The East African Rift, the Red Sea, and the Gulf of Aden are all zones where Earth's crust is pulling apart in a process known as crustal spreading. Their three-way meeting is known as a triple junction, and their spreading creates a triangular topographic depression for which the area was named.Not surprisingly, the topographic effects of crustal spreading are more dramatic in the Afar Triangle than anywhere else upon Earth's landmasses. The spreading is primarily evident as patterns of numerous tension cracks. But some of these cracks provide conduits for magma to rise to the surface to form volcanoes.Shown here are a few of the volcanoes of the Afar Triangle. The larger two are Nabro Volcano (upper right, in Eritrea) and Mallahle Volcano (lower left, in Ethiopia). Nabro Volcano shows clear evidence of multiple episodes of activity that resulted in a crater in a crater in a crater. Many volcanoes in this area are active, including one nearby that last erupted in 1990.This image was created directly from an SRTM elevation model. A shade image was derived by computing topographic slope in the north-south direction. Northern slopes appear bright and southern slopes appear dark. The shade image was then combined with a color coding of topographic height, with green at the lower elevations, rising through yellow, orange, and red, up to purple at the highest elevations.Elevation data used in this image was acquired by the Shuttle Radar Topography Mission (SRTM) aboard the Space Shuttle Endeavour, launched on February 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space Shuttle Endeavour in 1994. SRTM was designed to collect three-dimensional measurements of the Earth

Hydraulic correction method (HCM) to enhance the efficiency of SRTM DEM in flood modeling

Science.gov (United States)

Chen, Huili; Liang, Qiuhua; Liu, Yong; Xie, Shuguang

2018-04-01

Digital Elevation Model (DEM) is one of the most important controlling factors determining the simulation accuracy of hydraulic models. However, the currently available global topographic data is confronted with limitations for application in 2-D hydraulic modeling, mainly due to the existence of vegetation bias, random errors and insufficient spatial resolution. A hydraulic correction method (HCM) for the SRTM DEM is proposed in this study to improve modeling accuracy. Firstly, we employ the global vegetation corrected DEM (i.e. Bare-Earth DEM), developed from the SRTM DEM to include both vegetation height and SRTM vegetation signal. Then, a newly released DEM, removing both vegetation bias and random errors (i.e. Multi-Error Removed DEM), is employed to overcome the limitation of height errors. Last, an approach to correct the Multi-Error Removed DEM is presented to account for the insufficiency of spatial resolution, ensuring flow connectivity of the river networks. The approach involves: (a) extracting river networks from the Multi-Error Removed DEM using an automated algorithm in ArcGIS; (b) correcting the location and layout of extracted streams with the aid of Google Earth platform and Remote Sensing imagery; and (c) removing the positive biases of the raised segment in the river networks based on bed slope to generate the hydraulically corrected DEM. The proposed HCM utilizes easily available data and tools to improve the flow connectivity of river networks without manual adjustment. To demonstrate the advantages of HCM, an extreme flood event in Huifa River Basin (China) is simulated on the original DEM, Bare-Earth DEM, Multi-Error removed DEM, and hydraulically corrected DEM using an integrated hydrologic-hydraulic model. A comparative analysis is subsequently performed to assess the simulation accuracy and performance of four different DEMs and favorable results have been obtained on the corrected DEM.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

SRTM Perspective View with Landsat Overlay: Costa Rica Coastal Plain

Science.gov (United States)

2001-01-01

This perspective view shows the northern coastal plain of Costa Rica with the Cordillera Central, composed of a number of active and dormant volcanoes, rising in the background. This view looks toward the south over the Rio San Juan, which marks the boundary between Costa Rica and Nicaragua. The smaller river joining Rio San Juan in the center of the image is Rio Sarapiqui, which is navigable upstream as far inland as Puerto Viejo (Old Port) de Sarapiqui at the mountain's base. This river was an important transportation route for those few hardy settlers who first moved into this region, although as recently as 1953 a mere three thatched-roof houses were all that comprised the village of Puerto Viejo.This coastal plain is a sedimentary basin formed about 50 million years ago composed of river alluvium and lahar (mud and ash flow) deposits from the volcanoes of the Cordillera Central. It comprises the province of Heredia (the smallest of Costa Rica's seven) and demonstrates a wide range of climatic conditions, from warm and humid lowlands to cool and damp highlands, and including the mild but seasonally wet and dry Central Valley.This image was generated in support of the Central American Commission for Environment and Development through an agreement with NASA. The Commission involves eight nations working to develop the Mesoamerican Biological Corridor, an effort to study and preserve some of the most biologically diverse regions of the planet.This three-dimensional perspective view was generated using topographic data from the Shuttle Radar Topography Mission (SRTM) and an enhanced false-color Landsat 7 satellite image. Colors are from Landsat bands 5, 4, and 2 as red, green and blue, respectively. Topographic expression is exaggerated 2X.Landsat has been providing visible and infrared views of the Earth since 1972. SRTM elevation data matches the 30-meter resolution of most Landsat images and will substantially help in analyses of the large and growing Landsat

SRTM Colored Height and Shaded Relief: Lava plateaus in Argentina

Science.gov (United States)

2001-01-01

All of the major landforms relate to volcanism and/or erosion in this Shuttle Radar Topography Mission scene of Patagonia, near La Esperanza, Argentina. The two prominent plateaus once formed a continuous surface that extended over much of this region. Younger volcanoes have grown through and atop the plateau, and one just south of this scene has sent a long, narrow flow down a stream channel (lower left). The topographic pattern shows that streams dominate the erosion processes in this arid environment even though wind is known to move substantial amounts of sediment here.Two visualization methods were combined to produce this image: shading and color coding of topographic height. The shade image was derived by computing topographic slope in the north-south direction. Northern slopes appear bright and southern slopes appear dark, as would be the case at noon at this latitude in the southern hemisphere. Color-coding is directly related to topographic height, with green at the lower elevations, rising through yellow, red, and magenta, to white at the highest elevations.Elevation data used in this image was acquired by the Shuttle Radar Topography Mission aboard the Space Shuttle Endeavour, launched on February 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space Shuttle Endeavour in 1994. SRTM was designed to collect three-dimensional measurements of the Earth's surface. To collect the 3-D data, engineers added a 60-meter-long (200-foot) mast, installed additional C-band and X-band antennas, and improved tracking and navigation devices. The mission is a cooperative project between NASA, the National Imagery and Mapping Agency (NIMA) of the U.S. Department of Defense, and the German and Italian space agencies. It is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Earth Science Enterprise, Washington, DC.Size: 62.4 by 88.8 kilometers

Assessment of the relationships between morphometric characteristics of relief with quantitative and qualitative characteristics of forests using ASTER and SRTM digital terrain models

Directory of Open Access Journals (Sweden)

D. M. Chernikhovsky

2017-06-01

Full Text Available In the article are shown results of assessment of relationships between quantitative and qualitative characteristics of forests and morphometric characteristics of relief on an example model plot in Nanayskoe forest district of Khabarovsk Territory. The relevance of the investigation is connected with need for improvement of the system of forest evaluation operations in the Russian Federation, including with use of the landscape approach. The tasks of the investigation were assessment of relationships between characteristics of relief and characteristics of forest vegetation cover on different levels of forest management; evaluation of morphometric characteristics of relief are important for structure and productivity of forests; comparison of the results obtained through the use of digital terrain models ASTER and SRTM. Geoinformatic projects were formed for a model plot on the basis of digital terrain models and data of forest mensuration and State (National Forest Inventory. On the basis of the developed method with use geoinformatic technologies were estimated morphometric characteristics of relief (average height, standard deviation of height, entropy, exposition and gradient of slopes, indexes of ruggedness and roughness, quantitative and qualitative characteristics of forests. The multifactor regression analysis, where characteristics of forests (as dependent variables and morphometric characteristics of relief (as independent variables were used, have been done. As a result of research, the set of morphometric characteristics of relief able to influence to variability of quantitative and qualitative characteristics of forests was identified. The set of linear regression equations able to explain 30–50 % of variability of dependent variables was obtained. The regression equations, obtained on base of digital terrain models ASTER and SRTM, comparable to each other in strength of relations (coefficients of determination, but includes the

SRTM Perspective of Colored Height and Shaded Relief Laguna Mellquina, Andes Mountains, Argentina

Science.gov (United States)

2001-01-01

This depiction of an area south of San Martin de Los Andes, Argentina, is the first Shuttle Radar Topography Mission (SRTM)view of the Andes Mountains, the tallest mountain chain in the western hemisphere. This particular site does not include the higher Andes peaks, but it does include steep-sided valleys and other distinctive landforms carved by Pleistocene glaciers. Elevations here range from about 700 to 2,440 meters (2,300 to 8,000 feet). This region is very active tectonically and volcanically, and the landforms provide a record of the changes that have occurred over many thousands of years. Large lakes fill the broad mountain valleys, and the spectacular scenery here makes this area a popular resort destination for Argentinians.Three visualization methods were combined to produce this image: shading, color coding of topographic height and a perspective view. The shade image was derived by computing topographic slope in the north-south direction. Northern slopes appear bright and southern slopes appear dark, as would be the case at noon at this latitude in the southern hemisphere. Color coding is directly related to topographic height, with green at the lower elevations, rising through yellow, red, and magenta, to white at the highest elevations. The perspective is toward the west, 20 degrees off horizontal with 2X vertical exaggeration. The back (west) edge of the data set forms a false skyline within the Andes Range.Elevation data used in this image was acquired by the Shuttle Radar Topography Mission aboard Space Shuttle Endeavour, launched on February 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on Space Shuttle Endeavour in 1994. SRTM was designed to collect three-dimensional measurements of Earth's surface. To collect the 3-D data, engineers added a 60-meter-long (200-foot) mast, installed additional C-band and X-band antennas, and improved

The elevation and its distribution in geomorphological regions of the European Russia

Science.gov (United States)

Kharchenko, S. V.; Ermolaev, O. P.; Mukharamova, S. S.

2018-01-01

Spatial differences of elevation were analysed by side of view of geomorphological boundaries on the European Russia territory. Geomorphological pattern of the studied territory was taken from Geomorphological Map of the USSR at scale of 1: 2 500 000. There 2401 fragments for combinations of 58 types of structural landforms and 22 types of sculptural landforms were allocated. The elevation values computed by digital elevation model (cell size - 200 m, number of cells - 322M) based on SRTM (south of 60 nl.) and GDEM 2010 (north of 60 nl.) resampled data. It was founded that some types of structural (16 types) and sculptural (6 types) landforms located in the relatively thin intervals of elevation. Using of elevation above sea level is needed for effective automatic recognizing these landform regions.

Height and Biomass of Mangroves in Africa from ICEsat/GLAS and SRTM

Science.gov (United States)

Fatoyinbo, Temilola E.; Simard, Marc

2012-01-01

The accurate quantification of forest 3-D structure is of great importance for studies of the global carbon cycle and biodiversity. These studies are especially relevant in Africa, where deforestation rates are high and the lack of background data is great. Mangrove forests are ecologically significant and it is important to measure mangrove canopy heights and biomass. The objectives of this study are to estimate: 1. The total area, 2. Canopy height distributions and 3. Aboveground biomass of mangrove forests in Africa. To derive mangrove 3-D structure and biomass maps, we used a combination of mangrove maps derived from Landsat ETM+, LiDAR canopy height estimates from ICEsat/GLAS (Ice, Cloud, and land Elevation Satellite/Geoscience Laser Altimeter System) and elevation data from SRTM (Shuttle Radar Topography Mission) for the African continent. More specifically, we extracted mangrove forest areas on the SRTM DEM using Landsat based landcover maps. The LiDAR (Light Detection and Ranging) measurements from the large footprint GLAS sensor were used to derive local estimates of canopy height and calibrate the Interferometric Synthetic Aperture Radar (InSAR) data from SRTM. We then applied allometric equations relating canopy height to biomass in order to estimate above ground biomass (AGB) from the canopy height product. The total mangrove area of Africa was estimated to be 25 960 square kilometers with 83% accuracy. The largest mangrove areas and greatest total biomass was 29 found in Nigeria covering 8 573 km2 with 132 x10(exp 6) Mg AGB. Canopy height across Africa was estimated with an overall root mean square error of 3.55 m. This error also includes the impact of using sensors with different resolutions and geolocation error which make comparison between measurements sensitive to canopy heterogeneities. This study provides the first systematic estimates of mangrove area, height and biomass in Africa. Our results showed that the combination of ICEsat/GLAS and

Avaliação de modelos digitais de elevação para aplicação em um mapeamento digital de solos Evaluation of digital elevation models for application in a digital soil mapping

Directory of Open Access Journals (Sweden)

César S. Chagas

2010-02-01

Full Text Available No Brasil, normalmente os modelos digitais de elevação (MDEs são produzidos pelos próprios usuários e pouca atenção tem sido dada às suas limitações, como fonte de informação espacial. Este estudo propôs avaliar diferentes MDEs para subsidiar a escolha do modelo apropriado para derivar atributos topográficos utilizados em um mapeamento digital de solos, por redes neurais artificiais. A avaliação constou da determinação da raiz quadrada do erro médio quadrático da elevação (RMSE; análise das depressões espúrias; comparação entre drenagem mapeada e drenagem numérica, curvas de nível derivadas e curvas de nível originais, e análise das bacias de contribuição derivadas. Os resultados obtidos demonstraram que apenas o RMSE não foi suficiente para avaliar a qualidade desses modelos. O MDE, derivado de curvas de nível (CARTA, obtido com a utilização do módulo TOPOGRID apresentou qualidade superior aos MDEs derivados de sensores remotos (ASTER e SRTM. A análise qualitativa também identificou que o MDE CARTA é superior aos demais, pois estes apresentaram grande quantidade de erros que podem comprometer o estabelecimento das relações entre atributos do terreno e as condições locais de solos.In Brazil, the digital elevation models (DEMs are usually produced by users themselves and little attention has been given to their limitations as source of spatial information. The objective of this study was to evaluate different DEMs to help in choosing an appropriate model to derive topographical attributes used in a digital soil mapping based on a neural networks approach. The evaluation consisted of the following analysis: determination of root mean square error (RMSE of elevation; analysis of the spurious depressions; comparison between mapped drainage and numeric drainage and between derived contour lines and original contour lines; and analysis of the derived contribution basins. The results demonstrated that RMSE

Elements of the Chicxulub Impact Structure as revealed in SRTM and surface GPS topographic data

Science.gov (United States)

Kobrick, M.; Kinsland, G. L.; Sanchez, G.; Cardador, M. H.

2003-04-01

Pope et al have utilized elevations from the Petroleos Mexicanos (PEMEX) gravity data files to show that the main component of the surface expression of the Chicxu-lub Impact Structure is a roughly semi-circular, low-relief depression about 90 km in diameter. They also identified other topographic features and the elements of the buried impact which possibly led to the development of these features. Kinsland et al presented a connection between these topographic anomalies, small gravity anomalies and buried structure of the impact. Shaded relief images from recently acquired SRTM elevation data clearly show the circular depression of the crater and the moat/cenote ring. In addition we can readily identify Inner trough 1, Inner trough 2 and Outer trough as defined by Pope et al. The agreement between the topographic maps of Pope et al, Kinsland et al and SRTM data are remarkable considering that the distribution and types of data in the sets are so different. We also have ground topographic data collected with a special "autonomous differ-ential GPS" system during summer 2002. Profiles from these data generally agree with both the gravity data based topographic maps and profiles extracted from the SRTM data. Preliminary analyses of our new data, SRTM and GPS, have uncovered features not previously recognized: 1) as shown by the GPS data the moat/cenote ring consists of two distinct depressions separated by about 10 km...perhaps separate ring faults, 2) in the SRTM data over the southern part of the crater and on southward for perhaps 20 km beyond the moat/ cenote ring there exists a pattern, as yet unexplained, of roughly concentric topographic features whose center lies at about 21deg 40min N and 89deg 25min W, about 50km NNE of the moat/cenote ring center. The corroboration and better definition of the previously recognized topographic features yielded by the two new forms of data strengthens the cases for these fea-tures and for their relevance to the underlying

Elements of the Chicxulub Impact Structure as Revealed in SRTM and Surface GPS Topographic Data

Science.gov (United States)

Kinsland, Gary L.; Sanchez, Gary; Kobrick, Michael; Cardador, Manuel Hurtado

2003-01-01

Pope et al. [1] utilized the elevations from the Petroleos Mexicanos (PEMEX) gravity data files to show that the main component of the surface expression of the Chicxulub Impact Structure is a roughly semi-circular, lowrelief depression about 90 km in diameter. They also identified other topographic features and the elements of the buried impact, which possibly led to the development of these features. These are summarized in Table 1. Kinsland et al. [2] presented a connection between these topographic anomalies, small gravity anomalies and buried structure of the impact. Very recently we have acquired digital topography data from NASA s Shuttle Radar Topography Mission (SRTM). Our subset covers 6 square degrees from 20deg N 91degW to 22deg N 88degW (corner to corner) with a pixel size of about 90m. This area includes all of the identified portion of the crater on land.

Coastal Digital Elevation Models (DEMs)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Digital elevation models (DEMs) of U.S. and other coasts that typically integrate ocean bathymetry and land topography. The DEMs support NOAA's mission to understand...

Galveston, Texas Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Savannah, Georgia Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Biloxi, Mississippi Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Puerto Rico Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Hilo, Hawaii Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Hanalei, Hawaii Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Taholah, Washington Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Chignik, Alaska Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Monterey, California Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Garibaldi, Oregon Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Keauhou, Hawaii Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Atka, Alaska Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Lahaina, Hawaii Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Kawaihae, Hawaii Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Nikolski, Alaska Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Shemya, Alaska Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Portland, Maine Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Craig, Alaska Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Midway Atoll Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Adak, Alaska Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Cordova, Alaska Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Nantucket, Massachusetts Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Oahu, Hawaii Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Central Oregon Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

CREATING DIGITAL ELEVATION MODEL USING A MOBILE DEVICE

Directory of Open Access Journals (Sweden)

A. İ. Durmaz

2017-11-01

Full Text Available 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.

Southeast Alaska Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

Tatitlek, Alaska Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

Hoonah, Alaska Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

Whittier, Alaska Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

Gustavus, Alaska Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

Chenega, Alaska Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

Juneau, Alaska Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

Mariana Trench Bathymetric Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) created a bathymetric digital elevation model (DEM) for the Mariana Trench and adjacent seafloor in the Western...

Unalaska, Alaska Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

Tanzania Elevation and Surface Characteristics

Data.gov (United States)

US Agency for International Development — The dataset displays Elevation, Slope, Aspect, Topographic Position Index, Terrain Ruggedness, and Roughness based on Shuttle Radar Topography Mission (SRTM) (3...

Bora Bora, Tahaa, and Raiatea, French Polynesia, Landsat and SIR-C Images Compared to SRTM Shaded

Science.gov (United States)

2005-01-01

Bora Bora, Tahaa, and Raiatea (top to bottom) are Polynesian Islands about 220 kilometers (135 miles) west-northwest of Tahiti in the South Pacific. Each of the islands is surrounded by a coral reef and its associated islets ('motus') that enclose a lagoon. Actually, as seen here, Tahaa and Raiatea are close enough together to share a common lagoon and reef. These islands are volcanic in origin and were built up from the sea floor by lava extrusions millions of years ago. None is now active, and all are deeply eroded. This display compares three differing 'views from space' of these islands. On the left, an image from the Landsat 7 satellite shows the islands as they might have appeared to an astronaut in orbit in 1999 (but a little sharper and with atmospheric haze suppressed). In the middle is an image created from data gathered by the third-generation Shuttle Imaging Radar (SIR-C), flown in 1994. On the right is a graphic illustrating elevation data gathered by the Shuttle Radar Topography Mission (SRTM) in 2000. Each of these images shows very different information as compared to the other two. Landsat sees clouds, which are almost always above these islands, blocking the view of the terrain. It also readily sees through shallow water down to the reefs. SIR-C sees the waves and other effects of winds upon the ocean surface. It does not look through water to see the reefs, but it clearly separates land and water. It also provides a bolder (but distorted) view of the islands' topographic patterns. With the ability of radar to see through clouds and provision of its own illumination, the SIR-C view is not limited by clouds nor their shadows. SRTM was designed to provide new information that is missing in the Landsat and SIR-C views. Specifically, SRTM created the world's first near-global, detailed elevation model. Natural topographic shading in Landsat imagery and radar topographic shadowing of SIR-C give some evidence of the shape of the ground but do not

ASTER Digital Elevation Model V003

Data.gov (United States)

National Aeronautics and Space Administration — The ASTER Digital Elevation Model (DEM) product is generated using bands 3N (nadir-viewing) and 3B (backward-viewing) of an ASTER Level-1A image acquired by the...

ASTER Global Digital Elevation Model V002

Data.gov (United States)

National Aeronautics and Space Administration — The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM) was developed jointly by the U.S. National...

Kachemak Bay, Alaska Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Virginia Beach, Virginia Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Santa Barbara, California Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Ocean City, Maryland Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

King Cove, Alaska Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Panama City, Florida Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Montauk, New York Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Sand Point, Alaska Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

La Push, Washington Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Arena Cove, California Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Port Orford, Oregon Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Arecibo, Puerto Rico Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Grenada Digital Elevation Model - 1 arc-second

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Guayama, Puerto Rico Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Fajardo, Puerto Rico Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Corpus Christi, Texas Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Dutch Harbor, Alaska Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Ponce, Puerto Rico Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Daytona Beach, Florida Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Port Alexander Alaska Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

New Orleans, Louisiana Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions in the Gulf of Mexico....

New Zealand, SRTM Shaded Relief and Colored Height

Science.gov (United States)

2004-01-01

with the offset in the subduction zone pattern, vertical offsets (about 7 millimeters per year) are likewise consistent with the uplift of the Southern Alps. Two visualization methods were combined to produce this image: shading and color coding of topographic height. The shade image was derived by computing topographic slope in the northwest-southeast direction, so that northwest slopes appear bright and southeast slopes appear dark. Color coding is directly related to topographic height, with green at the lower elevations, rising through yellow and tan, to white at the highest elevations. Elevation data used in this image were acquired by the Shuttle Radar Topography Mission aboard the Space Shuttle Endeavour, launched on Feb. 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space Shuttle Endeavour in 1994. SRTM was designed to collect 3-D measurements of the Earth's surface. To collect the 3-D data, engineers added a 60-meter (approximately 200-foot) mast, installed additional C-band and X-band antennas, and improved tracking and navigation devices. The mission is a cooperative project between NASA, the National Geospatial-Intelligence Agency (NGA) of the U.S. Department of Defense and the German and Italian space agencies. It is managed by NASA's Jet Propulsion Laboratory, Pasadena, Calif., for NASA's Earth Science Enterprise, Washington, D.C. Location: 33.5 to 48 degrees South latitude, 165 to 180 degrees East longitude Orientation: North toward the top, cylindrical projection Image Data: Shaded and colored SRTM elevation model Date Acquired: February 2000

SRTM Anaglyph: Fiji Islands

Science.gov (United States)

2000-01-01

The Sovereign Democratic Republic of the Fiji Islands, commonly known as Fiji, is an independent nation consisting of some 332 islands surrounding the Koro Sea in the South Pacific Ocean. This topographic image shows Viti Levu, the largest island in the group. With an area of 10,429 square kilometers (about 4000 square miles), it comprises more than half the area of the Fiji Islands. Suva, the capital city, lies on the southeast shore. The Nakauvadra, the rugged mountain range running from north to south, has several peaks rising above 900 meters (about 3000 feet). Mount Tomanivi, in the upper center, is the highest peak at 1324 meters (4341 feet). The distinct circular feature on the north shore is the Tavua Caldera, the remnant of a large shield volcano that was active about 4 million years ago. Gold has been mined on the margin of the caldera since the 1930s. The Nadrau plateau is the low relief highland in the center of the mountain range. The coastal plains in the west, northwest and southeast account for only 15 percent of Viti Levu's area but are the main centers of agriculture and settlement.This shaded relief anaglyph image was generated using preliminary topographic data from the Shuttle Radar Topography Mission. A computer-generated artificial light source illuminates the elevation data from the top (north) to produce a pattern of light and shadows. Slopes facing the light appear bright, while those facing away are shaded. The stereoscopic effect was created by first draping the shaded relief image back over the topographic data and then generating two differing perspectives, one for each eye. When viewed through special glasses, the result is a vertically exaggerated view of the Earth's surface in its full three dimensions. Anaglyph glasses cover the left eye with a red filter and cover the right eye with a blue filter.This image was acquired by SRTM aboard the Space Shuttle Endeavour, launched on February 11, 2000. SRTM used the same radar instrument

Digital Elevation Models (DEMs) for the main 8 Hawaiian Islands

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Digital elevation model (DEM) data are arrays of regularly spaced elevation values referenced horizontally either to a Universal Transverse Mercator (UTM) projection...

Digital elevation modeling via curvature interpolation for lidar data

Science.gov (United States)

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...

San Juan Islands, Washington Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

San Juan, Puerto Rico Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

U.S. Virgin Islands Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Cape Hatteras, North Carolina Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Sand Point, Alaska MHW Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Port San Luis, California Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Rarotonga 1 arc-second Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Eastern Canada Digital Elevation Model - 3 arc-second

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Central Oregon Coastal Digital Elevation Model NAVD 88

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Atlantic City, New Jersey Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Galapagos Islands, Ecuador 1 sec Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Galapagos Islands, Ecuador 3 sec Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

ASTER Orthorectified Digital Elevation Model (DEM) V003

Data.gov (United States)

National Aeronautics and Space Administration — The ASTER L3 DEM and Orthorectified Images form a multi-file product that contains both the Digital Elevation Model (DEM), and the Orthorectified Image products....

Mount Saint Helens, Washington, USA, SRTM Perspective: Shaded Relief and Colored Height

Science.gov (United States)

2004-01-01

geometry of the surface as it would be viewed on a clear day. Elevation data used in this image were acquired by the Shuttle Radar Topography Mission aboard the Space Shuttle Endeavour, launched on Feb. 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space Shuttle Endeavour in 1994. SRTM was designed to collect 3-D measurements of the Earth's surface. To collect the 3-D data, engineers added a 60-meter (approximately 200-foot) mast, installed additional C-band and X-band antennas, and improved tracking and navigation devices. The mission is a cooperative project between NASA, the National Geospatial-Intelligence Agency (NGA) of the U.S. Department of Defense and the German and Italian space agencies. It is managed by NASA's Jet Propulsion Laboratory, Pasadena, Calif., for NASA's NASA's Science Mission Directorate, Washington, D.C. Size: View distance about 150 km (about 100 miles) Location: 46.2 degrees North latitude, 122.2 degrees West longitude Orientation: View Southeast Image Data: Shaded and colored SRTM elevation model Date Acquired: February 2000

Minnesota Digital Elevation Model - Tiled 93 Meter Resolution

Data.gov (United States)

Minnesota Department of Natural Resources — Digital Elevation Model (DEM) at a resolution of 93 meters. Original data resolution was 3 arc seconds which corresponds (approximately) to a matrix of points at a...

Effects of External Digital Elevation Model Inaccuracy on StaMPS-PS Processing: A Case Study in Shenzhen, China

Directory of Open Access Journals (Sweden)

Yanan Du

2017-11-01

Full Text Available External Digital Elevation Models (DEMs with different resolutions and accuracies cause different topographic residuals in differential interferograms of Multi-temporal InSAR (MTInSAR, especially for the phase-based StaMPS-PS. The PS selection and deformation parameter estimation of StaMPS-PS are closely related to the spatially uncorrected error, which is directly affected by external DEMs. However, it is still far from clear how the high resolution and accurate external DEM affects the results of the StaMPS-PS (e.g., PS selection and deformation parameter calculation on different platforms (X band TerraSAR, C band ENVISAT ASAR and L band ALOS/PALSAR1. In this study, abundant synthetic tests are performed to assess the influences of external DEMs on parameter estimations, such as the mean deformation rate and the deformation time-series. Real SAR images, covering Shenzhen city in China, are also selected to analyze the PS selection and distribution as well as to validate the results of synthetic tests. The results show that the PS points selected by the 5 m TanDEM-X DEM are 10.32%, 4.25% and 0.34% more than those selected by the 30 m SRTM DEM at X, C and L bands SAR platforms, respectively, when a multi-look geocoding operation is adopted for X band in the SRTM DEM case. We also find that the influences of external DEMs on the mean deformation rate are not significant and are inversely proportional to the wavelength of the satellite platforms. The standard deviations of the mean deformation rate difference for the X, C and L bands are 0.54, 0.30 and 0.10 mm/year, respectively. Similarly, the influences of external DEMs on the deformation time-series estimation for the three platforms are also slight, except for local artifacts whose root-mean-square error (RMSE ≥ 6 mm. Based on these analyses, some implications and suggestions for external DEMs on StaMPS-PS processing are discussed and provided.

Determination of the hydrological properties of a small-scale catchment area in Northern Greece from ASTER and SRTM DEMs and accuracy assessment with a local DTM

Science.gov (United States)

Tzanou, E. A.; Vergos, G. S.

2012-04-01

The combined use of Geographic Information Systems and recent high-resolution Digital Elevation Models (DEMs) from Remote Sensing imagery offers a unique opportunity to study the hydrological properties of basin and catchment dynamics and derive the hydrological features of specific regions of various spatial scales. Until recently, the availability of global DEMs was restricted to low-resolution and accuracy models, e.g., ETOPO5, ETOPO2 and GTOPO30, compared to local Digital Terrain Models (DTMs) derived from photogrammetric methods and offered usually in the form of topographic maps of various scales. The advent of the SRTM and ASTER missions, offer some new tools and opportunities in order to use their data within a GIS to study the hydrological properties of basins and consequently validate their performance both amongst each other, as well as in terms of the results derived from a local DTM. The present work focuses on the use of the recent SRTM v2 90 m and ASTER v2 30 m DEMs along with the national 500 m DTM generated by the Hellenic Military Geographic Service (HMGS), within a GIS in order to assess their performance in determining the hydrological properties of basins. To this respect, the ArcHydro extension tool of ArcGIS v9.3 and HEC-GeoRAS v4.3 have been exploited to determine the hydrographic data of the basins under study which are located in Northern Greece. The hydrological characteristics refer to stream geometry, curve number, flooding areas, etc. as well as the topographic characteristics of the basin itself, such as aspect, hillshade, slope e.t.c..

Radarsat Antarctic Mapping Project Digital Elevation Model, Version 2

Data.gov (United States)

National Aeronautics and Space Administration — The high-resolution Radarsat Antarctic Mapping Project (RAMP) Digital Elevation Model (DEM) combines topographic data from a variety of sources to provide consistent...

Multi-decadal elevation changes on Bagley Ice Valley and Malaspina Glacier, Alaska

Science.gov (United States)

Muskett, Reginald R.; Lingle, Craig S.; Tangborn, Wendell V.; Rabus, Bernhard T.

2003-08-01

Digital elevation models (DEMs) of Bagley Ice Valley and Malaspina Glacier produced by (i) Intermap Technologies, Inc. (ITI) from airborne interferometric synthetic aperture radar (InSAR) data acquired 4-13 September 2000, (ii) the German Aerospace Center (DRL) from spaceborne InSAR data acquired by the Shuttle Radar Topography Mission (SRTM) 11-22 February 2000, and (iii) the US Geological Survey (USGS) from aerial photographs acquired in 1972/73, were differenced to estimate glacier surface elevation changes from 1972 to 2000. Spatially non-uniform thickening, 10 +/- 7 m on average, is observed on Bagley Ice Valley (accumulation area) while non-uniform thinning, 47 +/- 5 m on average, is observed on the glaciers of the Malaspina complex (mostly ablation area). Even larger thinning is observed on the retreating tidewater Tyndall Glacier. These changes have resulted from increased temperature and precipitation associated with climate warming, and rapid tidewater retreat.

Easter Island, Chile Digital Elevation Model 3 arc-second

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Chignik, Alaska 1 arc-second Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

Akutan, Alaska 8 Arc-second Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

Mobile, Alabama 1/3 MHW Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions in the Gulf of Mexico....

International Digital Elevation Model Service (IDEMS): A Revived IAG Service

Science.gov (United States)

Kelly, K. M.; Hirt, C., , Dr; Kuhn, M.; Barzaghi, R.

2017-12-01

A newly developed International Digital Elevation Model Service (IDEMS) is now available under the umbrella of the International Gravity Field Service of the International Association of Geodesy. Hosted and operated by Environmental Systems Research Institute (Esri) (http://www.esri.com/), the new IDEMS website is available at: https://idems.maps.arcgis.com/home/index.html. IDEMS provides a focus for distribution of data and information about various digital elevation models, including spherical-harmonic models of Earth's global topography and lunar and planetary DEM. Related datasets, such as representation of inland water within DEMs, and relevant software which are available in the public domain are also provided. Currently, IDEMS serves as repository of links to providers of global terrain and bathymetry, terrain related Earth models and datasets such as digital elevation data services managed and maintained by Esri (Terrain and TopoBathy), Bedmap2-Ice thickness and subglacial topographic model of Antarctica and Ice, Cloud, and Land Elevation ICESat/GLAS Data, as well as planetary terrain data provided by PDS Geosciences Node at Washington University, St. Louis. These services provide online access to a collection of multi-resolution and multi-source elevation and bathymetry data, including metadata and source information. In addition to IDEMS current holdings of terrestrial and planetary DEMs, some topography related products IDEMS may include in future are: dynamic ocean topography, 3D crustal density models, Earth's dynamic topography, etc. IDEMS may also consider terrain related products such as quality assessments, global terrain corrections, global height anomaly-to-geoid height corrections and other geodesy-relevant studies and products. IDEMS encourages contributions to the site from the geodetic community in any of the product types listed above. Please contact the authors if you would like to contribute or recommend content you think appropriate for

St. Croix, U.S. Virgin Islands Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Wake Island 3 Arc-second MHW Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Barkley Sound, Canada 1 arc-second Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Miami 1/3 arc-second MHW Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Midway Atoll 3 Arc-second MHW Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Society Islands, French Polynesia Digital Elevation Model - 3 arc-second

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Sitka, Alaska 3 Arc-second MHW Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Kodiak, Alaska 1/3 arc-second Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Central California 1 Arc-second MWH Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Akutan, Alaska 8/3 Arc-second Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

Nikolski, Alaska 1 arc-second MHHW Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

Yakutat, Alaska 8 Arc-second MHHW Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

King Cove, Alaska 8 arc-second Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

Akutan, Alaska 8/15 Arc-second Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

Chiniak, Alaska 8/15 arc-second Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

Cold Bay, Alaska 8 arc-second Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

Chignik, Alaska 1/3 arc-second Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

Implications of different digital elevation models and preprocessing techniques to delineate debris flow inundation hazard zones in El Salvador

Science.gov (United States)

Anderson, E. R.; Griffin, R.; Irwin, D.

2013-12-01

Heavy rains and steep, volcanic slopes in El Salvador cause numerous landslides every year, posing a persistent threat to the population, economy and environment. Although potential debris inundation hazard zones have been delineated using digital elevation models (DEMs), some disparities exist between the simulated zones and actual affected areas. Moreover, these hazard zones have only been identified for volcanic lahars and not the shallow landslides that occur nearly every year. This is despite the availability of tools to delineate a variety of landslide types (e.g., the USGS-developed LAHARZ software). Limitations in DEM spatial resolution, age of the data, and hydrological preprocessing techniques can contribute to inaccurate hazard zone definitions. This study investigates the impacts of using different elevation models and pit filling techniques in the final debris hazard zone delineations, in an effort to determine which combination of methods most closely agrees with observed landslide events. In particular, a national DEM digitized from topographic sheets from the 1970s and 1980s provide an elevation product at a 10 meter resolution. Both natural and anthropogenic modifications of the terrain limit the accuracy of current landslide hazard assessments derived from this source. Global products from the Shuttle Radar Topography Mission (SRTM) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global DEM (ASTER GDEM) offer more recent data but at the cost of spatial resolution. New data derived from the NASA Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) in 2013 provides the opportunity to update hazard zones at a higher spatial resolution (approximately 6 meters). Hydrological filling of sinks or pits for current hazard zone simulation has previously been achieved through ArcInfo spatial analyst. Such hydrological processing typically only fills pits and can lead to drastic modifications of original elevation values

A new method to obtain ground control points based on SRTM data

Science.gov (United States)

Wang, Pu; An, Wei; Deng, Xin-pu; Zhang, Xi

2013-09-01

The GCPs are widely used in remote sense image registration and geometric correction. Normally, the DRG and DOM are the major data source from which GCPs are extracted. But the high accuracy products of DRG and DOM are usually costly to obtain. Some of the production are free, yet without any guarantee. In order to balance the cost and the accuracy, the paper proposes a method of extracting the GCPs from SRTM data. The method consist of artificial assistance, binarization, data resample and reshape. With artificial assistance to find out which part of SRTM data could be used as GCPs, such as the islands or sharp coast line. By utilizing binarization algorithm , the shape information of the region is obtained while other information is excluded. Then the binary data is resampled to a suitable resolution required by specific application. At last, the data would be reshaped according to satellite imaging type to obtain the GCPs which could be used. There are three advantages of the method proposed in the paper. Firstly, the method is easy for implementation. Unlike the DRG data or DOM data that charges a lot, the SRTM data is totally free to access without any constricts. Secondly, the SRTM has a high accuracy about 90m that is promised by its producer, so the GCPs got from it can also obtain a high quality. Finally, given the SRTM data covers nearly all the land surface of earth between latitude -60° and latitude +60°, the GCPs which are produced by the method can cover most important regions of the world. The method which obtain GCPs from SRTM data can be used in meteorological satellite image or some situation alike, which have a relative low requirement about the accuracy. Through plenty of simulation test, the method is proved convenient and effective.

Northern Gulf 1 Arc-second MHW Coast Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions in the Gulf of Mexico....

Mobile, Alabama 1/3 NAVD 88 Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions in the Gulf of Mexico....

Accuracy analysis of SRTM usage for upper Citarum River flood modeling

Directory of Open Access Journals (Sweden)

Inanda Siregar Riza

2017-01-01

Full Text Available Natural channel cross section is generally very irregular and varied, for complex cross-sections and natural cross sections no specific formula presents to express the elements of the geometric cross section of the channel. The study uses HEC-Geo RAS with Arc GIS 10 and HEC-RAS 4.1.0 for modeling and 1D hydrodynamic. The surveyed cross sections modeling is calibrated and validated with observed daily discharge. Then the surveyed data cross sections are replaced by the cross sections extracted from SRTM. Accuracy is suitability between the surveyed data cross sections with data cross sections which extracted from SRTM. Accuracy is expressed by the magnitude of the error. The ratio of simulated discharges between two models by surveyed data cross sections and SRTM data cross sections have index of performance indicator for Nash–Sutcliffe Index (NI is 0.95 and index of Root Mean Square Error (RMSE is 0.41. Index of Performance indicator for comparison of simulated discharges between models with Nash–Sutcliffe Index (NI is 0.95 and index of Root Mean Square Error (RMSE is 0.41. The results show that cross sections from SRTM can be an alternative to extract data cross sections for Upper Citarum River flood modeling.

Tweed Extinct Volcano, Australia, Stereo Pair of SRTM Shaded Relief and Colored Height

Science.gov (United States)

2005-01-01

elevations. The stereoscopic effect was then created by generating two differing perspectives, one for each eye (see Figure 1). The image can be seen in 3-D by viewing the left image with the right eye and the right image with the left eye (cross-eyed viewing) or by downloading, printing, and splitting the image pair and viewing them with a stereoscope. When stereoscopically merged, the result is a vertically exaggerated view of Earth's surface in its full three dimensions. Elevations range from sea level (shown in blue) to about 1340 meters (4400 feet) along the northwest caldera rim. Elevation data used in this image were acquired by the Shuttle Radar Topography Mission aboard the Space Shuttle Endeavour, launched on Feb. 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space Shuttle Endeavour in 1994. SRTM was designed to collect 3-D measurements of the Earth's surface. To collect the 3-D data, engineers added a 60-meter (approximately 200-foot) mast, installed additional C-band and X-band antennas, and improved tracking and navigation devices. The mission is a cooperative project between NASA, the National Geospatial-Intelligence Agency (NGA) of the U.S. Department of Defense and the German and Italian space agencies. It is managed by NASA's Jet Propulsion Laboratory, Pasadena, Calif., for NASA's Earth Science Enterprise, Washington, D.C. Size: 102 kilometers (63 miles) by 74 kilometers (46 miles) Location: 28.4 degrees South latitude, 153.3 degrees East longitude Orientation: North toward the top, cylindrical projection Image Data: Shaded and colored SRTM elevation model Date Acquired: February 2000

TSUNAMI HAZARD IN NORTHERN VENEZUELA

Directory of Open Access Journals (Sweden)

B. Theilen-Willige

2006-01-01

Full Text Available Based on LANDSAT ETM and Digital Elevation Model (DEM data derived by the Shuttle Radar Topography Mission (SRTM, 2000 of the coastal areas of Northern Venezuela were investigated in order to detect traces of earlier tsunami events. Digital image processing methods used to enhance LANDSAT ETM imageries and to produce morphometric maps (such as hillshade, slope, minimum and maximum curvature maps based on the SRTM DEM data contribute to the detection of morphologic traces that might be related to catastrophic tsunami events. These maps combined with various geodata such as seismotectonic data in a GIS environment allow the delineation of coastal regions with potential tsunami risk. The LANDSAT ETM imageries merged with digitally processed and enhanced SRTM data clearly indicate areas that might be prone by flooding in case of catastrophic tsunami events.

St. Croix, U.S. Virgin Islands Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The 1/3 arc-second St. Croix, U.S. Virgin Islands Coastal Digital Elevation Model will be used to support NOAA's tsunami forecast system and for tsunami inundation...

Digital Elevation Model (DEM) file of topographic elevations for the Death Valley region of southern Nevada and southeastern California processed from US Geological Survey 1-degree Digital Elevation Model data files

International Nuclear Information System (INIS)

Turner, A.K.; D'Agnese, F.A.; Faunt, C.C.

1996-01-01

Elevation data have been compiled into a digital data base for an ∼100,000-km 2 area of the southern Great Basin, the Death Valley region of southern Nevada, and SE Calif., located between lat 35 degree N, long 115 degree W, and lat 38 degree N, long 118 degree W. This region includes the Nevada Test Site, Yucca Mountain, and adjacent parts of southern Nevada and eastern California and encompasses the Death Valley regional ground-water system. Because digital maps are often useful for applications other than that for which they were originally intended, and because the area corresponds to a region under continuing investigation by several groups, these digital files are being released by USGS

Accuracy Assessment of Different Digital Surface Models

Directory of Open Access Journals (Sweden)

Ugur Alganci

2018-03-01

Full Text Available Digital elevation models (DEMs, which can occur in the form of digital surface models (DSMs or digital terrain models (DTMs, are widely used as important geospatial information sources for various remote sensing applications, including the precise orthorectification of high-resolution satellite images, 3D spatial analyses, multi-criteria decision support systems, and deformation monitoring. The accuracy of DEMs has direct impacts on specific calculations and process chains; therefore, it is important to select the most appropriate DEM by considering the aim, accuracy requirement, and scale of each study. In this research, DSMs obtained from a variety of satellite sensors were compared to analyze their accuracy and performance. For this purpose, freely available Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER 30 m, Shuttle Radar Topography Mission (SRTM 30 m, and Advanced Land Observing Satellite (ALOS 30 m resolution DSM data were obtained. Additionally, 3 m and 1 m resolution DSMs were produced from tri-stereo images from the SPOT 6 and Pleiades high-resolution (PHR 1A satellites, respectively. Elevation reference data provided by the General Command of Mapping, the national mapping agency of Turkey—produced from 30 cm spatial resolution stereo aerial photos, with a 5 m grid spacing and ±3 m or better overall vertical accuracy at the 90% confidence interval (CI—were used to perform accuracy assessments. Gross errors and water surfaces were removed from the reference DSM. The relative accuracies of the different DSMs were tested using a different number of checkpoints determined by different methods. In the first method, 25 checkpoints were selected from bare lands to evaluate the accuracies of the DSMs on terrain surfaces. In the second method, 1000 randomly selected checkpoints were used to evaluate the methods’ accuracies for the whole study area. In addition to the control point approach, vertical cross

Geomorphic Proxies to Test Strain Accommodation in Southwestern Puerto Rico from Digital Elevation Models

Science.gov (United States)

Barrios Galindez, I. M.; Xue, L.; Laó-Dávila, D. A.

2017-12-01

The Puerto Rico and the Virgin Island microplate is located in at the northeastern corner of the Caribbean plate boundary with North America is placed within an oblique subduction zone in which strain patterns remain unresolved. Seismic hazard is a major concern in the region as seen from the seismic history of the Caribbean-North America plate boundary zone. Most of the tectonic models of the microplate show the accommodation of strain occurring offshore, despite evidence from seismic activity, trench studies, and geodetic studies suggesting the existence of strain accomodation in southwest Puerto Rico. These studies also suggest active faulting specially in the western part of the island, but limited work has been done regarding their mechanism. Therefore, this work aims to define and map these active faults in western Puerto Rico by integrating data from analysis of fluvial terrains, and detailed mapping using digital elevation model (DEM) extracted from Shuttle Radar Topography Mission (SRTM) and LIDAR data. The goal is to (1) identify structural features such as surface lineaments and fault scarps for the Cerro Goden fault, South Lajas fault, and other active faults in the western of Puerto Rico, (2) correlate these information with the distribution pattern and values of the geomorphic proxies, including Chi integral (χ), normalized steepness (ksn) and Asymmetric factor (AF). Our preliminary results from geomorphic proxies and Lidar data provide some insight of the displacement and stage of activities of these faults (e.g. Boqueron-Punta Malva Fault and Cerro Goden fault). Also, the anomaly of the geomorphic proxies generally correlate with the locations of the landslides in the southwestern Puerto Rico. The geomorphic model of this work include new information of active faulting fundamental to produce better seismic hazards maps. Additionally, active tectonics studies are vital to issue and adjust construction buildings codes and zonification codes.

COMPARAÇÃO ENTRE DADOS ALTIMÉTRICOS SHUTTLE RADAR TOPOGRAPHY MISSION , CARTAS TOPOGRÁFICAS E GPS: NUMA ÁREA COM RELEVO ESCARPADO

OpenAIRE

Eduardo da Silva Pinheiro

2006-01-01

Shuttle Radar Topography Mission (SRTM) flown with Space Shuttle Endeavour, which was launched on 11 February 2000 , aimed to obtain the Earth digital elevation data (DEM). These data were acquired using Interferometric Synthetic Aperture Radar (InSAR) in C (5.6cm – 5.3GHz) and X (3.1cm – 9.6GHz) bands. This paper presents a comparative analysis of elevation data from SRTM and Topographic map (1:50.000) with Differential - GPS field data. The study was conducted in Planalto das Araucárias ar...

Marquesas Islands, French Polynesia 3 arc-second Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Port Alberni, Canada 1/3 arc-second Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Digital Elevation Model of Kauai, Hawaii, Integrating Bathymetric and Topographic Datasets

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Crescent City, California 1/3 Arc-second Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Cordova, Alaska 1/3 Arc-second MHW Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Tutuila, American Samoa 1/3 arc-second Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Eureka, California 1/3 Arc-second MHW Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Central Florida 1/3 arc-second MHW Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Puget Sound 1/3 arc-second MHW Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Society Islands (Leeward), French Polynesia Digital Elevation Model - 1 arc-second

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Midway Atoll 1/3 Arc-second MHW Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Society Islands (Windward), French Polynesia Digital Elevation Model - 1 arc-second

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Miami 1/3 arc-second NAVD 88 Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Central California 1 Arc-second NAVD 88 Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Wake Island 1/3 Arc-second MHW Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Monterey, California 1/3 Arc-second MHW Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Tampa Bay 1/3 arc-second MHW Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Garibaldi, Oregon 1/3 Arc-second MHW Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Sitka, Alaska 1/3 Arc-second MHW Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Object-oriented classification of drumlins from digital elevation models

Science.gov (United States)

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.

Comparison of digital elevation models for aquatic data development.

Science.gov (United States)

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...

False Pass, Alaska 8/15 arc-second Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

Yakutat, Alaska 8/15 Arc-second MHHW Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

Elfin Cove Alaska 1/3 Arc-second Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

Cordova, Alaska 8/15 Arc-second MHHW Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

King Cove, Alaska 8/3 arc-second Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

King Cove, Alaska 8/15 arc-second Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

Nikolski, Alaska 1/3 arc-second MHHW Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

Port Lions, Alaska 8/15 arc-second Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

Yakutat, Alaska 8/3 Arc-second MHHW Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

Digital Elevation Model of Southeast Alaska, Integrating Bathymetric and Topographic Datasets

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

Cold Bay, Alaska 8/15 arc-second Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

Earth elevation map production and high resolution sensing camera imaging analysis

Science.gov (United States)

Yang, Xiubin; Jin, Guang; Jiang, Li; Dai, Lu; Xu, Kai

2010-11-01

The Earth's digital elevation which impacts space camera imaging has prepared and imaging has analysed. Based on matching error that TDI CCD integral series request of the speed of image motion, statistical experimental methods-Monte Carlo method is used to calculate the distribution histogram of Earth's elevation in image motion compensated model which includes satellite attitude changes, orbital angular rate changes, latitude, longitude and the orbital inclination changes. And then, elevation information of the earth's surface from SRTM is read. Earth elevation map which produced for aerospace electronic cameras is compressed and spliced. It can get elevation data from flash according to the shooting point of latitude and longitude. If elevation data between two data, the ways of searching data uses linear interpolation. Linear interpolation can better meet the rugged mountains and hills changing requests. At last, the deviant framework and camera controller are used to test the character of deviant angle errors, TDI CCD camera simulation system with the material point corresponding to imaging point model is used to analyze the imaging's MTF and mutual correlation similarity measure, simulation system use adding cumulation which TDI CCD imaging exceeded the corresponding pixel horizontal and vertical offset to simulate camera imaging when stability of satellite attitude changes. This process is practicality. It can effectively control the camera memory space, and meet a very good precision TDI CCD camera in the request matches the speed of image motion and imaging.

1 Arc-second Digital Elevation Models (DEMs) - USGS National Map 3DEP Downloadable Data Collection

Data.gov (United States)

U.S. Geological Survey, Department of the Interior — This is a tiled collection of the 3D Elevation Program (3DEP) and is 1 arc-second (approximately 30 m) resolution.The elevations in this Digital Elevation Model...

Northern Gulf 1 Arc-second NAVD 88 Coast Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions in the Gulf of Mexico....

TSUNAMI HAZARD ASSESSMENT IN THE NORTHERN AEGEAN SEA

Directory of Open Access Journals (Sweden)

Barbara Theilen-Willige

2008-01-01

Full Text Available Emergency planning for the assessment of tsunami hazard inundation and of secondary effects of erosion and landslides, requires mapping that can help identify coastal areas that are potentially vulnerable. The present study reviews tsunami susceptibility mapping for coastal areas of Turkey and Greece in the Aegean Sea. Potential tsunami vulnerable locations were identified from LANDSAT ETM imageries, Shuttle Radar Topography Mission (SRTM, 2000 data and QuickBird imageries and from a GIS integrated spatial database. LANDSAT ETM and Digital Elevation Model (DEM data derived by the SRTM-Mission were investigated to help detect traces of past flooding events. LANDSAT ETM imageries, merged with digitally processed and enhanced SRTM data, clearly indicate the areas that may be prone to flooding if catastrophic tsunami events or storm surges occur.

Estimating Coastal Digital Elevation Model (DEM) Uncertainty

Science.gov (United States)

Amante, C.; Mesick, S.

2017-12-01

Integrated bathymetric-topographic digital elevation models (DEMs) are representations of the Earth's solid surface and are fundamental to the modeling of coastal processes, including tsunami, storm surge, and sea-level rise inundation. Deviations in elevation values from the actual seabed or land surface constitute errors in DEMs, which originate from numerous sources, including: (i) the source elevation measurements (e.g., multibeam sonar, lidar), (ii) the interpolative gridding technique (e.g., spline, kriging) used to estimate elevations in areas unconstrained by source measurements, and (iii) the datum transformation used to convert bathymetric and topographic data to common vertical reference systems. The magnitude and spatial distribution of the errors from these sources are typically unknown, and the lack of knowledge regarding these errors represents the vertical uncertainty in the DEM. The National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Information (NCEI) has developed DEMs for more than 200 coastal communities. This study presents a methodology developed at NOAA NCEI to derive accompanying uncertainty surfaces that estimate DEM errors at the individual cell-level. The development of high-resolution (1/9th arc-second), integrated bathymetric-topographic DEMs along the southwest coast of Florida serves as the case study for deriving uncertainty surfaces. The estimated uncertainty can then be propagated into the modeling of coastal processes that utilize DEMs. Incorporating the uncertainty produces more reliable modeling results, and in turn, better-informed coastal management decisions.

SRTM Anaglyph: Las Bayas, Argentina

Science.gov (United States)

2001-01-01

and navigation devices. The mission is a cooperative project between NASA, the National Imagery and Mapping Agency of the U.S. Department of Defense, and the German and Italian space agencies. It is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Earth Science Enterprise, Washington, DC.Size: 54.3 x 36.4 kilometers ( 33.7 x 22.6 miles) Location: 41.4 deg. South lat., 70.8 deg. West lon. Orientation: North toward the top Image Data: Shaded SRTM elevation model Date Acquired: February 2000

Eureka, California 1/3 Arc-second NAVD 88 Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Myrtle Beach, South Carolina 1/ Arc-second MWH Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Bar Harbor, Maine 1/3 Arc-second MWH Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Santa Monica, California 1/3 Arc-second MHW Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

San Diego, California 1/3 Arc-second MHW Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Pago Pago, American Samoa 3 Arc-second MWH Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Central Florida 1/3 arc-second NAVD 88 Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Fort Bragg, California 1/3 Arc-second MHW Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Port Townsend, Washington 1/3 Arc-second MWH Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Tampa Bay 1/3 arc-second NAVD 88 Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Puget Sound 1/3 arc-second NAVD 88 Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Key West, Florida 1/3 Arc-second MHW Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Pensacola, Florida 1/3 arc-second NAVD 88 Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information (NCEI) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These...

Palm Beach, Florida 1/3 Arc-second MWH Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Garibaldi, Oregon 1/3 Arc-second NAVD 88 Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Monterey, California 1/3 Arc-second NAVD 88 Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Central Washington Coast 1/3 arc-second NAVD 88 Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Destin, Florida 1/3 arc-second NAVD88 Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

Elfin Cove Alaska 1/3 Arc-second MHHW Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

Prince William Sound, Alaska 8 Arc-second MHHW Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

Comparison between hydrographically conditioned digital elevation models in the morphometric charaterization of watersheds Comparação de modelos digitais de elevação hidrograficamente condicionados na caracterização morfométrica de bacias hidrográficas

Directory of Open Access Journals (Sweden)

Hugo A. S. Guedes

2012-10-01

Full Text Available The aim of this study was to compare the hydrographically conditioned digital elevation models (HCDEMs generated from data of VNIR (Visible Near Infrared sensor of ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer, of SRTM (Shuttle Radar Topography Mission and topographical maps from IBGE in a scale of 1:50,000, processed in the Geographical Information System (GIS, aiming the morphometric characterization of watersheds. It was taken as basis the Sub-basin of São Bartolomeu River, obtaining morphometric characteristics from HCDEMs. Root Mean Square Error (RMSE and cross validation were the statistics indexes used to evaluate the quality of HCDEMs. The percentage differences in the morphometric parameters obtained from these three different data sets were less than 10%, except for the mean slope (21%. In general, it was observed a good agreement between HCDEMs generated from remote sensing data and IBGE maps. The result of HCDEM ASTER was slightly higher than that from HCDEM SRTM. The HCDEM ASTER was more accurate than the HCDEM SRTM in basins with high altitudes and rugged terrain, by presenting frequency altimetry nearest to HCDEM IBGE, considered standard in this study.O objetivo deste estudo foi comparar modelos digitais de elevação hidrograficamente condicionados (MDEHCs, gerados a partir de dados do sensor VNIR (Visible Near Infrared do ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer, da SRTM (Shuttle Radar Topography Mission e de cartas topográficas do IBGE na escala 1:50.000, processados em Sistema de Informações Geográficas (SIG, visando à caracterização morfométrica de bacias hidrográficas. A área de estudo selecionada foi a sub-bacia hidrográfica do Ribeirão São Bartolomeu, sendo obtidas as características morfométricas a partir dos MDEHCs. Aplicaram-se o índice estatístico Raiz do Erro Médio Quadrático (REMQ e a validação cruzada para avaliar a qualidade dos MDEHCs. A

New Orleans, Louisiana 1/3 Arc-second MLLW Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions in the Gulf of Mexico....

New Orleans, Louisiana 1/3 Arc-second MHW Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions in the Gulf of Mexico....

Panama City, Florida 1/3 Arc-second MHW Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions in the Gulf of Mexico....

A 30 m Resolution Surface Water Mask Including Estimation of Positional and Thematic Differences Using Landsat 8, SRTM and OpenStreetMap: A Case Study in the Murray-Darling Basin, Australia

Directory of Open Access Journals (Sweden)

Gennadii Donchyts

2016-05-01

Full Text Available Accurate maps of surface water are essential for many environmental applications. Surface water maps can be generated by combining measurements from multiple sources. Precise estimation of surface water using satellite imagery remains a challenging task due to the sensor limitations, complex land cover, topography, and atmospheric conditions. As a complementary dataset, in the case of hilly landscapes, a drainage network can be extracted from high-resolution digital elevation models. Additionally, Volunteered Geographic Information (VGI initiatives, such as OpenStreetMap, can also be used to produce high-resolution surface water masks. In this study, we derive a high-resolution water mask using Landsat 8 imagery and OpenStreetMap as well as (potential a drainage network using 30 m SRTM. Our approach to derive a surface water mask from Landsat 8 imagery comprises the use of a lower 15% percentile of Landsat 8 Top of Atmosphere (TOA reflectance from 2013 to 2015. We introduce a new non-parametric unsupervised method based on the Canny edge filter and Otsu thresholding to detect water in flat areas. For hilly areas, the method is extended with an additional supervised classification step used to refine the water mask. We applied the method across the Murray-Darling basin, Australia. Differences between our new Landsat-based water mask and the OpenStreetMap water mask regarding positional differences along the rivers and overall coverage were analyzed. Our results show that about 50% of the OpenStreetMap linear water features can be confirmed using the water mask extracted from Landsat 8 imagery and the drainage network derived from SRTM. We also show that the observed distances between river features derived from OpenStreetMap and Landsat 8 are mostly smaller than 60 m. The differences between the new water mask and SRTM-based linear features and hilly areas are slightly larger (110 m. The overall agreement between OpenStreetMap and Landsat 8 water

NOAA Coastal Services Center Coastal Inundation Digital Elevation Model: Philadelphia WFO - Pennsylvania

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This digital elevation model (DEM) is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Coastal Services Center's Sea Level...

A global digital elevation model - GTOP030

Science.gov (United States)

1999-01-01

GTOP030, the U.S. Geological Survey's (USGS) digital elevation model (DEM) of the Earth, provides the flrst global coverage of moderate resolution elevation data.  The original GTOP30 data set, which was developed over a 3-year period through a collaborative effort led by the USGS, was completed in 1996 at the USGS EROS Data Center in Sioux Falls, South Dakota.  The collaboration involved contributions of staffing, funding, or source data from cooperators including the National Aeronautics and Space Administration (NASA), the United Nations Environment Programme Global Resource Information Database (UNEP/GRID), the U.S. Agency for International Development (USAID), the Instituto Nacional de Estadistica Geografia e Informatica (INEGI) of Mexico, the Geographical Survey Institute (GSI) of Japan, Manaaki Whenua Landcare Research of New Zealand, and the Scientific Committee on Antarctic Research (SCAR). In 1999, work was begun on an update to the GTOP030 data set. Additional data sources are being incorporated into GTOP030 with an enhanced and improved data set planned for release in 2000.

Recent temperature trends at mountain stations on the southern ...

Indian Academy of Sciences (India)

in quantifying the magnitude of climatic trends in mountainous regions such as Nepal. .... Note: The topography is classified by using the SRTM3 digital elevation model (DEM), which ...... trends and flooding risk in the west of Scotland; Nordic.

A New Method to Estimate Changes in Glacier Surface Elevation Based on Polynomial Fitting of Sparse ICESat—GLAS Footprints

Directory of Open Access Journals (Sweden)

Tianjin Huang

2017-08-01

Full Text Available We present in this paper a polynomial fitting method applicable to segments of footprints measured by the Geoscience Laser Altimeter System (GLAS to estimate glacier thickness change. Our modification makes the method applicable to complex topography, such as a large mountain glacier. After a full analysis of the planar fitting method to characterize errors of estimates due to complex topography, we developed an improved fitting method by adjusting a binary polynomial surface to local topography. The improved method and the planar fitting method were tested on the accumulation areas of the Naimona’nyi glacier and Yanong glacier on along-track facets with lengths of 1000 m, 1500 m, 2000 m, and 2500 m, respectively. The results show that the improved method gives more reliable estimates of changes in elevation than planar fitting. The improved method was also tested on Guliya glacier with a large and relatively flat area and the Chasku Muba glacier with very complex topography. The results in these test sites demonstrate that the improved method can give estimates of glacier thickness change on glaciers with a large area and a complex topography. Additionally, the improved method based on GLAS Data and Shuttle Radar Topography Mission-Digital Elevation Model (SRTM-DEM can give estimates of glacier thickness change from 2000 to 2008/2009, since it takes the 2000 SRTM-DEM as a reference, which is a longer period than 2004 to 2008/2009, when using the GLAS data only and the planar fitting method.

Creating high-resolution digital elevation model using thin plate spline interpolation and Monte Carlo simulation

International Nuclear Information System (INIS)

Pohjola, J.; Turunen, J.; Lipping, T.

2009-07-01

In this report creation of the digital elevation model of Olkiluoto area incorporating a large area of seabed is described. The modeled area covers 960 square kilometers and the apparent resolution of the created elevation model was specified to be 2.5 x 2.5 meters. Various elevation data like contour lines and irregular elevation measurements were used as source data in the process. The precision and reliability of the available source data varied largely. Digital elevation model (DEM) comprises a representation of the elevation of the surface of the earth in particular area in digital format. DEM is an essential component of geographic information systems designed for the analysis and visualization of the location-related data. DEM is most often represented either in raster or Triangulated Irregular Network (TIN) format. After testing several methods the thin plate spline interpolation was found to be best suited for the creation of the elevation model. The thin plate spline method gave the smallest error in the test where certain amount of points was removed from the data and the resulting model looked most natural. In addition to the elevation data the confidence interval at each point of the new model was required. The Monte Carlo simulation method was selected for this purpose. The source data points were assigned probability distributions according to what was known about their measurement procedure and from these distributions 1 000 (20 000 in the first version) values were drawn for each data point. Each point of the newly created DEM had thus as many realizations. The resulting high resolution DEM will be used in modeling the effects of land uplift and evolution of the landscape in the time range of 10 000 years from the present. This time range comes from the requirements set for the spent nuclear fuel repository site. (orig.)

San Francisco Bay, California 1/3 Arc-second MHW Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Palm Beach, Florida 1/3 Arc-second NAVD 88 Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Key West, Florida 1/3 Arc-second NAVD 88 Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Orange County, California 1/3 arc-second NAVD 88 Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information (NCEI) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These...

Pago Pago, American Samoa 1/3 Arc-second MWH Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Astoria, Oregon 1/3 arc-second MHW Coastal Digital Elevation Model Vers.3

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information (NCEI) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These...

Port Townsend, Washington 1/3 Arc-second NAVD 88 Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Santa Monica, California 1/3 Arc-second NAVD 88 Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Mayaguez, Puerto Rico 2006 1/3 Arc-second MWH Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Fort Bragg, California 1/3 Arc-second NAVD 88 Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Myrtle Beach, South Carolina 1/3 Arc-second MWH Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

South Padre Island, Texas 1/3 Arc-second MHW Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Crescent City, California 1/3 Arc-second NAVD 88 Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

San Juan, Puerto Rico 1/9 arc-second PRVD Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information (NCEI) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These...

San Diego, California 1/3 Arc-second NAVD 88 Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

St. Thomas and St. John, U.S. Virgin Islands Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Mayaguez, Puerto Rico 2007 1/3 Arc-second MWH Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Morehead City, North Carolina 1/3 Arc-second MHW Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Port San Luis, California 1/3 Arc-second MWH Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Bar Harbor, Maine 1/3 Arc-second NAVD 88 Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Comparação entre a Feição de Hidrografia Extraída de uma Imagem do Srtm (Shuttle Radar Topography Mission) e a Vetorizada pelo Módulo Arcscan/ Arcgis®: : Estudo de Caso para Fins de Análise Hidrológica na Bacia Hidrográfica do Rio Grande, Divisa entre os Estados de MG e SP

OpenAIRE

Sady Júnior M. C. de Menezes; Thiago P. M. Soares; Vanessa Mendes Lana; Cleverson Alves de Lima; Fernando Soares de Oliveira; Claubert Wagner G. de Menezes; Carlos Antonio Alvares Soares Ribeiro; Vicente Paulo Soares

2011-01-01

O SRTM - Shutle Radar Topography Mission – é uma missão o qual gerou-se uma base topográfica digital de alta resolução. A SRTM consiste num sistema de radar especialmente modificado que voou a bordo do Endea-vour (ônibus espacial), em fevereiro de 2000. As imagens obtidas pelo SRTM garantiu amplas aplicações em estudos espaciais, uma vez que os processos de comunicação visual para a produção de cartografia de base e mapas de precisão da análise espacial foram utilizados. O present...

Prince William Sound, Alaska 8/3 Arc-second MHHW Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

Perryville and Ivanof Bay, Alaska 1/3 arc-second Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

Panama City, Florida 1/3 Arc-second NAVD 88 Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions in the Gulf of Mexico....

Alaska 2 Arc-second Digital Elevation Models (DEMs) - USGS National Map 3DEP Downloadable Data Collection

Data.gov (United States)

U.S. Geological Survey, Department of the Interior — This is a tiled collection of the 3D Elevation Program (3DEP) and is 2 arc-second (approximately 60 m) resolution covering Alaska. The elevations in this Digital...

NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: Charleston WFO (Georgia)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This digital elevation model (DEM) is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Sea...

APLICAÇÃO DE IMAGENS DO RADAR INTERFEROMÉTRICO (SRTM NA AVALIAÇÃO DA FRAGILIDADE DA BACIA DO CÓRREGO CACHOEIRINHA, NOS MUNICÍPIOS DE CÁCERES E PORTO ESTRELA /MT / THE USE OF SHUTTLE RADAR TOPOGRAPHY MISSION (SRTM IMAGES TO EVALUATE THE ENVIRONMENTAL VULNERABILITY OF CÓRREGO CACHOEIRINHA WATERSHED, BETWEEN THE MUNICIPALITIES OF CÁCERES AND PORTO ESTRELA /MT

Directory of Open Access Journals (Sweden)

Leonardo Franklin Fornelos

2008-08-01

Full Text Available The environmental analyses, on the geographical approach, provide technical and scientific support for thezoning generation, used in environmental planning. In this perspective it’s necessary to evaluate theenvironmental vulnerabilities within the ecodynamical conception (Tricart, 1977, based on systems theory.One of the widely used evaluation methodologies, not only in the geographical environment, is the UniversalSoil Loss Equation (USLE, using maps to spatialize and quantify its factors. Whereas progress have beenmade in the generation of Remote Sensing products, through new sensors, this paper proposes the use ofSRTM elevation data to generate one of the USLE factors, the Lenght-Slope map. The studied area wascórrego Cachoeirinha watershed, located in the municipalities of Cáceres and Porto Estrela, Mato Grosso- Brazil. The implementation involved the drafting of rainfall erosivity, soil erodibility, lenght-slope factor,crop/vegetation factor and support practices maps. These maps were combined in ArcGis, allowing thequantification of soil losses in the watershed and the determination of different fragility degrees, in conformitywith the classification proposed by UNESCO (1980. The LS map generated from SRTM revealed moredetails on the hillside shapes. It’s emphasized the greater agility to produce the soil loss maps, consequentlythe vulnerability, using SRTM.

Efficient extraction of drainage networks from massive, radar-based elevation models with least cost path search

Directory of Open Access Journals (Sweden)

M. Metz

2011-02-01

Full Text Available The availability of both global and regional elevation datasets acquired by modern remote sensing technologies provides an opportunity to significantly improve the accuracy of stream mapping, especially in remote, hard to reach regions. Stream extraction from digital elevation models (DEMs is based on computation of flow accumulation, a summary parameter that poses performance and accuracy challenges when applied to large, noisy DEMs generated by remote sensing technologies. Robust handling of DEM depressions is essential for reliable extraction of connected drainage networks from this type of data. The least-cost flow routing method implemented in GRASS GIS as the module r.watershed was redesigned to significantly improve its speed, functionality, and memory requirements and make it an efficient tool for stream mapping and watershed analysis from large DEMs. To evaluate its handling of large depressions, typical for remote sensing derived DEMs, three different methods were compared: traditional sink filling, impact reduction approach, and least-cost path search. The comparison was performed using the Shuttle Radar Topographic Mission (SRTM and Interferometric Synthetic Aperture Radar for Elevation (IFSARE datasets covering central Panama at 90 m and 10 m resolutions, respectively. The accuracy assessment was based on ground control points acquired by GPS and reference points digitized from Landsat imagery along segments of selected Panamanian rivers. The results demonstrate that the new implementation of the least-cost path method is significantly faster than the original version, can cope with massive datasets, and provides the most accurate results in terms of stream locations validated against reference points.

St. Thomas and St. John, U.S. Virgin Islands Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The 1/3 arc-second St. Thomas and St. John, U.S. Virgin Islands Coastal Digital Elevation Model will be used to support NOAA's tsunami forecast system and for...

Quantification of soil losses from tourist trails - use of Digital Elevation Models

Science.gov (United States)

Tomczyk, Aleksandra

2010-05-01

Tourism impacts in protected mountain areas are one of the main concerns for land managers. Impact to environment is most visible at locations of highly concentrated activities like tourist trails, campsites etc. The main indicators of the tourist trail degradation are: vegetation loss (trampling of vegetation cover), change of vegetation type and composition, widening of the trails, muddiness and soil erosion. The last one is especially significant, since it can cause serious transformation of the land surface. Such undesirable changes cannot be repaired without high-cost management activities, and, in some cases they can made the trails difficult and unsafe to use. Scientific understanding of soil erosion related to human impact can be useful for more effective management of the natural protected areas. The aim of this study was to use of digital elevation models (DEMs) to precisely quantify of soil losses from tourist trails. In the study precise elevation data were gathered in several test fields of 4 by 5 m spatial dimension. Measurements were taken in 13 test fields, located in two protected natural areas in south Poland: Gorce National Park and Popradzki Landscape Park. The measuring places were located on trails characterized by different slope, type of vegetation and type of use. Each test field was established by four special marks, firmly dug into the ground. Elevation data were measured with the electronic total station. Irregular elevation points were surveying with essential elements of surrounding terrain surface being included. Moreover, surveys in fixed profile lines were done. For each test field a set of 30 measurements in control points has been collected and these data provide the base for verification of digital elevation models. Average density of the surveying was 70 points per square meter (1000 - 1500 elevation points per each test fields). Surveys in each test field were carried out in August and September of 2008, June 2009 and August

Sources of Artefacts in Synthetic Aperture Radar Interferometry Data Sets

Science.gov (United States)

Becek, K.; Borkowski, A.

2012-07-01

In recent years, much attention has been devoted to digital elevation models (DEMs) produced using Synthetic Aperture Radar Interferometry (InSAR). This has been triggered by the relative novelty of the InSAR method and its world-famous product—the Shuttle Radar Topography Mission (SRTM) DEM. However, much less attention, if at all, has been paid to sources of artefacts in SRTM. In this work, we focus not on the missing pixels (null pixels) due to shadows or the layover effect, but rather on outliers that were undetected by the SRTM validation process. The aim of this study is to identify some of the causes of the elevation outliers in SRTM. Such knowledge may be helpful to mitigate similar problems in future InSAR DEMs, notably the ones currently being developed from data acquired by the TanDEM-X mission. We analysed many cross-sections derived from SRTM. These cross-sections were extracted over the elevation test areas, which are available from the Global Elevation Data Testing Facility (GEDTF) whose database contains about 8,500 runways with known vertical profiles. Whenever a significant discrepancy between the known runway profile and the SRTM cross-section was detected, a visual interpretation of the high-resolution satellite image was carried out to identify the objects causing the irregularities. A distance and a bearing from the outlier to the object were recorded. Moreover, we considered the SRTM look direction parameter. A comprehensive analysis of the acquired data allows us to establish that large metallic structures, such as hangars or car parking lots, are causing the outliers. Water areas or plain wet terrains may also cause an InSAR outlier. The look direction and the depression angle of the InSAR system in relation to the suspected objects influence the magnitude of the outliers. We hope that these findings will be helpful in designing the error detection routines of future InSAR or, in fact, any microwave aerial- or space-based survey. The

SOURCES OF ARTEFACTS IN SYNTHETIC APERTURE RADAR INTERFEROMETRY DATA SETS

Directory of Open Access Journals (Sweden)

K. Becek

2012-07-01

Full Text Available In recent years, much attention has been devoted to digital elevation models (DEMs produced using Synthetic Aperture Radar Interferometry (InSAR. This has been triggered by the relative novelty of the InSAR method and its world-famous product—the Shuttle Radar Topography Mission (SRTM DEM. However, much less attention, if at all, has been paid to sources of artefacts in SRTM. In this work, we focus not on the missing pixels (null pixels due to shadows or the layover effect, but rather on outliers that were undetected by the SRTM validation process. The aim of this study is to identify some of the causes of the elevation outliers in SRTM. Such knowledge may be helpful to mitigate similar problems in future InSAR DEMs, notably the ones currently being developed from data acquired by the TanDEM-X mission. We analysed many cross-sections derived from SRTM. These cross-sections were extracted over the elevation test areas, which are available from the Global Elevation Data Testing Facility (GEDTF whose database contains about 8,500 runways with known vertical profiles. Whenever a significant discrepancy between the known runway profile and the SRTM cross-section was detected, a visual interpretation of the high-resolution satellite image was carried out to identify the objects causing the irregularities. A distance and a bearing from the outlier to the object were recorded. Moreover, we considered the SRTM look direction parameter. A comprehensive analysis of the acquired data allows us to establish that large metallic structures, such as hangars or car parking lots, are causing the outliers. Water areas or plain wet terrains may also cause an InSAR outlier. The look direction and the depression angle of the InSAR system in relation to the suspected objects influence the magnitude of the outliers. We hope that these findings will be helpful in designing the error detection routines of future InSAR or, in fact, any microwave aerial- or space

Comparative lahar hazard mapping at Volcan Citlaltépetl, Mexico using SRTM, ASTER and DTED-1 digital topographic data

Science.gov (United States)

Hubbard, Bernard E.; Sheridan, Michael F.; Carrasco-Nunez, Gerardo; Diaz-Castellon, Rodolfo; Rodriguez, Sergio R.

2007-01-01

In this study, we evaluated and compared the utility of spaceborne SRTM and ASTER DEMs with baseline DTED-1 “bald-earth” topography for mapping lahar inundation hazards from volcan Citlaltépetl, Mexico, a volcano which has had a history of producing debris flows of various extents. In particular, we tested the utility of these topographic datasets for resolving ancient valley-filling deposits exposed around the flanks of the volcano, for determining their magnitude using paleohydrologic methods and for forecasting their inundation limits in the future. We also use the three datasets as inputs to a GIS stream inundation flow model, LAHARZ, and compare the results.

South Padre Island, Texas 1/3 Arc-second NAVD 88 Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Port San Luis, California 1/3 Arc-second NAVD 88 Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

San Francisco Bay, California 1/3 Arc-second NAVD 88 Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

Morehead City, North Carolina 1/3 Arc-second NAVD 88 Coastal Digital Elevation Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

ACE2 Global Digital Elevation Model : User Analysis

Science.gov (United States)

Smith, R. G.; Berry, P. A. M.; Benveniste, J.

2013-12-01

Altimeter Corrected Elevations 2 (ACE2), first released in October 2009, is the Global Digital Elevation Model (GDEM) created by fusing the high accuracy of over 100 million altimeter retracked height estimates, derived primarily from the ERS-1 Geodetic Mission, with the high frequency content available within the near-global Shuttle Radar Topography Mission. This novel ACE2 GDEM is freely available at 3”, 9”, 30” and 5' and has been distributed via the web to over 680 subscribers. This paper presents the results of a detailed analysis of geographical distribution of subscribed users, along with fields of study and potential uses. Investigations have also been performed to determine the most popular spatial resolutions and the impact these have on the scope of data downloaded. The analysis has shown that, even though the majority of users have come from Europe and America, a significant number of website hits have been received from South America, Africa and Asia. Registered users also vary widely, from research institutions and major companies down to individual hobbyists looking at data for single projects.

Making Digital Elevation ModelsAccessible, Comprehensible, and Engaging through Real-Time Visualization

DEFF Research Database (Denmark)

Kjeldsen, Thomas Kim; Mikkelsen, Peter Trier; Mosegaard, Jesper

2015-01-01

In this paper we present our initial experiments with the new high quality digital elevation model, “Danmarks Højdemodel-2015” (DHM) exposed as an interactive 3D visualization on web and in virtual reality. We argue that such data has great opportunities to spawn new business and new insight...

Extracting topographic structure from digital elevation data for geographic information-system analysis

Science.gov (United States)

Jenson, Susan K.; Domingue, Julia O.

1988-01-01

Software tools have been developed at the U.S. Geological Survey's EROS Data Center to extract topographic structure and to delineate watersheds and overland flow paths from digital elevation models. The tools are specialpurpose FORTRAN programs interfaced with general-purpose raster and vector spatial analysis and relational data base management packages.

Anisotropic Third-Order Regularization for Sparse Digital Elevation Models

KAUST Repository

Lellmann, Jan

2013-01-01

We consider the problem of interpolating a surface based on sparse data such as individual points or level lines. We derive interpolators satisfying a list of desirable properties with an emphasis on preserving the geometry and characteristic features of the contours while ensuring smoothness across level lines. We propose an anisotropic third-order model and an efficient method to adaptively estimate both the surface and the anisotropy. Our experiments show that the approach outperforms AMLE and higher-order total variation methods qualitatively and quantitatively on real-world digital elevation data. © 2013 Springer-Verlag.

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

Science.gov (United States)

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.

A new, high-resolution digital elevation model of Greenland fully validated with airborne laser altimeter data

DEFF Research Database (Denmark)

Bamber, J.L.; Ekholm, Simon; Krabill, W.B.

2001-01-01

were corrected for a slope-dependent bias that had been identified in a previous study. The radar altimetry was supplemented with stereophotogrammetric data sets, synthetic aperture radar interferometry, and digitized cartographic maps over regions of bare rock and where gaps in the satellite altimeter...... the bare rock areas the accuracy ranged from 20 to 200 m, dependent on the data source available. The new digital elevation model was used as an input data set for a positive degree day model of ablation. The new elevation model was found to reduce ablation by only 2% compared with using an older, 2.5-km...

MORPHOLOGICAL FILLING OF DIGITAL ELEVATION MODELS

Directory of Open Access Journals (Sweden)

T. Krauß

2012-09-01

Full Text Available In this paper a new approach for a more detailed post processing and filling of digital elevation models (DEMs in urban areas is presented. To reach the required specifications in a first step the errors in digital surface models (DSMs generated by dense stereo algorithms are analyzed and methods for detection and classification of the different types of errors are implemented. Subsequently the classified erroneous areas are handled in separate manner to eliminate outliers and fill the DSM properly. The errors which can be detected in DSMs range from outliers – single pixels or small areas containing extremely high or low values – over noise from mismatches, single small holes to occlusions, where large areas are not visible in one of the images of the stereo pair. To validate the presented method artificial DSMs are generated and superimposed with all different kinds of described errors like noise (small holes cut in, outliers (small areas moved up/down, occlusions (larger areas beneath steep walls and so on. The method is subsequently applied to the artificial DSMs and the resulting filled DSMs are compared to the original artificial DSMs without the introduced errors. Also the method is applied to stereo satellite generated DSMs from the ISPRS Comission 1 WG4 benchmark dataset and the results are checked with the also provided first pulse laser DSM data. Finally the results are discussed, strengths and weaknesses of the approach are shown and suggestions for application and optimization are given.

NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: San Diego (CA) WFO

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This digital elevation model (DEM) is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Sea...

Louisiana Digital Elevation Dataset from LDEQ source data, UTM Zone 15 NAD83, LOSCO (2004) [24KDEM_LDEQ_2004

Data.gov (United States)

Louisiana Geographic Information Center — The Louisiana Digital Elevation Dataset was derived from the U.S. Geological Survey National Elevation Database (NED). This data was projected to Universal...

Global multi-resolution terrain elevation data 2010 (GMTED2010)

Science.gov (United States)

Danielson, Jeffrey J.; Gesch, Dean B.

2011-01-01

In 1996, the U.S. Geological Survey (USGS) developed a global topographic elevation model designated as GTOPO30 at a horizontal resolution of 30 arc-seconds for the entire Earth. Because no single source of topographic information covered the entire land surface, GTOPO30 was derived from eight raster and vector sources that included a substantial amount of U.S. Defense Mapping Agency data. The quality of the elevation data in GTOPO30 varies widely; there are no spatially-referenced metadata, and the major topographic features such as ridgelines and valleys are not well represented. Despite its coarse resolution and limited attributes, GTOPO30 has been widely used for a variety of hydrological, climatological, and geomorphological applications as well as military applications, where a regional, continental, or global scale topographic model is required. These applications have ranged from delineating drainage networks and watersheds to using digital elevation data for the extraction of topographic structure and three-dimensional (3D) visualization exercises (Jenson and Domingue, 1988; Verdin and Greenlee, 1996; Lehner and others, 2008). Many of the fundamental geophysical processes active at the Earth's surface are controlled or strongly influenced by topography, thus the critical need for high-quality terrain data (Gesch, 1994). U.S. Department of Defense requirements for mission planning, geographic registration of remotely sensed imagery, terrain visualization, and map production are similarly dependent on global topographic data. Since the time GTOPO30 was completed, the availability of higher-quality elevation data over large geographic areas has improved markedly. New data sources include global Digital Terrain Elevation Data (DTEDRegistered) from the Shuttle Radar Topography Mission (SRTM), Canadian elevation data, and data from the Ice, Cloud, and land Elevation Satellite (ICESat). Given the widespread use of GTOPO30 and the equivalent 30-arc

Delineation of watershed in a mountainous area using different digital elevation modelsDelimitação de bacia hidrográfica em região montanhosa a partir de diferentes modelos digitais de elevação

Directory of Open Access Journals (Sweden)

Roberto Avelino Cecílio

2013-10-01

Full Text Available The precise delineation of watersheds is essential to studies related to environmental and hydrologic modeling. Such delineation is performed automatically in GIS softwares using algorithms that identify the watershed from grid representation of the terrain, the digital elevation model (DEM. This study evaluated the automatic delineation of a watershed located in the southern mountainous region of Espirito Santo (Brazil using six different DEMs. Three MDEs were obtained by radar images (SRTM and its refinements. Other three MDEs were obtained by process spatial interpolation of topographic data using different interpolators. It was found that the MDE obtained by the interpolation of topographic data using Top To Raster interpolator, (taking mapped hydrography as support promoted the best representation of the watershed topography for the purpose of its delimitation. A correta delimitação dos divisores de água da uma bacia hidrográfica é de grande importância para estudos ligados à modelagem hidrológica e ambiental. Tal procedimento é realizado de forma automática em aplicativos computacionais de Sistemas de Informaç��es Geográficas, por meio de algoritmos que identificam os divisores de águas a partir de uma representação matricial da topografia do terreno, denominada Modelo Digital de Elevação (MDE. O presente trabalho avaliou a delimitação automática de uma bacia hidrográfica situada em região montanhosa do Sul do Estado do Espírito Santo (Brasil feita a partir de seis diferentes MDEs: três MDEs originários de imagem de radar (SRTM e seus refinamentos, além de três MDEs originários de processos de interpolação espacial de curvas de nível por meio de diferentes formas de interpolação. Verificou-se que o MDE gerado a partir das curvas de nível e da hidrografia mapeada utilizando o interpolador Topo To Raster apresentou o melhor desempenho de representação do relevo da bacia para fins de delimitação da

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

Science.gov (United States)

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 preliminary assessment for groundwater in a part of North Central ...

African Journals Online (AJOL)

The geological map of the study area, Landsat7 ETM+, and Shuttle Radar Topographic Mission (SRTM) imageries covering the area were employed in this study. ... To eliminate bias and subjectivity, Normalized Difference Vegetation Index (NDVI) and Digital Elevation Model (DEM) of the study area were processed for ...

Benchmarking flood models from space in near real-time: accommodating SRTM height measurement errors with low resolution flood imagery

Science.gov (United States)

Schumann, G.; di Baldassarre, G.; Alsdorf, D.; Bates, P. D.

2009-04-01

In February 2000, the Shuttle Radar Topography Mission (SRTM) measured the elevation of most of the Earth's surface with spatially continuous sampling and an absolute vertical accuracy greater than 9 m. The vertical error has been shown to change with topographic complexity, being less important over flat terrain. This allows water surface slopes to be measured and associated discharge volumes to be estimated for open channels in large basins, such as the Amazon. Building on these capabilities, this paper demonstrates that near real-time coarse resolution radar imagery of a recent flood event on a 98 km reach of the River Po (Northern Italy) combined with SRTM terrain height data leads to a water slope remarkably similar to that derived by combining the radar image with highly accurate airborne laser altimetry. Moreover, it is shown that this space-borne flood wave approximation compares well to a hydraulic model and thus allows the performance of the latter, calibrated on a previous event, to be assessed when applied to an event of different magnitude in near real-time. These results are not only of great importance to real-time flood management and flood forecasting but also support the upcoming Surface Water and Ocean Topography (SWOT) mission that will routinely provide water levels and slopes with higher precision around the globe.

Author Details

African Journals Online (AJOL)

Olayinka, DN. Vol 7, No 1 (2012) - Articles Determination of Land Surface Temperature (LST) and Potential Urban Heat Island Effect in Parts of Lagos State using Satellite Imageries Abstract · Vol 7, No 1 (2012) - Articles Transformation of Shuttle Radar Topography Mission (SRTM) Digital Elevation Data to Nigerian Height ...

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African Journals Online (AJOL)

Items 51 - 70 of 70 ... Vol 7, No 1 (2012), Transformation of Shuttle Radar Topography Mission (SRTM) Digital Elevation Data to Nigerian Height System, Abstract. PC Nwilo, DN Olayinka, CJ Okolie, EA Adzandeh. Vol 5, No 1 (2010), Urban Crises and Rental Values Differential in Kaduna Metropolis, Abstract. BJ Ajibuah.

FUTY Journal of the Environment

African Journals Online (AJOL)

Transformation of Shuttle Radar Topography Mission (SRTM) Digital Elevation Data to Nigerian Height System · EMAIL FULL TEXT EMAIL FULL TEXT DOWNLOAD FULL TEXT DOWNLOAD FULL TEXT. PC Nwilo, DN Olayinka, CJ Okolie, EA Adzandeh, 73-89. http://dx.doi.org/10.4314/fje.v7i1.6 ...

5 Meter Alaska Digital Elevation Models (DEMs) - USGS National Map 3DEP Downloadable Data Collection

Data.gov (United States)

U.S. Geological Survey, Department of the Interior — This dataset is comprised of 5-meter ifsar-derived Digital Elevation Models (DEMs) over Alaska only. It is distributed as one-degree blocks with overedge. Horizontal...

Author Details

African Journals Online (AJOL)

Okolie, CJ. Vol 7, No 1 (2012) - Articles Transformation of Shuttle Radar Topography Mission (SRTM) Digital Elevation Data to Nigerian Height System Abstract. ISSN: 1597-8826. AJOL African Journals Online. HOW TO USE AJOL... for Researchers · for Librarians · for Authors · FAQ's · More about AJOL · AJOL's Partners ...

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African Journals Online (AJOL)

Adzandeh, EA. Vol 7, No 1 (2012) - Articles Transformation of Shuttle Radar Topography Mission (SRTM) Digital Elevation Data to Nigerian Height System Abstract. ISSN: 1597-8826. AJOL African Journals Online. HOW TO USE AJOL... for Researchers · for Librarians · for Authors · FAQ's · More about AJOL · AJOL's ...

How processing digital elevation models can affect simulated water budgets

Science.gov (United States)

Kuniansky, E.L.; Lowery, M.A.; Campbell, B.G.

2009-01-01

For regional models, the shallow water table surface is often used as a source/sink boundary condition, as model grid scale precludes simulation of the water table aquifer. This approach is appropriate when the water table surface is relatively stationary. Since water table surface maps are not readily available, the elevation of the water table used in model cells is estimated via a two-step process. First, a regression equation is developed using existing land and water table elevations from wells in the area. This equation is then used to predict the water table surface for each model cell using land surface elevation available from digital elevation models (DEM). Two methods of processing DEM for estimating the land surface for each cell are commonly used (value nearest the cell centroid or mean value in the cell). This article demonstrates how these two methods of DEM processing can affect the simulated water budget. For the example presented, approximately 20% more total flow through the aquifer system is simulated if the centroid value rather than the mean value is used. This is due to the one-third greater average ground water gradients associated with the centroid value than the mean value. The results will vary depending on the particular model area topography and cell size. The use of the mean DEM value in each model cell will result in a more conservative water budget and is more appropriate because the model cell water table value should be representative of the entire cell area, not the centroid of the model cell.

A new algorithm for least-cost path analysis by correcting digital elevation models of natural landscapes

Science.gov (United States)

Baek, Jieun; Choi, Yosoon

2017-04-01

Most algorithms for least-cost path analysis usually calculate the slope gradient between the source cell and the adjacent cells to reflect the weights for terrain slope into the calculation of travel costs. However, these algorithms have limitations that they cannot analyze the least-cost path between two cells when obstacle cells with very high or low terrain elevation exist between the source cell and the target cell. This study presents a new algorithm for least-cost path analysis by correcting digital elevation models of natural landscapes to find possible paths satisfying the constraint of maximum or minimum slope gradient. The new algorithm calculates the slope gradient between the center cell and non-adjacent cells using the concept of extended move-sets. If the algorithm finds possible paths between the center cell and non-adjacent cells with satisfying the constraint of slope condition, terrain elevation of obstacle cells existing between two cells is corrected from the digital elevation model. After calculating the cumulative travel costs to the destination by reflecting the weight of the difference between the original and corrected elevations, the algorithm analyzes the least-cost path. The results of applying the proposed algorithm to the synthetic data sets and the real-world data sets provide proof that the new algorithm can provide more accurate least-cost paths than other conventional algorithms implemented in commercial GIS software such as ArcGIS.

Antarctic 1 km Digital Elevation Model (DEM) from Combined ERS-1 Radar and ICESat Laser Satellite Altimetry

Data.gov (United States)

National Aeronautics and Space Administration — This data set provides a 1 km resolution Digital Elevation Model (DEM) of Antarctica. The DEM combines measurements from the European Remote Sensing Satellite-1...

SRTM Colored Height and Shaded Relief: Las Bayas, Argentina

Science.gov (United States)

2001-01-01

X-band antennas, and improved tracking and navigation devices. The mission is a cooperative project between NASA, the National Imagery and Mapping Agency of the U.S. Department of Defense, and the German and Italian space agencies. It is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Earth Science Enterprise, Washington, DC.Size: 54.3 x 36.4 kilometers ( 33.7 x 22.6 miles) Location: 41.4 deg. South lat., 70.8 deg. West lon. Orientation: North toward the top Image Data: Shaded and colored SRTM elevation model Date Acquired: February 2000

KAJIAN PEMANFAATAN DEM SRTM & GOOGLE EARTH UNTUK PARAMETER PENILAIAN POTENSI KERUGIAN EKONOMI AKIBAT BANJIR ROB

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Arief L Nugraha

2013-12-01

Full Text Available Tidal flood is a significant threat for the economic growth rate in the city of Semarang. The threat mitigation requires planning, thereby reducing the impact of the losses. The availability of global data with free access can provide solutions in disaster management, the data are SRTM DEM and Google Earth. With both of these data can be mapped potential economic losses caused by tidal flooding. With the techniques of remote sensing and GIS to handle the SRTM DEM data and Google Earth, the techniques can be generated maps and models of tidal inundation area maps woke up in the city of Semarang. Analysis of potential economic losses can be calculated by doing an overlay of the two maps generated. The results achieved from this study is SRTM DEM and Google Earth can able to produce thematic maps of situational tidal flood disaster so that it can be used as a parameter value calculation of the potential economic losses. This study also obtain the result that the area of ​​land affected by the tidal flood an area of ​​8339.31 hectares and the number of buildings reaching 78 299 pieces, which the district that has the highest impact on the tidal flood that North Semarang.

Original Product Resolution (OPR) Source Digital Elevation Models (DEMs) - USGS National Map 3DEP Downloadable Data Collection

Data.gov (United States)

U.S. Geological Survey, Department of the Interior — This data collection is the Original Product Resolution (OPR) Digital Elevation Model (DEM) as provided to the USGS. This DEM is delivered in the original...

NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: Melbourne (FL) WFO - Brevard and Volusia Counties

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This digital elevation model (DEM) is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Sea...

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

Science.gov (United States)

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...

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

Science.gov (United States)

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.

Side-specific effect of yolk testosterone elevation on second-to-fourth digit ratio in a wild passerine

Science.gov (United States)

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.

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

Science.gov (United States)

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.

USING SRTM TO QUANTIFY SIZE PARAMETERS AND SPATIAL DISTRIBUTION OF ENDORHEIC BASINS IN SOUTHERN SOUTH AMERICA

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Ralf Hesse

2008-08-01

Full Text Available The SRTM data set is the highest resolution DEM with global or continental coverage. It is therefore theDEM of choice for continental-scale geomorphological mapping and quantitative analysis. In this study,SRTM data are used for the identification and characterisation of endorheic basins in southern SouthAmerica (south of 19°S. The results show the feasibility of continental-scale quantitative geomorphologybased on SRTM data and provide insights into the distribution of closed basins. The largest endorheicbasin is located in the Puna region and consists of several interconnected sub-basins. This basin accountsfor 38.6 % (7877 km3 of the total volume of the endorheic basins identified in this study. Analyses of thegeographic distribution show a narrow longitudinal distribution between 64.5 and 71.5° W and a multimodallatitudinal distribution which is characterised by two groups of basins at 22.5–27.5°S and 37.5–50.0° Sand an almost complete absence of basins between 27.5 and 37.5° S. Problems and sources ofmisinterpretation arising from data quality and resolution are discussed. Further research, targeting in particularthe genesis and potential for paleoenvironmental reconstruction of closed basins in southern Argentina, iscalled for.

Comparação entre a Feição de Hidrografia Extraída de uma Imagem do Srtm (Shuttle Radar Topography Mission e a Vetorizada pelo Módulo Arcscan/ Arcgis®: : Estudo de Caso para Fins de Análise Hidrológica na Bacia Hidrográfica do Rio Grande, Divisa entre os Estados de MG e SP

Directory of Open Access Journals (Sweden)

Sady Júnior M. C. de Menezes

2011-08-01

Full Text Available O SRTM - Shutle Radar Topography Mission – é uma missão o qual gerou-se uma base topográfica digital de alta resolução. A SRTM consiste num sistema de radar especialmente modificado que voou a bordo do Endea-vour (ônibus espacial, em fevereiro de 2000. As imagens obtidas pelo SRTM garantiu amplas aplicações em estudos espaciais, uma vez que os processos de comunicação visual para a produção de cartografia de base e mapas de precisão da análise espacial foram utilizados. O presente estudo foi baseado em duas etapas de processamento de dados: inicialmente, incidiu sobre a manipulação de bases vetorizadas (dados de hidrografia obtidos pelo IBGE - Instituto Brasileiro de Geografia e Estatística e, em seguida, gerou-se informações vetorizadas a partir de imagens SRTM. A área de estudo é a Bacia do Rio Grande, MG/SP. Usando o programa de Sistemas de Informação Geográfica - ArcGIS 9.3.1 - foi obtido pelo módulo Spatial Analyst a hidrografia que foi extraída do SRTM. Após essa extração, foram comparadas as informações obtidas com o IBGE (vetor da base de dados utilizando o módulo Arcscan/ArcGIS e as informações obtidas pelo SRTM. Verificou-se uma ligeira diferença entre a distribuição e a concentração dos prováveis canais de drenagem entre os mapas dos vetores gerados (IBGE x SRTM. O trabalho demonstrou o uso dos dados do SRTM possibilitando a atualização de dados da rede hidrográfica de extensas áreas de modo bastante facilitado, com a vantagem de ser organizado pela mesma equipe e pelo mesmo processo metodológico, sem riscos de desigualdades durante sua geração.

Contours, This Layer was derived from the USGS National Elevation Dataset (NED) based on 7.5 minute Digital Elevation Model (DEM) image files., Published in 1999, 1:24000 (1in=2000ft) scale, Atlanta Regional Commission.

Data.gov (United States)

NSGIC Regional | GIS Inventory — Contours dataset current as of 1999. This Layer was derived from the USGS National Elevation Dataset (NED) based on 7.5 minute Digital Elevation Model (DEM) image...

NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: Portland (OR) WFO - Tillamook, Lincoln, and Lane Counties

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This digital elevation model (DEM) is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Sea...

NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: Jacksonville (FL) WFO - Duval, Clay, and Nassau Counties

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This digital elevation model (DEM) is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Sea...

NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: Eureka (CA) WFO - Humboldt and Del Norte Counties

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This digital elevation model (DEM) is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Sea...

Digitial Elevation Model (DEM) 100K

Data.gov (United States)

Kansas Data Access and Support Center — Digital Elevation Model (DEM) is the terminology adopted by the USG to describe terrain elevation data sets in a digital raster form. The standard DEM consists of a...

Digtial Elevation Model (DEM) 250K

Data.gov (United States)

Kansas Data Access and Support Center — Digital Elevation Model (DEM) is the terminology adopted by the USGS to describe terrain elevation data sets in a digital raster form. The standard DEM consists of a...

Revealing topographic lineaments through IHS enhancement of DEM data. [Digital Elevation Model

Science.gov (United States)

Murdock, Gary

1990-01-01

Intensity-hue-saturation (IHS) processing of slope (dip), aspect (dip direction), and elevation to reveal subtle topographic lineaments which may not be obvious in the unprocessed data are used to enhance digital elevation model (DEM) data from northwestern Nevada. This IHS method of lineament identification was applied to a mosiac of 12 square degrees using a Cray Y-MP8/864. Square arrays from 3 x 3 to 31 x 31 points were tested as well as several different slope enhancements. When relatively few points are used to fit the plane, lineaments of various lengths are observed and a mechanism for lineament classification is described. An area encompassing the gold deposits of the Carlin trend and including the Rain in the southeast to Midas in the northwest is investigated in greater detail. The orientation and density of lineaments may be determined on the gently sloping pediment surface as well as in the more steeply sloping ranges.

MEaSUREs Greenland Ice Mapping Project (GIMP) Digital Elevation Model from GeoEye and WorldView Imagery, Version 1

Data.gov (United States)

National Aeronautics and Space Administration — This data set consists of an enhanced resolution digital elevation model (DEM) for the Greenland Ice Sheet. The DEM is derived from sub-meter resolution,...

Preparation of the Digital Elevation Model for Orthophoto CR Production

Science.gov (United States)

Švec, Z.; Pavelka, K.

2016-06-01

The Orthophoto CR is produced in co-operation with the Land Survey Office and the Military Geographical and Hydrometeorological Office. The product serves to ensure a defence of the state, integrated crisis management, civilian tasks in support of the state administration and the local self-government of the Czech Republic as well. It covers the whole area of the Republic and for ensuring its up-to-datedness is reproduced in the biennial period. As the project is countrywide, it keeps the project within the same parameters in urban and rural areas as well. Due to economic reasons it cańt be produced as a true ortophoto because it requires large side and forward overlaps of the aerial photographs and a preparation of the digital surface model instead of the digital terrain model. Use of DTM without some objects of DSM for orthogonalization purposes cause undesirable image deformations in the Orthophoto. There are a few data sets available for forming a suitable elevation model. The principal source should represent DTMs made from data acquired by the airborne laser scanning of the entire area of the Czech Republic that was carried out in the years 2009-2013, the DMR4G in the grid form and the DMR5G in TIN form respectively. It can be replenished by some vector objects (bridges, dams, etc.) taken from the geographic base data of the Czech Republic or obtained by new stereo plotting. It has to be taken into account that the option of applying DSM made from image correlation is also available. The article focuses on the possibilities of DTM supplement for ortogonalization. It looks back to the recent transition from grid to hybrid elevation models, problems that occurred, its solution and getting some practical remarks. Afterwards it assesses the current state and deals with the options for updating the model. Some accuracy analysis are included.

PREPARATION OF THE DIGITAL ELEVATION MODEL FOR ORTHOPHOTO CR PRODUCTION

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Z. Švec

2016-06-01

Full Text Available The Orthophoto CR is produced in co-operation with the Land Survey Office and the Military Geographical and Hydrometeorological Office. The product serves to ensure a defence of the state, integrated crisis management, civilian tasks in support of the state administration and the local self-government of the Czech Republic as well. It covers the whole area of the Republic and for ensuring its up-to-datedness is reproduced in the biennial period. As the project is countrywide, it keeps the project within the same parameters in urban and rural areas as well. Due to economic reasons it can´t be produced as a true ortophoto because it requires large side and forward overlaps of the aerial photographs and a preparation of the digital surface model instead of the digital terrain model. Use of DTM without some objects of DSM for orthogonalization purposes cause undesirable image deformations in the Orthophoto. There are a few data sets available for forming a suitable elevation model. The principal source should represent DTMs made from data acquired by the airborne laser scanning of the entire area of the Czech Republic that was carried out in the years 2009-2013, the DMR4G in the grid form and the DMR5G in TIN form respectively. It can be replenished by some vector objects (bridges, dams, etc. taken from the geographic base data of the Czech Republic or obtained by new stereo plotting. It has to be taken into account that the option of applying DSM made from image correlation is also available. The article focuses on the possibilities of DTM supplement for ortogonalization. It looks back to the recent transition from grid to hybrid elevation models, problems that occurred, its solution and getting some practical remarks. Afterwards it assesses the current state and deals with the options for updating the model. Some accuracy analysis are included.

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

Science.gov (United States)

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.

A new digital elevation model of Antarctica derived from CryoSat-2 altimetry

Science.gov (United States)

Slater, Thomas; Shepherd, Andrew; McMillan, Malcolm; Muir, Alan; Gilbert, Lin; Hogg, Anna E.; Konrad, Hannes; Parrinello, Tommaso

2018-05-01

We present a new digital elevation model (DEM) of the Antarctic ice sheet and ice shelves based on 2.5 × 108 observations recorded by the CryoSat-2 satellite radar altimeter between July 2010 and July 2016. The DEM is formed from spatio-temporal fits to elevation measurements accumulated within 1, 2, and 5 km grid cells, and is posted at the modal resolution of 1 km. Altogether, 94 % of the grounded ice sheet and 98 % of the floating ice shelves are observed, and the remaining grid cells north of 88° S are interpolated using ordinary kriging. The median and root mean square difference between the DEM and 2.3 × 107 airborne laser altimeter measurements acquired during NASA Operation IceBridge campaigns are -0.30 and 13.50 m, respectively. The DEM uncertainty rises in regions of high slope, especially where elevation measurements were acquired in low-resolution mode; taking this into account, we estimate the average accuracy to be 9.5 m - a value that is comparable to or better than that of other models derived from satellite radar and laser altimetry.

NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: Tampa (FL) WFO - Manatee, Sarasota, Charlotte, and Lee Counties

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This digital elevation model (DEM) is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Sea...

NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: Jacksonville (FL) WFO - St. Johns, Flagler and Putnam Counties

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This digital elevation model (DEM) is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Sea...

Hydrography-driven coarsening of grid digital elevation models

Science.gov (United States)

Moretti, G.; Orlandini, S.

2017-12-01

A new grid coarsening strategy, denoted as hydrography-driven (HD) coarsening, is developed in the present study. The HD coarsening strategy is designed to retain the essential hydrographic features of surface flow paths observed in high-resolution digital elevation models (DEMs): (1) depressions are filled in the considered high-resolution DEM, (2) the obtained topographic data are used to extract a reference grid network composed of all surface flow paths, (3) the Horton order is assigned to each link of the reference grid network, and (4) within each coarse grid cell, the elevation of the point lying along the highest-order path of the reference grid network and displaying the minimum distance to the cell center is assigned to this coarse grid cell center. The capabilities of the HD coarsening strategy to provide consistent surface flow paths with respect to those observed in high-resolution DEMs are evaluated over a synthetic valley and two real drainage basins located in the Italian Alps and in the Italian Apennines. The HD coarsening is found to yield significantly more accurate surface flow path profiles than the standard nearest neighbor (NN) coarsening. In addition, the proposed strategy is found to reduce drastically the impact of depression-filling procedures in coarsened topographic data. The HD coarsening strategy is therefore advocated for all those cases in which the relief of the extracted drainage network is an important hydrographic feature. The figure below reports DEMs of a synthetic valley and extracted surface flow paths. (a) 10-m grid DEM displaying no depressions and extracted surface flow path (gray line). (b) 1-km grid DEM obtained from NN coarsening. (c) 1-km grid DEM obtained from NN coarsening plus depression-filling and extracted surface flow path (light blue line). (d) 1-km grid DEM obtained from HD coarsening and extracted surface flow path (magenta line).

Slope Estimation from ICESat/GLAS

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Craig Mahoney

2014-10-01

Full Text Available We present a novel technique to infer ground slope angle from waveform LiDAR, known as the independent slope method (ISM. The technique is applied to large footprint waveforms (\\(\\sim\\ mean diameter from the Ice, Cloud and Land Elevation Satellite (ICESat Geoscience Laser Altimeter System (GLAS to produce a slope dataset of near-global coverage at \\(0.5^{\\circ} \\times 0.5^{\\circ}\\ resolution. ISM slope estimates are compared against high resolution airborne LiDAR slope measurements for nine sites across three continents. ISM slope estimates compare better with the aircraft data (R\\(^{2}=0.87\\ and RMSE\\(=5.16^{\\circ}\\ than the Shuttle Radar Topography Mission Digital Elevation Model (SRTM DEM inferred slopes (R\\(^{2}=0.71\\ and RMSE\\(=8.69^{\\circ}\\ ISM slope estimates are concurrent with GLAS waveforms and can be used to correct biophysical parameters, such as tree height and biomass. They can also be fused with other DEMs, such as SRTM, to improve slope estimates.

Soil-landscape modelling using fuzzy c-means clustering of attribute data derived from a Digital Elevation Model (DEM).

NARCIS (Netherlands)

Bruin, de S.; Stein, A.

1998-01-01

This study explores the use of fuzzy c-means clustering of attribute data derived from a digital elevation model to represent transition zones in the soil-landscape. The conventional geographic model used for soil-landscape description is not able to properly deal with these. Fuzzy c-means

An Image Matching Algorithm Integrating Global SRTM and Image Segmentation for Multi-Source Satellite Imagery

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Xiao Ling

2016-08-01

Full Text Available This paper presents a novel image matching method for multi-source satellite images, which integrates global Shuttle Radar Topography Mission (SRTM data and image segmentation to achieve robust and numerous correspondences. This method first generates the epipolar lines as a geometric constraint assisted by global SRTM data, after which the seed points are selected and matched. To produce more reliable matching results, a region segmentation-based matching propagation is proposed in this paper, whereby the region segmentations are extracted by image segmentation and are considered to be a spatial constraint. Moreover, a similarity measure integrating Distance, Angle and Normalized Cross-Correlation (DANCC, which considers geometric similarity and radiometric similarity, is introduced to find the optimal correspondences. Experiments using typical satellite images acquired from Resources Satellite-3 (ZY-3, Mapping Satellite-1, SPOT-5 and Google Earth demonstrated that the proposed method is able to produce reliable and accurate matching results.

Textured digital elevation model formation from low-cost UAV LADAR/digital image data

Science.gov (United States)

Bybee, Taylor C.; Budge, Scott E.

2015-05-01

Textured digital elevation models (TDEMs) have valuable use in precision agriculture, situational awareness, and disaster response. However, scientific-quality models are expensive to obtain using conventional aircraft-based methods. The cost of creating an accurate textured terrain model can be reduced by using a low-cost (processing step and enables both 2D- and 3D-image registration techniques to be used. This paper describes formation of TDEMs using simulated data from a small UAV gathering swaths of texel images of the terrain below. Being a low-cost UAV, only a coarse knowledge of position and attitude is known, and thus both 2D- and 3D-image registration techniques must be used to register adjacent swaths of texel imagery to create a TDEM. The process of creating an aggregate texel image (a TDEM) from many smaller texel image swaths is described. The algorithm is seeded with the rough estimate of position and attitude of each capture. Details such as the required amount of texel image overlap, registration models, simulated flight patterns (level and turbulent), and texture image formation are presented. In addition, examples of such TDEMs are shown and analyzed for accuracy.

Iowa Bedrock Surface Elevation

Data.gov (United States)

Iowa State University GIS Support and Research Facility — This Digital Elevation Model (DEM) of the bedrock surface elevation in Iowa was compiled using all available data, principally information from GEOSAM, supplemented...

NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: Tampa (FL) WFO - Citrus, Hernando, Pasco, Pinellas, and Hillsborough Counties

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This digital elevation model (DEM) is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Sea...

NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: Melbourne (FL) WFO - Indian River, St. Lucie, and Martin Counties

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This digital elevation model (DEM) is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Sea...

NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: Los Angeles/Oxnard (CA) WFO - Los Angeles and Ventura Counties

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This digital elevation model (DEM) is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Sea...

A new digital elevation model of Antarctica derived from CryoSat-2 altimetry

Directory of Open Access Journals (Sweden)

T. Slater

2018-05-01

Full Text Available We present a new digital elevation model (DEM of the Antarctic ice sheet and ice shelves based on 2.5 × 108 observations recorded by the CryoSat-2 satellite radar altimeter between July 2010 and July 2016. The DEM is formed from spatio-temporal fits to elevation measurements accumulated within 1, 2, and 5 km grid cells, and is posted at the modal resolution of 1 km. Altogether, 94 % of the grounded ice sheet and 98 % of the floating ice shelves are observed, and the remaining grid cells north of 88° S are interpolated using ordinary kriging. The median and root mean square difference between the DEM and 2.3 × 107 airborne laser altimeter measurements acquired during NASA Operation IceBridge campaigns are −0.30 and 13.50 m, respectively. The DEM uncertainty rises in regions of high slope, especially where elevation measurements were acquired in low-resolution mode; taking this into account, we estimate the average accuracy to be 9.5 m – a value that is comparable to or better than that of other models derived from satellite radar and laser altimetry.

Accuracy assessment of TanDEM-X IDEM using airborne LiDAR on the area of Poland

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Woroszkiewicz Małgorzata

2017-06-01

Full Text Available 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.

VERTICAL ACCURACY ASSESSMENT OF ZY-3 DIGITAL SURFACE MODEL USING ICESAT/GLAS LASER ALTIMETER DATA

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G. Li

2017-05-01

Full Text Available The Ziyuan-3 (ZY-3 satellite, as the first civilian high resolution surveying and mapping satellite in China, has a very important role in national 1 : 50,000 stereo mapping project. High accuracy digital surface Model (DSMs can be generated from the three line-array images of ZY-3, and ZY-3 DSMs of China can be produced without using any ground control points (GCPs by selecting SRTM (Shuttle Radar Topography Mission and ICESat/GLAS (Ice, Cloud, and land Elevation Satellite, Geo-science Laser Altimeter System as the datum reference in the Satellite Surveying and Mapping Application Center, which is the key institute that manages and distributes ZY-3 products. To conduct the vertical accuracy evaluation of ZY-3 DSMs of China, three representative regions were chosen and the results were compared to ICESat/GLAS data. The experimental results demonstrated that the root mean square error (RMSE elevation accuracy of the ZY-3 DSMs was better than 5.0 m, and it even reached to less than 2.5 m in the second region of eastern China. While this work presents preliminary results, it is an important reference for expanding the application of ZY-3 satellite imagery to widespread regions. And the satellite laser altimetry data can be used as referenced data for wide-area DSM evaluation.

Estuarine Bathymetric Digital Elevation Models (30 meter and 3 arc second resolution) Derived From Source Hydrographic Survey Soundings Collected by NOAA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — These Bathymetric Digital Elevation Models (DEM) were generated from original point soundings collected during hydrographic surveys conducted by the National Ocean...

Development of a LiDAR derived digital elevation model (DEM) as Input to a METRANS geographic information system (GIS).

Science.gov (United States)

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 ...

Object-based classification of global undersea topography and geomorphological features from the SRTM30_PLUS data

Science.gov (United States)

Dekavalla, Maria; Argialas, Demetre

2017-07-01

The analysis of undersea topography and geomorphological features provides necessary information to related disciplines and many applications. The development of an automated knowledge-based classification approach of undersea topography and geomorphological features is challenging due to their multi-scale nature. The aim of the study is to develop and evaluate an automated knowledge-based OBIA approach to: i) decompose the global undersea topography to multi-scale regions of distinct morphometric properties, and ii) assign the derived regions to characteristic geomorphological features. First, the global undersea topography was decomposed through the SRTM30_PLUS bathymetry data to the so-called morphometric objects of discrete morphometric properties and spatial scales defined by data-driven methods (local variance graphs and nested means) and multi-scale analysis. The derived morphometric objects were combined with additional relative topographic position information computed with a self-adaptive pattern recognition method (geomorphons), and auxiliary data and were assigned to characteristic undersea geomorphological feature classes through a knowledge base, developed from standard definitions. The decomposition of the SRTM30_PLUS data to morphometric objects was considered successful for the requirements of maximizing intra-object and inter-object heterogeneity, based on the near zero values of the Moran's I and the low values of the weighted variance index. The knowledge-based classification approach was tested for its transferability in six case studies of various tectonic settings and achieved the efficient extraction of 11 undersea geomorphological feature classes. The classification results for the six case studies were compared with the digital global seafloor geomorphic features map (GSFM). The 11 undersea feature classes and their producer's accuracies in respect to the GSFM relevant areas were Basin (95%), Continental Shelf (94.9%), Trough (88

Method for Measuring the Information Content of Terrain from Digital Elevation Models

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Lujin Hu

2015-10-01

Full Text Available As digital terrain models are indispensable for visualizing and modeling geographic processes, terrain information content is useful for terrain generalization and representation. For terrain generalization, if the terrain information is considered, the generalized terrain may be of higher fidelity. In other words, the richer the terrain information at the terrain surface, the smaller the degree of terrain simplification. Terrain information content is also important for evaluating the quality of the rendered terrain, e.g., the rendered web terrain tile service in Google Maps (Google Inc., Mountain View, CA, USA. However, a unified definition and measures for terrain information content have not been established. Therefore, in this paper, a definition and measures for terrain information content from Digital Elevation Model (DEM, i.e., a digital model or 3D representation of a terrain’s surface data are proposed and are based on the theory of map information content, remote sensing image information content and other geospatial information content. The information entropy was taken as the information measuring method for the terrain information content. Two experiments were carried out to verify the measurement methods of the terrain information content. One is the analysis of terrain information content in different geomorphic types, and the results showed that the more complex the geomorphic type, the richer the terrain information content. The other is the analysis of terrain information content with different resolutions, and the results showed that the finer the resolution, the richer the terrain information. Both experiments verified the reliability of the measurements of the terrain information content proposed in this paper.

NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: San Francisco Bay/Monterey (CA) WFO - Santa Cruz and Monterey Counties

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This digital elevation model (DEM) is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Sea...

NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: Seattle (WA) WFO - Clallam, Jefferson, Kitsap, Mason, Pierce, and Thurston Counties

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This digital elevation model (DEM) is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Sea...

Analysis the Accuracy of Digital Elevation Model (DEM) for Flood Modelling on Lowland Area

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Zainol Abidin, Ku Hasna Zainurin Ku; Razi, Mohd Adib Mohammad; Bukari, Saifullizan Mohd

2018-04-01

Flood is one type of natural disaster that occurs almost every year in Malaysia. Commonly the lowland areas are the worst affected areas. This kind of disaster is controllable by using an accurate data for proposing any kinds of solutions. Elevation data is one of the data used to produce solutions for flooding. Currently, the research about the application of Digital Elevation Model (DEM) in hydrology was increased where this kind of model will identify the elevation for required areas. University of Tun Hussein Onn Malaysia is one of the lowland areas which facing flood problems on 2006. Therefore, this area was chosen in order to produce DEM which focussed on University Health Centre (PKU) and drainage area around Civil and Environment Faculty (FKAAS). Unmanned Aerial Vehicle used to collect aerial photos data then undergoes a process of generating DEM according to three types of accuracy and quality from Agisoft PhotoScan software. The higher the level of accuracy and quality of DEM produced, the longer time taken to generate a DEM. The reading of the errors created while producing the DEM shows almost 0.01 different. Therefore, it has been identified there are some important parameters which influenced the accuracy of DEM.

Optimizing digital elevation models (DEMs) accuracy for planning and design of mobile communication networks

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Hassan, Mahmoud A.

2004-02-01

Digital elevation models (DEMs) are important tools in the planning, design and maintenance of mobile communication networks. This research paper proposes a method for generating high accuracy DEMs based on SPOT satellite 1A stereo pair images, ground control points (GCP) and Erdas OrthoBASE Pro image processing software. DEMs with 0.2911 m mean error were achieved for the hilly and heavily populated city of Amman. The generated DEM was used to design a mobile communication network resulted in a minimum number of radio base transceiver stations, maximum number of covered regions and less than 2% of dead zones.

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

Science.gov (United States)

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.

NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: Los Angeles/Oxnard (CA) WFO - Santa Barbara and San Luis Obispo Counties

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This digital elevation model (DEM) is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Sea...

NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: Seattle (WA) WFO - Whatcom, San Juan, Skagit, Island, Snohomish, and King Counties

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This digital elevation model (DEM) is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Sea...

NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: Miami (FL) WFO - Palm Beach, Broward, Miami-Dade, and Monroe (Keys) Counties

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This digital elevation model (DEM) is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Sea...

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

Science.gov (United States)

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

Parabolic Equation Modeling of Propagation over Terrain Using Digital Elevation Model

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Xiao-Wei Guan

2018-01-01

Full Text Available The parabolic equation method based on digital elevation model (DEM is applied on propagation predictions over irregular terrains. Starting from a parabolic approximation to the Helmholtz equation, a wide-angle parabolic equation is deduced under the assumption of forward propagation and the split-step Fourier transform algorithm is used to solve it. The application of DEM is extended to the Cartesian coordinate system and expected to provide a precise representation of a three-dimensional surface with high efficiency. In order to validate the accuracy, a perfectly conducting Gaussian terrain profile is simulated and the results are compared with the shift map. As a consequence, a good agreement is observed. Besides, another example is given to provide a theoretical basis and reference for DEM selection. The simulation results demonstrate that the prediction errors will be obvious only when the resolution of the DEM used is much larger than the range step in the PE method.

Satellite remote sensing of landscape freeze/thaw state dynamics for complex Topography and Fire Disturbance Areas Using multi-sensor radar and SRTM digital elevation models

Science.gov (United States)

Podest, Erika; McDonald, Kyle; Kimball, John; Randerson, James

2003-01-01

We characterize differences in radar-derived freeze/thaw state, examining transitions over complex terrain and landscape disturbance regimes. In areas of complex terrain, we explore freezekhaw dynamics related to elevation, slope aspect and varying landcover. In the burned regions, we explore the timing of seasonal freeze/thaw transition as related to the recovering landscape, relative to that of a nearby control site. We apply in situ biophysical measurements, including flux tower measurements to validate and interpret the remotely sensed parameters. A multi-scale analysis is performed relating high-resolution SAR backscatter and moderate resolution scatterometer measurements to assess trade-offs in spatial and temporal resolution in the remotely sensed fields.

Improving salt marsh digital elevation model accuracy with full-waveform lidar and nonparametric predictive modeling

Science.gov (United States)

Rogers, Jeffrey N.; Parrish, Christopher E.; Ward, Larry G.; Burdick, David M.

2018-03-01

Salt marsh vegetation tends to increase vertical uncertainty in light detection and ranging (lidar) derived elevation data, often causing the data to become ineffective for analysis of topographic features governing tidal inundation or vegetation zonation. Previous attempts at improving lidar data collected in salt marsh environments range from simply computing and subtracting the global elevation bias to more complex methods such as computing vegetation-specific, constant correction factors. The vegetation specific corrections can be used along with an existing habitat map to apply separate corrections to different areas within a study site. It is hypothesized here that correcting salt marsh lidar data by applying location-specific, point-by-point corrections, which are computed from lidar waveform-derived features, tidal-datum based elevation, distance from shoreline and other lidar digital elevation model based variables, using nonparametric regression will produce better results. The methods were developed and tested using full-waveform lidar and ground truth for three marshes in Cape Cod, Massachusetts, U.S.A. Five different model algorithms for nonparametric regression were evaluated, with TreeNet's stochastic gradient boosting algorithm consistently producing better regression and classification results. Additionally, models were constructed to predict the vegetative zone (high marsh and low marsh). The predictive modeling methods used in this study estimated ground elevation with a mean bias of 0.00 m and a standard deviation of 0.07 m (0.07 m root mean square error). These methods appear very promising for correction of salt marsh lidar data and, importantly, do not require an existing habitat map, biomass measurements, or image based remote sensing data such as multi/hyperspectral imagery.

Digital elevation models for site investigation programme in Oskarshamn. Site description version 1.2

International Nuclear Information System (INIS)

Brydsten, Lars; Stroemgren, Maarten

2005-06-01

In the Oskarshamn area, a digital elevation model has been produced using elevation data from many elevation sources on both land and sea. Many elevation model users are only interested in elevation models over land, so the model has been designed in three versions: Version 1 describes land surface, lake water surface, and sea bottom. Version 2 describes land surface, sediment levels at lake bottoms, and sea bottoms. Version 3 describes land surface, sediment levels at lake bottoms, and sea surface. In cases where the different sources of data were not in point form 'such as existing elevation models of land or depth lines from nautical charts' they have been converted to point values using GIS software. Because data from some sources often overlaps with data from other sources, several tests were conducted to determine if both sources of data or only one source would be included in the dataset used for the interpolation procedure. The tests resulted in the decision to use only the source judged to be of highest quality for most areas with overlapping data sources. All data were combined into a database of approximately 3.3 million points unevenly spread over an area of about 800 km 2 . The large number of data points made it difficult to construct the model with a single interpolation procedure, the area was divided into 28 sub-models that were processed one by one and finally merged together into one single model. The software ArcGis 8.3 and its extension Geostatistical Analysis were used for the interpolation. The Ordinary Kriging method was used for interpolation. This method allows both a cross validation and a validation before the interpolation is conducted. Cross validation with different Kriging parameters were performed and the model with the most reasonable statistics was chosen. Finally, a validation with the most appropriate Kriging parameters was performed in order to verify that the model fit unmeasured localities. Since both the quality and the

Analisis Zona Permeabel Fluida Sistem Panas Bumi Gunungapi Slamet Berdasarkan Analisis Kerapatan Kelurusan Citra SRTM Dan Struktur Geologi

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Sachrul Iswahyudi

2016-03-01

Full Text Available Keberadaan manifestasi panasbumi di sekitar Gunungapi Slamet tidak dapat dipisahkan dari zona-zona permeabilitas yang berkembang. Lokasi-lokasi lulus air tersebut (zona permeabel yang memungkinkan terbentuknya sirkulasi fluida tempat air masuk untuk mengisi reservoir panas bumi dan air keluar ke permukaan bumi sebagai manifesatasi mata air panasbumi di sekitar Gunungapi Slamet. Publikasi yang berupa hasil penelitian ini mencoba mengidentifikasi zona-zona permeabel tersebut berdasarkan anaslisis kerapatan kelurusan yang terekam dalam citra SRTM. Identifikasi kelurusan-kelurusan pada citra berdasarkan komponen-komponen interpretasi citra, yaitu tona, tekstur, pola, bentuk dan relief. Hasil analisis tersebut dikompilasi dengan data struktur geologi regional yang sebelumnya telah diidentifikasi dan data lapangan berupa manifestasi mata air panas. Lokasi-lokasi dengan kerapatan kelurusan yang tinggi pada citra SRTM umumnya bersesuaian dengan zona struktur geologi regional keberadaan manifestasi mata air panas. Daerah tersebut memanjang relatif utara-selatan di bagian barat dan timur-barat di bagian selatan peta. Daerah-daerah inilah yang merupakan daerah lulus air tempat fluida bersirkulasi membentuk sistem panasbumi Gunungapi Slamet.

Guiana Highlands, Shaded Relief and Colored Height

Science.gov (United States)

2003-01-01

[figure removed for brevity, see original site] These two images show exactly the same area in South America, the Guiana Highlands straddling the borders of Venezuela, Guyana and Brazil. The image on the left was created using the best global topographic data set previously available, the U.S. Geological Survey's GTOPO30. In contrast, the image on the right was generated with a new data set recently released by the Shuttle Radar Topography Mission (SRTM) called SRTM30, which represents a significant improvement in our knowledge of the topography of much of the world.GTOPO30, with a resolution of about 928 meters (1496 feet), was developed over a three-year period and published in 1996, and since then has been the primary source of digital elevation data for scientists and analysts involved in global studies. However, since it was compiled from a number of different map sources with varying attributes, the data for some parts of the globe were inconsistent or of low quality.The SRTM data, on the other hand, were collected within a ten-day period using the same instrument in a uniform fashion, and were processed into elevation data using consistent processing techniques. Thus SRTM30 provides a new resource of uniform quality for all parts of the Earth, and since the data, which have an intrinsic resolution of about 30 meters, were averaged and resampled to match the GTOPO30 sample spacing and format, and can be used by the same computer software without modification.The Guiana Highlands are part of the Guyana Shield, which lies in northeast South America and represent one of the oldest land surfaces in the world. Chemical weathering over many millions of years has created a landscape of flat-topped table mountains with dramatic, steep cliffs with a large number of spectacular waterfalls. For example Angel Falls, at 979 meters the highest waterfall in the world, plunges from Auyan Tebuy, part of a mesa of the type that may have been the inspiration for Arthur Conan

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

Science.gov (United States)

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

2016-01-01

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. PMID:27164457

MAPPING OF THE RUSSIAN NORTHERN SEAS BOTTOM RELIEF USING DIGITAL ELEVATION MODELS

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S. M. Koshel

2014-01-01

Full Text Available The task of the project is the design of the digital elevation models (DEM of the bottoms of Barents Sea, Pechora Sea, and the White Sea. Accuracy (resolution of DEMs allows for adequate delineation of morphological structures and peculiarities of the sea bottoms and the design of bathymetrical and derivative maps. DEMs of the sea bottom were compiled using data from navigation charts of different scales, where additional isobaths were drawn manually taking into account the classification features of the bottom topography forms. Next procedures were carried out: scanning of these charts, processing of scanned images, isobaths vectorization and creation of attribute tables, vector layers transformation to geographical coordinates as well editing, merging and joining of the map sheets, correction of geometry and attributes. For generation of digital model of bottom topography it is important to choose algorithm which allows for representation all of the sea bottom features expressed by isobaths in most details. The original algorithm based on fast calculation of distances to the two different nearest isobaths was used. Interpretation of isolines as vector linear objects is the main peculiarity of this algorithm. The resulted DEMs were used to design bathymetrical maps of Barents Sea of 1:2 500 000 scale, Pechora Sea of 1:1 000 000 scale, and White Sea of 1:750 000 scale. Different derivative maps were compiled based on DEM of the White Sea.

Mapeo de lineamientos a partir de un DEM (SRTM3: desarrollo y aplicaciones para el estudio de un área de los Andes Patagónicos Septentrionales

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Ernesto Gallegos

2008-12-01

correlación entre lineamientos obtenidos con la técnica presentada y geología, fallas y fracturas sugiere que los DEM pueden ser un componente importante en el mapeo geológico. Sin embargo, los lineamientos regionales obtenidos deben ser contrastados con la información estructural obtenida en el campo.This paper explores the usefulness of mapping lineaments with shaded relief maps produced by satellite image analysis software from Digital Elevation Models (DEM of three seconds spatial resolution. The area of study is located between 39ºS and 39º30´S and between 71ºW and 71º30'W and three shaded relief maps were use with incident light at 45º from the horizontal and azimuths of 120º, 240º and 360º. Three operators mapped lineaments separately in the different images obtaining a result of nine independent maps. Reproducible lineaments were considered only those mapped in at least two shaded relief maps by at least two operators or by three operators in at least one image, in the end 23 lineaments were obtained. The tendencies observed were 55º, 106º, 140º and 153º. These lineaments were compared with lineaments mapped in a GeoCoverTM Landsat Enhanced Thematic Mapper Imagery ortorrectified compressed mosaic, in the geologic map 1:200.000 (SEGEMAR and in topographic maps 1: 50.000 (IGM. Some lineaments that were clearly identified with the DEM were not observed in the geological and topographic maps or in the Landsat imagery. The authors consider there are certain advantages in applying digital elevation models in the mapping of regional lineaments: 1 the users can control the incident angle and its azimuth; 2 The working scale can be change as needed; 3 in contrast to aerial photography, the satellite data have no deformation and it doesn't show any kind influences with anthropologic features or interference in the interpretation due to vegetation. Another advantage of the DEM (SRTM3 V2 and the GeoCoverT image used in this procedure is that the data is for

Brief communication: Unabated wastage of the Juneau and Stikine icefields (southeast Alaska) in the early 21st century

Science.gov (United States)

Berthier, Etienne; Larsen, Christopher; Durkin, William J.; Willis, Michael J.; Pritchard, Matthew E.

2018-04-01

The large Juneau and Stikine icefields (Alaska) lost mass rapidly in the second part of the 20th century. Laser altimetry, gravimetry and field measurements suggest continuing mass loss in the early 21st century. However, two recent studies based on time series of Shuttle Radar Topographic Mission (SRTM) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) digital elevation models (DEMs) indicate a slowdown in mass loss after 2000. Here, the ASTER-based geodetic mass balances are recalculated carefully avoiding the use of the SRTM DEM because of the unknown penetration depth of the C-band radar signal. We find strongly negative mass balances from 2000 to 2016 (-0.68 ± 0.15 m w.e. a-1 for the Juneau Icefield and -0.83 ± 0.12 m w.e. a-1 for the Stikine Icefield), in agreement with laser altimetry, confirming that mass losses are continuing at unabated rates for both icefields. The SRTM DEM should be avoided or used very cautiously to estimate glacier volume change, especially in the North Hemisphere and over timescales of less than ˜ 20 years.

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

Science.gov (United States)

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

ASTER Global Digital Elevation Model Version 2 - summary of validation results

Science.gov (United States)

Tachikawa, Tetushi; Kaku, Manabu; Iwasaki, Akira; Gesch, Dean B.; Oimoen, Michael J.; Zhang, Z.; Danielson, Jeffrey J.; Krieger, Tabatha; Curtis, Bill; Haase, Jeff; Abrams, Michael; Carabajal, C.; Meyer, Dave

2011-01-01

On June 29, 2009, NASA and the Ministry of Economy, Trade and Industry (METI) of Japan released a Global Digital Elevation Model (GDEM) to users worldwide at no charge as a contribution to the Global Earth Observing System of Systems (GEOSS). This “version 1” ASTER GDEM (GDEM1) was compiled from over 1.2 million scenebased DEMs covering land surfaces between 83°N and 83°S latitudes. A joint U.S.-Japan validation team assessed the accuracy of the GDEM1, augmented by a team of 20 cooperators. The GDEM1 was found to have an overall accuracy of around 20 meters at the 95% confidence level. The team also noted several artifacts associated with poor stereo coverage at high latitudes, cloud contamination, water masking issues and the stacking process used to produce the GDEM1 from individual scene-based DEMs (ASTER GDEM Validation Team, 2009). Two independent horizontal resolution studies estimated the effective spatial resolution of the GDEM1 to be on the order of 120 meters.

Digital elevation models for site investigation programme in Oskarshamn. Site description version 1.2

Energy Technology Data Exchange (ETDEWEB)

Brydsten, Lars; Stroemgren, Maarten [Umeaa Univ. (Sweden). Dept. of Biology and Environmental Science

2005-06-01

In the Oskarshamn area, a digital elevation model has been produced using elevation data from many elevation sources on both land and sea. Many elevation model users are only interested in elevation models over land, so the model has been designed in three versions: Version 1 describes land surface, lake water surface, and sea bottom. Version 2 describes land surface, sediment levels at lake bottoms, and sea bottoms. Version 3 describes land surface, sediment levels at lake bottoms, and sea surface. In cases where the different sources of data were not in point form 'such as existing elevation models of land or depth lines from nautical charts' they have been converted to point values using GIS software. Because data from some sources often overlaps with data from other sources, several tests were conducted to determine if both sources of data or only one source would be included in the dataset used for the interpolation procedure. The tests resulted in the decision to use only the source judged to be of highest quality for most areas with overlapping data sources. All data were combined into a database of approximately 3.3 million points unevenly spread over an area of about 800 km{sup 2}. The large number of data points made it difficult to construct the model with a single interpolation procedure, the area was divided into 28 sub-models that were processed one by one and finally merged together into one single model. The software ArcGis 8.3 and its extension Geostatistical Analysis were used for the interpolation. The Ordinary Kriging method was used for interpolation. This method allows both a cross validation and a validation before the interpolation is conducted. Cross validation with different Kriging parameters were performed and the model with the most reasonable statistics was chosen. Finally, a validation with the most appropriate Kriging parameters was performed in order to verify that the model fit unmeasured localities. Since both the

Using digital elevation models as an environmental predictor for soil clay contents

DEFF Research Database (Denmark)

Greve, Mogens Humlekrog; Bou Kheir, Rania; Greve, Mette Balslev

2012-01-01

resolution) explained the variability of SCC measurements quasi-similarly (variance V = 60%) to the LIDAR tree models with 24-m (T2) or 90-m (T3) resolution (V = 60% for T2 and 61.5% for T3). The prediction performances (in terms of RMSE) of the produced maps (using these trees) compared with independent...... field observations from the validation data set (9000 sites) were estimated as follows: Map T1, RMSE = 3.57%; Map T2, RMSE = 3.25%; and Map T3, RMSE = 3.15%. The relative improvement of T2 compared with T1 or T3 varied between 8.96 and 11.76%, respectively. Independent validation data also reflected...... higher correlations between measured SCC and SCC predicted from T2 (R2 = 0.60) compared with the other tree models (T1, R2 = 0.56; T3, R2 = 0.54). The modeling results indicate that the SRTM (including derivatives) has less predictive power than the LIDAR DEMs (with different resolutions) for mapping SCC...

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

DEFF Research Database (Denmark)

Korsgaard, Niels J.; Nuth, Christopher; Khan, Shfaqat Abbas

2016-01-01

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...... 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 generation from satellite interferometric synthetic aperture radar: Chapter 5

Science.gov (United States)

Lu, Zhong; Dzurisin, Daniel; Jung, Hyung-Sup; Zhang, Lei; Lee, Wonjin; Lee, Chang-Wook

2012-01-01

An accurate digital elevation model (DEM) is a critical data set for characterizing the natural landscape, monitoring natural hazards, and georeferencing satellite imagery. The ideal interferometric synthetic aperture radar (InSAR) configuration for DEM production is a single-pass two-antenna system. Repeat-pass single-antenna satellite InSAR imagery, however, also can be used to produce useful DEMs. DEM generation from InSAR is advantageous in remote areas where the photogrammetric approach to DEM generation is hindered by inclement weather conditions. There are many sources of errors in DEM generation from repeat-pass InSAR imagery, for example, inaccurate determination of the InSAR baseline, atmospheric delay anomalies, and possible surface deformation because of tectonic, volcanic, or other sources during the time interval spanned by the images. This chapter presents practical solutions to identify and remove various artifacts in repeat-pass satellite InSAR images to generate a high-quality DEM.

Automatic delimitation of microwatershed using SRTM data of the NASA

Directory of Open Access Journals (Sweden)

Freddy Aníbal Jumbo Castillo

2015-12-01

Full Text Available The watershed as the basic territorial unit of planning and management of water resources, requires its proper delimitation of the catchment or drainage area, faced with this situation, the lack of geographic information of Casacay river micro watersheds, hydrographic unit should be resolved, for this purpose the research was aimed at automatic delimitation of micro watersheds using of Geographic Information Systems (GIS techniques and the project Shuttle Radar Topographic Mission (SRTM 30 meters spatial resolution data. The selected methodology was the Pfafstetter one, with which nine micro watersheds were obtained with their respective codification allowing to continue with watersheds standardization adopted by Ecuador Water's Secretariat. With the investigation results watersheds will be updated with more detail information, promoting the execution of tasks or activities related to the integrated management of the hydrographic unit studied

TecDEM: A MATLAB Based Toolbox for understanding Tectonics from Digital Elevation Models

Science.gov (United States)

Shahzad, F.; Mahmood, S. A.; Gloaguen, R.

2009-04-01

TecDEM is a MATLAB based tool box for understanding the tectonics from digital elevation models (DEMs) of any area. These DEMs can be derived from data of any spatial resolution (Low, medium and High). In the first step we extract drainage network from the DEMs using flow grid approach. Drainage network is a group of streams having elevation and catchment area information as a function of spatial locations. We implement an array of stream structure to study this drainage network. Knickpoints can be identified on each stream of the drainage network by a graphical user interface and are helpful for understanding stream morphology. Stream profile analysis in steady state condition is applied on all streams to calculate geomorphic parameters and regional uplift rates. Hack index is calculated for all the profiles at a certain interval and over the change of knickpoints. Reports menu of this tool box generates detailed statistics report, complete tabulated report, graphical output of each analyzed stream profile and Hack index profile. All the calculated values are part of stream structure and is saved as .mat file for later use with this tool box. The spatial distribution of geomorphic parameters, uplift rates and knickpoints are exported as a shape files for visualization in professional GIS software. We test this tool box on DEMs from different tectonic settings worldwide and received verifiable results with other studies.

An Alternative Approach of Coastal Sea-Level Observation from Remote Sensing Imageries

Science.gov (United States)

Peng, H. Y.; Tseng, K. H.; Chung-Yen, K.; Lin, T. H.; Liao, W. H.; Chen, C. F.

2017-12-01

Coastal sea level can be observed as waterline changes along a coastal digital elevation model (DEM). However, most global DEMs, such as the Shuttle Radar Topography Mission (SRTM) DEM with 30 m resolution, provide limited coverage over coastal area due to the impermeability of radar signal over water and the lack of low-tide coincidence. Therefore, we aim to extend to coverage of SRTM DEM for the determination of intertidal zone and to monitor sea-level changes along the entire coastline of Taiwan (>1200km). We firstly collect historical cloud-free images since the 1980s, including Landsat series, SPOT series and Sentinel-2, and then calculate the Modified Normalized Difference Water Index (MNDWI) to identify water pixels. After computing water appearance probability of each pixel, it is converted into actual elevation by introducing the DTU10 tide model for high tide and low tide boundaries. A coastal DEM of intertidal zone is reconstructed and the accuracy is at 50 cm level as compared with in situ DEM built by an unmanned aerial vehicle (UAV). Finally, we use this product to define the up-to-date intertidal zone and estimate sea-level changes by using remote sensing snapshots.

3D Fractal reconstruction of terrain profile data based on digital elevation model

International Nuclear Information System (INIS)

Huang, Y.M.; Chen, C.-J.

2009-01-01

Digital Elevation Model (DEM) often makes it difficult for terrain reconstruction and data storage due to the failure in acquisition of details with higher resolution. If original terrain of DEM can be simulated, resulting in geographical details can be represented precisely while reducing the data size, then an effective reconstruction scheme is essential. This paper adopts two sets of real-world 3D terrain profile data to proceed data reducing, i.e. data sampling randomly, then reconstruct them through 3D fractal reconstruction. Meanwhile, the quantitative and qualitative difference generated from different reduction rates were evaluated statistically. The research results show that, if 3D fractal interpolation method is applied to DEM reconstruction, the higher reduction rate can be obtained for DEM of larger data size with respect to that of smaller data size under the assumption that the entire terrain structure is still maintained.

Uncertainty aspects of the digital elevation model for the Forsmark area

Energy Technology Data Exchange (ETDEWEB)

Stroemgren, Maarten; Brydsten, Lars (Umeaa Univ., Umeaa (Sweden))

2009-10-15

A digital elevation model (DEM) describes the terrain relief. A proper DEM is an important data source for many of the different site description models conducted in the Forsmark region. Input data for the Forsmark DEM is elevation data for both land and sea areas of different origin and quality. No statistical analysis of the error in the Forsmark DEM is so far carried out. However, the Forsmark DEM is part of the quality assessment of the regolith depth model for the Forsmark area since it represents the upper surface of the regolith depth model. The aim of this project was to calculate the errors in different areas in the Forsmark DEM and present them in terms of general descriptive statistics. Measurements have confirmed the knowledge that the 0.25-metre DEM produced from the laser scanning measurements in the Laxemar-Simpevarp area is of very high quality. The 0.25-metre DEM was used to calculate the errors of the 10 and 50-metre DEMs, and the errors for different sea shoreline sources. These error distributions were placed randomly among points for the same data sources in the Forsmark area and used for correction of the original elevation levels. Using the corrected input data for the 10 and 50-metre DEMs and for the sea shoreline, a new DEM was produced. All other input data remained unchanged. The error for the Forsmark DEM was calculated for areas within the data sources corrected from the 0.25-metre DEM. The 0.25-metre DEM from the Laxemar-Simpevarp area was also used for a calculation of how density of input data points used in interpolation affects quality in a 20-metre DEM. Part of the input data was removed in the sea area, new DEMs were produced and compared to the existing Forsmark DEM within the areas of the removed data, to get a measure of the error in these areas of the DEM. In areas of input data for the sea shoreline, the quality of the Forsmark DEM is high. The errors within the SKB 10-metre DEM are slightly less than within the extension

Uncertainty aspects of the digital elevation model for the Forsmark area

International Nuclear Information System (INIS)

Stroemgren, Maarten; Brydsten, Lars

2009-10-01

A digital elevation model (DEM) describes the terrain relief. A proper DEM is an important data source for many of the different site description models conducted in the Forsmark region. Input data for the Forsmark DEM is elevation data for both land and sea areas of different origin and quality. No statistical analysis of the error in the Forsmark DEM is so far carried out. However, the Forsmark DEM is part of the quality assessment of the regolith depth model for the Forsmark area since it represents the upper surface of the regolith depth model. The aim of this project was to calculate the errors in different areas in the Forsmark DEM and present them in terms of general descriptive statistics. Measurements have confirmed the knowledge that the 0.25-metre DEM produced from the laser scanning measurements in the Laxemar-Simpevarp area is of very high quality. The 0.25-metre DEM was used to calculate the errors of the 10 and 50-metre DEMs, and the errors for different sea shoreline sources. These error distributions were placed randomly among points for the same data sources in the Forsmark area and used for correction of the original elevation levels. Using the corrected input data for the 10 and 50-metre DEMs and for the sea shoreline, a new DEM was produced. All other input data remained unchanged. The error for the Forsmark DEM was calculated for areas within the data sources corrected from the 0.25-metre DEM. The 0.25-metre DEM from the Laxemar-Simpevarp area was also used for a calculation of how density of input data points used in interpolation affects quality in a 20-metre DEM. Part of the input data was removed in the sea area, new DEMs were produced and compared to the existing Forsmark DEM within the areas of the removed data, to get a measure of the error in these areas of the DEM. In areas of input data for the sea shoreline, the quality of the Forsmark DEM is high. The errors within the SKB 10-metre DEM are slightly less than within the extension

2012 NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: Mobile/Tallahassee (AL/FL) WFO - Wakulla (portion), Franklin (portion), Jefferson, Taylor, Dixie, and Levy Counties

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This digital elevation model (DEM) is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Sea...

A guide for the use of digital elevation model data for making soil surveys

Science.gov (United States)

Klingebiel, A.A.; Horvath, Emil H.; Reybold, William U.; Moore, D.G.; Fosnight, E.A.; Loveland, Thomas R.

1988-01-01

The intent of this publication is twofold: (1) to serve as a user guide for soil scientists and others interested in learning about the value and use of digital elevation model (DEM) data in making soil surveys and (2) to provide documentation of the Soil Landscape Analysis Project (SLAP). This publication provides a step-by-step guide on how digital slope-class maps are adjusted to topographic maps and orthophotoquads to obtain accurate slope-class maps, and how these derivative maps can be used as a base for soil survey premaps. In addition, guidance is given on the use of aspect-class maps and other resource data in making pre-maps. The value and use of tabular summaries are discussed. Examples of the use of DEM products by the authors and by selected field soil scientists are also given. Additional information on SLAP procedures may be obtained from USDA, Soil Conservation Service, Soil Survey Division, P.O. Box 2890, Washington, D.C. 20013, and from references (Horvath and others, 1987; Horvath and others, 1983; Klingebiel and others, 1987; and Young, 1987) listed in this publication. The slope and aspect products and the procedures for using these products have evolved during 5 years of cooperative research with the USDA, Soil Conservation Service and Forest Service, and the USDI, Bureau of Land Management.

Gradient based filtering of digital elevation models

DEFF Research Database (Denmark)

Knudsen, Thomas; Andersen, Rune Carbuhn

We present a filtering method for digital terrain models (DTMs). The method is based on mathematical morphological filtering within gradient (slope) defined domains. The intention with the filtering procedure is to improbé the cartographic quality of height contours generated from a DTM based...

VERTICAL ACCURACY COMPARISON OF DIGITAL ELEVATION MODEL FROM LIDAR AND MULTITEMPORAL SATELLITE IMAGERY

Directory of Open Access Journals (Sweden)

J. Octariady

2017-05-01

Full Text Available Digital elevation model serves to illustrate the appearance of the earth's surface. DEM can be produced from a wide variety of data sources including from radar data, LiDAR data, and stereo satellite imagery. Making the LiDAR DEM conducted using point cloud data from LiDAR sensor. Making a DEM from stereo satellite imagery can be done using same temporal or multitemporal stereo satellite imagery. How much the accuracy of DEM generated from multitemporal stereo stellite imagery and LiDAR data is not known with certainty. The study was conducted using LiDAR DEM data and multitemporal stereo satellite imagery DEM. Multitemporal stereo satellite imagery generated semi-automatically by using 3 scene stereo satellite imagery with acquisition 2013–2014. The high value given each of DEM serve as the basis for calculating high accuracy DEM respectively. The results showed the high value differences in the fraction of the meter between LiDAR DEM and multitemporal stereo satellite imagery DEM.

Construction of a digital elevation model: methods and parallelization

International Nuclear Information System (INIS)

Mazzoni, Christophe

1995-01-01

The aim of this work is to reduce the computation time needed to produce the Digital Elevation Models (DEM) by using a parallel machine. It is made in collaboration between the French 'Institut Geographique National' (IGN) and the Laboratoire d'Electronique de Technologie et d'Instrumentation (LETI) of the French Atomic Energy Commission (CEA). The IGN has developed a system which provides DEM that is used to produce topographic maps. The kernel of this system is the correlator, a software which automatically matches pairs of homologous points of a stereo-pair of photographs. Nevertheless the correlator is expensive In computing time. In order to reduce computation time and to produce the DEM with same accuracy that the actual system, we have parallelized the IGN's correlator on the OPENVISION system. This hardware solution uses a SIMD (Single Instruction Multiple Data) parallel machine SYMPATI-2, developed by the LETI that is involved in parallel architecture and image processing. Our analysis of the implementation has demonstrated the difficulty of efficient coupling between scalar and parallel structure. So we propose solutions to reinforce this coupling. In order to accelerate more the processing we evaluate SYMPHONIE, a SIMD calculator, successor of SYMPATI-2. On an other hand, we developed a multi-agent approach for what a MIMD (Multiple Instruction, Multiple Data) architecture is available. At last, we describe a Multi-SIMD architecture that conciliates our two approaches. This architecture offers a capacity to apprehend efficiently multi-level treatment image. It is flexible by its modularity, and its communication network supplies reliability that interest sensible systems. (author) [fr

Bathymetric survey and digital elevation model of Little Holland Tract, Sacramento-San Joaquin Delta, California

Science.gov (United States)

Snyder, Alexander G.; Lacy, Jessica R.; Stevens, Andrew W.; Carlson, Emily M.

2016-06-10

The U.S. Geological Survey conducted a bathymetric survey in Little Holland Tract, a flooded agricultural tract, in the northern Sacramento-San Joaquin Delta (the “Delta”) during the summer of 2015. The new bathymetric data were combined with existing data to generate a digital elevation model (DEM) at 1-meter resolution. Little Holland Tract (LHT) was historically diked off for agricultural uses and has been tidally inundated since an accidental levee breach in 1983. Shallow tidal regions such as LHT have the potential to improve habitat quality in the Delta. The DEM of LHT was developed to support ongoing studies of habitat quality in the area and to provide a baseline for evaluating future geomorphic change. The new data comprise 138,407 linear meters of real-time-kinematic (RTK) Global Positioning System (GPS) elevation data, including both bathymetric data collected from personal watercraft and topographic elevations collected on foot at low tide. A benchmark (LHT15_b1) was established for geodetic control of the survey. Data quality was evaluated both by comparing results among surveying platforms, which showed systematic offsets of 1.6 centimeters (cm) or less, and by error propagation, which yielded a mean vertical uncertainty of 6.7 cm. Based on the DEM and time-series measurements of water depth, the mean tidal prism of LHT was determined to be 2,826,000 cubic meters. The bathymetric data and DEM are available at http://dx.doi.org/10.5066/F7RX9954. 

A new 100-m Digital Elevation Model of the Antarctic Peninsula derived from ASTER Global DEM: methods and accuracy assessment

Directory of Open Access Journals (Sweden)

A. J. Cook

2012-10-01

Full Text Available A high resolution surface topography Digital Elevation Model (DEM is required to underpin studies of the complex glacier system on the Antarctic Peninsula. A complete DEM with better than 200 m pixel size and high positional and vertical accuracy would enable mapping of all significant glacial basins and provide a dataset for glacier morphology analyses. No currently available DEM meets these specifications. We present a new 100-m DEM of the Antarctic Peninsula (63–70° S, based on ASTER Global Digital Elevation Model (GDEM data. The raw GDEM products are of high-quality on the rugged terrain and coastal-regions of the Antarctic Peninsula and have good geospatial accuracy, but they also contain large errors on ice-covered terrain and we seek to minimise these artefacts. Conventional data correction techniques do not work so we have developed a method that significantly improves the dataset, smoothing the erroneous regions and hence creating a DEM with a pixel size of 100 m that will be suitable for many glaciological applications. We evaluate the new DEM using ICESat-derived elevations, and perform horizontal and vertical accuracy assessments based on GPS positions, SPOT-5 DEMs and the Landsat Image Mosaic of Antarctica (LIMA imagery. The new DEM has a mean elevation difference of −4 m (± 25 m RMSE from ICESat (compared to −13 m mean and ±97 m RMSE for the original ASTER GDEM, and a horizontal error of less than 2 pixels, although elevation accuracies are lower on mountain peaks and steep-sided slopes. The correction method significantly reduces errors on low relief slopes and therefore the DEM can be regarded as suitable for topographical studies such as measuring the geometry and ice flow properties of glaciers on the Antarctic Peninsula. The DEM is available for download from the NSIDC website: http://nsidc.org/data/nsidc-0516.html (Brief communication: Unabated wastage of the Juneau and Stikine icefields (southeast Alaska in the early 21st century

Directory of Open Access Journals (Sweden)

E. Berthier

2018-04-01

Full Text Available The large Juneau and Stikine icefields (Alaska lost mass rapidly in the second part of the 20th century. Laser altimetry, gravimetry and field measurements suggest continuing mass loss in the early 21st century. However, two recent studies based on time series of Shuttle Radar Topographic Mission (SRTM and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER digital elevation models (DEMs indicate a slowdown in mass loss after 2000. Here, the ASTER-based geodetic mass balances are recalculated carefully avoiding the use of the SRTM DEM because of the unknown penetration depth of the C-band radar signal. We find strongly negative mass balances from 2000 to 2016 (−0.68 ± 0.15 m w.e. a−1 for the Juneau Icefield and −0.83 ± 0.12 m w.e. a−1 for the Stikine Icefield, in agreement with laser altimetry, confirming that mass losses are continuing at unabated rates for both icefields. The SRTM DEM should be avoided or used very cautiously to estimate glacier volume change, especially in the North Hemisphere and over timescales of less than  ∼  20 years.

New metrics for evaluating channel networks extracted in grid digital elevation models

Science.gov (United States)

Orlandini, S.; Moretti, G.

2017-12-01

Channel networks are critical components of drainage basins and delta regions. Despite the important role played by these systems in hydrology and geomorphology, there are at present no well-defined methods to evaluate numerically how two complex channel networks are geometrically far apart. The present study introduces new metrics for evaluating numerically channel networks extracted in grid digital elevation models with respect to a reference channel network (see the figure below). Streams of the evaluated network (EN) are delineated as in the Horton ordering system and examined through a priority climbing algorithm based on the triple index (ID1,ID2,ID3), where ID1 is a stream identifier that increases as the elevation of lower end of the stream increases, ID2 indicates the ID1 of the draining stream, and ID3 is the ID1 of the corresponding stream in the reference network (RN). Streams of the RN are identified by the double index (ID1,ID2). Streams of the EN are processed in the order of increasing ID1 (plots a-l in the figure below). For each processed stream of the EN, the closest stream of the RN is sought by considering all the streams of the RN sharing the same ID2. This ID2 in the RN is equal in the EN to the ID3 of the stream draining the processed stream, the one having ID1 equal to the ID2 of the processed stream. The mean stream planar distance (MSPD) and the mean stream elevation drop (MSED) are computed as the mean distance and drop, respectively, between corresponding streams. The MSPD is shown to be useful for evaluating slope direction methods and thresholds for channel initiation, whereas the MSED is shown to indicate the ability of grid coarsening strategies to retain the profiles of observed channels. The developed metrics fill a gap in the existing literature by allowing hydrologists and geomorphologists to compare descriptions of a fixed physical system obtained by using different terrain analysis methods, or different physical systems

NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: San Francisco Bay/Monterey (CA) WFO - Contra Costa, San Francisco, Alameda, San Mateo, and Santa Clara Counties

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This digital elevation model (DEM) is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Sea...

FEMA DFIRM Base Flood Elevations

Data.gov (United States)

Minnesota Department of Natural Resources — The Base Flood Elevation (BFE) table is required for any digital data where BFE lines will be shown on the corresponding Flood Insurance Rate Map (FIRM). Normally,...

Base Flood Elevation (BFE) Lines

Data.gov (United States)

Department of Homeland Security — The Base Flood Elevation (BFE) table is required for any digital data where BFE lines will be shown on the corresponding Flood Insurance Rate Map (FIRM). Normally if...

World in Mercator Projection, Shaded Relief and Colored Height

Science.gov (United States)

2003-01-01

This image of the world was generated with data from the Shuttle Radar Topography Mission (SRTM). The SRTM Project has recently released a new global data set called SRTM30, where the original one arcsecond of latitude and longitude resolution (about 30 meters, or 98 feet, at the equator) was reduced to 30 arcseconds (about 928 meters, or 1496 feet.) This image was created from that data set and shows the world between 60 degrees south and 60 degrees north latitude, covering 80% of the Earth's land mass. The image is in the Mercator Projection commonly used for maps of the world.Two visualization methods were combined to produce the image: shading and color coding of topographic height. The shade image was derived by computing topographic slope in the northwest-southeast direction, so that northwest slopes appear bright and southeast slopes appear dark. Color coding is directly related to topographic height, with green at the lower elevations, rising through yellow and tan, to white at the highest elevations.Elevation data used in this image were acquired by the Shuttle Radar Topography Mission aboard the Space Shuttle Endeavour, launched on Feb. 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space Shuttle Endeavour in 1994. SRTM was designed to collect 3-D measurements of the Earth's surface. To collect the 3-D data, engineers added a 60-meter (approximately 200-foot) mast, installed additional C-band and X-band antennas, and improved tracking and navigation devices. The mission is a cooperative project between NASA, the National Imagery and Mapping Agency (NIMA) of the U.S. Department of Defense and the German and Italian space agencies. It is managed by NASA's Jet Propulsion Laboratory, Pasadena, Calif., for NASA's Earth Science Enterprise,Washington, D.C.Orientation: North toward the top, Mercator projection Image Data: shaded and colored SRTM

World Globes, Shaded Relief and Colored Height

Science.gov (United States)

2003-01-01

These images of the world were generated with data from the Shuttle Radar Topography Mission (SRTM). The SRTM Project has recently released a new global data set called SRTM30, where the original one arcsecond of latitude and longitude resolution (about 30 meters, or 98 feet, at the equator) was reduced to 30 arcseconds (about 928 meters, or 1496 feet.) These images were created from that data set and show the Earth as it would be viewed from a point in space centered over the Americas, Africa and the western Pacific.Two visualization methods were combined to produce the image: shading and color coding of topographic height. The shade image was derived by computing topographic slope in the northwest-southeast direction, so that northwest slopes appear bright and southeast slopes appear dark. Color coding is directly related to topographic height, with green at the lower elevations, rising through yellow and tan, to white at the highest elevations.Elevation data used in this image were acquired by the Shuttle Radar Topography Mission aboard the Space Shuttle Endeavour, launched on Feb. 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space Shuttle Endeavour in 1994. SRTM was designed to collect 3-D measurements of the Earth's surface. To collect the 3-D data, engineers added a 60-meter (approximately 200-foot) mast, installed additional C-band and X-band antennas, and improved tracking and navigation devices. The mission is a cooperative project between NASA, the National Imagery and Mapping Agency (NIMA) of the U.S. Department of Defense and the German and Italian space agencies. It is managed by NASA's Jet Propulsion Laboratory, Pasadena, Calif., for NASA's Earth Science Enterprise,Washington, D.C.Orientation: North toward the top Image Data: shaded and colored SRTM elevation model Original Data Resolution: SRTM 1 arcsecond (about 30 meters or 98 feet

Digital elevation model production from scanned topographic contour maps via thin plate spline interpolation

International Nuclear Information System (INIS)

Soycan, Arzu; Soycan, Metin

2009-01-01

GIS (Geographical Information System) is one of the most striking innovation for mapping applications supplied by the developing computer and software technology to users. GIS is a very effective tool which can show visually combination of the geographical and non-geographical data by recording these to allow interpretations and analysis. DEM (Digital Elevation Model) is an inalienable component of the GIS. The existing TM (Topographic Map) can be used as the main data source for generating DEM by amanual digitizing or vectorization process for the contours polylines. The aim of this study is to examine the DEM accuracies, which were obtained by TMs, as depending on the number of sampling points and grid size. For these purposes, the contours of the several 1/1000 scaled scanned topographical maps were vectorized. The different DEMs of relevant area have been created by using several datasets with different numbers of sampling points. We focused on the DEM creation from contour lines using gridding with RBF (Radial Basis Function) interpolation techniques, namely TPS as the surface fitting model. The solution algorithm and a short review of the mathematical model of TPS (Thin Plate Spline) interpolation techniques are given. In the test study, results of the application and the obtained accuracies are drawn and discussed. The initial object of this research is to discuss the requirement of DEM in GIS, urban planning, surveying engineering and the other applications with high accuracy (a few deci meters). (author)

Mapping and characterization of wheat stem rust resistance genes SrTm5 and Sr60 from Triticum monococcum.

Science.gov (United States)

Chen, Shisheng; Guo, Yan; Briggs, Jordan; Dubach, Felix; Chao, Shiaoman; Zhang, Wenjun; Rouse, Matthew N; Dubcovsky, Jorge

2018-03-01

The new stem rust resistance gene Sr60 was fine-mapped to the distal region of chromosome arm 5A m S, and the TTKSK-effective gene SrTm5 could be a new allele of Sr22. The emergence and spread of new virulent races of the wheat stem rust pathogen (Puccinia graminis f. sp. tritici; Pgt), including the Ug99 race group, is a serious threat to global wheat production. In this study, we mapped and characterized two stem rust resistance genes from diploid wheat Triticum monococcum accession PI 306540. We mapped SrTm5, a previously postulated gene effective to Ug99, on chromosome arm 7A m L, completely linked to Sr22. SrTm5 displayed a different race specificity compared to Sr22 indicating that they are distinct. Sequencing of the Sr22 homolog in PI 306540 revealed a novel haplotype. Characterization of the segregating populations with Pgt race QFCSC revealed an additional resistance gene on chromosome arm 5A m S that was assigned the official name Sr60. This gene was also effective against races QTHJC and SCCSC but not against TTKSK (a Ug99 group race). Using two large mapping populations (4046 gametes), we mapped Sr60 within a 0.44 cM interval flanked by sequenced-based markers GH724575 and CJ942731. These two markers delimit a 54.6-kb region in Brachypodium distachyon chromosome 4 and a 430-kb region in the Chinese Spring reference genome. Both regions include a leucine-rich repeat protein kinase (LRRK123.1) that represents a potential candidate gene. Three CC-NBS-LRR genes were found in the colinear Brachypodium region but not in the wheat genome. We are currently developing a Bacterial Artificial Chromosome library of PI 306540 to determine which of these candidate genes are present in the T. monococcum genome and to complete the cloning of Sr60.

WATERSHED SPATIAL DISCRETIZATION FOR THE ANALYSIS OF LAND USE CHANGE IN COASTAL REGIONS

Directory of Open Access Journals (Sweden)

Vassiliki Terezinha Galvão Boulomytis

Full Text Available In this study, we present a methodology to discretize a non-assessed basin based on terrain analysis using the SRTM digital elevation model (DEM and a high resolution surface model (DSM with a drainage network semi-automatic extraction process. The Juqueriquerê River Basin was used for the case study, which has the most representative non-urbanized plains of the northern coastline of São Paulo State, Brazil. The low-lying region is featured by elevations close to the sea level, mild slopes, and shallow water tables. It is also influenced by tidal variation and orographic rains. Therefore, frequent flooding occurs, even in vegetated areas. Two conflicting land use scenarios, proposed by the City Master Plan (CMP of Caraguatatuba and the Ecological-Economical Zoning (EEZ, were compared to analyze the flood vulnerability increase and geotechnical risk caused by the urbanization process. The drainage extraction techniques showed better results on high resolution DSM for low-lying regions than the SRTM DEM and determined with accuracy the locations of flood potentiality in the plains. The watershed spatial discretization allowed us to show the effects of the two different land use approaches, considering the flood vulnerability and geotechnical risk of each sub-basin

Discussion on the 3D visualizing of 1:200 000 geological map

Science.gov (United States)

Wang, Xiaopeng

2018-01-01

Using United States National Aeronautics and Space Administration Shuttle Radar Topography Mission (SRTM) terrain data as digital elevation model (DEM), overlap scanned 1:200 000 scale geological map, program using Direct 3D of Microsoft with C# computer language, the author realized the three-dimensional visualization of the standard division geological map. User can inspect the regional geology content with arbitrary angle, rotating, roaming, and can examining the strata synthetical histogram, map section and legend at any moment. This will provide an intuitionistic analyzing tool for the geological practitioner to do structural analysis with the assistant of landform, dispose field exploration route etc.

Sri Lanka, Colored Height

Science.gov (United States)

2005-01-01

The topography of the island nation of Sri Lanka is well shown in this color-coded shaded relief map generated with digital elevation data from the Shuttle Radar Topography Mission (SRTM). Two visualization methods were combined to produce the image: shading and color coding of topographic height. The shade image was derived by computing topographic slope in the northwest-southeast direction, so that northwest slopes appear bright and southeast slopes appear dark. Color coding is directly related to topographic height, with green at the lower elevations, rising through yellow and tan, to white at the highest elevations. For this special view heights below 10 meters (33 feet) above sea level have been colored red. These low coastal elevations extend 5 to 10 km (3.1 to 6.2 mi) inland on Sri Lanka and are especially vulnerable to flooding associated with storm surges, rising sea level, or, as in the aftermath of the earthquake of December 26, 2004, tsunami. These so-called tidal waves have occurred numerous times in history and can be especially destructive, but with the advent of the near-global SRTM elevation data planners can better predict which areas are in the most danger and help develop mitigation plans in the event of particular flood events. Sri Lanka is shaped like a giant teardrop falling from the southern tip of the vast Indian subcontinent. It is separated from India by the 50km (31mi) wide Palk Strait, although there is a series of stepping-stone coral islets known as Adam's Bridge that almost form a land bridge between the two countries. The island is just 350km (217mi) long and only 180km (112mi) wide at its broadest, and is about the same size as Ireland, West Virginia or Tasmania. The southern half of the island is dominated by beautiful and rugged hill country, and includes Mt Pidurutalagala, the islandaE(TM)s highest point at 2524 meters (8281 ft). The entire northern half comprises a large plain extending from the edge of the hill country to the

Suitability of digital elevation models generated by uav photogrammetry for slope stability assessment (case study of landslide in Svätý Anton, Slovakia

Directory of Open Access Journals (Sweden)

Rusnák Miloš

2016-12-01

Full Text Available Assessing the accuracy of photogrammetrically-derived digital elevation models (DEMs from UAV is essential in many geoscience disciplines. The suitability of different DEM devised for slope stability assessment was evaluated in the example of the landslide in Svätý Anton village in Slovakia. Aerial data was acquired during a one-day field campaign in autumn 2014. The point cloud from 218 images (54,607,748 points was manually classified into 7 different classes for filtering vegetation cover and buildings. Assessment of vertical differences between the UAV derived elevation model and real terrain surface was based on comparison of control points targeted by GPS (337 points and unclassified and ground classified point cloud for raster elevation models with 1, 5, 10, 20 and 50 cm pixel resolution.

Landform classification using a sub-pixel spatial attraction model to increase spatial resolution of digital elevation model (DEM

Directory of Open Access Journals (Sweden)

Marzieh Mokarrama

2018-04-01

Full Text Available The purpose of the present study is preparing a landform classification by using digital elevation model (DEM which has a high spatial resolution. To reach the mentioned aim, a sub-pixel spatial attraction model was used as a novel method for preparing DEM with a high spatial resolution in the north of Darab, Fars province, Iran. The sub-pixel attraction models convert the pixel into sub-pixels based on the neighboring pixels fraction values, which can only be attracted by a central pixel. Based on this approach, a mere maximum of eight neighboring pixels can be selected for calculating of the attraction value. In the mentioned model, other pixels are supposed to be far from the central pixel to receive any attraction. In the present study by using a sub-pixel attraction model, the spatial resolution of a DEM was increased. The design of the algorithm is accomplished by using a DEM with a spatial resolution of 30 m (the Advanced Space borne Thermal Emission and Reflection Radiometer; (ASTER and a 90 m (the Shuttle Radar Topography Mission; (SRTM. In the attraction model, scale factors of (S = 2, S = 3, and S = 4 with two neighboring methods of touching (T = 1 and quadrant (T = 2 are applied to the DEMs by using MATLAB software. The algorithm is evaluated by taking the best advantages of 487 sample points, which are measured by surveyors. The spatial attraction model with scale factor of (S = 2 gives better results compared to those scale factors which are greater than 2. Besides, the touching neighborhood method is turned to be more accurate than the quadrant method. In fact, dividing each pixel into more than two sub-pixels decreases the accuracy of the resulted DEM. On the other hand, in these cases DEM, is itself in charge of increasing the value of root-mean-square error (RMSE and shows that attraction models could not be used for S which is greater than 2. Thus considering results, the proposed model is highly capable of

Computation of spatial significance of mountain objects extracted from multiscale digital elevation models

International Nuclear Information System (INIS)

Sathyamoorthy, Dinesh

2014-01-01

The derivation of spatial significance is an important aspect of geospatial analysis and hence, various methods have been proposed to compute the spatial significance of entities based on spatial distances with other entities within the cluster. This paper is aimed at studying the spatial significance of mountain objects extracted from multiscale digital elevation models (DEMs). At each scale, the value of spatial significance index SSI of a mountain object is the minimum number of morphological dilation iterations required to occupy all the other mountain objects in the terrain. The mountain object with the lowest value of SSI is the spatially most significant mountain object, indicating that it has the shortest distance to the other mountain objects. It is observed that as the area of the mountain objects reduce with increasing scale, the distances between the mountain objects increase, resulting in increasing values of SSI. The results obtained indicate that the strategic location of a mountain object at the centre of the terrain is more important than its size in determining its reach to other mountain objects and thus, its spatial significance

Generation and performance assessment of the global TanDEM-X digital elevation model

Science.gov (United States)

Rizzoli, Paola; Martone, Michele; Gonzalez, Carolina; Wecklich, Christopher; Borla Tridon, Daniela; Bräutigam, Benjamin; Bachmann, Markus; Schulze, Daniel; Fritz, Thomas; Huber, Martin; Wessel, Birgit; Krieger, Gerhard; Zink, Manfred; Moreira, Alberto

2017-10-01

The primary objective of the TanDEM-X mission is the generation of a global, consistent, and high-resolution digital elevation model (DEM) with unprecedented global accuracy. The goal is achieved by exploiting the interferometric capabilities of the two twin SAR satellites TerraSAR-X and TanDEM-X, which fly in a close orbit formation, acting as an X-band single-pass interferometer. Between December 2010 and early 2015 all land surfaces have been acquired at least twice, difficult terrain up to seven or eight times. The acquisition strategy, data processing, and DEM calibration and mosaicking have been systematically monitored and optimized throughout the entire mission duration, in order to fulfill the specification. The processing of all data has finally been completed in September 2016 and this paper reports on the final performance of the TanDEM-X global DEM and presents the acquisition and processing strategy which allowed to obtain the final DEM quality. The results confirm the outstanding global accuracy of the delivered product, which can be now utilized for both scientific and commercial applications.

Greenland 5 km DEM, Ice Thickness, and Bedrock Elevation Grids

Data.gov (United States)

National Aeronautics and Space Administration — A Digital Elevation Model (DEM), ice thickness grid, and bedrock elevation grid of Greenland acquired as part of the PARCA program are available in ASCII text format...

Shoreline Erosion and Slope Failure Detection over Southwest Lakeshore Michigan using Temporal Radar and Digital Elevation Model

Science.gov (United States)

Sataer, G.; Sultan, M.; Yellich, J. A.; Becker, R.; Emil, M. K.; Palaseanu, M.

2017-12-01

Throughout the 20th century and into the 21st century, significant losses of residential, commercial and governmental property were reported along the shores of the Great Lakes region due to one or more of the following factors: high lake levels, wave actions, groundwater discharge. A collaborative effort (Western Michigan University, University of Toledo, Michigan Geological Survey [MGS], United States Geological Survey [USGS], National Oceanographic and Atmospheric Administration [NOAA]) is underway to examine the temporal topographic variations along the shoreline and the adjacent bluff extending from the City of South Haven in the south to the City of Saugatuck in the north within the Allegan County. Our objectives include two main tasks: (1) identification of the timing of, and the areas, witnessing slope failure and shoreline erosion, and (2) investigating the factors causing the observed failures and erosion. This is being accomplished over the study area by: (1) detecting and measuring slope subsidence rates (velocities along line of site) and failures using radar interferometric persistent scatter (PS) techniques applied to ESA's European Remote Sensing (ERS) satellites, ERS-1 and -2 (spatial resolution: 25 m) that were acquired in 1995 to 2007, (2) extracting temporal high resolution (20 cm) digital elevation models (DEM) for the study area from temporal imagery acquired by Unmanned Aerial Vehicles (UAVs), and applying change detection techniques to the extracted DEMs, (3) detecting change in elevation and slope profiles extracted from two LIDAR Coastal National Elevation Database (CoNED) DEMs (spatial resolution: 0.5m), acquired on 2008 and 2012, and (4) spatial and temporal correlation of the detected changes in elevation with relevant data sets (e.g., lake levels, precipitation, groundwater levels) in search of causal effects.

Shaded Relief of Minnesota Elevation - Color

Data.gov (United States)

Minnesota Department of Natural Resources — This file is a product of a shaded relief process on the 30 meter resolution Digital Elevation Model data (dem30im3). This image was created using a custom AML...

Topographic Map of Quadrangles 3060 and 2960, Qala-I-Fath (608), Malek-Sayh-Koh (613), and Gozar-E-Sah (614) Quadrangles, Afghanistan

Science.gov (United States)

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

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

Science.gov (United States)

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

Topographic Map of Quadrangles 3666 and 3766, Balkh (219), Mazar-I-Sharif (220), Qarqin (213), and Hazara Toghai (214) Quadrangles, Afghanistan

Science.gov (United States)

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

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

Science.gov (United States)

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

Topographic Map of Quadrangle 3470 and the Northern Edge of 3370, Jalal-Abad (511), Chaghasaray (512), and Northernmost Jaji-Maydan (517) Quadrangles, Afg

Science.gov (United States)

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

Topographic Map of Quadrangles 3764 and 3664, Jalajin (117), Kham-Ab (118), Char Shangho (123), and Sheberghan (124) Quadrangles, Afghanistan

Science.gov (United States)

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

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

Science.gov (United States)

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

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

Science.gov (United States)

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

Topographic Map of Quadrangles 3168 and 3268, Yahya-Wona (703), Wersek (704), Khayr-Kot (521), and Urgon (522) Quadrangles, Afghanistan

Science.gov (United States)

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

Topographic Map of Quadrangles 3770 and 3870, Maymayk (211), Jamarj-I-Bala (212), Faydz-Abad (217), and Parkhaw (218) Quadrangles, Afghanistan

Science.gov (United States)

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

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

Science.gov (United States)

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

Topographic Map of Quadrangles 3560 and 3562, Sir-Band (402), Khawja-Jir (403), and Bala-Murghab (404) Quadrangles, Afghanistan

Science.gov (United States)

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

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

Science.gov (United States)

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

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

Science.gov (United States)

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

Topographic Map of Quadrangles 3260 and 3160, Dasht-E-Chahe-Mazar (419), Anardara (420), Asparan (601), and Kang (602) Quadrangles, Afghanistan

Science.gov (United States)

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

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

Science.gov (United States)

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

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

Science.gov (United States)

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

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

Science.gov (United States)

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

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

Science.gov (United States)

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

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

Science.gov (United States)

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

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

Science.gov (United States)

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

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

Science.gov (United States)

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

Topographic Map of Quadrangles 3062 and 2962, Charburjak (609), Khanneshin (610), Gawdezereh (615), and Galachah (616) Quadrangles, Afghanistan

Science.gov (United States)

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

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

Science.gov (United States)

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

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

Science.gov (United States)

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

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

Science.gov (United States)

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

Topographic Map of Quadrangles 3460 and 3360, Kol-I-Namaksar (407), Ghuryan (408), Kawir-I-Naizar (413), and Kohe-Mahmudo-Esmailjan (414) Quadrangles, Afghanistan

Science.gov (United States)

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

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

Science.gov (United States)

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

Topographic Map of Quadrangle 3368 and Part of Quadrangle 3370, Ghazni (515), Gardez (516), and Jaji-Maydan (517) Quadrangles, Afghanistan

Science.gov (United States)

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

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

Science.gov (United States)

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

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

Science.gov (United States)

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

Topographic Map of Quadrangle 3768 and 3668, Imam-Saheb (215), Rustaq (216), Baghlan (221), and Taloqan (222) Quadrangles, Afghanistan

Science.gov (United States)

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

2012 NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: Mobile/Tallahassee (AL/FL) WFO - Mobile County in Alabama and Escambia, Santa Rosa, and Okaloosa (portion) Counties in Florida

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This digital elevation model (DEM) is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Sea...

Global 30m Height Above the Nearest Drainage

Science.gov (United States)

Donchyts, Gennadii; Winsemius, Hessel; Schellekens, Jaap; Erickson, Tyler; Gao, Hongkai; Savenije, Hubert; van de Giesen, Nick

2016-04-01

Variability of the Earth surface is the primary characteristics affecting the flow of surface and subsurface water. Digital elevation models, usually represented as height maps above some well-defined vertical datum, are used a lot to compute hydrologic parameters such as local flow directions, drainage area, drainage network pattern, and many others. Usually, it requires a significant effort to derive these parameters at a global scale. One hydrological characteristic introduced in the last decade is Height Above the Nearest Drainage (HAND): a digital elevation model normalized using nearest drainage. This parameter has been shown to be useful for many hydrological and more general purpose applications, such as landscape hazard mapping, landform classification, remote sensing and rainfall-runoff modeling. One of the essential characteristics of HAND is its ability to capture heterogeneities in local environments, difficult to measure or model otherwise. While many applications of HAND were published in the academic literature, no studies analyze its variability on a global scale, especially, using higher resolution DEMs, such as the new, one arc-second (approximately 30m) resolution version of SRTM. In this work, we will present the first global version of HAND computed using a mosaic of two DEMS: 30m SRTM and Viewfinderpanorama DEM (90m). The lower resolution DEM was used to cover latitudes above 60 degrees north and below 56 degrees south where SRTM is not available. We compute HAND using the unmodified version of the input DEMs to ensure consistency with the original elevation model. We have parallelized processing by generating a homogenized, equal-area version of HydroBASINS catchments. The resulting catchment boundaries were used to perform processing using 30m resolution DEM. To compute HAND, a new version of D8 local drainage directions as well as flow accumulation were calculated. The latter was used to estimate river head by incorporating fixed and

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

Science.gov (United States)

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.

Comparison of Multi-Scale Digital Elevation Models for Defining Waterways and Catchments Over Large Areas

Science.gov (United States)

Harris, B.; McDougall, K.; Barry, M.

2012-07-01

Digital Elevation Models (DEMs) allow for the efficient and consistent creation of waterways and catchment boundaries over large areas. Studies of waterway delineation from DEMs are usually undertaken over small or single catchment areas due to the nature of the problems being investigated. Improvements in Geographic Information Systems (GIS) techniques, software, hardware and data allow for analysis of larger data sets and also facilitate a consistent tool for the creation and analysis of waterways over extensive areas. However, rarely are they developed over large regional areas because of the lack of available raw data sets and the amount of work required to create the underlying DEMs. This paper examines definition of waterways and catchments over an area of approximately 25,000 km2 to establish the optimal DEM scale required for waterway delineation over large regional projects. The comparative study analysed multi-scale DEMs over two test areas (Wivenhoe catchment, 543 km2 and a detailed 13 km2 within the Wivenhoe catchment) including various data types, scales, quality, and variable catchment input parameters. Historic and available DEM data was compared to high resolution Lidar based DEMs to assess variations in the formation of stream networks. The results identified that, particularly in areas of high elevation change, DEMs at 20 m cell size created from broad scale 1:25,000 data (combined with more detailed data or manual delineation in flat areas) are adequate for the creation of waterways and catchments at a regional scale.

Towards the optimal fusion of high-resolution Digital Elevation Models for detailed urban flood assessment

Science.gov (United States)

Leitão, J. P.; de Sousa, L. M.

2018-06-01

Newly available, more detailed and accurate elevation data sets, such as Digital Elevation Models (DEMs) generated on the basis of imagery from terrestrial LiDAR (Light Detection and Ranging) systems or Unmanned Aerial Vehicles (UAVs), can be used to improve flood-model input data and consequently increase the accuracy of the flood modelling results. This paper presents the first application of the MBlend merging method and assesses the impact of combining different DEMs on flood modelling results. It was demonstrated that different raster merging methods can have different and substantial impacts on these results. In addition to the influence associated with the method used to merge the original DEMs, the magnitude of the impact also depends on (i) the systematic horizontal and vertical differences of the DEMs, and (ii) the orientation between the DEM boundary and the terrain slope. The greater water depth and flow velocity differences between the flood modelling results obtained using the reference DEM and the merged DEMs ranged from -9.845 to 0.002 m, and from 0.003 to 0.024 m s-1 respectively; these differences can have a significant impact on flood hazard estimates. In most of the cases investigated in this study, the differences from the reference DEM results were smaller for the MBlend method than for the results of the two conventional methods. This study highlighted the importance of DEM merging when conducting flood modelling and provided hints on the best DEM merging methods to use.

ICESat laser altimetry over small mountain glaciers

Directory of Open Access Journals (Sweden)

D. Treichler

2016-09-01

Full Text Available Using sparsely glaciated southern Norway as a case study, we assess the potential and limitations of ICESat laser altimetry for analysing regional glacier elevation change in rough mountain terrain. Differences between ICESat GLAS elevations and reference elevation data are plotted over time to derive a glacier surface elevation trend for the ICESat acquisition period 2003–2008. We find spatially varying biases between ICESat and three tested digital elevation models (DEMs: the Norwegian national DEM, SRTM DEM, and a high-resolution lidar DEM. For regional glacier elevation change, the spatial inconsistency of reference DEMs – a result of spatio-temporal merging – has the potential to significantly affect or dilute trends. Elevation uncertainties of all three tested DEMs exceed ICESat elevation uncertainty by an order of magnitude, and are thus limiting the accuracy of the method, rather than ICESat uncertainty. ICESat matches glacier size distribution of the study area well and measures small ice patches not commonly monitored in situ. The sample is large enough for spatial and thematic subsetting. Vertical offsets to ICESat elevations vary for different glaciers in southern Norway due to spatially inconsistent reference DEM age. We introduce a per-glacier correction that removes these spatially varying offsets, and considerably increases trend significance. Only after application of this correction do individual campaigns fit observed in situ glacier mass balance. Our correction also has the potential to improve glacier trend significance for other causes of spatially varying vertical offsets, for instance due to radar penetration into ice and snow for the SRTM DEM or as a consequence of mosaicking and merging that is common for national or global DEMs. After correction of reference elevation bias, we find that ICESat provides a robust and realistic estimate of a moderately negative glacier mass balance of around −0.36 ± 0.07�

FULLY AUTOMATED GENERATION OF ACCURATE DIGITAL SURFACE MODELS WITH SUB-METER RESOLUTION FROM SATELLITE IMAGERY

Directory of Open Access Journals (Sweden)

J. Wohlfeil

2012-07-01

Full Text Available Modern pixel-wise image matching algorithms like Semi-Global Matching (SGM are able to compute high resolution digital surface models from airborne and spaceborne stereo imagery. Although image matching itself can be performed automatically, there are prerequisites, like high geometric accuracy, which are essential for ensuring the high quality of resulting surface models. Especially for line cameras, these prerequisites currently require laborious manual interaction using standard tools, which is a growing problem due to continually increasing demand for such surface models. The tedious work includes partly or fully manual selection of tie- and/or ground control points for ensuring the required accuracy of the relative orientation of images for stereo matching. It also includes masking of large water areas that seriously reduce the quality of the results. Furthermore, a good estimate of the depth range is required, since accurate estimates can seriously reduce the processing time for stereo matching. In this paper an approach is presented that allows performing all these steps fully automated. It includes very robust and precise tie point selection, enabling the accurate calculation of the images’ relative orientation via bundle adjustment. It is also shown how water masking and elevation range estimation can be performed automatically on the base of freely available SRTM data. Extensive tests with a large number of different satellite images from QuickBird and WorldView are presented as proof of the robustness and reliability of the proposed method.

Forest operations planning by using RTK-GPS based digital elevation model

Directory of Open Access Journals (Sweden)

Neşe Gülci

2015-07-01

Full Text Available Having large proportion of forests in mountainous terrain in Turkey, the logging methods that not only minimize operational costs but also minimize environmental damages should be determined in forest operations planning. In a case where necessary logging equipment and machines are available, ground slope is the most important factor in determining the logging method. For this reason, accurate, up to date, and precise ground slope data is very crucial in the success of forest operations planning. In recent years, high-resolution Digital Elevation Models (DEM can be generated for forested areas by using Real Time Kinematic (RTK GPS method and these DEMs can be used to develop precise slope maps. In this study, high-resolution DEM was developed by RTK-GPS method to generate precise slope map in a sample area. Then, the slope map was classified into slope classes specified by IUFRO in order to assist forest operations planning. According to the results, logging methods that are suitable for very steep and steep terrain conditions (i.e. skyline logging, cable pulling, and chute systems should be preferred in 48.1% of the study area. It was also found that logging methods that are suitable for terrain with medium slope (i.e. skidding and cable pulling and gentle slope (i.e. skidding and mobile winch should be preferred in 34.1% and 17.8% of the study area, respectively.

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

Science.gov (United States)

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

Quantifying the performance of automated GIS-based geomorphological approaches for riparian zone delineation using digital elevation models

Directory of Open Access Journals (Sweden)

D. Fernández

2012-10-01

Full Text Available Riparian zone delineation is a central issue for managing rivers and adjacent areas; however, criteria used to delineate them are still under debate. The area inundated by a 50-yr flood has been indicated as an optimal hydrological descriptor for riparian areas. This detailed hydrological information is usually only available for populated areas at risk of flooding. In this work we created several floodplain surfaces by means of two different GIS-based geomorphological approaches using digital elevation models (DEMs, in an attempt to find hydrologically meaningful potential riparian zones for river networks at the river basin scale. Objective quantification of the performance of the two geomorphologic models is provided by analysing coinciding and exceeding areas with respect to the 50-yr flood surface in different river geomorphological types.

An automated, open-source pipeline for mass production of digital elevation models (DEMs) from very-high-resolution commercial stereo satellite imagery

Science.gov (United States)

Shean, David E.; Alexandrov, Oleg; Moratto, Zachary M.; Smith, Benjamin E.; Joughin, Ian R.; Porter, Claire; Morin, Paul

2016-06-01

We adapted the automated, open source NASA Ames Stereo Pipeline (ASP) to generate digital elevation models (DEMs) and orthoimages from very-high-resolution (VHR) commercial imagery of the Earth. These modifications include support for rigorous and rational polynomial coefficient (RPC) sensor models, sensor geometry correction, bundle adjustment, point cloud co-registration, and significant improvements to the ASP code base. We outline a processing workflow for ˜0.5 m ground sample distance (GSD) DigitalGlobe WorldView-1 and WorldView-2 along-track stereo image data, with an overview of ASP capabilities, an evaluation of ASP correlator options, benchmark test results, and two case studies of DEM accuracy. Output DEM products are posted at ˜2 m with direct geolocation accuracy of process individual stereo pairs on a local workstation, the methods presented here were developed for large-scale batch processing in a high-performance computing environment. We are leveraging these resources to produce dense time series and regional mosaics for the Earth's polar regions.

Anaglyph, Salt Lake City, Utah

Science.gov (United States)

2002-01-01

The 2002 Winter Olympics are hosted by Salt Lake City at several venues within the city, in nearby cities, and within the adjacent Wasatch Mountains. This anaglyph image provides a stereoscopic map view of north central Utah that includes all of these Olympic sites. In the south, next to Utah Lake, Provo hosts the ice hockey competition. In the north, northeast of the Great Salt Lake, Ogden hosts curling and the nearby Snowbasin ski area hosts the downhill events. In between, southeast of the Great Salt Lake, Salt Lake City hosts the Olympic Village and the various skating events. Further east, across the Wasatch Mountains, the Park City ski resort hosts the bobsled, ski jumping, and snowboarding events. The Winter Olympics are always hosted in mountainous terrain. This view shows the dramatic landscape that makes the Salt Lake City region a world-class center for winter sports.The stereoscopic effect of this anaglyph was created by first draping a Landsat satellite image over a Shuttle Radar Topography Mission digital elevation model and then generating two differing perspectives, one for each eye. When viewed through special glasses, the result is a vertically exaggerated view of Earth's surface in its full three dimensions. Anaglyph glasses cover the left eye with a red filter and cover the right eye with a blue filter.Landsat has been providing visible and infrared views of the Earth since 1972. SRTM elevation data matches the 30-meter (98-foot) resolution of most Landsat images and will substantially help in analyzing the large and growing Landsat image archive, managed by the U.S. Geological Survey (USGS).Elevation data used in this image was acquired by the Shuttle Radar Topography Mission (SRTM) aboard the Space Shuttle Endeavour, launched on Feb. 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space Shuttle Endeavour in 1994. SRTM was designed

Stereo Pair, Salt Lake City, Utah

Science.gov (United States)

2002-01-01

The 2002 Winter Olympics are hosted by Salt Lake City at several venues within the city, in nearby cities, and within the adjacent Wasatch Mountains. This image pair provides a stereoscopic map view of north central Utah that includes all of these Olympic sites. In the south, next to Utah Lake, Provo hosts the ice hockey competition. In the north, northeast of the Great Salt Lake, Ogden hosts curling and the nearby Snowbasin ski area hosts the downhill events. In between, southeast of the Great Salt Lake, Salt Lake City hosts the Olympic Village and the various skating events. Further east, across the Wasatch Mountains, the Park City ski resort hosts the bobsled, ski jumping, and snowboarding events. The Winter Olympics are always hosted in mountainous terrain. This view shows the dramatic landscape that makes the Salt Lake City region a world-class center for winter sports.This stereoscopic image was generated by draping a Landsat satellite image over a Shuttle Radar Topography Mission digital elevation model. Two differing perspectives were then calculated, one for each eye. They can be seen in 3-D by viewing the left image with the right eye and the right image with the left eye (cross-eyed viewing or by downloading and printing the image pair and viewing them with a stereoscope. When stereoscopically merged, the result is a vertically exaggerated view of Earth's surface in its full three dimensions.Landsat has been providing visible and infrared views of the Earth since 1972. SRTM elevation data matches the 30-meter (98-foot) resolution of most Landsat images and will substantially help in analyzing the large and growing Landsat image archive, managed by the U.S. Geological Survey (USGS).Elevation data used in this image was acquired by the Shuttle Radar Topography Mission (SRTM) aboard the Space Shuttle Endeavour, launched on Feb. 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR

Interpolation Routines Assessment in ALS-Derived Digital Elevation Models for Forestry Applications

Directory of Open Access Journals (Sweden)

Antonio Luis Montealegre

2015-07-01

Full Text Available Airborne Laser Scanning (ALS is capable of estimating a variety of forest parameters using different metrics extracted from the normalized heights of the point cloud using a Digital Elevation Model (DEM. In this study, six interpolation routines were tested over a range of land cover and terrain roughness in order to generate a collection of DEMs with spatial resolution of 1 and 2 m. The accuracy of the DEMs was assessed twice, first using a test sample extracted from the ALS point cloud, second using a set of 55 ground control points collected with a high precision Global Positioning System (GPS. The effects of terrain slope, land cover, ground point density and pulse penetration on the interpolation error were examined stratifying the study area with these variables. In addition, a Classification and Regression Tree (CART analysis allowed the development of a prediction uncertainty map to identify in which areas DEMs and Airborne Light Detection and Ranging (LiDAR derived products may be of low quality. The Triangulated Irregular Network (TIN to raster interpolation method produced the best result in the validation process with the training data set while the Inverse Distance Weighted (IDW routine was the best in the validation with GPS (RMSE of 2.68 cm and RMSE of 37.10 cm, respectively.

The Importance of Precise Digital Elevation Models (DEM) in Modelling Floods

Science.gov (United States)

Demir, Gokben; Akyurek, Zuhal

2016-04-01

Digital elevation Models (DEM) are important inputs for topography for the accurate modelling of floodplain hydrodynamics. Floodplains have a key role as natural retarding pools which attenuate flood waves and suppress flood peaks. GPS, LIDAR and bathymetric surveys are well known surveying methods to acquire topographic data. It is not only time consuming and expensive to obtain topographic data through surveying but also sometimes impossible for remote areas. In this study it is aimed to present the importance of accurate modelling of topography for flood modelling. The flood modelling for Samsun-Terme in Blacksea region of Turkey is done. One of the DEM is obtained from the point observations retrieved from 1/5000 scaled orthophotos and 1/1000 scaled point elevation data from field surveys at x-sections. The river banks are corrected by using the orthophotos and elevation values. This DEM is named as scaled DEM. The other DEM is obtained from bathymetric surveys. 296 538 number of points and the left/right bank slopes were used to construct the DEM having 1 m spatial resolution and this DEM is named as base DEM. Two DEMs were compared by using 27 x-sections. The maximum difference at thalweg of the river bed is 2m and the minimum difference is 20 cm between two DEMs. The channel conveyance capacity in base DEM is larger than the one in scaled DEM and floodplain is modelled in detail in base DEM. MIKE21 with flexible grid is used in 2- dimensional shallow water flow modelling. The model by using two DEMs were calibrated for a flood event (July 9, 2012). The roughness is considered as the calibration parameter. From comparison of input hydrograph at the upstream of the river and output hydrograph at the downstream of the river, the attenuation is obtained as 91% and 84% for the base DEM and scaled DEM, respectively. The time lag in hydrographs does not show any difference for two DEMs and it is obtained as 3 hours. Maximum flood extents differ for the two DEMs

Digital Soil Mapping Using Landscape Stratification for Arid Rangelands in the Eastern Great Basin, Central Utah

OpenAIRE

Fonnesbeck, Brook B.

2015-01-01

Digital soil mapping typically involves inputs of digital elevation models, remotely sensed imagery, and other spatially explicit digital data as environmental covariates to predict soil classes and attributes over a landscape using statistical models. Digital imagery from Landsat 5, a digital elevation model, and a digital geology map were used as environmental covariates in a 67,000-ha study area of the Great Basin west of Fillmore, UT. A “pre-map” was created for selecting sampling locatio...

Quantification of morphological properties of terrace surface using digital elevation model and its application to stratigraphic correlation of terraces

International Nuclear Information System (INIS)

Yamamoto, Shinya; Hataya, Ryuta; Hamada, Takaomi

2008-01-01

Uplift estimation during late Quaternary is required for site selection of geological disposal facility of high level radioactive waste (NUMO, 2004). Terrace level and/or difference in elevation of terraces are good indicators of uplift. Therefore, a reliable method of terrace correlation and chronology is a key issues. Air-photograph interpretation is generally carried out in the early stage of a terrace investigation. However, a terrace classification often depends on the observer's qualitative interpretation. In order to improve objectivity of geomorphic investigation with air-photograph interpretation, we examine to quantify the morphological properties of terrace surface by some morphometric variables that are computed from Digital Elevation Model (DEM). In this study, four morphometric variables (average slope, average laplacian, remaining ratio of a terrace surface, and average depth of erosion) were calculated using data sets of terraces of which chronological data are clearly described. The relationship between these variables and terrace ages shows constant tendencies respond to the geomorphological process caused by the erosion. To examine capability of morphometric variables as an index of terrace correlation, regression analyses were carried out. The regression age estimated from morphometric variables allows to classify terraces in correct sequence, and the error with the observed age falls up to 100,000 years. In addition, to discuss appropriate quantities of DEM for terrace correlation, we used three different elevation data to create DEM: 1) aerial photogrammetry data; 2) airborne laser scanner data; 3) 1:25000-scale contour map. By comparing analysis results of each DEMs, we show suitable qualities of elevation data and DEM grid size to represent the degree of erosion correctly. (author)

COMPARISON OF MULTI-SCALE DIGITAL ELEVATION MODELS FOR DEFINING WATERWAYS AND CATCHMENTS OVER LARGE AREAS

Directory of Open Access Journals (Sweden)

B. Harris

2012-07-01

Full Text Available Digital Elevation Models (DEMs allow for the efficient and consistent creation of waterways and catchment boundaries over large areas. Studies of waterway delineation from DEMs are usually undertaken over small or single catchment areas due to the nature of the problems being investigated. Improvements in Geographic Information Systems (GIS techniques, software, hardware and data allow for analysis of larger data sets and also facilitate a consistent tool for the creation and analysis of waterways over extensive areas. However, rarely are they developed over large regional areas because of the lack of available raw data sets and the amount of work required to create the underlying DEMs. This paper examines definition of waterways and catchments over an area of approximately 25,000 km2 to establish the optimal DEM scale required for waterway delineation over large regional projects. The comparative study analysed multi-scale DEMs over two test areas (Wivenhoe catchment, 543 km2 and a detailed 13 km2 within the Wivenhoe catchment including various data types, scales, quality, and variable catchment input parameters. Historic and available DEM data was compared to high resolution Lidar based DEMs to assess variations in the formation of stream networks. The results identified that, particularly in areas of high elevation change, DEMs at 20 m cell size created from broad scale 1:25,000 data (combined with more detailed data or manual delineation in flat areas are adequate for the creation of waterways and catchments at a regional scale.

The ASTER Global Digital Elevation Model (GDEM) -for societal benefit -

Science.gov (United States)

Hato, M.; Tsu, H.; Tachikawa, T.; Abrams, M.; Bailey, B.

2009-12-01

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM) was developed jointly by the Ministry of Economy, Trade and Industry (METI) of Japan and the United States National Aeronautics and Space Administration (NASA) under the agreement of contribution to GEOSS and a public release was started on June 29th. ASTER GDEM can be downloaded to users from the Earth Remote Sensing Data Analysis Center (ERSDAC) of Japan and NASA’s Land Processes Distributed Active Archive Center (LP DAAC) free of charge. The ASTER instrument was built by METI and launched onboard NASA’s Terra spacecraft in December 1999. It has an along-track stereoscopic capability using its near infrared spectral band (NIR) and its nadir-viewing and backward-viewing telescopes to acquire stereo image data with a base-to-height ratio of 0.6. The ASTER GDEM was produced by applying newly-developed automated algorithm to more than 1.2 million NIR data Produced DEMs of all scene data was stacked after cloud masking and finally partitioned into 1° x 1°unit (called ‘tile’) data for convenience of distribution and handling by users. Before start of public distribution, ERSDAC and USGS/NASA together with many volunteers did validation and characterization by using a preliminary product of the ASTER GDEM. As a result of validation, METI and NASA evaluated that Version 1 of the ASTER GDEM has enough quality to be used as “experimental” or “research grade” data and consequently decided to release it. The ASTER GDEM covering almost all land area of from 83N to 83S on the earth represents as an important contribution to the global earth observation community. We will show our effort of development of ASTER GDEM and its accuracy and character.

Shaded Relief of Minnesota Elevation - Black & White

Data.gov (United States)

Minnesota Department of Natural Resources — This file is a product of a shaded relief process on the 30 meter resolution Digital Elevation Model data (dem30im3). This image was created using a custom AML...

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

Science.gov (United States)

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.

A new seamless, high-resolution digital elevation model of the San Francisco Bay-Delta Estuary, California

Science.gov (United States)

Fregoso, Theresa A.; Wang, Rueen-Fang; Ateljevich, Eli; Jaffe, Bruce E.

2017-06-14

Climate change, sea-level rise, and human development have contributed to the changing geomorphology of the San Francisco Bay - Delta (Bay-Delta) Estuary system. The need to predict scenarios of change led to the development of a new seamless, high-resolution digital elevation model (DEM) of the Bay – Delta that can be used by modelers attempting to understand potential future changes to the estuary system. This report details the three phases of the creation of this DEM. The first phase took a bathymetric-only DEM created in 2005 by the U.S. Geological Survey (USGS), refined it with additional data, and identified areas that would benefit from new surveys. The second phase began a USGS collaboration with the California Department of Water Resources (DWR) that updated a 2012 DWR seamless bathymetric/topographic DEM of the Bay-Delta with input from the USGS and modifications to fit the specific needs of USGS modelers. The third phase took the work from phase 2 and expanded the coverage area in the north to include the Yolo Bypass up to the Fremont Weir, the Sacramento River up to Knights Landing, and the American River up to the Nimbus Dam, and added back in the elevations for interior islands. The constant evolution of the Bay-Delta will require continuous updates to the DEM of the Delta, and there still are areas with older data that would benefit from modern surveys. As a result, DWR plans to continue updating the DEM.

Ground target geolocation based on digital elevation model for airborne wide-area reconnaissance system

Science.gov (United States)

Qiao, Chuan; Ding, Yalin; Xu, Yongsen; Xiu, Jihong

2018-01-01

To obtain the geographical position of the ground target accurately, a geolocation algorithm based on the digital elevation model (DEM) is developed for an airborne wide-area reconnaissance system. According to the platform position and attitude information measured by the airborne position and orientation system and the gimbal angles information from the encoder, the line-of-sight pointing vector in the Earth-centered Earth-fixed coordinate frame is solved by the homogeneous coordinate transformation. The target longitude and latitude can be solved with the elliptical Earth model and the global DEM. The influences of the systematic error and measurement error on ground target geolocation calculation accuracy are analyzed by the Monte Carlo method. The simulation results show that this algorithm can improve the geolocation accuracy of ground target in rough terrain area obviously. The geolocation accuracy of moving ground target can be improved by moving average filtering (MAF). The validity of the geolocation algorithm is verified by the flight test in which the plane flies at a geodetic height of 15,000 m and the outer gimbal angle is <47°. The geolocation root mean square error of the target trajectory is <45 and <7 m after MAF.

GEOMETRIC ACCURACY ANALYSIS OF WORLDDEM IN RELATION TO AW3D30, SRTM AND ASTER GDEM2

Directory of Open Access Journals (Sweden)

S. Bayburt

2017-05-01

Full Text Available In a project area close to Istanbul the quality of WorldDEM, AW3D30, SRTM DSM and ASTER GDEM2 have been analyzed in relation to a reference aerial LiDAR DEM and to each other. The random and the systematic height errors have been separated. The absolute offset for all height models in X, Y and Z is within the expectation. The shifts have been respected in advance for a satisfying estimation of the random error component. All height models are influenced by some tilts, different in size. In addition systematic deformations can be seen not influencing the standard deviation too much. The delivery of WorldDEM includes information about the height error map which is based on the interferometric phase errors, and the number and location of coverage’s from different orbits. A dependency of the height accuracy from the height error map information and the number of coverage’s can be seen, but it is smaller as expected. WorldDEM is more accurate as the other investigated height models and with 10 m point spacing it includes more morphologic details, visible at contour lines. The morphologic details are close to the details based on the LiDAR digital surface model (DSM. As usual a dependency of the accuracy from the terrain slope can be seen. In forest areas the canopy definition of InSAR X- and C-band height models as well as for the height models based on optical satellite images is not the same as the height definition by LiDAR. In addition the interferometric phase uncertainty over forest areas is larger. Both effects lead to lower height accuracy in forest areas, also visible in the height error map.

Modelling groundwater discharge areas using only digital elevation models as input data

International Nuclear Information System (INIS)

Brydsten, Lars

2006-10-01

Advanced geohydrological models require data on topography, soil distribution in three dimensions, vegetation, land use, bedrock fracture zones. To model present geohydrological conditions, these factors can be gathered with different techniques. If a future geohydrological condition is modelled in an area with positive shore displacement (say 5,000 or 10,000 years), some of these factors can be difficult to measure. This could include the development of wetlands and the filling of lakes. If the goal of the model is to predict distribution of groundwater recharge and discharge areas in the landscape, the most important factor is topography. The question is how much can topography alone explain the distribution of geohydrological objects in the landscape. A simplified description of the distribution of geohydrological objects in the landscape is that groundwater recharge areas occur at local elevation curvatures and discharge occurs in lakes, brooks, and low situated slopes. Areas in-between these make up discharge areas during wet periods and recharge areas during dry periods. A model that could predict this pattern only using topography data needs to be able to predict high ridges and future lakes and brooks. This study uses GIS software with four different functions using digital elevation models as input data, geomorphometrical parameters to predict landscape ridges, basin fill for predicting lakes, flow accumulations for predicting future waterways, and topographical wetness indexes for dividing in-between areas based on degree of wetness. An area between the village of and Forsmarks' Nuclear Power Plant has been used to calibrate the model. The area is within the SKB 10-metre Elevation Model (DEM) and has a high-resolution orienteering map for wetlands. Wetlands are assumed to be groundwater discharge areas. Five hundred points were randomly distributed across the wetlands. These are potential discharge points. Model parameters were chosen with the

Improving maps of ice-sheet surface elevation change using combined laser altimeter and stereoscopic elevation model data

DEFF Research Database (Denmark)

Fredenslund Levinsen, Joanna; Howat, I. M.; Tscherning, C. C.

2013-01-01

We combine the complementary characteristics of laser altimeter data and stereoscopic digital elevation models (DEMs) to construct high-resolution (_100 m) maps of surface elevations and elevation changes over rapidly changing outlet glaciers in Greenland. Measurements from spaceborne and airborne...... laser altimeters have relatively low errors but are spatially limited to the ground tracks, while DEMs have larger errors but provide spatially continuous surfaces. The principle of our method is to fit the DEM surface to the altimeter point clouds in time and space to minimize the DEM errors and use...... that surface to extrapolate elevations away from altimeter flight lines. This reduces the DEM registration errors and fills the gap between the altimeter paths. We use data from ICESat and ATM as well as SPOT 5 DEMs from 2007 and 2008 and apply them to the outlet glaciers Jakobshavn Isbræ (JI...

EFFECT OF DIGITAL ELEVATION MODEL MESH SIZE ON GEOMORPHIC INDICES: A CASE STUDY OF THE IVAÍ RIVER WATERSHED - STATE OF PARANÁ, BRAZIL

Directory of Open Access Journals (Sweden)

Vanessa Cristina Dos Santos

Full Text Available Abstract: Geomorphometry is the science of quantitative description of land surface morphology by the mean of geomorphic indices extracted from Digital Elevation Models (DEMs. The analysis of these indices is the first and most common procedure performed in several geoscience-related subjects. This study aims to assess the impact of mesh size degradation on different local and regional geomorphic indices extracted for GDEM and TOPODATA DEMs. Thus, these DEMs, having a mesh size of 30 m, were subsampled to 60, 120 and 240 m and then geomorphic indices were calculated using the full resolution DEM and the subsampled ones. Depending on their behavior, these indices are then classified into stable and unstable. The results show that the most affected indices are slope and hydrographic indices such as Strahler order, stream sinuosity and fractal dimension and watershed perimeter, whereas elevation remains stable. It also shows that the effect depends on the presence of the canopy and geological structures in the studied area.

Perspective View with Landsat Overlay, Costa Rica

Science.gov (United States)

2002-01-01

This perspective view shows the Caribbean coastal plain of Costa Rica, with the Cordillera Central rising in the background and the Pacific Ocean in the distance. The prominent river in the center of the image is the Rio Sucio, which merges with the Rio Sarapiqui at the bottom of the image and eventually joins with Rio San Juan on the Nicaragua border.Like much of Central America, Costa Rica is generally cloud covered so very little satellite imagery is available. The ability of the Shuttle Radar Topography Mission (SRTM) instrument to penetrate clouds and make three-dimensional measurements will allow generation of the first complete high-resolution topographic map of the entire region. These data were used to generate the image.This three-dimensional perspective view was generated using elevation data from SRTM and an enhanced false-color Landsat 7 satellite image. Colors are from Landsat bands 5, 4, and 2 as red, green and blue, respectively. Topographic expression is exaggerated two times.Landsat has been providing visible and infrared views of the Earth since 1972. SRTM elevation data matches the 30-meter resolution of most Landsat images and will substantially help in analyses of the large and growing Landsat image archive. The Landsat 7 Thematic Mapper image used here was provided to the SRTM by the United States Geological Survey, Earth Resources Observation Systems (EROS) Data Center, Sioux Falls, S.D.Elevation data used in this image was acquired by the SRTM aboard the Space Shuttle Endeavour, launched on February 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space Shuttle Endeavour in 1994. SRTM was designed to collect three-dimensional measurements of the Earth's surface. To collect the 3-D data, engineers added a 60-meter-long (200-foot) mast, installed additional C-band and X-band antennas, and improved tracking and navigation devices

High Resolution Digital Elevation Models of Pristine Explosion Craters

Science.gov (United States)

Farr, T. G.; Krabill, W.; Garvin, J. B.

2004-01-01

In order to effectively capture a realistic terrain applicable to studies of cratering processes and landing hazards on Mars, we have obtained high resolution digital elevation models of several pristine explosion craters at the Nevada Test Site. We used the Airborne Terrain Mapper (ATM), operated by NASA's Wallops Flight Facility to obtain DEMs with 1 m spacing and 10 cm vertical errors of 4 main craters and many other craters and collapse pits. The main craters that were mapped are Sedan, Scooter, Schooner, and Danny Boy. The 370 m diameter Sedan crater, located on Yucca Flat, is the largest and freshest explosion crater on Earth that was formed under conditions similar to hypervelocity impact cratering. As such, it is effectively pristine, having been formed in 1962 as a result of a controlled detonation of a 100 kiloton thermonuclear device, buried at the appropriate equivalent depth of burst required to make a simple crater. Sedan was formed in alluvium of mixed lithology and subsequently studied using a variety of field-based methods. Nearby secondary craters were also formed at the time and were also mapped by ATM. Adjacent to Sedan and also in alluvium is Scooter, about 90 m in diameter and formed by a high-explosive event. Schooner (240 m) and Danny Boy (80 m) craters were also important targets for ATM as they were excavated in hard basalt and therefore have much rougher ejecta. This will allow study of ejecta patterns in hard rock as well as engineering tests of crater and rock avoidance and rover trafficability. In addition to the high resolution DEMs, crater geometric characteristics, RMS roughness maps, and other higher-order derived data products will be generated using these data. These will provide constraints for models of landing hazards on Mars and for rover trafficability. Other planned studies will include ejecta size-frequency distribution at the resolution of the DEM and at finer resolution through air photography and field measurements

A quality control system for digital elevation data

Science.gov (United States)

Knudsen, Thomas; Kokkendorf, Simon; Flatman, Andrew; Nielsen, Thorbjørn; Rosenkranz, Brigitte; Keller, Kristian

2015-04-01

In connection with the introduction of a new version of the Danish national coverage Digital Elevation Model (DK-DEM), the Danish Geodata Agency has developed a comprehensive quality control (QC) and metadata production (MP) system for LiDAR point cloud data. The architecture of the system reflects its origin in a national mapping organization where raw data deliveries are typically outsourced to external suppliers. It also reflects a design decision of aiming at, whenever conceivable, doing full spatial coverage tests, rather than scattered sample checks. Hence, the QC procedure is split in two phases: A reception phase and an acceptance phase. The primary aim of the reception phase is to do a quick assessment of things that can typically go wrong, and which are relatively simple to check: Data coverage, data density, strip adjustment. If a data delivery passes the reception phase, the QC continues with the acceptance phase, which checks five different aspects of the point cloud data: Vertical accuracy Vertical precision Horizontal accuracy Horizontal precision Point classification correctness The vertical descriptors are comparatively simple to measure: The vertical accuracy is checked by direct comparison with previously surveyed patches. The vertical precision is derived from the observed variance on well defined flat surface patches. These patches are automatically derived from the road centerlines registered in FOT, the official Danish map data base. The horizontal descriptors are less straightforward to measure, since potential reference material for direct comparison is typically expected to be less accurate than the LiDAR data. The solution selected is to compare photogrammetrically derived roof centerlines from FOT with LiDAR derived roof centerlines. These are constructed by taking the 3D Hough transform of a point cloud patch defined by the photogrammetrical roof polygon. The LiDAR derived roof centerline is then the intersection line of the two primary

A NEW METHOD TO DETECT REGIONS ENDANGERED BY HIGH WIND SPEEDS

Directory of Open Access Journals (Sweden)

P. Fischer

2016-06-01

Full Text Available In this study we evaluate whether the methodology of Boosted Regression Trees (BRT suits for accurately predicting maximum wind speeds. As predictors a broad set of parameters derived from a Digital Elevation Model (DEM acquired within the Shuttle Radar Topography Mission (SRTM is used. The derived parameters describe the surface by means of quantities (e.g. slope, aspect and quality (landform classification. Furthermore land cover data from the CORINE dataset is added. The response variable is maximum wind speed, measurements are provided by a network of weather stations. The area of interest is Switzerland, a country which suits perfectly for this study because of its highly dynamic orography and various landforms.

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

Science.gov (United States)

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

What is a Dune: Developing AN Automated Approach to Extracting Dunes from Digital Elevation Models

Science.gov (United States)

Taylor, H.; DeCuir, C.; Wernette, P. A.; Taube, C.; Eyler, R.; Thopson, S.

2016-12-01

Coastal dunes can absorb storm surge and mitigate inland erosion caused by elevated water levels during a storm. In order to understand how a dune responds to and recovers from a storm, it is important that we can first identify and differentiate the beach and dune from the rest of the landscape. Current literature does not provide a consistent definition of what the dune features (e.g. dune toe, dune crest) are or how they can be extracted. The purpose of this research is to develop enhanced approaches to extracting dunes from a digital elevation model (DEM). Manual delineation, convergence index, least-cost path, relative relief, and vegetation abundance were compared and contrasted on a small area of Padre Island National Seashore (PAIS), Preliminary results indicate that the method used to extract the dune greatly affects our interpretation of how the dune changes. The manual delineation method was time intensive and subjective, while the convergence index approach was useful to easily identify the dune crest through maximum and minimum values. The least-cost path method proved to be time intensive due to data clipping; however, this approach resulted in continuous geomorphic landscape features (e.g. dune toe, dune crest). While the relative relief approach shows the most features in multi resolution, it is difficult to assess the accuracy of the extracted features because extracted features appear as points that can vary widely in their location from one meter to the next. The vegetation approach was greatly impacted by the seasonal and annual fluctuations of growth but is advantageous in historical change studies because it can be used to extract consistent dune formation from historical aerial imagery. Improving our ability to more accurately assess dune response and recovery to a storm will enable coastal managers to more accurately predict how dunes may respond to future climate change scenarios.

Application of Digital Elevation Model (DEM for description of soil microtopography changes in laboratory experiments

Directory of Open Access Journals (Sweden)

Stańczyk Tomasz

2016-12-01

Full Text Available In the study we evaluated spatial and quantitative changes in soil surface microtopography to describe water erosion process under simulated rain with use of a non-contact optical 3D scanner. The experiment was conducted in two variants: with and without drainage layer. Two clay soils collected from farmlands from the catchment of lake Zgorzała (Warsaw were investigated. Six tests of simulated rain were applied, with 55 mm·h−1. The surface roughness and microrelief were determined immediately after every 10 min of rainfall simulation by 3D scanner. The volume of surface and underground runoff as well as soil moisture were measured. The surface points coordinates obtained while scanning were interpolated using natural neighbour method and GIS software to generate Digital Elevation Models (DEM with a 0.5 mm resolution. Two DEM-derived surface roughness indices: Random Roughness (RR and Terrain Ruggedness Index (TRI were used for microrelief description. Calculated values of both roughness factors have decreased with time under the influence of rainfall in all analyzed variants. During the sprinkling the moisture of all samples had been growing rapidly from air-dry state reaching values close to the maximum water capacity (37–48% vol. in 20–30 min. Simultaneously the intensity of surface runoff was increasing and cumulative runoff value was: 17–35% for variants with drainage and 72–83% for the variants without drainage, relative to cumulative rainfall. The observed soil surface elevation changes were associated with aggregates decomposition, erosion and sedimentation, and above all, with a compaction of the soil, which was considered to be a dominant factor hindering the assessment of the erosion intensity of the of the scanned surface.

Automated identification of stream-channel geomorphic features from high‑resolution digital elevation models in West Tennessee watersheds

Science.gov (United States)

Cartwright, Jennifer M.; Diehl, Timothy H.

2017-01-17

High-resolution digital elevation models (DEMs) derived from light detection and ranging (lidar) enable investigations of stream-channel geomorphology with much greater precision than previously possible. The U.S. Geological Survey has developed the DEM Geomorphology Toolbox, containing seven tools to automate the identification of sites of geomorphic instability that may represent sediment sources and sinks in stream-channel networks. These tools can be used to modify input DEMs on the basis of known locations of stormwater infrastructure, derive flow networks at user-specified resolutions, and identify possible sites of geomorphic instability including steep banks, abrupt changes in channel slope, or areas of rough terrain. Field verification of tool outputs identified several tool limitations but also demonstrated their overall usefulness in highlighting likely sediment sources and sinks within channel networks. In particular, spatial clusters of outputs from multiple tools can be used to prioritize field efforts to assess and restore eroding stream reaches.

Extraction and representation of nested catchment areas from digital elevation models in lake-dominated topography

Science.gov (United States)

Mackay, D. Scott; Band, Lawrence E.

1998-04-01

This paper presents a new method for extracting flow directions, contributing (upslope) areas, and nested catchments from digital elevation models in lake-dominated areas. Existing tools for acquiring descriptive variables of the topography, such as surface flow directions and contributing areas, were developed for moderate to steep topography. These tools are typically difficult to apply in gentle topography owing to limitations in explicitly handling lakes and other flat areas. This paper addresses the problem of accurately representing general topographic features by first identifying distinguishing features, such as lakes, in gentle topography areas and then using these features to guide the search for topographic flow directions and catchment marking. Lakes are explicitly represented in the topology of a watershed for use in water routing. Nonlake flat features help guide the search for topographic flow directions in areas of low signal to noise. This combined feature-based and grid-based search for topographic features yields improved contributing areas and watershed boundaries where there are lakes and other flat areas. Lakes are easily classified from remotely sensed imagery, which makes automated representation of lakes as subsystems within a watershed system tractable with widely available data sets.

ASTC-MIMO-TOPS Mode with Digital Beam-Forming in Elevation for High-Resolution Wide-Swath Imaging

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Pingping Huang

2015-03-01

Full Text Available Future spaceborne synthetic aperture radar (SAR missions require complete and frequent coverage of the earth with a high resolution. Terrain Observation by Progressive Scans (TOPS is a novel wide swath mode but has impaired azimuth resolution. In this paper, an innovative extended TOPS mode named Alamouti Space-time Coding multiple-input multiple-output TOPS (ASTC-MIMO-TOPS mode combined with digital beam-forming (DBF in elevation and multi-aperture SAR signal reconstruction in azimuth is proposed. This innovative mode achieves wide-swath coverage with a high geometric resolution and also overcomes major drawbacks in conventional MIMO SAR systems. The data processing scheme of this imaging scheme is presented in detail. The designed system example of the proposed ASTC-MIMO-TOPS mode, which has the imaging capacity of a 400 km wide swath with an azimuth resolution of 3 m, is given. Its system performance analysis results and simulated imaging results on point targets demonstrate the potential of the proposed novel spaceborne SAR mode for high-resolution wide-swath (HRWS imaging.

The influence of digital elevation model resolution on overland flow networks for modelling urban pluvial flooding.

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Leitão, J P; Boonya-Aroonnet, S; Prodanović, D; Maksimović, C

2009-01-01

This paper presents the developments towards the next generation of overland flow modelling of urban pluvial flooding. Using a detailed analysis of the Digital Elevation Model (DEM) the developed GIS tools can automatically generate surface drainage networks which consist of temporary ponds (floodable areas) and flow paths and link them with the underground network through inlets. For different commercially-available Rainfall-Runoff simulation models, the tool will generate the overland flow network needed to model the surface runoff and pluvial flooding accurately. In this paper the emphasis is placed on a sensitivity analysis of ponds and preferential overland flow paths creation. Different DEMs for three areas were considered in order to compare the results obtained. The DEMs considered were generated using different acquisition techniques and hence represent terrain with varying levels of resolution and accuracy. The results show that DEMs can be used to generate surface flow networks reliably. As expected, the quality of the surface network generated is highly dependent on the quality and resolution of the DEMs and successful representation of buildings and streets.

Digital image transformation and rectification of spacecraft and radar images

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Wu, S. S. C.

1985-01-01

The application of digital processing techniques to spacecraft television pictures and radar images is discussed. The use of digital rectification to produce contour maps from spacecraft pictures is described; images with azimuth and elevation angles are converted into point-perspective frame pictures. The digital correction of the slant angle of radar images to ground scale is examined. The development of orthophoto and stereoscopic shaded relief maps from digital terrain and digital image data is analyzed. Digital image transformations and rectifications are utilized on Viking Orbiter and Lander pictures of Mars.

Cascading water underneath Wilkes Land, East Antarctic ice sheet, observed using altimetry and digital elevation models

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Flament, T.; Berthier, E.; Rémy, F.

2014-04-01

We describe a major subglacial lake drainage close to the ice divide in Wilkes Land, East Antarctica, and the subsequent cascading of water underneath the ice sheet toward the coast. To analyse the event, we combined altimetry data from several sources and subglacial topography. We estimated the total volume of water that drained from Lake CookE2 by differencing digital elevation models (DEM) derived from ASTER and SPOT5 stereo imagery acquired in January 2006 and February 2012. At 5.2 ± 1.5 km3, this is the largest single subglacial drainage event reported so far in Antarctica. Elevation differences between ICESat laser altimetry spanning 2003-2009 and the SPOT5 DEM indicate that the discharge started in November 2006 and lasted approximately 2 years. A 13 m uplift of the surface, corresponding to a refilling of about 0.6 ± 0.3 km3, was observed between the end of the discharge in October 2008 and February 2012. Using the 35-day temporal resolution of Envisat radar altimetry, we monitored the subsequent filling and drainage of connected subglacial lakes located downstream of CookE2. The total volume of water traveling within the theoretical 500-km-long flow paths computed with the BEDMAP2 data set is similar to the volume that drained from Lake CookE2, and our observations suggest that most of the water released from Lake CookE2 did not reach the coast but remained trapped underneath the ice sheet. Our study illustrates how combining multiple remote sensing techniques allows monitoring of the timing and magnitude of subglacial water flow beneath the East Antarctic ice sheet.

Uncertainty of soil erosion modelling using open source high resolution and aggregated DEMs

Directory of Open Access Journals (Sweden)

Arun Mondal

2017-05-01

Full Text Available Digital Elevation Model (DEM is one of the important parameters for soil erosion assessment. Notable uncertainties are observed in this study while using three high resolution open source DEMs. The Revised Universal Soil Loss Equation (RUSLE model has been applied to analysis the assessment of soil erosion uncertainty using open source DEMs (SRTM, ASTER and CARTOSAT and their increasing grid space (pixel size from the actual. The study area is a part of the Narmada river basin in Madhya Pradesh state, which is located in the central part of India and the area covered 20,558 km2. The actual resolution of DEMs is 30 m and their increasing grid spaces are taken as 90, 150, 210, 270 and 330 m for this study. Vertical accuracy of DEMs has been assessed using actual heights of the sample points that have been taken considering planimetric survey based map (toposheet. Elevations of DEMs are converted to the same vertical datum from WGS 84 to MSL (Mean Sea Level, before the accuracy assessment and modelling. Results indicate that the accuracy of the SRTM DEM with the RMSE of 13.31, 14.51, and 18.19 m in 30, 150 and 330 m resolution respectively, is better than the ASTER and the CARTOSAT DEMs. When the grid space of the DEMs increases, the accuracy of the elevation and calculated soil erosion decreases. This study presents a potential uncertainty introduced by open source high resolution DEMs in the accuracy of the soil erosion assessment models. The research provides an analysis of errors in selecting DEMs using the original and increased grid space for soil erosion modelling.

Global Land One-kilometer Base Elevation (GLOBE) v.1

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — GLOBE is a project to develop the best available 30-arc-second (nominally 1 kilometer) global digital elevation data set. This version of GLOBE contains data from 11...

Modelling groundwater discharge areas using only digital elevation models as input data

Energy Technology Data Exchange (ETDEWEB)

Brydsten, Lars [Umeaa Univ. (Sweden). Dept. of Biology and Environmental Science

2006-10-15

Advanced geohydrological models require data on topography, soil distribution in three dimensions, vegetation, land use, bedrock fracture zones. To model present geohydrological conditions, these factors can be gathered with different techniques. If a future geohydrological condition is modelled in an area with positive shore displacement (say 5,000 or 10,000 years), some of these factors can be difficult to measure. This could include the development of wetlands and the filling of lakes. If the goal of the model is to predict distribution of groundwater recharge and discharge areas in the landscape, the most important factor is topography. The question is how much can topography alone explain the distribution of geohydrological objects in the landscape. A simplified description of the distribution of geohydrological objects in the landscape is that groundwater recharge areas occur at local elevation curvatures and discharge occurs in lakes, brooks, and low situated slopes. Areas in-between these make up discharge areas during wet periods and recharge areas during dry periods. A model that could predict this pattern only using topography data needs to be able to predict high ridges and future lakes and brooks. This study uses GIS software with four different functions using digital elevation models as input data, geomorphometrical parameters to predict landscape ridges, basin fill for predicting lakes, flow accumulations for predicting future waterways, and topographical wetness indexes for dividing in-between areas based on degree of wetness. An area between the village of and Forsmarks' Nuclear Power Plant has been used to calibrate the model. The area is within the SKB 10-metre Elevation Model (DEM) and has a high-resolution orienteering map for wetlands. Wetlands are assumed to be groundwater discharge areas. Five hundred points were randomly distributed across the wetlands. These are potential discharge points. Model parameters were chosen with the

Sredinnyy Khrebet, Kamchatka Peninsula, Russia

Science.gov (United States)

2002-01-01

The Kamchatka Peninsula in eastern Russia is shown in this scene created from a preliminary elevation model derived from the first data collected during the Shuttle Radar Topography Mission (SRTM) on February 12, 2000. Sredinnyy Khrebet, the mountain range that makes up the spine of the peninsula, is a chain of active volcanic peaks. Pleistocene and recent glaciers have carved the broad valleys and jagged ridges that are common here. The relative youth of the volcanism is revealed by the topography as infilling and smoothing of the otherwise rugged terrain by lava, ash, and pyroclastic flows, particularly surrounding the high peaks in the south central part of the image. Elevations here range from near sea level up to 2,618 meters (8,590 feet). Two visualization methods were combined to produce this image: shading and color coding of topographic height. The shade image was derived by computing topographic slope in the north-south direction. Northern slopes appear bright and southern slopes appear dark. Color coding is directly related to topographic height, with green at the lower elevations, rising through yellow, red, and magenta, to white at the highest elevations. Elevation data used in this image were acquired by the Shuttle Radar Topography Mission (SRTM) aboard Space Shuttle Endeavour, launched on February 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on Space Shuttle Endeavour in 1994. SRTM was designed to collect three-dimensional measurements of Earth's surface. To collect the 3-D data, engineers added a 60-meter-long (200-foot) mast, installed additional C-band and X-band antennas, and improved tracking and navigation devices. The mission is a cooperative project between the National Aeronautics and Space Administration (NASA), the National Imagery and Mapping Agency (NIMA) of the U.S. Department of Defense, and the German and Italian space

Digital terrain model evaluation and computation of the terrain correction and indirect effect in South America

Directory of Open Access Journals (Sweden)

Denizar Blitzkow

2009-12-01

Full Text Available The main objectives of this paper are to compare digital terrain models, to show the generated models for South America and to present two applications. Shuttle Radar Topography Mission (SRTM produced the most important and updated height information in the world. This paper addresses the attention to comparisons of the following models: SRTM3, DTM2002, GLOBE, GTOPO30, ETOPO2 and ETOPO5, at the common points of the grid. The comparisons are limited by latitudes 60º S and 25 º N and longitudes 100 º W and 25 º W. All these data, after some analysis, have been used to create three models for South America: SAM_1mv1, SAM_1mv2 (both of 1' grid spacing and SAM_30s (30" grid spacing. Besides this effort, the three models as well as STRM were evaluated using Bench Marks (BM in Brazil and Argentina. This paper also shows two important geodesy and geophysics applications using the SAM_1mv1: terrain correction (one of the reductions applied to the gravity acceleration and indirect effect (a consequence of the reduction of the external mass to the geoid. These are important at Andes for a precise geoid computation.Los objetivos principales de este documento son comparar modelos digitales del continente; enseñar los modelos generados para Sudamérica y presentar dos aplicaciones. Shuttle Radar Topography Mission (SRTM produjo la información más importante y más actualizada de las altitudes del mundo. Este trabajo centra su atención en las comparaciones de los modelos siguientes: SRTM3, DTM2002, GLOBO, GTOPO30, ETOPO2 y ETOPO5, en los puntos comunes de la rejilla. Las comparaciones son limitadas por las latitudes 60º S y 25 º N y longitudes 100 º W y 25 º W. Todos estos datos, después de los análisis, se han utilizado para crear tres modelos para Sudamérica: SAM_1mv1, SAM_1mv2 (1' de espaciamiento de la rejilla y SAM_30s (30" de espaciamiento de la rejilla. Los tres modelos bien como el STRM fueron evaluados usando puntos de referencia de

Hydrodynamic modelling and global datasets: Flow connectivity and SRTM data, a Bangkok case study.

Science.gov (United States)

Trigg, M. A.; Bates, P. B.; Michaelides, K.

2012-04-01

The rise in the global interconnected manufacturing supply chains requires an understanding and consistent quantification of flood risk at a global scale. Flood risk is often better quantified (or at least more precisely defined) in regions where there has been an investment in comprehensive topographical data collection such as LiDAR coupled with detailed hydrodynamic modelling. Yet in regions where these data and modelling are unavailable, the implications of flooding and the knock on effects for global industries can be dramatic, as evidenced by the recent floods in Bangkok, Thailand. There is a growing momentum in terms of global modelling initiatives to address this lack of a consistent understanding of flood risk and they will rely heavily on the application of available global datasets relevant to hydrodynamic modelling, such as Shuttle Radar Topography Mission (SRTM) data and its derivatives. These global datasets bring opportunities to apply consistent methodologies on an automated basis in all regions, while the use of coarser scale datasets also brings many challenges such as sub-grid process representation and downscaled hydrology data from global climate models. There are significant opportunities for hydrological science in helping define new, realistic and physically based methodologies that can be applied globally as well as the possibility of gaining new insights into flood risk through analysis of the many large datasets that will be derived from this work. We use Bangkok as a case study to explore some of the issues related to using these available global datasets for hydrodynamic modelling, with particular focus on using SRTM data to represent topography. Research has shown that flow connectivity on the floodplain is an important component in the dynamics of flood flows on to and off the floodplain, and indeed within different areas of the floodplain. A lack of representation of flow connectivity, often due to data resolution limitations, means

Delineation of the riparian zone in data-scarce regions using fuzzy membership functions: An evaluation based on the case of the Naryn River in Kyrgyzstan

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Betz, Florian; Lauermann, Magdalena; Cyffka, Bernd

2018-04-01

Riparian zones contain important ecosystems with a high biodiversity and relevant ecosystem services. From a process point of view, riparian zones are characterized by the interaction of hydrological, geomorphological and ecological processes. Consequently, their boundary is dynamic and blurred as it depends on not only the local valley morphology but also the hydrological regime. This makes a delineation of riparian zones from digital elevation data a challenging task as it should represent this blurred nature of riparian zone boundaries. While the application of high resolution topography from LIDAR and hydraulic models have become standard in many developed countries, studies and applications in remote areas still commonly rely on the freely available coarse resolution digital elevation models. In this article, we present the delineation of riparian zones from the SRTM-1 elevation model and fuzzy membership functions for the Naryn River in Kyrgyzstan having a length of approximately 700 km. We evaluate the extraction of the underlying channel network as well as the different indicator variables. The maximum user's accuracy for the delineation of riparian zones along the entire Naryn River is 82.14% reflecting the uncertainty arising from the heterogeneity of the riverscape as well as from the quality of the underlying elevation data. Despite the uncertainty, the fuzzy membership approach is considered as an appropriate method for riparian zone delineation as it reflects their dynamic, transitional character and can be used as indicator of connectivity within a riverscape.

Modelling vertical error in LiDAR-derived digital elevation models

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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 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

Transformation of Shuttle Radar Topography Mission (SRTM) Digital ...

African Journals Online (AJOL)

Determination of height information using the classical field surveying and geodetic methods is rather expensive, rigorous and time consuming. It is also limited in the capacity of the earth surface data gathered. These conventional topographic mapping technologies have produced maps with a variety of scales and of ...

High-Accuracy Tidal Flat Digital Elevation Model Construction Using TanDEM-X Science Phase Data

Science.gov (United States)

Lee, Seung-Kuk; Ryu, Joo-Hyung

2017-01-01

This study explored the feasibility of using TanDEM-X (TDX) interferometric observations of tidal flats for digital elevation model (DEM) construction. Our goal was to generate high-precision DEMs in tidal flat areas, because accurate intertidal zone data are essential for monitoring coastal environment sand erosion processes. To monitor dynamic coastal changes caused by waves, currents, and tides, very accurate DEMs with high spatial resolution are required. The bi- and monostatic modes of the TDX interferometer employed during the TDX science phase provided a great opportunity for highly accurate intertidal DEM construction using radar interferometry with no time lag (bistatic mode) or an approximately 10-s temporal baseline (monostatic mode) between the master and slave synthetic aperture radar image acquisitions. In this study, DEM construction in tidal flat areas was first optimized based on the TDX system parameters used in various TDX modes. We successfully generated intertidal zone DEMs with 57-m spatial resolutions and interferometric height accuracies better than 0.15 m for three representative tidal flats on the west coast of the Korean Peninsula. Finally, we validated these TDX DEMs against real-time kinematic-GPS measurements acquired in two tidal flat areas; the correlation coefficient was 0.97 with a root mean square error of 0.20 m.

Regional Distribution of Forest Height and Biomass from Multisensor Data Fusion

Science.gov (United States)

Yu, Yifan; Saatchi, Sassan; Heath, Linda S.; LaPoint, Elizabeth; Myneni, Ranga; Knyazikhin, Yuri

2010-01-01

Elevation data acquired from radar interferometry at C-band from SRTM are used in data fusion techniques to estimate regional scale forest height and aboveground live biomass (AGLB) over the state of Maine. Two fusion techniques have been developed to perform post-processing and parameter estimations from four data sets: 1 arc sec National Elevation Data (NED), SRTM derived elevation (30 m), Landsat Enhanced Thematic Mapper (ETM) bands (30 m), derived vegetation index (VI) and NLCD2001 land cover map. The first fusion algorithm corrects for missing or erroneous NED data using an iterative interpolation approach and produces distribution of scattering phase centers from SRTM-NED in three dominant forest types of evergreen conifers, deciduous, and mixed stands. The second fusion technique integrates the USDA Forest Service, Forest Inventory and Analysis (FIA) ground-based plot data to develop an algorithm to transform the scattering phase centers into mean forest height and aboveground biomass. Height estimates over evergreen (R2 = 0.86, P forests (R2 = 0.93, P forests were less accurate because of the winter acquisition of SRTM data and loss of scattering phase center from tree ]surface interaction. We used two methods to estimate AGLB; algorithms based on direct estimation from the scattering phase center produced higher precision (R2 = 0.79, RMSE = 25 Mg/ha) than those estimated from forest height (R2 = 0.25, RMSE = 66 Mg/ha). We discuss sources of uncertainty and implications of the results in the context of mapping regional and continental scale forest biomass distribution.

Shaded Relief and Radar Image with Color as Height, Madrid, Spain

Science.gov (United States)

2002-01-01

The white, mottled area in the right-center of this image from NASA's Shuttle Radar Topography Mission (SRTM) is Madrid, the capital of Spain. Located on the Meseta Central, a vast plateau covering about 40 percent of the country, this city of 3 million is very near the exact geographic center of the Iberian Peninsula. The Meseta is rimmed by mountains and slopes gently to the west and to the series of rivers that form the boundary with Portugal. The plateau is mostly covered with dry grasslands, olive groves and forested hills.Madrid is situated in the middle of the Meseta, and at an elevation of 646 meters (2,119 feet) above sea level is the highest capital city in Europe. To the northwest of Madrid, and visible in the upper left of the image, is the Sistema Central mountain chain that forms the 'dorsal spine' of the Meseta and divides it into northern and southern subregions. Rising to about 2,500 meters (8,200 feet), these mountains display some glacial features and are snow-capped for most of the year. Offering almost year-round winter sports, the mountains are also important to the climate of Madrid.Three visualization methods were combined to produce this image: shading and color coding of topographic height and radar image intensity. The shade image was derived by computing topographic slope in the northwest-southeast direction. North-facing slopes appear bright and south-facing slopes appear dark. Color coding is directly related to topographic height, with green at the lower elevations, rising through yellow and brown to white at the highest elevations. The shade image was combined with the radar intensity image in the flat areas.Elevation data used in this image was acquired by the SRTM aboard the Space Shuttle Endeavour, launched on Feb. 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space Shuttle Endeavour in 1994. SRTM was designed to

Dengue transmission based on urban environmental gradients in different cities of Pakistan.

Science.gov (United States)

Khalid, Bushra; Ghaffar, Abdul

2015-03-01

This study focuses on the dengue transmission in different regions of Pakistan. For this purpose, the data of dengue cases for 2009-2012 from four different cities (Rawalpindi, Islamabad, Lahore, and Karachi) of the country is collected, evaluated, and compiled. To identify the reasons and regions of higher risk of Dengue transmission, land use classification, analysis of climate covariates and drainage patterns was done. Analysis involves processing of SPOT 5 10 m, Landsat TM 30 m data sets, and SRTM 90 m digital elevation models by using remote sensing and GIS techniques. The results are based on the change in urbanization and population density, analysis of temperature, rainfall, and wind speed; calculation of drainage patterns including stream features, flow accumulation, and drainage density of the study areas. Results suggest that the low elevation areas with calm winds and minimum temperatures higher than the normal, rapid increase in unplanned urbanization, low flow accumulation, and higher drainage density areas favor the dengue transmission.

Digital Elevation Profile: A Complex Tool for the Spatial Analysis of Hiking

Directory of Open Access Journals (Sweden)

Laura TÎRLĂ

2014-11-01

Full Text Available One of the current attributions of mountain geomorphology is to provide information for tourism purposes, such as the spatial analysis of hiking trails. Therefore, geomorphic tools are indispensable for terrain analyses. Elevation profile is one of the most adequate tools for assessing the morphometric patterns of the hiking trails. In this study we tested several applications in order to manage raw data, create profile graphs and obtain the morphometric parameters of five hiking trails in the Căpățânii Mountains (South Carpathians, Romania. Different data complexity was explored: distance, elevation, cumulative gain or loss, slope etc. Furthermore, a comparative morphometric analysis was performed in order to emphasize the multiple possibilities provided by the elevation profile. Results show that GPS Visualizer, Geocontext and in some manner Google Earth are the most adequate applications that provide high-quality elevation profiles and detailed data, with multiple additional functions, according to user's needs. The applied tools and techniques are very useful for mountain route planning, elaborating mountain guides, enhancing knowledge about specific trails or routes, or assessing the landscape and tourism value of a mountain area.

Remote sensing analysis of depositional landforms in alluvial settings: Method development and application to the Taquari megafan, Pantanal (Brazil)

Science.gov (United States)

Zani, Hiran; Assine, Mario Luis; McGlue, Michael Matthew

2012-08-01

Traditional Shuttle Radar Topography Mission (SRTM) topographic datasets hold limited value in the geomorphic analysis of low-relief terrains. To address this shortcoming, this paper presents a series of techniques designed to enhance digital elevation models (DEMs) of environments dominated by low-amplitude landforms, such as a fluvial megafan system. These techniques were validated through the study of a wide depositional tract composed of several megafans located within the Brazilian Pantanal. The Taquari megafan is the most remarkable of these features, covering an area of approximately 49,000 km2. To enhance the SRTM-DEM, the megafan global topography was calculated and found to be accurately represented by a second order polynomial. Simple subtraction of the global topography from altitude produced a new DEM product, which greatly enhanced low amplitude landforms within the Taquari megafan. A field campaign and optical satellite images were used to ground-truth features on the enhanced DEM, which consisted of both depositional (constructional) and erosional features. The results demonstrate that depositional lobes are the dominant landforms on the megafan. A model linking baselevel change, avulsion, clastic sedimentation, and erosion is proposed to explain the microtopographic features on the Taquari megafan surface. The study confirms the potential promise of enhanced DEMs for geomorphological research in alluvial settings.

NATURAL HAZARD ASSESSMENT OF SW MYANMAR - A CONTRIBUTION OF REMOTE SENSING AND GIS METHODS TO THE DETECTION OF AREAS VULNERABLE TO EARTHQUAKES AND TSUNAMI / CYCLONE FLOODING

Directory of Open Access Journals (Sweden)

George Pararas-Carayannis

2009-01-01

Full Text Available Myanmar, formerly Burma, is vulnerable to several natural hazards, such as earthquakes, cyclones, floods, tsunamis and landslides. The present study focuses on geomorphologic and geologic investigations of the south-western region of the country, based on satellite data (Shuttle Radar Topography Mission-SRTM, MODIS and LANDSAT. The main objective is to detect areas vulnerable to inundation by tsunami waves and cyclone surges. Since the region is also vulnerable to earthquake hazards, it is also important to identify seismotectonic patterns, the location of major active faults, and local site conditions that may enhance ground motions and earthquake intensities. As illustrated by this study, linear, topographic features related to subsurface tectonic features become clearly visible on SRTM-derived morphometric maps and on LANDSAT imagery. The GIS integrated evaluation of LANDSAT and SRTM data helps identify areas most susceptible to flooding and inundation by tsunamis and storm surges. Additionally, land elevation maps help identify sites greater than 10 m in elevation height, that would be suitable for the building of protective tsunami/cyclone shelters.

Shaded Relief with Height as Color and Landsat, Yucatan Peninsula, Mexico

Science.gov (United States)

2003-01-01

The top picture is a shaded relief image of the northwest corner of Mexico's Yucatan Peninsula generated from Shuttle Radar Topography Mission (SRTM) data, and shows a subtle, but unmistakable, indication of the Chicxulub impact crater. Most scientists now agree that this impact was the cause of the Cretatious-Tertiary Extinction, the event 65 million years ago that marked the sudden extinction of the dinosaurs as well as the majority of life on Earth. The pattern of the crater's rim is marked by a trough, the darker green semicircular line near the center of the picture. This trough is only about 3 to 5 meters (10 - 15 feet) deep and is about 5 km (3 miles) wide; so subtle that if you walked across it you probably would not notice it. It is the surface expression of the buried crater's outer boundary. Scientists believe the impact, which was centered just off the coast in the Caribbean, altered the subsurface rocks such that the overlying limestone sediments, which formed later and erode very easily, would preferentially erode along the crater rim. This formed the trough as well as numerous sinkholes (called cenotes) which are visible as small circular depressions.The bottom picture is the same area viewed by the Landsat satellite, and was made by displaying the Thematic Mapper's Band 7 (mid-infrared), Band 4 (near-infrared) and Band 2 (green) as red, green and blue. These colors were chosen to maximize the contrast between different vegetation and land cover types, with native vegetation and cultivated land showing as green, yellow and magenta, and urban areas as white. The circular white area near the center of the image is Merida, a city of about 720,000 population. Notice that in the SRTM image, which shows only topography, the city is not visible, while in the Landsat image, which does not show elevations, the trough is not visible.Two visualization methods were combined to produce the SRTM image: shading and color coding of topographic height. The shade

Geodetic Mass Balance of the Northern Patagonian Icefield from 2000 to 2012 Using Two Independent Methods

Directory of Open Access Journals (Sweden)

Inés Dussaillant

2018-02-01

Full Text Available We compare two independent estimates of the rate of elevation change and geodetic mass balance of the Northern Patagonian Icefield (NPI between 2000 (3,856 km2 and 2012 (3,740 km2 from space-borne data. The first is obtained by differencing the Shuttle Radar Topography Mission (SRTM digital elevation model (DEM from February 2000 and a Satellite pour l'Observation de la Terre 5 (SPOT5 DEM from March 2012. The second is deduced by fitting pixel-based linear elevation trends over 118 DEMs calculated from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER stereo images acquired between 2000 and 2012. Both methods lead to similar and strongly negative icefield-wide mass balance rates of −1.02 ± 0.21 and −1.06 ± 0.14 m w.e. yr−1 respectively, which is in agreement with earlier studies. Contrasting glacier responses are observed, with individual glacier mass balance rates ranging from −0.15 to −2.30 m w.e. yr−1 (standard deviation = 0.49 m w.e. yr−1; N = 38. For individual glaciers, the two methods agree within error bars, except for small glaciers poorly sampled in the SPOT5 DEM due to clouds. Importantly, our study confirms the lack of penetration of the C-band SRTM radar signal into the NPI snow and firn except for a region above 2,900 m a.s.l. covering <1% of the total area. Ignoring penetration would bias the mass balance by only 0.005 m w.e. yr−1. A strong advantage of the ASTER method is that it relies only on freely available data and can thus be extended to other glacierized areas.

Firm Elevation of Reconstructed Auricle Using Polydactyly Digit in Microtia.

Science.gov (United States)

Jang, Suk Yoon; Kim, Woo Seob; Kim, Han Koo; Bae, Tae Hui

2018-03-01

Total ear reconstruction for microtia is usually accomplished in 2 stages which is known as Nagata technique. After framework fabrication and implantation, the elevation procedure is required as a second step surgery. The authors are introducing a novel material for augmenting projection of rib cartilage framework in microtia treatment.