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The Influence of DEM Quality on Mapping Accuracy of Coniferous- and Deciduous-Dominated Forest Using TerraSAR‑X Images
Directory of Open Access Journals (Sweden)
Gerald Kändler
2012-03-01
Full Text Available Climate change is a factor that largely contributes to the increase of forest areas affected by natural damages. Therefore, the development of methodologies for forest monitoring and rapid assessment of affected areas is required. Space-borne synthetic aperture radar (SAR imagery with high resolution is now available for large-scale forest mapping and forest monitoring applications. However, a correct interpretation of SAR images requires an adequate preprocessing of the data consisting of orthorectification and radiometric calibration. The resolution and quality of the digital elevation model (DEM used as reference is crucial for this purpose. Therefore, the primary aim of this study was to analyze the influence of the DEM quality used in the preprocessing of the SAR data on the mapping accuracy of forest types. In order to examine TerraSAR-X images to map forest dominated by deciduous and coniferous trees, High Resolution SpotLight images were acquired for two study sites in southern Germany. The SAR images were preprocessed with a Shuttle Radar Topography Mission (SRTM DEM (resolution approximately 90 m, an airborne laser scanning (ALS digital terrain model (DTM (5 m resolution, and an ALS digital surface model (DSM (5 m resolution. The orthorectification of the SAR images using high resolution ALS DEMs was found to be important for the reduction of errors in pixel location and to increase the classification accuracy of forest types. SAR images preprocessed with ALS DTMs resulted in the highest classification accuracies, with kappa coefficients of 0.49 and 0.41, respectively. SAR images preprocessed with ALS DTMs resulted in greater accuracy than those preprocessed with ALS DSMs in most cases. The classification accuracy of forest types using SAR images preprocessed with the SRTM DEM was fair, with kappa coefficients of 0.23 and 0.32, respectively.Analysis of the radar backscatter indicated that sample plots dominated by coniferous trees
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Application of the PROMETHEE technique to determine depression outlet location and flow direction in DEM
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Chou, Tien-Yin; Lin, Wen-Tzu; Lin, Chao-Yuan; Chou, Wen-Chieh; Huang, Pi-Hui
2004-02-01
With the fast growing progress of computer technologies, spatial information on watersheds such as flow direction, watershed boundaries and the drainage network can be automatically calculated or extracted from a digital elevation model (DEM). The stubborn problem that depressions exist in DEMs has been frequently encountered while extracting the spatial information of terrain. Several filling-up methods have been proposed for solving depressions. However, their suitability for large-scale flat areas is inadequate. This study proposes a depression watershed method coupled with the Preference Ranking Organization METHod for Enrichment Evaluations (PROMETHEEs) theory to determine the optimal outlet and calculate the flow direction in depressions. Three processing procedures are used to derive the depressionless flow direction: (1) calculating the incipient flow direction; (2) establishing the depression watershed by tracing the upstream drainage area and determining the depression outlet using PROMETHEE theory; (3) calculating the depressionless flow direction. The developed method was used to delineate the Shihmen Reservoir watershed located in Northern Taiwan. The results show that the depression watershed method can effectively solve the shortcomings such as depression outlet differentiating and looped flow direction between depressions. The suitability of the proposed approach was verified.
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Accurate Determination of Glacier Surface Velocity Fields with a DEM-Assisted Pixel-Tracking Technique from SAR Imagery
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Shiyong Yan
2015-08-01
Full Text Available We obtained accurate, detailed motion distribution of glaciers in Central Asia by applying digital elevation model (DEM assisted pixel-tracking method to L-band synthetic aperture radar imagery. The paper firstly introduces and analyzes each component of the offset field briefly, and then describes the method used to efficiently and precisely compensate the topography-related offset caused by the large spatial baseline and rugged terrain with the help of DEM. The results indicate that the rugged topography not only forms the complex shapes of glaciers, but also affects the glacier velocity estimation, especially with large spatial baseline. The maximum velocity, 0.85 m∙d−1, was observed in the middle part on the Fedchenko Glacier, which is the world’s longest mountain glacier. The motion fluctuation on its main trunk is apparently influenced by mass flowing in from tributaries, as well as angles between tributaries and the main stream. The approach presented in this paper was proved to be highly appropriate for monitoring glacier motion and will provide valuable sensitive indicators of current and future climate change for environmental analysis.
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DemQSAR: predicting human volume of distribution and clearance of drugs.
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Demir-Kavuk, Ozgur; Bentzien, Jörg; Muegge, Ingo; Knapp, Ernst-Walter
2011-12-01
In silico methods characterizing molecular compounds with respect to pharmacologically relevant properties can accelerate the identification of new drugs and reduce their development costs. Quantitative structure-activity/-property relationship (QSAR/QSPR) correlate structure and physico-chemical properties of molecular compounds with a specific functional activity/property under study. Typically a large number of molecular features are generated for the compounds. In many cases the number of generated features exceeds the number of molecular compounds with known property values that are available for learning. Machine learning methods tend to overfit the training data in such situations, i.e. the method adjusts to very specific features of the training data, which are not characteristic for the considered property. This problem can be alleviated by diminishing the influence of unimportant, redundant or even misleading features. A better strategy is to eliminate such features completely. Ideally, a molecular property can be described by a small number of features that are chemically interpretable. The purpose of the present contribution is to provide a predictive modeling approach, which combines feature generation, feature selection, model building and control of overtraining into a single application called DemQSAR. DemQSAR is used to predict human volume of distribution (VD(ss)) and human clearance (CL). To control overtraining, quadratic and linear regularization terms were employed. A recursive feature selection approach is used to reduce the number of descriptors. The prediction performance is as good as the best predictions reported in the recent literature. The example presented here demonstrates that DemQSAR can generate a model that uses very few features while maintaining high predictive power. A standalone DemQSAR Java application for model building of any user defined property as well as a web interface for the prediction of human VD(ss) and CL is
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Some safe and sensible shortcuts for efficiently upscaled updates of existing elevation models.
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Knudsen, Thomas; Aasbjerg Nielsen, Allan
2013-04-01
The Danish national elevation model, DK-DEM, was introduced in 2009 and is based on LiDAR data collected in the time frame 2005-2007. Hence, DK-DEM is aging, and it is time to consider how to integrate new data with the current model in a way that improves the representation of new landscape features, while still preserving the overall (very high) quality of the model. In LiDAR terms, 2005 is equivalent to some time between the palaeolithic and the neolithic. So evidently, when (and if) an update project is launched, we may expect some notable improvements due to the technical and scientific developments from the last half decade. To estimate the magnitude of these potential improvements, and to devise efficient and effective ways of integrating the new and old data, we currently carry out a number of case studies based on comparisons between the current terrain model (with a ground sample distance, GSD, of 1.6 m), and a number of new high resolution point clouds (10-70 points/m2). Not knowing anything about the terms of a potential update project, we consider multiple scenarios ranging from business as usual: A new model with the same GSD, but improved precision, to aggressive upscaling: A new model with 4 times better GSD, i.e. a 16-fold increase in the amount of data. Especially in the latter case speeding up the gridding process is important. Luckily recent results from one of our case studies reveal that for very high resolution data in smooth terrain (which is the common case in Denmark), using local mean (LM) as grid value estimator is only negligibly worse than using the theoretically "best" estimator, i.e. ordinary kriging (OK) with rigorous modelling of the semivariogram. The bias in a leave one out cross validation differs on the micrometer level, while the RMSE differs on the 0.1 mm level. This is fortunate, since a LM estimator can be implemented in plain stream mode, letting the points from the unstructured point cloud (i.e. no TIN generation) stream
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DEM GPU studies of industrial scale particle simulations for granular flow civil engineering applications
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Pizette, Patrick; Govender, Nicolin; Wilke, Daniel N.; Abriak, Nor-Edine
2017-06-01
The use of the Discrete Element Method (DEM) for industrial civil engineering industrial applications is currently limited due to the computational demands when large numbers of particles are considered. The graphics processing unit (GPU) with its highly parallelized hardware architecture shows potential to enable solution of civil engineering problems using discrete granular approaches. We demonstrate in this study the pratical utility of a validated GPU-enabled DEM modeling environment to simulate industrial scale granular problems. As illustration, the flow discharge of storage silos using 8 and 17 million particles is considered. DEM simulations have been performed to investigate the influence of particle size (equivalent size for the 20/40-mesh gravel) and induced shear stress for two hopper shapes. The preliminary results indicate that the shape of the hopper significantly influences the discharge rates for the same material. Specifically, this work shows that GPU-enabled DEM modeling environments can model industrial scale problems on a single portable computer within a day for 30 seconds of process time.
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Comparison of elevation and remote sensing derived products as auxiliary data for climate surface interpolation
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Alvarez, Otto; Guo, Qinghua; Klinger, Robert C.; Li, Wenkai; Doherty, Paul
2013-01-01
Climate models may be limited in their inferential use if they cannot be locally validated or do not account for spatial uncertainty. Much of the focus has gone into determining which interpolation method is best suited for creating gridded climate surfaces, which often a covariate such as elevation (Digital Elevation Model, DEM) is used to improve the interpolation accuracy. One key area where little research has addressed is in determining which covariate best improves the accuracy in the interpolation. In this study, a comprehensive evaluation was carried out in determining which covariates were most suitable for interpolating climatic variables (e.g. precipitation, mean temperature, minimum temperature, and maximum temperature). We compiled data for each climate variable from 1950 to 1999 from approximately 500 weather stations across the Western United States (32° to 49° latitude and −124.7° to −112.9° longitude). In addition, we examined the uncertainty of the interpolated climate surface. Specifically, Thin Plate Spline (TPS) was used as the interpolation method since it is one of the most popular interpolation techniques to generate climate surfaces. We considered several covariates, including DEM, slope, distance to coast (Euclidean distance), aspect, solar potential, radar, and two Normalized Difference Vegetation Index (NDVI) products derived from Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS). A tenfold cross-validation was applied to determine the uncertainty of the interpolation based on each covariate. In general, the leading covariate for precipitation was radar, while DEM was the leading covariate for maximum, mean, and minimum temperatures. A comparison to other products such as PRISM and WorldClim showed strong agreement across large geographic areas but climate surfaces generated in this study (ClimSurf) had greater variability at high elevation regions, such as in the Sierra
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EXTRACTING PRECISE AND AFFORDABLE DEMS DESPITE OF THE CLOUDS. AJAX: THE JOINING OF RADAR AND OPTICAL STRENGTHS
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1 L. Cunin
2012-07-01
The DEMs extracted from TerraSAR-X and HRS proved extremely consistent with each other, showing a mean difference of 0.80m. This allows to propose a unified Elevation30 product to the users, with a guaranteed accuracy materialized into the product through a dedicated vertical Accuracy Commitment Mask.
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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
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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.
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Drainage Structure Datasets and Effects on LiDAR-Derived Surface Flow Modeling
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Ruopu Li
2013-12-01
Full Text Available With extraordinary resolution and accuracy, Light Detection and Ranging (LiDAR-derived digital elevation models (DEMs have been increasingly used for watershed analyses and modeling by hydrologists, planners and engineers. Such high-accuracy DEMs have demonstrated their effectiveness in delineating watershed and drainage patterns at fine scales in low-relief terrains. However, these high-resolution datasets are usually only available as topographic DEMs rather than hydrologic DEMs, presenting greater land roughness that can affect natural flow accumulation. Specifically, locations of drainage structures such as road culverts and bridges were simulated as barriers to the passage of drainage. This paper proposed a geospatial method for producing LiDAR-derived hydrologic DEMs, which incorporates data collection of drainage structures (i.e., culverts and bridges, data preprocessing and burning of the drainage structures into DEMs. A case study of GIS-based watershed modeling in South Central Nebraska showed improved simulated surface water derivatives after the drainage structures were burned into the LiDAR-derived topographic DEMs. The paper culminates in a proposal and discussion of establishing a national or statewide drainage structure dataset.
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Dynamic multibody modeling for tethered space elevators
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Williams, Paul
2009-08-01
This paper presents a fundamental modeling strategy for dealing with powered and propelled bodies moving along space tethers. The tether is divided into a large number of discrete masses, which are connected by viscoelastic springs. The tether is subject to the full range of forces expected in Earth orbit in a relatively simple manner. Two different models of the elevator dynamics are presented. In order to capture the effect of the elevator moving along the tether, the elevator dynamics are included as a separate body in both models. One model treats the elevator's motion dynamically, where propulsive and friction forces are applied to the elevator body. The second model treats the elevator's motion kinematically, where the distance along the tether is determined by adjusting the lengths of tether on either side of the elevator. The tether model is used to determine optimal configurations for the space elevator. A modal analysis of two different configurations is presented which show that the fundamental mode of oscillation is a pendular one around the anchor point with a period on the order of 160 h for the in-plane motion, and 24 h for the out-of-plane motion. Numerical simulation results of the effects of the elevator moving along the cable are presented for different travel velocities and different elevator masses.
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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.
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Extraction of multi-scale landslide morphological features based on local Gi* using airborne LiDAR-derived DEM
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Shi, Wenzhong; Deng, Susu; Xu, Wenbing
2018-02-01
For automatic landslide detection, landslide morphological features should be quantitatively expressed and extracted. High-resolution Digital Elevation Models (DEMs) derived from airborne Light Detection and Ranging (LiDAR) data allow fine-scale morphological features to be extracted, but noise in DEMs influences morphological feature extraction, and the multi-scale nature of landslide features should be considered. This paper proposes a method to extract landslide morphological features characterized by homogeneous spatial patterns. Both profile and tangential curvature are utilized to quantify land surface morphology, and a local Gi* statistic is calculated for each cell to identify significant patterns of clustering of similar morphometric values. The method was tested on both synthetic surfaces simulating natural terrain and airborne LiDAR data acquired over an area dominated by shallow debris slides and flows. The test results of the synthetic data indicate that the concave and convex morphologies of the simulated terrain features at different scales and distinctness could be recognized using the proposed method, even when random noise was added to the synthetic data. In the test area, cells with large local Gi* values were extracted at a specified significance level from the profile and the tangential curvature image generated from the LiDAR-derived 1-m DEM. The morphologies of landslide main scarps, source areas and trails were clearly indicated, and the morphological features were represented by clusters of extracted cells. A comparison with the morphological feature extraction method based on curvature thresholds proved the proposed method's robustness to DEM noise. When verified against a landslide inventory, the morphological features of almost all recent (historical (> 10 years) landslides were extracted. This finding indicates that the proposed method can facilitate landslide detection, although the cell clusters extracted from curvature images should
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DEM Calibration Approach: design of experiment
Science.gov (United States)
Boikov, A. V.; Savelev, R. V.; Payor, V. A.
2018-05-01
The problem of DEM models calibration is considered in the article. It is proposed to divide models input parameters into those that require iterative calibration and those that are recommended to measure directly. A new method for model calibration based on the design of the experiment for iteratively calibrated parameters is proposed. The experiment is conducted using a specially designed stand. The results are processed with technical vision algorithms. Approximating functions are obtained and the error of the implemented software and hardware complex is estimated. The prospects of the obtained results are discussed.
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Construction of Urban 3-D Model of Hanoi, Vietnam Using FOSS Tools
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Yonezawa, G.; Mitamura, M.; Sakurai, K.; Luan, T. X.; Raghavan, V.; Masumoto, S.; Nemoto, T.; Nonogaki, S.
2013-12-01
In this study, we investigate an urban transformation of Hanoi City, Vietnam from topographic changes in the 19-20 centuries. To analyze the relief of terrain and micro-topography for such an urban transfiguration, we need to generate the DEM (Digital Elevation Model) using the elevation survey data. DEM is a digital representation of ground surface topography and the most important element of topographic analysis for urban transfiguration. And, the three dimensional (3-D) mode of buildings which we generated from house map in Hanoi City can be also expressed apparently. It must be useful for an urban transformation because it is difficult to estimate how so many lakes and ponds disappeared by using two dimensional (2-D) spatial analysis only. We generated the DEM (8km x 8km) of Hanoi City from approximately 24,000 points data collected in 2005. This survey data was provided by Hanoi University of Mining and Geology (HUMG). Based on the surface estimation method using Cubic B-Spline Function, we generated this DEM at 2 meters resolution (Nonogaki et al., 2008). The very subtle elevation gaps which can not be distinguished on the satellite image are significantly recognizable on it. The example of the visualization of 3-D DEM is shown in Figure 1 using the NVIZ of visualization tool in GRASS GIS software. It is overlaid the Hanoi road map on the generated DEM. We generated the vector map of each block of houses in the Pho Co district in Hanoi City by using the house maps in 2005 which are provided by HUMG. It is consisted of 12,000 polygon data. These are converted the 3-D data (features) using the GIS software. This 3-D model is not only visualized the landscape in the Pho Co district accurately, but also reflected the elevation in this area. Thus, the 3-D features are built on DEM which is shown in Chapter 3. Therefore, we can create an overview of how the current urbanization is advancing in the area where the lakes and ponds existed in the past. Example of the
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Fusion of Multi-Source Satellite Data and DEMs to Create a New Glacier Inventory for Novaya Zemlya
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Philipp Rastner
2017-11-01
Full Text Available Monitoring glacier changes in remote Arctic regions are strongly facilitated by satellite data. This is especially true for the Russian Arctic where recently increased optical and SAR satellite imagery (Landsat 8 OLI, Sentinel 1/2, and digital elevation models (TanDEM-X, ArcticDEM are becoming available. These datasets offer new possibilities to create high-quality glacier inventories. Here, we present a new glacier inventory derived from a fusion of multi-source satellite data for Novaya Zemlya in the Russian Arctic. We mainly used Landsat 8 OLI data to automatically map glaciers with the band ratio method. Missing debris-covered glacier parts and misclassified lakes were manually corrected. Whereas perennial snow fields were a major obstacle in glacier identification, seasonal snow was identified and removed using Landsat 5 TM scenes from the year 1998. Drainage basins were derived semi-automatically using the ArcticDEM (gap-filled by the ASTER GDEM V2 and manually corrected using fringes from ALOS PALSAR. The new glacier inventory gives a glacierized area of 22,379 ± 246.16 km2 with 1474 glacier entities >0.05 km2. The region is dominated by large glaciers, as 909 glaciers <0.5 km2 (62% by number cover only 156 ± 1.7 km2 or 0.7% of the area, whereas 49 glaciers >100 km2 (3.3% by number cover 18,724 ± 205.9 km2 or 84%. In total, 41 glaciers are marine terminating covering an area of 16,063.7 ± 118.8 km2. The mean elevation is 596 m for all glaciers in the study region (528 m in the northern part, 641 in the southern part. South-east (north-west facing glaciers cover >35% (20% of the area. For the smaller glaciers in the southern part we calculated an area loss of ~5% (52.5 ± 4.5 km2 from 2001 to 2016.
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An evaluation of automated GIS tools for delineating karst sinkholes and closed depressions from 1-meter LIDAR-derived digital elevation data
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Doctor, Daniel H.; Young, John A.
2013-01-01
LiDAR (Light Detection and Ranging) surveys of karst terrains provide high-resolution digital elevation models (DEMs) that are particularly useful for mapping sinkholes. In this study, we used automated processing tools within ArcGIS (v. 10.0) operating on a 1.0 m resolution LiDAR DEM in order to delineate sinkholes and closed depressions in the Boyce 7.5 minute quadrangle located in the northern Shenandoah Valley of Virginia. The results derived from the use of the automated tools were then compared with depressions manually delineated by a geologist. Manual delineation of closed depressions was conducted using a combination of 1.0 m DEM hillshade, slopeshade, aerial imagery, and Topographic Position Index (TPI) rasters. The most effective means of visualizing depressions in the GIS was using an overlay of the partially transparent TPI raster atop the slopeshade raster at 1.0 m resolution. Manually identified depressions were subsequently checked using aerial imagery to screen for false positives, and targeted ground-truthing was undertaken in the field. The automated tools that were utilized include the routines in ArcHydro Tools (v. 2.0) for prescreening, evaluating, and selecting sinks and depressions as well as thresholding, grouping, and assessing depressions from the TPI raster. Results showed that the automated delineation of sinks and depressions within the ArcHydro tools was highly dependent upon pre-conditioning of the DEM to produce "hydrologically correct" surface flow routes. Using stream vectors obtained from the National Hydrologic Dataset alone to condition the flow routing was not sufficient to produce a suitable drainage network, and numerous artificial depressions were generated where roads, railways, or other manmade structures acted as flow barriers in the elevation model. Additional conditioning of the DEM with drainage paths across these barriers was required prior to automated 2delineation of sinks and depressions. In regions where the DEM
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High-resolution digital elevation model of lower Cowlitz and Toutle Rivers, adjacent to Mount St. Helens, Washington, based on an airborne lidar survey of October 2007
Science.gov (United States)
Mosbrucker, Adam
2015-01-01
The lateral blast, debris avalanche, and lahars of the May 18th, 1980, eruption of Mount St. Helens, Washington, dramatically altered the surrounding landscape. Lava domes were extruded during the subsequent eruptive periods of 1980–1986 and 2004–2008. More than three decades after the emplacement of the 1980 debris avalanche, high sediment production persists in the Toutle River basin, which drains the northern and western flanks of the volcano. Because this sediment increases the risk of flooding to downstream communities on the Toutle and lower Cowlitz Rivers, the U.S. Army Corps of Engineers (USACE), under the direction of Congress to maintain an authorized level of flood protection, continues to monitor and mitigate excess sediment in North and South Fork Toutle River basins to help reduce this risk and to prevent sediment from clogging the shipping channel of the Columbia River. From October 22–27, 2007, Watershed Sciences, Inc., under contract to USACE, collected high-precision airborne lidar (light detection and ranging) data that cover 273 square kilometers (105 square miles) of lower Cowlitz and Toutle River tributaries from the Columbia River at Kelso, Washington, to upper North Fork Toutle River (below the volcano's edifice), including lower South Fork Toutle River. These data provide a digital dataset of the ground surface, including beneath forest cover. Such remotely sensed data can be used to develop sediment budgets and models of sediment erosion, transport, and deposition. The U.S. Geological Survey (USGS) used these lidar data to develop digital elevation models (DEMs) of the study area. DEMs are fundamental to monitoring natural hazards and studying volcanic landforms, fluvial and glacial geomorphology, and surface geology. Watershed Sciences, Inc., provided files in the LASer (LAS) format containing laser returns that had been filtered, classified, and georeferenced. The USGS produced a hydro-flattened DEM from ground-classified points at
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Multiscale geomorphometric modeling of Mercury
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Florinsky, I. V.
2018-02-01
Topography is one of the key characteristics of a planetary body. Geomorphometry deals with quantitative modeling and analysis of the topographic surface and relationships between topography and other natural components of landscapes. The surface of Mercury is systematically studied by interpretation of images acquired during the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) mission. However, the Mercurian surface is still little explored by methods of geomorphometry. In this paper, we evaluate the Mercury MESSENGER Global DEM MSGR_DEM_USG_SC_I_V02 - a global digital elevation model (DEM) of Mercury with the resolution of 0.015625° - as a source for geomorphometric modeling of this planet. The study was performed at three spatial scales: the global, regional (the Caloris basin), and local (the Pantheon Fossae area) ones. As the initial data, we used three DEMs of these areas with resolutions of 0.25°, 0.0625°, and 0.015625°, correspondingly. The DEMs were extracted from the MESSENGER Global DEM. From the DEMs, we derived digital models of several fundamental morphometric variables, such as: slope gradient, horizontal curvature, vertical curvature, minimal curvature, maximal curvature, catchment area, and dispersive area. The morphometric maps obtained represent peculiarities of the Mercurian topography in different ways, according to the physical and mathematical sense of a particular variable. Geomorphometric models are a rich source of information on the Mercurian surface. These data can be utilized to study evolution and internal structure of the planet, for example, to visualize and quantify regional topographic differences as well as to refine geological boundaries.
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Use of Light Detection and Ranging (LiDAR) to Obtain High-Resolution Elevation Data for Sussex County, Delaware
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Barlow, Roger A.; Nardi, Mark R.; Reyes, Betzaida
2008-01-01
Sussex County, Delaware, occupies a 938-square-mile area of low relief near sea level in the Atlantic Coastal Plain. The county is bounded on the east by the Delaware Bay and the Atlantic Ocean, including a barrier-island system, and inland bays that provide habitat for valuable living resources. Eastern Sussex County is an area of rapid population growth with a long-established beach-resort community, where land elevation is a key factor in determining areas that are appropriate for development. Of concern to State and local planners are evacuation routes inland to escape flooding from severe coastal storms, as most major transportation routes traverse areas of low elevation that are subject to inundation. The western half of the county is typically rural in character, and land use is largely agricultural with some scattered forest land cover. Western Sussex County has several low-relief river flood-prone areas, where accurate high-resolution elevation data are needed for Federal Emergency Management Agency (FEMA) Digital Flood Insurance Rate Map (DFIRM) studies. This fact sheet describes the methods and techniques used to collect and process LiDAR elevation data, the generation of the digital elevation model (DEM) and the 2-foot contours, and the quality-assurance procedures and results. It indicates where to view metadata on the data sets and where to acquire bare-earth mass points, DEM data, and contour data.
