37,306 research outputs found
Evaluating the Differences of Gridding Techniques for Digital Elevation Models Generation and Their Influence on the Modeling of Stony Debris Flows Routing: A Case Study From Rovina di Cancia Basin (North-Eastern Italian Alps)
Debris \ufb02ows are among the most hazardous phenomena in mountain areas. To cope
with debris \ufb02ow hazard, it is common to delineate the risk-prone areas through
routing models. The most important input to debris \ufb02ow routing models are the
topographic data, usually in the form of Digital Elevation Models (DEMs). The quality
of DEMs depends on the accuracy, density, and spatial distribution of the sampled
points; on the characteristics of the surface; and on the applied gridding methodology.
Therefore, the choice of the interpolation method affects the realistic representation
of the channel and fan morphology, and thus potentially the debris \ufb02ow routing
modeling outcomes. In this paper, we initially investigate the performance of common
interpolation methods (i.e., linear triangulation, natural neighbor, nearest neighbor,
Inverse Distance to a Power, ANUDEM, Radial Basis Functions, and ordinary kriging)
in building DEMs with the complex topography of a debris \ufb02ow channel located
in the Venetian Dolomites (North-eastern Italian Alps), by using small footprint full-
waveform Light Detection And Ranging (LiDAR) data. The investigation is carried
out through a combination of statistical analysis of vertical accuracy, algorithm
robustness, and spatial clustering of vertical errors, and multi-criteria shape reliability
assessment. After that, we examine the in\ufb02uence of the tested interpolation algorithms
on the performance of a Geographic Information System (GIS)-based cell model for
simulating stony debris \ufb02ows routing. In detail, we investigate both the correlation
between the DEMs heights uncertainty resulting from the gridding procedure and
that on the corresponding simulated erosion/deposition depths, both the effect of
interpolation algorithms on simulated areas, erosion and deposition volumes, solid-liquid
discharges, and channel morphology after the event. The comparison among the tested
interpolation methods highlights that the ANUDEM and ordinary kriging algorithms
are not suitable for building DEMs with complex topography. Conversely, the linear
triangulation, the natural neighbor algorithm, and the thin-plate spline plus tension and completely regularized spline functions ensure the best trade-off among accuracy
and shape reliability. Anyway, the evaluation of the effects of gridding techniques on
debris \ufb02ow routing modeling reveals that the choice of the interpolation algorithm does
not signi\ufb01cantly affect the model outcomes
Discrete Surface Modeling Based on Google Earth: A Case Study
Google Earth (GE) has become a powerful tool for geological, geophysical and
geographical modeling; yet GE can be accepted to acquire elevation data of
terrain. In this paper, we present a real study case of building the discrete
surface model (DSM) at Haut-Barr Castle in France based on the elevation data
of terrain points extracted from GE using the COM API. We first locate the
position of Haut-Barr Castle and determine the region of the study area, then
extract elevation data of terrain at Haut-Barr, and thirdly create a planar
triangular mesh that covers the study area and finally generate the desired DSM
by calculating the elevation of vertices in the planar mesh via interpolating
with Universal Kriging (UK) and Inverse Distance Weighting (IDW). The generated
DSM can reflect the features of the ground surface at Haut-Barr well, and can
be used for constructingthe Sealed Engineering Geological Model (SEGM) in
further step.Comment: Proceedings of IEEE Conference, ICCSNT 2012, in Pres
Use of plan curvature variations for the identification of ridges and channels on DEM
This paper proposes novel improvements in the traditional algorithms for the identification of ridge and channel (also called ravines) topographic features on raster digital elevation models (DEMs). The overall methodology consists of two main steps: (1) smoothing the DEM by applying a mean filter, and (2) detection of ridge and channel features as cells with positive and negative plan curvature respectively, along with a decline and incline in plan curvature away from the cell in direction orthogonal to the feature axis respectively. The paper demonstrates a simple approach to visualize the multi-scale structure of terrains and utilize it for semi-automated topographic feature identification. Despite its simplicity, the revised algorithm produced markedly superior outputs than a comparatively sophisticated feature extraction algorithm based on conic-section analysis of terrain
Terrain Database Correlation Assessment Using an Open Source Tool
Configuring networked simulators for training military teams in a distributed
environment requires the usage of a set of terrain databases to represent the
same training area. The results of simulation exercises can be degraded if the
terrain databases are poorly correlated. A number of methodologies for
determining the correlation between terrain databaHowever, there are few
computational tools for this task and most of them were developed to address
government needs, have limited availability, and handle specific digital
formats. The goal of this paper is thus to present a novel open source tool
developed as part of an academic research project.Comment: 12 pages, I/ITSEC 201
Fast approximation of visibility dominance using topographic features as targets and the associated uncertainty
An approach to reduce visibility index computation time andmeasure the associated uncertainty in terrain visibility analysesis presented. It is demonstrated that the visibility indexcomputation time in mountainous terrain can be reduced substantially,without any significant information loss, if the lineof sight from each observer on the terrain is drawn only to thefundamental topographic features, i.e., peaks, pits, passes,ridges, and channels. However, the selected sampling of targetsresults in an underestimation of the visibility index ofeach observer. Two simple methods based on iterative comparisonsbetween the real visibility indices and the estimatedvisibility indices have been proposed for a preliminary assessmentof this uncertainty. The method has been demonstratedfor gridded digital elevation models
Airborne LiDAR for DEM generation: some critical issues
Airborne LiDAR is one of the most effective and reliable means of terrain data collection. Using LiDAR data for DEM generation is becoming a standard practice in spatial related areas. However, the effective processing of the raw LiDAR data and the generation of an efficient and high-quality DEM remain big challenges. This paper reviews the recent advances of airborne LiDAR systems and the use of
LiDAR data for DEM generation, with special focus on LiDAR data filters, interpolation methods, DEM resolution, and LiDAR data reduction. Separating LiDAR points into ground and non-ground is the most critical and difficult step for
DEM generation from LiDAR data. Commonly used and most recently developed LiDAR filtering methods are presented. Interpolation methods and choices of suitable interpolator and DEM resolution for LiDAR DEM generation are discussed in detail. In order to reduce the data redundancy and increase the efficiency in terms of storage
and manipulation, LiDAR data reduction is required in the process of DEM generation. Feature specific elements such as breaklines contribute significantly to DEM quality. Therefore, data reduction should be conducted in such a way that critical elements are kept while less important elements are removed. Given the highdensity
characteristic of LiDAR data, breaklines can be directly extracted from LiDAR data. Extraction of breaklines and integration of the breaklines into DEM generation are presented
Assessment of a photogrammetric approach for urban DSM extraction from tri-stereoscopic satellite imagery
Built-up environments are extremely complex for 3D surface modelling purposes. The main distortions that hamper 3D reconstruction from 2D imagery are image dissimilarities, concealed areas, shadows, height discontinuities and discrepancies between smooth terrain and man-made features. A methodology is proposed to improve automatic photogrammetric extraction of an urban surface model from high resolution satellite imagery with the emphasis on strategies to reduce the effects of the cited distortions and to make image matching more robust. Instead of a standard stereoscopic approach, a digital surface model is derived from tri-stereoscopic satellite imagery. This is based on an extensive multi-image matching strategy that fully benefits from the geometric and radiometric information contained in the three images. The bundled triplet consists of an IKONOS along-track pair and an additional near-nadir IKONOS image. For the tri-stereoscopic study a densely built-up area, extending from the centre of Istanbul to the urban fringe, is selected. The accuracy of the model extracted from the IKONOS triplet, as well as the model extracted from only the along-track stereopair, are assessed by comparison with 3D check points and 3D building vector data
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