21,486 research outputs found
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
Exploring multiple viewshed analysis using terrain features and optimisation techniques
The calculation of viewsheds is a routine operation in geographic information systems and is used in a wide range of applications. Many of these involve the siting of features, such as radio masts, which are part of a network and yet the selection of sites is normally done separately for each feature. The selection of a series of locations which collectively maximise the visual coverage of an area is a combinatorial problem and as such cannot be directly solved except for trivial cases. In this paper, two strategies for tackling this problem are explored. The first is to restrict the search to key topographic points in the landscape such as peaks, pits and passes. The second is to use heuristics which have been applied to other maximal coverage spatial problems such as location-allocation. The results show that the use of these two strategies results in a reduction of the computing time necessary by two orders of magnitude, but at the cost of a loss of 10% in the area viewed. Three different heuristics were used, of which Simulated Annealing produced the best results. However the improvement over a much simpler fast-descent swap heuristic was very slight, but at the cost of greatly increased running times. © 2004 Elsevier Ltd. All rights reserved
An examination of spectral band rationing to reduce the topographic effect on remotely sensed data
There are no author-identified significant results in this report
3D cut-cell modelling for high-resolution atmospheric simulations
Owing to the recent, rapid development of computer technology, the resolution
of atmospheric numerical models has increased substantially. With the use of
next-generation supercomputers, atmospheric simulations using horizontal grid
intervals of O(100) m or less will gain popularity. At such high resolution
more of the steep gradients in mountainous terrain will be resolved, which may
result in large truncation errors in those models using terrain-following
coordinates. In this study, a new 3D Cartesian coordinate non-hydrostatic
atmospheric model is developed. A cut-cell representation of topography based
on finite-volume discretization is combined with a cell-merging approach, in
which small cut-cells are merged with neighboring cells either vertically or
horizontally. In addition, a block-structured mesh-refinement technique is
introduced to achieve a variable resolution on the model grid with the finest
resolution occurring close to the terrain surface. The model successfully
reproduces a flow over a 3D bell-shaped hill that shows a good agreement with
the flow predicted by the linear theory. The ability of the model to simulate
flows over steep terrain is demonstrated using a hemisphere-shaped hill where
the maximum slope angle is resolved at 71 degrees. The advantage of a locally
refined grid around a 3D hill, with cut-cells at the terrain surface, is also
demonstrated using the hemisphere-shaped hill. The model reproduces smooth
mountain waves propagating over varying grid resolution without introducing
large errors associated with the change of mesh resolution. At the same time,
the model shows a good scalability on a locally refined grid with the use of
OpenMP.Comment: 19 pages, 16 figures. Revised version, accepted for publication in
QJRM
Surface networks
© Copyright CASA, UCL. The desire to understand and exploit the structure of continuous surfaces is common to researchers in a range of disciplines. Few examples of the varied surfaces forming an integral part of modern subjects include terrain, population density, surface atmospheric pressure, physico-chemical surfaces, computer graphics, and metrological surfaces. The focus of the work here is a group of data structures called Surface Networks, which abstract 2-dimensional surfaces by storing only the most important (also called fundamental, critical or surface-specific) points and lines in the surfaces. Surface networks are intelligent and “natural ” data structures because they store a surface as a framework of “surface ” elements unlike the DEM or TIN data structures. This report presents an overview of the previous works and the ideas being developed by the authors of this report. The research on surface networks has fou
Simulations of snow distribution and hydrology in a mountain basin
We applied a version of the Regional Hydro‐Ecologic Simulation System (RHESSys) that implements snow redistribution, elevation partitioning, and wind‐driven sublimation to Loch Vale Watershed (LVWS), an alpine‐subalpine Rocky Mountain catchment where snow accumulation and ablation dominate the hydrologic cycle. We compared simulated discharge to measured discharge and the simulated snow distribution to photogrammetrically rectified aerial (remotely sensed) images. Snow redistribution was governed by a topographic similarity index. We subdivided each hillslope into elevation bands that had homogeneous climate extrapolated from observed climate. We created a distributed wind speed field that was used in conjunction with daily measured wind speeds to estimate sublimation. Modeling snow redistribution was critical to estimating the timing and magnitude of discharge. Incorporating elevation partitioning improved estimated timing of discharge but did not improve patterns of snow cover since wind was the dominant controller of areal snow patterns. Simulating wind‐driven sublimation was necessary to predict moisture losses
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