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Spectral filtering as a method of visualising and removing striped artefacts in digital elevation data
Spectral filtering was compared with traditional mean spatial filters to assess their ability to identify and remove striped artefacts in digital elevation data. The techniques were applied to two datasets: a 100 m contour derived digital elevation model (DEM) of southern Norway and a 2 m LiDAR DSM of the Lake District, UK. Both datasets contained diagonal data artefacts that were found to propagate into subsequent terrain analysis. Spectral filtering used fast Fourier transformation (FFT) frequency data to identify these data artefacts in both datasets. These were removed from the data by applying a cut filter, prior to the inverse transform. Spectral filtering showed considerable advantages over mean spatial filters, when both the absolute and spatial distribution of elevation changes made were examined. Elevation changes from the spectral filtering were restricted to frequencies removed by the cut filter, were small in magnitude and consequently avoided any global smoothing. Spectral filtering was found to avoid the smoothing of kernel based data editing, and provided a more informative measure of data artefacts present in the FFT frequency domain. Artefacts were found to be heterogeneous through the surfaces, a result of their strong correlations with spatially autocorrelated variables: landcover and landsurface geometry. Spectral filtering performed better on the 100 m DEM, where signal and artefact were clearly distinguishable in the frequency data. Spectrally filtered digital elevation datasets were found to provide a superior and more precise representation of the landsurface and be a more appropriate dataset for any subsequent geomorphological applications
Debris Thickness of Glaciers in the Everest Area (Nepal Himalaya) Derived from Satellite Imagery Using a Nonlinear Energy Balance Model
Debris thickness is an important characteristic of debris-covered glaciers in the Everest region of the Himalayas. The debris thickness controls the melt rates of the glaciers, which has large implications for hydrologic models, the glaciers' response to climate change, and the development of glacial lakes. Despite its importance, there is little knowledge of how the debris thickness varies over these glaciers. This paper uses an energy balance model in conjunction with Landsat7 Enhanced Thematic Mapper Plus (ETM+) satellite imagery to derive thermal resistances, which are the debris thickness divided by the thermal conductivity. Model results are reported in terms of debris thickness using an effective thermal conductivity derived from field data. The developed model accounts for the nonlinear temperature gradient in the debris cover to derive reasonable debris thicknesses. Fieldwork performed on Imja-Lhotse Shar Glacier in September 2013 was used to compare to the modeled debris thicknesses. Results indicate that accounting for the nonlinear temperature gradient is crucial. Furthermore, correcting the incoming shortwave radiation term for the effects of topography and resampling to the resolution of the thermal band's pixel is imperative to deriving reasonable debris thicknesses. Since the topographic correction is important, the model will improve with the quality of the digital elevation model (DEM). The main limitation of this work is the poor resolution (60m) of the satellite's thermal band. The derived debris thicknesses are reasonable at this resolution, but trends related to slope and aspect are unable to be modeled on a finer scale. Nonetheless, the study finds this model derives reasonable debris thicknesses on this scale and was applied to other debris-covered glaciers in the Everest region.USAID Climate Change Resilient Development (CCRD) projectCenter for Research in Water Resource
Forestry timber typing. Tanana demonstration project, Alaska ASVT
The feasibility of using LANDSAT digital data in conjunction with topographic data to delineate commercial forests by stand size and crown closure in the Tanana River basin of Alaska was tested. A modified clustering approach using two LANDSAT dates to generate an initial forest type classification was then refined with topographic data. To further demonstrate the ability of remotely sensed data in a fire protection planning framework, the timber type data were subsequently integrated with terrain information to generate a fire hazard map of the study area. This map provides valuable assistance in initial attack planning, determining equipment accessibility, and fire growth modeling. The resulting data sets were incorporated into the Alaska Department of Natural Resources geographic information system for subsequent utilization
Diagnosing the time-dependence of active region core heating from the emission measure: I. Low-frequency nanoflares
Observational measurements of active region emission measures contain clues
to the time-dependence of the underlying heating mechanism. A strongly
non-linear scaling of the emission measure with temperature indicates a large
amount of hot plasma relative to warm plasma. A weakly non-linear (or linear)
scaling of the emission measure indicates a relatively large amount of warm
plasma, suggesting that the hot active region plasma is allowed to cool and so
the heating is impulsive with a long repeat time. This case is called {\it
low-frequency} nanoflare heating and we investigate its feasibility as an
active region heating scenario here. We explore a parameter space of heating
and coronal loop properties with a hydrodynamic model. For each model run, we
calculate the slope of the emission measure distribution . Our conclusions are: (1) low-frequency nanoflare heating is
consistent with about 36% of observed active region cores when uncertainties in
the atomic data are not accounted for; (2) proper consideration of
uncertainties yields a range in which as many as 77% of observed active regions
are consistent with low-frequency nanoflare heating and as few as zero; (3)
low-frequency nanoflare heating cannot explain observed slopes greater than 3;
(4) the upper limit to the volumetric energy release is in the region of 50 erg
cm to avoid unphysical magnetic field strengths; (5) the heating
timescale may be short for loops of total length less than 40 Mm to be
consistent with the observed range of slopes; (6) predicted slopes are
consistently steeper for longer loops
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
Scaling gridded river networks for macroscale hydrology: Development, analysis, and control of error
A simple and robust river network scaling algorithm (NSA) is presented to rescale fineâresolution networks to any coarser resolution. The algorithm was tested over the Danube River basin and the European continent. Coarseâresolution networks, at 2.5, 5, 10, and 30 min resolutions, were derived from higherâresolution gridded networks using NSA and geomorphometric attributes, such as river order, shape index, and width function. These parameters were calculated and compared at each resolution. Simple scaling relationships were found to predict decreasing river lengths with coarserâresolution data. This relationship can be used to correct river length as a function of grid resolution. The lengthâcorrected width functions of the major river basins in Europe were compared at different resolutions to assess river network performance. The discretization error in representing basin area and river lengths at coarser resolutions were analyzed, and simple relationships were found to calculate the minimum number of grid cells needed to maintain the catchment area and length within a desired level of accuracy. This relationship among geomorphological characteristics, such as shape index and width function (derived from gridded networks at different resolutions), suggests that a minimum of 200â300 grid cells is necessary to maintain the geomorphological characteristics of the river networks with sufficient accuracy
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
Rapid methods of landslide hazard mapping : Fiji case study
A landslide hazard probability map can help planners (1) prepare for, and/or mitigate against,
the effects of landsliding on communities and infrastructure, and (2) avoid or minimise the
risks associated with new developments. The aims of the project were to establish, by means
of studies in a few test areas, a generic method by which remote sensing and data analysis
using a geographic information system (GIS) could provide a provisional landslide hazard
zonation map. The provision of basic hazard information is an underpinning theme of the
UNâs International Decade for Natural Disaster Reduction (IDNDR). It is an essential
requirement for disaster preparedness and mitigation planning. This report forms part of BGS
project 92/7 (R5554) âRapid assessment of landslip hazardsâ Carried out under the ODA/BGS
Technology Development and Research Programme as part of the British Governmentâs
provision of aid to developing countries. It provides a detailed technical account of work
undertaken in a test area in Viti Levu in collaboration with Fiji Mineral Resources
Department. The study represents a demonstration of a methodology that is applicable to
many developing countries.
The underlying principle is that relationships between past landsliding events, interpreted
from remote sensing, and factors such as the geology, relief, soils etc provide the basis for
modelling where future landslides are most likely to occur. This is achieved using a GIS by
âweightingâ each class of each variable (e.g. each lithology âclassâ of the variable âgeologyâ)
according to the proportion of landslides occurring within it compared to the regional
average. Combinations of variables, produced by summing the weights in individual classes,
provide âmodelsâ of landslide probability. The approach is empirical but has the advantage
of potentially being able to provide regional scale hazard maps over large areas quickly and
cheaply; this is unlikely to be achieved using conventional ground-based geotechnical
methods.
In Fiji, landslides are usually triggered by intense rain storms commonly associated with
tropical cyclones. However, the regional distribution of landslides has not been mapped nor
is it known how far geology and landscape influence the location and severity of landsliding
events. The report discusses the remote sensing and GIS methodology, and describes the
results of the pilot study over an area of 713 km2 in south east Viti Levu. The landslide
model uses geology, elevation, slope angle, slope aspect, soil type, and forest cover as
inputs. The resulting provisional landslide hazard zonation map, divided into high, medium
and low zones of landslide hazard probability, suggests that whilst rainfall is the immediate
cause, others controls do exert a significant influence. It is recommended that consideration
be given in Fiji to implementing the techniques as part of a national strategic plan for
landslide hazard zonation mapping
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