scholarly journals Approaches to Mesoscale Pressure Patterns from Mobile Data Platforms

2021 ◽  
Vol 8 (1) ◽  
pp. 46
Author(s):  
Loren White
Keyword(s):  
Dynamic Change ◽  
Potential Temperature ◽  
Barometric Pressure ◽  
Flow Speed ◽  
State University ◽  
Least Squares Regression ◽  
Digital Elevation ◽  
Elevation Data ◽  
Elevation Changes ◽  
Elevation Model

Measurements of atmospheric pressure by mesoscale transects of vehicle platforms such as the National Severe Storms Lab (NSSL) mobile mesonets have previously been collected in various targeted field campaigns. The challenges involved were specifically documented in the very different environments of tornadogenesis (Markowski et al., 2002) and orographic foehn winds (Raab and Mayr 2008). In recent years, the Jackson State University Mobile Meteorology Unit (MMU) has been developed with broad ranging applications in mind. Barometric pressure was originally expected only to be used for calculation of potential temperature over transects with significant elevation change. Previous studies have determined a dynamic change in measured pressure due to vehicle motion relative to the air that varies quadratically with speed, in agreement with theoretical expectations. This quadratic relationship is examined for the MMU under a variety of conditions. In order to consider least squares regression of this relationship, it was necessary to also have accurate speed and elevation data. Since even quite small elevation changes can produce measurable pressure changes, it was considered necessary to reduce pressures in each transect to the mean elevation using the methodology of Markowski et al. (2002). This required a combination of digital elevation model (DEM) and geographic positioning system (GPS) data to have sufficiently accurate elevations matched to the locations of the pressure measurements. Speed relative to ground from the GPS was used in place of actual air flow speed. Cases to be discussed include transects from approximately 20 to 200 km in length: approximately uniform conditions in flat terrain; crossing of orographic barriers; and cold fronts. Differences between pressure data collected with and without a pressure port are also considered. The impacts for determination of mesoscale pressure gradients, potential temperature, and other derived quantities will be evaluated.

scholarly journals Use of historical elevation data to calculate surface-elevation and volume changes of Ha-Iltzuk Icefield, southwest British Columbia, Canada, 1970 to mid-1980s

2011 ◽  
Vol 52 (59) ◽  
pp. 109-115 ◽  
Author(s):  
Jeffrey A. VanLooy ◽  
Richard R. Forster
Keyword(s):  
British Columbia ◽  
Average Rate ◽  
Meteorological Data ◽  
Surface Elevation ◽  
Volume Changes ◽  
Digital Elevation ◽  
Elevation Data ◽  
Elevation Changes ◽  
Elevation Model ◽  
Thinning Rate

AbstractInvestigations into glacial changes, including understanding variations in the rates of glacial volume and surface-elevation changes, have increased over the past decade. This study uses historical glacier elevation data in the form of topographic maps from 1970 and a digital elevation model from the mid-1980s to calculate surface-elevation and volume changes for Ha-Iltzuk Icefield, southwest British Columbia, Canada. Results indicate that the icefield thinned at an average rate of 0.76±0.25 ma–1 during this period. A previous study of Ha-Iltzuk Icefield also using the geodetic method found a thinning rate of 1.0±0.20ma–1 between the mid-1980s and 1999, indicating a slight increase in the amount of icefield thinning. Within the ablation zone, thinning increased with decreasing elevation at a rate of 1.9±0.68 ma–1 km–1 between these two periods (1970 to mid-1980s versus mid-1980s to 1999). Analysis of meteorological data suggests that increases in both temperature and rainfall, as well as decreases in snowfall, likely contributed to the increased thinning rate.

Urban Flood Mapping

2017 ◽  
Author(s):  
Indra Riyanto ◽  
Lestari Margatama
Keyword(s):  
Natural Disasters ◽  
Satisfying Condition ◽  
Three Dimensions ◽  
Urban Flood ◽  
Digital Elevation ◽  
Elevation Data ◽  
Recent Occurrence ◽  
Elevation Model ◽  
Digital Elevation Model Data ◽  
Potential Area

The recent degradation of environment quality becomes the prime cause of the recent occurrence of natural disasters. It also contributes in the increase of the area that is prone to natural disasters. Flood history data in Jakarta shows that flood occurred mainly during rainy season around January – February each year, but the flood area varies each year. This research is intended to map the flood potential area in DKI Jakarta by segmenting the Digital Elevation Model data. The data used in this research is contour data obtained from DPP–DKI with the resolution of 1 m. The data processing involved in this research is extracting the surface elevation data from the DEM, overlaying the river map of Jakarta with the elevation data. Subsequently, the data is then segmented using watershed segmentation method. The concept of watersheds is based on visualizing an image in three dimensions: two spatial coordinates versus gray levels, in which there are two specific points; that are points belonging to a regional minimum and points at which a drop of water, if placed at the location of any of those points, would fall with certainty to a single minimum. For a particular regional minimum, the set of points satisfying the latter condition is called the catchments basin or watershed of that minimum, while the points satisfying condition form more than one minima are termed divide lines or watershed lines. The objective of this segmentation is to find the watershed lines of the DEM image. The expected result of the research is the flood potential area information, especially along the Ciliwung river in DKI Jakarta.

scholarly journals MAT: GIS-Based Morphometry Assessment Tools for Concave Landforms

2021 ◽  
Vol 13 (14) ◽  
pp. 2810
Author(s):  
Joanna Gudowicz ◽  
Renata Paluszkiewicz
Keyword(s):  
Rapid Development ◽  
Assessment Tools ◽  
Lidar Data ◽  
Automatic Extraction ◽  
Sensing Technology ◽  
Digital Elevation ◽  
Elevation Data ◽  
Elevation Model ◽  
Morphometric Assessment ◽  
Morphometric Evaluation

The rapid development of remote sensing technology for obtaining high-resolution digital elevation models (DEMs) in recent years has made them more and more widely available and has allowed them to be used for morphometric assessment of concave landforms, such as valleys, gullies, glacial cirques, sinkholes, craters, and others. The aim of this study was to develop a geographic information systems (GIS) toolbox for the automatic extraction of 26 morphometric characteristics, which include the geometry, hypsometry, and volume of concave landforms. The Morphometry Assessment Tools (MAT) toolbox in the ArcGIS software was developed. The required input data are a digital elevation model and the form boundary as a vector layer. The method was successfully tested on an example of 21 erosion-denudation valleys located in the young glacial area of northwest Poland. Calculations were based on elevation data collected in the field and LiDAR data. The results obtained with the tool showed differences in the assessment of the volume parameter at the average level of 12%, when comparing the field data and LiDAR data. The algorithm can also be applied to other types of concave forms, as well as being based on other DEM data sources, which makes it a universal tool for morphometric evaluation.

scholarly journals An algorithm for delineating and extracting hillslopes and hillslope width functions from gridded elevation data

2011 ◽  
Vol 8 (5) ◽  
pp. 8865-8901
Author(s):  
P. Noel ◽  
A. N. Rousseau ◽  
C. Paniconi
Keyword(s):  
Three Dimensional ◽  
Rainfall Runoff ◽  
Dimensional Representation ◽  
New Approach ◽  
One Dimensional ◽  
Digital Elevation ◽  
Elevation Data ◽  
Average Profile ◽  
Elevation Model ◽  
Digital Elevation Model Resolution

Abstract. Subdivision of catchment into appropriate hydrological units is essential to represent rainfall-runoff processes in hydrological modelling. The commonest units used for this purpose are hillslopes (e.g. Fan and Bras, 1998; Troch et al., 2003). Hillslope width functions can therefore be utilised as one-dimensional representation of three-dimensional landscapes by introducing profile curvatures and plan shapes. An algorithm was developed to delineate and extract hillslopes and hillslope width functions by introducing a new approach to calculate an average profile curvature and plan shape. This allows the algorithm to be independent of digital elevation model resolution and to associate hillslopes to nine elementary landscapes according to Dikau (1989). This algortihm was tested on two flat and steep catchments of the province of Quebec, Canada. Results showed great area coverage for hillslope width function over individual hillslopes and entire watershed.

scholarly journals Environmental classification of administrative units of the Ukrainian Carpathians

2014 ◽  
pp. 245-253
Author(s):  
Ivan Kruhlov
Keyword(s):  
Cluster Analysis ◽  
Standard Deviation ◽  
Satellite Images ◽  
Environmental Classification ◽  
Digital Elevation ◽  
Elevation Data ◽  
Digital Elevation Data ◽  
Administrative Units ◽  
Elevation Model

Boundaries of 43 administrative units (raions and oblast towns) were digitized and manually rectified using official schemes and satellite images. SRTM digital elevation data were used to calculate mean relative elevation and its standard deviation for each unit, as well as to delineate altitudinal bioclimatic belts and their portions within the units. These parameters were used to classify the units via agglomerative cluster analysis into nine environmental classes. Key words: cluster analysis, digital elevation model, geoecosystem, geo-spatial analysis.

scholarly journals Assessing Optimal Digital Elevation Model Selection for Active River Area Delineation Across Broad Regions

2021 ◽  
Author(s):  
Shizhou Ma ◽  
Karen Beazley ◽  
Patrick Nussey ◽  
Chris Greene
Keyword(s):  
High Resolution ◽  
Digital Elevation Model ◽  
Smoothing Algorithm ◽  
Processing Efficiency ◽  
Spatial Approach ◽  
Digital Elevation ◽  
Elevation Data ◽  
Computer Based ◽  
Lidar Dem ◽  
Elevation Model

Abstract The Active River Area (ARA) is a spatial approach for identifying the extent of functional riparian area. Given known limitations in terms of input elevation data quality and methodology, ARA studies to date have not achieved effective computer-based ARA-component delineation, limiting the efficacy of the ARA framework in terms of informing riparian conservation and management. To achieve framework refinement and determine the optimal input elevation data for future ARA studies, this study tested a novel Digital Elevation Model (DEM) smoothing algorithm and assessed ARA outputs derived from a range of DEMs for accuracy and efficiency. It was found that the tested DEM smoothing algorithm allows the ARA framework to take advantage of high-resolution LiDAR DEM and considerably improves the accuracy of high-resolution LiDAR DEM derived ARA results; smoothed LiDAR DEM in 5-meter spatial resolution best balanced ARA accuracy and data processing efficiency and is ultimately recommended for future ARA delineations across large regions.

scholarly journals ANALYSIS OF INFLUENCE OF TERRAIN RELIEF ROUGHNESS ON DEM ACCURACY GENERATED FROM LIDAR IN THE CZECH REPUBLIC TERRITORY

2016 ◽  
Vol XLI-B4 ◽  
pp. 25-30 ◽  
Author(s):  
M. Hubacek ◽  
V. Kovarik ◽  
V. Kratochvil
Keyword(s):  
Czech Republic ◽  
Laser Scanning ◽  
Vegetation Coverage ◽  
The Czech Republic ◽  
Digital Elevation ◽  
Lower Accuracy ◽  
Check Points ◽  
Elevation Data ◽  
Dem Accuracy ◽  
Elevation Model

Digital elevation models are today a common part of geographic information systems and derived applications. The way of their creation is varied. It depends on the extent of area, required accuracy, delivery time, financial resources and technologies available. The first model covering the whole territory of the Czech Republic was created already in the early 1980's. Currently, the 5th DEM generation is being finished. Data collection for this model was realized using the airborne laser scanning which allowed creating the DEM of a new generation having the precision up to a decimetre. Model of such a precision expands the possibilities of employing the DEM and it also offers new opportunities for the use of elevation data especially in a domain of modelling the phenomena dependent on highly accurate data. The examples are precise modelling of hydrological phenomena, studying micro-relief objects, modelling the vehicle movement, detecting and describing historical changes of a landscape, designing constructions etc. <br><br> Due to a nature of the technology used for collecting data and generating DEM, it is assumed that the resulting model achieves lower accuracy in areas covered by vegetation and in built-up areas. Therefore the verification of model accuracy was carried out in five selected areas in Moravia. The network of check points was established using a total station in each area. To determine the reference heights of check points, the known geodetic points whose heights were defined using levelling were used. Up to several thousands of points were surveyed in each area. Individual points were selected according to a different configuration of relief, different surface types, and different vegetation coverage. The sets of deviations were obtained by comparing the DEM 5G heights with reference heights which was followed by verification of tested elevation model. Results of the analysis showed that the model reaches generally higher precision than the declared one in majority of areas. This applies in particular to areas covered by vegetation. By contrast, the larger deviations occurred in relation to the slope of the terrain, in particular in the micro-relief objects. The results are presented in this article.

scholarly journals Automated Conflation of Digital Elevation Model with Reference Hydrographic Lines

2020 ◽  
Vol 9 (5) ◽  
pp. 334
Author(s):  
Timofey E. Samsonov
Keyword(s):  
Spatial Analysis ◽  
Digital Elevation Model ◽  
Spatial Data ◽  
Drainage Network ◽  
Map Generalization ◽  
Data Types ◽  
Digital Elevation ◽  
Elevation Data ◽  
Elevation Model ◽  
Different Sources

Combining misaligned spatial data from different sources complicates spatial analysis and creation of maps. Conflation is a process that solves the misalignment problem through spatial adjustment or attribute transfer between similar features in two datasets. Even though a combination of digital elevation model (DEM) and vector hydrographic lines is a common practice in spatial analysis and mapping, no method for automated conflation between these spatial data types has been developed so far. The problem of DEM and hydrography misalignment arises not only in map compilation, but also during the production of generalized datasets. There is a lack of automated solutions which can ensure that the drainage network represented in the surface of generalized DEM is spatially adjusted with independently generalized vector hydrography. We propose a new method that performs the conflation of DEM with linear hydrographic data and is embeddable into DEM generalization process. Given a set of reference hydrographic lines, our method automatically recognizes the most similar paths on DEM surface called counterpart streams. The elevation data extracted from DEM is then rubbersheeted locally using the links between counterpart streams and reference lines, and the conflated DEM is reconstructed from the rubbersheeted elevation data. The algorithm developed for extraction of counterpart streams ensures that the resulting set of lines comprises the network similar to the network of ordered reference lines. We also show how our approach can be seamlessly integrated into a TIN-based structural DEM generalization process with spatial adjustment to pre-generalized hydrographic lines as additional requirement. The combination of the GEBCO_2019 DEM and the Natural Earth 10M vector dataset is used to illustrate the effectiveness of DEM conflation both in map compilation and map generalization workflows. Resulting maps are geographically correct and are aesthetically more pleasing in comparison to a straightforward combination of misaligned DEM and hydrographic lines without conflation.

scholarly journals New elevation data triple estimates of global vulnerability to sea-level rise and coastal flooding

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Scott A. Kulp ◽  
Benjamin H. Strauss
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
High Tide ◽  
Water Levels ◽  
Low Carbon ◽  
Digital Elevation ◽  
Elevation Data ◽  
Global Mean Sea Level ◽  
Elevation Model ◽  
Global Mean

Abstract Most estimates of global mean sea-level rise this century fall below 2 m. This quantity is comparable to the positive vertical bias of the principle digital elevation model (DEM) used to assess global and national population exposures to extreme coastal water levels, NASA’s SRTM. CoastalDEM is a new DEM utilizing neural networks to reduce SRTM error. Here we show – employing CoastalDEM—that 190 M people (150–250 M, 90% CI) currently occupy global land below projected high tide lines for 2100 under low carbon emissions, up from 110 M today, for a median increase of 80 M. These figures triple SRTM-based values. Under high emissions, CoastalDEM indicates up to 630 M people live on land below projected annual flood levels for 2100, and up to 340 M for mid-century, versus roughly 250 M at present. We estimate one billion people now occupy land less than 10 m above current high tide lines, including 230 M below 1 m.

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

2013 ◽  
Vol 59 (215) ◽  
pp. 524-532 ◽  
Author(s):  
J.F. Levinsen ◽  
I.M. Howat ◽  
C.C. Tscherning
Keyword(s):  
Point Clouds ◽  
Altimeter Data ◽  
Laser Altimeter ◽  
Registration Errors ◽  
Digital Elevation ◽  
Surface Elevation Change ◽  
Laser Altimeters ◽  
Elevation Changes ◽  
Elevation Model ◽  
Spot 5

AbstractWe 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) and Kangerdlugssuaq (KL). We find that the main trunks of JI and KL lowered at rates of 30–35 and 7–20 m a−1,respectively. The rates decreased inland. The corresponding errors were 0.3–5.2 m a−1for JI and 0.3–5.1 m a−1for KL, with errors increasing proportionally with distance from the altimeter paths.

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