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.

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 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 Reconstructing Pre-Industrial Long Distance Roads in a Hilly Region in Germany, Based on Historical and Archaeological Data

2017 ◽  
Vol 1 (2) ◽  
pp. 642-660 ◽  
Author(s):  
Irmela Herzog
Keyword(s):  
Cross Sections ◽  
Lidar Data ◽  
Long Distance ◽  
Early 19Th Century ◽  
Digital Elevation ◽  
Hilly Region ◽  
Local Accuracy ◽  
Cost Paths ◽  
Elevation Model ◽  
The One

The aim of this contribution is on the one hand to map pre-industrial long distance roads located in a hilly region east of Cologne, Germany, as exactly as possible and on the other hand to assess the accuracy of least-cost approaches that are increasingly applied by archaeologists for prehistoric road reconstruction. Probably the earliest map covering the study area east of Cologne dates back to 1575. The map is distorted so that rectification is difficult. But it is possible to assess the local accuracy of the map and to transfer the approximate routes to a modern map manually. Most of the area covered by the 1575 map is also depicted on a set of more accurate maps created in the early 19th century and a somewhat later historical map set (ca. 1842 AD). The historical roads on these rectified historical maps close to the approximate roads were digitized and compared to the outcomes of least-cost analysis, specifically least-cost paths and accessibility maps. Based on these route reconstructions with limited accuracy, Lidar data is checked to identify remains of these roads. Several approaches for visualizing Lidar data are tested to identify appropriate methods for detecting sunken roads. Possible sunken roads detected on the Lidar images were validated by checking cross sections in the digital elevation model and in the field.

scholarly journals Influência de lineamentos estruturais no desencadeamento dos movimentos de massa no maciço de Uruburetama, Ceará

2020 ◽  
Vol 13 (3) ◽  
pp. 1294
Author(s):  
Eduardo Viana Freires ◽  
Cláudio Ângelo da Silva Neto ◽  
Cynthia Romariz Duarte ◽  
César Ulisses Vieira Veríssimo ◽  
Daniel Dantas Moreira Gomes ◽  
...  
Keyword(s):  
High Energy ◽  
Automatic Extraction ◽  
Mass Movements ◽  
Alos Palsar ◽  
Geological Structures ◽  
Physical Conditions ◽  
Directional Filters ◽  
Digital Elevation ◽  
Predominant Orientation ◽  
Elevation Model

A disposição de estruturas geológicas em áreas planálticas é elemento importante na compreensão da dinâmica que ocorre na superfície de suas encostas e que é responsável pela esculturação do relevo. Neste contexto destacam-se os movimentos gravitacionais, que podem gerar perdas econômicas, ambientais e humanas em eventos de alta energia e/ou com grande extensão. Esta pesquisa analisou a influência de lineamentos estruturais no desencadeamento dos movimentos gravitacionais no maciço de Uruburetama, localizado no estado do Ceará. A metodologia consistiu na extração automática de lineamentos a partir do Modelo Digital de Elevação (MDE) fornecido pelo sensor orbital ALOS PALSAR. A partir da média de filtros direcionais aplicados a 0°, 45°, 90° e 135° de iluminação foi possível realçar as feições lineares da imagem original, facilitando sua extração. Posteriormente, foram elaborados mapas de distribuição espacial e densidade de lineamentos, além de diagrama de roseta. Tais produtos subsidiaram a análise da disposição dos principais trends estruturais da área, destacando que a maior densidade e a orientação predominante de lineamentos podem ser indicativas do grau de susceptibilidade à ocorrência de movimentos de massa no maciço de Uruburetama, desde que também sejam consideradas as características físicas dominantes e o grau de intervenção humana nas encostas. Os resultados demonstraram que os lineamentos estruturais obtidos de forma automática, quando analisados em conjunto com as características ambientais podem ser aplicados na análise de susceptibilidade à ocorrência de movimentos de massa.  Influence of structural lineaments as a trigger of mass movements in the Uruburetama massif, Ceará state, Brazil A B S T R A C TThe geological structures arrangement in plateau areas is an important element in understanding the dynamics that occur on the surface of their slopes and which is responsible for relief sculpting. In this context, gravitational movements stand out, which can generate economic, environmental and human losses in high energy events and / or with large extension. This research analyzed the influence of structural lineaments in the gravitational movements triggering in the Uruburetama massif, located in the state of Ceará. The methodology consisted of automatic extraction of lineaments from the Digital Elevation Model (DEM) provided by the ALOS PALSAR orbital sensor. From the average of directional filters applied at 0°, 45°, 90° and 135° of illumination it was possible to enhance the linear features of the original image, facilitating their extraction. Subsequently, maps of spatial distribution and lineaments density were developed, as well as a rosette diagram. Such products subsidized the analysis of the disposition of the main structural trends of the area, emphasizing that the higher density and the predominant orientation of lineaments may be indicative of the degree of susceptibility to the occurrence of mass movements in the Uruburetama massif, if the dominant physical conditions and the degree of human intervention on the slopes are also considered. The results showed that the structural lineaments obtained automatically, when analyzed together with the environmental characteristics can be applied in the susceptibility analysis to the occurrence of mass movements.Keywords: ALOS PALSAR, directional filters, image fusion, lineaments extraction

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 CREATING DIGITAL ELEVATION MODEL USING A MOBILE DEVICE

2017 ◽  
Vol IV-4/W4 ◽  
pp. 203-207 ◽  
Author(s):  
A. İ. Durmaz
Keyword(s):  
Mobile Devices ◽  
Digital Elevation Model ◽  
Mobile Device ◽  
Point Clouds ◽  
Lidar Data ◽  
Government Agencies ◽  
Gps Data ◽  
Digital Elevation ◽  
The World ◽  
Elevation Model

DEM (Digital Elevation Models) is the best way to interpret topography on the ground. In recent years, lidar technology allows to create more accurate elevation models. However, the problem is this technology is not common all over the world. Also if Lidar data are not provided by government agencies freely, people have to pay lots of money to reach these point clouds. In this article, we will discuss how we can create digital elevation model from less accurate mobile devices’ GPS data. Moreover, we will evaluate these data on the same mobile device which we collected data to reduce cost of this modeling.

scholarly journals Retrieval of similar topographic areas.

2016 ◽  
Vol 47 (1) ◽  
pp. 275
Author(s):  
E. Kokinou ◽  
C. Panagiotakis ◽  
Th. Kinigopoulos
Keyword(s):  
Image Processing ◽  
High Efficiency ◽  
Automatic Extraction ◽  
Local Minima ◽  
Initial Model ◽  
Area Of Interest ◽  
Digital Elevation ◽  
Elevation Data ◽  
Digital Elevation Data ◽  
Step Number

Image processing and understanding and further pattern recognition comprises a precious tool for the automatic extraction of information using digital topography. The aim of this work is the retrieval of areas with similar topography using digital elevation data. It can be applied to geomorphology, forestry, regional and urban planning, and many other applications for analyzing and managing natural resources. In specifics, the user selects the area of interest, navigating overhead a high resolution elevation image and determines two (3) parameters (step, number of local minima and display scale). Furthermore the regions with similar relief to the initial model are determined. Experimental results show high efficiency of the proposed scheme.

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.

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