scholarly journals Effect of DEM Interpolation Neighbourhood on Terrain Factors

2019 ◽  
Vol 8 (1) ◽  
pp. 30 ◽  
Author(s):  
Ying Zhu ◽  
Xuejun Liu ◽  
Jing Zhao ◽  
Jianjun Cao ◽  
Xiaolei Wang ◽  
...  
Keyword(s):  
Interpolation Method ◽  
Simulated Data ◽  
Topographic Features ◽  
Structure And Morphology ◽  
Digital Elevation ◽  
Different Types ◽  
Slope Error ◽  
Elevation Model ◽  
The Impact ◽  
Mls Method

Topographic factors such as slope and aspect are essential parameters in depicting the structure and morphology of a terrain surface. We study the effect of the number of points in the neighbourhood of a digital elevation model (DEM) interpolation method on mean slope, mean aspect, and RMSEs of slope and aspect from the interpolated DEM. As the moving least squares (MLS) method can maintain the inherent properties and other characteristics of a surface, this method is chosen for DEM interpolation. Three areas containing different types of topographic features are selected for study. Simulated data from a Gauss surface is also used for comparison. First, the impact of the number of points on the DEM root mean square error (RMSE) is analysed. The DEM RMSE in the three study areas decreases gradually with the number of points in the neighbourhood. In addition, the effect of the number of points in the neighbourhood on mean slope and mean aspect was studied across varying topographies through regression analysis. The two variables respond differently to changes in terrain. However, the RMSEs of the slope and aspect in all study areas are logarithmically related to the number of points in the neighbourhood and the values decrease uniformly as the number of points in the neighbourhood increases. With more points in the neighbourhood, the RMSEs of the slope and aspect are not sensitive to topography differences and the same trends are observed for the three studied quantities. Results for the Gauss surface are similar. Finally, this study analyses the spatial distribution of slope and aspect errors. The slope error is concentrated in ridges, valleys, steep-slope areas, and ditch edges while the aspect error is concentrated in ridges, valleys, and flat regions. With more points in the neighbourhood, the number of grid cells in which the slope error is greater than 15° is gradually reduced. With similar terrain types and data sources, if the calculation efficiency is not a concern, sufficient points in the spatial autocorrelation range should be analysed in the neighbourhood to maximize the accuracy of the slope and aspect. However, selecting between 10 and 12 points in the neighbourhood is economical.

scholarly journals A New Approach to the Quality Control of Slope and Aspect Classes Derived from Digital Elevation Models

2021 ◽  
Vol 13 (11) ◽  
pp. 2069
Author(s):  
M. V. Alba-Fernández ◽  
F. J. Ariza-López ◽  
M. D. Jiménez-Gamero
Keyword(s):  
Quality Control ◽  
Hypothesis Test ◽  
Simulated Data ◽  
Slope Aspect ◽  
New Approach ◽  
Reference Set ◽  
Digital Elevation ◽  
Using Data ◽  
Elevation Model ◽  
Degree Of Similarity

The usefulness of the parameters (e.g., slope, aspect) derived from a Digital Elevation Model (DEM) is limited by its accuracy. In this paper, a thematic-like quality control (class-based) of aspect and slope classes is proposed. A product can be compared against a reference dataset, which provides the quality requirements to be achieved, by comparing the product proportions of each class with those of the reference set. If a distance between the product proportions and the reference proportions is smaller than a small enough positive tolerance, which is fixed by the user, it will be considered that the degree of similarity between the product and the reference set is acceptable, and hence that its quality meets the requirements. A formal statistical procedure, based on a hypothesis test, is developed and its performance is analyzed using simulated data. It uses the Hellinger distance between the proportions. The application to the slope and aspect is illustrated using data derived from a 2×2 m DEM (reference) and 5×5 m DEM in Allo (province of Navarra, Spain).

scholarly journals Impact of Spatial Resolution of Digital Elevation Model on Landslide Susceptibility Mapping: A case Study in Kullu Valley, Himalayas

Geosciences ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. 360 ◽  
Author(s):  
Sansar Raj ◽  
Thimmaiah
Keyword(s):  
Digital Elevation Model ◽  
Spatial Resolution ◽  
Landslide Susceptibility ◽  
Susceptibility Mapping ◽  
Landslide Susceptibility Mapping ◽  
Mountainous Regions ◽  
Digital Elevation ◽  
Kullu Valley ◽  
Elevation Model ◽  
The Impact

Landslides are one of the most damaging geological hazards in mountainous regions such as the Himalayas. The Himalayan region is, tectonically, the most active region in the world that is highly vulnerable to landslides and associated hazards. Landslide susceptibility mapping (LSM) is a useful tool for understanding the probability of the spatial distribution of future landslide regions. In this research, the landslide inventory datasets were collected during the field study of the Kullu valley in July 2018, and 149 landslide locations were collected as global positioning system (GPS) points. The present study evaluates the LSM using three different spatial resolution of the digital elevation model (DEM) derived from three different sources. The data-driven traditional frequency ratio (FR) model was used for this study. The FR model was used for this research to assess the impact of the different spatial resolution of DEMs on the LSM. DEM data was derived from Advanced Land Observing Satellite-1 (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) ALOS-PALSAR for 12.5 m, the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global for 30 m, and the Shuttle Radar Topography Mission (SRTM) for 90 m. As an input, we used eight landslide conditioning factors based on the study area and topographic features of the Kullu valley in the Himalayas. The ASTER-Global 30m DEM showed higher accuracy of 0.910 compared to 0.839 for 12.5 m and 0.824 for 90 m DEM resolution. This study shows that that 30 m resolution is better suited for LSM for the Kullu valley region in the Himalayas. The LSM can be used for mitigation and future planning for spatial planners and developmental authorities in the region.

scholarly journals Assessment of Changes in a Viewshed in the Western Carpathians Landscape as a Result of Reforestation

Land ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 430
Author(s):  
Michał Sobala ◽  
Urszula Myga-Piątek ◽  
Bartłomiej Szypuła
Keyword(s):  
Digital Elevation Model ◽  
Forest Succession ◽  
Western Carpathians ◽  
Surface Model ◽  
Digital Surface Model ◽  
Mountainous Areas ◽  
Viewshed Analysis ◽  
Digital Elevation ◽  
Elevation Model ◽  
The Impact

A viewshed analysis is of great importance in mountainous areas characterized by high landscape values. The aim of this research was to determine the impact of reforestation occurring on former pasturelands on changes in the viewshed, and to quantify changes in the surface of glades. We combine a horizontal and a vertical approach to landscape analysis. The changes in non-forest areas and the viewshed from viewpoints located in glades were calculated using historical cartographic materials and a more recent Digital Elevation Model and Digital Surface Model. An analysis was conducted using a Visibility tool in ArcGIS. The non-forest areas decreased in the period 1848–2015. The viewshed in the majority of viewpoints also decreased in the period 1848–2015. In the majority of cases, the maximal viewsheds were calculated in 1879/1885 and 1933 (43.8% of the analyzed cases), whereas the minimal ones were calculated in 2015 (almost 57.5% of analyzed cases). Changes in the viewshed range from 0.2 to 23.5 km2 with half the cases analyzed being no more than 1.4 km2. The results indicate that forest succession on abandoned glades does not always cause a decline in the viewshed. Deforestation in neighboring areas may be another factor that has an influence on the decline.

scholarly journals Sensitivity analysis of the DEM resolution and effective parameters of runoff yield in the SWAT model: a case study

2019 ◽  
Vol 69 (1) ◽  
pp. 39-54 ◽  
Author(s):  
Mohammad Nazari-Sharabian ◽  
Masoud Taheriyoun ◽  
Moses Karakouzian
Keyword(s):  
Sensitivity Analysis ◽  
Assessment Tool ◽  
Swat Model ◽  
Computation Time ◽  
Effective Parameters ◽  
Digital Elevation ◽  
Elevation Model ◽  
The Impact ◽  
Reduce Computation Time

Abstract This study investigates the impact of different digital elevation model (DEM) resolutions on the topological attributes and simulated runoff, as well as the sensitivity of runoff parameters in the Mahabad Dam watershed in Iran. The watershed and streamlines were delineated in ArcGIS, and the hydrologic analyses were performed using the Soil and Water Assessment Tool (SWAT). The sensitivity analysis on runoff parameters was performed, using the Sequential Uncertainties FItting Ver. 2 algorithm, in the SWAT Calibration and Uncertainty Procedures (SWAT-CUP) program. The results indicated that the sensitivity of runoff parameters, watershed surface area, and elevations changed under different DEM resolutions. As the distribution of slopes changed using different DEMs, surface parameters were most affected. Furthermore, higher amounts of runoff were generated when DEMs with finer resolutions were implemented. In comparison with the observed value of 8 m3/s at the watershed outlet, the 12.5 m DEM showed more realistic results (6.77 m3/s). Comparatively, the 12.5 m DEM generated 0.74% and 2.73% more runoff compared with the 30 and 90 m DEMs, respectively. The findings of this study indicate that in order to reduce computation time, researchers may use DEMs with coarser resolutions at the expense of minor decreases in accuracy.

scholarly journals DEM Void Filling Based on Context Attention Generation Model

2020 ◽  
Vol 9 (12) ◽  
pp. 734
Author(s):  
Chunsen Zhang ◽  
Shu Shi ◽  
Yingwei Ge ◽  
Hengheng Liu ◽  
Weihong Cui
Keyword(s):  
Interpolation Method ◽  
Digital Simulation ◽  
Generation Model ◽  
Generative Adversarial Network ◽  
Cloud Data ◽  
Adversarial Network ◽  
Network Training ◽  
Digital Elevation ◽  
Elevation Model ◽  
Feature Expression

The digital elevation model (DEM) generates a digital simulation of ground terrain in a certain range with the usage of 3D point cloud data. It is an important source of spatial modeling information. Due to various reasons, however, the generated DEM has data holes. Based on the algorithm of deep learning, this paper aims to train a deep generation model (DGM) to complete the DEM void filling task. A certain amount of DEM data and a randomly generated mask are taken as network inputs, along which the reconstruction loss and generative adversarial network (GAN) loss are used to assist network training, so as to perceive the overall known elevation information, in combination with the contextual attention layer, and generate data with reliability to fill the void areas. The experimental results have managed to show that this method has good feature expression and reconstruction accuracy in DEM void filling, which has been proven to be better than that illustrated by the traditional interpolation method.

scholarly journals EVALUATION DIGITAL ELEVATION MODEL GENERATED BY SYNTHETIC APERTURE RADAR DATA

2016 ◽  
Vol XLI-B1 ◽  
pp. 57-62
Author(s):  
H. B. Makineci ◽  
H. Karabörk
Keyword(s):  
Remote Sensing ◽  
Digital Elevation Model ◽  
Interpolation Method ◽  
Digital Elevation Models ◽  
European Space Agency ◽  
Mountain Area ◽  
Synthetic Aperture Radar Data ◽  
Radar Images ◽  
Digital Elevation ◽  
Elevation Model

Digital elevation model, showing the physical and topographical situation of the earth, is defined a tree-dimensional digital model obtained from the elevation of the surface by using of selected an appropriate interpolation method. DEMs are used in many areas such as management of natural resources, engineering and infrastructure projects, disaster and risk analysis, archaeology, security, aviation, forestry, energy, topographic mapping, landslide and flood analysis, Geographic Information Systems (GIS). Digital elevation models, which are the fundamental components of cartography, is calculated by many methods. Digital elevation models can be obtained terrestrial methods or data obtained by digitization of maps by processing the digital platform in general. Today, Digital elevation model data is generated by the processing of stereo optical satellite images, radar images (radargrammetry, interferometry) and lidar data using remote sensing and photogrammetric techniques with the help of improving technology. <br><br> One of the fundamental components of remote sensing radar technology is very advanced nowadays. In response to this progress it began to be used more frequently in various fields. Determining the shape of topography and creating digital elevation model comes the beginning topics of these areas. <br><br> It is aimed in this work , the differences of evaluation of quality between Sentinel-1A SAR image ,which is sent by European Space Agency ESA and Interferometry Wide Swath imaging mode and C band type , and DTED-2 (Digital Terrain Elevation Data) and application between them. The application includes RMS static method for detecting precision of data. Results show us to variance of points make a high decrease from mountain area to plane area.

scholarly journals Floods Risk Mapping and Assessing Vulnerability of Morang, Nepal

2021 ◽  
Author(s):  
Pawan Thapa ◽  
Narayan Thapa
Keyword(s):  
Drainage Density ◽  
Google Earth ◽  
Food And Agriculture ◽  
Food And Agriculture Organization ◽  
Digital Elevation ◽  
Two Factors ◽  
Flooding Risk ◽  
Elevation Model ◽  
The One ◽  
The Impact

Abstract Background: The impact of flooding rises due to unplanned settlements, especially in developing and underdeveloped countries. This study tries to address these issues by mapping flood risk places and assessing their impact on population and household.Methods: This study used the dataset available in Google Earth Engine (GEE), Food and Agriculture Organization (FAO), Central Bureau Statistics (CBS), Earth Data for preparing slope, drainage density, digital elevation model, rainfall, land use map, and soil map. These maps create using GEE and QGIS through overlay analysis that has two factors. The one is influence and other slopes, and it has provided high and low value according to its role on flooding.Results: The risk assessment shows around twenty-four percent population is at higher risk, whereas more than three thousand settlements are prone to flooding. It depicts a significant increasing trend of floods in the Morang district.Conclusion: This settlement risk map can help determine the flood safe and very high-risk areas in the Morang district. It will support residential places' planning by the local government, urban planners, and community people to reduce flooding risk.

scholarly journals APPLICATION OF AHP METHOD FOR MAPPING SLOPE GEOMORPHIC PHENOMENA

2017 ◽  
Author(s):  
Florin Constantin MIHAI
Keyword(s):  
Risk Mitigation ◽  
Characteristic Curve ◽  
Confusion Matrix ◽  
Predictive Performance ◽  
Landslide Risk ◽  
Good Correspondence ◽  
Topographic Features ◽  
Digital Elevation ◽  
Elevation Model ◽  
Hierarchy Process

Landslides are common and frequent geomorphic phenomena for the plateau regions in Romania having important consequences, especially economic ones, that needs designing scientific and technical plans for landslide risk mitigation. For this, an important preliminary step is assessing and mapping the landslide susceptibility. This paper examines a plateau zone in eastern Romania providing such a map, based on the landslides inventory, the digital elevation model (DEM) and the thematic layers of several factors thought to be potential predictors of landslides occurrence: topographic features, land use, and lithology. The methodological framework is based on the analytical hierarchy process (AHP) principles and factors weights attributed based on frequency of landslides. The predictive performance of the model was assessed using the confusion matrix, the ROC (receiver operating characteristic) curve and the AUC (area under curve) parameter. The results indicate a good correspondence between the susceptibility estimated for the test samples and for the validation samples

scholarly journals Floods Risk Mapping and Assessing Vulnerability of Morang, Nepal

2021 ◽  
Author(s):  
Pawan Thapa ◽  
Narayan Thapa
Keyword(s):  
Drainage Density ◽  
Google Earth ◽  
Food And Agriculture ◽  
Food And Agriculture Organization ◽  
Digital Elevation ◽  
Two Factors ◽  
Flooding Risk ◽  
Elevation Model ◽  
The One ◽  
The Impact

Abstract Background: The impact of flooding rises due to unplanned settlements, especially in developing countries. This study tries to address these issues by mapping flood risk places and assessing their impact on population and household.Methods: This study used the dataset available in Google Earth Engine (GEE), Food and Agriculture Organization (FAO), Central Bureau Statistics (CBS), Earth Data for preparing slope, drainage density, digital elevation model, rainfall, land use map, and soil map. These maps create using GEE and QGIS through overlay analysis that has two factors. The one is influence and other slopes, and it has provided high and low value according to its role on flooding.Results: The risk assessment shows around twenty-four percent population is at higher risk, whereas more than three thousand settlements are prone to flooding. It depicts a significant increasing trend of floods in the Morang district.Conclusion: This settlement risk map can help determine the flood safe and very high-risk areas in the Morang district. It will support residential places' planning by the local government, urban planners, and community people to reduce flooding risk.

scholarly journals The Impact of Spatiotemporal Changes in Land Development (1984–2019) on the Increase in the Runoff Coefficient in Erbil, Kurdistan Region of Iraq

2020 ◽  
Vol 12 (8) ◽  
pp. 1302 ◽  
Author(s):  
Andam Mustafa ◽  
Michał Szydłowski
Keyword(s):  
Agricultural Land ◽  
Land Development ◽  
Flash Floods ◽  
Kurdistan Region ◽  
Lulc Changes ◽  
Digital Elevation ◽  
Large Expansion ◽  
Spatiotemporal Changes ◽  
Elevation Model ◽  
The Impact

Nowadays, geospatial techniques are a popular approach for estimating urban flash floods by considering spatiotemporal changes in urban development. In this study, we investigated the impact of Land Use/Land Cover (LULC) changes on the hydrological response of the Erbil basin in the Kurdistan Region of Iraq (KRI). In the studied area, the LULC changes were calculated for 1984, 1994, 2004, 2014 and 2019 using the Digital Elevation Model (DEM) and satellite images. The analysis of LULC changes showed that the change between 1984 and 2004 was slower than that between 2004 and 2019. The LULC analysis revealed a 444.4% growth in built-up areas, with a 60.4% decrease in agricultural land between 1984 and 2019. The influence of LULC on urban floods caused by different urbanization scenarios was ascertained using the HEC-GeoHMS and HEC-HMS models. Over 35 years, there was a 15% increase in the peak discharge of outflow, from 392.2 m3/s in 1984 to 450 m3/s in 2014, as well as the runoff volume for a precipitation probability distribution of 10%, which increased from 27.4 mm in 1984 to 30.9 mm in 2014. Overall, the probability of flash floods increased in the center of the city due to the large expansion of built-up areas.

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