scholarly journals DIGITAL ELEVATION MODEL INTERPOLATION BY FUSION OF MORPHOLOGICAL RECONSTRUCTION AND DISTANCE TRANSFORMATION

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 881-885
Author(s):  
J. Shen ◽  
W. L. Han ◽  
J. Ge ◽  
L. B. Zhang ◽  
H. Tan
Keyword(s):  
Digital Elevation Model ◽  
Flow Line ◽  
Interpolation Method ◽  
Linear Interpolation ◽  
Morphological Reconstruction ◽  
Distance Transformation ◽  
Spatial Point ◽  
Contour Lines ◽  
Digital Elevation ◽  
Elevation Model

Interpolation methods have significant impacts on the accuracy of the digital elevation model (DEM) from contours which are one of frequently employed data sources. In this paper, an interpolation method is presented to build DEM from contour lines by fusion/integration of morphological reconstruction and distance transformation with obstacles. Particularly, morphological reconstruction is used to get the elevation values of the higher contour lines and the lower contour lines of any a spatial point between two contour lines, and distance transformation with obstacles is used to get the geodesic distances of the spatial point to the higher contour lines and the lower contour lines respectively. At last, linear interpolation along water flow line is used to get the elevation values of the pixels to be interpolated. The experiment demonstrates that feasibility of our proposed method.

scholarly journals Spatial Analysis Using Temporal Point Clouds in Advanced GIS: Methods for Ground Elevation Extraction in Slant Areas and Building Classifications

2019 ◽  
Vol 8 (3) ◽  
pp. 120 ◽  
Author(s):  
Sara Shirowzhan ◽  
Samad Sepasgozar
Keyword(s):  
Digital Elevation Model ◽  
Urban Growth ◽  
Urban Areas ◽  
Future Directions ◽  
3D Data ◽  
Contour Lines ◽  
Digital Elevation ◽  
The Future ◽  
Elevation Model ◽  
Skewness And Kurtosis

Deriving 3D urban development patterns is necessary for urban planners to control the future directions of 3D urban growth considering the availability of infrastructure or being prepared for fundamental infrastructure. Urban metrics have been used so far for quantification of landscape and land-use change. However, these studies focus on the horizontal development of urban form. Therefore, questions remain about 3D growth patterns. Both 3D data and appropriate 3D metrics are fundamentally required for vertical development pattern extraction. Airborne light detection and ranging (Lidar) as an advanced remote-sensing technology provides 3D data required for such studies. Processing of airborne lidar to extract buildings’ heights above a footprint is a major task and current automatic algorithms fail to extract such information on vast urban areas especially in hilly sites. This research focuses on proposing new methods of extraction of ground points in hilly urban areas using autocorrelation-based algorithms. The ground points then would be used for digital elevation model generation and elimination of ground elevation from classified buildings points elevation. Technical novelties in our experimentation lie in choosing a different window direction and also contour lines for the slant area, and applying moving windows and iterating non-ground extraction. The results are validated through calculation of skewness and kurtosis values. The results show that changing the shape of windows and their direction to be narrow long squares parallel to the ground contour lines, respectively, improves the results of classification in slant areas. Four parameters, namely window size, window shape, window direction and cell size are empirically chosen in order to improve initial digital elevation model (DEM) creation, enhancement of the initial DEM, classification of non-ground points and final creation of a normalised digital surface model (NDSM). The results of these enhanced algorithms are robust for generating reliable DEMs and separation of ground and non-ground points in slant urban scenes as evidenced by the results of skewness and kurtosis. Offering the possibility of monitoring urban growth over time with higher accuracy and more reliable information, this work could contribute in drawing the future directions of 3D urban growth for a smarter urban growth in the Smart Cities paradigm.

Study on the Utilization of Digital Elevation Model for Calculation Method of Reservoir Capacity

2012 ◽  
Vol 472-475 ◽  
pp. 1627-1631
Author(s):  
Li Fang Lai ◽  
Yu Fen Zhang
Keyword(s):  
Digital Elevation Model ◽  
Calculation Method ◽  
Reservoir Capacity ◽  
Contour Lines ◽  
Digital Elevation ◽  
Capacity Calculation ◽  
Elevation Model

Reservoir capacity is a very important parameter for reservoir. This paper discusses the use of contour lines to establish digital elevation model (DEM) of reservoir, and to calculate reservoir capacity to improve the accuracy of the capacity calculation through the method that uses digital elevation model.

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 Solar Radiation Estimation Using Data Mining Techniques for Remote Areas—A Case Study in Ethiopia

Energies ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 5714
Author(s):  
Bizuayehu Abebe Worke ◽  
Hans Bludszuweit ◽  
José A. Domínguez-Navarro
Keyword(s):  
Data Mining ◽  
Solar Radiation ◽  
Digital Elevation Model ◽  
Interpolation Method ◽  
Inference System ◽  
Remote Areas ◽  
Radiation Data ◽  
Digital Elevation ◽  
Elevation Model

High quality of solar radiation data is essential for solar resource assessment. For remote areas this is a challenge, as often only satellite data with low spatial resolution are available. This paper presents an interpolation method based on topographic data in digital elevation model format to improve the resolution of solar radiation maps. The refinement is performed with a data mining method based on first-order Sugeno type Adaptive Neuro-Fuzzy Inference System. The training set contains topographic characteristics such as terrain aspect, slope and elevation which may influence the solar radiation distribution. An efficient sampling method is proposed to obtain representative training sets from digital elevation model data. The proposed geographic information system based approach makes this method reproducible and adaptable for any region. A case study is presented on the remote Amhara region in North Shewa, Ethiopia. Results are shown for interpolation of solar radiation data from 10 km × 10 km to a resolution of 1 km × 1 km and are validated with data from the PVGIS and SWERA projects.

scholarly journals Generation of a High-Precision Digital Elevation Model for Fields in Mountain Regions Using RTK-GPS

2019 ◽  
Vol 13 (5) ◽  
pp. 671-678
Author(s):  
Liangliang Yang ◽  
Hao Guo ◽  
Shuming Yang ◽  
Yohei Hoshino ◽  
Soichiro Suzuki ◽  
...  
Keyword(s):  
Digital Elevation Model ◽  
High Precision ◽  
Interpolation Method ◽  
Steering System ◽  
Test Field ◽  
Mountain Regions ◽  
Quality Signals ◽  
Digital Elevation ◽  
Rtk Gps ◽  
Elevation Model

In modern agriculture, many advanced automated devices are used on farms. To improve the working efficiency of agricultural vehicles, fields are expected to be pre-leveled, because the vehicles work more effectively on a flat field. Leveling a field requires the current field elevation map. Some farmers in Japan have begun to use high-precision real-time kinematic Global Positioning System (RTK-GPS)-based self-steering tractors in the fields. This study uses the RTK-GPS information from a self-steering tractor system to generate a digital elevation model (DEM) especially in mountain regions where the fields are not flat. In addition, all of the information is from the self-steering system with the result that farmers can use the method of this study without additional instruments. However, the GPS receiver sometimes cannot obtain high-quality signals from satellites in mountain regions. Therefore, this study focuses on how to create a high-precision DEM even when a GPS signal is unavailable. It proposes a dynamic interpolation method for generating a DEM. In addition, a test was conducted in a field in a mountain region. The test results show that the dynamic interpolation method can provide an accuracy of less than 0.03 m in the test field for creating a DEM.

scholarly journals A Comparative Study of Three Non-Geostatistical Methods for Optimising Digital Elevation Model Interpolation

2018 ◽  
Vol 7 (8) ◽  
pp. 300 ◽  
Author(s):  
Serajis Salekin ◽  
Jack Burgess ◽  
Justin Morgenroth ◽  
Euan Mason ◽  
Dean Meason
Keyword(s):  
Digital Elevation Model ◽  
Spatial Resolution ◽  
Laser Scanning ◽  
Interpolation Method ◽  
Digital Elevation Models ◽  
Global Navigation Satellite Systems ◽  
Digital Elevation ◽  
Dem Accuracy ◽  
Elevation Model ◽  
Gnss Data

It is common to generate digital elevation models (DEMs) from aerial laser scanning (ALS) data. However, cost and lack of knowledge may preclude its use. In contrast, global navigation satellite systems (GNSS) are seldom used to collect and generate DEMs. These receivers have the potential to be considered as data sources for DEM interpolation, as they can be inexpensive, easy to use, and mobile. The data interpolation method and spatial resolution from this method needs to be optimised to create accurate DEMs. Moreover, the density of GNSS data is likely to affect DEM accuracy. This study investigates three different deterministic approaches, in combination with spatial resolution and data thinning, to determine their combined effects on DEM accuracy. Digital elevation models were interpolated, with resolutions ranging from 0.5 m to 10 m using natural neighbour (NaN), topo to raster (ANUDEM), and inverse distance weighted (IDW) methods. The GNSS data were thinned by 25% (0.389 points m−2), 50% (0.259 points m−2), and 75% (0.129 points m−2) and resulting DEMs were contrast against a DEM interpolated from unthinned data (0.519 points m−2). Digital elevation model accuracy was measured by root mean square error (RMSE) and mean absolute error (MAE). It was found that the highest resolution, 0.5 m, produced the lowest errors in resulting DEMs (RMSE = 0.428 m, MAE = 0.274 m). The ANUDEM method yielded the greatest DEM accuracy from a quantitative perspective (RMSE = 0.305 m and MAE = 0.197 m); however, NaN produced a more visually appealing surface. In all the assessments, IDW showed the lowest accuracy. Thinning the input data by 25% and even 50% had relatively little impact on DEM quality; however, accuracy decreased markedly at 75% thinning (0.129 points m−2). This study showed that, in a time where ALS is commonly used to generate DEMs, GNSS-surveyed data can be used to create accurate DEMs. This study confirmed the need for optimization to choose the appropriate interpolation method and spatial resolution in order to produce a reliable DEM.

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. &lt;br&gt;&lt;br&gt; 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. &lt;br&gt;&lt;br&gt; 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 Applied spatial analytic tools in orchards with special regard to agro-ecology

2011 ◽  
Vol 17 (1-2) ◽  
Author(s):  
T. Fórián ◽  
A. Nagy ◽  
J. Tamás ◽  
Z. Szabó ◽  
M. Soltész ◽  
...  
Keyword(s):  
Digital Elevation Model ◽  
Digital Terrain Model ◽  
Analytical Techniques ◽  
Soil Surface ◽  
Terrain Model ◽  
Digital Terrain ◽  
Contour Lines ◽  
Digital Elevation ◽  
Elevation Model ◽  
Fruit Orchards

Our investigation was carried out in several orchards in Hungary. This study reviews applicability of the different spatial analytical techniques in orchard especially models based on surface relief, such as digital elevation model, digital terrain model, slope and aspect maps. In recent time, the generation of digital elevation model has become a popular examination method. However, the elevation models generated from contour lines or elevation points could be applied to evaluate agro- ecological potential of fruit orchards to some extent. The highest deficiency of these models is the fact that these show the altitude of soil surface only and do not demonstrate landmarks on the surface. Consequently, the calculation of the radiation value results data relating to soil surface. The terrain model generated and applied by our team demonstrates fine surface texture and the landmarks in the orchard, so it is suitable for further examination.

scholarly journals DEM Reconstruction Based on Adaptive Local RBF

2014 ◽  
Vol 8 (1) ◽  
pp. 232-236
Author(s):  
Ping Duan ◽  
Yehua Sheng ◽  
Siyang Zhang ◽  
Haiyang Lv ◽  
Jia Li
Keyword(s):  
Radial Basis Function ◽  
Digital Elevation Model ◽  
Basis Function ◽  
Interpolation Method ◽  
Reference Points ◽  
Experimental Result ◽  
Good Effect ◽  
Digital Elevation ◽  
Radial Basis ◽  
Elevation Model

As the core of digital elevation model, interpolation methods have been run through the each link, such as production, quality control, accuracy assessment, analytical applications and etc. The local radial basis function interpolation method based on spatial relationship of natural neighbor was proposed in this paper. The interpolation reference points were chosen by the Delaunay Triangulation. The first-order and second-order neighboring of interpolation points as the interpolation reference points were used to construct local radial basis function. This method was applied to the construction of digital elevation model, and the correspondent errors were analyzed. Experimental result shows that the method has a good effect on the construction of different landform.

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