scholarly journals Avaliação de modelos digitais de elevação para estudos geoecológicos no maciço da Pedra Branca, Rio de Janeiro, Brasil

2009 ◽  
Vol 32 (1) ◽  
pp. 21-33
Author(s):  
Leandro Gomes Souza ◽  
Gustavo Mota de Sousa ◽  
Pedro Henrique Ferreira Coura ◽  
Manoel Do Couto Fernandes
Keyword(s):  
Interpolation Method ◽  
Real Surface ◽  
Regular Grid ◽  
The Real ◽  
Digital Elevation ◽  
Correct Calculation ◽  
Triangular Irregular Network ◽  
Elevation Model ◽  
Integrated Study ◽  
Adequate Method

Geoprocessing tools have been increasingly used to support the integrated study of geoecological variables, once they allow fast and efficient analysis. One of the products generated by geoprocessing of great importance do analysis that considerate the real surface of the terrain is the Digital Elevation Model (DEM). The consideration of the real surface is essential for the correct calculation of volumes, areas and distances, parameters of great importance for geomorfological indicators. There are many kinds of methods to generate this models and no consensus about which method has the best results, once it's precision will depend on characteristics of the study area. This work aims to compare the different DEM generation methods for irregular relief areas, using the Pedra Branca massif, RJ, as study area. It has been generated DEMs by two different interpolation methods and grids: one based in rectangular regular grid (TOPOGRID) and the interpolation method of Delaunay constrained, based in triangular irregular network (TIN), both generated in the software ArcGIS 9.2. For the verification of the quality and altimetric precision of these models, it has been utilized a map of declivities generated from the triangular irregular network model. Results show that the more adequate method for the study area is the TOPOGRID. However, it has been noted that this behavior is unequally distributed along its declivities classes, and it's errors are bigger in the great declivities, where the TIN model has been more efficient.

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 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.

Modeling of Three-Dimensional Terrain Data for Intelligent Control of Unmanned Construction Machine in Deterministic Surfacing Process

2014 ◽  
Vol 1073-1076 ◽  
pp. 1917-1921
Author(s):  
Xin Min Shen ◽  
Jian Zhao Zhou ◽  
Li Qun Han
Keyword(s):  
Intelligent Control ◽  
Three Dimensional ◽  
Residual Error ◽  
Operation Planning ◽  
Regular Grid ◽  
3D Terrain ◽  
Surface Data ◽  
Digital Elevation ◽  
Construction Machine ◽  
Elevation Model

Deterministic surfacing technique is an effective method for intelligent control of operation planning of the unmanned construction machine, and its foundation is the accurate modeling of the three-dimensional terrain data. According to the digital elevation model based on regular grid, the modeling of 3D terrain surface data is obtained. The evaluation of residual error is further investigated, which is quite important for the iterated operation in deterministic surfacing. Through revealing flow chart of the deterministic surfacing method, the importance of the modeling of terrain data and that of the evaluation of residual error are emphasized. The study on modeling of terrain data will promote application of the deterministic surfacing in intelligent control of unmanned construction machine.

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 InSAR Baseline Estimation for Gaofen-3 Real-Time DEM Generation

2018 ◽  
Author(s):  
Huan Lu ◽  
Zhiyong Suo ◽  
Zhenfang Li ◽  
Jinwei Xie ◽  
Qingjun Zhang
Keyword(s):  
Real Time ◽  
Estimation Method ◽  
Shuttle Radar Topography Mission ◽  
The Real ◽  
Digital Elevation ◽  
Orbit Fitting ◽  
Elevation Model ◽  
Interferometric Sar ◽  
Baseline Estimation ◽  
Baseline Error

For Interferometry Synthetic Aperture Radar (InSAR), the normal baseline is one of the main factors that affect the accuracy of the ground elevation. For Gaofen-3 (GF-3) InSAR processing, the poor accuracy of the real-time orbit determination resulting in a large baseline error, leads to the modulation error in azimuth and the slope error in range for timely Digital Elevation Model (DEM) generation. In order to address this problem, a baseline estimation method based on external DEM is proposed in this paper. Firstly, according to the characteristic of the real-time orbit of GF-3 images, orbit fitting is executed to remove the non-linear error factor. Secondly, the height errors are obtained in slant-range plane between Shuttle Radar Topography Mission (SRTM) DEM and the GF-3 generated DEM after orbit fitting. At the same time, the height errors are used to estimate the baseline error which has a linear variation. In this way, the orbit error can be calibrated by the estimated baseline error. Finally, DEM generation is performed by using the modified baseline and orbit. This procedure is implemented iteratively to achieve a higher accuracy DEM. Based on the results of GF-3 interferometric SAR data for Hebei, the effectiveness of the proposed algorithm is verified and the accuracy of GF-3 real-time DEM products can be improved extensively.

scholarly journals SRTM DEM levels over papyrus swamp vegetation – a correction approach

2009 ◽  
Vol 21 ◽  
pp. 81-84 ◽  
Author(s):  
G. Petersen ◽  
I. Lebed ◽  
N. Fohrer
Keyword(s):  
Correction Factor ◽  
Ground Level ◽  
Shuttle Radar Topography Mission ◽  
Radar Signal ◽  
Real Surface ◽  
Srtm Dem ◽  
Ground Control Points ◽  
Digital Elevation ◽  
Elevation Data ◽  
Elevation Model

Abstract. The SRTM DEM, a digital elevation model based on the Shuttle Radar Topography Mission of February 2000 is a source of elevation data with nearly worldwide coverage. It has proven its usefulness in various regions but problems persist for densely vegetated areas where, caused by the organic matter and water content of the vegetation, the radar signal is reflected at some level between the vegetation canopy and the ground level. This level varies with different types and densities of vegetation cover and has so far not been assessed for papyrus areas. The paper describes the approach and establishment of a correction factor for a pilot area in the Sudd swamps of southern Sudan based on comparison of SRTM reference levels and ground control points collected during field surveys between 2004 and 2006. Results show a correction factor between the sensed and the real surface of 4.66 m and a average penetration depth of the radar signal into the dense papyrus vegetation of 0.34 m.

EXPERIMENTS TO LOCATE RIDGES AND CHANNELS TO CREATE A NEW TYPE OF DIGITAL ELEVATION MODEL

1987 ◽  
Vol 41 (3) ◽  
pp. 373-406 ◽  
Author(s):  
David H. Douglas
Keyword(s):  
Digital Elevation Model ◽  
Network Model ◽  
Digital Elevation ◽  
Other Information ◽  
Triangular Irregular Network ◽  
New Type ◽  
Elevation Model

There have been numerous proposals to combine the advantages of the adaptability of the contour digital elevation model with the neighbourhood functions of the grid. Notable among these is the triangular irregular network model (TIN). This paper presents another approach to digital elevation modelling based on traces of channels and ridges, and other information — rich lines that may be identified on a surface.

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