• Korean Journal of Remote Sensing
• /
• v.35 no.5_1
• /
• pp.715-726
• /
• 2019

With the increasing prevalence of high-resolution satellite images, the need for technology to generate accurate 3D information from the satellite images is emphasized. In order to create a digital terrain model (DTM) that is widely used in applications such as change detection and object extraction, it is necessary to extract trees, buildings, etc. that exist in the digital surface model (DSM) and estimate the height of the ground. This paper presents a method for automatically generating DTM from DSM extracted from KOMPSAT-3A stereo images. The technique was developed to detect the non-ground area and estimate the height value of the ground by using the previously constructed low-resolution topographic data. The average vertical accuracy of DTMs generated in the four experimental sites with various topographical characteristics, such as mountainous terrain, densely built area, flat topography, and complex terrain was about 5.8 meters. The proposed technique would be useful to produce high-quality DTMs that represent precise features of the bare-earth's surface.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.13 no.2
• /
• pp.291-298
• /
• 1995

This paper describes the test results of terrain corrections as the short wave length effect and geoid effects in gravity field modelling using Digital Terrain Model(DTM) in Korea. For a rigorous determination of terrain correction a dense grided DTM data wave prepard spacing $500\times{500m}$ was used for the computation of terrain effects. From the results obtained by the mass prism model and the mass line model, we were found that the terrain effects are large depend on the topography in the test area. It means that we should considered the terrain effects for the precise geoid determination.

• Journal of Institute of Control, Robotics and Systems
• /
• v.20 no.4
• /
• pp.449-455
• /
• 2014

This paper presents a method for developing a TM (Traversability Map) from a DTM (Digital Terrain Model) collected by remote sensors of autonomous mobile robots. Such a map can be used to plan traversable paths and estimate navigation speed quantitatively in real time for robots capable of performing autonomous tasks over rough terrain environments. The proposed method consists of three parts: a DTM partition module which divides the DTM into equally spaced patches, a terrain information module which extracts the slope and roughness of the partitioned patches using the curve fitting and the fractal-based triangular prism method, and a traversability analysis module which assesses traversability incorporating with extracted terrain information and fuzzy inference to construct a TM. The potential of the proposed method is validated via simulation works over a set of fractal DTMs.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.25 no.6_2
• /
• pp.645-651
• /
• 2007

In general, contours in digital vector maps, which represent terrain characteristics and shape, are created by 3D digitizing the same height points using aerial photographs on the analytical or digital plotters with stereoscopic viewing. Hence, it requires lots of task, and subjective decision and experience of the operators. DTMs are generated indirectly by using contours since the national digital maps do not include digital terrain model (DTM) data. In this study, model key points which depict the important information about terrain characteristics were extracted from the contours. Further, determination of the efficient and flexible grid sizes were proposed to generate optimal DTM in terms of both quantitative and qualitative aspects. For this purpose, a progressive sampling technique was implemented, i.e., the smaller grid sizes are assigned for the mountainous areas where have large relief while the larger grid sizes are assigned for the relatively flat areas. In consequence, DTMs with multi-grid for difference areas could be generated instead of DTMs with a fixed grid size. The multi-grid DTMs reduce computations for data processing and provide fast display.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.37 no.6
• /
• pp.499-506
• /
• 2019

NDSM (Normalized Digital Surface Model) is key information for the detailed analysis of remote sensing data. Although NDSM can be simply obtained by subtracting a DTM (Digital Terrain Model) from a DSM (Digital Surface Model), in case of UAV (Unmanned Aerial Vehicle) data, it is difficult to get an accurate DTM due to high resolution characteristics of UAV data containing a large number of complex objects on the ground such as vegetation and urban structures. In this study, RGB-based UAV vegetation index, ExG (Excess Green) was used to extract initial seed points having low ExG values for region growing such that a DTM can be generated cost-effectively based on high resolution UAV data. For this process, local window analysis was applied to resolve the problem of erroneous seed point extraction from local low ExG points. Using the DSM values of seed points, region growing was applied to merge neighboring terrain pixels. Slope criteria were adopted for the region growing process and the seed points were determined as terrain points in case the size of segments is larger than 0.25 ㎡. Various slope criteria were tested to derive the optimized value for UAV data-based NDSM generation. Finally, the extracted terrain points were evaluated and interpolation was performed using the terrain points to generate an NDSM. The proposed method was applied to agricultural area in order to extract the above ground heights of crops and check feasibility of agricultural monitoring.

• Journal of Navigation and Port Research
• /
• v.35 no.1
• /
• pp.51-56
• /
• 2011

In this paper, we presents an algorithm which restores lost data or increases resolution of a DTM(Digital terrain model) using fractal theory. Terrain information(fractal dimension and standard deviation) around the patch to be restored is extracted and then with this information and original data, the elevations of cells are interpolated using the random midpoint displacement method. The results of the proposed algorithm are compared with those of the bilinear and bicubic methods on a fractal terrain map.

• Journal of Navigation and Port Research
• /
• v.33 no.6
• /
• pp.451-456
• /
• 2009

In this paper, we presents an algorithm which generates its high-resolution DTM using a low-resolution DTM of the sea floor terrain and fractal theory. The fractal dimension of each patch region divided from the DTM is extracted and then with this information and original data, each cell region in the patch is interpolated using the midpoint displacement method and a median filter is incorporated to generate natural and smooth sea floor surface. The effectiveness of the proposed algorithm is tested on a fractal terrain map.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.885-887
• /
• 2003

The purpose of this investigation is to generate true orthophotos from high resolution satellite images. The major works of this research include 4 parts: (1) determination of orientation parameters, (2) generating traditional orthophotos using terrain model, (3) relief correction for buildings, and (4) process for hidden areas. To determine the position of satellites, we correct the onboard orientation parameters to fine tune the orbit. In the generation of traditional orthophotos, we employ orientation parameters and digital terrain model(DTM) to rectify tilt displacements and relief displacements for terrain. We, then, compute relief displacements for buildings with digital building model (DBM). To avoid double mapping, we detect hidden areas. Due to the satellite’s small field of view, an efficient method for the detection of hidden areas and building rectification will be proposed in this paper. Test areas cover the city of Kaohsiung in southern Taiwan. Test images are from the QuickBird satellite.

• Spatial Information Research
• /
• v.15 no.4
• /
• pp.363-370
• /
• 2007

This study has been carried for the development of the basic algorithm of helicopter navigation system based on TRN (Terrain Referenced Navigation) with information input from the GPS. The helicopter determines flight path due to Origination-Destination analysis on the Cartesian coordinate system of 3-D DTM. This system shows 3-D mesh map and the O-D flight path profile for the pilot's acknowledgement of the terrain, at first. The system builds TCF (terrain clearance floor) far the buffer zone upon the surface of ground relief to avid the ground collision. If the helicopter enters to the buffer zone during navigation, the real-time warning message which commands to raise the body pops up using Matlab menu. While departing or landing, control of the height of the body is possible. At present, the information (x, y, z coordinates) from the GPS is assumed to be input into the system every 92.8 m of horizontal distance while navigating along flight path. DTM of 3" interval has been adopted from that which was provided by ChumSungDae Co., Ltd..

• Korean Journal of Remote Sensing
• /
• v.24 no.5
• /
• pp.463-471
• /
• 2008

The quality of orthoimages mainly depends on the elevation information and exterior orientation (EO) parameters. Since LiDAR data directly provides the elevation information over the earth's surface including buildings and trees, the concept of true orthorectification has been rapidly developed and implemented. If a LiDAR-driven digital surface model (DSM) is used for orthorectification, the displacements caused by trees and buildings are effectively removed when compared with the conventional orthoimages processed with a digital elevation model (DEM). This study utilized LiDAR data to generate orthorectified digital aerial images. Experimental orthoimages were produced using digital terrain model (DTM) and DSM. For the preparation of orthorectification, EO components, one of the inputs for orthorectification, were adjusted with the ground control points (GCPs) collected from the LiDAR point data, and the ground points were extracted by a filtering method used in a previous research. The orthoimage generated by DSM corresponded more closely to non-ground LiDAR points than the orthoimage produced by DTM.