• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.25 no.6_1
• /
• pp.545-555
• /
• 2007

3D buildings are the most prominent feature comprising urban scene. A few of mega-cities in the globe are virtually reconstructed in photo-realistic 3D models, which becomes accessible by the public through the state-of-the-art online mapping services. A lot of research efforts have been made to develop automatic reconstruction technique of large-scale 3D building models from remotely sensed data. However, existing methods still produce irregular building polygons due to errors induced partly by uncalibrated sensor system, scene complexity and partly inappropriate sensor resolution to observed object scales. Thus, a geometric regularization technique is urgently required to rectify such irregular building polygons that are quickly captured from low sensory data. This paper aims to develop a new method for regularizing noise building outlines extracted from airborne LiDAR data, and to evaluate its performance in comparison with existing methods. These include Douglas-Peucker's polyline simplication, total least-squared adjustment, model hypothesis-verification, and rule-based rectification. Based on Minimum Description Length (MDL) principal, a new objective function, Geometric Minimum Description Length (GMDL), to regularize geometric noises is introduced to enhance the repetition of identical line directionality, regular angle transition and to minimize the number of vertices used. After generating hypothetical regularized models, a global optimum of the geometric regularity is achieved by verifying the entire solution space. A comparative evaluation of the proposed geometric regulator is conducted using both simulated and real building vectors with various levels of noise. The results show that the GMDL outperforms the selected existing algorithms at the most of noise levels.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.28 no.3
• /
• pp.299-304
• /
• 2010

Depending on the progress of the surveying and information processing technology, the rapidly developing field of spatial information and the 3D real world spatial information for a variety of content on the computer was able to easily access. In this research, to study on the spot or to use aerial photographs to measure trees of the acquired data, calculate the trees height, forest area and capacity, determine the distribution of the density of acquired points in the forest and analyze accurate and objective information was acquired. The United States, Canada and so on through the capacity of trees biomass, forest resource analysis, time series monitoring, wildfire behavior modeling and applied research and has been declared. During worldwide is increasing interest in forest resources. In nationally, extensive research and analysis of the forest consists of the correct management and protection of forest resources to be effective.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.30 no.2
• /
• pp.181-188
• /
• 2012

The most recent, Digital photogrammetric camera, Airborne LiDAR and GPS/INS same sensors are used to acquire spatial information of various kinds in the field of aerial survey. In addition, Direct Georeferencing technology has been widely utilized with digital photogrammetric camera and GPS/INS. However, the sensor Calibration to be performed according to the combination of various sensors is followed by problems. Most of all, boresight calibration of integrated sensors is a critical element in the mapping process when using direct georeferencing or using the GPS/INS aerotriangulation. The establishment of a national test-bed in Sejong-si for aerial sensor calibration is absolutely necessary to solve this problem. And accurate calibration with used to integration of GPS/INS by aerotriangulation of aerial imagery was necessary for determination of system parameters, evaluation of systematic errors. Also, an investigation of efficient method for Direct georeferencing to determine the exterior orientation parameters and assessment of geometric accuracy of integrated sensors are performed.

• Proceedings of the Korea Contents Association Conference
• /
• 2008.05a
• /
• pp.449-452
• /
• 2008

The building heights of big cities which charged with most space are 3-D information as relative vertical distance from ground control points, but they didn't know the heights using contour with maps as lose of skyline or building heights for downtown, practically continuously developed of many technology methods for implementation of 3-D spatial earth. So, For the view as stereos of variety earth form generated 3-D spatial and made terrain perspective map, 3-D simulated of regional and urban space as aviation images. In this papers, it composited geospatial informations and images by DEM generation, and developed and presented for techniques overlay of CAD data and photos captured at our surroundings uses. Particularly, The airborne LiDAR surveying which are very interesting trend have laser scanning sensor and determine the ground heights through detecting angle and range to the grounds, and then designated 3-D spatial composite and simulation from urban areas. Therefore in this papers are suggested ease selections on the users situation by compare as various simulations that its generation of 3-D spatial image by collective for downtown space and urban sub, and the implementation methods for more accurate, more select for the best images.

• Korean Journal of Remote Sensing
• /
• v.39 no.5_4
• /
• pp.1145-1153
• /
• 2023

Urban trees play an important role in absorbing carbon dioxide from the atmosphere, improving air quality, mitigating the urban heat island effect, and providing ecosystem services. To effectively manage and conserve urban trees, accurate spatial information on their location, condition, species, and population is needed. In this study, we propose an algorithm that uses a high-resolution urban tree cover map constructed from deep learning approach to separate trees from the urban land surface and accurately detect tree locations through local maximum filtering. Instead of using a uniform filter size, we improved the tree detection performance by selecting the appropriate filter size according to the tree height in consideration of various urban growth environments. The research output, the location and height of individual trees in human settlement over Suwon, will serve as a basis for sustainable management of urban ecosystems and carbon reduction measures.

• Korean Journal of Remote Sensing
• /
• v.29 no.4
• /
• pp.361-373
• /
• 2013

The monitoring of urban area, target detection and building reconstruction have been actively studied and investigated since high resolution X-band SAR images could be acquired by airborne and/or satellite SAR systems. This paper describes an efficient approach to reconstruct artificial structures (e.g. apartment, building and house) in urban area using high resolution X-band SAR images. Building footprint was first extracted from 1:25,000 digital topographic map and then a corner line of building was detected by an automatic detecting algorithm. With SAR amplitude images, an initial building height was calculated by the length of layover estimated using KS-test (Kolmogorov-Smirnov test) from the corner line. The interferometric SAR phases were simulated depending on SAR geometry and changable building heights ranging from -10 m to +10 m of the initial building height. With an interferogram from real SAR data set, the simulation results were compared using the method of the phase consistency. One of results can be finally defined as the reconstructed building height. The developed algorithm was applied to repeat-pass TerraSAR-X spotlight mode data set over an apartment complex in Daejeon city, Korea. The final building heights were validated against reference heights extracted from LiDAR DSM, with an RMSE (Root Mean Square Error) of about 1~2m.

• Korean Journal of Remote Sensing
• /
• v.39 no.5_3
• /
• pp.1009-1029
• /
• 2023

Urban trees play a vital role in urban ecosystems,significantly reducing impervious surfaces and impacting carbon cycling within the city. Although previous research has demonstrated the efficacy of employing artificial intelligence in conjunction with airborne light detection and ranging (LiDAR) data to generate urban tree information, the availability and cost constraints associated with LiDAR data pose limitations. Consequently, this study employed freely accessible, high-resolution multispectral satellite imagery (i.e., Sentinel-2 data) to estimate fractional tree canopy cover (FTC) within the urban confines of Suwon, South Korea, employing machine learning techniques. This study leveraged a median composite image derived from a time series of Sentinel-2 images. In order to account for the diverse land cover found in urban areas, the model incorporated three types of input variables: average (mean) and standard deviation (std) values within a 30-meter grid from 10 m resolution of optical indices from Sentinel-2, and fractional coverage for distinct land cover classes within 30 m grids from the existing level 3 land cover map. Four schemes with different combinations of input variables were compared. Notably, when all three factors (i.e., mean, std, and fractional cover) were used to consider the variation of landcover in urban areas(Scheme 4, S4), the machine learning model exhibited improved performance compared to using only the mean of optical indices (Scheme 1). Of the various models proposed, the random forest (RF) model with S4 demonstrated the most remarkable performance, achieving R² of 0.8196, and mean absolute error (MAE) of 0.0749, and a root mean squared error (RMSE) of 0.1022. The std variable exhibited the highest impact on model outputs within the heterogeneous land covers based on the variable importance analysis. This trained RF model with S4 was then applied to the entire Suwon region, consistently delivering robust results with an R² of 0.8702, MAE of 0.0873, and RMSE of 0.1335. The FTC estimation method developed in this study is expected to offer advantages for application in various regions, providing fundamental data for a better understanding of carbon dynamics in urban ecosystems in the future.

• Ecology and Resilient Infrastructure
• /
• v.4 no.1
• /
• pp.12-23
• /
• 2017

The Naeseong Stream is a meandering sand-bed stream flowing through mountains and has so long maintained its geomorphological uniqueness characterized by extensive braided bare bars. Recently, its long-lasting landscape has been changed due to encroachment of vegetation. In this study being a part of long-term monitoring research morphological changes of the 56.8 km long study reach of the Naeseong Stream, which occurred during the period of 2012 - 2016 were analyzed. Airborne LiDAR and terrestrial cross-section surveys were carried out. Hydrological and on-site investigation data were also collected. Among the main four sites, two bend reaches showed point bars enlarged, while along the other two straight reaches mid-channel bars were either newly formed or increased in area and height. At the highest deposition point of each bar, vertical changes which were caused by one or two times of sediment deposition amounted to 0.6 - 1.4 m. On the contrary channel bed degradation was not obvious. Overall morphological changes in the study reach were attributed to deposition of sediment which occurred during the flood in July 2016 on the bar surfaces vegetated during the precedent dry seasons. These kind of geomorphological processes are thought to be the same as those related to the existing mid-channel islands along the mid- and downstream reach of the Naeseong Stream.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.44 no.1
• /
• pp.93-106
• /
• 2016

This study aimed to estimate and evaluate the thermal mitigation of the urban tree canopy on the summer outdoor environment by quantitative use of mean radiant temperature. This study applied the SOLWEIG model based $T_{mrt}$ comparison method by using both (1) urban tree canopy presence examples and (2) urban tree canopy absence examples as constructed from airborne LiDAR system based three-dimensional point cloud data. As a result, it was found that an urban tree canopy can provide a decrease in the entire domain averaged daily mean $T_{mrt}$ about $5^{\circ}C$ and that the difference can increase up to $33^{\circ}C$ depending both on sun position and site conditions. These results will enhance urban microclimate studies such as indices (e.g., wind speed, humidity, air temperature) and biometeorology (e.g., perceived temperature) and will be used to support forest based public green policy development.

• Journal of Korean Society for Geospatial Information Science
• /
• v.24 no.3
• /
• pp.49-58
• /
• 2016

Applications of drone in various fields have been increasing in recent years. Drone has great potential for forest management. Therefore this paper is using drone for forest damage areas. Forest damage areas is divided into caused by anthropogenic and occurs naturally, the possibility of disasters, such as slope sliding, slope failures and landslides, sediment runoff exists. Therefore, this research was to utilize the drone photogrammetry to perform the damage analysis of forest damage areas. Geometrical treatment processing results in Drone Photogrammetry, the plane position error RMSE was ${\pm}0.034m$, the elevation error RMSE was ${\pm}0.017m$. The plane position error of orthophoto RMSE was ${\pm}0.083m$, the elevation error of digital elevation model RMSE was ${\pm}0.085m$. In addition, It was possible to current state analysis of damage in forest damage areas of airborne LiDAR data of before forest damage and drone photogrammetry data of after forest damage. and application of drone photogrammetry for production base data for restoration and design in forest damage areas.