• Korean Journal of Remote Sensing
• /
• v.34 no.1
• /
• pp.45-74
• /
• 2018

Landslide is a natural hazard that threats lives and properties in many areas around the world. Landslides are difficult to recognize, particularly in rainforest regions. Thus, an accurate, detailed, and updated inventory map is required for landslide susceptibility, hazard, and risk analyses. The inconsistency in the results obtained using different features selection techniques in the literature has highlighted the importance of evaluating these techniques. Thus, in this study, six techniques of features selection were evaluated. Very-high-resolution LiDAR point clouds and orthophotos were acquired simultaneously in a rainforest area of Cameron Highlands, Malaysia by airborne laser scanning (LiDAR). A fuzzy-based segmentation parameter (FbSP optimizer) was used to optimize the segmentation parameters. Training samples were evaluated using a stratified random sampling method and set to 70% training samples. Two machine-learning algorithms, namely, Support Vector Machine (SVM) and Random Forest (RF), were used to evaluate the performance of each features selection algorithm. The overall accuracies of the SVM and RF models revealed that three of the six algorithms exhibited higher ranks in landslide detection. Results indicated that the classification accuracies of the RF classifier were higher than the SVM classifier using either all features or only the optimal features. The proposed techniques performed well in detecting the landslides in a rainforest area of Malaysia, and these techniques can be easily extended to similar regions.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.36 no.1
• /
• pp.17-24
• /
• 2018

DEM (Digital Elevation Model) is a useful dataset which represents the earth surface. Beside many applications, production and frequent update of DEM is a costly task. Recently global satellite based DEMs are available which has huge potential for application. To check the accuracy, this study compares two global DEMs: AW3D30 (Advanced Land Observing Satellite World 3D 30m) and SRTM30 (Shuttle Radar Topography Mission Global 30m) with reference resampled LiDAR DEM 30m in a test area around Chuncheon, Korea. The comparison analysis was based on statistics of each DEM, their difference, profiles, slope, basin and stream orders. As a result, it is found that SRTM30 and AW3D30 were much similar but inconsistent in the test area compared to the LiDAR30 DEM. In addition, SRTM30 shows less difference with LiDAR30 compared to the AW3D30 DEM. But, DEMs should be very carefully examined for area which has temporal or season changes. For basin and stream analysis, global DEMs can be used only for regional scale analysis not local large scales.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.26 no.3D
• /
• pp.527-534
• /
• 2006

This study estimated the forest damage of Kangwon-Do fire disaster occurred April 2005. For the estimation, the delineation of fire damaged area was performed using SPOT-4 satellite image and DSM (Digital surface model)/DTM (Digital Terrain Model) was generated by airborne and ground LiDAR data to calculate forests height. The damaged amount of money was calculated in forest area using stand volume formula, combining the canopy height from forest height model and digital stock map. The total forest damage amounted to 3.9 billion won.

• Proceedings of the KSRS Conference
• /
• v.1
• /
• pp.504-507
• /
• 2006

Airborn Lidar technology has been applied to diverse applications with the advantages of accurate 3D information. Further, Lidar intensity, backscattered signal power, can provid us additional information regarding target's characteristics. Lidar intensity varies by the target reflectance, moisture condition, range, and viewing geometry. This study purposes to generate normalized airborne LiDAR intensity image considering those influential factors such as reflectance, range and geometric/topographic factors (scan angle, ground height, aspect, slope, local incidence angle: LIA). Laser points from one flight line were extracted to simplify the geometric conditions. Laser intensities of sample plots, selected by using a set of reference data and ground survey, werethen statistically analyzed with independent variables. Target reflectance, range between sensor and target, and surface slope were main factors to influence the laser intensity. Intensity of laser points was initially normalized by removing range effect only. However, microsite topographic factor, such as slope angle, was not normalized due to difficulty of automatic calculation.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
• /
• 2010.04a
• /
• pp.257-258
• /
• 2010

Recently data, which are obtained by the airborne laser scanner system have been utilized to rapidly obtain three-dimensional location coordinates for a large area. According to operation regulation, the distance between a GPS base station and a aircraft GPS is fixed within a radius of 30km. In this paper, we compare data obtained by GPS observation station operated in National Geographic Information Institute with those obtained by GPS base station for making a airborne laser survey.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.20 no.3
• /
• pp.181-194
• /
• 2017

This study aims to develop a regression model for forest volume estimation using field-collected forest inventory information and airborne LiDAR data. The response variable of the model is forest stem volume, was measured by random sampling from each individual plot of the 30 circular sample plots collected in Bonghwa-gun, Gyeong sangbuk-do, while the predictor variables for the model are Height Percentiles(HP) and Height Bin(HB), which are metrics extracted from raw LiDAR data. In order to find the most appropriate model, the candidate models are constructed from simple linear regression, quadratic polynomial regression and multiple regression analysis and the cross-validation tests were conducted for verification purposes. As a result, $R^2$ of the multiple regression models of $HB_{5-10}$, $HB_{15-20}$, $HB_{20-25}$, and $HBgt_{25}$ among the estimated models was the highest at 0.509, and the PRESS statistic of the simple linear regression model of $HP_{25}$ was the lowest at 122.352. $HB_{5-10}$, $HB_{15-20}$, $HB_{20-25}$, and $HBgt_{25}-based$ models, thus, are comparatively considered more appropriate for Korean forests with complicated vertical structures.

• Korean Journal of Remote Sensing
• /
• v.29 no.1
• /
• pp.81-94
• /
• 2013

The Radar altimeter transmits radio signals to the surface, receives the backscattered signals and measures the distance between the airplane and the nadir surface. The measurements of radar altimeter are affected by various factors on the surface below the aircraft. This study performed flight campaigns in June 2012 and acquired raw data from radar altimeter, LiDAR and other sensors. Based on the LiDAR DSM (Digital Surface Model) as a reference data, the characteristics of radar altimeter were analyzed in the respect of range and surface area affecting on the receiving power of the radar altimeter. Consequently, the radar altimeter was strongly affected by the surface area within beam width and reflectivity related to RCS (Radar Cross Section) rather than range.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.11 no.3
• /
• pp.136-150
• /
• 2008

Many studies have been carried out for automatic extraction of building by LiDAR data or airphoto. Combining the benefits of 3D location information data and shape information data of image can improve the accuracy. So, in this research building recognition algorithm based on contour was used to improve accuracy of building recognition by LiDAR data and elaborate building boundary recognition by airphoto. Building recognition algorithm based on contour can generate building boundary and roof structure information. Also it shows better accuracy of building detection than the existing recognition methods based on TIN or NDSM. Out of creating buffers in regular size on the building boundary which is presumed by contour, this research limits the boundary area of airphoto and elaborate building boundary to fit into edge of airphoto by double active contour. From the result of this research, 3D building boundary will be able to be detected by optimal matching on the constant range of extracted boundary in the future.

• Spatial Information Research
• /
• v.20 no.1
• /
• pp.27-38
• /
• 2012

The recent development of CFD techniques are being involved w ith Environmental Impact Assessment and Environmental DesignroThey are being applied to the Site Planning and Engineering Design works as a new trendroHowever, CFD laboratory works are not extended to the field works in Industrial Project due to inaccuracy of the data input process that is cause by absence of regional height informationsroHence, in this study, we promote to build a new initial input data processing steps and algorithms for CFD Model generation. ENVI-met model is very popular, efficient, and freely downloadable CFD model. Light Detection And Ranging (LiDAR) are well known state of art technology and dataset proving a reliable accuracy for CFD. We use LiDAR data as a input source for CFD input producing process and algorithm development and evaluation. CFD initial input data generation process and results derived from am development and set is very useful and efficient for rapid CFD input data producing and maklomore reliable CFD Model forec st for atmospheric and climatic analysis for planning and design engineering industry.

• Journal of Korean Society for Geospatial Information Science
• /
• v.19 no.1
• /
• pp.97-103
• /
• 2011

LiDAR system has become a popular tool for generating 3D surface data such as Digital Surface Model. Extraction of valuable information, such as digital building models, from LiDAR data has been an attractive research subject. This research addresses to extract planar patches from LiDAR data. Planar patches are important primitives consisting of man-made objects such as buildings. In order to determine the best fitted planes, this research proposed a method to reduce/eliminate the impact of the outliers and the intersection areas of two planes. After finishing plane fitting, planar patches are segmented by pseudo color values which are calculated by determined three plane parameters for each LiDAR point. In addition, a segmentation procedure is conducted using the pseudo color values to find planar patches. This paper evaluates the feasibility of the proposed method using both airborne and terrestrial LiDAR data.