• Journal of Cadastre & Land InformatiX
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• v.47 no.1
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• pp.15-26
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• 2017

The decrease of green space according to the urbanization has caused many environmental problems as the destruction of habitat, air pollution, heat island effect. With interest growing in natural view recently, proper management of evergreen tree which is lived even the winter season has been on the rise importantly. This study analyzed the distribution area of evergreen tree using vegetation index based on unmanned aerial vehicle (UAV). Firstly, RGB and NIR+RG camera were loaded in fixed-wing UAV and image mosaic was achieved using GCPs based on Pix4d SW. And normalized differences vegetation index (NDVI) and soil adjusted vegetation index (SAVI) was calculated by band math function from acquired ortho mosaic image. validation points were applied to evaluate accuracy of the distribution of evergreen tree for each range value and analysis showed that kappa coefficient marked the highest as 0.822 and 0.816 respectively in "NDVI > 0.5" and "SAVI > 0.7". The area of evergreen tree in "NDVI > 0.5" and "SAVI > 0.7" was $11,824m^2$ and $15,648m^2$ respectively, that was ratio of 4.8% and 6.3% compared to total area. It was judged that UAV could supply the latest and high resolution information to vegetation works as urban environment, air pollution, climate change, and heat island effect.

• Journal of Cadastre & Land InformatiX
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• v.47 no.1
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• pp.213-223
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• 2017

Recently, the air quality of South Korea has deteriorated and public interest has been increasing. Various observation means are used for the monitoring of the atmospheric environment, but it relies on the experience and judgment of the observer in the absence of spatial information on the emission facilities. The purpose of this study was to determine the availability of using drones for monitoring air pollutant emission facilities. A texture transformation method was applied to the drone ortho image to detect the small gas emission facility and the slope data calculated by the digital surface model (DSM) was used to reduce the false alarm ratio. As a result, it shows the possibility of using drones in the detection of small gas emission facilities by showing about 80% of positive detection ratio and 40% of false alarm ratio. In the future, various researches are required to the improve positive detection ratio and the reduction of the false alarm ratio. Based on these results, it is necessary to construct a database including 3D spatial information of air pollutant emission facilities.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.3
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• pp.241-253
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• 2008

Recently, it is appearing that new paradigm of urban planning that ubiquitous concept such as the u-City, uECO-City is introduced while is rising necessity about third dimensional geo-spatial information of high quality for urban area. Orthophoto can manufacture by expense and time that is less easily than digital map using personal computer even if is not highly technician and according as position relation between manmade feature and natural feature is equal, can get information of distance, angle, horizontal and vertical position coordinate of topographic, area etc.. directly through orthophoto. Also, visual effect is good that orthophoto is expressed by image and interpretation is easy to detailed part of topographic. Manufacture and practical use are consisting in various field, for it is having advantage that can recognize information effectively than digital map. Therefore, this study presents a way of generating a detailed DSM for producing a true-orthphoto of the urban area, and this study also presents a way to produce an optimum true-orthophoto for an urban area by investigating through experiment the optimum variable for the geometric and radiometric correction of the orthophoto. This study also examined the potentials of the thesis by building a 3-dimensional city model of the model region with the above thesis on optimum generating method.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.3
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• pp.253-259
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• 2004

The sheetwise cadastral map data needs to become a Serial Cadastral Map (SCM) database for the promotion of the reliability of cadastral surveying, for the efficient operation of the Parcel Based Land Information System, and for the convenient use of land information as well. A large amount of money and time are required for the editing process of producing SCM DB in accordance with the $\ulcorner$Guideline for the Production of Serial Cadastral Maps$\lrcorner$ by the Ministry of Construction & Transportation if any of field surveying techniques is accompanied by. In addition, a boundary line that extends to a neat line does not meet the counterpart of the neighboring map sheet at a point. Such cases frequently occur and are much dependent upon the decisions of individuals in charge of editing or inspecting. The core processes of the research, firstly overlay SCM produced by the edition of the sheetwise cadastral maps with Autodesk Map on orthophoto images, secondly adjust the parcel boundaries which are delineated over more than one map sheet, and lastly compare the original boundary coordinates and areas with the corresponding adjusted ones and calculate root mean square errors (RMSEs). The research aims at promoting the quality of SCM by minimizing the inconsistency of parcel boundaries by means of the comparative analysis of the calculated RMSEs.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.4_1
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• pp.319-326
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• 2014

The accurate geo-referencing processes that apply ground control points is prerequisite for effective end use of HRSI (High-resolution satellite imagery). Since the conventional control point acquisition by human operator takes long time, demands for the automated matching to existing reference data has been increasing its popularity. Among many options of reference data, the airborne LiDAR (Light Detection And Ranging) data shows high potential due to its high spatial resolution and vertical accuracy. Additionally, it is in the form of 3-dimensional point cloud free from the relief displacement. Recently, a new matching method between LiDAR data and HRSI was proposed that is based on the image projection of whole LiDAR data into HRSI domain, however, importing and processing the large amount of LiDAR data considered as time-consuming. Therefore, we wmotivated to ere propose a local LiDAR chip generation for the HRSI geo-referencing. In the procedure, a LiDAR point cloud was rasterized into an ortho image with the digital elevation model. After then, we selected local areas, which of containing meaningful amount of edge information to create LiDAR chips of small data size. We tested the LiDAR chips for fully-automated geo-referencing with Kompsat-2 and Kompsat-3 data. Finally, the experimental results showed one-pixel level of mean accuracy.

• Journal of the Society of Disaster Information
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• v.14 no.4
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• pp.501-509
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• 2018

Purpose: UAV-based photo measurements are being researched using UAVs in the space information field as they are not only cost-effective compared to conventional aerial imaging but also easy to obtain high-resolution data on desired time and location. In this study, the UAV-based high-resolution images were used to perform the land cover classification. Method: RGB cameras were used to obtain high-resolution images, and in addition, multi-distribution cameras were used to photograph the same regions in order to accurately classify the feeding areas. Finally, Land cover classification was carried out for a total of seven classes using created ortho image by RGB and multispectral camera, DSM(Digital Surface Model), NDVI(Normalized Difference Vegetation Index), GLCM(Gray-Level Co-occurrence Matrix) using RF (Random Forest), a representative supervisory classification system. Results: To assess the accuracy of the classification, an accuracy assessment based on the error matrix was conducted, and the accuracy assessment results were verified that the proposed method could effectively classify classes in the region by comparing with the supervisory results using RGB images only. Conclusion: In case of adding orthoimage, multispectral image, NDVI and GLCM proposed in this study, accuracy was higher than that of conventional orthoimage. Future research will attempt to improve classification accuracy through the development of additional input data.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.367-378
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• 2021

Field compost is a representative non-point pollution source for livestock. If the field compost flows into the water system due to rainfall, nutrients such as phosphorus and nitrogen contained in the field compost can adversely affect the water quality of the river. In this paper, we propose a method for detecting field compost using unmanned aerial vehicle images and deep learning-based semantic segmentation. Based on 39 ortho images acquired in the study area, about 30,000 data were obtained through data augmentation. Then, the accuracy was evaluated by applying the semantic segmentation algorithm developed based on U-net and the filtering technique of Open CV. As a result of the accuracy evaluation, the pixel accuracy was 99.97%, the precision was 83.80%, the recall rate was 60.95%, and the F1-Score was 70.57%. The low recall compared to precision is due to the underestimation of compost pixels when there is a small proportion of compost pixels at the edges of the image. After, It seems that accuracy can be improved by combining additional data sets with additional bands other than the RGB band.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.187-193
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• 2022

In the Yeongdong region of Gangwon-do, coastal areas are important resources in terms of cultural, social and economic aspects. However, the coast of Gangwon-do is experiencing severe erosion, and it is concerned that its adverse effects will gradually increase. In this study, coastline changes of Yangyang and Gangneung in Gangwon-do were tracked and analyzed over a long period of time. In order to build time series image data, aerial photos from the 1940s to the present were mainly used, and data from CORONA satellite, which operated from the 1960s to the early 1970s, were collected and used together. Using 51cm resolution ortho image and 2m resolution Digital Elevation Model(DEM) as reference, ground control points were selected to perform geometric correction on the aerial photos and CORONA images. Subsequently, Canny edge detector applied to these images to extract the coastlines. As a result of analyzing the extracted and vectorized coastlines by overlaying them in chronological order, erosion and deposition occurring around the artificial structures and on the nearby beaches were observed. In this study, the effect of seasonal variation, tide, and various coastal management including the beach filling were not considered. Because coastal erosion is greatly affected by geographic factors, each local government must find its own solution. Continuous research and local data accumulation are required.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1015-1023
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• 2022

The Entry-Descent-Landing process of a lander involves many environmental and technical challenges. To solve these problems, recently, terrestrial relative navigation (TRN) technology has been essential for landers. TRN is a technology for estimating the position and attitude of a lander by comparing Inertial Measurement Unit (IMU) data and image data collected from a descending lander with pre-built reference data. In this paper, we present a method for generating descent dataset and extracting landmarks, which are key elements for developing TRN technologies to be used on Mars. The proposed method generates IMU data of a descending lander using a simulated Mars landing trajectory and generates descent images from high-resolution ortho-map and digital elevation map through a ray tracing technique. Landmark extraction is performed by an area-based extraction method due to the low-textured surfaces on Mars. In addition, search area reduction is carried out to improve matching accuracy and speed. The performance evaluation result for the descent dataset generation method showed that the proposed method can generate images that satisfy the imaging geometry. The performance evaluation result for the landmark extraction method showed that the proposed method ensures several meters of positioning accuracy while ensuring processing speed as fast as the feature-based methods.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.6
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• pp.579-586
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• 2010

Due to the recent development of measuring technology and 3D programs, it has become possible to obtain various spatial data. This study utilizes the 2-dimensional data and 3-dimensional data extraction technology based on the existing empirical and statistical DB. The data obtained from geospatial data technology are integrated with civil engineering BIM to conduct the modeling of the topography of the target region and select the optimum location condition by using the cut and fill balance of the volume of earth. The target area is the land around Tamjin River, Jangheong-gun, Jeolla-do. The 3-dimensional topology linked with 3-dimensional mapping technology by using the orth-image and aerial LiDAR that uses aerial photo of the target area is visualized with Civil3D of AutoDesk. By using Civil3D program, the Thanks to the recent development of measuring technology and 3D programs, target area is analyzed through visualization and related data can be obtained for analysis. The method of using civil engineering BIM enables to obtain various and accurate information about the target area which is helpful for addressing the issues risen from the existing methodology. In this regard, it aims at searching for the alternatives and provides suggestions to utilize the information.