• 한국환경복원기술학회지
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• 제13권5호
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• pp.123-134
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• 2010

Environmental conservation planning as set forth in the "Framework Act for Environmental Policy" is a representative planning that demands linkages with spatial development planning like urban master plan. However, despite the intentions and efforts of government (including revision of relevant guidelines etc.), controversy still continues regarding the efficacy of environmental conservation planning in respect of its linkages to spatial development planning. Accordingly, this study was devised to examine existing issues and produce proposals for improvement in ensuring the efficacy of environmental conservation planning by local governments. This study focused in particular on the establishment of spatial environmental plans as suggested in the guidelines of the Ministry of Environment for the purposes of strengthening the efficacy of environmental conservation planning. Based of questionnaires for relevant officials of local governments, the study found that although local governments with established current spatial environmental plans are not numerous, the need for establishment of spatial environmental plans were high in terms of the applicability of environmental conservation and spatial plans. Furthermore, this study also confirmed through analysis of questionnaires data, archival research and case study research that there were a number of salient issues including an overly access and program centered planning method based on individual pollution sources and individual post factor measures in the planning aspect, a lack of usable spatial information in the application of spatial environmental information, and inadequate connections with spatial development planning in respect of linkages with other plans. Under these circumstances, various proposals for improvement were presented including the establishment of contents in environmental conservation planning for each urban master planning item from the standpoint of planning, strengthening of basic environmental surveys for spatial planning and preparation of applicable proposals from the perspective of leveraging of spatial environmental information, and systematic improvements that can enable mutual consideration through feedback between environmental conservation planning and urban master planning from the perspective of connections with spatial planning.

• 대한원격탐사학회지
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• 제35권2호
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• pp.317-326
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• 2019

개발사업 및 관련 환경영향은 공간 위에서 이루어지므로 환경영향평가 과정에서는 공간정보의 활용이 필수적이다. 본 연구에서는 환경영향평가의 공간정보 활용을 확대하기 위해 산재된 공간정보를 인벤토리로 구축, 환경영향평가 과정에서 활용할 수 있도록 제시하고자 한다. 이를 위해 환경영향평가 과정에서의 공간정보 이용 현황과 공공의 정보시스템에서 제공하는 환경 관련 공간정보 목록을 조사하였다. 그리고 선행연구 분석을 통해 도출한 인벤토리 구축 방법론을 적용, 환경영향평가 시 활용할 수 있는 공간정보 목록을 작성하였다. 그 결과 환경영향평가 업무에서 활용중인 공간정보는 64개 항목으로 조사되었으며, 자료 활용성 및 연계 갱신 가능성을 토대로 환경영향평가에 활용 가능한 국토환경공간정보는 45개 항목으로 조사되었다. 최종적으로 중복 제거 및 항목 재구성을 통해 14개의 신규 항목을 포함한 총 49개 항목을 도출, 공간정보 인벤토리로 제시하여 공간정보 기반의 환경영향평가에 기여할 수 있도록 하였다.

• 대한원격탐사학회지
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• 제37권1호
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• pp.153-160
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• 2021

Land Surface Temperature (LST) is the radiological surface temperature which observed by satellite. It is very important factor to estimate condition of the Earth such as Global warming and Heat island. For these reasons, many countries operate their own satellite to observe the Earth condition. South Korea has many landcovers such as forest, crop land, urban. Therefore, if we want to retrieve accurate LST, we would use high-resolution satellite data. In this study, we made LSTs with 4 LST retrieval algorithms which are used widely with Landsat-8 data which has 30 m spatial resolution. We retrieved LST using equations of Price, Becker et al. Prata, Coll et al. and they showed very similar spatial distribution. We validated 4 LSTs with Moderate resolution Imaging Spectroradiometer (MODIS) LST data to find the most suitable algorithm. As a result, every LST shows 2.160 ~ 3.387 K of RMSE. And LST by Prata algorithm show the lowest RMSE than others. With this validation result, we choose LST by Prata algorithm as the most suitable LST to South Korea.

• 대한원격탐사학회지
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• 제37권4호
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• pp.777-788
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• 2021

Since aerosol has a relatively short duration and significant spatial variation, satellite observations become more important for the spatially and temporally continuous quantification of aerosol. However, optical remote sensing has the disadvantage that it cannot detect AOD (Aerosol Optical Depth) for the regions covered by clouds or the regions with extremely high concentrations. Such missing values can increase the data uncertainty in the analyses of the Earth's environment. This paper presents a spatial gap-filling framework using a univariate statistical method such as DCT-PLS (Discrete Cosine Transform-based Penalized Least Square Regression) and FMM (Fast Matching Method) inpainting. We conducted a feasibility test for the hourly AOD product from AHI (Advanced Himawari Imager) between January 1 and December 31, 2019, and compared the accuracy statistics of the two spatial gap-filling methods. When the null-pixel area is not very large (null-pixel ratio < 0.6), the validation statistics of DCT-PLS and FMM techniques showed high accuracy of CC=0.988 (MAE=0.020) and CC=0.980 (MAE=0.028), respectively. Together with the AI-based gap-filling method using extra explanatory variables, the DCT-PLS and FMM techniques can be tested for the low-resolution images from the AMI (Advanced Meteorological Imager) of GK2A (Geostationary Korea Multi-purpose Satellite 2A), GEMS (Geostationary Environment Monitoring Spectrometer) and GOCI2 (Geostationary Ocean Color Imager) of GK2B (Geostationary Korea Multi-purpose Satellite 2B) and the high-resolution images from the CAS500 (Compact Advanced Satellite) series soon.

• 대한원격탐사학회지
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• 제33권5_3호
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• pp.763-771
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• 2017

본 사설은 대한원격탐사학회지의 환경공간정보 이해와 활용 특별호 발간의 배경과 목적 그리고 발간 논문의 의의 고찰을 목적으로 한다. 환경정보는 환경과 관련된 정보(문헌, 통계 및 이미지 등)를 포괄적으로 의미한다. 이러한 환경정보가 지역적으로 발생하는 환경의 변화나 이슈로써 공간적인 형태로 발전하여 환경공간정보로 정의된다. 원격탐사자료는 광역 국지적인 환경에 대한 정보를 포함하여 환경공간정보에 대한 직 간접적인 자료로 매우 높은 활용성을 지니고 있으며, 몇 가지 개선을 통하여 환경분야에 국한되지 않고 보다 다양한 활용이 가능할 것이다. 이를 위하여 첫째, 환경공간정보 구축 기반기술의 정밀화 및 과학화하여 활용을 증대할 수 있다. 둘째, 기존의 환경공간정보의 개념과 내용을 확대함으로써 활용분야를 넓힐 수 있다. 셋째, 기존 환경공간정보의 활용을 지속적으로 증가시키는 것이다. 본 논문에서는 환경공간정보의 최근 변화(데이터의 형식의 전환 및 ICT(Information and Communications Technologies)와 접목 등)를 반영한 발전방향을 고찰하였다. 특히, 환경공간정보 구축의 기본이 되는 기반기술이 정밀화 및 과학화를 다양한 논문을 통하여 고찰하였다. 위와 관련된 연구를 통해 국내 환경공간정보의 활용을 다각화시키고 이를 활용한 정책개발 및 환경요소의 효율적인 관리가 가능할 것이다.

• 대한원격탐사학회지
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• 제37권1호
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• pp.85-95
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• 2021

Recently, as data mining and artificial neural network techniques are developed, analyzing large amounts of data is proposed to reduce the dimension of the data. In general, empirical orthogonal function (EOF) used to reduce the dimension in the ocean data and recently, Self-organizing maps (SOM) algorithm have been investigated to apply to the ocean field. In this study, both algorithms used the monthly Sea level anomaly (SLA) data from 1993 to 2018 around the East Asia Coasts. There was dominated by the influence of the Kuroshio Extension and eddy kinetic energy. It was able to find the maximum amount of variance of EOF modes. SOM algorithm summarized the characteristic of spatial distributions and periods in EOF mode 1 and 2. It was useful to find the change of SLA variable through the movement of nodes. Node 1 and 5 appeared in the early 2000s and the early 2010s when the sea level was high. On the other hand, node 2 and 6 appeared in the late 1990s and the late 2000s, when the sea level was relatively low. Therefore, it is considered that the application of the SOM algorithm around the East Asia Coasts is well distinguished. In addition, SOM results processed by SLA data, it is able to apply the other climate data to explain more clearly SLA variation mechanisms.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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• pp.361-364
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• 2008

It is well known that combining spatial and spectral information can improve land use classification from satellite imagery. High spatial resolution classification has a limitation when only using the spectral information due to the complex spatial arrangement of features and spectral heterogeneity within each class. Therefore, extracting the spatial information is one of the most important steps in high resolution satellite image classification. In this paper, we propose a new spatial feature extraction method. The extracted features are integrated with spectral bands to improve overall classification accuracy. The classification is achieved by applying a Support Vector Machines classifier. In order to evaluate the proposed feature extraction method, we applied our approach to KOMPSAT-2 data and compared the result with the other methods.

• 대한원격탐사학회지
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• 제36권4호
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• pp.637-643
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• 2020

In this study, the information from environmental impact statements was converted into spatial data because environmental data from development sites are collected during the environmental impact assessment (EIA) process. Spatiotemporal big data were built from environmental spatial data for each environmental medium for 2,235 development sites during 2007-2018, available from public data portals. Comparing air-quality monitoring stations, 33,863 measurement points were constructed, which is approximately 75 times more measurement points than that 452 in Air Korea's real-time measurement network. Here, spatiotemporal big data from 2,677,260 EIAs were constructed. In the future, such data might be used not only for EIAs but also for various spatial plans.

• 환경정책연구
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• 제9권2호
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• pp.111-133
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• 2010

환경정책기본법에 근거하여 수립되는 환경보전계획은 친환경적인 공간구축을 위한 활용 가능성과 잠재성에도 불구하고 선언적이면서 형식적인 계획으로 사실상 인지되고 있다. 이러한 인식의 중요한 요인 중의 하나는 공간개발과 직접적인 관련성이 있는 공간계획(도시기본계획 등)이나 도시개발계획과의 연계성을 확보하지 못한 것에 기인하며, 이는 공간환경계획이라는 계획 간의 연계수단의 필요성으로 종결된다. 이에 환경보전계획의 활용성과 계획 간의 연계성 확보를 위한 공간환경계획의 수립을 위해 선행되어야 할 공간환경정보의 체계화를 제안하고자 하며, 이를 위해 기존의 환경정보를 파악하고 공간환경계획과의 연계방안에 대해서 살펴보고자 하였다. 이와 관련해서 국가차원 및 지자체 차원에서 구축하고 있는 공간정보시스템을 살펴보고, 환경매체별로 활용 가능한 공간정보를 분류하였다. 또한 9개의 환경매체별로 공간환경계획에 포함될 수 있는 공간정보 및 계획 항목을 도출하여, 기존의 공간정보시스템, 공간환경 현황정보, 공간환경 관리계획으로 이어지는 연계체계를 구축하였다. 나아가, 공간환경계획 활성화를 위해 공간환경정보 구축에 관한 개선사항을 제안하였다. 체계적인 공간정보 구축은 공간환경계획 수립을 용이하게 함으로써 환경보전계획을 강화하고 위상을 높임은 물론, 관련 공간계획과의 연계성 강화에도 기여할 것이다.

• 대한원격탐사학회지
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• 제39권1호
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• pp.77-86
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• 2023

Ship detection is widely used in areas such as maritime security, maritime traffic, fisheries management, illegal fishing, and border control, and ship detection is important for rapid response and damage minimization as ship accident rates increase due to recent increases in international maritime traffic. Currently, according to a number of global and national regulations, ships must be equipped with automatic identification system (AIS), which provide information such as the location and speed of the ship periodically at regular intervals. However, most small vessels (less than 300 tons) are not obligated to install the transponder and may not be transmitted intentionally or accidentally. There is even a case of misuse of the ship'slocation information. Therefore, in this study, ship detection was performed using high-resolution optical satellite images that can periodically remotely detect a wide range and detectsmallships. However, optical images can cause false-alarm due to noise on the surface of the sea, such as waves, or factors indicating ship-like brightness, such as clouds and wakes. So, it is important to remove these factors to improve the accuracy of ship detection. In this study, false alarm wasreduced, and the accuracy ofship detection wasimproved by removing wake.As a ship detection method, ship detection was performed using machine learning-based random forest (RF), and convolutional neural network (CNN) techniquesthat have been widely used in object detection fieldsrecently, and ship detection results by the model were compared and analyzed. In addition, in this study, the results of RF and CNN were combined to improve the phenomenon of ship disconnection and the phenomenon of small detection. The ship detection results of thisstudy are significant in that they improved the limitations of each model while maintaining accuracy. In addition, if satellite images with improved spatial resolution are utilized in the future, it is expected that ship and wake simultaneous detection with higher accuracy will be performed.