• Journal of the Korean Society of Environmental Restoration Technology
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• v.13 no.5
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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.

• Korean Journal of Remote Sensing
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• v.35 no.2
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• pp.317-326
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• 2019

Development projects and related environmental impacts take place in space. Therefore, it is important to use spatial information in the environmental impact assessment process. This study proposes to construct spatial information produced by various organizations as an inventory and suggests it to be utilized in environmental impact assessment process. For this purpose, investigate the use of spatial information in the environmental impact assessment process and list of environmental space information provided by public information systems. and applied the methodology derived from previous studies to build an inventory of spatial information using environmental impact assessment. The spatial information utilized in the environmental impact assessment work was 64 items. Based on the data availability, linkage and renewability, the spatial information of the Environment that can be used for the environmental impact assessment was 45 items. Finally 49 items, including 19 new items were presented as an inventory, contributing to the performance of environmental impact assessment based on spatial information.

• Korean Journal of Remote Sensing
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• v.37 no.1
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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.

• Korean Journal of Remote Sensing
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• v.37 no.4
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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.

• Korean Journal of Remote Sensing
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• v.33 no.5_3
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• pp.763-771
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• 2017

The purpose of this paper is to review the background and purpose of the special issue on Theory of Environment Geospatial Information and Its Applications in Korean Journal of Remote Sensing. The significance of the paper was also discussed. Environmental information refers to environment related information (literature, statistics, images, etc.) in a comprehensive manner. Such environmental information as a local change or issue of the environment is defined as environmental spatial information by developing in a spatial form. Remote sensing data is very useful as direct or indirect data including environmental spatial information on wide-area and local environment. Various applications will be possible not only in the environmental field through several improvements. For this purpose, first, refining and scientificization of technology to build environmental spatial information could be performed. Second, the application field can be expanded by developing the concept and contents of existing environmental spatial information. The third method is continuous increase of the application of existing environmental spatial information. In this paper, the direction of development was examined that reflects recent changes of environmental spatial information such as conversion of data formats and integration with ICT (Information and Communications Technologies). In particular, the basic technology for the construction of environmental spatial information was reviewed through various papers. Through the studies related to the above, utilization of domestic environmental spatial information would be diversified. Also, the development of environment policy and efficient management of environmental factors could be possible.

• Korean Journal of Remote Sensing
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• v.37 no.1
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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.

• Proceedings of the KSRS Conference
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• 2008.10a
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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.

• Korean Journal of Remote Sensing
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• v.36 no.4
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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.

• Journal of Environmental Policy
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• v.9 no.2
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• pp.111-133
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• 2010

Environmental conservation plan, notwithstanding their feasibility and potential utility in construction of environment-friendly spaces, has long been perceived in practice as "declarative" and a "formality." Such perceptions are largely the result of the failure to provide spatial planning that is directly relevant to development of the space in question, and to sufficiently interconnect with urban development plan. This demonstrates the need for ways to link disparate plans, i.e. to enact "spatial environment plan." In response to these issues, this study proposes the systematization of spatial environment data as a necessary prerequisite to the establishment of spatial environment plan, which would provide both linkages with other plans, and ensure the applicability of environmental conservation plan. To this end, this study analyzed existing environmental data, and then proposed systems for links with spatial environment plan. In respect of this, the study examined spatial data systems, and then classified applicable spatial according to each environmental medium. The study also produced spatial information and planning items that can be included in spatial environment plans for each of the nine environmental media, and then constructed a system that could link the existing spatial information system, current spatial environment data, and spatial environment management plan. Furthermore, the study proposed matters for improvement in the construction of spatial environmental data to ensure the activation of spatial environment plan. The construction of a systematic spatial database, by facilitating the smooth establishment of spatial environment plan, can enhance and upgrade environmental conservation plan, while contributing to enhanced linkages with related spatial plans.

• Korean Journal of Remote Sensing
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• v.39 no.1
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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.