남북 산림과학협력 대응 북한 지리정보체계 분야 연구 동향 분석

임중빈(Joongbin Lim),김경민(Kyoung-min Kim) 대한공간정보학회 2018 한국공간정보학회 학술대회 Vol.2018 No.11

농림위성 산림분야 식생지수 검보정 사이트 설계

임중빈 ( Joongbin Lim ),차성은 ( Sungeun Cha ),원명수 ( Myoungsoo Won ),김준 ( Joon Kim ),박주한 ( Juhan Park ),류영렬 ( Youngryel Ryu ),이우균 ( Woo-kyun Lee ) 대한원격탐사학회 2022 대한원격탐사학회지 Vol.38 No.3

The Compact Advanced Satellite 500-4 (CAS500-4) is under development to efficiently manage and monitor forests in Korea and is scheduled to launch in 2025. The National Institute of Forest Science is developing 36 types of forestry applications to utilize the CAS500-4 efficiently. The products derived using the remote sensing method require validation with ground reference data, and the quality monitoring results for the products must be continuously reported. Due to it being the first time developing the national forestry satellite, there is no official calibration and validation site for forestry products in Korea. Accordingly, the author designed a calibration and validation site for the forestry products following international standards. In addition, to install calibration and validation sites nationwide, the authors selected appropriate sensors and evaluated the applicability of the sensors. As a result, the difference between the ground observation data and the Sentinel-2 image was observed to be within ±5%, confirming that the sensor could be used for nationwide expansion.

데이터 마이닝을 활용한 북한 산림과학 연구 동향 분석(1962~2016)

임중빈 ( Joongbin Lim ),김경민 ( Kyoung-min Kim ),김명길 ( Myung-kil Kim ),이종민 ( Jong Min Yi ),박진우 ( Jin Woo Park ) 한국산림과학회 2020 한국산림과학회지 Vol.109 No.1

In this study, forest-related research papers published in North Korean journals were analyzed to understand the research trends in North Korean forest science. The Korea Science and Technology Information Institute (KISTI) North Korea Science and Technology Network (NKtech) is constructing a database related to science and technology in North Korea. From this, a total of 1,389 articlespublished from 1962 to 2016 were collected with forest science key words based on the South Korean National Science and Technology Standard Classification System. The topics were divided into four categories: afforestation, forest protection, forest use, and forest management. In the field of afforestation, research activities on nursery and agroforestry were active, and the survival rate was emphasized. In the forest protection field, there was a significant research effort into forest pests, and efforts were being made to reduce soil erosion through agroforestry. In the field of forest use, research activities on pulp/paper and mushrooms were active. In the forest management field, activities related to ecological information were conspicuous, and efforts were being made to reduce carbon. These results suggest that the perspective of North Korean forest research has changed from nature reorganization to nature protection. Thus, a comparative study on forest science and technology in each sub-sector of the forest research field, along with analysis of the relationship between policy direction and research direction of North Korea over time, would be worthwhile future investigations. To overcome the problem of technical terminology, a compilation/dictionary of inter-Korean forestry terminology would be useful for effective communication between the two Koreas.

음영기복 알고리즘을 활용한 한반도 촬영 위성영상에서의 지형그림자 탐지

김형규,임중빈,김경민,원명수,김태정,Hyeong-Gyu Kim,Joongbin Lim,Kyoung-Min Kim,Myoungsoo Won,Taejung Kim 대한원격탐사학회 2023 대한원격탐사학회지 Vol.39 No.5

In recent years, the number of users has been increasing with the rapid development of earth observation satellites. In response, the Committee on Earth Observation Satellites (CEOS) has been striving to provide user-friendly satellite images by introducing the concept of Analysis Ready Data (ARD) and defining its requirements as CEOS ARD for Land (CARD4L). In ARD, a mask called an Unusable Data Mask (UDM), identifying unnecessary pixels for land analysis, should be provided with a satellite image. UDMs include clouds, cloud shadows, terrain shadows, etc. Terrain shadows are generated in mountainous terrain with large terrain relief, and these areas cause errors in analysis due to their low radiation intensity. previous research on terrain shadow detection focused on detecting terrain shadow pixels to correct terrain shadows. However, this should be replaced by the terrain correction method. Therefore, there is a need to expand the purpose of terrain shadow detection. In this study, to utilize CAS500-4 for forest and agriculture analysis, we extended the scope of the terrain shadow detection to shaded areas. This paper aims to analyze the potential for terrain shadow detection to make a terrain shadow mask for South and North Korea. To detect terrain shadows, we used a Hill-shade algorithm that utilizes the position of the sun and a surface's derivatives, such as slope and aspect. Using RapidEye images with a spatial resolution of 5 meters and Sentinel-2 images with a spatial resolution of 10 meters over the Korean Peninsula, the optimal threshold for shadow determination was confirmed by comparing them with the ground truth. The optimal threshold was used to perform terrain shadow detection, and the results were analyzed. As a qualitative result, it was confirmed that the shape was similar to the ground truth as a whole. In addition, it was confirmed that most of the F1 scores were between 0.8 and 0.94 for all images tested. Based on the results of this study, it was confirmed that automatic terrain shadow detection was well performed throughout the Korean Peninsula.

정오표

강유진,조동진,한대현,임정호,임중빈,오금희,권언혜,Kang, Yoojin,Cho, Dongjin,Han, Daehyeon,Im, Jungho,Lim, Joongbin,Oh, Kum-hui,Kwon, Eonhye 대한원격탐사학회 2022 대한원격탐사학회지 Vol.38 No.2

딥러닝 모델 기반 위성영상 데이터세트 공간 해상도에 따른 수종분류 정확도 평가

박정묵,심우담,김경민,임중빈,이정수,Park, Jeongmook,Sim, Woodam,Kim, Kyoungmin,Lim, Joongbin,Lee, Jung-Soo 대한원격탐사학회 2022 대한원격탐사학회지 Vol.38 No.6

This study was conducted to classify tree species and assess the classification accuracy, using SE-Inception, a classification-based deep learning model. The input images of the dataset used Worldview-3 and GeoEye-1 images, and the size of the input images was divided into 10 × 10 m, 30 × 30 m, and 50 × 50 m to compare and evaluate the accuracy of classification of tree species. The label data was divided into five tree species (Pinus densiflora, Pinus koraiensis, Larix kaempferi, Abies holophylla Maxim. and Quercus) by visually interpreting the divided image, and then labeling was performed manually. The dataset constructed a total of 2,429 images, of which about 85% was used as learning data and about 15% as verification data. As a result of classification using the deep learning model, the overall accuracy of up to 78% was achieved when using the Worldview-3 image, the accuracy of up to 84% when using the GeoEye-1 image, and the classification accuracy was high performance. In particular, Quercus showed high accuracy of more than 85% in F₁ regardless of the input image size, but trees with similar spectral characteristics such as Pinus densiflora and Pinus koraiensis had many errors. Therefore, there may be limitations in extracting feature amount only with spectral information of satellite images, and classification accuracy may be improved by using images containing various pattern information such as vegetation index and Gray-Level Co-occurrence Matrix (GLCM).

북한의 생태지리구획을 활용한 임농복합경영 적정 수종 및 작물 고찰 연구

박소희 ( Sohee Park ),임중빈 ( Joongbin Lim ),김은희 ( Eun-hee Kim ),양아람 ( A-ram Yang ) 한국산림과학회 2021 한국산림과학회지 Vol.110 No.3

This study aims to identify appropriate tree species and crops for agroforestry target sites in North Korea based on ecological geography and site properties. To this end, an ecological geographic map (13 regions and 4 zones) of North Korea was made using satellite images and North Korean academic journal articles. The target agroforestry sites were selected and mapped according to 18 site conditions depending on 3 site characteristics, and the sites were divided into short-term and long-term target sites depending on the agroforestry management period. Finally, optimal combinations of 30 tree species and 19 crops were selected by overlapping the ecological geographic map and agroforestry target site map. For regions within the same zone, tree species and crops were almost similar; however, compared to regions in other zones, they differed. This is likely because the geographical climatic characteristics reflected in the ecological geographic map vary greatly from zone to zone. These results will be used to propose a combination of suitable tree species and crops that takes into account both management purposes and management types for inter-Korean forest cooperation in the agroforestry sector.

농림위성 활용을 위한 산불 피해지 분류 딥러닝 알고리즘 평가

차성은,원명수,장근창,김경민,김원국,백승일,임중빈,Cha, Sungeun,Won, Myoungsoo,Jang, Keunchang,Kim, Kyoungmin,Kim, Wonkook,Baek, Seungil,Lim, Joongbin 대한원격탐사학회 2022 대한원격탐사학회지 Vol.38 No.6

Recently, forest fires have frequently occurred due to climate change, leading to human and property damage every year. The forest fire monitoring technique using remote sensing can obtain quick and large-scale information of fire-damaged areas. In this study, the Gangneung and Donghae forest fires that occurred in March 2022 were analyzed using the spectral band of Sentinel-2, the normalized difference vegetation index (NDVI), and the normalized difference water index (NDWI) to classify the affected areas of forest fires. The U-net based convolutional neural networks (CNNs) model was simulated for the fire-damaged areas. The accuracy of forest fire classification in Donghae and Gangneung classification was high at 97.3% (f₁=0.486, IoU=0.946). The same model used in Donghae and Gangneung was applied to Uljin and Samcheok areas to get rid of the possibility of overfitting often happen in machine learning. As a result, the portion of overlap with the forest fire damage area reported by the National Institute of Forest Science (NIFoS) was 74.4%, confirming a high level of accuracy even considering the uncertainty of the model. This study suggests that it is possible to quantitatively evaluate the classification of forest fire-damaged area using a spectral band and indices similar to that of the Compact Advanced Satellite 500 (CAS500-4) in the Sentinel-2.

RapidEye 위성영상과 구글 어스를 활용한 북한 DMZ의 산림현황 및 산림황폐지 변화 분석

권수경 ( Sookyung Kwon ),김은희 ( Eunhee Kim ),임중빈 ( Joongbin Lim ),양아람 ( A-ram Yang ) 한국지리정보학회 2021 한국지리정보학회지 Vol.24 No.4

This study was conducted to analyze the forest status and deforestation area changes of the DMZ region in North Korea based on satellite images. Using growing and non-growing season’s RapidEye satellite images, land cover of the North Korean DMZ was classified into stocking land(conifer, deciduous, mixed), deforested land(unstocked mountain, cultivated mountain, bare mountain), and non-forest areas. Deforestation rates in the Yeonan-baecheon, Beopdong-Pyeonggang, Heoyang-Geumgang and Tongcheon-Goseong district were calculated as 14.24%, 16.75%, 5.98%, and 16.63% respectively. Forest fire and land use change of forest were considered as the main causes of deforestation of DMZ. Changes in deforestation area were analyzed through Google Earth images. As a results, it was shown that the area of deforestation was on a decreasing trend. This study can be used as basic data for establishing inter-Korean border region’s forest cooperation strategies by providing forest spatial information on the North Korea’s DMZ.

모의영상을 이용한 농림위성 대기보정의 주요 파라미터 민감도 분석 및 타위성 산출물 활용 가능성 제시

강유진 ( Yoojin Kang ),조동진 ( Dongjin Cho ),한대현 ( Daehyeon Han ),임정호 ( Jungho Im ),임중빈 ( Joongbin Lim ),오금희 ( Kum-hui Oh ),권언혜 ( Eonhye Kwon ) 대한원격탐사학회 2021 대한원격탐사학회지 Vol.37 No.5

As part of the next-generation Compact Advanced Satellite 500 (CAS500) project, CAS500- 4 is scheduled to be launched in 2025 focusing on the remote sensing of agriculture and forestry. To obtain quantitative information on vegetation from satellite images, it is necessary to acquire surface reflectance through atmospheric correction. Thus, it is essential to develop an atmospheric correction method suitable for CAS500-4. Since the absorption and scattering characteristics in the atmosphere vary depending on the wavelength, it is needed to analyze the sensitivity of atmospheric correction parameters such as aerosol optical depth (AOD) and water vapor (WV) considering the wavelengths of CAS500-4. In addition, as CAS500-4 has only five channels (blue, green, red, red edge, and near-infrared), making it difficult to directly calculate key parameters for atmospheric correction, external parameter data should be used. Therefore, this study performed a sensitivity analysis of the key parameters (AOD, WV, and O₃) using the simulated images based on Sentinel-2 satellite data, which has similar wavelength specifications to CAS500-4, and examined the possibility of using the products of GEO-KOMPSAT-2A (GK2A) as atmospheric parameters. The sensitivity analysis showed that AOD was the most important parameter with greater sensitivity in visible channels than in the near-infrared region. In particular, since AOD change of 20% causes about a 100% error rate in the blue channel surface reflectance in forests, a highly reliable AOD is needed to obtain accurate surface reflectance. The atmospherically corrected surface reflectance based on the GK2A AOD and WV was compared with the Sentinel-2 L2A reflectance data through the separability index of the known land cover pixels. The result showed that two corrected surface reflectance had similar Seperability index (SI) values, the atmospheric corrected surface reflectance based on the GK2A AOD showed higher SI than the Sentinel-2 L2A reflectance data in short-wavelength channels. Thus, it is judged that the parameters provided by GK2A can be fully utilized for atmospheric correction of the CAS500-4. The research findings will provide a basis for atmospheric correction of the CAS500-4 in the future.