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Most-read articles are from the articles published in 2022 during the last three month.

Original Papers
Quantitative Study of Butterfly Diversity in Wando Quercus acuta Forest Over 5 Years (2017-2021)
Sanghun Lee, Na-Hyun Ahn
GEO DATA. 2023;5(2):55-59.   Published online June 20, 2023
  • 1,642 View
  • 259 Download
AbstractAbstract PDF
This study presents the long-term quantitative data on butterflies in Wando Arboretum, which represents the only warm-temperate forest located in the southernmost part of South Korea. This arboretum has significant academic value as approximately 770 species of rare woody plants or herbs, such as the Japanese evergreen oak (Quercus acuta), found in warm temperate zones grow under natural conditions here. In this project, the butterflies in this region were studied due to their sensitivity to temperature changes. The study was conducted from March-April to October-November over 5 years (2017-2021) in the region dominated by Japanese evergreen oak. We found 1,743 individuals of 47 butterfly species belonging to five families. The acquired butterfly data could serve as a reference for the further development of a network-oriented database for assessing temporal climate changes.
High-Resolution Bioclimatic Variables in Mt. Jirisan and Hallasan under Climate Change Scenario
Sanghun Lee, Seungbum Hong, Kyungeun Lee
GEO DATA. 2023;5(4):314-320.   Published online December 20, 2023
  • 468 View
  • 62 Download
AbstractAbstract PDF
Many endemic and rare species live in Korea’s subalpine zone, but there have been many research results showing that alpine creatures are disappearing due to recent climate change. Therefore, in this study, bioclimatic variables with 100 m resolution were created for Mt. Jirisan and Mt. Hallasan, representative mountainous regions in Korea. Nineteen high-resolution bioclimatic variables were created for the current and 4 future periods, and the generated data is believed to represent topographical characteristics well. This data is expected to be useful to predict potential habitats through species distribution modeling and the impact of climate change on organisms limited to alpine regions.
Data used for GIS-based Flood Susceptibility Mapping
Saro Lee, Fatemeh Rezaie
GEO DATA. 2022;4(1):1-15.   Published online March 31, 2022
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  • 87 Download
AbstractAbstract PDF
The dramatic increase in flood incidents as a significant threat to human life and property, environment, and infrastructure indicates the necessity of mapping spatial distribution of flood susceptible areas to reduce destructive effects of flooding. During the last decade, the integration of the geographic information system (GIS) with the remote sensing data provide efficient means to generate a more reliable and precise flood susceptibility map. The present study contains a review of 200 articles on the application of GIS-based methods in indicating flood vulnerable areas. The papers were reviewed in terms of influential variables, study area, and the number of articles published in the last 10 years. The review shows that the number of studies has increased since 2012. The total study areas covered 39 countries that were mostly located in Asia where the major developments and infrastructures have been constructed in the floodplains. The most common study areas was Iran (44 articles, 22%), followed by India (26 articles, 13%), China (26 articles, 11%), and Vietnam (15 articles, 7.5%). More than 90 variables were considered to map flood susceptible areas that the top 5 widely used flood conditioning factor are slope (98% of total articles), followed by elevation (92% of total articles), land use/land cover (79.5% of total articles), distance to the river (76.5% of total articles), and rainfall (73% of total articles). The review implies that many natural and anthropogenic factors affect flooding and the combination of both groups of factors is necessary to accurately detect and map flood-prone parts of the study area.
Original Papers
Construction of Exploration Data for Greenhouse Gas Geologic Storage: Focusing on Geological Cross-section Data
Bokyun Ko, Sungjae Park, Saro Lee
GEO DATA. 2023;5(3):222-229.   Published online September 26, 2023
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  • 64 Download
AbstractAbstract PDF
In this study, the most basic data, underground geological structure data, that is, geological cross-section data, were established to select a candidate site for underground storage of greenhouse gases based on AI. As a target area, the Gyeongsang Basin, where a large amount of sedimentary rocks are distributed, was selected as the greenhouse gas can be stored most effectively in sedimentary rocks. To this end, the acquisition and edit step, the refinement step, and the labeling step were carried out in the order of raw data collection, source data and labeling data construction to construct the geological cross-section data. This data can be downloaded through the AI hub site ( Menu=115&topMenu=100&aihubDataSe=realm&dataSetSn=71390) operated by the Korea Institute for Intelligent Information Society Promotion.
GeoAI Dataset for Rural Hazardous Facilities Segmentation from KOMPSAT Ortho Mosaic Imagery
Sung-Hyun Gong, Hyung-Sup Jung, Moung-Jin Lee, Kwang-Jae Lee, Kwan-Young Oh, Jae-Young Chang
GEO DATA. 2023;5(4):231-237.   Published online December 28, 2023
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  • 21 Download
AbstractAbstract PDF
In South Korea, rural areas have been recognized for their potential as sustainable spaces for the future, but they are currently facing major problems. Unplanned construction of facilities such as factories, livestock facilities, and solar panels near residential areas is destroying the rural environment and deteriorating the quality of life of residents. Detection and monitoring of rural facilities are necessary to prevent disorderly development in rural areas and to manage rural space in a planned manner. In this study, satellite imagery data was utilized to obtain information on rural areas, which is useful for observing large areas and monitoring time series changes compared to field surveys. In this study, KOMPSAT ortho-mosaic optical imagery from 2019 and 2020 were utilized to construct AI training datasets for rural hazardous facilities segmentation for Seosan, Anseong, Naju, and Geochang areas. The dataset can be used in image segmentation models to classify rural facilities and can be used to monitor potentially hazardous facilities in rural areas. It is expected to contribute to solving rural problems by serving as the basis for rural planning.
Review Paper
Global Geospatial Data for Flood and Landslide Susceptibility Mapping
Saro Lee, Rezaie Fatemeh
GEO DATA. 2023;5(4):380-393.   Published online December 28, 2023
  • 280 View
  • 47 Download
AbstractAbstract PDF
Susceptibility mapping is an important component of natural hazard risk assessment and management. Susceptibility maps for floods and landslides, which are particularly damaging to human life and property, can provide a comprehensive understanding of risk areas and factors related to flood and landslide susceptibility. To create a global flood and landslide susceptibility map, global geospatial data for 37,984 landslide and 6,682 flood locations, as well as 11 selected environmental factors were used to construct a geographic information system database. The 11 environmental factors found to influence flood and landslide occurrence were rainfall, slope, terrain position index, plane curvature, terrain wetness index, distance from rivers, land use, soil texture, soil moisture, geology, and temperature. These data were then used directly to create a global flood and landslide susceptibility map.
Original Papers
Small Unmanned Aerial Vehicle LiDAR-based High Spatial Resolution Topographic Dataset in Russell Glacier, Greenland
Yongsik Jeong, Sungjae Lee, Seung Hee Kim, Hyun-Cheol Kim
GEO DATA. 2023;5(1):1-7.   Published online March 29, 2023
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  • 121 Download
AbstractAbstract PDF
Greenland contains a large continental glacier. The influence of glacier melting has been expanding due to global warming. Although regional monitoring based on satellite data is being conducted, the demand for local/specific variation observation has increased as rising climate temperature patterns in the polar region. In this study, a precise topographic dataset was created for Greenland’s Russell glacier using a small unmanned aerial vehicle (sUAV) onboarded LiDAR sensor. A precise digital surface model (DSM) was constructed based on LiDAR data obtained at an altitude of about 100 to 200 m, and DSM resampled to a 2 m sample distance was produced to confirm its applicability by comparing before-and-after variations. This study provides DSM data applied with a pre/post-processing used for the comparison analysis.
The Study of Distribution for the Flora of Alien Species and Ecosystem Disturbing Species on Coastal Sand Dune in Chungcheong to Jeolla Region, South Korea
Seonghun Lee, Jihyun Kang, Hyun-Su Hwang
GEO DATA. 2023;5(4):262-272.   Published online December 20, 2023
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  • 26 Download
AbstractAbstract PDF
This study was conducted to provide the coastal sand dunes flora of vascular plants in Chungcheong to Jeolla region based national coastal dune natural environment survey from 2018 to 2019. In the study area, a total 631 taxa, consisting of 119 family, 372 genera, 566 species, 8 subspecies, 50 varieties, and 7 forma, were found. Among them, there were 95 taxa with 23 family, 66 genera, 99 species and 5 varieties as alien species. The number of alien species ranged from 7 to 45 on each coastal sand dune. The largest number was recorded in Sinjimyeongsa dune, while the lowest was in Namujeon dune. Moreover, ecosystem disturbing species had mainly existed on Sinhap dune. Japanese hop (Humulus japonicus) were distributed most widely on 17 coastal sand dune, and bur cucumber (Sicyos angulatus) was only found on Sinhap dune. The spatial status of flora of coastal sand dune in our data can be basic ecological information for the conservation and management of the coastal dune plant species diversity.
Dataset on the Distribution of Ecosystem-Disturbing Plants in the Republic of Korea
Man-Seok Shin, Yu Jin Hong, Sanghun Lee
GEO DATA. 2023;5(2):66-76.   Published online June 27, 2023
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  • 89 Download
AbstractAbstract PDF
In this study, we presented distribution data for 16 plant species designated as ecosystem-disturbing species by the Ministry of Environment of the Republic of Korea. These data include location information for the ecosystem-disturbing plants from four survey projects (Monitoring of invasive alien species designated by the wildlife protection act, Nationwide survey of non-native species in Korea, The 3rd and 4th national ecosystem survey) conducted by two agencies (National Institute of Ecology and National Institute of Environmental Research) between 2014 and 2021. Additionally, the data includes habitat environmental characteristics and administrative district information on the survey sites of the ecosystem-disturbing plants. These data have a high potential for utilization as basic information for natural environmental policies and related research by identifying the habitat characteristics of invasive alien species.
The Dataset of UAV Based High-resolution Tidal Topography at the Nakdong Estuary: Focusing on Jin-u Island and Shin-ja Island
Yeongjae Jang, Jingyo Lee, Joo-Hyung Ryu, Kye-Lim Kim, Hahn Chul Jung, Keunyong Kim
GEO DATA. 2022;4(1):27-36.   Published online March 31, 2022
  • 564 View
  • 29 Download
  • 1 Citations
AbstractAbstract PDF
In the tidal flats of the Nakdong Estuary, eight weirs were installed as part of the Four Major River Restoration Project in 2011, and the environment changed from a flowing stream to a still water stream. As the Nakdong River’s weir was permanently opened in February 2022, the topography and ecological environment are expected to large change. In this study, Unmanned Aerial Vehicle (UAV) photogrammetry was conducted on the tidal flats of the Nakdong Estuary in November 2021, the environment before the Nakdong River floodgates were opened. The study area was surveyed using the Network-RTK (Real-Time Kinematic) method to obtain Ground Control Point (GCP), and using an UAV, orthographic image and digital elevation model were generated for an area of 3.47 ㎢ near Jin-u island and 2.75 ㎢ near Shin-ja island. A result of spatial resolution of 1.8 cm was obtained, the result was verified using checkpoints, and results with accuracy exceeding 1 cm were obtained in both Sin-u Island and Jin-woo Island. In the future, changes in the topography and sedimentation environment of this area are expected, so it will be useful data for various research and conservation management.


Citations to this article as recorded by  
  • Influence of Precipitation Conditions and Discharge Rates of River Estuary Barrages on Geomorphological Changes in an Estuarine Area
    Sung-Bo Kim, Doo-Pyo Kim
    Applied Sciences.2023; 13(17): 9661.     CrossRef
Distribution characteristics of invasive alien amphibians and reptiles in Korean
HeeNam Yoon, YongKi Kim, ManSeok Shin
GEO DATA. 2022;4(4):20-27.   Published online December 31, 2022
  • 725 View
  • 44 Download
AbstractAbstract PDF
This study analyzed the distribution and habitat status of 1 species of amphibian and 4 species in 1 genus of reptiles among “ecosystem-disturbing species” designated by the Ministry of Environment through the National Habitat Survey of Alien Species (2015-2021). As a result, Rana catesbeiana with 415 sites, Trachemys spp. with 513 sites, Pseudemys concinna with 174 sites, Pseudemys nelsoni with 66 sites, and Mauremys sinensis with 31 sites. Of the total habitat area of R. catesbeiana, the agricultural land area accounted for 46% and the used(urbanized/dry) area accounted for 15%. Of the total habitat area of T. spp, the ratio of agricultural land areas was 35%, and the ratio of used areas was 24%. These species were found to live mainly in reservoir areas with higher natural characteristics than in urbanized and dry areas. However, M. sinensis, which were introduced in early 2000 and have a small number of habitats, mainly inhabited agricultural land areas with high naturalness, with agricultural land areas accounting for 43% and used areas accounting for 29% of the total habitat area. Accordingly, a detailed study on the ecology and artificial release of the M. sinensis is needed.
Original Papers
Development of Machine Learning Algorithms for Riverside Land Cover Classification Using Synthetic Aperture Radar Satellite Imagery and Terrain Data
Jaese Lee, Dukwon Bae, Young Jun Kim, Jungho Im
GEO DATA. 2023;5(3):119-125.   Published online September 25, 2023
  • 552 View
  • 60 Download
AbstractAbstract PDF
Riverine environments play a crucial role in maintaining the stability of river ecosystems as well as biodiversity. Furthermore, the appropriate management of small rivers has a significant impact not only on stable water supplies but also on water resource management. Wide monitoring of the riverside environment including land covers and their changes is an important issue in water resource management. This study aims to develop a high-resolution (10 m) model for classifying riverside land cover by integrating Sentinel-1 synthetic aperture radar (SAR) data and terrestrial characteristics using machine learning algorithms. We constructed a total of 3,284 landcover reference point datasets near the four major rivers of South Korea with five classes: water, barren, grass, forest, and built-up. The Random Forest and Light Gradient Boosting Machine classification models were developed using eight input variables derived from SAR signal and digital terrain data. The models showed an overall cross-validation accuracy exceeding 80% while maintaining consistent spatial distributions, except for the barren class. The false alarms on barren would be corrected through additional sampling processes and incorporating optical characteristics in further study. The high-resolution riverside land cover maps are expected to contribute to the establishment of a comprehensive management system for water resources such as riverside land cover change detection, river ecosystem monitoring, and flood hazard management. Furthermore, the utilization of the next generation medium satellite 5 (C-band SAR) would improve the performance of riverside land cover classification algorithm in the future.
The Cheonji Lake GeoAI Dataset Based in Synthetic Aperture Radar Images: TerraSAR-X, Sentinel-1 and ALOS PALSAR-2
Eu-Ru Lee, Ha-Seong Lee, Ji-Min Lee, Sun-Cheon Park, Hyung-Sup Jung
GEO DATA. 2023;5(4):251-261.   Published online December 29, 2023
  • 235 View
  • 23 Download
AbstractAbstract PDF
The fluctuations in the area and level of Cheonji in Baekdu Mountain have been employed as significant indicators of volcanic activity. Monitoring these changes directly in the field is challenging because of the geographical and spatial features of Baekdu Mountain. Therefore, remote sensing technology is crucial. Synthetic aperture radar utilizes high-transmittance microwaves to directly emit and detect the backscattering from objects. This weatherproof approach allows monitoring in every climate. Additionally, it can accurately differentiate between water bodies and land based on their distinct roughness and permittivity characteristics. Therefore, satellite radar is highly suitable for monitoring the water area of Cheonji. The existing algorithms for classifying water bodies using satellite radar images are significantly impacted by speckle noise and shadows, resulting in frequent misclassification. Deep learning techniques are being utilized in algorithms to accurately compute the area and boundary of interest in an image, surpassing the capabilities of previous algorithms. This study involved the creation of an AI dataset specifically designed for detecting water bodies in Cheonji. The dataset was constructed using satellite radar images from TerraSAR-X, Sentinel-1, and ALOS-2 PALSAR-2. The primary objective was to accurately detect the area and level of water bodies. Applying the dataset of this study to deep learning techniques for ongoing monitoring of the water bodies and water levels of Cheonji is anticipated to significantly contribute to a systematic method for monitoring and forecasting volcanic activity in Baekdu Mountain.
A Study on the Development of Biotope Type and Evaluation Map of Gochang-gun
Jeong-Cheol Kim, Chang-Hoon You, Dong-Wook Kim, WooSeok Oh
GEO DATA. 2023;5(4):277-285.   Published online December 20, 2023
  • 226 View
  • 9 Download
AbstractAbstract PDF
Gochang-gun, situated in Korea, has achieved the distinction of being the second city in the country to have all three UNESCO-designated natural environmentrelated World Heritage Sites, following in the footsteps of Jeju Island. UNESCO has conferred upon Gochang-gun the prestigious designations of a biosphere reserve, World Natural Heritage (Gochang-Buan mudflat), and World Geopark (Jeonbuk West Coast Geopark). Notably, the entire administrative district has been designated as a UNESCO Biosphere Reserve, signifying its role as a meticulously preserved region of outstanding natural beauty and ecological significance. Within this UNESCO Biosphere Reserve, the core areas encompass remarkable features, including the Gochang-Buan Mudflat, Ungok Wetland, Dolmen World Cultural Heritage sites, Seonunsan Provincial Park, and Dongrim Reservoir. In pursuit of a comprehensive ecological map of Gochang-gun, the National Institute of Ecology (NIE) conducted an extensive two-year ecological survey and biotope survey from 2021 to 2022. Ecological spatial data was meticulously compiled based on the results of these surveys. The resulting Biotope map provides detailed information on various attributes, encompassing Biotope types, Biotope grades, land cover status, land use status, and topographic details. This dataset is formally registered and rigorously managed, employing the Digital Object Identifier (DOI) system. The primary aim of this paper is to provide a comprehensive introduction to each attribute of the Gochang-gun Biotope map, which represents a detailed collection of spatial ecology data for the region. The intent is to make this data readily accessible for future research and studies, thereby advancing our understanding of Gochang-gun’s distinctive ecological and cultural heritage.
Meteorological and Sea Surface Water Measurement Data from Icebreaker Research Vessel ARAON for 2020-2021 Arctic Research Expeditions
Sungjae Lee, Hyun-Cheol Kim, Dongseob Shin, Suhwan Kim, HyunGyu Choi
GEO DATA. 2023;5(1):26-33.   Published online March 28, 2023
  • 776 View
  • 23 Download
AbstractAbstract PDF
Since its construction in 2010, the icebreaker ARAON has been conducting regular polar field surveys to observe changes in the atmosphere and marine environment in polar regions. The Arctic Ocean, a major research area, is directly affected by changes in the ocean, atmosphere and energy circulation system due to the continuous decrease in sea ice. During the Arctic summer season, when sea ice becomes smaller and thinner, the ARAON passes through East Sea, Bering Sea, Chukchi Sea, and Beaufort Sea to investigate the marine environment on the high latitude high seas. The Arctic Ocean is important not only for scientific research due to climate change, but also for economic research such as undersea energy, mineral resources, and Northern Sea route. However, it is difficult to access the Arctic and conduct long-term and continuous field surveys. ARAON carries out Arctic research voyages using various research equipment, and the most basic observation among them is meteorological information and sea water observation data. Weather data include solar radiation, atmospheric temperature, humidity, wind speed and wind direction, and seawater observations include sea water temperature, salinity, conductivity and fluorescence substances. In addition, three-dimensional location information of the research line was obtained. The data will be used as inspection data for satellite data and polar field survey data.