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

Original Papers
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
DOI: https://doi.org/10.22761/GD.2023.0054
  • 816 View
  • 52 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.
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
DOI: https://doi.org/10.22761/GD.2023.0010
  • 2,135 View
  • 367 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
DOI: https://doi.org/10.22761/GD.2023.0039
  • 725 View
  • 79 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.
Article
UAV Photogrammetry and LiDAR Based Dataset of Spartina anglica Distribution and High-resolution Topographic Map in Ganghwado
Keunyong Kim, Yeongjae Jang, Jingyo Lee, Joo-Hyung Ryu
GEO DATA. 2022;4(2):1-8.   Published online June 30, 2022
DOI: https://doi.org/10.22761/DJ2022.4.2.001
  • 694 View
  • 52 Download
  • 1 Citations
AbstractAbstract PDF
The Spartina anglica in the tidal flat at the southern part of Ganghwado, it is known that the distribution area has gradually expanded since it was officially announced as invasive alien species in 2015. The government and local governments are continuing their efforts to remove the S. anglica, and for this, continuous distribution change monitoring is required. This study extracted the data of distribution and extent area of S. anglica from Zenmuse P1 sensor, and generated the high-resolution Digital Elevation Model (DEM) from Zenmuse L1 sensor. Optical and Lidar images were photographed at an altitude of 70 m, and Ground Sampling Distance (GSD) of optical images was obtained at 0.9 cm and GSD of lidar images at 5 cm spatial resolution. However, the data are resampled and provided in GSD 25 cm to comply with the "National Spatial Information Security Management Regulations of the Ministry of Land, Infrastructure and Transport" and "Security Business Regulations of the National Intelligence Service".

Citations

Citations to this article as recorded by  
  • Spartina anglica-Derived Carbon-Coated PE Separator for Physically Restraining Polysulfide Migration in Lithium-Sulfur Batteries
    Ye Jin Jeon, Yuna Ha, Jang Kyun Kim, Youn-Jung Kim, Taeeun Yim
    Korean Journal of Chemical Engineering.2024; 41(4): 1187.     CrossRef
Original Paper
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
DOI: https://doi.org/10.22761/GD.2023.0031
  • 494 View
  • 37 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.
Erratum
Erratum to: Detailed Bathymetry and Seafloor Backscatter Image Dataset for Monitoring Ecosystem Environment: Southern Ulleungdo
Soon Young Choi, Chang Hwan Kim, Won Hyuck Kim, Chan Hong Park
GEO DATA. 2024;6(1):43-43.   Published online February 1, 2024
DOI: https://doi.org/10.22761/GD.2024.e001
Corrects: GEO DATA 2023;5(4):364
  • 380 View
  • 10 Download
PDF
Original Papers
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
DOI: https://doi.org/10.22761/GD.2023.0056
  • 478 View
  • 29 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
DOI: https://doi.org/10.22761/GD.2023.0034
  • 433 View
  • 11 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.
GeoAI Dataset for Industrial Park and Quarry Classification from KOMPSAT-3/3A Optical Satellite Imagery
Che-Won Park, Hyung-Sup Jung, Won-Jin Lee, Kwang-Jae Lee, Kwan-Young Oh, Jae-Young Chang, Moung-jin Lee, Geun-Hyouk Han, Il-Hoon Choi
GEO DATA. 2023;5(4):238-243.   Published online December 28, 2023
DOI: https://doi.org/10.22761/GD.2023.0052
  • 425 View
  • 41 Download
AbstractAbstract PDF
Air pollution is a serious problem in the world, and it is necessary to monitor air pollution emission sources in other neighboring countries to respond to the problem of air pollution spreading across borders. In this study, we utilized domestic and international optical images from KOMPSAT-3/3A satellites to build an AI training dataset for classifying industrial parks and quarries, which are representative sources of air pollution emissions. The data can be used to identify the distribution of air pollution emission sources located at home and abroad along with various state-of-the-art models in the image segmentation field, and is expected to contribute to the preservation of Korea’s air environment as a basis for establishing air-related policies.
Review
Data used for GIS-based Flood Susceptibility Mapping
Saro Lee, Fatemeh Rezaie
GEO DATA. 2022;4(1):1-15.   Published online March 31, 2022
DOI: https://doi.org/10.22761/DJ2022.4.1.001
  • 943 View
  • 92 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
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
DOI: https://doi.org/10.22761/GD.2023.0006
  • 1,531 View
  • 129 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.
Evaluating the Longitudinal Connectivity of Dorim Stream in Seoul based on Artificial Constructure and Fish Data
Jeong Ho Hwang, Myeong-Hun Ko, Sungmin Jung, Jong-Hak Yun
GEO DATA. 2023;5(4):286-297.   Published online December 27, 2023
DOI: https://doi.org/10.22761/GD.2023.0040
  • 394 View
  • 10 Download
AbstractAbstract PDF
The vertical connectivity of the river aquatic ecosystem was evaluated based on fish and artificial structures in Dorim stream, an urban stream in Seoul. As a result of a survey in the downstream area in 100.0 m of a total of 71 artificial structures, 13,728 individuals of fishes belonging to five orders, seven families, and 25 species were investigated, with the dominant species Zacco platypus and the subdominant species Rhynchocypris oxycephalus. As for endemic species, seven species were investigated and in terms of feeding characteristics, omnivorous species were the most common with 17 species (68%). Also an alien species, Poecilia reticulata was found. Fish species tended to decrease as the survey was conducted to upstream. Based on the movement characteristics of the fish species and the features of artificial structure survey results, the longitudinal continuity of each artificial structure was evaluated as 43 continuity, two damaged, 19 discontinuity, and seven absent. In inclined structures, stream velocity was found to be the main factor for discontinuity. In vertical structures, the down depth and head drop appeared to be the main factors for discontinuity. The results of this survey are expected to serve as basic data for the conservation of river aquatic ecosystems in the future.
Article
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
DOI: https://doi.org/10.22761/DJ2022.4.1.003
  • 745 View
  • 30 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

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
Original Papers
GeoAI Dataset for Training Deep Learning-Based Optical Satellite Image Matching Model
Jin-Woo Yu, Che-Won Park, Hyung-Sup Jung
GEO DATA. 2023;5(4):244-250.   Published online December 28, 2023
DOI: https://doi.org/10.22761/GD.2023.0048
  • 409 View
  • 24 Download
AbstractAbstract PDF
Satellite imagery is being used to monitor the Earth, as it allows for the continuous provision of multi-temporal observations with consistent quality. To analyze time series remote sensing data with high accuracy, the process of image registration must be conducted beforehand. Image registration techniques are mainly divided into region-based registration and feature-based registration, and both techniques extract the same points based on the similarity of spectral characteristics and object shapes between master and slave images. In addition, recently, deep learning-based siamese neural network and convolutional neural network models have been utilized to match images. This has high performance compared to previous non-deep learning algorithms, but a very large amount of data is required to train a deep learning-based image registration model. In this study, we aim to generate a dataset for training a deep learning-based optical image registration model. To build the data, we acquired Satellite Side-Looking (S2Looking) data, an open dataset, and performed preprocessing and data augmentation on the data to create input data. After that, we added offsets to the X and Y directions between the master and slave images to create label data. The preprocessed input data and labeled data were used to build a dataset suitable for image registration. The data is expected to be useful for training deep learning-based satellite image registration models.
Investigation of Wildlife Crossing Structures in South Korea
Euigeun Song, Sooahn Heo, Il Ryong Kim, Sehee Kim, Hanbi Lee
GEO DATA. 2023;5(4):273-276.   Published online December 22, 2023
DOI: https://doi.org/10.22761/GD.2023.0041
  • 383 View
  • 31 Download
AbstractAbstract PDF
Roads, railways and infrastructure are constructed with consideration of their environmental impacts, especially habitat fragmentation. Wildlife crossing structures increase the permeability of roads and other linear infrastructures for wildlife by allowing animals to safely cross under or over roads and by reducing the risk of wildlife-vehicle collosions. We investigated the location and type of 564 wildlife crossing structures in South Korea. Between April and October 2023, we identified 365 overpasses and 199 underpasses of wildlife crossing structures respectively. Gyeonggi-do and Gyeongsangbuk-do had the largest number of wildlife crossing structures. This study can provide basic information for the effective management of wildlife crossing structures.

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