GEO DATA

Volume 6(3); September 2024

Detailed Information for This Issue

Data Articles

Distribution Status for the Plants of Alien Species on the Baekdudaegan Protected Area, South Korea: Hyungsoo Seo, Hyun-Su Hwang, Hyun-Chul Shin, Daeun Kim, Donghui Choi, Youngjun Park; GEO DATA. 2024;6(3):101-109. Published online September 30, 2024; DOI: https://doi.org/10.22761/GD.2024.0019

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Abstract PDF: This study was conducted to provide information on alien species to the Baekdudaegan Protected Area eco-survey by Ministry of Environment in South Korea from 2015 to 2019. The scope of the survey is based on data from 26 subsections out of 44 subsections in five regions, excluding Korea National Park. In the study area, a total 58 taxa, consisting of 16 family, 48 genera, 56 species, two varieties were found. In addition, five species of ecosystem-disturbing species were identified that Ambrosia artemisiifolia, Aster pilosus, Rumex acetosella, Solanum carolinense, Humulus japonicus. However, the habitat of ecosystem-disturbing species could not be confirmed in the subsections of Dakmokjae-Kubusiryeong (designated number, 13-20), Gisdaebaegibong-Doraegijae (designated number, 23, 24), Ihwaryeong-Haneuljae (designated number, 33), and Neuljae-Miljae (designated number, 37). The spatial status of alien flora on the Baekdudaegan Protected Area monitored by Ministry of Environment in our data can be basic ecological information for the conservation and management of plant species diversity on it.

Fish Diversity of East Sea Streams in Nakdong River Region: Jeong Ho Hwang, Jong-Hak Yun; GEO DATA. 2024;6(3):110-122. Published online September 30, 2024; DOI: https://doi.org/10.22761/GD.2024.0020

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Abstract PDF: Fish surveys were conducted near artificial structures installed in eight streams flowing from the Nakdong River region to the east coast of Korea. As a result of the survey, a total of 20,000 individuals belonging to nine orders, 17 families, and 47 species were found. The dominant species was Zacco koreanus, and the subdominant species was Pungtungia herzi. Among the surveyed fish species, endangered species were Pseudobagrus brevicorpus (rank I) and Cottus hangiongensis (rank II). In addition, migratory fish species were Oncorhynchus keta, Plecoglossus altivelis, and Tribolodon hakonensis. As a result of community analysis, the highest diversity, dominance, richness, and evenness indices were Wangpi, Chuksan, Gokgang, and Janggi Stream respectively. The highest number of species was surveyed in Gokgang Stream (25 species). Alpha diversity, the number of species at each survey point in each stream, was the highest at a survey point in Wangpi Stream (20 species), and beta diversity, species at each stream survey point that does not overlap with nearby survey point, was the highest at survey points in Gokgang Stream (12 species). As a result of the similarity analysis, surveyed streams were divided into four groups: group 1 (Chuksan, Baeknok Stream), group 2 (Uljinnamdae, Wangpi, Yungdeokosip Steam), group 3 (Gokgang Stream), and group 4 (Janggi, Hoeya Stream). This study is expected to serve as basic data for managing the aquatic ecosystem of streams flowing from the Nakdong River region to the east coast.

Occurrences Status of Biota in Gochang-gun, South Korea: Dong-Uk Kim, Jeong-Cheol Kim, Chang-Hoon You, WooSeok Oh; GEO DATA. 2024;6(3):123-143. Published online September 30, 2024; DOI: https://doi.org/10.22761/GD.2024.0015

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Abstract PDF: The Gochang-gun biotope map was used as a benchmarking model when preparing a county unit in the future, and was prepared for the purpose of constructing detailed spatial data for eco-friendly urban management and efficient management and value improvement of cultural assets. The purpose of this study is to provide data so that it is used as basic data for the distribution status of animals and plants and the systematic management of endangered wild animals. As a result of the survey of animals and plants in Gochang-gun, a total of 255 species of 88 families and 184 genera appeared. A total of eight families and 14 species of mammals appeared. A total of 32 families and 52 species of birds appeared. A total of nine and 26 species of fish appeared, and five species endemic to Korea appeared. Six and seven species of amphibians and reptiles appeared, respectively, and one species of exotic specices appeared. A total of 26 species of benthic large-scale vertebrates appeared, and three species endemic to Korea appeared. As for endangered wild creatures, two species of plants, six species of birds and three species of mammals appeared. It is judged that the data on animals and plants based on the urban ecological status map of Gochang-gun can be used as basic data for environmental policy decisions such as the management of ecosystem disturbances in Gochang-gun, the protection of endangered wild creatures, and the protection and restoration of plant and plant habitats.

Pest Control and Safety Management Monitoring in Outdoor Plantation Using Unmanned Aerial Vehicle Captured Images: Sung Min Han, Kyong-Hee Nam; GEO DATA. 2024;6(3):144-149. Published online September 27, 2024; DOI: https://doi.org/10.22761/GD.2024.0023

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Abstract PDF: The National Institute of Ecology in Seocheon, Chungcheongnam-do, exhibits and studies Korea’s diverse ecosystems to communicate the importance of biodiversity conservation to the general public. The site faces the challenge of preserving the natural environment while ensuring visitor convenience. This requires systematic data collection to quickly detect and respond to threats from pests and natural disasters. In this study, high-resolution orthoimages were acquired to monitor ecological changes using unmanned aerial vehicles. Images were captured through flights monthly from March to July 2024. Digital elevation models and orthoimages were generated to identify dead trees and assess areas of damage caused by heavy rainfall. The study covered an area of 998,655 m2, and the image resolution was 3.6 cm/pixel. The orthophotos were useful in identifying plant pest damage. They also helped evaluate damage caused by rain, showing that the total area of damage was 29,384 m2, mainly due to soil erosion. Furthermore, it is expected that the accumulation of such unmanned remote sensing image data can also be applied to the safety management of various natural conservation areas and public facilities.

A Dataset for Species Distribution Modelling of Mangroves in Vietnam: Based on the National Forest Inventory Monitoring: Sungsoo Yoon, Nguyen Duy Liem, Le Hoang Tu, Nguyen Kim Loi; GEO DATA. 2024;6(3):150-158. Published online September 30, 2024; DOI: https://doi.org/10.22761/GD.2024.0022

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Abstract PDF: Mangroves provides essential ecosystem services such as protection of coastal areas, carbon sequestration, and habitat provision for diverse species in coastal ecosystems. Species distribution models (SDMs) are powerful tools for predicting the potential distribution of mangrove species, which support impact assessments of climate changes on biodiversity and ecological functions of mangrove ecosystems. A comprehensive dataset for mangrove occurrence information derived from the Forest Inventory Map of Vietnam was designed to facilitate the building and projection of SDMs. The prediction data designed for training SDMs integrates ecological information including 701 field survey-based mangrove occurrences at the genus level and 21 environmental variables such as bioclimatic variables, digital elevation model and soil properties with 1 km spatial resolution. The projection data for provide sets of predictors aligned with four shared socioeconomic pathways scenarios representing two future periods to support the projection of SDM results under future climate conditions in Vietnam. This dataset serves as a valuable ecological information resource, enabling the modeling and predicting of potential mangrove habitats and distributions for the protection and restoration of mangroves in Vietnam under changing environmental conditions.

Study on Grain Size, Physical Properties and Organic Matter Characteristics of Tidal Flat Surface Sediments: May 2022 Hwangdo Tidal Flat Dataset, Cheonsu Bay: Jun-Ho Lee, Hoi-Soo Jung, Huigyeong Ryu, Keunyong Kim, Joo-Hyung Ryu, Yeongjae Jang; GEO DATA. 2024;6(3):159-174. Published online September 30, 2024; DOI: https://doi.org/10.22761/GD.2024.0011

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Abstract PDF: This study analyzes the geological and geochemical features of surface sediments in the Hwangdo Tidal Flat, located on Korea’s West Coast. The tidal flat experiences semi-diurnal tides, impacting organic matter decomposition and nutrient cycling. Ninety one sediment samples were collected and analyzed for physical and chemical properties including grain size, density, water content, organic carbon, and nitrogen. Sediments consist mainly of sand and silt, with coarser sediments near the main channel and finer sediments towards the west. Sediment grain size averages 4.12 Φ with a sorting coefficient of 1.96 Φ, indicating diverse energy environments. Total organic carbon and nitrogen correlate positively with grain size and density, reflecting sediment origin and environment. Kriging maps sediment grain size distribution, while correlation and linear regression analyses show relationships between variables. High correlations exist between various parameters, aligning with tidal flat characteristics and aiding understanding of sediment transport and deposition. The study provides baseline data for understanding the tidal flat’s geological, geochemical, and physical aspects, valuable for remote sensing validation and environmental monitoring. The dataset is freely available for research and management purposes.

Dataset for Deep Learning-based GEMS Asian Dust Detection: Jin-Woo Yu, Che-Won Park, Won-Jin Lee, Yong-Mi Lee, Yu-Ha Kim, Hyung-Sup Jung; GEO DATA. 2024;6(3):175-185. Published online September 27, 2024; DOI: https://doi.org/10.22761/GD.2023.0049

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Abstract PDF: In South Korea, Asian dust frequently occurs during the spring, causing various health issues, including respiratory diseases. Consequently, public awareness and concern about air pollutants have increased, leading to demands for improved air quality and accurate forecasting. To meet these demands, the Ministry of Environment has deployed the Geostationary Environment Monitoring Spectrometer (GEMS) on the GK2B satellite to monitor atmospheric pollutants and climate change-inducing substances in real-time. The current GEMS dust product, generated using thresholds of the UV-aerosol index and visible-aerosol index, has shown limitations in accurately detecting suspended particulate matter. This study aims to develop a comprehensive AI dataset for improving GEMS Asian dust detection. Data were collected from January to May 2021, focusing on dates with significant dust events. Label data were meticulously generated through annotations based on outputs from various satellites and groundbased observations. Subsequent data preprocessing and augmentation techniques, including normalization and cut-mix, were applied to enhance the dataset’s robustness and generalizability. To evaluate the dataset, model training was conducted. The results predicted by the model showed improvements over the detection results of existing algorithms. Future datasets will be developed with improved labeling methods and accuracy verification techniques. These dataset improvements are expected to contribute to the development of deep learning models with superior predictive performance compared to current dust detection algorithms.

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