GEO DATA

Ground-based data from wheat cropping fields in Australia for development of soil moisture retrieval algorithm using satellite images: SeungJae Lee, SunGu Lee, Dongryeol Ryu; GEO DATA. 2020;2(2):1-4. Published online December 30, 2020; DOI: https://doi.org/10.22761/DJ2020.2.2.001

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Abstract PDF: Soil moisture is an important data which can be used for crop growth estimation, drought prediction, irrigation, and development of hydrological model. However, it is difficult to obtain soil moisture data from inaccessible area or very large area using only general field campaign. For this reason, many soil moisture retrieval algorithms have been developed based on satellite remote sensing technique. It should be noted that both satellite images and ground-based data for the region of interest are required to effectively develop the soil moisture retrieval algorithm using satellite images. Thus, Korea aerospace research institute, KARI, have collected ground-based data containing soil moisture, soil temperature, and crop height in collaboration with the university of Melbourne from wheat cropping fields in Australia which are suitable for the development of soil moisture retrieval algorithm. The ground-based data was collected from wheat cropping fields containing various types of soils for about 7 months from May 2019 to November 2019.

Above water remote sensing reflectance dataset on the coastal waters of California and Korea: Jee-Eun Min, Jeong-Eon Moon, Jong-Kuk Choi, Liane Guild, Joo-Hyung Ryu; GEO DATA. 2020;2(2):5-13. Published online December 30, 2020; DOI: https://doi.org/10.22761/DJ2020.2.2.002

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Abstract PDF: Remote sensing reflectance (R_rs) is a fundamental data of ocean color remote sensing that is used as an input data for algorithm development. In this study, the Rrs spectra acquired from the coast of Korea and California, on the opposite side of the Pacific Ocean, were analyzed and compared. The waters of Gyeonggi Bay and Mokpo had a similar spectrum to those of the waters inside of the San Francisco Bay, although the waters of each region had different characteristics. The South Sea in Korea showed similar spectral characteristics on the waters of Monterey Bay and outside of the San Francisco Bay in California. The upward slope of the Rrs spectra in the range of 400 to 600 nm obtained from the inside of the San Francisco Bay was higher than the coastal waters on the Gyeonggi Bay and Mokpo in Korea. The Rrs spectra showing peaks on 580 nm and 680 ~ 700 nm due to chlorophyll were similarly observed in the South and East Seas of Korea, and the coastal waters of Monterey Bay and the outside of the San Francisco Bay in California.

Barn Swallow (Hirundo rustica) Breeding Ground Temperature and Relative Humidity data in Sejong City and Seocheon County: Sung hoon Choi, Seon-Deok Jin, Tae Han Kang, Hong-Shik OH; GEO DATA. 2020;2(2):14-17. Published online December 30, 2020; DOI: https://doi.org/10.22761/DJ2020.2.2.003

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Abstract PDF: This study was conducted on the barn swallows that share habitats with humans, and the effect of changes in temperature and relative humidity, an important environmental factor for bird breeding, on swallow breeding was examined in Sejong City and Seocheon County. Barn swallows in both regions arrived from the end of April to the middle of June, and there was no big difference between the regions. In the average, maximum, and minimum temperatures at the time of arrival, there were no significant differences between the regions. The incubation period was confirmed twice. From 1 May to 20 May, the first incubation period the average temperature in the two regions was 17.3 to 18 ℃, and both the maximum and minimum temperatures were similar. The average temperature was 20.0 ℃ in Seocheon, 22.8 ℃ in Sejong, the maximum temperature was 26.9 ℃, and minimum temperature was 16.7 ℃. The brooding period in the two regions was 23.6~30.7 days on average, which was 7.1 days longer in Seocheon, and the average temperature, maximum temperature, and minimum temperature were similar.

Topographic dataset of Gomso bay tidal flat: Deuk Jae Hwang, Kye Lim Kim, Yoon Kyung Lee, Jun-Ho Lee, Han Jun Woo, Joo Hyung Ryu; GEO DATA. 2020;2(2):18-25. Published online December 30, 2020; DOI: https://doi.org/10.22761/DJ2020.2.2.004

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Gomso bay tidal flat is influenced by human activity, such as Saemangeum dyke construction, Southwest sea offshore wind power plant construction, and reclamation. To observe continuous change of tidal flat topography, topographic change observation was carried out from Oct. 1991 to Oct. 2016. Gomso bay is located between latitude 35.5°N to 35.6°N and longitude 124.4°E to 126.7°E and elevation is measured at three transect located at tidal flat of outer bay, middle bay, and inner bay, respectively. RTK-GPS (Real time kinetic global positioning system) and sedimentation plate are used to measure elevation change of each transect. Line KM, which is located at outer bay tidal flat nearby Mandol-ri, has approximately 2 km distance from shoreline to lower intertidal zone and elevation is measured at 22 stations with RTK-GPS and sedimentation rate is measured at 10 stations with sedimentation plate. Line KH, which is located at middle bay tidal flat nearby Hajeon-ri, has approximately 5 km distance, and 50 stations and 20 stations are measured by RTK-GPS and sedimentation plate. Line KB, which has 1 km distance, approximately, and 10 stations and 9 stations are measured by RTK-GPS and sedimentation plate. Long term elevation change data is expected to predict long term elevation measurement data.

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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. CrossRef
A Geological Environment Characteristics Dataset of Tidal Flat Surface Sediments: A 2021 Pilot Study of the Gomso Bay Tidal Flat Area to Use of Sediment Type Data
Kyoungkyu Park, Han Jun Woo, Hoi-Soo Jung, Joo Bong Jeong, Joo-Hyung Ryu, Jun-Ho Lee
GEO DATA.2022; 4(2): 9. CrossRef

The Dataset of Sedimentary Environments at Hwangdo Tidal Flat on the Western Coast of Korea (2004 to 2013): Kye-Lim Kim, Jong-Kuk Choi, Joo-Hyung Ryu; GEO DATA. 2020;2(2):26-35. Published online December 30, 2020; DOI: https://doi.org/10.22761/DJ2020.2.2.005

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Abstract PDF: The Hwangdo tidal flat has been subjected to local hydrodynamic changes caused by the construction of seawalls and bridges, which are changing the distribution of sediments and topographic characteristics. These changes would affect the sedimentary environments. It is essential to establish sedimentary environments dataset such as sediment distributions and elevation in order to understand the sedimentary environments and the pattern of change in the tidal flat. Therefore, between 2004 and 2013, data on sedimentary environmental factors such as surface sedimentary facies and elevation were obtained through the field survey, and soil moisture content of each sediment was measured to analysis the correlation between seawater and optical reflectance in the tidal flat. As a result, 12 sedimentary facies were distributed in the Hwangdo tidal flat, and the sand content and elevation gradually increased between 2004 and 2013. It was also shown that the amount of seawater present in the surface decreased as elevation and grain size increased. These data will be useful for understanding the changes in the sedimentary environments and for establishing plans for change and conservation management in Hwangdo tidal flat.

Construction of Topographic/Hydrologic Data using DEM and Its Service: Saro Lee, Minji Kim; GEO DATA. 2020;2(2):36-44. Published online December 30, 2020; DOI: https://doi.org/10.22761/DJ2020.2.2.006

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In this study, 10 types of terrain analysis maps and 10 types of hydrology analysis maps were constructed through various topographic/hydrological analysis using a digital topographic model (DEM). The construction range is for the entire South Korea, the resolution is 30m, and the coordinate system is UTM-K coordinates. The constructed data format is provided in three formats: ASCII, ARCGIS GRID, and GEOTIFF. In addition, all data is provided in the form of the above three data format for whole of South Korea and each administrative district. All of these topographic/hydrological analysis data can be downloaded for free from the environment big data platform (www.bigdata-environment.kr).

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Predictors of Unilateral Arm Lymphedema in Non-obese Locoregionally Advanced Breast Cancer Patients Undergoing Neoadjuvant Chemotherapy, Modified Radical Mastectomy, and Postoperative Irradiation
Surjeet Dwivedi, Amiy Arnav, Varun Kumar Agarwal, S K Deshpande, Rohit Sharma, Naresh Saidha
European Journal of Breast Health.2024; 20(2): 149. CrossRef
Need for Staging Investigations in Newly Diagnosed Breast Cancer: Establishing Local Guidelines for Radiological Staging in Bahrain
Ahmed Adel Alkazaz, Noora Fuad Ali, Ahmed Zuhair Salman, Sayed Ali Almahari, Tareq Hamed Altaei, Wegdan Zaki Albati, Hisham Mustafa Habib, Aysha Adnan Alsadoon, Noor Ali Almawlani, Fatema Ali Alkhabbaz, Raja Eid, Hussain Adnan Abdulla
European Journal of Breast Health.2024; 20(2): 136. CrossRef
Wildfire susceptibility mapping by incorporating damage proxy maps, differenced normalized burn Ratio, and deep learning algorithms based on sentinel-1/2 data: a case study on Maui Island, Hawaii
Suci Ramayanti, BongChan Kim, Sungjae Park, Chang-Wook Lee
GIScience & Remote Sensing.2024;[Epub] CrossRef
Construction of Topographic/Hydrologic Data using DEM and its Service 2
Saro Lee, Minju Kim
GEO DATA.2021; 3(4): 1. CrossRef

Construction of Analyzed Satellite Image and Service: Won-Kyung Baek, Sung-Hwan Park, Jin-Woo Yu, Young-Woong Yoon, Hyung-Sup Jung; GEO DATA. 2020;2(2):45-55. Published online December 30, 2020; DOI: https://doi.org/10.22761/DJ2020.2.2.007

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In this study, 17 types of satellite analysis maps were generated using Landsat-8 and Sentinel-2 satellite images acquired at 2019 and 2020. Totally, 68 of satellite analysis data were produced. The scope of deployment is South Korea as a whole, with a resolution of 30 meters, and the coordinate system is UTM-K coordinates. The established data will be provided in both South Korean and regional data respectively. In addition, it is provided by three data format: ASCII, ArcGIS Grid, and GeoTIFF for enhancing accessibility of the data. All these satellite analysis data can be downloaded free of charge from the Environmental Big Data website (www.bigdata-environment.kr), an environmental business big data platform.

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Expand and Renewal of Analyzed Satellite Image and Service
Young-Woong Yoon, Che-Won Park, Sung-Hyun Gong, Won-Kyung Baek, Hyung-Sup Jung
GEO DATA.2021; 3(4): 32. CrossRef

AI Training Dataset for Cloud Detection of KOMPSAT Images: Bo-Ram Kim, Han Oh; GEO DATA. 2020;2(2):56-62. Published online December 30, 2020; DOI: https://doi.org/10.22761/DJ2020.2.2.008

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Clouds that appear inevitably when acquiring optical satellite images hinder the interpretation of surface information, so removing them is a crucial procedure to increase the utilization of satellite images. Currently, for KOMPSAT (Korea Multi-purpose Satellite) images, only the cloud amount by visual measurement is proved for the entire scene and detailed cloud masks are not provided. Since cloud detection is a time-consuming task, we built a cloud dataset for KOMPSAT images so as to develop an algorithm that expedites the task with state-of-the-art artificial intelligent techniques. In the dataset, satellite images were selected from various regions considering that clouds have different characteristics depending on the region, and masks were classified into thin clouds, thick clouds, cloud shadows, and clear sky. The size of dataset is over 4,000 image/mask pairs by an image size of 1000x1000 and one of the largest among publicly available cloud datasets, as of this writing. The dataset is built by a government AI (artificial intelligent) training dataset building program and will be available through the website, aihub.or.kr.

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Cloud Detection Using a UNet3+ Model with a Hybrid Swin Transformer and EfficientNet (UNet3+STE) for Very-High-Resolution Satellite Imagery
Jaewan Choi, Doochun Seo, Jinha Jung, Youkyung Han, Jaehong Oh, Changno Lee
Remote Sensing.2024; 16(20): 3880. CrossRef

In-situ Measurement of the Arctic Ocean for Optical Property Analysis During 2019 Cruise: Sungjae Lee, Hyun-Cheol Kim; GEO DATA. 2020;2(2):63-70. Published online December 30, 2020; DOI: https://doi.org/10.22761/DJ2020.2.2.009

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Abstract PDF: The Arctic issue has increased due to global warming. The Arctic is losing the role of cooling because reducing sea ice by warming on the Arctic, which is changing the energy balance on the Earth system. Change of Arctic ocean, atmosphere, and cryosphere influence on an ecosystem of Arctic as well. These changes are monitoring by remote sensing due to the Arctic is difficult for human access, and where is a wide area. However, a low solar altitude on the Arctic limits Ocean Color Algorithms applies to the Arctic because most ocean color algorithms are based on empirical data in the mid-latitude. Continuous data sampling on the Arctic ocean is the best way to improve and develop a suitable ocean color algorithm for the Arctic. This paper aims to report ocean observation data acquired by Ice-Breaker research vessel Araon during the summer Arctic expedition of 2019. Acquired samples are chlorophyll-a, suspended sediment concentration, in-situ measured ocean optical properties. Sampled data showed that there is a significant effect of dissolved organic matter in its inherent optical properties. We use these data for the aims of improving and develop ocean color algorithms in the Arctic.

The Characteristic of Temperature in Hibernacula of the Greater Horseshoe Bat (Rhinolophus ferrumequinum): Sun-Sook Kim, Byeori Kim, Taek-Woo Lee; GEO DATA. 2020;2(2):71-76. Published online December 30, 2020; DOI: https://doi.org/10.22761/DJ2020.2.2.010

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Abstract PDF: The daily ambient temperature of hibernacula for Rhinolophus ferrumequinum in two regions (the Sanpyeong abandoned mine, Seowoon-myeon, Anseong, Gyeonggi and the Beollari-cave, Seongsan-eup, Seoguipo, Jeju) were collected. The mean ambient temperature of the Sanpyeong-ri mine was 7.69±1.19℃ (±SD, range (min.~max. temperature): 4.5~10.5℃) from 9 November 2018 to 17 April 2019. The mean temperature of the Beollari-cave was 6.73±1.76℃ (±SD, range (min.~max. temperature): 4.1~11.9℃) from 29 November 2018 to 6 March 2019.

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