Conference Presentations Since 2008
Underlined : EGLab members
* : Presenterย
2026
[109] Soyeon Park, Jihyun Kim, Kwan-Dong Park, Seokhoon Oh, and No-Wook Park*, 2026. A two-stage spatio-spectral image fusion approach to generating synthetic spectral bands for high spatial resolution satellite imagery, geoENV 2026 (The 16th International Conference on Geostatistics for Environmental Applications), Limassol, Cyprus, June 11.
[108] Inseon Lee*, Soyeon Park, Jaehwa Jang, Eui Ho Hwang, and No-Wook Park, 2026. Regression-based error refinement for cloud-contaminated regions reconstructed via SAR-to-optical image translation, ISRS 2026, Matsue, Japan, May 14.
[107] Soyeon Park*, Inseon Lee, Eui Ho Hwang, and No-Wook Park, 2026. Cloud removal using bi-temporal optical imagery and generative deep learning, ISRS 2026, Matsue, Japan, May 14.
2025
[106] ์ด์ธ์ *, ๋ฐ์์ฐ, ๋ฐ์ ์, ๋ฐ๋ ธ์ฑ, 2025. ์๊ณ์ด Sentinel-1 ์์์ ์ด์ฉํ ์กฐ๊ธฐ ์๋ฌผ ๋ถ๋ฅ: ๋ฏธ๊ตญ ์ผ๋ฆฌ๋ ธ์ด ์ฌ๋ก ์ฐ๊ตฌ, 2025 ๋ํ์๊ฒฉํ์ฌํํ ์ถ๊ณํ์ ๋ํ, ์ฌ์, 2025.10.23.ย
[105] ๋ฐ์ ์*, ๋ฐ์์ฐ, ํฉ์ํธ, ๋ฐ๋ ธ์ฑ, 2025. ๋ค์ค์๊ธฐ SAR ๋ฐ ๊ดํ์์๊ณผ ์์ฑํ AI๋ฅผ ์ด์ฉํ ๊ฐ์ ๊ดํ์์ ์์ฑ, 2025 ๋ํ์๊ฒฉํ์ฌํํ ์ถ๊ณํ์ ๋ํ, ์ฌ์, 2025.10.23.ย
[104] ๋ฐ์์ฐ*, ๋ฐ์ ์, ๋ฐ๋ ธ์ฑ, ํฉ์ํธ, 2025. ์จ์ด๋ธ๋ ๋ณํ ๊ธฐ๋ฐ ์กฐ๊ฑด๋ถ ์์ฑ์ ์ ๋ ์ ๊ฒฝ๋ง์ ์ด์ฉํ ๊ณ ํด์๋ SAR-๊ดํ ์์ ๋ณํ, 2025 ๋ํ์๊ฒฉํ์ฌํํ ์ถ๊ณํ์ ๋ํ, ์ฌ์, 2025.10.23.ย
[103] ๋ฐ์์ฐ, ๋ฐ๋ ธ์ฑ*, 2025. ์จ์ด๋ธ๋ ๋ณํ ๊ธฐ๋ฐ ํน์ง๊ณผ ์์ฑํ AI ๊ธฐ๋ฐ SAR-๊ดํ ์์ ๋ณํ์ ์ด์ฉํ ๊ณ ํด์๋ ๊ฐ์ ๊ดํ ์์ ์์ฑ, 2025 ํ๊ตญ์ง๊ตฌ๊ณผํํ ์ถ๊ณํ์ ๋ฐํํ, ํ๊ตญ์ง์ง์์์ฐ๊ตฌ์, 2025.09.26. ์ฐ์ ํฌ์คํฐ์
[102] ๋ฐ๋ ธ์ฑ*, ๋ฐ์์ฐ, 2025. ๋ค์ค์ผ์ ์์ ์ตํฉ์ ์ด์ฉํ ๊ฐ์ ๊ดํ ์์ฑ์์ ์์ฑ: ์๊ณต๊ฐ ์ตํฉ๊ณผ ์์ ๋ณํ์ ์ค์ฌ์ผ๋ก, 2025 ํ๊ตญ์ง๊ตฌ๊ณผํํ ์ถ๊ณํ์ ๋ฐํํ, ํ๊ตญํด์๊ณผํ๊ธฐ์ ์, 2025.04.11.ย
[101]ย Soyeon Park* and No-Wook Park, 2025. Optical image restoration using SAR imagery and generative deep learning models, ISRS 2025, Incheon, Korea, May 15.ย
2024
[100] ๋ฐ์์ฐ*, ๋ฐ์๋ฏผ, ๊น์์ฌ, ๊นํ์ฅ, ์์ข ํ, ๊นํ์ , ๋ฐ๋ ธ์ฑ, 2024. ๊ณ ํด์๋ ์๊ณ์ด ๊ดํ ์์ฑ์์ ์์ฑ์ ์ํ ์๊ณต๊ฐ ์ตํฉ ๋ฐฉ๋ฒ๋ค์ ๋ฏผ๊ฐ๋ ๋ถ์, 2024 ๋ํ์๊ฒฉํ์ฌํํ ์ถ๊ณํ์ ๋ํ, ์์ธ, 2024.10.17. ย
[99] ๋ฐ์์ฐ*, ๋ฐ๋ ธ์ฑ, ํฉ์ํธ, 2024. ๊ณ ํด์๋ ๊ดํ์์ ๋ณต์์ ์ํ SAR-๊ดํ ์์ ๋ณํ ๋ฐฉ๋ฒ์ ๋น๊ต, 2024 ๋ํ์๊ฒฉํ์ฌํํ ์ถ๊ณํ์ ๋ํ, ์์ธ, 2024.10.17. ย
[98] ์ ์น๊ท, ๊น์ ์ง, ํฉ์ธ์ฌ, ๋ฐ์์ฐ, ๋ฐ๋ ธ์ฑ*, 2024. ๋ค๋ณ๋ ์ง๊ตฌํต๊ณํ๊ณผ ํ๊ฒฝ ๊ณต๊ฐ์ ๋ณด๋ฅผ ์ด์ฉํ ๋ฉง๋ผ์ง ์์๋ฐ๋ ์ถ์ , ํ๊ตญ์ง๊ตฌ๊ณผํํ 2024 ์ถ๊ณํ์ ๋ฐํํ, ์์ธ๋ํ๊ต ์ํฅ์บ ํผ์ค, 2024.10.11.ย
[97] Soyeon Park* and No-Wook Park, 2024. Generation of cloud-free high spatial resolution optical images using spatio-temporal fusion, IGARSS 2024, Athens, Greece, July 7โ12.
[96] No-Wook Park*, Soyeon Park, and Seokhoon Oh, 2024. Hypothetical optical image generation using multi-sensor image fusion for environmental monitoring, geoENV 2024 (The 15th International Conference on Geostatistics for Environmental Applications), Chania, Greece, June 20.ย
[95]ย Soyeon Park* and No-Wook Park, 2024. Generation of seamless high spatial resolution normalized difference vegetation index using spatiotemporal fusion and cloud removal, ISRS 2024, Taichung, Taiwan, April 25. Best Student Paper Award
2023
[94] ๋ฐ์์ฐ*, ๋ฐ๋ ธ์ฑ, ์ํธ์ฉ, 2023. ์๊ณ์ด ๊ณ ํด์๋ ๊ดํ์์ ์์ฑ์ ์ํ ๊ตฌ๋ฆ ์ ๊ฑฐ์ ์๊ณต๊ฐ ์ตํฉ์ ๊ฒฐํฉ, 2023 ๋ํ์๊ฒฉํ์ฌํํ ์ถ๊ณํ์ ๋ํ, ๊ฒฝ์ฃผ, 2023.11.16.
[93] ๋ฐ๋ ธ์ฑ*, ๋ฐ์์ฐ, ์ํธ์ฉ, 2023. ์๋ฌผ ๋ชจ๋ํฐ๋ง์ ์ํ ์๊ณต๊ฐ ์ตํฉ ๊ธฐ๋ฐ ์๊ณ์ด ๊ณ ํด์๋ ์์์ง์ ์์ฑ, 2023 ๋ํ์๊ฒฉํ์ฌํํ ์ถ๊ณํ์ ๋ํ, ๊ฒฝ์ฃผ, 2023.11.16.
[92] ์ ์น๊ท, ํฉ์ธ์ฌ, ๊น์ ์ง, ๋ฐ๋ ธ์ฑ*, ๊ถ์ค์ค, 2023. ํ๊ฒฝ ๊ณต๊ฐ์ ๋ณด์ ์์ฑ์์์ ์ด์ฉํ ๋ฉง๋ผ์ง ์์ฉ๋ ฅ ์ถ์ ์๋น ์ฐ๊ตฌ, 2023 ๋ํ์๊ฒฉํ์ฌํํ ์ถ๊ณํ์ ๋ํ, ๊ฒฝ์ฃผ, 2023.11.16.
[91] ๋ฐ๋ ธ์ฑ*, ๋ฐ์์ฐ, 2022. ๊ฐ์์์ ์์ฑ์ ์ํ ๋ค์ค์ผ์ ์์ ์ตํฉ: ๊ธฐ์ ํํฉ๊ณผ ์ ๋ง, 2023 GeoAI๋ฐ์ดํฐํํ ์ถ๊ณ์ปจํผ๋ฐ์ค, ๋ถ์ฐ, 2022.06.29.
[90] Soyeon Park*, No-Wook Park, and Minju Park, 2023. Combining regression and segmentation for object-based spatiotemporal fusion, ISRS 2023 & UAV-g 2023, Jeju, Korea, April 19โ21.
[89] Geun-Ho Kwak*, No-Wook Park, and Seungchan Lee, 2023. SAR-to-optical image translation using multi-temporal conditional generative adversarial networks for environmental monitoring, ISRS 2023 & UAV-g 2023, Jeju, Korea, April 19โ21.
2022
[88] ๋ฐ์์ฐ*, ๋ฐ๋ ธ์ฑ, ์ด๋ณ๋ชจ, 2022. ๊ดํ ์์ ๋ณต์์ ์ํ ๊ฐ์ฐ์์ ํ๋ก์ธ์ค ํ๊ท ๋ชจํ ๊ธฐ๋ฐ ๊ตฌ๋ฆ ์ ๊ฑฐ ๋ฐฉ๋ฒ๋ก ์ ๊ฐ์ , ๋ํ์๊ฒฉํ์ฌํํ ์ถ๊ณํ์ ๋ํ, ๋ถ์ฐ, 2022.11.08.
[87] ๊ณฝ๊ทผํธ*, ๋ฐ๋ ธ์ฑ, 2022. ๋น์ง๋ ๋๋ฉ์ธ ์ ์ ๊ธฐ๋ฐ ์๋ฌผ ๋ถ๋ฅ๋ฅผ ์ํ ์๊ฐ ํ๋ จ๊ณผ ์ ๋์ ํ์ต์ ๊ฒฐํฉ, ๋ํ์๊ฒฉํ์ฌํํ ์ถ๊ณํ์ ๋ํ, ๋ถ์ฐ, 202.11.08.
[86] ๊ฐ์์, ๋ฐ์์ฐ*, ๋ฐ๋ ธ์ฑ, 2022. ์ด์ข ์ผ์ ์๋ฃ๋ฅผ ์ด์ฉํ ๊ฐ์์ ๊ณ ํด์๋ ๊ดํ ๋ฐด๋ ์์ฑ์ ๊ดํ ์ฐ๊ตฌ, KSCE 2022 Convention, ๋ถ์ฐ, 2022.10.21.
[85] ๊ณฝ๊ทผํธ*, ๋ฐ๋ ธ์ฑ, ๋ฐ์์ฐ, 2022. ์๊ฐ ํ์ต ๊ธฐ๋ฐ ์๊ฒฉํ์ฌ ์์ ๋ถ๋ฅ๋ฅผ ์ํ ๋น์ง๋ ๋๋ฉ์ธ ์ ์ ๋ชจ๋ธ, 2022 GeoAI๋ฐ์ดํฐํํ ์ถ๊ณ์ํฌ์ต, ๋ถ์ฐ, 2022.06.16.
[84] Soyeon Park* and No-Wook Park, 2022. Gap-filling of cloud-contaminated Sentinel-2 images using Gaussian process regression for crop monitoring, ISRS 2022, Virtual Conference, May 16โ18.ย
[83] Geun-Ho Kwak* and No-Wook Park, 2022. Unsupervised adversarial domain adaptation for crop classification using UAV images, ISRS 2022, Virtual Conference, May 16โ18.
2021
[82] ๋ฐ์์ฐ*, ๋์์ผ, ๋ฐ๋ ธ์ฑ, 2021. ์๊ท๋ชจ ์๋ฌผ ์ฌ๋ฐฐ์ง ๋ชจ๋ํฐ๋ง์ ์ํ ๋ค์ค์ผ์ ๊ณ ํด์๋ ์์ฑ์์์ ์ตํฉ, ๋ํ์๊ฒฉํ์ฌํํ ์ถ๊ณํ์ ๋ํ, ์จ๋ผ์ธ, 2021.10.21. ์ฐ์๋ฐํ๋ ผ๋ฌธ์
[81] ๊ณฝ๊ทผํธ*, ์ํธ์ฉ, ๋ฐ๋ ธ์ฑ, 2021. ๋ฅ๋ฌ๋ ๊ธฐ๋ฐ ๋น์ง๋ ๋๋ฉ์ธ ์ ์ ๋ชจ๋ธ์ ์ด์ฉํ ์๋ฌผ ๋ถ๋ฅ, ๋ํ์๊ฒฉํ์ฌํํ ์ถ๊ณํ์ ๋ํ, ์จ๋ผ์ธ, 2021.10.21.
[80] Soyeon Park* and No-Wook Park, 2021. An object-based weighting model for spatio-temporal fusion of multi-sensor high spatial resolution satellite images, BIEN 2021 (The 4th International Conference of Women Scientists and Engineers), Online & Hotel ICC, Daejeon, Korea, Aug. 18โ20.
[79] Stylianos Hadjipetrou*, Stelios Liodakis, Anastasia Sykioti, Phaedon Kyriakidis, and No-Wook Park, 2021. Geostatistical downscaling of offshore wind speed data derived from numerical weather prediction models using higher spatial resolution satellite products, geoENV 2020 (The 13th International Conference on Geostatistics for Environmental Applications), Virtual Conference, Jun. 18.
[78] Soyeon Park, Sang-il Na, and No-Wook Park*, 2021. An improved weighted function-based model for spatio-temporal fusion using high spatial resolution satellite images, ISRS 2021, Virtual Conference, May 26โ28.
[77] Min-Gyu Park and No-Wook Park*, 2021. Generation of virtual optical imagery using deep learning for early crop mapping, ISRS 2021, Virtual Conference, May 26โ28.
[76] Geun-Ho Kwak*, Chan-won Park, Ho-yong Ahn, and No-Wook Park, 2021. Crop classification using LSTM-based auto-encoder and CNN, ISRS 2021, Virtual Conference, May 26โ28.
[75] Geun-Ho Kwak*, Chan-won Park, Kyung-do Lee, Sang-il Na, Ho-yong Ahn, and No-Wook Park, 2021. A hybrid model for crop classification with limited training data and input images, ISRS 2021, Virtual Conference, May 26โ28.
2020
[74] ์ฅ์ฌํ*, ๋ฐ๋ ธ์ฑ, 2020. Sentinel-2 ์ ์ ๊ฒฝ๊ณ ์์์ ๊ณต๊ฐ ํด์๋ ํฅ์์ ์ํ ๊ณต๊ฐ ์์ธํ ๋ชจ๋ธ์ ๋น๊ต, ๋ํ์๊ฒฉํ์ฌํํ ์ถ๊ณํ์ ๋ํ, ์จ๋ผ์ธ, 2020.11.05.
[73] ๋ฐ์์ฐ*, ๋ฐ๋ ธ์ฑ, 2020. ๋๊ฒฝ์ง ๊ด์ธก์ ์ํ ๋ค์ค ์ผ์ ์์ฑ์์์ ์๊ณต๊ฐ ์ตํฉ ๋ชจ๋ธ์ ๋น๊ต, ๋ํ์๊ฒฉํ์ฌํํ ์ถ๊ณํ์ ๋ํ, ์จ๋ผ์ธ, 2020.11.05.
[72] ๋ฐ๋ฏผ๊ท*, ๋ฐ๋ ธ์ฑ, 2020. ์กฐ๊ฑด๋ถ ์์ฑ์ ์ ๋ ์ ๊ฒฝ๋ง๊ณผ SAR ์์์ ์ด์ฉํ ๊ดํ ์์ ๋ณต์, ๋ํ์๊ฒฉํ์ฌํํ ์ถ๊ณํ์ ๋ํ, ์จ๋ผ์ธ, 2020.11.05.
[71] ๊ณฝ๊ทผํธ*, ๋ฐ์ฐฌ์, ์ํธ์ฉ, ๋ฐ๋ ธ์ฑ, 2020. ์๊ฐ ๋๋ฉ์ธ ์ ์์ ์ํ ํ๋ จ์๋ฃ์ ์๋ ์ถ์ถ, ๋ํ์๊ฒฉํ์ฌํํ ์ถ๊ณํ์ ๋ํ, ์จ๋ผ์ธ, 2020.11.05.
[70] Stylianos Hadjipetrou*, Stelios Liodakis, Anastasia Sykioti, Philip Fayad, Evangelos Akylas, No-Wook Park, and Phaedon Kyriakidis, 2020. Preliminary assessment of offshore wind speed around Cyprus based on Sentinel-1 Level 2 OCN data, Proceedings of SPIE 11524, Eighth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2020) (2020.08)
2019
[69] ๋ฐ์์ฐ*, ๊ณฝ๊ทผํธ, ๋ฐ๋ ธ์ฑ, 2019. ์๊ณต๊ฐ ์ ์ดํ์ต์ ์ด์ฉํ ์๋ฌผ๊ตฌ๋ถ๋ ์ ์, ํ๊ตญ์ง๋ฆฌ์ ๋ณดํํ ์ถ๊ณํ์ ๋ํ, ์ ์ฃผ, 2019.11.01.
[68] ๋ฐ๋ฏผ๊ท*, ๊ณฝ๊ทผํธ, ๋ฐ๋ ธ์ฑ, 2019. ๋ค์ค ์ค์ผ์ผ ๊ณต๊ฐ ํน์ง๊ณผ ํฉ์ฑ๊ณฑ ์ ๊ฒฝ๋ง์ ์ด์ฉํ ์๋ฌผ ๋ถ๋ฅ, ํ๊ตญ์ง๋ฆฌ์ ๋ณดํํ ์ถ๊ณํ์ ๋ํ, ์ ์ฃผ, 2019.10.31. ์ฐ์๋ ผ๋ฌธ์
[67] Soyeon Park* and No-Wook Park, 2019. Effects of class purity of training data on crop classification with 2D-CNN, ACRS 2019, Daejeon, Korea, Oct. 14โ18. Best Paper Award
[66] Min-Gyu Park* and No-Wook Park, 2019. Application of deep learning algorithms considering spatio-temporal features for crop classification, ACRS 2019, Daejeon, Korea, Oct. 14โ18.
[65] Geun-Ho Kwak*, Chan-Won Park, Kyung-Do Lee, Sang-Il Na, Ho-Yong Ahn, and No-Wook Park, 2019. Combination of 2D-CNN and random forest models for crop classification with UAV imagery, ACRS 2019, Daejeon, Korea, Oct. 14โ18.ย
[64] Yeseul Kim* and No-Wook Park, 2019. Accounting for temporal information from dense time-series coarse-scale satellite data for spatio-temporal downscaling, ACRS 2019, Daejeon, Korea, Oct. 14โ18.
[63] ๊ณฝ๊ทผํธ*, ๊น์์ฌ, ๋ฐ์ฐฌ์, ์ด๊ฒฝ๋, ๋์์ผ, ์ํธ์ฉ, ๋ฐ๋ ธ์ฑ, 2019. UAV ์์์ ์ด์ฉํ ์๊ท๋ชจ ๋ฐญ์๋ฌผ ์ฌ๋ฐฐ์ง ๋ถ๋ฅ, ํ๊ตญ์ง๋ฆฌ์ ๋ณด ์ถ๊ณํ์ ๋ํ, ์ถ์ฒ, 2019.05.16.
[62] Yeseul Kim, Geun-Ho Kwak, and No-Wook Park*, 2019. Area-to-area filtered kriging for error correction of satellite-based products, ISRS 2019, Taipei, Taiwan, April 17โ19.
2018
[61] ๋ฐ๋ ธ์ฑ*, ๊น์์ฌ, ๊ณฝ๊ทผํธ, ๋ฐ๋ฏผ๊ท, ๋ฐ์์ฐ, ์ฑ์นํธ, 2018. ์ง๊ตฌํต๊ณํ์ ์๋ฎฌ๋ ์ด์ ์ ์ด์ฉํ ์ ํด์๋ ์์ฑ ์๋ฃ์ ๋ค์ด์ค์ผ์ผ๋ง, ๋ํ์๊ฒฉํ์ฌํํ ์ถ๊ณํ์ ๋ํ, ๋ฌด์ฃผ, 2018.10.25.
[60] ๊ณฝ๊ทผํธ*, ๋ฐ๋ฏผ๊ท, ๋ฐ๋ ธ์ฑ, 2018. UAV ์์๊ณผ ํ ์ค์ณ ์ ๋ณด๋ฅผ ์ด์ฉํ ๊ณ ๋ญ์ง ๋ฐฐ์ถ ์ฃผ์ฐ์ง ๋ถ๋ฅ, ๋ํ์๊ฒฉํ์ฌํํ ์ถ๊ณํ์ ๋ํ, ๋ฌด์ฃผ, 2018.10.25. ์ฐ์๋ฐํ๋ ผ๋ฌธ์
[59] ๊น์์ฌ*, ๊ณฝ๊ทผํธ, ๋ฐ์์ฐ, ๋ฐ๋ ธ์ฑ, 2018. ๋ฌด์ธ๊ธฐ ์์ ๊ธฐ๋ฐ ์๋ฌผ๋ถ๋ฅ๋ฅผ ์ํ ๊ธฐ๊ณํ์ต ๋ชจํ์ ๋น๊ต, ๋ํ์๊ฒฉํ์ฌํํ ์ถ๊ณํ์ ๋ํ, ๋ฌด์ฃผ, 2018.10.25.
[58] Geun-Ho Kwak*, Chan-Won Park, Kyung-Do Lee, Sang-Il Na, and No-Wook Park, 2018. Impact of new informative training data on classification performance in semi-supervised learning, ISRS 2018, Pyeongchang, Korea, May 9โ11.
[57] Yeseul Kim*, Chan-Won Park, Kyung-Do Lee, Sang-Il Na, and No-Wook Park, 2018. Using past land-cover maps and uncertainty information for self-learning based early season crop mapping, ISRS 2018, Pyeongchang, Korea, May 9โ11.
2017
[56] ๊ณฝ๊ทผํธ*, ๋ฐ์์ฐ, 2017. ์ ์ดํ์ต๊ณผ ๊ฐ์ฒด๊ธฐ๋ฐ ๋ถ๋ฅ๋ฅผ ์ด์ฉํ ํ ์งํผ๋ณต๋ ๊ฐฑ์ ๋ฐฉ์ ์ฐ๊ตฌ, ํ๊ฒฝ๊ณต๊ฐ์ ๋ณด ์ฐ์๋ ผ๋ฌธ ๊ณต๋ชจ์ , ์์ฐ, 2017.11.02. ์ฐ์์(ํ๊ฒฝ๋ถ์ฅ๊ด์)
[55] ๊น์์ฌ*, ๋ฐ๋ ธ์ฑ, ์ด๊ฒฝ๋, 2017. ์๊ฒฉํ์ฌ ์๋ฃ๋ฅผ ์ด์ฉํ ์ฃผ์ ์๋ฌผ ์์ ๊ตญ์ ์ฐ๊ฐ ๊ฒฝ์ง ๋ฉด์ ๋ณํ ๋ชจ๋ํฐ๋ง-์ค๊ตญ ์ฐ๋์ฑ ์ฌ๋ก์ฐ๊ตฌ, ๋ํ์๊ฒฉํ์ฌํํ ์ถ๊ณํ์ ๋ํ, ์์ฐ, 2017.11.02.
[54] ์ ํฌ์*, ๊ณฝ๊ทผํธ, ์ด๊ฒฝ๋, ๋์์ผ, ๋ฐ์ฐฌ์, ๋ฐ๋ ธ์ฑ, 2017. ๋ค์ค ์๊ธฐ ์๊ฒฉํ์ฌ ์๋ฃ๋ฅผ ์ด์ฉํ ๋ถํ ๋ํ๋จ ์ง์ญ์ ๋ฐญ์๋ฌผ ์์ก์ฃผ๊ธฐ ์ถ์ , ๋ํ์๊ฒฉํ์ฌํํ ์ถ๊ณํ์ ๋ํ, ์์ฐ, 2017.11.02.
[53] Geun-Ho Kwak*, Yong-Jae Kim, Byung-Uck Chang, and No-Wook Park, 2017. Geostatistical integration of geogenic factors for indoor radon concentration mapping in South Korea, IAMG 2017, Fremantle, Australia, September 2โ7.ย
[52] Yeseul Kim* and No-Wook Park, 2017. Comparison of regression models for spatial downscaling of coarse scale satellite-based precipitation products, IGARSS 2017, Fort Worth, USA, July 23โ28.
[51] Geun-Ho Kwak*, Kyung-Do Lee, Sang-Il Na, Yeseul Kim, and No-Wook Park, 2017. Semi-supervised learning for classification of crop areas in North Korea, ISRS 2017, Nagoya, Japan, May 18.
[50] Yeseul Kim*, Geun-Ho Kwak, and No-Wook Park, 2017. Impact analysis of errors in coarse scale satellite data on predictive performance of spatial downscaling, ISRS 2017, Nagoya, Japan, May 17.
2016
[49] ๋ฐ๋ ธ์ฑ*, 2016. ์ ํด์๋ ์์ฑ ์ฐ์ถ๋ฌผ์ ๊ณต๊ฐ ์์ธํ: ์ต์ ๊ธฐ์ ๊ณผ ์ด์, ๋ํ์๊ฒฉํ์ฌํํ ์ถ๊ณํ์ ๋ํ, ์ถฉ์ฃผ, 2016.11.04.
[48] ๊น์์ฌ*, ๋ฐ๋ ธ์ฑ, 2016. ์ ํด์๋ ์๊ฒฉํ์ฌ ์๋ฃ์ ๊ณต๊ฐ ์์ธํ์์ ์์ฐจ ๋ณด์ ์ ์ํฅ ๋ถ์, ๋ํ์๊ฒฉํ์ฌํํ ์ถ๊ณํ์ ๋ํ, ์ถฉ์ฃผ, 2016.11.04. ์ฐ์๋ฐํ๋ ผ๋ฌธ์
[47] ๊ณฝ๊ทผํธ*, ์ ํฌ์, ๋ฐ๋ ธ์ฑ, 2016. ๋ค์ค์๊ธฐ Landsat ์์์ ์ด์ฉํ ๋ถํ ์ง์ญ ์๋ฌผ ๋ถ๋ฅ: ๋ํ๋จ ์ผ๋ ์ฌ๋ก์ฐ๊ตฌ, ๋ํ์๊ฒฉํ์ฌํํ ์ถ๊ณํ์ ๋ํ, ์ถฉ์ฃผ, 2016.11.04.
[46] ๋ฐ๋ ธ์ฑ*, ์ด์ฑ์, ์ ํฌ์, ์ด๊ฒฝ๋, ๋์์ผ, 2016. ๋ถ๊ด ํน์ฑ ๋ถ์๊ณผ ๊ณ ํด์๋ ์์ฑ์์์ ์ด์ฉํ ๋ฐญ์๋ฌผ ๊ตฌ๋ถ ๊ฐ๋ฅ์ฑ ์ฐ๊ตฌ, ํ๊ตญ์ง๋ฆฌ์ ๋ณดํํ ์ถ๊ณํ์ ๋ํ, ์ ์ฒ, 2016.10.13.
[45] ๋ฐ๋ ธ์ฑ*, 2016. ์ง๊ตฌํต๊ณํ์ ์ด์ฉํ ๊ณต๊ฐ์๋ฃ์ ์์ธํ ๋ฐ ํตํฉ, ํ๊ตญ์ง๊ตฌ๋ฌผ๋ฆฌ ๋ฌผ๋ฆฌํ์ฌํํ ์ถ๊ณํ์ ๋ํ, ์ธ์ฒ, 2016.10.06.
[44] No-Wook Park*, Yongjae Kim, and Byung-Uck Chang, 2016. Mapping indoor radon concentrations using random forests and residual kriging with geology and TRMS data, 13th International Workshop on the Geological Aspects of Radon Risk Mapping (GARRM), Prague, Czech Republic, Sept. 12โ16.
[43] Yeseul Kim*, Hee Young Yoo, Suk-Young Hong, and No-Wook Park, 2016. Comparison of crop classification schemes using time-series vegetation index and past land-cover maps, ICEO-SI 2016, Keelung, Taiwan, June 26โ28. Oral Presentation Award
[42] No-Wook Park*, 2016. Quantifying uncertainty in spatial downscaling of coarse scale remote sensing products using geostatistical simulation, ICEO-SI 2016, Keelung, Taiwan, June 26โ28.
[41] ๋ฐ๋ ธ์ฑ*, 2016. ์ถ๊ณ๋ก ์ ์๋ฎฌ๋ ์ด์ ์ ์ด์ฉํ ๊ณต๊ฐ ์๋ฃ์ ์์ธํ, ํ๊ตญ์ง๋ฆฌ์ ๋ณดํํ ์ถ๊ณํ์ ๋ํ, ๊ตฌ๋ฏธ, 2016.05.19.
[40] No-Wook Park*, 2016. Quantitative assessment of low resolution remote sensing products using geostatistical downscaling and validation data, ISRS 2016, Jeju, Korea, April 20โ22.
[39] Hee Young Yoo*, Suk-Young Hong, Kyung-Do Lee, Sang-Il Na, and No-Wook Park, 2016. Applicability of multi-temporal satellite images for the classification of small scale field crop areas, ISRS 2016, Jeju, Korea, April 20โ22.
[38] Yeseul Kim*, Suk-Young Hong, and No-Wook Park, 2016. Crop mapping and change detection in Mato Grosso state, Brazil using time-series MODIS NDVI data, ISRS 2016, Jeju, Korea, April 20โ22.
[37] No-Wook Park and Phaedon C. Kyriakidis*, 2016. Geostatistical error assessment of coarse spatial resolution remote sensing products, 4th International Conference on Remote Sensing and Geoinformation of Environment 2016 (RSCy 2016), Cyprus, April 4โ8.
2015
[36] ๊น์์ฌ*, ์ ํฌ์, ํ์์, ๋ฐ๋ ธ์ฑ, 2015. ์๋ฌผ ์ฌ๋ฐฐ ๊ท์น์ ์ด์ฉํ ๋ฅ๋ ํ์ต ๊ธฐ๋ฐ ์๋ฌผ ๋ถ๋ฅ์ ๊ฐ์ , ๋ํ์๊ฒฉํ์ฌํํ ์ถ๊ณํ์ ๋ํ, ๊ด์ฃผ, 2015.10.15. ์ฐ์๋ฐํ๋ ผ๋ฌธ์
[35] ๋ฐ๋ ธ์ฑ, ํฉ์น์, ์ ํฌ์, ๊น์์ฌ*, 2015. ๊ณต๊ฐ ํ๊ท ๋ชจํ์ ์ด์ฉํ ์์ด๋ฅ ์๋ฃ์ ์ฐ๊ด ์ํ ์ธ์์์ ์๊ด์ฑ ๋ถ์, ํ๊ตญ์ง๋ฆฌ์ ๋ณดํํ ์ถ๊ณํ์ ๋ํ, ๋๊ตฌ, 2015.04.16.
[34] ๋ฐ๋ ธ์ฑ, ๊น์์ฌ*, ์ ํฌ์, 2015. ์ ํด์๋ ํ ์งํผ๋ณต ์ ๋ณด์ ์ง๊ตฌํต๊ณํ ๊ธฐ๋ฐ ํด์๋ ๋ณํ, ํ๊ตญ์ง๋ฆฌ์ ๋ณดํํ ์ถ๊ณํ์ ๋ํ, ๋๊ตฌ, 2015.04.16.
[33] ๊น์์ฌ*, ๋ฐ๋ ธ์ฑ, ์ ํฌ์, ํ์์, ์ด๊ฒฝ๋, 2015. ๊ณก๋ฌผ ์์ฐ์ง๋ ๋ถ๋ฅ๋ฅผ ์ํ ์๊ฒฉํ์ฌ ์๋ฃ์ ๊ณผ๊ฑฐ ํ ์งํผ๋ณต๋์ ๊ฒฐํฉ: ๋ฏธ๊ตญ ๊ฒจ์ธ๋ฐ ์ฃผ์ฐ์ง ์ฌ๋ก์ฐ๊ตฌ, ํ๊ตญ์ง๋ฆฌ์ ๋ณดํํ ์ถ๊ณํ์ ๋ํ, ๋๊ตฌ, 2015.04.16.
2014
[32] ๊น์์ฌ*, ๋ฐ๋ ธ์ฑ, ํ์ฑ์ฑ, 2014. ์ ํด์๋ ์๊ฒฉํ์ฌ ์๋ฃ ๊ธฐ๋ฐ ์ฃผ์ ์ ๋ณด์ ์์ธํ๋ฅผ ์ํ ๊ณต๊ฐ ํต๊ณ ๊ธฐ๋ฐ ๋ฐฉ๋ฒ๋ก ์ ๋น๊ต, ๋ํ์๊ฒฉํ์ฌํํ ์ถ๊ณํ์ ๋ํ, ์ ์ฃผ, 2014.10.17. ์ฐ์๋ฐํ๋ ผ๋ฌธ์
[31] ๋ฐ๋ ธ์ฑ*, ๊น์์ฌ, ์ ํฌ์, ํ์์, ์ด๊ฒฝ๋, 2014. ์์ฑ์์ ๊ธฐ๋ฐ ์ฃผ์ ๊ณก๋ฌผ์ง๋ ์๋ฌผ ์ฌ๋ฐฐ๋ฉด์ ์ฐ์ , ๋ํ์๊ฒฉํ์ฌํํ ์ถ๊ณํ์ ๋ํ, ์ ์ฃผ, 2014.10.16.
[30] ํ์์*, ์ด๊ฒฝ๋, ๊น์ดํ, ์๊ทํธ, ๊ฐ์ ๊ท, ๋ฐ๋ ธ์ฑ, ์ฅ๋ฏผ์, ํ์ค, ์ด์ฐ๊ฒฝ, 2014. ์๊ฒฉํ์ฌ ๊ธฐ๋ฐ ๋์ ์์ฐํ๊ฒฝ ๋ชจ๋ํฐ๋ง ํํฉ๊ณผ ๊ณํ, ๋ํ์๊ฒฉํ์ฌํํ ์ถ๊ณํ์ ๋ํ, ์ ์ฃผ, 2014.10.16.
[29] ๊ฐ์ ๊ท*, ์ด์งํ, ์ฅ๊ทผ์ฐฝ, ๊ณ ์ข ํ, ํ์์, ์์ค๋ฐฐ, ํ์ง๋, ๋ฐ๋ ธ์ฑ, 2014. MODIS๋ฅผ ์ด์ฉํ ์ฃผ์ ๊ณก๋ฌผ ์ง๋ ์๋ฌผ ๊ฑด์ค๋ ๋ฐ ์๋ ์ถ์ , ๋ํ์๊ฒฉํ์ฌํํ ์ถ๊ณํ์ ๋ํ, ์ ์ฃผ, 2014.10.16.
[28] No-Wook Park*, 2014. Geostatistical approach to spatio-temporal mapping of PM10 concentrations, ICEO-SI 2014, Miaoli, Taiwan, June 22โ24.
[27] ๋ฐ๋ ธ์ฑ*, ๊น์์ฌ, ์ ํฌ์, 2014. ์ง๊ตฌํต๊ณํ์ ์๋ฎฌ๋ ์ด์ ์ ์ด์ฉํ ์ง๋ณ ์ํ๋ ์ถ์ ์ ๊ตญ์์ ๊ตฐ์ง ๋ถ์์์ ์ํฅ ๋ถ์, ํ๊ตญ์ง๋ฆฌ์ ๋ณดํํ ์ถ๊ณํ์ ๋ํ, ์์ธ, 2014.04.24.
[26] ๋ฐ๋ ธ์ฑ*, ๊น์์ฌ, ์ ํฌ์, ์ด๊ฒฝ๋, ๊น์ดํ, ํ์์, 2014. ์๊ณ์ด MODIS ์์์ง์์ ๊ณผ๊ฑฐ ํ ์งํผ๋ณต๋๋ฅผ ์ด์ฉํ ๊ณก๋ฌผ์์ฐ์ง๋ ํ ์งํผ๋ณต ๋ถ๋ฅ, ํ๊ตญ์ง๋ฆฌ์ ๋ณดํํ ์ถ๊ณํ์ ๋ํ, ์์ธ, 2014.04.24.
[25] ๊น์์ฌ*, ์ ํฌ์, ๋ฐ๋ ธ์ฑ, 2014. ์๊ณ์ด Landsat ์๋ฃ๋ฅผ ์ด์ฉํ ํ ์งํผ๋ณต ๋ณํ์ ๋ฐ๋ฅธ ์งํ ์จ๋ ๋ถ์, ํ๊ตญ์ง๋ฆฌ์ ๋ณดํํ ์ถ๊ณํ์ ๋ํ, ์์ธ, 2014.04.24.
[24] Hee Young Yoo*, No-Wook Park, Suk-Young Hong, Yi-Hyun Kim, Kyung-Do Lee, and Yeseul Kim, 2014. Multi-temporal SAR data classification using feature extraction and multiple classifiers, ISRS 2014, Busan, Korea, April 16โ18.
2013
[23] Hee Young Yoo*, No-Wook Park, Yeseul Kim, and Hogil Lee, 2013. A transfer learning approach to the integration of spectral information with temporal contextual information from an existing land-cover map for land-cover classification, 2013 ICGIS (International Conference on Geospatial Information Science), Seoul, Korea, November 14โ15.
[22] ์ ํฌ์*, ๋ฐ๋ ธ์ฑ, ์ด๊ฒฝ๋, ํ์์, ๊น์ดํ, 2013. ์๋ฃ ๋ณํ ๊ธฐ๋ฐ ํน์ง์ ์ด์ฉํ ๋ค์ค ์๊ธฐ ์๊ฒฉํ์ฌ ์๋ฃ์ ๋ถ๋ฅ, ํ๊ตญ์ง๋ฆฌ์ ๋ณดํํ ์ถ๊ณํ์ ๋ํ, ์ ์ฃผ, 2013.10.31.
[21] ๋ฐ๋ ธ์ฑ*, ์ ํฌ์, ๊น์์ฌ, 2013. ํฌ์์ก ํฌ๋ฆฌ๊น ์ ์ด์ฉํ ์์ญ ๊ธฐ๋ฐ ์ง๋ณ ์ํ๋ ์ถ์ , ํ๊ตญ์ง๋ฆฌ์ ๋ณดํํ ์ถ๊ณํ์ ๋ํ, ์ ์ฃผ, 2013.10.30.
[20] ๊น์์ฌ*, ์ ํฌ์, ์ดํธ๊ธธ, ๋ฐ๋ ธ์ฑ, 2013. ์๊ณต๊ฐ ํฌ๋ฆฌ๊น ์ ์ด์ฉํ ์๊ณ์ด ๋ฏธ์ธ๋จผ์ง ๋๋ ๋ถํฌ๋ ์์ฑ, ํ๊ตญ์ง๋ฆฌ์ ๋ณดํํ ์ถ๊ณํ์ ๋ํ, ์ ์ฃผ, 2013.10.30.
[19] Yeseul Kim*, Hee Young Yoo, No-Wook Park, and Dong-Ho Jang, 2013. Detection of geomorphological environmental changes using time-series Landsat images and grain size data: a case study in Baramarae tidal flats, Korea, ACRS 2013, Bali, Indonesia, October 20โ24.
[18] ์ ํฌ์*, ๋ฐ๋ ธ์ฑ, ๊น์์ฌ, 2013. ๊ธฐ์ ์ ํ ์งํผ๋ณต๋์ ์ ์ดํ์ต์ ์ด์ฉํ ๊ฐ์ฒด ๊ธฐ๋ฐ ์๊ฒฉํ์ฌ ์๋ฃ ๋ถ๋ฅ, ๋ํ์๊ฒฉํ์ฌํํ ์ถ๊ณํ์ ๋ํ, ์ฒ์, 2013.10.10.
[17] No-Wook Park* and Hee Young Yoo, 2013. The effects of spatial prediction of grain size fractions on intertidal surface sediments classification, IGARSS 2013, Melbourne, Australia, July 21โ26.
[16] Hee Young Yoo*, Stefan Leyk, and No-Wook Park, 2013. Assessing the uncertainty of non-change in national-scale vegetation mapping using 3d wavelet transformed NDVI time series, IGARSS 2013, Melbourne, Australia, July 21โ26.
[15] No-Wook Park*, 2013. Geostatistical downscaling of low resolution precipitation data with high resolution DEM and NDVI data, ICEO-SI 2013, Tainan, Taiwan, June 23โ25.
[14] ๊น์์ฌ*, ์ ํฌ์, ๋ฐ๋ ธ์ฑ, ์ฅ๋ํธ, 2013. ๋ค์ค ์๊ธฐ ์๊ฒฉํ์ฌ ์๋ฃ ๊ธฐ๋ฐ DEM์ ์ด์ฉํ ๊ฐ์์ง ํด์ ํ๊ฒฝ ๋ณํ ์ ๋ณด ์ถ์ถ, ํ๊ตญ์ง๋ฆฌ์ ๋ณดํํ ์ถ๊ณํ์ ๋ํ, ๊ณต์ฃผ, 2013.05.09. ์ฐ์๋ฐํ๋ ผ๋ฌธ์
[13] ์ด์์*, ๋ฐ๋ ธ์ฑ, ์ ํฌ์, ์ฅ๋ํธ, ๊น๋์ง, ๊น์์ฌ, 2013. ๋ค์ค ์ผ์ ๊ณ ํด์๋ ์์ฑ ์๋ฃ์ ํ์ฅ ์กฐ์ฌ ์๋ฃ๋ฅผ ์ด์ฉํ ๊ฐ์์ง ํ์ธต ํด์ ๋ฌผ ์ฑ๋ถ ๋ถํฌ๋ ์ ์, ํ๊ตญ์ง๋ฆฌ์ ๋ณดํํ ์ถ๊ณํ์ ๋ํ, ๊ณต์ฃผ, 2013.05.09.ย
2012
[12] ๊น์์ฌ*, ์ ํฌ์, ๋ฐ๋ ธ์ฑ, ์ฅ๋ํธ, 2012. ๋ค์ค ์๊ธฐ ์๊ฒฉํ์ฌ ์๋ฃ์ ํ์ฅ ์กฐ์ฌ ์๋ฃ๋ฅผ ์ด์ฉํ ๊ฐ์์ง DEM ์์ฑ, ํ๊ตญ์ง๋ฆฌ์ ๋ณดํํ ์ถ๊ณํ์ ๋ํ, ์ ์ฃผ, 2012.11.09.
[11] ์ด์์*, ๋ฐ๋ ธ์ฑ, ๊น๋์ง, ์ ํฌ์, ์ฅ๋ํธ, 2012. ๊ณ ํด์๋ ๊ดํ ๋ฐ SAR ์๋ฃ๋ฅผ ์ด์ฉํ ๊ฐ์์ง ํ์ธต ํด์ ๋ฌผ ๋ถ๋ฅ, ํ๊ตญ์ง๋ฆฌ์ ๋ณดํํ ์ถ๊ณํ์ ๋ํ, ์ ์ฃผ, 2012.11.09.ย
[10] ๋ฐ๋ ธ์ฑ*, ์ ํฌ์, 2012. ์๊ณต๊ฐ ์๋ฃ ๋ถ์์ ์ํ ์ง๊ตฌํต๊ณํ์ ํํฉ๊ณผ ์ ๋ง, ํ๊ตญ์ง๋ฆฌ์ ๋ณดํํ ์ถ๊ณํ์ ๋ํ, ์ ์ฃผ, 2012.11.08.
[9] No-Wook Park* and Hee Young Yoo, 2012. Downscaling of coarse scale thematic maps using geostatistics and fine scale secondary data, ISRS 2012 ICSANE, Incheon, Korea, October 10โ12.
[8] Hee Yong Yoo* and No-Wook Park, 2012. The wavelet analysis of hyperspectral imagery for anomaly detection, ISRS 2012 ICSANE, Incheon, Korea, October 10โ12.
[7] No-Wook Park, Hee Young Yoo, Sang-Won Lee, and Hyo-Sook Lim, 2012. Geostatistical integration of ground observation data and coarse scale remote sensing data to generate fine scale thematic maps, ICEO-SI 2012, Taipei, Taiwan, June 25โ27. Student Presentation Award
[6] ์ด์์*, ๋ฐ๋ ธ์ฑ, 2012. ์กฐ๊ฐ๋ ํ์ธต ํด์ ๋ฌผ ๋ถ๋ฅ๋ฅผ ์ํ ๊ณ ํด์๋ ์์ฑ์๋ฃ์ ํ์ฅ ์กฐ์ฌ ์๋ฃ์ ์ง๊ตฌํต๊ณํ์ ํตํฉ, ํ๊ตญ์ง๋ฆฌ์ ๋ณดํํ ์ถ๊ณํ์ ๋ํ, ๊ตฌ๋ฏธ, 2012.05.11. ์ฐ์๋ฐํ๋ ผ๋ฌธ์
[5] ์ด์์*, ๋ฐ๋ ธ์ฑ, ์ฅ๋ํธ, 2012. KOMPSAT-2 ์์๊ณผ ๊ณต๊ฐ ์๊ด์ฑ ์ ๋ณด๋ฅผ ์ด์ฉํ ์กฐ๊ฐ๋ ํ์ธต ํด์ ์ ๋ถ๋ฅ, ๋ํ์๊ฒฉํ์ฌํํ ์ถ๊ณํ์ ๋ํ, ๋ฌด์ฃผ, 2012.03.29.
2011
[4] Ki-Weon Seo*, Clark R. Wilson, Jianli Chen, No-Wook Park, Masayoshi Ishii, Choon-Ki Lee, and Byong-Kwon Park, 2011. Global and arctic mean sea level variations observed by GRACE with the optimum ocean kernel, AGU Fall Meeting 2011, San Francisco, USA, December 5โ9.
[3] ์ด์์, ์ก์๋*, 2011. ํ๊ฒฝ์ ๋ณด์ ๊ณต๊ฐ ๋ถ์์ ์ด์ฉํ ์์ ์ฌ๊ณ ํผํด์ ์ํฅ ํ๊ฐ: ์ฒด๋ฅด๋ ธ๋น ์์ ์ฌ๊ณ ์ฌ๋ก์ฐ๊ตฌ, ์นํ๊ฒฝ์ ์ฑ ๋์ฐ๋ฏธ ํ๊ฒฝ๊ณต๊ฐ์ ๋ณด ์ฐ์๋ ผ๋ฌธ ๊ณต๋ชจ์ , ISRS 2011, ์ฌ์, 2011.11.02. ํ์๋ถ ์ฐ์์
2010
[2] No-Wook Park*, 2010. Evidential reasoning applied to GIS-based landslide hazard mapping with multiple geospatial data, IGARSS 2010, Hawaii, USA, July 26โ30.
2008
[1] No-Wook Park* and Phaedon C. Kyriakidis, 2008. The effects of uncertain topographic data on spatial prediction of landslide hazard, ISRS 2008, Daejeon, Korea, October 29โ30.