Browse > Article
http://dx.doi.org/10.7780/kjrs.2021.37.5.1.28

Estimation of High-resolution Sea Wind in Coastal Areas Using Sentinel-1 SAR Images with Artificial Intelligence Technique  

Joh, Sung-uk (Department of Hydrography, Pukyong National University)
Ahn, Jihye (Geomatics Research Institute, Pukyong National University)
Lee, Yangwon (Department of Spatial Information Engineering, Division of Earth Environmental System Science, Pukyong National University)
Publication Information
Korean Journal of Remote Sensing / v.37, no.5_1, 2021 , pp. 1187-1198 More about this Journal
Abstract
Sea wind isrecently drawing attraction as one of the sources of renewable energy. Thisstudy describes a new method to produce a 10 m resolution sea wind field using Sentinel-1 images and low-resolution NWP (Numerical Weather Prediction) data with artificial intelligence technique. The experiment for the South East coast in Korea, 2015-2020,showed a 40% decreased MAE (Mean Absolute Error) than the generic CMOD (C-band Model) function, and the CC (correlation coefficient) of our method was 0.901 and 0.826, respectively, for the U and V wind components. We created 10m resolution sea wind maps for the study area, which showed a typical trend of wind distribution and a spatially detailed wind pattern as well. The proposed method can be applied to surveying for wind power and information service for coastal disaster prevention and leisure activities.
Keywords
Sea wind; Sentinel-1; SAR; Deep neural network;
Citations & Related Records
연도 인용수 순위
  • Reference
1 EORC, 2021. ALOS Global Digital Surface Model (DSM), ALOS World 3D - 30 m (AW3D30) Version 3.2/3.1, Product Description Ed.2.1, Earth Observation Research Center Japan Aerospace Exploration Agency, SAITAMA, JP.
2 ArgoGIS, 2021. Geographic Information of Marine Spaces, https://www.argogis.com/, Accessed on Jun. 5, 2021.
3 ECMWF (European Centre for Medium-Range Weather Forecasts), 2021. ERA5: How to Calculate Wind speed and Wind direction from U and V Components of the Wind? https://confluence.ecmwf.int/pages/viewpage.action?pageId=133262398, Accessed on Jun. 5, 2021.
4 ESA (European Space Agency), 2021b. Level-2, https://sentinel.esa.int/web/sentinel/user-guides/sentinel-1-sar/product-types-processing-levels/level-2, Accessed on Jun. 5, 2021.
5 EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites), 2021a. ASCAT, Advanced Scatterometer, https://www.eumetsat.int/ascat, Accessed on Oct. 11, 2021.
6 GEBCO (General Bathymetric Chart of the Oceans), 2021. General Bathymetric Charts of Oceans, https://www.gebco.net/, Accessed on Jun. 5, 2021.
7 H2O. ai, 2021. The H2O AI Hybrid Cloud, https://www.h2o.ai/, Accessed on Jun. 5, 2021.
8 Hwang, H. and H. Kim, 2011. Analysis on offshore wind using SAR satellite imagery, Journal of the Wind Engineering Institute of Korea, 15(4): 67-71 (in Korean with English Abstract).
9 KMA (Korea Meteorological Administration), 2021b. Ocean Prediction, https://www.weather.go.kr/w/ocean/prediction/nwp.do, Accessed on Sep. 24, 2021.
10 Larasati, A., A. Dwiastutik, D. Ramadhanti and A. Mahardika, 2018. The effect of kurtosis on the accuracy of artificial neural network predictive model, MATEC Web of Conferences, 204: 02018.
11 SNAP, 2021. Science Toolbox Exploitation Platform Toolbox Exploitation Platform, https://step.esa.int/main/toolboxes/snap/, Accessed on Jun. 5, 2021.
12 JAXA (Japan Aerospace Exploration Agency), 2021. Japan Aerospace Exploration Agency, Advanced Land Observing Satellites, https://www.eorc.jaxa.jp/ALOS/a/en/index_e.htm, Accessed on Jun. 5, 2021.
13 KHOA (Korea Hydrographic and Oceanographic Agency), 2021. Ocean Data in Grid Framework, http://www.khoa.go.kr/oceangrid/gis/category/reference/distribution.do, Access on Jun. 5, 2021.
14 Corazza, A., A. Khenchafand, and F. Comblet, 2020. Assessment of wind direction estimation methods from SAR Images, Remote Sensing, 12: 3631.   DOI
15 KMA (Korea Meteorological Administration), 2007. Development of Wind Resource Map, KMA Technical Note 11-1360000-000355-14, Korea Meteorological Administration, Seoul, KR.
16 KMA (Korea Meteorological Administration), 2021a. Types of Numerical Weather Prediction Models, https://www.kma.go.kr/aboutkma/intro/supercom/model/model_category.jsp, Accessed on Sep. 24, 2021.
17 KMA (Korea Meteorological Administration), 2021c. LDAPS (Local Data Assimilation and Prediction System), https://data.kma.go.kr/data/rmt/rmtList.do?code=340&pgmNo=65, Accessed on Sep. 24, 2021.
18 KMA (Korea Meteorological Administration), 2021d. Open Meteorological Data Portal, https://data.kma.go.kr/, Accessed on Jun. 5, 2021.
19 La, TV., A. Khenchaf, F. Comblet, and C. Nahum, 2017. Exploitation of C-band Sentinel-1 images for high-resolution wind field retrieval in coastal zones (Iroise Coast, France), IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(12): 5458-5471.   DOI
20 NASA, 2021. Earth Data Search, https://search.earthdata.nasa.gov, Accessed on Jun. 5, 2021.
21 Yue C., and M. Yang, 2009. Exploring the potential of wind energy for a coastal state, Energy Policy, 37(2009): 3925-3940.   DOI
22 Stoffelen, A., J.A. Verspeek, J. Vogelzang, and A. Verhoef, 2017. The CMOD7 geophysical model function for ASCAT and ERS wind retrievals, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(5): 2123-2134.   DOI
23 Yun J., Y. Kim, and H. Choi, 2021. Analyses of the meteorological characteristics over South Korea for wind power applications using KMAPP, Atmosphere, 31(1): 1-15.   DOI
24 MOTIE (Ministry of Trade, Industry and Energy), 2020. Development Plan for Offshore Wind Power, http://www.motie.go.kr/common/download.do?fid=bbs&bbs_cd_n=81&bbs_seq_n=163153&file_seq_n=1, Accessed on Sep. 24, 2021.
25 ESA (European Space Agency), 2021a. Sentinel-1, https://sentinel.esa.int/web/sentinel/missions/sentinel-1, Accessed on Jun. 5, 2021.
26 EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites), 2021b. The Metop-A, B and C polar orbiting meteorological satellites, https://www.eumetsat.int/metop, Accessed on Oct. 11, 2021.
27 Kim, H., Y. Kang, H. Lee, and W. Jung, 2009. Application system for national wind map KIER-WindMap, Proc. of 2009 Fall Conference of the Korean Society for New and Renewable Energy, Jeonju, KR, Nov. 25-27, pp. 532-533.
28 KMA (Korea Meteorological Administration), 2021e. Open Meteorological Data Portal, https://data.kma.go.kr/climate/ObsValSearch/selectObsVal SearchWindRose.do, Accessed on Jun. 5, 2021.
29 Li, Xiao-Ming, T. Qin and K. Wu, 2020. Retrieval of sea surface wind speed from spaceborne SAR over the Arctic marginal ice zone with a neural network, Remote Sensing, 12: 3291.   DOI
30 Shiyan, W., Y. Shengb and X. Dewei, 2020. On accuracy of SAR wind speed retrieval in coastal area, Applied Ocean Research, 95: 102012.   DOI