空间信息技术支持下的沿海风能资源评价
收稿日期: 2004-04-01
修回日期: 2004-09-01
网络出版日期: 2004-11-25
基金资助
973项目“黄河流域水资源演化规律与可再生性维持机理”(G1999043602)。
Wind Energy Resources Assessment in the Coastal Zones I33 Based on Spatial Information Technique
Received date: 2004-04-01
Revised date: 2004-09-01
Online published: 2004-11-25
江 东, 王建华 . 空间信息技术支持下的沿海风能资源评价[J]. 地理科学进展, 2004 , 23(6) : 41 -48 . DOI: 10.11820/dlkxjz.2004.06.005
Coastal zones play a very important role in wind energy resources exploration in China. Offshore wind is an attractive energy source due to the potential of very high wind power as a result of relatively low sea surface roughness. The great variation of wind field near the ground baffles wind energy resources assessment. Synthetic aperture radar (SAR) images from remote sensing satellites have been achieved over the oceans on a continuous basis. Their unique characters, including independence on daylight, uninfluenced from clouds, high spatial resolution and large spatial coverage, make them a very useful tool for acquiring main parameters of wind fields in ocean areas. Main data sources are ERS-1 and ERS-2 satellites of Europe, the RADARSAT-1 satellite of Canada, and the latest European satellite ENVISAT. SAR-derived sea wind maps may be estimated from empirical scatter meter algorithms that are valid for open sea conditions. With recent development of spatial information techniques, methodology and algorithm for retrieving wind vectors from SAR onboard satellite become mature. The physical principle is that capillary waves and short gravity waves at the sea surface created by the instantaneous wind field backscatters electromagnetic radiation in the C-band as emitted and received by the SAR instrument. Relationship between backscatter coefficient and sea surface wind field was established based on Bragg mechanism, and key factors such as wind direction and speed were derived. Empirical algorithms, the so-called scatterometer models CMOD-4 and CMOD-IFR, relate the backscattered signal to wind speed. The paper gave a brief review in this area. Means for wind field retrieval and validation were presented in detail. Problems and application prospect in China were also discussed.
Key words： assessment; resource; spatial information techniques; wind energy
[1] Johannessen, O.M. and E. Bjorgo, Wind energy mapping of coastal zones by synthetic aperture radar (SAR) for siting potential windmill locations. International Journal of Remote Sensing, 2000. 21(9): 1781~1786.
[2] Hasager, C.B., H.P. Frank, and B.R. Furevik, On offshore wind energy mapping using satellite SAR. Canadian Journal of Remote Sensing, 2002. 28(1): 80~89.
[3] Kim, D. and W.M. Moon, Estimation of sea surface wind vector using RADARSAT data. Remote Sensing of Environment, 2002. 80: 55~64.
[4] 张永红， 张继贤， 林宗坚. 合成孔径雷达成像处理的数学原理. 遥感信息. 2000,4:13~15.
[5] 董 庆， 郭华东， 王长林. 多波段多极化合成孔径雷达的海洋学应用. 2001,1:67~72.
[6] Scoon, A., I. S. Robinson and P. J. Meadows Demonstration of an improved calibration scheme for ERS-1 SAR imagery using a scatterometer wind model, Int. J. Remote Sens., 地球科学进展. 1996, 17 (2): 413~418.
[7] Frank, H., and L. Landberg Modelling the wind climate of Ireland, Boundary-Layer Meteorology, 1997, 85: 359~378.
[8] Stoffelen A. and Anderson D.L.T. 'ERS-1 Scatterometer Data and Characteristics and Wind Retrieval Skills' Proceeding of first ERS-1 Symposium, ESA SP-359, March, 1993.
[9] Thompson D.R., T.M. Elfouhaily, B. Chapron. Polarization ratio for microwave backscattering from the ocean surface at low to moderate incidence angles. Proceedings of 1998 International Geoscience and Remote Sensing Symposium. 1998, 1671~1673.
[10] Gerling, T.W. Structure of the surface wind field from SEASAT SAR, Journal of Geophysical Research, 1986, 91: 2308~2320.
[11] Du, Y., P. Vachon, J. Wolf. Wind direction estimation from SAR images of the ocean using wavelet analysis, Can. J. Remote Sens., 2002, 28, 498~509.
[12] Fichaux, N., T. Rachin. Combined extraction of high spatial resolution wind speed and direction from SAR images: a new approach using wavelet transform, Canada Journal of Remote Sensing., 2002, 28: 510~516.
[13] Vachon P., FW Dobson. Validation of wind vector retrieval from ERS-1 SAR images over the ocean, Global Atmosphere and Ocean System. 1996, 5:177~187.
[14] 杨劲松，黄韦艮，周长宝 等. 合成孔径雷达图像的近岸海面风场反演. 遥感学报. 2001,5(1):13~16.
[15] 宫靖远, 贺德馨, 孙如林, 吴运东 主编. 风电场工程技术手册. 北京：机械工业出版社，2004.
[16] Stoffelen A., D. Anderson. Wind retrieval and ERS scatterometer radar backscatter measurements. Advance in Space Research. 1993, 13:53~60.
[17] Lehner, S., J. Horstmann, W. Koch, W. Rosenthal, Mesoscale wind measurements using recalibrated ERS SAR images, Journal of Geophysical Research,1998, 103:7847~7856.
[18] Horstmann, J., W. Koch, S. Lehner, R. Tonboe, Wind retrieval over the ocean using syntheticaperture radar with C-band HH polarization. . IEEE Transection of Geoscience and Remote Sensing. 2000, 38:2122~2131.
[19] K.S.Chem. J.T.Wang, A.J.Chem. Retrieval Of Ocean Winds Form Ers-1/2 Scatterometer And Sar Data Using Natural Network. Proceedings of the 18th Asian Conference on Remote Sensing, October 1997, 20~24 Malaysia.
[20] Horstmann, J., Lehner, S., Koch, W., and Tonboe, R. Computation of Wind Vectors Over the Ocean Using Spaceborne Syntheric Aperture Radar. John Hopkins APL Technical Digest, 2000, 21, 100~107.
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