The Inversion Of Sea Surface Temperature Based On Multi-source Remote Sensing

The macro advantage of remote sensing information has important practical value in sea surface temperature monitoring. The resource of remote sensing data is becoming diversion, selecting data and methods for research target are always be focus in remote sensing information processing. From the perspective of sea surface temperature inversion, this paper study of the practicality and accuracy in multi-source remote sensing data, such as Landsat ETM+, HJ-1A/1B CCD/IRS, and Terra MODIS, aimed at establish accurate temperature inversion method for different RS data sources, in order to improve the practicality in small-scale multi-source inversion, and provide sea surface temperature production quickly and accurately, and be convenient for departments to monitoring real-time sea.surface temperature, in order to provide effective data and theoretical support for environmental monitoring department.Atmosphere radiation had effects on the received remote sensing information. The atmospheric correction can eliminate the effects from images, and recover the real radiation information of earth surface, can provide accurate data for follow-up research. In this paper, the atmospheric radiative transfer model is discussed; the different remote sensing data source is corrected by using atmospheric correction models, such as MODTRAN model, FLAASH model and6S model, in order to find the most effective atmospheric correction way for different data source. By comparing, showed that FLAASH model is more effective than6S model in atmospheric correction of non-thermal band, and MODTRAN model is more accurate than6S model in simulation atmospheric profiles of thermal band. And the atmospheric profiles data can provide accurate estimated parameters for quantitative remote sensing inversion.This paper study of sea surface temperature inversion method for different data sources based on atmospheric correction. The algorithm based on existing surface temperature inversion method is improved, such as single-window algorithm and split window algorithm, the inversion methods which are applicable to different thermal radiation data is proposed, and a case study of sea surface temperature around Yueqing Power Plants is studied.By comparing the remote sensing inversion result of before and after Yueqing Power Plants working, this paper show that, after plants operation, the temperature rise strength of HYPP in east shore is higher than ZYPP in west shore because of the different plants installed capacity; and the influence region of ZYPP is bigger than HYPP because of the impact of bay terrain and flow direction. Due to the power plants, the harbor around them had an increasing zone with the highest temperature rise of4.5℃in winter, but the rise region of higher than3℃were only in0.35km2, just a small influence range; And the impact of sea surface temperature rise around plants were been steady, range between+/-0.5℃, since the plants in operation. The inversion result of ETM+and IRS based on modified single-window algorithm were more accurate than MODIS based on modified split-window algorithm, the deviation is smaller, so they are more suitable for small-scale sea surface temperature inversion. Thereby, the high temporal resolution of IRS is provide effective support for sea surface temperature real-time monitoring.