Improved Mono-Window Algorithm to Retrieve Lake Surface Temperature Using HJ-IRS Thermal Infrared Data
Remote sensing data has an important application value and scientific significance .in retrieval of lake surface temperature (LST). On September 6, 2008, China successfully launched two optical small satellites (respectively called HJ-lA, HJ-IB.) to monitor and predicate environment and disaster. HJ-lB satellite includes an infrared camera (TRS). The camera has a thermal infrared band which can dynamically monitor LST of large river basins in 4 days. HJ-IRS is a new sensor, so there are few papers researching on the retrieval of LST.The main goal of this paper is to introduce a practical method to obtain LST from HJ-IRS thermal data. In this paper, we reviewed primary algorithms of LST retrieval and mainly analyzed Qins mono-window algorithm retrieving LST from Landsat TM6 (Thematic Mapper) thermal data. This algorithm included two empirical relationships about atmospheric transmittance and atmospheric average temperature. But these relationships are only suitable for TM6. So on the basis of the spectral response function of HJ-IRS thermal band we use radiance transfer software MODTRAN4 to simulate and calculate new coefficients in the two relationships. New algorithm requires three parameters: emissivity, vertical water vapor column and atmosphenc temperature about 2 meters above the ground. We use two images of Lake Taihu to retrieve LST and validate the improved algorithm. Bias of LST retrieved from HJ-IRS data and the field measurements are smaller than 1.2K which means this algorithm is applicable for HJ-IRS thermal band to retrieve LST.
lake surface temperature mono-window algorithm MODTRAN HJ-IRS
Liang Shanshan Li Junsheng Zhang Bing Zhang Hao Shen Qian
Center for Earth Observation and Digital Earth Chinese Academy of Science CEODE Beijing, China Center for Earth Observation and Digital Earth Chinese Academy of Science CEODE Beijing,China
国际会议
昆明
英文
258-262
2010-10-17（万方平台首次上网日期，不代表论文的发表时间）