利用MODIS近红外数据反演大气水汽含量研究

Precipitable Water Vapor Retrieval with MODIS Near Infrared Data

大气水汽含量（precipitable water vapor,PWV）对遥感定量化及生态环境方面研究具有重要意义。针对传统水汽探测方法存在的问题,提出一种基于多通道表观反射率的ICIBR（improved continuum interpolated band ratio）水汽遥感反演方法。该方法结合MODIS数据第17,18和19三个近红外通道的水汽吸收特点,利用MODTRAN模型模拟大气含水量与三个通道ICIBR之间的关系,构建了适用于MODIS数据的ICIBR大气水汽含量定量反演模型。基于提出的ICIBR水汽反演方法,选择北美洲南部典型干旱、半干旱区德克萨斯州、俄克拉荷马州等地区为研究区,使用不同时间的四期MODIS 1B数据进行水汽反演实验。同时,选择SuomiNet提供的GPS水汽地基观测数据对反演结果进行精度验证以及MODIS大气水汽产品（MOD05）进行对比评价。验证和对比结果表明：该算法水汽反演结果与GPS水汽实测数据具有较高的一致性（r=0.967）,均方根误差为0.276 cm,有71.08%的观测点对满足水汽反演误差精度（EE～±0.05＋0.15PWV（gps））要求,同时与MOD05大气水汽产品相比,该方法在反演精度和准确估计方面有了较大提高,能够有效降低61%的水汽反演高估现象。该方法较传统算法更为简易、实用,具有较高的整体水汽反演精度。

Precipitable water vapor（PWV） shows great significance in remote sensing quantitative application and ecological research.Aiming at solving the problems of traditional methods,an Improved Continuum Interpolated Band Ratio（ICIBR） algorithm was proposed based on the ratios of apparent reflectance of multi-channels in this paper.The ICIBR algorithm considers the absorption characteristics of water vapor absorption in three MODIS near infrared channels（Bands 17,18 and 19） and the relationship between the PWV and the ICIBRs of above three channels were simulated by using the MORTRAN model.Then the PWV retrieval model for MODIS data was constructed.Texas,Oklahoma region,a typical arid/semi-arid areas,located in North South America were selected as the study area and four different MODIS IB data were obtained to perform PWV retrieval experiments using the ICIBR algorithm.Last,the corresponding GPS PWV ground observation data provided by SuomiNet and the MODIS PWV product（MOD05） were obtained to verify the experiment results.Evaluation and comparison results showed that the PWV retrievals showed a higher consistency（r=0.967） with the GPS ground measured PWV data with smaller RMSE～0.276 cm and a total of 71.08%of observation points falling within PWV Expected Errors（EE～±0.05 ＋ 0.ISPWV（Gps））.Moreover,the ICIBR algorithm showed an obviously great improvement in PWV estimation,which can effectively reduce 61%overestimation of PWV retrievals than MOD05 PWV products.This new algorithm is more simple and practical with an overall more reliable retrieval accuracy.