【摘要】 介绍了"黑河综合遥感联合试验"在水文和生态变量与参数反演、估算和模型应用方面取得的进展。在水文变量遥感方面,利用车载双偏振多普勒雷达在黑河上游和中游分别开展了高精度降水观测,获取了后向散射系数和极化信息与降水强度之间的定量关系。在综合利用多源观测信息,改进和发展蒸散发估算模型方面取得了实质性的进展。发展了利用K和Ka波段机载微波辐射计数据反演山区积雪深度的方法。针对SAR观测数据反演土壤水分中地表粗糙度的显著干扰,发展了消除粗糙度影响的反演方法。在生态过程遥感参量估算方面,提出了一种基于机载激光雷达和高分辨率光学影像的高精度地物信息分类方法。发展了从高光谱航空遥感提取植被自然光照下的荧光,并与NDVI结合的C3/C4植被分类方法。发展和改进了使用多角度、多光谱观测反演叶面积指数的方法,挖掘了激光雷达在植被垂直结构探测上的潜力,探索了叶面积指数遥感中的尺度转换规律。发展了利用高光谱数据中的荧光信息反演光能利用率的新方法;建立了考虑土壤反射率、冠层结构等因素的光合作用有效辐射比率反演模型;改进了利用遥感估计生态系统生产力的模型。发展了利用高光谱遥感数据提取叶绿素含量和叶绿素荧光强度的方法。更多还原

【Abstract】 This paper reviewed and summarized the progresses on the remote sensing-based inversion and estimation of hydrological and ecological variables/parameters,within the framework of the Watershed Allied Telemetry Experimental Research(WATER) project.We make progresses in remote sensing of hydrological variables as follows:The basin-scale precipitation observation with high accuracy are carried out with a truck-mounted dual polarized Doppler radar in the upstream and midstream of the Heihe River basin,aiming to obtain the quantitative relationship between the precipitation rate,radar reflectivity and its polarization information.The substantial developments and improvements of remote sensing estimation models of evapotranspiration are achieved with the aid of multi-source observations.A retrieval algorithm of snow depth in the mountainous area is developed by using the K and Ka band airborne microwave radiometry.The method to eliminate the influence of surface roughness on soil moisture remote sensing is proposed by using the multi-angles SAR data.We also succeed in the remote sensing estimation of ecological-process variables/parameters as follows:Fine land surface classification method is developed by combining information from airborne laser radar and high-resolution optical images.The C3/C4 vegetation functional type classification is realized by integrating the vegetation fluorescence under solar light condition extracted from the hyper-spectral airborne remote sensing images,and NDVI information.The methods using multi-angles and multi-spectrums remote sensing information to retrieve the LAI are improved,especially exploiting the potential of LiDAR to obtain the vegetation vertical structure,and the scale conversion of remote sensing based LAI is also explored.Other progresses include developing a new method to retrieve light-use efficiency using fluorescence information from hyperspectral data,proposing an inversion model of FPAR taking the soil reflectance and canopy structure into considerations,improving the remote sensing estimation model of ecosystem productivity and developing a method to obtain chlorophyll content and chlorophyll fluorescence intensity by using hyper-spectral remote sensing data.更多还原