Integrating ASTER and GLASS broadband emissivity products using a multi-resolution Kalman filter

In this study, the multi-resolution Kalman filter (MKF) algorithm, which can handle multi-resolution problems with high computational efficiency, was used to blend two emissivity products: the Global LAnd Surface Satellite (GLASS) (BBE) product and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) narrowband emissivity (NBE) product. The ASTER NBE product was first converted into a BBE product. A new detrending method was used to transfer the BBEs into a process suitable for the MKF. The new detrending method was superior to the two existing methods. Finally, both the de-trended GLASS and ASTER BBE products were incorporated into the MKF framework to obtain the optimal estimation at each scale. Field measurements collected in North America were used to validate the integrated BBEs. Visually, the fusion map showed good continuity, with the exception of the border areas, and the quality of the fusion map was better than that of the original maps. The validation results indicate that the MKF improved the BBE product accuracy at the coarse scale. In addition, the MKF was capable of recovering missing pixels at a finer scale.     

Integrated approach of using ASTER-derived emissivity and pixel temperature for delineating different granitoids – a case study in parts of Dharwar Craton,India

We have delineated different granitoids based on variation in emissivity and relative surface temperature recorded in thermal bands of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor of EO-1 satellite. In this regard, we have used emissivity normalization algorithm to derive broadband emissivity from thermal bands of ASTER sensor to delineate different lithounits of the granitoid family. We have compared emissivity and radiance image composites in terms of delineation of different granitoids. We have also used false colour composite (FCC) image derived using two emissivity bands and temperature (derived using emissivity normalisation method) bands to delineate different granitoids. We could differentiate different granitoids in the three-dimensional (3D) data space of ASTER-derived emissivity bands (second and third bands) and temperature bands. Based on the analysis of 3D scatter plot, we also proposed a ternary diagram of emissivity and temperature, which can be used to delineate different granitoids.     

多频率多极化地表辐射参数化模型

发展了针对对地观测系统被动微波辐射计AMSR-E应用的裸露地表辐射模型。首先，利用1993年法国INRA地面试验数据对AIEM在宽波段高频率和大角度的辐射信号模拟能力进行评价。验证结果表明，AIEM模型模拟值与地面实测数据吻合很好，说明AIEM模型能很好模拟宽波段和大角度的辐射信号。在此基础上，用AIEM模型建立了一个针对AMSR-E传感器参数配置．包含各种地表粗糙度和介电特性的裸露地表辐射模拟数据库。利用AIEM模拟数据和地面实测数据对目前人们使用的半经验地表模型进行了比较和分析，发展了多频率多极化的地表辐射参数化模型——Qp模型。该模型中，地表粗糙度对辐射信号的影响通过粗糙度参数Qp来表示。参数Qp可简单表示为均方根高度与相关长度的比值（s／l）。从Qp模型与AIEM模型模拟的发射率比较结果来看，它们之间的绝对误差很小，不超过10^-3因而，本文发展的参数化模型可用作模拟地表辐射的前向模型，如用于估算AMSR-E传感器的亮温值，同时模型的发展有利于提高人们对辐射机制的理解和认识。     

利用时空信息的单波段地表温度遥感反演

地表温度被认为是影响生态系统的关键因子之一,它与许多地表过程有关。目前,热红外卫星遥感技术是获取有关区域和全球尺度地表温度信息的一个有效、可行的手段。针对不同卫星上搭载的热红外传感器,许多学者开展了大量的研究,其中针对单波段热红外的特点(如Landsat TM/ETM+,CBERS和HJ-1B)提出了单通道(或单窗)算法。该类算法需要准确的地表比辐射率和大气参数(如大气水分含量)。这些参数在现实中又很难轻易获得,从而在一定程度上限制了现有算法的应用。针对HJ-1B高回访频率的特点,本文提出了利用多时相影像的时空信息来直接反演地表温度的Multi-Temporal and Spatial Information-Based Single Channel(MTSC),以解决现有算法对地表比辐射率和大气参数的过度依赖性。实例分析结果显示,基于MTSC法由HJ-1B反演得到的地表温度结果与MODIS地表(陆表和海表)温度产品具有很好的空间一致性;HJ-1B的陆表温度结果总体上被高估了约1 K,而海表温度结果总体上被高估了0.5 K;同时,MTSC法得到的HJ-1B地表温度结果具有更好的细节和空间完整性。最后,通过分析和讨论指出了一些可能的完善途径,如相似像元的确定、修改优化求解中的目标函数、参数的自适应初始化等,以便提高MTSC法的反演精度和实用性。     

基于Clementine热红外数据的Apollo17登月点区域氧化钙含量反演

为了研究利用Clementine热红外数据反演月球表面岩石的氧化钙(Ca O)含量,论文选取了两景覆盖Apollo17登月点的Clementine热红外影像,将其覆盖的区域选为研究区。利用月球表面温度物理模型模拟月表温度,结合普朗克函数,完成发射率反演。在此基础上,对LPI中35个除Apollo17登月计划外所采集的样品Ca O含量与其热红外发射率特征做回归统计分析,发现存在很好的线性关系(R2=0.661)。由此,基于Clementine热红外发射率实现了研究区Ca O含量反演。通过利用LPI Apollo17月岩(壤)样品实际Ca O含量分析数据对反演结果进行精度评价,发现8组反演值与实际值的相对误差最小为1.77%,最大为9.29%,均方根误差为0.767。研究结果表明,使用发射率进行Ca O含量反演方法可行,为利用Clementine热红外数据对月表矿物成分含量定量反演提供一种新的思路。     

红外高光谱资料近地面通道应用

由于下垫面的复杂性,卫星近地面通道的辐射率资料没有得到充分开发和利用。就我国自主研发的GRAPES 3DVar而言,红外高光谱近地面通道资料还没有应用于陆地,即使在下垫面相对简单的海洋,由于背景场海表温度估计不够准确,红外高光谱资料的使用效果也不甚理想。针对GRAPES模式的背景场海表温度估计不够准确这一问题,本文利用大气红外探测仪器AIRS(The Atmospheric Infrared Sounder)辐射率观测资料通过一维变分（1DVar）方法对其晴空视场点内的背景场海表温度进行调整,再运用GRAPES全球分析预报系统进行同化分析,研究了海表温度调整后对分析场的影响。结果表明,利用一维变分调整后的海表温度不仅使得低层通道的模拟亮温与观测亮温更加匹配,而且有效地改进了分析场,对位势高度场高、中、低层均有不错的改进,对低层湿度场以及风场的改进也较为明显。     

利用不同地表比辐射率对ETM＋数据地表温度反演对比研究

地表温度作为研究环境生态影响的一个重要指标之一,以Landsat ETM+的热红外波段作为数据源,辅助大气透过率、大气平均气温等参数,利用单窗算法基于混合像元、NDVI、植被和裸露地三种不同地表比辐射率反演泉州市地表温度,对比分析结果表明采用这三种地表比辐射率反演地表温度的方法均是可行的,对于具体采用哪一种地表比辐射率应需要结合实际的研究区域地表地物的实际监测地表温度进行对比后,方可选择合适的地表比辐射率进行地表温度反演,会更具实际意义。反演结果可为城市热岛效应等研究提供支持数据源。     

中巴地球资源卫星数据反演地表温度产品设计

利用CBERS IRMSS/IRS传感器红外通道数据,基于MODTRAN4和查找表算法,根据地表数字高程和全球/区域一体化数值预报模式,建立相应高度和气象条件下温度反演配套系数,利用CBERS可见/近红外通道和地表比辐射率数据库最终生成地表温度/地表发射率产品。最后介绍了温度产品的验证工作,并对温度反演中存在的参数敏感性和不确定性问题进行了分析。     

Consistency of precipitation products over the Arabian Peninsula and interactions with soil moisture and water storage

The regional-scale consistency between four precipitation products from the GPCC, TRMM, WM, and CMORPH datasets over the Arabian Peninsula was assessed. Their macroscale relationships were inter-compared with soil moisture and total water storage (TWS) estimates from AMSR-E and GRACE. The consistency analysis was studied with multivariate statistical hypothesis testing and Pearson correlation metrics for the period from January 2000 to December 2010. The products and GRACE estimates were assessed over a representative sub-domain (United Arab Emirates) with available in situ well observations. Next, geographically temporally weighted regression (GTWR) was employed to examine the interdependencies among the peninsula’s hydrological components. The results showed GPCC-TRMM recording the highest correlation (0.85) with insignificant mean differences over more than 90% of the peninsula. The highest GTWR predictive performance of TWS (R² = 0.84) was achieved with TRMM forcing, which indicates its potential to monitor changes in TWS over the arid peninsular region.     

基于热红外光谱的干旱区土壤盐分监测研究

土壤盐渍化是新疆最常见的土地退化过程,已经严重威胁到了当地的农业生产、生态稳定和经济发展。通过对渭库绿洲土壤含盐量和土壤热红外光谱分析,探讨了土壤含盐量与热红外发射率之间的定量关系。结果表明：（1）盐渍化土壤的发射率随着含盐量的变化而发生变化,当土壤盐分增加时,发射率也随之增大。（2）土壤含盐量与热红外发射率光谱数据相关性在8.5～9.5 μm波段范围内表现尤为显著,相关系数超过0.8,最高为0.90,对应波段范围9.259～9.271 μm。（3）运用回归模型一阶导数变换形式下建模效果和预测精度都是最优的,R²达到了0.899,RMSE最小为1.734。热红外光谱技术可以反演土壤含盐量,为利用热红外遥感识别土壤盐分信息提供技术支撑。