Estimation of soil moisture using optical/thermal infrared remote sensing in the Canadian Prairies

A new approach to estimate soil moisture (SM) based on evaporative fraction (EF) retrieved from optical/thermal infrared MODIS data is presented for Canadian Prairies in parts of Saskatchewan and Alberta. An EF model using the remotely sensed land surface temperature (Ts)/vegetation index concept was modified by incorporating North American Regional Reanalysis (NAAR) Ta data and used for SM estimation. Two different combinations of temperature and vegetation fraction using the difference between Ts from MODIS Aqua and Terra images and Ta from NARR data (Ts−Ta Aqua-day and Ts−Ta Terra-day, respectively) were proposed and the results were compared with those obtained from a previously improved model (ΔTs Aqua-DayNight) as a reference. For the estimation of SM from EF, two empirical models were tested and discussed to find the most appropriate model for converting MODIS-derived EF data to SM values. Estimated SM values were then correlated with in situ SM measurements and their relationships were statistically analyzed. Results indicated statistically significant correlations between SM estimated from all three EF estimation approaches and field measured SM values (R² = 0.42–0.77, p values < 0.04) exhibiting the possibility to estimate SM from remotely sensed EF models. The proposed Ts−Ta MODIS Aqua-day and Terra-day approaches resulted in better estimations of SM (on average higher R² values and similar RMSEs) as compared with the ΔTs reference approach indicating that the concept of incorporating NARR Ta data into Ts/Vegetation index model improved soil moisture estimation accuracy based on evaporative fraction. The accuracies of the predictions were found to be considerably better for intermediate SM values (from 12 to 22 vol/vol%) with square errors averaging below 11 (vol/vol%)². This indicates that the model needs further improvements to account for extreme soil moisture conditions. The findings of this research can be potentially used to downscale SM estimations obtained from passive microwave remote sensing techniques.     

Fusing MODIS with Landsat 8 data to downscale weekly normalized difference vegetation index estimates for central Great Basin rangelands,USA

Data fused from distinct but complementary satellite sensors mitigate tradeoffs that researchers make when selecting between spatial and temporal resolutions of remotely sensed data. We integrated data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Terra satellite and the Operational Land Imager sensor aboard the Landsat 8 satellite into four regression-tree models and applied those data to a mapping application. This application produced downscaled maps that utilize the 30-m spatial resolution of Landsat in conjunction with daily acquisitions of MODIS normalized difference vegetation index (NDVI) that are composited and temporally smoothed. We produced four weekly, atmospherically corrected, and nearly cloud-free, downscaled 30-m synthetic MODIS NDVI predictions (maps) built from these models. Model results were strong with R² values ranging from 0.74 to 0.85. The correlation coefficients (r ≥ 0.89) were strong for all predictions when compared to corresponding original MODIS NDVI data. Downscaled products incorporated into independently developed sagebrush ecosystem models yielded mixed results. The visual quality of the downscaled 30-m synthetic MODIS NDVI predictions were remarkable when compared to the original 250-m MODIS NDVI. These 30-m maps improve knowledge of dynamic rangeland seasonal processes in the central Great Basin, United States, and provide land managers improved resource maps.     

Snow Cover Monitoring in Qinghai-Tibetan Plateau Based on Chinese Fengyun-3/VIRR Data

Snow cover monitoring in the Qinghai-Tibetan Plateau is very important to global climate change research. Because of the geographic distribution of ground meteorological stations in Qinghai-Tibetan Plateau is too sparse, satellite remote sensing became the only choice for snow cover monitoring in Qinghai-Tibetan Plateau. In this paper, multi-channel data from Visible and Infrared Radiometer (VIRR) on Chinese polar orbiting meteorological satellites Fengyun-3(FY-3) are utilized for snow cover monitoring, in this work, the distribution of snow cover is extracted from the normalized difference snow index(NDSI), and the multi-channel threshold from the brightness temperature difference in infrared channels. Then, the monitoring results of FY-3A and FY-3B are combined to generate the daily composited snow cover product. Finally, the snow cover products from MODIS and FY-3 are both verified by snow depth of meteorological station observations, result shows that the FY-3 products and MODIS products are basically consistent, the overall accuracy of FY-3 products is higher than MODIS products by nearly 1 %. And the cloud coverage rate of FY-3 products is less than MODIS by 2.64 %. This work indicates that FY-3/VIRR data can be reliable data sources for monitoring snow cover in the Qinghai-Tibetan Plateau.     

FY-3C VIRR大气可降水产品生成和检验

风云三号C星(FY-3C)可见光红外扫描辐射计(VIRR)两个红外分裂窗通道数据生成的晴空大气可降水(TPW)产品已投入业务使用。本文介绍了该产品的生成方法,并从产品精度和稳定性两个方面评价产品质量。与MODIS Terra TPW的月平均数据对比,FY-3C VIRR TPW能正确反应大气可降水的全球分布。与2015年3月—4月的全球探空数据对比,FY-3C VIRR TPW均方根误差为5.36 mm,相对误差在水汽值大于30 mm时在20%以内,并且夜间产品精度优于白天。相比于MODIS红外TPW产品与探空数据的误差,FY-3C TPW精度略好。计算2015年1月至2016年7月FY-3C VIRR TPW产品相对探空数据的月均方根误差,19个月均方根误差的标准差是0.54 mm,小于同期MODIS Terra TPW均方根误差的标准差,说明FY-3C VIRR TPW产品在检验时期内更稳定。FY-3C VIRR TPW产品精度较高且质量稳定,具备广泛应用能力。     

基于蒸渗仪的蒸散量时间尺度扩展方法对比

蒸散量（ET,Evapotranspiration）时间尺度扩展方法模拟效果受多种因素影响。本文利用蒸渗仪实测的冬小麦生育期ET数据,对比分析基于蒸发比、作物系数和冠层阻力的不同ET时间尺度扩展方法的估算效果。结果表明,对小时到日尺度的ET时间扩展而言,利用上午时段（10：00-11：00）的ET实测数据,基于冠层阻力的日ET尺度扩展值估算效果要优于基于蒸发比和作物系数的效果,而利用下午时段（14：00-15：00）的ET实测数据,基于作物系数的日ET尺度扩展值估算效果要优于基于蒸发比和冠层阻力的效果,对于从典型日到生育期尺度的ET时间扩展,基于作物系数的生育期ET尺度扩展值估算效果要好于基于蒸发比和冠层阻力的效果。应根据当地的气候气象条件、作物种植状况、时间尺度扩展类型、土壤水分、ET观测设施种类等因素,择优适宜的ET时间尺度扩展方法。     

利用FY-3C折射率对大气边界层高度的反演与分析

2013年中国发射了首颗进行全球导航卫星系统(global navigation satellite system,GNSS)掩星观测的气象卫星风云3号C星(Fengyun-3C,FY-3C),且已发布自2014年6月以来的FY-3C掩星大气产品,但目前还未见将其应用于大气边界层的相关研究.首次尝试利用FY-3C折射率...     

FY-3A MERSI数据干旱监测能力评价

对FY-3A MERSI数据进行辐射定标、几何定位预处理,与同期MODIS数据预处理结果进行对比;选用温度植被干旱指数法对两种数据进行监测,分析了监测结果的相对精度。实验结果表明,FY-3A MERSI数据的干旱监测结果精度与MODIS数据基本一致,且在空间分辨率及光谱分辨率方面有较大的提高。     

风云三号C星SEM高能粒子数据检验及应用

风云三号C星(FY-3C卫星)空间环境监测器(SEM)可监测轨道高度上的高能带电粒子(质子、电子和重离子)辐射环境及其引起的辐射剂量和表面充电等空间天气效应,是空间天气监测预警业务不可或缺的自主数据源之一。为验证FY-3C卫星高能粒子探测数据的有效性,需开展数据的定量检验工作。本文采用与同类卫星同类数据进行交叉比对的方式来进行检验。首先,根据一定的假设条件,对比对数据进行归一化处理,尽量消除不同卫星间观测时间、空间(星下点经、纬度和高度)、方向和能量范围等差异对高能粒子分布的影响,然后进行比对,最后计算比对数据间的相关系数、斜率和标准偏差等统计参数,并据此评价比对数据的一致性。通过空间天气平静期高能质子和高能电子与NOAA-18和FY-3B卫星数据的交叉比对可以看出,FY-3C卫星高能粒子数据与比对卫星数据具有较好的一致性。由于工作原理和技术指标相同,FY-3C与FY-3B卫星高能粒子数据的一致性更好,也证明了载荷技术状态的稳定性。通过对太阳质子事件和高能电子暴的观测实例证明,FY-3C卫星高能粒子数据能够准确地反映空间天气扰动事件的特征和强度。以上结果表明,FY-3C卫星高能粒子数据可信度较高,能够用于空间天气监测、预警以及研究工作。     

闪电河流域农牧交错带微波遥感土壤水分产品评价

空间网格分辨率为9 km 的 SMAP(Soil Moisture Active and Passive)、0.1D(Degree)的 ASCAT(The Advanced Scatterometer)、25 km 的 FY-3B 以及25 km ESA-CCI(European Space Agency-Climat...     

Downscaling of Land Surface Temperature Maps in the Texas High Plains with the TsHARP Method

High-resolution evapotranspiration (ET) maps can assist demand-based irrigation management. Development of high-resolution daily ET maps requires high-resolution land surface temperature (LST) images. Earth-observing satellite sensors such as the Landsat 5 Thematic Mapper (TM) and MODerate resolution Imaging Spectroradiometer (MODIS) provide thermal images that are coarser than simultaneously acquired visible and near-infrared images. In this study, we evaluated the TsHARP downscaling technique for its capability to downscale coarser LST images using finer resolution normalized difference vegetation index (NDVI) data. The TsHARP technique was implemented to downscale seven coarser scale (240, 360, 480, 600, 720, 840, and 960 m) synthetic images to a 120 m LST image. The TsHARP was also evaluated for downscaling a coarser 960 m LST image to 240 m to mimic MODIS datasets. Comparison between observed 120 m LST images and 120 m LST images downscaled from coarser 240, 360, 480, 600, 720, 840, and 960 m images yielded root mean square errors of 1.0, 1.3, 1.5, 1.6, 1.7, 1.8, and 1.9°C, respectively. This indicates that the TsHARP method can be used for downscaling coarser (960 m) MODIS-based LST images using finer Landsat (120 m) or MODIS (240 m)-derived NDVI images. However, the TsSHARP method should be evaluated further with real datasets before using it for an operational ET remote sensing program for irrigation scheduling purposes.     

Precise orbit determination of the Fengyun-3C satellite using onboard GPS and BDS observations

The GNSS Occultation Sounder instrument onboard the Chinese meteorological satellite Fengyun-3C (FY-3C) tracks both GPS and BDS signals for orbit determination. One month’s worth of the onboard dual-frequency GPS and BDS data during March 2015 from the FY-3C satellite is analyzed in this study. The onboard BDS and GPS measurement quality is evaluated in terms of data quantity as well as code multipath error. Severe multipath errors for BDS code ranges are observed especially for high elevations for BDS medium earth orbit satellites (MEOs). The code multipath errors are estimated as piecewise linear model in \(2{^{\circ }}\times 2{^{\circ }}\) grid and applied in precise orbit determination (POD) calculations. POD of FY-3C is firstly performed with GPS data, which shows orbit consistency of approximate 2.7 cm in 3D RMS (root mean square) by overlap comparisons; the estimated orbits are then used as reference orbits for evaluating the orbit precision of GPS and BDS combined POD as well as BDS-based POD. It is indicated that inclusion of BDS geosynchronous orbit satellites (GEOs) could degrade POD precision seriously. The precisions of orbit estimates by combined POD and BDS-based POD are 3.4 and 30.1 cm in 3D RMS when GEOs are involved, respectively. However, if BDS GEOs are excluded, the combined POD can reach similar precision with respect to GPS POD, showing orbit differences about 0.8 cm, while the orbit precision of BDS-based POD can be improved to 8.4 cm. These results indicate that the POD performance with onboard BDS data alone can reach precision better than 10 cm with only five BDS inclined geosynchronous satellite orbit satellites and three MEOs. As the GNOS receiver can only track six BDS satellites for orbit positioning at its maximum channel, it can be expected that the performance of POD with onboard BDS data can be further improved if more observations are generated without such restrictions.     

Scrutinising MODIS and GIMMS Vegetation Indices for Extracting Growth Rhythm of Natural Vegetation in India

Satellite derived vegetation vigour has been successfully used for various environmental modeling since 1972. However, extraction of reliable annual growth information about natural vegetation (i.e., phenology) has been of recent interest due to their important role in many global models and free availability of time-series satellite data. In this study, usability of Moderate Resolution Imaging Spectro-radiometer (MODIS) and Global Inventory Modelling and Mapping Studies (GIMMS) based products in extracting phenology information about evergreen, semi-evergreen, moist deciduous and dry deciduous vegetation in India was explored. The MODIS NDVI and EVI time-series data (MOD13C1: 5.6 km spatial resolution with 16 day temporal resolution—2001 to 2010) and GIMMS NDVI time-series data(8 km spatial resolution with 15 day temporal resolution—2000 to 2006) were used. These three differently derived vegetation indices were analysed to extract and understand the vegetative growth rhythm over different regions of India. Algorithm was developed to derive onset of greenness and end of senescence automatically. The comparative analysis about differences in the results from these products was carried out. Due to dominant noise in the values of NDVI from GIMMS and MODIS during monsoon period the phenology rhythm were wrongly depicted, especially for evergreen and semi-evergreen vegetation in India. Hence, care is needed before using these data sets for understanding vegetative dynamics, biomass cestimation and carbon studies. MODIS EVI based results were truthful and comparable to ground reality. The study reveals spatio-temporal patterns of phenology, rate of greening, rate of senescence, and differences in results from these three products.     

Regional scale evapotranspiration estimation using satellite derived albedo and surface temperature

In the studies reteted to surface energy balance, satellite data provides important inputs for estimating regional surface albedo and evapotranspiration. The paper describes the use of satellite data in determining the surface emissivity over heterogeneous a’reas by taking Normalized Difference Vegetation Index (NDVI) as modulating parameter at pixel resolution. The estimated emissivity values have been used to find the surface temperature at the pixel scale. Landsat-TM-visible, NIR, TIR bands data and some ground meteorological data have been used in an energy balance model for estimating surface albedo and evapotranspiration. The ET values derived from the model are in good agreement with the values obtained with. ‘CENTURY MODEL’ and ground observations over the area, suggesting the possible use of this approach fot regional scale studies on evapotranspiration.     

风云静止卫星地表温度产品空值数据稳健修复

静止卫星地表温度数据是研究昼夜气候和环境变化的重要参数。但现有发布的静止卫星地表温度数据由于受到云等大气因素的影响,往往出现数值缺失现象。针对该问题,提出基于昼夜变化模型的风云静止卫星地表温度空值数据的稳健修复方法。由多项式、傅里叶函数和高斯函数构建新的昼夜变化模型,并利用LevenbergMarquardt算法进行模型参数的求解与优化,进而实现空值修复。以风云2号F星数据(FY-2F)为例,模拟不同类型的像元缺失情况进行修复,并将不同模型修复结果与真实温度值比较,同时也对真实数据进行了测试。结果表明:本文提出的修复方法能有效对温度空值数据修复,且优于传统方法。     

FY-3B/MWRI和Aqua/AMSR-E海冰密集度比较及印证

本文对2011-07-01—2011-09-30风云三号B星(FY-3B)搭载的微波成像仪MWRI(Microwave Radiometer Imager)和Aqua卫星搭载的微波扫描辐射计AMSR-E(Advanced Microwave Scanning Radiometer for Earth Observing System)观测数据获取的海冰密集度产品进行比较及印证。首先,逐日比较FY-3B/MWRI和Aqua/AMSR-E区域平均海冰密集度;其次,逐月比较FY-3B/MWRI和Aqua/AMSR-E月平均海冰密集度;最后,使用Aqua卫星搭载的中等分辨率成像光谱辐射计MODIS数据进行印证。MWRI和AMSR-E比较结果为(1)MWRI与AMSR-E逐日区域平均海冰密集度变化趋势一致,MWRI海冰密集度均高于AMSR-E,7—9月MWRI与AMSR-E逐日平均偏差月平均值分别为8.55%、7.67%、2.58%,逐日标准差月平均值分别为12.16%、12.08%、10.43%,二者差异逐月减小。(2)MWRI与AMSR-E月平均海冰密集度差呈现逐月递减趋势,7—9月MWRI与AMSR-E逐月平均偏差分别为7.37%、6.53%、1.51%,逐月标准差分别为4.61%、4.36%、3.64%,MWRI与AMSR-E差异逐月减小的原因是二者在密集度较低的边缘区域差异较大,而夏季随着边缘区域海冰的融化,二者差异逐渐减小。MWRI和AMSRE海冰密集度与MODIS印证结果为:(1)密集度小于95%情况下,MWRI与AMSR-E海冰密集度均比MODIS偏高,AMSR-E更接近MODIS,MWRI高估,误差较大。(2)密集度大于等于95%情况下,MWRI与AMSR-E海冰密集度均比MODIS偏低,AMSR-E偏低更多,MWRI结果更好。     

FY-3C无线电掩星折射率廓线的反演及验证

2013年,中国发射了首颗进行全球导航卫星系统(global navigation satellite system,GNSS)无线电掩星观测的气象卫星FY-3C,其掩星数据产品已由国家卫星气象中心(national satellite meteorological center,NSMC)发布。基于FY-3C附加相位数据,通过几何光学反演和全谱反演相结合的方法自主反演获取大气折射率廓线,并利用NSMC提供的折射率产品和欧洲中期天气预报中心(European Centre for Medium-Range Weather Forecasts, ECMWF)的气候再分析数据集(ECMWF reanalysis-interim,ERA-Interim)对反演结果进行验证。2017年全年FY-3C掩星折射率自主反演的成功率为82%,与NSMC 83.5%的反演成功率基本一致。以ERA-Interim再分析资料为参考,自主反演折射率相对偏差绝对值在25 km以下,小于1.5%,略优于NSMC产品,但偏差标准差比NSMC产品略大,达到了3.6%。自主反演和NSMC的折射率廓线在高纬地区的相对偏差...     

Monitoring global land surface drought based on a hybrid evapotranspiration model

The latent heat of evapotranspiration (ET) plays an important role in the assessment of drought severity as one sensitive indicator of land drought status. A simple and accurate method of estimating global ET for the monitoring of global land surface droughts from remote sensing data is essential. The objective of this research is to develop a hybrid ET model by introducing empirical coefficients based on a simple linear two-source land ET model, and to then use this model to calculate the Evaporative Drought Index (EDI) based on the actual estimated ET and the potential ET in order to characterize global surface drought conditions. This is done using the Global Energy and Water Cycle Experiment (GEWEX) Surface Radiation Budget (SRB) products, AVHRR-NDVI products from the Global Inventory Modeling and Mapping Studies (GIMMS) group, and National Centers for Environmental Prediction Reanalysis-2 (NCEP-2) datasets. We randomly divided 22 flux towers into two groups and performed a series of cross-validations using ground measurements collected from the corresponding flux towers. The validation results from the second group of flux towers using the data from the first group for calibration show that the daily bias varies from −6.72 W/m² to 12.95 W/m² and the average monthly bias is −1.73 W/m². Similarly, the validation results of the first group of flux towers using data from second group for calibration show that the daily bias varies from −12.91 W/m² to 10.26 W/m² and the average monthly bias is −3.59 W/m². To evaluate the reliability of the hybrid ET model on a global scale, we compared the estimated ET from the GEWEX, AVHRR-GIMMS-NDVI, and NECP-2 datasets with the latent heat flux from the Global Soil Wetness Project-2 (GSWP-2) datasets. We found both of them to be in good agreement, which further supports the validity of our model's global ET estimation. Significantly, the patterns of monthly EDI anomalies have a good spatial and temporal correlation with the Palmer Drought Severity Index (PDSI) anomalies from January 1984 to December 2002, which indicates that the method can be used to accurately monitor long-term global land surface drought.     

基于MODIS产品影像及陆面能量平衡系统(SEBS)的河北平原区域蒸散估算

地表蒸散是区域水文循环的重要组成部分之一,传统的地表蒸散估算一般基于点上的气象观测数据,当用于区域地表蒸散评价时,具有一定的局限性.随着遥感技术的发展,利用遥感影像能够对大区域进行观测的优势进行区域地表蒸散估算已成为可能.地表能量平衡系统(SEBS)是根据地表能量平衡估算地表蒸散量的一种方法,该方法由于提出了地表能量传输过程中关键制约因素热传导粗糙度的估算模型而在遥感蒸散计算方面具有较高的精度.本文在SEBS模型的基础上,以河北平原为例,采取中分辨率成像光谱辐射仪(MODIS)产品影像,根据研究区下垫面的实际情况进行了参数估算,进行了区域实际蒸发蒸腾量计算及模型精确度评价,并在SEBS模型的基础上,提出了新的"标准化温度差-反照率"特征空间分析方法,对研究区内地表土壤水分现状进行了评价;最后,对河北平原地表蒸散时空分布进行了分析.计算结果表明,在所选取的晴空乌云条件下,根据SEBS模型计算所得的地表蒸散与研究区内利用大型承重式蒸渗仪所测量的地表实际蒸散量具有很好的一致性,说明SEBS模型在遥感蒸散计算方面据有较高的可信度.然而,由于地表蒸散的遥感估算是以所获取的遥感影像单元为基础,计算误差不可避免,尤其是使用低分辨率遥感影像的时候,每个影像单元所反映的地表蒸散为单元内各种地表覆盖的综合反映,当与只反映一种地表覆盖蒸散的大型承重式蒸渗仪测量结果进行比较时,误差是显而易见的,因此,若着重考虑模型精度验证,尚需在以后的研究中考虑使用高分辨率的遥感影像.地表土壤水分或湿度状况是地表能量交换及蒸散发生的主要控制因素.利用地表温度与植被指数的关系对区域地表湿度状况进行监测在实践中被广泛利用,然而,由于不用地区地表属性的千差万别,当利用这种方法进行区域地表湿度评价时,"地表温度-植被指数"特征空间的边界很难确定.本文在SEBS模型的基础上,提出新的"标准化温度差-反照率"特征空间分析方法,对研究区内地表土壤水分现状进行评价,结果显示,由于在SEBS模型中考虑了干限和湿限两种极端情况下的能量平衡,"标准化温度差.反照率"特征空间的边界问题很容易被确定,利用修正的特征空间,可以对区域土壤水分或湿度状况进行客观的评价.下垫面的几何特征参数的精确反演是进行地表能量平衡模拟的基础,目前多根据有关经验公式利用遥感影像进行下垫面几何特征参数估算,由于已有的经验公式多基于不同研究区域获得,当应用到新的研究区时,其具体参数需要进一步调整,以获得对下垫面的几何特征的精确描述.由于缺乏相关实测资料,本研究中利用经验公式进行下垫面几何特征参数,误差不可避免,需要在以后的研究中进行深入探索.另外,地表蒸散的计算只是进行区域水资源评价、农业节水措施评价以及全球变化等研究的一个中间环节,需要在以后的研究中根据具体研究目的进行进一步研究.     

风云三号卫星被动微波反演海洋上空云液态水含量

云液态水含量是气候和水循环研究的重要云微物理参数，也是目前气候变化研究中的最不确定因素之一。通过极轨气象卫星被动微波观测的光谱和极化特征能够实现对云液态水含量的直接测量，本文介绍了一种基于风云三号卫星微波成像仪（MWRI）观测亮温的全天候云液态水含量反演算法，利用快速辐射传输模式、云模型和大气廓线库建立MWRI模拟亮温库并训练反演系数的宽气候态物理算法可以保证算法系数在不同季节和不同地区的适应性。同时提出了一种基于观测增量（O-B）筛选晴空像元并对算法系数及比例因子进行订正的方法。利用统计直方图方法和卫星间交叉比对方法对反演产品精度进行了检验，统计直方图方法检验结果表明，FY-3C云水反演误差为0.028 mm，FY-3D为0.025 mm，与国外同类产品的精度相当；与低轨卫星微波辐射计GMI云水产品的交叉比对结果表明，两者具有较高一致性，均方根误差为0.0325 mm。FY-3C/3D CLW产品目前已经投入业务应用，上下午星组网能够一天内基本覆盖全球，实现全球云水分布监测。     

数据驱动的蒸散发遥感反演方法及产品研究进展

蒸散发是水圈、大气圈和生物圈中水分循环和能量交换的纽带。在全球尺度上,蒸散发约占陆地降水总量的60%;作为其能量表达形式,潜热通量约占地表净辐射的80%。随着通量观测技术的发展,全球长期持续的观测数据得以获取和共享,近年来基于数据驱动的蒸散发遥感反演方法取得了较好的研究进展。本文针对数据驱动的蒸散发遥感反演方法和产品,从经验回归、机器学习和数据融合3个方面展开,对现有的研究进展进行了梳理、归纳和总结,并从驱动数据、反演方法、已有产品等方面指出目前仍存在的问题和不足。未来仍需开展数据驱动的高时空分辨率的蒸散发遥感反演方法的研究,有效考虑地表温度和土壤水分等可以指示地表蒸散发短期变化的重要信息,同时加强基于过程驱动的物理模型与数据驱动的模型的结合,使两类模型能互为补充、各自发挥所长,共同推动蒸散发遥感反演研究水平的进步。