遥感技术在陆面过程研究中的应用进展

探讨了当前陆面过程 (LSP)研究的特点 ,指出遥感在陆面过程研究中的应用以及陆面过程国际合作实验是突出的特点 ,进而对遥感技术的陆面参数获取、地表能量通量的计算以及与 LSP模式的结合研究及进展进行了综述。根据不同特征的地表参数选择光学遥感或微波遥感已成共识 ,而综合利用不同遥感数据获取同一种地表参数也已成为研究热点 ,当前及今后发射的携载多种遥感仪器的众多遥感卫星为此项研究提供了条件 ;遥感与 LSP模式的结合研究是遥感在陆面过程研究中深入应用的一个方面 ,国际陆面过程合作实验是这项研究的重要保证。     

土壤水分与干旱遥感研究的进展与趋势

对土壤水分和干旱遥感监测的国内外发展情况进行了回顾,依据土壤水分和干旱遥感监测的原理,围绕着可见光与近红外、热红外、微波光谱波段的使用,分别以土壤和植被为观测对象,对国内外土壤水分与干旱遥感现状与发展趋势进行讨论。重点对微波遥感土壤湿度的算法发展和研究趋势进行了较详细的论述。在总结国内外土壤水分遥感监测研究实验中所用过的方法与原理的基础上,对目前遥感监测土壤水分研究领域的重点、难点和未来的发展方向进行了评述。土壤水分遥感监测是一个复杂的间接过程,波段及变量选择、传感器的性能等因素对土壤水分监测是至关重要的,土壤的各种理化性状、地形的分异作用以及气候变化和人为的土壤管理措施对土壤水分均有不同的影响,地表特征与土壤水分也存在着一定的相关性。改进的热惯量法和作物缺水指数法是当前土壤水分遥感监测中较为成熟的方法。GIS技术的广泛应用、土壤水分遥感监测模型的优化。微波遥感的应用将是该领域的重点研究方向。     

Estimation of improved resolution soil moisture in vegetated areas using passive AMSR-E data

Microwave remote sensing provides a unique capability for soil parameter retrievals. Therefore, various soil parameters estimation models have been developed using brightness temperature (BT) measured by passive microwave sensors. Due to the low resolution of satellite microwave radiometer data, the main goal of this study is to develop a downscaling approach to improve the spatial resolution of soil moisture estimates with the use of higher resolution visible/infrared sensor data. Accordingly, after the soil parameters have been obtained using Simultaneous Land Parameters Retrieval Model algorithm, the downscaling method has been applied to the soil moisture estimations that have been validated against in situ soil moisture data. Advance Microwave Scanning Radiometer-EOS BT data in Soil Moisture Experiment 2003 region in the south and north of Oklahoma have been used to this end. Results illustrated that the soil moisture variability is effectively captured at 5 km spatial scales without a significant degradation of the accuracy.     

Remote sensing of soil moisture: implications for groundwater recharge

Remote sensing provides information on the land surface. Therefore, linkages must be established if these data are to be used in groundwater and recharge analyses. Keys to this process are the use of remote sensing techniques that provide information on soil moisture and water-balance models that tie these observations to the recharge. Microwave remote sensing techniques are used to map the spatial domain of surface soil moisture and to monitor its temporal dynamics, information that cannot be measured using other techniques. The physical basis of this approach is presented with examples of how microwave remote sensing is utilized in groundwater recharge and related studies. Electronic Publication     

卫星遥感反演土壤水分研究综述

土壤水分是影响地表过程的核心变量之一。精准地测量土壤水分及其时空分布,长期以来是定量遥感研究领域的难点问题。简要回顾基于光学、被动微波、主动微波和多传感器联合反演等卫星遥感反演土壤水分的主要反演算法、存在的难点和前沿性研究问题,介绍了应用土壤水分反演算法所形成的3种主要全球土壤水分数据集,包括欧洲气象业务卫星（ERS/MetOp）数据集、高级微波扫描辐射计（AMSR-E）数据集、土壤湿度与海洋盐分卫星（SMOS）数据集,并结合目前存在的问题探讨卫星遥感反演土壤水分研究的发展趋势。     

被动微波反演裸露区土壤水分综述

被动微波具有全天候、穿透性以及不受云的影响等特征,使其在反演土壤水分时具有很大的优势。通过研究发现,被动微波遥感是反演土壤水分的各种技术中最有效的方法之一。概括了主要的被动微波传感器并从被动微波遥感的原理出发,针对被动微波遥感裸露区地表随机粗糙面的模型以及土壤水分反演算法作了简要介绍。     

联合机载PLMR微波辐射计和MODIS产品反演黑河中游张掖绿洲土壤水分研究

土壤水分是气候、水文学研究中的重要变量,微波遥感是获取区域地表土壤水分的重要手段,而L波段更是微波土壤水分反演的最优波段。依托HiWATER黑河中游绿洲试验区的地面观测及机载PLMR微波辐射计亮温数据,利用微波辐射传输模型L-MEB,并将MODIS地表温度产品(MOD11A1)和叶面积指数产品(MYD15A2)作为模型及反演中的先验辅助信息,借助LM优化算法,通过PLMR双极化多角度的亮温观测,针对土壤水分、植被含水量(VWC)和地表粗糙度这3个主要参数,分别进行土壤水分单参数反演、土壤水分与VWC或粗糙度的双参数反演以及这3个参数的同时反演。通过对不同反演方法的比较可以得出结论,多源辅助数据及PLMR双极化、多角度信息的应用可以显著降低反演的不确定性,提高土壤水分反演精度。证明在合理的模型参数和反演策略下,SMOS的L-MEB模型和产品算法可以达到0.04 cm3/cm3的反演精度,另外无线传感器网络可以在遥感产品真实性检验中起到重要作用。     

月壤厚度的研究方法与进展

月壤厚度的研究对未来月球探测、登月与月球资源开发均具有十分重要的意义。它是恢复月球起源和演化历史的重要参数,也是估算月球3He资源量的必要前提。本文将月壤厚度的研究方法归纳为直接和间接两类,直接方法主要是利用月震数据对月壤厚度进行推算,间接方法包括基于撞击坑形态、分布以及地基雷达遥感数据估算月壤厚度两种。随着定量微波遥感的发展,结合我国嫦娥探月工程的实施,利用高分辨率被动微波遥感亮温反演月壤厚度为月壤厚度的研究指出一个新的方向。     

地表冻融过程被动微波遥感机理研究进展

地表冻融过程及参数特征是陆表过程、气候模式、全球变化等研究的重要方面。被动微波遥感由于具有对土壤水分敏感、高时间分辨率等特点,非常适合用于地表冻融过程的监测和相关参数的反演。在分析地表冻融过程被动微波遥感机理研究发展现状的基础上,面向全球范围内大尺度陆表冻融过程微波遥感算法发展的需求,针对由土壤、积雪和植被组合的复杂地...     

基于热红外遥感的农田蒸散估算方法研究综述

农田蒸散是农田土壤蒸发和作物蒸腾的总称,基于热红外遥感的农田蒸散估算方法研究是农业遥感领域重要前沿课题之一。经过30多年的发展,基于热红外遥感的遥感蒸散算法逐渐成熟并广泛应用于农业、气象以及水文等多个领域。简要回顾基于热红外遥感地表温度与空气温度温差的经验方法、地表能量平衡的单层和双层模型、基于热红外遥感数据源的彭曼公式以及遥感参数化的Priestley-Taylor模型等多种遥感蒸散模型的基本原理、核心算法以及存在问题等研究。针对这些方法的优缺点,指出了基于热红外遥感的农田蒸散估算方法在农业遥感中尚需解决的关键问题,并提出可能的解决途径。     

Extraction of soil moisture from RADARSAT-1 and its role in the formation of the 6 December 2008 landslide at Bukit Antarabangsa,Kuala Lumpur

Active microwave has a huge potential in the estimation of soil moisture especially over large areas where the meteorological observations are seldom. The large contrast in dielectric constant between different types of soil is considered as the main factor for measuring the moisture content. This study is aimed at the extraction of soil moisture over the areas of Bukit Antarabangsa, Malaysia using active microwave remote sensing technique in order to examine the impact of moisture content dynamically on landslides occurrence, which have been a basic challenge that threaten Bukit Antarabangsa area, particularly in falling of monsoon seasons. This study addressed a specific event that took place in 6 December 2008 due to a very high level of precipitation that resulted in a raise in ground water table causing the occurrence of landslide. One Radarsat-1 image acquired in July 2008 before the landslide was used for generating the moisture content map. The resultant moisture content map showed a reasonable distribution of the moisture concentrated over the forest areas which has previous records landslides. Moreover, it was found that the previous landslide events were within the high moisture zone indicating the presence of high moisture content. Subsequently, three moisture maps were extracted from Landsat-7 ETM+, which were then used for validation process. A statistically based validation technique was used by calculating area under the curve that correlates the high moisture values of three images. In order to validate the Landsat-7 ETM+ moisture content, monthly rainfall data was plotted against the high moisture values derived from three Landsat-7 images. The validation result indicated an acceptable compatibility. The spatial relation between high moisture areas in Landsat-7 ETM+ images along the year resulted in a good fitting in the high–low moisture distribution areas with sensitivity ranged of 60–70 %. Finally, the moisture content map generated by Radarsat-1 was validated using a landslide inventory map. The resultant validation produced an area under curve of 0.704 (70 %).     

利用反射GPS信号遥感土壤湿度

在水文、气候、农业等问题的研究中，土壤湿度信息十分重要。近年来，利用GPS系统进行遥感的新方法，已经越来越多地引起研究者们的关注。特别是GPS卫星广播的L1（1.57542GHz）频率信号，是土壤湿度遥感的最佳频率。反射GPS信号功率是土壤介电常数的函数，而土壤介电常数又和土壤湿度有关。根据这一原理，美国国家航空与航天局于2002年进行了基于地表面反射GPS信号的遥感土壤湿度实验。结果证明反射GPS信号对土壤湿度特性十分敏感，由于植被的影响对反射率进行了修正，并用此方法模型与其它方法进行了比较。在利用GPS遥感土壤湿度方面，研制高增益天线，更好的修正信号波动的影响，发展更加完善的遥感土壤湿度方法等是今后在此项研究中所要解决的问题。     

Research advances in passive microwave remote sensing of surface freeze-thaw state北大核心CSCD

Soil freeze-thaw cycles have important effects on surface water and energy balance,and then affect vegetation growth,soil water content,carbon cycle and terrestrial ecosystem. Passive microwave plays an important role in monitoring global and regional surface freeze-thaw processes due to its high temporal resolution,abundant data and sensitivity to soil moisture. With the launch of passive microwave sensors at home and abroad,it provides conditions for the study of permafrost interannual variation,seasonal variation,diurnal variation and long time series of near-surface soil freeze-thaw cycle. In recent years,the study of surface freeze-thaw cycle using passive microwave data has gradually increased. Based on previous studies,this paper summarizes the types of passive microwave remote sensing data and the characteristics of the bands contained in them. Expounded the principle of passive microwave monitoring data used for freezing and thawing,focus on passive microwave data in five categories in the study of freezing and thawing monitoring algorithms,including double index algorithm,the decision tree algorithm,freeze-thaw discriminant algorithm,seasonal threshold algorithm and based on the freezing L-band relative factors discriminant algorithm threshold,and analysis of 5 kinds of algorithms are compared;The freeze-thaw products based on different algorithms and passive microwave data were combed. Finally,the problems and future research directions of passive microwave remote sensing in surface freeze-thaw applications are summarized. In the acquisition of passive microwave data,it is found that the passive microwave data is missing due to the physical characteristics of the sensor,the shape and orbit of the earth,and the low resolution of passive microwave data leads to the low precision of freeze-thaw discrimination. For the problem of missing passive microwave data,it is proposed to use the average value of passive microwave data before and after two days to fill the missing brightness temperature data,or establish statistical function to complement the missing data. For the problem of low passive microwave resolution,the current development trend is to scale down based on passive microwave data and combine with multiple data products,such as ground temperature and active microwave data,or perform probability discrimination on surface freezing-thawing state in pixels,so as to better describe surface freeze-thaw state. In terms of the algorithm for discriminating surface freezing-thawing,based on the problem that dual-index algorithm,decision tree algorithm,freezing-thawing discriminant algorithm and seasonal threshold algorithm cannot accurately distinguish snow and frozen soil,this paper proposes to adopt the method of data assimilation or start from the snow radiation and frozen soil dielectric model. Optimization of the algorithm for the snow covered surface can further improve the accuracy of freeze-thaw classification. Based on existing freeze-thaw products,Although SMAP freeze-thaw products continue to be updated,SAMP satellite was launched late,and SAMP freeze-thaw products have a short time series. In the future,the time span of this algorithm for freezing-thawing products can be extended by combining L-band data provided by SMOS satellite. The problems mentioned above and the direction of further research are of great significance for improving the accuracy of freezing and thawing discrimination and improving the understanding of the variation law of freezing and thawing cycles,and also have certain research space. © 2022 Science Press (China).     

MODIS在水文水资源中的应用与展望

MODIS是新一代遥感技术,其遥测数据与其他单独的遥感平台(如NOAA和Land Sat)所获得的数据相比,具有免费、较高时间分辨率(0.5d)、空间分辨率(250m)和光谱分辨率(波谱范围0.4～14μm,36个光谱通道)等优势和特点.详细介绍了国内外的研究现状,着重对MODIS在洪水过程和洪灾范围实时动态监测、冰川和积雪、降水、植被、土壤水分、蒸发、水文模型、水质等方面的应用和研究进展进行了评述,指出MODIS在水文水资源中具有广阔的应用前景.     

基于块克里金的土壤水分点观测向像元尺度的尺度上推研究

土壤水分是陆面水文过程的一个重要分量,土壤水分的地面点观测与卫星观测的尺度是不匹配的,用点观测数据进行遥感反演结果的验证或者融合这两种观测都需要开展点观测数据向卫星像元尺度的尺度上推研究.土壤水分时空异质性的分析和描述是进行尺度上推的基础,地统计方法是描述连续随机变量空间结构的经典方法.应用块克里金法分别将黑河寒区遥感试验阿柔试验区2008年4月1日与L波段微波辐射计同步的地面液态含水量和含冰量点观测数据经过尺度转换,得到与遥感像元相匹配的像元平均估计值和标准差,可用于该天L波段微波辐射计土壤液态含水量和含冰量反演结果的真实性检验,估计结果充分利用了像元临近位置的观测,得到了比直接的采样平均更合理的块估计结果,对块克里金估计值与采样平均值进行比较,发现两种结果趋势是一致的,块克里金法提供了更为合理的块估计结果,土壤水分空间结构的时间变异、小尺度的土壤特性的变化和测量误差都会对估计结果带来一定的不确定性.     

遥感技术在水文学中的应用与研究进展

从遥感技术在水文学中的直接和间接应用两个方面,详细阐述了遥感技术在洪水过程实时动态监测、水域面积、冰川/积雪水文、降水、区域蒸发、土壤水分、径流和水文模型、水质等领域的应用和研究进展,继而对遥感和地理信息系统在水文学中的联合应用问题进行了讨论。     

植被覆盖度遥感估算研究进展

植被覆盖度是刻画地表植被覆盖的重要参数,在全球变化研究、地表过程模拟和水文生态模型中发挥着重要作用.遥感能够反映不同空间尺度的植被覆盖信息及其变化趋势,是获取区域及全球植被覆盖度参数的一个重要手段.综合分析了用于植被覆盖度估算的遥感数据源,包括高光谱数据、多光谱数据、微波数据和激光雷达数据.而且分析了各种常用的植被覆盖度遥感估算方法及其优缺点,并评价了现有基于遥感数据的植被覆盖度产品及存在问题.最后,针对目前研究中存在的问题,讨论了植被覆盖度遥感估算研究的发展趋势,指出高时空分辨率长时间序列的全球植被覆盖度数据集、多源遥感数据融合和同化技术是未来植被覆盖度遥感估算研究的主要方向.     

Scale-invariance of soil moisture variability and its implications for the frequency-size distribution of landslides

Power spectral analyses of soil moisture variability are carried out from scales of 100 m to 10 km on the microwave remotely-sensed data from the Washita experimental watershed during 1992. The power spectrum S(k) has an approximate power-law dependence on wave number k with the exponent −1.8. This behavior is consistent with the behavior of a stochastic differential equation for soil moisture at a point, and it has important consequences for the frequency-size distribution of landslides. We present the cumulative frequency-size distributions of landslides induced by precipitation in Japan and Bolivia as well as landslides triggered by the 1994 Northridge, California earthquake. Large landslides in these regions, despite being triggered by different mechanisms, have a cumulative frequency-size distribution with a power-law dependence on area with an exponent ranging from −1.5 to −2. We use a soil moisture field with the above statistics in conjunction with a slope stability analysis to model the frequency-size distribution of landslides. In our model, landslides occur when a threshold shear stress dependent on cohesion, pore pressure, internal friction and slope angle is exceeded. This implies a threshold dependence on soil moisture and slope angle since cohesion, pore pressure and internal friction are primarily dependent on soil moisture. The cumulative frequency-size distribution of domains of shear stress greater than a threshold value with soil moisture modeled as above and topography modeled as a Brownian walk is a power-law function of area with an exponent of −1.8 for large landslide areas. This distribution is similar to that observed for landslides. The effect of strong ground motion from earthquakes lowers the shear stress necessary for failure, but does not change the frequency-size distribution of failed areas. This is consistent with observations. This work suggests that remote sensing of soil moisture can be of great importance in monitoring landslide hazards and proposes a specific quantitative model for landslide hazard assessment.     

Advances in microwave remote sensing of the ocean and atmosphere

This article reviews the current state-of-the-art and future prospects of the microwave techniques for remote sensing of the earth’s atmosphere and ocean. Geophysical parameters and their relationship with measured thermal microwave radiation is established through radiative transfer processes. The atmospheric temperature profile obtained from microwave sounding unit (msu) onboardtiros-N series of satellites is operational and is used for numerical weather prediction. The demonstrated applications of scanning multichannel microwave radiometer (smmr) onboard most recent and advancedseasat satellite are highlighted.The capability ofseasat active sensors for monitoring ocean parameters have also been indicated. Feasible applications of microwave techniquese.g. moisture profile with advanced moisture sounder (amsu), and surface pressure from multifrequency active microwave pressure sounder (mps) are also described. Finally the recent and advanced microwave limb sounding (mls) technique and its applications to upper atmospheric research has been reviewed.     

Research and Application of Cosmic-ray Fast Neutron Method to Measure Soil Moisture in the Field

It is very difficult to measure large region soil moisture. In recent years, measurement of surface soil moisture by the cosmic ray fast neutron probe has gradually attracted more attention. By this passive, non-invasive and intermediate scale measurement, soil moisture at a horizontal scale of around 300 m can be observed, which makes this method available to fill the gap between little scale of traditional point measurement and large scale of remote sensing in the measurement of soil moisture. In this paper, Cosmic-ray Soil Moisture Observing System (COSMOS) and Wireless Sensor Network (WSN) were used to observe field soil moisture in Zhangye Oasis. The results of the COSMOS soil moisture well reflected the variation trend of soil moisture at the field scale. There were some regular changes with the cosmic ray soil moisture during the irrigation period. Combined with irrigation data in cosmic-ray probe footprint, a bimodal change was showed in the cosmic-ray soil moisture figure during irrigation period. This was because that the order of irrigation of the three communities was different in cosmic-ray probe footprint. WSN data were used to validate this result and we found that root-mean-square error between cosmic-ray soil moisture and SoilNET average soil moisture was very large during irrigation periods because of the impact of cosmic-ray measurement theory. While root-mean-square error would decrease from 0.037 m³/m³ to 0.028 m³/m³ after we eliminated the data in irrigation period. So COSMOS can be used to measure field soil moisture under high heterogeneity condition and provide truly ground data for the validation of remote sensing