积雪、土壤冻融与土壤水分遥感监测研究进展

积雪、土壤冻融与土壤水分是陆表能量与水分以及碳交换过程研究中的重要因子,为了更好地了解积雪覆盖、雪深/雪水当量、土壤冻融状态和土壤水分等参数的遥感监测领域的发展动态,对这些参数遥感监测方法的研究进展进行了梳理,总结了利用光学与微波遥感,以及多源遥感融合的监测方法,并对该研究领域的发展趋势进行了展望。积雪、土壤冻融与土壤水分的遥感监测能力不断提升,监测算法从单一传感器向多传感器、单波段单一模式向多波段多模式集成,以及卫星虚拟星座综合观测概念的提出,均促进了现有卫星观测地表参数能力的提升;长时间序列产品的开发,对于研究和掌握全球变化大背景下对气候的响应提供了很好的数据基础;同时有助于促进遥感在水文、气象、气候、生态等领域的应用。以上的研究综述,有望对陆表水循环遥感参数反演领域,以及水循环遥感关键参数的应用领域有一定的借鉴作用。     

被动微波遥感在地表冻融监测中的应用研究进展

地表冻融过程强烈影响着地气能量交换、地表径流、作物生长和碳循环等陆地表层过程,利用微波遥感监测地表冻融循环及其相关的地表信息对气候的响应和反馈显然极其重要。随着SMOS(Soil Moisture and Ocean Salinity mission)、SMAP(Soil Moisture Active Passive mission)计划的实施,相对于早期广泛使用的C、X、K和Ka微波波段,L波段具有更低的频率、更深的穿透深度以及对土壤介电常数变化的敏感性,不仅被用于传统的地表冻融状态监测,还被扩展应用于估算土壤冻结深度、冻结速率、相变水含量等信息,显示出更广阔的应用前景。回顾了近年来被动微波遥感在地表冻融循环监测方面的最新研究进展,包含遥感监测原理、微波传感器、遥感算法等方面,重点介绍和总结了L波段在地表冻融循环遥感监测中的前沿研究,并对其应用潜力进行了展望。     

中国微波遥感发展的新阶段与新任务

在回顾和总结国际微波遥感近50年发展和中国微波遥感发展30余年的基础上,着重分析中国微波遥感技术发展现状,分析了中国在未来几十年对微波遥感发展的广泛需求。提出适应这些需求并进一步提高微波遥感发展水平的若干战略设想和一些应着重研究的前沿技术领域,指出了当前我国在发展微波遥感中值得重视的几个问题。     

电波环境研究在微波遥感中的应用

电波环境特性与微波遥感技术的研究和应用之间具有紧密的联系。与光学和红外等其它遥感手段相比, 微波遥感以全天候全天时工作能力、穿透性强和多频段与极化信息丰富等特点受到遥感界的重视, 特别是随着理论和技术的发展, 微波成像和遥感信息解译(判读、反演、分类、识别等) 能力不断提高, 微波遥感的应用得到了迅速的发展, 微波信息原有的不足得到了很大的改善。但是, 电波环境效应的影响却制约了微波定量遥感和成像技术的进一步发展。电波环境在微波遥感中的作用可以分为两个方面, 一是直接作为微波遥感的目标或对象, 如地表特征信息; 二是作为对遥感目标的影响参与遥感过程。针对微波遥感中的电波环境效应影响, 分析了相关的电波环境因素和条件, 讨论了相应的几何和物理分析方法与模型。     

农作物覆盖地表微波遥感模型研究进展

农作物是人类主要的粮食来源,微波遥感技术已被广泛应用于作物长势监测和作物生物量、含水量反演等研究领域,特别是微波遥感模型的发展更是提高了农田参数反演的精度。综述了农作物微波散射和辐射经验、半经验和理论模型的研究进展,对各模型的适用范围及优缺点进行了介绍,最后对农田微波遥感模型未来发展的难度和重点提出了一些见解。
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微波遥感土壤湿度研究进展

发展实用的微波遥感土壤湿度卫星反演算法,以提供区域尺度上的土壤湿度信息,对水文学、气象学以及农业科学研究与应用至关重要。简要分析了主动微波遥感土壤湿度的研究进展情况,重点对被动微波遥感土壤湿度的原理、算法发展及研究趋势进行了详细论述。主动微波具有卫星数据空间分辨率高的特点,随着携载主动微波器的一系列卫星的发射,主动微波遥感土壤湿度将受到重视。被动微波遥感研究历史长、反演算法特别是卫星遥感算比较成熟,是今后区域尺度乃至全球尺度监测土壤湿度的重要手段。     

第三届微波遥感技术研讨会

随着我国微波遥感技术的快速发展,为了促进我国微波遥感技术及其应用的发展,为国内从事微波遥感技术研究的单位和个人提供一个进行技术交流和研讨的平台,中国空间科学学会遥感分会和IEEE GRSS北京分会决定于2012年11月底12月初在福建省武夷山召开第三届微波遥感技术研讨会,希望有关研究单位和个人积极投稿,并对会议的议题和内容提出建议和意见。     

星载微波遥感观测海表温度的研究进展

随着卫星遥感技术的快速发展,星载微波遥感作为观测海温的手段之一,受到越来越多的关注。总结了国内外星载微波遥感观测海温的发展历程和微波遥感反演海温的理论基础,归纳了多元线性回归算法和非线性迭代算法两种主要的算法类型,在此基础上介绍了国外的TMI和AMSR-E以及国内FY-3和HY-2等卫星上搭载的先进微波传感器仪器的运行参数、通道特征及其相应的反演算法,最后分析了微波遥感反演海温的影响因素,指出了目前研究中存在的问题,并对今后的研究方向进行了展望。     

微波波段土壤的介电常数模型研究进展

介电常数反映了电介质与电磁波相互作用的特征。土壤介电常数是决定地表微波辐射散射特性的关键因素之一,是微波遥感研究中的一个关键参数。目前国内外对于土壤介电常数的研究已经持续很多年,建立多种土壤介电常数模型,包括理论模型、半经验模型和经验模型等。本文将详细介绍土壤介电常数的相关模型,指出了现有土壤介电常数模型存在的不足,并提出今后土壤介电常数模型的发展方向。     

冻融交替对水稻土水溶性有机碳含量及有机碳矿化的影响

冻融交替影响土壤水分的有效性及土壤团聚体稳定性,进而影响土壤中微生物的活性及土壤有机碳的矿化。通过室内冻融模拟(即分别在-7℃和28℃下处理土壤)及培养实验,研究了不同冻融交替循环处理下土壤水溶性有机碳(WSOC)、微生物生物量及土壤有机碳矿化的变化规律。结果表明,1到3次冻融交替处理会增加土壤中水溶性有机碳的含量,其中经过1次冻融交替处理的2种土壤其WSOC含量分别增加了25%,20%;但在本实验条件下如果继续增加冻融交替次数则会使土壤水溶性有机碳含量减少。冻融交替处理降低土壤微生物生物量,因此也会影响土壤有机碳的矿化。冻融交替处理对培养第1天的土壤有机碳矿化具有激发效应,激发能力:1次冻融交替>3次冻融交替>6次冻融交替,经过1次冻融交替处理后的土壤其呼吸速率与对照相比增加了17%～40%;其后,冻融交替处理土壤呼吸速率迅速下降,在培养后期甚至低于对照处理。     

AMSR-E亮温监测中国近地表冻融循环算法研究

为更加精细地获取日内地表冻融循环信息,联合使用AMSR-E升轨(13:30)和降轨(1:30)一天两次过境的逐日亮温数据,采用双指标算法,分别判定升轨和降轨过境时刻的地表冻融状态,综合两次过境信息将地表细分为日内完全冻结、日内完全融化、日内冻融循环和日内逆向冻融循环4种类型。经过验证,日内完全冻结地表分类精度达90%,日内完全融化地表和日内冻融循环地表分类精度约为70%。在日内地表冻融循环分类基础上,将年冻融循环周期划分为稳定冻结期、稳定融化期、春季冻融过渡期和秋季冻融过渡期。根据2004年分类结果得出,1月份,日内完全冻结地表和日内完全融化地表大体以秦岭淮河为界,随着温度逐渐升高,日内完全冻结地表南界、日内完全融化地表北界和日内冻融循环地表的南北界从东南向西北移动,温度降低,各边界线从西北向东南移动;稳定冻结期主要出现在1月和2月,稳定融化期出现在7月和8月,春季冻融过渡期是3~5月,秋季冻融过渡期是9~11月。     

中国长时间序列地表冻融状态数据集

地表冻结和融化状态的转换表征着陆地表层过程的休眠和活跃,亦可作为水文循环和生态系统活动的“开关”。本文主要介绍根据双指标冻融状态分类算法和决策树算法制备的中国区域长时间序列地表冻融数据集(分别为1978~2015年与1987~2009年),该数据集可用于分析中国区域地表冻融循环的开始/结束日期、冻结期、冻结天数、冻结范围等指标的时空分布和变化趋势,可为中国区域的冰冻圈和水文相关研究,以及气候变化分析提供重要的数据支持。
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Radar remote sensing of springtime near-surface soil thaw events at mid-latitudes

Detection of springtime near-surface soil thaw events in mid-latitude areas is important for understanding the near-surface earth surface system. Radar backscatter time series, such as QuikSCAT K_u-band, are valuable for surface thaw detection in permafrost areas, but their usefulness in mid-latitudes remains unverified. In order to validate the application of radar backscatter time series for surface thaw detection in mid-latitude areas, we propose a new multi-step method based on the significant signature of radar backscatter time series when springtime soil thaw events happen. The method mainly focuses on the estimated geographical boundary of thaw events and the detection of the primary thaw date; the duration of the freeze–thaw transition period is a lesser focus. The method is applied to soil freeze–thaw conditions in a mid-latitude area – northern China and Mongolia – including humid land and dryland, and achieves a reliability of R ²?=?0.678 ± 0.021 (P < 0.01) by comparison with ground truth measurements. The results indicate that elevation/temperature and soil moisture conditions are the key drivers of the timing of springtime soil thaw events. The success of our study demonstrates the potential for our method to be applied in mid-latitude areas, and widens the application potential of radar backscatter time series beyond high north and permafrost studies.     

A decision tree algorithm for surface soil freeze/thaw classification over China using SSM/I brightness temperature

This paper reports the development of a decision tree algorithm to classify the surface soil freeze/thaw states. The algorithm uses SSM/I brightness temperatures recorded in the early morning. Three critical indices are used as classification criteria—the scattering index (SI), the 37 GHz vertical polarization brightness temperature (T_37V), and the 19 GHz polarization difference (PD₁₉). The thresholds of these criteria were obtained from samples of frozen soil, thawed soil, desert, and snow. The algorithm is capable of distinguishing between frozen soil, thawed soil, desert, and precipitation. In-situ 4-cm deep soil temperatures on the Qinghai-Tibetan Plateau were used to validate the classification results, and the average classification accuracy was found to be 87%. Regarding the misclassified pixels, about 40% and 73% of them appeared when the surface soil temperature ranged from − 0.5 °C to 0.5 °C and from − 2.0 °C to 2.0 °C, respectively, which means that most misclassifications occurred near the soil freezing point. In addition, misclassifications mainly occurred from April to May and September to October, the transition periods between warm and cold seasons. A grid-to-grid Kappa analysis was also conducted to evaluate the consistency between the map of the actual number of frozen days obtained using the decision tree classification algorithm and the reference map of geocryological regionalization and classification in China. The overall classification accuracy was 91.7%, and the Kappa index was 80.5%. The boundary between the frozen and thawed soil was consistent with the southern limit of seasonally frozen ground from the reference map. The statistics show that the maximum area of frozen soil is about 6.82 × 10⁶ km² in late January, accounting for 69% of total Chinese land area.     

Retrieval of Soil Unfrozen Water in Maqu Region of Tibetan Plateau based on SMAP Brightness Temperature Measurement

Unfrozen water and ice co-exist in frozen soil, and their mutual transformation, namely freezing-thawing change, profoundly affects the surface water circulation and energy budget in cold regions. Passive microwave remote sensing technology is the main means of soil water monitoring, but it is mostly applied to the retrieval of water in non-frozen soil, and the retrieval of unfrozen water in frozen soil under negative temperature environment is less. Based on the brightness temperature measurement data obtained from the SMAP satellite ascending and descending overpass and the improved zero-order microwave radiation model applicable to the Tibetan Plateau, using Single-Channel Algorithm (SCA) and Dual-Channel Algorithm (DCA), The content of unfrozen water in the seasonal frozen soil in Maqu region which is the source region of the Yellow River in the east of Tibetan Plateau was inverted. The results show that the in-situ measured values dynamics are better captured by the retrieval values based on the brightness temperature measurement at the different moments of SMAP satellite overpass and different algorithms of soil unfrozen water in the study area(the correlation coefficient R is greater than 0.9). Among them, the retrieval results based on the brightness temperature measurement at the SMAP descending are significantly underestimated in the transition season of freezing-thawing cycle, while the retrieval results based on the brightness temperature measurement at the SMAP ascending are more accurate. The unbiased root-mean-square error (ubRMSE) of the retrieval values which obtained based on the V-polarization Single Channel Algorithm (SCA-V) and DCA and the in-situ values is 0.035 m³m^-3 and 0.039 m³m^-3, respectively, which are both meet the established requirements of SMAP mission. Compared with SMAP standard products, the soil moisture in warm season obtained by retrieval based on SCA-V algorithm is more accurate in this study. In addition, the algorithm adopted in this study can successfully retrieval the dynamic change of soil unfrozen water during freezing period, so it is more suitable for the retrieval of soil moisture under freezing and thawing conditions in Tibetan Plateau.     

基于SMAP亮温数据反演青藏高原玛曲区域土壤未冻水

未冻水和冰共同存在于冻土中,两者的相互转化即冻融变化深刻影响寒区地表水分循环和能量收支。被动微波遥感技术是土壤水分监测的主要手段,但目前大多应用于非冻结土壤的水分反演,对负温环境下冻结土壤中未冻水的反演研究较少。基于SMAP卫星升轨和降轨时刻的亮温观测数据和经改进后适用于青藏高原地区的零阶微波辐射模型,利用单通道算法（SCA）和双通道算法（DCA）,对青藏高原东部黄河源区玛曲区域季节冻土中的未冻水含量进行反演。结果表明：基于SMAP不同过境时刻亮温观测及不同算法的土壤未冻水反演结果均较同步地反映了研究区实测值的动态变化特征（相关系数R均大于0.9）。其中,基于SMAP降轨时刻亮温观测的反演结果在冻融交替的过渡季节存在明显低估,而基于升轨时刻亮温观测得到的反演结果精度更高。基于垂直极化亮温观测的单通道（SCA-V）和DCA算法得到的升轨时刻的反演值与实测值的无偏均方根误差（ubRMSE）分别为0.035 m³m^-3和0.039 m³m^-3,均达到SMAP任务的设计要求（即ubRMSE≤0.04 m³m^-3）,其中SCA-V对该研究区土壤未冻水的反演精度最高。与SMAP标准产品相比,基于SCA-V算法反演得到的暖季土壤水分精度更高。此外,该算法能成功反演得到冻结期土壤未冻水的动态变化,因此更适用于青藏高原地区冻融土壤条件下的水分反演。     

Estimation of effects of a freezing environment on vegetation using model simulation and a truck-mounted microwave radiometer

Passive microwave remote-sensing techniques can monitor surface soil freeze/thaw states at the frozen soil surface. Studies found that the negative spectral gradient at 19 and 37 GHz is a good criterion for the determination of frozen soil. To remove vegetation effects on soil microwave emission signatures, only vegetation attenuation was considered, omitting vegetation emission contributions. Studies on vegetation effects indicated that at high frequencies, scattering and attenuation effects should be considered. In this article, a matrix-doubling microwave emission model evaluated vegetation effects in a cold environment at 18.7 and 36.5 GHz. To verify the model, a multi-channel truck-mounted radiometer collected emission data at a young tree stand and a grass-like field in 2008. Comparisons between model simulations and field measurements corresponded well. The model then established an emission database of natural, vegetated surface in the freezing environment, matched with the τ–ω model (which is a zeroth-order microwave emission model) in the same environment using least-square error. The effective scattering and attenuation of vegetation at both frequencies in the freezing environment were retrieved.     

黄河流域甘肃片土壤侵蚀遥感普查的初步分析

以TM影像为主要信息源,借助GIS(地理信息系统)软件ARC/INFO作技术支撑,对黄河流域甘肃片土壤侵蚀现状进行普查。通过提取影响土壤侵蚀主导因子并综合分析确定甘肃片土壤侵蚀类型、分布及强度。