日光诱导叶绿素荧光遥感反演及碳循环应用进展

在植被遥感领域,遥感植被指数在过去30年极大地促进了从宏观尺度上来理解和认识地球生物圈,但是以"绿度"观测为主的植被指数仅表征植被"潜在光合作用",而不能直接量化"实际光合作用"。植被叶绿素荧光在光合作用探测上具有优势,是"实际光合作用"的直接探测方法。日光诱导叶绿素荧光(SIF)遥感是近年快速发展起来的新型遥感技术,尤其是2011年实现全球尺度卫星反演以来,在反演算法、植被监测和碳循环应用等方面发展迅速,是近10年来植被遥感领域最具突破性的研究前沿。本文阐述了现阶段(2011年以来)SIF遥感反演及其在碳循环应用方面的进展。本文首先介绍了卫星SIF遥感的发展及其反演算法现状;然后重点剖析了其在陆地生态系统总初级生产力(GPP)估算、全球碳循环监测、物候和植被胁迫监测等方面的应用现状和特点;最后从卫星SIF反演算法优化、SIF-GPP关系机理、SIF多尺度综合观测和全球碳循环监测等方面对今后植被SIF遥感的发展前景进行了展望。     

关于植被激光荧光遥感的若干基本问题

本文较系统地论述了应用激光荧光技术进行植被遥感的若干基本向题。其中包括原理、荧光探测的植物生理学基础、植物荧光光谱特征的意义及激光诱导荧光遥感方法的应用前景等。     

太阳诱导叶绿素荧光的卫星遥感反演方法

利用卫星遥感探测区域和全球尺度太阳诱导叶绿素荧光SIF(Solar-Inducedchlorophyll Fluorescence)近年来成为研究热点。由于地球大气吸收和散射的影响,卫星尺度的SIF反演问题较为复杂,科学界对该问题一直存在争议,不同科学团队提出了众多方法。本文介绍了大气层顶SIF反演的机理、难点及思路,总结了近10年来最新发展的大气层顶SIF反演算法,并将这些算法归纳为3类:基于辐射传输方程的算法、简化的物理模型算法和数据驱动算法,分析讨论了各算法的特点及适用性;以应用最广泛的数据驱动算法为例,基于GOME-2数据详细介绍了算法的中间环节及注意事项;最后回顾了卫星遥感反演SIF的发展历程,汇总了目前及未来具有荧光探测能力的星载传感器,并依据数据源的特点相应地给出了适用的SIF反演算法,为今后基于航空和卫星高光谱数据的SIF反演提供了依据。     

利用夫琅和费暗线探测自然光条件下的植被光合作用荧光研究

自然光照条件下测定的植被反射的辐照度光谱既包括太阳光诱导荧光的发射光谱，又包括叶片对入射光的反射光谱，研究如何从冠层光谱中提取荧光光谱有十分重要的应用价值。首先，论文介绍了夫琅和费暗线探测自然光条件下的光合作用荧光的基本原理和方法。其次，将太阳大气的夫琅和费暗线拓展到地球大气，发现地物光谱仪测定的冠层辐照度光谱中688nm和760nm两个氧气吸收形成的夫琅和费暗线特征明显，且荧光较强，所以利用这两个波段的夫琅和费暗线可以探测自然光条件下的光合作用荧光。第三，研究并分析了夫琅和费暗线方法计算的688nm和760nm波段的荧光特性，结果表明该方法计算的荧光是可靠的，它与光合有效辐射（PAR）关系密切，复相关系数达到了0．9；冬小麦冠层荧光光谱在760nm和688nm波段的荧光大小基本相等，而地锦冠层荧光光谱在688nm波段的荧光强度是760nm的3倍左右，表明荧光光谱能够更加敏感地反映植被物种或生理生化状况的差别。最后，将夫琅和费暗线方法计算的688nm和760nm波段的荧光数据与激光脉冲调制荧光仪测定Fv／Fm荧光参数进行了统计分析，结果表明它与Fv／Fm存在极显著的负相关关系。所以利用夫琅和费暗线方法能够探测植被冠层荧光，并有可能替代传统的测定方法，并推广到航空航天平台，实现荧光探测从接触式点测量方式到航空或卫星遥感大面积监测的技术飞越。     

遥感技术在考古中的应用综述

遥感技术能够快速有效地探明地上和地下古遗址的分布信息,在现代考古中发挥着重要的作用,逐渐成为考古研究的重要手段。阐述了遥感考古探测的基本原理,以遥感考古探测平台为序系统介绍了遥感考古探测方法与进展情况,对遥感考古探测的作用、局限性及发展前景进行了评述。     

叶绿素a荧光遥感研究进展

继叶绿素a反演的“蓝绿比值法”后,叶绿素a荧光遥感成为海水叶绿素a浓度反演的重要方法,对提高二类水体和赤潮水体的叶绿素a浓度的反演精度效果明显。本文回顾了人们对水体叶绿素a荧光的认识、测量和研究的历史过程,介绍了荧光产生的生物学机理以及它随叶绿素a浓度的正相关和“红移现象”等主要光谱特征。本文还总结了荧光量子产量、不同藻种生理状态、水体其他物质及大气的吸收等多种因素对叶绿素a荧光遥感的影响。基于对叶绿素a荧光光谱特征和影响因素的认识,人们相继建立了两种荧光遥感方法———基线荧光高度法和归一化荧光高度法。对于前景广阔的叶绿素荧光遥感领域,人们正进行着更深入的研究与探索,积累更多的现场数据和卫星同步数据,逐步完善和改进反演模型。     

激光荧光遥感系统在地物识别上的应用研究

应用我国自行研制组装的激光荧光遥感系统,测试了包括岩石、土壤、植物、水体以及人工建筑材料在内的各种样品的激光诱导荧光光谱。研究结果表明,应用地物荧光峰的位置、强度及它们的组合指标,不仅能区分上述各基本类型的地物,而且还能往下级单元续分。还表明,激光荧光遥感系统具有相当广泛的应用前景,在某些方面可望超过当前常用的、以反射光谱为基础的被动式遥感。     

不同施肥条件下玉米的荧光光谱特征及其在遥感中应用的可能性

在田间栽种玉米,并按氮、磷肥的不同施用量分为10种情况处理。在不同生长期进行了生长形态指标测量和活体叶片的荧光光谱与激光诱导荧光光谱测量,并测试了叶片浸出液的荧光光谱。结果表明,不同的施肥条件.不仅使玉米在长势上有所反映,而且还会引起光合作用效率和叶绿素含量等的变化,因而导致了玉米叶片荧光光谱的变化。利用440,550,685nm等处的荧光强度可探测玉米的养分供应状况,当利用它们的比值时,表征更为明显。这就为遥感监测玉米的长势和估产提供了新的途径和可靠依据。从玉米的需肥情况、农时、荧光光谱的差异性以及遥感的可行性来看,在拔节期是遥感监测的最佳时期。     

老航片在考古中的应用研究

通过国家863计划项目“考古遥感与地球物理综合探测技术”和国家历史博物馆项目“周王陵历史变迁研究”的研究成果，介绍了老航片在考古研究中的应用方法和应用效果。     

国外遥感技术在烃类微渗漏探测中的应用简介

油气藏中的挥发组份通过上覆地层微裂隙渗漏到地表,形成烃类物质地球化学异常晕。遥感作为一门新技术,已有效地应用到地表油气微渗漏异常的探测。本文主要介绍国外在因烃类微渗漏而造成的油气田地表土壤变化、岩石蚀变和地植物异常等方面的研究现状,以及国外在探索其形成机制方面的进展,并介绍国外石油遥感专家利用各种遥感手段进行烃类微渗漏探测的有效方法,望能达到推动我国石油遥感研究进一步深入与发展的目的。     

浅水湖泊水生植被遥感监测研究进展

在浅水湖泊中,水生植物具有净化水质、抑制藻类、提供鱼类食物和栖息环境等生态功能,同时,其过度扩张也会加速湖泊淤浅和沼泽化、引起湖泊二次污染等环境负效应.实时动态地掌握湖泊水生植被类群和种群的空间分布及其面积、生物量等指标信息,对湖泊生态修复和评估、水生植被恢复和管理等具有重要现实意义.遥感技术的大面积、实时、动态等特点...     

植被光能利用率高光谱遥感反演研究进展

光能利用率是表征植被通过光合作用将所截获/吸收的能量转化为有机干物质效率的指标。光能利用率是植被光合作用的重要概念,也是区域尺度以遥感参数模型监测植被生产力的关键参数。不同植被类型的光能利用率具有明显的时空差异,水分、温度、养分供给等环境胁迫因素会影响植被的光能利用率。随着高分辨率光谱测量传感器的使用,位于可见光和近红外区域的窄波段可以捕捉到植被冠层反射率的细微变化,也促进了光能利用率遥感反演技术的发展。本文结合国际植被光能利用率遥感反演最新研究成果,从基于环境胁迫因子的光能利用率反演,基于植被光谱指数的光能利用率反演、基于叶绿素荧光的光能利用率反演,以及基于涡度相关测量数据和遥感数据相结合的光能利用率反演四个方面,详细介绍了植被光能利用率遥感反演的主要技术方法,并对植被光能利用率遥感研究存在的主要问题和发展趋势进行了讨论。     

Proximal Remote Sensing of Herbicide and Drought Stress in Field Grown Colocasia and Sweet Potato Plants by Sunlight-Induced Chlorophyll Fluorescence Imaging

Chlorophyll fluorescence is an indicator of plant photosynthetic activity and has been used to monitor the health status of vegetation. Several studies have exploited the application of red/far-red chlorophyll fluorescence ratio in detecting the impact of various types of stresses in plants. Recently, sunlight-induced chlorophyll fluorescence imaging has been used to detect and discriminate different stages of mosaic virus infection in potted cassava plants with a multi-spectral imaging system (MSIS). In this study, the MSIS is used to investigate the impact of drought and herbicide stress in field grown crop plants. Towards this control and treatment groups of colocasia and sweet potato plants were grown in laterite soil beds and the reflectance images of these crop plants were recorded up to 14-days of treatment at the Fraunhofer lines of O₂ B at 687 nm and O₂ A at 759.5 nm and the off-lines at 684 and 757.5 nm. The recorded images were analyzed using the Fraunhofer Line Discrimination technique to extract the sunlight-induced chlorophyll fluorescence component from the reflectance images of the plant leaves. As compared to the control group, the chlorophyll fluorescence image ratio (F ₆₈₇/F ₇₆₀) in the treatment groups of both the plant varieties shows an increasing trend with increase in the extent of stress. Further, the F ₆₈₇/F ₇₆₀ ratio was found to correlate with the net photosynthetic rate (Pn) and stomatal conductance (g_s) of leaves. The correlation coefficient (R ²) for the relationship of F ₆₈₇/F ₇₆₀ ratio with Pn were found to be 0.78, 0.79 and 0.78, respectively for the control, herbicide treated and drought treated colocasia plants, while these were 0.77, 0.86 and 0.88, respectively for sweet potato plants. The results presented show the potential of proximal remote sensing and the application F ₆₈₇/F ₇₆₀ fluorescence image ratio for effective monitoring of stress-induced changes in field grown plants.     

Using multi-date high spectral resolution data to assess the physiological status of macroscopically undamaged foliage on a regional scale

Forests play an important role in regulation of the global climate; moreover, they provide human beings with a whole range of ecosystem services. Forest health and ecosystem functioning have been influenced by anthropogenic activities and their consequences, such as air pollution, surface mining, heavy metal contamination, and other biotic and abiotic stress factors, which had an especially serious effect on central Europe. Many aspects of the physiological state of trees are more or less related to the concentrations of two main groups of leaf photosynthetic pigments: chlorophylls and carotenoids. Therefore, their contents can be used as non-specific indicators of the actual tree physiological status, stress and the pre-visible tree damage. Variations in leaf biochemical composition affect foliar optical properties and can be assessed remotely using high spectral resolution data (hyperspectral data). These data were successfully used in earlier studies to detect vegetation stress and damage. However, only a few approaches have dealt with the use of hyperspectral remote sensing to assess vegetation physiological status on a regional scale. Moreover, little or no research has been done on assessing vegetation health while utilizing multi-date hyperspectral images.In this study, the method for assessing forest health conditions using optical indices retrieved from hyperspectral data was applied to the two temporal HyMap date sets acquired in 07/2009 and 08/2010 to detect stress for the Norway spruce forests in Sokolov, NW Bohemia, a region affected by long-term extensive mining. The classification results were validated by ground truth data (total chlorophyll – Cab, carotenoids – Car and carotenoid to chlorophyll ratio – Car/Cab) and were associated with the geochemical conditions of the forest stands. Both biochemical analysis of the sampled foliage and classification of 2009 and 2010 hyperspectral image identified the same sites affected by vegetation stress. In addition to higher Car/Cab, which enabled detection of the stressed trees using hyperspectral image data, these sites showed critically low pH and lower values for the macronutrient parameters in both organic horizons and, in addition, both sites exhibit critically low base cation to aluminum ratios (Bc/Al) for lower organic and top mineral (0–20 cm) soil horizons.The results of this study demonstrate (i) the potential application of hyperspectral remote sensing as a rapid method of identifying tree stress prior to symptom expression, and (ii) the added value of multi-temporal approaches for hyperspectral data and its further potential for monitoring forest ecosystems.     

Comparing the Use of Remote Sensing with Traditional Techniques to Detect Nitrogen Stress in Wheat

Abstract

An experiment was designed to compare ground‐based methods of nitrogen (N) stress detection with N stress detection using remote sensing. The study area, located in Minidoka, Idaho, is a 64 ha center pivot with a crop of Penawawa spring white wheat. Nitrogen was varied on four transects approximately 40 m wide and 805 m long. The N application rates chosen for the research were 0%, 40%, 100%, and 130% of normal. Nitrogen deficiency was quantified from tissue sampling, which was used as the response variable. Nitrogen was then measured or estimated at key stages in the wheat growth cycle using visual observation, a chlorophyll meter, and remotely‐sensed data. Visual observation was the normally‐employed method for area farmers. These methods of N stress detection were compared for accuracy, timeliness, usefulness, and cost. Remote sensing was comparable to the chlorophyll meter in accuracy. The chlorophyll meter was the timeliest method for obtaining a quantitative measurement.     

基于环境因素的沿岸水域叶绿素遥感探测研究

海洋叶绿素的调查一直是海洋生物资源与海洋生态学的研究重点。遥感技术是海洋叶绿素调查的有力工具。利用遥感光谱信号探测海水叶绿素在大洋水体(一类水体)中十分成功,但在沿岸水体(二类水体)的精度却不高,主要是由于悬浮泥沙、黄色物质等的干扰太大。从叶绿素的生存条件入手,提出了利用海水叶绿素环境生存因子作为辅助因素的方法建立叶绿素遥感探测模型。并以珠江口海域作为研究对象展开试验,结果表明:环境因子的引用,使模型的误差从32·48%降为17·96%,精度大大提高,从而证明该方法的可行性和有效性。     

森林垂直结构参数遥感反演综述

随着遥感技术的发展,林业遥感从早期森林分类制图的定性研究,逐步发展到森林整体特性的遥感定量反演研究。目前利用遥感反演的森林叶面积指数、生物量、叶绿素浓度、碳储量等参数以描述森林生化理化特征、水平结构特征为主,而描述森林垂直结构的参数较少。本文针对不同高度处森林的叶面积密度和冠层垂直高度廓线参数,综述了遥感获取森林垂直结构参数的方法以及典型地表类型的垂直结构参数曲线,并总结了森林垂直结构参数提取方法中存在的问题,探讨未来研究方向。