2002年—2018年太湖水体溶解二氧化碳浓度卫星遥感数据集

湖泊在全球碳循环中发挥着重要作用,而湖泊中溶解CO2浓度(CCO2)控制着其CO2通量的方向及大小,是湖泊CO2排放估算的关键参数.中国第三大淡水湖——太湖虽然具有长期的野外监测数据,但其样点分布在空间和时间上并不均匀,很可能给其CO2排放的估算带来不确定性和偏差.有必要利用更高频率和覆盖范围地遥感手段来弥补野外监测在...     

基于网络复合架构的全球碳循环关键参数共享平台

在课题经费、软硬件环境受限的前提下,研究全球碳循环关键参数产品共享平台的关键技术.基于Java 2 Platform Enterprise Edition(J2EE)、百度网盘等相关计算机技术,搭建了基于网络复合架构的全球碳循环关键参数产品低成本共享原型系统,为"全球生态系统碳循环关键参数立体观测与反演"课题所生产的2...     

干旱对草地生产力影响的定量评估研究

正全球变化与陆地生态系统碳循环是当前全球变化研究的重要内容。内蒙古草原位于中国东北样带环境敏感区,干旱发生频繁,强度大,持续时间长,对内蒙古草原生态系统碳循环产生了重大影响。在可预见的未来,干旱的变化趋势是发生更加频繁,等级更高和持续时间更长,可能超出生态系统能够承受的压力阈值,对生态系统碳     

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。     

乌梁素海

乌梁素海位于内蒙古乌拉特前旗境内，是由黄河改道而形成的河迹湖，是黄河流域最大的湖泊，也是全球荒漠半荒漠地区极为少见的大型草原湖泊，有着丰富的鸟类资源，是世界上著名的鸟类迁徒地和繁殖地，2002年被国际湿地公约组织正式列入国际重要湿地名录，是深受国际社会关注的湿地系统生物多样性保护区。     

青藏高原西部湖泊与构造背景关系遥感研究

利用遥感技术对青藏高原腹地湖泊的大小、形态、数量和空间分布进行了研究,发现大部分湖泊受张性断裂控制。湖泊的形态及空间分布具有非常强的规律性,且与GPS测量数据吻合,反映了区域应力场的现状。不同应力条件下,湖泊的形态和空间分布具有地域性,这种规律体现了各个区域构造背景的差异。青藏高原中部岩石圈物质向SE方向大规模逃逸是大量断陷湖泊形成的重要原因。湖泊分布规律是高原区域构造研究的一个窗口,对地下水的勘查具有一定的指导意义。     

一种基于动态多尺度聚类的湖泊选取方法

当前湖泊选取方法多采用整体选取的形式,且难以兼顾湖泊的属性特征、分布特征和拓扑特征。通过分析和模仿制图专家人工选取湖泊的认知行为和过程,提出一种顾及分布特征和拓扑特征保持的基于动态多尺度聚类的湖泊选取方法。首先设置面积阈值以选取大面积湖泊,然后通过缓冲区选取"孤立"湖泊,接下来对湖泊群进行动态多尺度聚类来划分出湖泊分布密度不同的区域,对不同区域按开方根规律确定选取数量指标并采用不同选取策略,其中对包含湖泊数量较多的区域依据由主成分分析法定量计算出的重要性综合评价进行迭代选取,直至达到选取数量指标。实验对比表明,该方法在综合考虑重要性的前提下,有效地保持了选取前后湖泊群的形态结构和密度对比。     

基于高原湖泊的数据处理与空间可视化研究

近年来,随着工业化和城市化进程的加快,生态破坏、环境污染、湖泊品质恶化等一系列环境问题日趋严重,高原湖泊作为生态环境的重要指示剂,已逐渐成为研究的重点。空间可视化技术特有的交互性、多维性和可视化多样性的本质,更能直观形象地体现高原湖泊的变化。本文以阿雅克库木湖为研究区域,基于GIS平台,利用Landsat遥感影像数据(包括MSS、TM和ETM影像),运用改进的湖泊边界矢量化提取方法和GIS空间可视化技术,对高原湖泊的变化规律进行了研究。结果表明,历年的湖泊变化规律表现为湖泊的面积随着年份的增大而逐渐增大,某一年内的湖泊变化规律表现为减-增-减的规律,其中在2月份达到最低,在10月份达到最高,这对于保护高原湖泊和环境、预测未来环境等具有重要意义。     

基于遥感与碳循环过程模型估算土壤有机碳储量

土壤有机碳含量的估算是当前全球碳循环研究的热点之一,但不同学者之间的估算值差异较大。从估算方法看,主要有基于土壤剖面的直接估算法和基于生态系统碳循环过程模型的间接估算法,这两种方法各有优缺点。直接估算法由于只反映了不同土壤或植被类型的土壤有机碳含量平均值的差异,因而空间分辨率较低。而间接估算法由于参数的简化,影响了土壤有机碳估算的空间精度。作者将遥感的高时空分辨率特征、反映生态系统碳循环动态变化的过程模型、实际测量的土壤有机碳结合起来,以求提高土壤有机碳估算的空间分辨率。考虑到受温度、水分的影响,土壤呼吸与土壤有机碳含量的关系并不好,而土壤基础呼吸由于剔除了温度和水分的影响,从而使其与土壤有机碳的关系非常密切,其测定系数R^2可达0.78。采用了结合遥感和碳循环过程的CASA模型及Van＇t Hoff土壤呼吸模型,首先估算了8km分辨率的土壤基础呼吸的空间分布,在此基础上结合实测的土壤有机碳估算了8km分辨率的土壤有机碳的空间分布。     

全球碳循环关键参数共享平台建设方案研究

当前数据产品共享模式在我国各行各业均得到了快速应用和发展,纷纷将共性的、标准化的数据产品纳入共享中心进行处理.本文以"全球生态系统碳循环关键参数立体观测与反演"重点专项中的全球碳循环关键参数为研究对象,针对其特殊的限制条件,提出了基于网络复合架构的切实可行的低成本共享系统落地解决方案,可为具有类似特征的系统建设提供借鉴.     

湖泊遥感研究进展与展望

湖泊遥感作为一门新型交叉学科,是湖泊科学和遥感科学的重要分支.本文探讨了湖泊遥感科学的研究对象、内容和方法,通过梳理国内外总体研究进展,总结出湖泊遥感的5个发展趋势:(1)关注问题,从兴趣导向发展到问题导向;(2)观测手段,从地基遥感/中分辨率卫星发展到高分辨率/高光谱/无人机;(3)算法算力,从单机版经验/机理模型发...     

遥感陆地水循环的进展与展望

随着遥感技术的不断进步,许多陆地水循环的变量已经能够通过遥感定量估算。遥感方法能够提供大范围、长周期的水循环变量数据,这极大地推进了人们对陆地水循环过程的认识和理解。阐述了遥感观测陆地水循环重要变量的基本原理,回顾了陆地水循环遥感主要技术方法的重要进展和最新成果,指出下一步可能的发展方向。尽管目前遥感技术具备获取大范围水循环关键变量的能力,但是遥感估算的水循环分量还难以满足基本的水量平衡,表明当前遥感数据的水文一致性还待加强。未来遥感陆地水循环研究的发展一方面需要新型传感器和平台来提供更高精度且时空一致的观测数据,另一方面需要开展大型地面水循环同步全过程观测试验来对遥感产品进行深入评估,以促进遥感技术在陆地水循环研究中的应用。     

A review of progress in identifying and characterizing biocrusts using proximal and remote sensing

Biocrusts are critical components of desert ecosystems, significantly modifying the surfaces they occupy. The mixture of biological components and soil particles that form the crust, in conjunction with moisture, determines the biocrusts’ spectral signatures. Proximal and remote sensing in complementary spectral regions, namely the reflective region, and the thermal region, have been used to study biocrusts in a non-destructive manner, in the laboratory, in the field, and from space. The objectives of this review paper are to present the spectral characteristics of biocrusts across the optical domain, and to discuss significant developments in the application of proximal and remote sensing for biocrust studies in the last few years. The motivation for using proximal and remote sensing in biocrust studies is discussed. Next, the application of reflectance spectroscopy to the study of biocrusts is presented followed by a review of the emergence of high spectral resolution thermal remote sensing, which facilitates the application of thermal spectroscopy for biocrust studies. Four specific topics at the forefront of proximal and remote sensing of biocrusts are discussed: (1) The use of remote sensing in determining the role of biocrusts in global biogeochemical cycles; (2) Monitoring the inceptive establishment of biocrusts; (3) Identifying and characterizing biocrusts using Longwave infrared spectroscopy; and (4) Diurnal emissivity dynamics of biocrusts in a sand dune environment. The paper concludes by identifying innovative technologies such as low altitude and high resolution imagery that are increasingly used in remote sensing science, and are expected to be used in future biocrusts studies.     

叶绿素荧光的GOSAT卫星遥感反演

由于大气吸收和散射等大气辐射传输影响,叶绿素荧光卫星遥感反演存在很大的困难和挑战。本文利用日本温室气体观测卫星GOSAT的TANSO-FTS超光谱数据,选取770 nm附近受大气影响较弱的KI夫琅和费暗线,借助KPNO2010高分辨率太阳辐照度光谱,设计了加权最小二乘拟合的叶绿素荧光卫星反演算法,利用矩阵的谱条件数确定了算法中KI吸收线所采用的权重系数,获得了中国区域2010年1月至2011年6月的叶绿素荧光数据。并利用TANSO-CAI云标识数据剔除了受云影响的反演结果,并按照2°×2°格网逐月计算了荧光强度均值。将反演叶绿素荧光强度结果与同期MODIS的增强性植被指数EVI、光合有效辐射比例FPAR、总初级生产力GPP产品作对比分析,结果表明：荧光强度高值主要分布在中国西南、中南等植被覆盖度高、生长旺盛的地区,荧光强度季节性变化规律与EVI、FPAR、GPP等相似,但季节变化比上述各参数变化提前且更敏感,可以反映其他参数所不具备的独特信息。     

Estimating dissolved organic carbon concentration in turbid coastal waters using optical remote sensing observations

Dissolved Organic Carbon (DOC) is an important component in the global carbon cycle. It also plays an important role in influencing the coastal ocean biogeochemical (BGC) cycles and light environment. Studies focussing on DOC dynamics in coastal waters are data constrained due to the high costs associated with in situ water sampling campaigns. Satellite optical remote sensing has the potential to provide continuous, cost-effective DOC estimates. In this study we used a bio-optics dataset collected in turbid coastal waters of Moreton Bay (MB), Australia, during 2011 to develop a remote sensing algorithm to estimate DOC. This dataset includes data from flood and non-flood conditions. In MB, DOC concentration varied over a wide range (20–520 μM C) and had a good correlation (R² = 0.78) with absorption due to coloured dissolved organic matter (CDOM) and remote sensing reflectance. Using this data set we developed an empirical algorithm to derive DOC concentrations from the ratio of R_rs(412)/R_rs(488) and tested it with independent datasets. In this study, we demonstrate the ability to estimate DOC using remotely sensed optical observations in turbid coastal waters.     

High resolution remote sensing for reducing uncertainties in urban forest carbon offset life cycle assessments

Background

Urban forests reduce greenhouse gas emissions by storing and sequestering considerable amounts of carbon. However, few studies have considered the local scale of urban forests to effectively evaluate their potential long-term carbon offset. The lack of precise, consistent and up-to-date forest details is challenging for long-term prognoses. Therefore, this review aims to identify uncertainties in urban forest carbon offset assessment and discuss the extent to which such uncertainties can be reduced by recent progress in high resolution remote sensing. We do this by performing an extensive literature review and a case study combining remote sensing and life cycle assessment of urban forest carbon offset in Berlin, Germany.

Main text

Recent progress in high resolution remote sensing and methods is adequate for delivering more precise details on the urban tree canopy, individual tree metrics, species, and age structures compared to conventional land use/cover class approaches. These area-wide consistent details can update life cycle inventories for more precise future prognoses. Additional improvements in classification accuracy can be achieved by a higher number of features derived from remote sensing data of increasing resolution, but first studies on this subject indicated that a smart selection of features already provides sufficient data that avoids redundancies and enables more efficient data processing. Our case study from Berlin could use remotely sensed individual tree species as consistent inventory of a life cycle assessment. However, a lack of growth, mortality and planting data forced us to make assumptions, therefore creating uncertainty in the long-term prognoses. Regarding temporal changes and reliable long-term estimates, more attention is required to detect changes of gradual growth, pruning and abrupt changes in tree planting and mortality. As such, precise long-term urban ecological monitoring using high resolution remote sensing should be intensified, especially due to increasing climate change effects. This is important for calibrating and validating recent prognoses of urban forest carbon offset, which have so far scarcely addressed longer timeframes. Additionally, higher resolution remote sensing of urban forest carbon estimates can improve upscaling approaches, which should be extended to reach a more precise global estimate for the first time.

Conclusions

Urban forest carbon offset can be made more relevant by making more standardized assessments available for science and professional practitioners, and the increasing availability of high resolution remote sensing data and the progress in data processing allows for precisely that.

     

遥感与中国可持续发展:机遇和挑战

中国要实现可持续发展,必须积极应对资源短缺、环境恶化、海洋开发和气候变化等一系列重大资源环境问题;随着全球经济发展一体化进程加快,中国必须以全球视角研究和解决面临的资源环境问题。遥感在地球科学、环境科学、资源科学与全球变化研究中具有宏观动态的优点,是不可替代的全球观测手段,是实施可持续发展战略的基础性技术支撑。本文回顾了遥感科学技术进步的历程,总结了国际上围绕可持续发展所开展的全球遥感科学计划,分析了中国遥感现状和服务于可持续发展的前景,并结合国际上地球综合观测系统的发展态势,提出了中国遥感科学技术发展面临的挑战和机遇,进一步阐述了遥感发展面临的建立地球综合观测系统之系统、高精度遥感模型与参数反演、遥感产品真实性检验与遥感性能判据及测试系统、遥感数据与地球系统模式同化、遥感大数据与主动服务等前沿科学与技术问题。最后指出遥感要更好地服务于社会可持续发展,服务于国家的全球战略,服务于国民经济建设;必须创新遥感应用服务模式,加快遥感产业化和商业化进程;建议推进卫星观测系统的商业化,加快无人机遥感发展,促进遥感应用市场化。     

天宫一号高光谱遥感场景分类数据集及应用

天宫一号高光谱成像仪具有空间分辨率高、光谱分辨率高、图谱合一等特性，在中国航天高光谱领域具有里程碑的意义。针对一般遥感场景分类数据集尺度单一、光谱分辨率较低等问题，本文提出基于天宫一号的多谱段、高空间分辨率、多时相高光谱遥感场景分类数据集(TG1HRSSC)。利用天宫一号高光谱成像仪获取的高质量数据，经过辐射校正、几何校正、空间裁剪、波段筛选、数据质量分析与控制等，制作了一批通用的航天高光谱遥感场景分类数据集，通过载人航天空间应用数据推广服务平台（http://www.msadc.cn[2019-09-10]）进行分发和共享。该数据集包括天宫一号高光谱成像仪获取的城镇、农田、林地、养殖塘、荒漠、湖泊、河流、港口、机场等9个典型地物场景的204个高光谱影像数据，其中5 m分辨率全色谱段1个波段、10 m分辨率可见近红外谱段54个有效波段以及20 m分辨率短波红外谱段52个有效波段。研究利用AlexNet、VGG-VD-16、GoogLeNet等深度学习算法网络对构建的数据集进行场景分类的试验，结果表明该数据集的场景分类应用实现较好效果。由于该数据集具备高分辨、高光谱等特征优势，未来在语义理解、多目标检测等方面有着广泛的应用价值。     

The refined spatiotemporal representation of soil organic matter based on remote images fusion of Sentinel-2 and Sentinel-3

Remote sensing technology is important for soil organic matter (SOM) estimation, but existing studies have mainly relied on a single data source. This limitation makes it difficult to simultaneously ensure high spatial resolution, high spectral accuracy and refined temporal granularity simultaneously, which cannot meet the requirements of the spatiotemporal dynamics representation. This study aimed to introduce a new remote sensing image source into SOM modeling and spatiotemporal estimation generated by fusing together Sentinel-2 and Sentinel-3 remote sensing images that have a 5-day revisit cycle; 10 m spatial resolution; and 21 different bands in blue, green, red and NIR spectral ranges. According to the image fusion process, a total of 52 available images were acquired between November 2016 and December 2018 in Donghai County, China. The fused images were used for SOM estimation model associated with 107 field samples. The results indicated that, first, the optimal model consisted of the band reflectivity (B20) and RVI (B18/B9), which were derived from the fused images, and the R² approached 0.7 in the two phases of the synchronized data. Second, the modeling accuracy was influenced to some extent by the actual SOM content. The R² values exceeded 0.75 when the SOM content was higher than 24 g/kg, while the R² was even lower than 0.35 when the SOM content was lower. Third, the averaged SOM contents remained stable in general, while the seasonal variances can also be found during the two-year interval. The SOM contents maintained a low level during autumn and winter, while higher SOM levels were found in the spring and summer. Finally, the spatial variations could be described as ‘low in the west and high in the east’. In summary, the spatiotemporal dynamics of SOM highlighted the necessity of modeling with fused remote sensing images, and more effective modeling could be expected with the continued increase in SOM in future.     

无人机遥感：大众化与拓展应用发展趋势

当前遥感领域各个国家不断加大投入,星载数据资源日益丰富。伴随大数据等前沿技术的发展与深入应用,遥感在宏观层面上已经得到了较为充分应用,对于全球变化以及地球系统科学研究而言是一个重要的数据源。我国已经成为国际上的遥感大国,高分专项的实施标志着民用航天遥感进入亚米级时代。但是,由于空间分辨率与重访周期之间的矛盾,高分辨率卫星数据的可获得性尚不能满足一些不断增长的应用需求。国内遥感应用尚停留在宏观层面,主导是政府部门,用户也是政府各级部门。遥感在满足大量微观和大众具体应用层面尚没有落地。无人机遥感的出现与快速发展,为促进遥感应用落地起了很好的助推作用,无人机遥感在区域信息精细化上具有高科学价值,具有高空间分辨率、高频次、高性价比等特点,可以与卫星遥感能力形成互补,缓解了高空间分辨率和时间分辨率的矛盾,在低成本的基础上实现了空间和时间的辩证统一。当前无人机遥感的发展尚处于初级阶段,但呈现出一些极具特色的应用前景,尤其是无人机"遥感+"应用发展迅猛。同时,发展过程中也还有诸多政策、技术与方法方面的问题。本文在总结无人机未来发展趋势的同时,对无人机遥感的发展,从政策、技术与应用等层面提出了建议。