基于MPI并行计算的卫星遥感数据变化监测系统设计

为控制卫星遥感数据变化指征与非变化指征之间的实值误差,实现对卫星遥感数据传输变化行为的准确监测,设计基于MPI并行计算的卫星遥感数据变化监测系统。建立A/D转换电路与Zigbee网络节点的匹配关系,将所得卫星遥感数据按需分配给传感器模块与协调器设备,完成数据采集与监测终端的硬件设计。按照并行拓扑结构连接形式,实施MPI的基本调用,再联合数据进程编写原则,实现对MPI并行计算的完善。根据传感器几何校正原理,求取遥感数据度量值,再分析核函数表达式,完成对卫星遥感数据的处理。利用MPI并行计算,控制数据采集与监测终端的硬件执行设备,完成卫星遥感数据变化监测系统设计。实验结果表明,所设计系统的卫星遥感数据变化指征与非变化指征之间的实值误差明显缩小,能够准确监测卫星遥感数据传输变化行为。     

HJ-1A/B星CCD多光谱遥感数据特征评价及应用研究

我国现有的风云系列卫星、资源卫星及海洋卫星都可实现多种性能的对地观测,在灾害与环境监测方面发挥了很好的作用。然而,面对复杂多样的自然灾害及环境问题,这些卫星却都难以完全满足灾害和环境监测与预报所需的空间分辨率、时间分辨率和光谱分辨率以及全天候的要求。主要对环境与灾害监测预报小卫星A、B(HJ-1A/B)星多光谱遥感数据进行了质量评价,提取数据特征,以便为该数据的推广应用提供参考。     

HJ-1A/1B卫星远程播报系统的实现

基于环境与灾害监测预报小卫星星座中的HJ-1A、1B卫星遥感数据,提出一种卫星影像数据与矢量数据在远程播报系统中快速叠加匹配的方法与技术流程。在此基础上,实现了HJ-1A、1B卫星宽覆盖CCD相机的数据远程播报。系统测试表明,远程播报系统对HJ-1A、1B卫星数据空间定位准确,数据处理速度快,满足远程播报实时显示数据的要求。     

HJ-1A高光谱数据预处理方法研究

高光谱遥感数据处理与应用已成为目前遥感应用研究领域的热点和难点之一。介绍了环境与减灾监测预报小卫星中高光谱遥感数据产品命名规则和内容,以及产品数据的主要特点,通过对HSI数据辐射定标、Flaash大气校正和几何精校正等数据预处理方法,得出Flaash大气校正后的HSI数据,提高了高光谱数据的质量,地物光谱曲线更加符合实际情况,为下一步定量遥感研究奠定了基础。     

基于国产小卫星遥感数据的矿区土地覆盖与景观格局变化研究

采用北京一号小卫星和环境与灾害监测预报小卫星遥感数据,对徐州西矿区2008年～2009年土地利用/覆盖及景观格局变化进行分析。通过对4种分类方法的比较,选择精度最高的决策树分类图进行分析。试验表明:采矿活动导致徐州西矿区植被面积下降明显,大部分转为建筑用地;同时,矿区土地复垦使塌陷积水面积减少;区域景观破碎化程度有所下降,斑块的形状趋于规则化,景观多样性减小。评价变化检测精度,结果表明:国产小卫星遥感数据能有效地应用于矿区土地利用/覆盖及景观格局变化监测。     

基于遥感数据的云数据库技术的研究及应用

近年来,国产高分辨率卫星技术迅速发展,卫星监测遥感技术的应用范围越来越广泛,随之而来的卫星遥感数据量迅速增加,特别是航空遥感以及地面遥感等领域的出现,遥感数量已经达到十TB级。基于此,对海量遥感数据的存储、共享以及应用研究迫在眉睫。基于此,本文对遥感数据下的云数据库技术进行研究。本文主要分两部分介绍基于遥感数据的云数据库技术,首先介绍面向遥感数据的云数据库相关理论,然后研究遥感数据的云数据库技术的应用。     

海量遥感卫星数据存档方法的探讨

遥感卫星存档数据是整个遥感数据应用过程的基础。它具有数据量大、保存时间长、唯一性强的突出特点。近年来,随着遥感技术的发展,卫星下行数据的分辨率和采样率越来越高,如何能够高效的完成海量遥感数据的存档已成为一项急需解决的关键性问题。本文结合遥感卫星存档数据的特点,对数据存档的流程和目前的现状进行了介绍和分析,并根据计算机技术、数据存储技术的发展,探讨了海量遥感卫星数据存档方法的可能发展趋势。     

基于三级并行的遥感业务化处理系统研究

分析了遥感业务化处理系统的现实需求,针对当前遥感业务化处理系统存在的不足,结合遥感业务化处理系统和遥感影像并行处理算法两方面研究的成果,提出了基于三级并行的遥感业务化处理系统设计方案,将数据并行、功能并行、任务并行融合到遥感业务化系统中,并在环境与灾害监测预报小卫星星座系统工程中得到应用,为环境减灾提供了快速的遥感处理支持。介绍了系统的体系结构,工作流程,重点研究了三级并行的实现方式,并借助产品实例对其性能进行了测试。结果表明,基于三级并行的遥感业务化处理系统设计方案能够有效的提高遥感业务化处理的效率。     

我国首座千级净化水平环境样品库落成

国家环境保护卫星遥感重点实验室将开展卫星遥感图像处理与信息提取关键技术研究和空气、水、生态等环境质量遥感监测技术研究,建立环境突发事件遥感监测应急响应和跟踪系统,建立环境卫星遥感应用系统和便捷式环境卫星遥感快速监测系统。技术人员正在维护卫星地面接受站设备。     

影像数据分布并行计算处理平台体系架构研究

遥感影像数据并行处理系统大多依赖于国外商用产品,而国内自主化并行计算处理系统的任务流程化支撑能力以及并行计算性能难以适应规模化生产。为此,基于Hadoop的HDFS,MapReduce集群并行架构、CPU和GPU协同并行处理、内存映像、BMP等技术,提出流程驱动执行的高性能分布式并行计算处理平台体系架构。实验结果表明,工作站集群和工作站内多粒度混合的并行计算架构提高了平台并行处理性能,为海量遥感影像数据产品的批量生产提供一种自主化解决方案。     

Commentary on Krishnaswamy et al. - Quantifying and mapping biodiversity and ecosystem services: Utility of a multi-season NDVI based Mahalanobis distance surrogate

Remote sensing is a powerful tool for characterizing, estimating or modelling species diversity. Differences in environmental properties of different habitats should lead to differences of spectral responses, which can be detected by satellite imagery. Hence, spectral distance may be related to species diversity. Based on previous studies, Krishnaswamy et al. [Krishnaswamy, J., Bawa, K. S., Ganeshaiah, K. N., & Kiran, M. C. (2009). Quantifying and mapping biodiversity and ecosystem services: Utility of a multi-season NDVI based Mahalanobis distance surrogate. Remote Sensing of Environment.] used spectral distance to estimate species diversity. Since a noisy scatterplot of species versus spectral diversity is expected, the commonly used Ordinary Least Square regression may fail to detect trends which occur across other quantiles than the mean.Krishnaswamy et al. [Krishnaswamy, J., Bawa, K. S., Ganeshaiah, K. N., & Kiran, M. C. (2009). Quantifying and mapping biodiversity and ecosystem services: Utility of a multi-season NDVI based Mahalanobis distance surrogate. Remote Sensing of Environment.] proposed a quantile-quantile plot method as an alternative to conventional regression based approaches which are inappropriate for dependent pair-wise dissimilarity or similarity data. By this commentary I demonstrate the utility of a quantile regression technique to complement the Krishnaswamy et al. [Krishnaswamy, J., Bawa, K. S., Ganeshaiah, K. N., & Kiran, M. C. (2009). Quantifying and mapping biodiversity and ecosystem services: Utility of a multi-season NDVI based Mahalanobis distance surrogate. Remote Sensing of Environment.] graphical approach in terms of a predictive model.     

遥感网格的数据压缩与任务分配方法研究

网格计算作为分布式计算在科学计算领域的发展方向,可以为对地观测数据的处理提供强大的计算力。在分析遥感信息服务网格节点(Remote Sensing Information Service Grid Nodes,RSSN)中网络数据传输和负载均衡两个关键问题的基础上,提出了一种有效的基于游程编码和Huffman编码的数据压缩方法和基于"计算端元"的任务分配策略,该方法针对遥感影像特点进行有效数据压缩,具有较好的压缩比,达到了17%,且能实现任务负载均衡。并在遥感信息服务网格节点计算平台上,以中国范围内1km分辨率气溶胶光学厚度(Aerosol Optical Depth,AOD)反演计算为例,从压缩率和计算时间效率方面验证和分析了上述方法的有效性。     

Efficient parallel algorithm for pixel classification in remote sensing imagery

An important approach for image classification is the clustering of pixels in the spectral domain. Fast detection of different land cover regions or clusters of arbitrarily varying shapes and sizes in satellite images presents a challenging task. In this article, an efficient scalable parallel clustering technique of multi-spectral remote sensing imagery using a recently developed point symmetry-based distance norm is proposed. The proposed distributed computing time efficient point symmetry based K-Means technique is able to correctly identify presence of overlapping clusters of any arbitrary shape and size, whether they are intra-symmetrical or inter-symmetrical in nature. A Kd-tree based approximate nearest neighbor searching technique is used as a speedup strategy for computing the point symmetry based distance. Superiority of this new parallel implementation with the novel two-phase speedup strategy over existing parallel K-Means clustering algorithm, is demonstrated both quantitatively and in computing time, on two SPOT and Indian Remote Sensing satellite images, as even K-Means algorithm fails to detect the symmetry in clusters. Different land cover regions, classified by the algorithms for both images, are also compared with the available ground truth information. The statistical analysis is also performed to establish its significance to classify both satellite images and numeric remote sensing data sets, described in terms of feature vectors.     

低功耗异构计算架构的高光谱遥感图像分类研究

高光谱图像分类算法通常需要逐点对图像中的像素点进行迭代处理,计算复杂度及并行程度存在较大差异。随着高光谱遥感图像空间、光谱和辐射分辨率的不断提升,这些算法无法满足实时处理海量遥感图像数据的需求。通过分析NPU存储计算一体化模式与遥感图像分类算法的实现步骤,设计低功耗CPU+NPU异构资源计算架构的低秩稀疏子空间聚类（LRSSC）算法,将数据密集型计算转移至NPU,并利用NPU数据驱动并行计算和内置AI加速,对基于机器学习算法的海量遥感数据进行实时分类。受到big.LITTLE计算范式的启发,CPU+NPU异构资源计算架构由8 bit和低精度位宽NPU共同组成以提高整体吞吐量,同时减少图网络推理过程中的能量损耗。实验结果表明,与CPU计算架构和CPU+GPU异构计算架构的LRSSC算法相比,CPU+NPU异构计算架构的LRSSC算法在Pavia University遥感数据集下的计算速度提升了3~14倍。     

热红外遥感监测土壤含水量模型及其应用

在从理论上分析了地表土壤日温差、热惯量和土壤含水量三者的关系后,探讨了由地表土壤日温差推求热惯量、再由热惯量推求土壤含水量的方法,建立了气象卫星热红外遥感监测土壤含水量模型。将所建立的模型应用于实际土壤含水量的监测,做出了辽宁省,1988年8月11日近地表(10cm)土壤含水量分布图,通过实测资料验证,该模型具有较高精度。     

Commentary on Wang and Zender—MODIS snow albedo bias at high solar zenith angles relative to theory and to in situ observations in Greenland

The recent paper by Wang and Zender [Wang, X., & Zender, C. S. (2010). MODIS snow albedo bias at high solar zenith angles relative to theory and to in situ observations in Greenland. Remote Sensing of Environment.] draws erroneous conclusions about solar zenith angle biases at high latitudes by not making appropriate use of the extensive quality flags available with the MODIS BRDF/Albedo. Coarse resolution MODIS white-sky albedo data are compared with actual blue-sky field albedometer measurements from the Greenland GC-Net. By utilizing large area averages of the MODIS data product that combine both high quality and poor quality data indiscriminately, the authors erroneously conclude that the accuracy deteriorates for solar zenith angle (SZA) > 55° and often becomes physically unrealistic for SZA > 65°. Once the quality flags are considered, however, the comparisons demonstrate that the MODIS product performs quite well out to the recommended limit for product use of 70° SZA. This verifies the conclusions of an earlier more rigorous evaluation performed by Stroeve et al. [Stroeve, J., Box, J. E., Gao, F., Liang, S., Nolin, A., & Schaaf, C. B. (2005). Accuracy assessment of the MODIS 16-day albedo product for snow: comparisons with Greenland in situ measurements. Remote Sensing of Environment.]. With over a decade of observations and products now available from the MODIS instrument, these data are increasingly being used to evaluate and tune climate and biogeochemical models. However, such use should take into account the documented quality and limitations of the satellite-derived product.     

水质遥感信息与GIS集成方法与实现

讨论了RS和GIS技术及其集成的内在涵义、相互关系。以太湖流域的多源水环境监测信息为对象,将灰度图像数据与地面实测数据相结合,提出了基于RS、GIS集成技术的太湖流域动态监测分析方法。以RS、GIS和VisualBasic为工具,开发了太湖水环境监测信息管理系统,并简单地阐述了该系统的组成,通过对实际监测数据的处理和表达,说明了该系统在快速、高效、实时等方面具有明显优势。     

基于对象的可靠群组通信机制研究

近年来,网格计算技术日益成为用来解决数据和计算密集型应用的可行方案,网格运行平台本身和在网格环境中的并行应用都需要大量的点对多点的群组通信.提出一种灵活、可容错的群组通信机制.该机制基于远程方法调用(RMI),可为分布式并行应用提供高效、可容错的群组通信.通信方法可以在本地对象、远程对象,或一组对象中激活.这种通信采用异步方式,通信发起者可以选择全等待或必要性等待两种机制来获取通信结果.从而最大程度地保证通信的可靠性或高效性.     

Application of Meteosat derived meteorological information for crop yield predictions in Europe

This paper presents the utilization of surface fluxes and relative evapotranspiration derived from satellites for crop yield prediction using a dedicated crop growth simulation algorithm, the Environmental Analysis and Remote Sensing (EARS) Crop Growth Simulation algorithm (EARS-CGS). The objective was to test the EARS-CGS algorithm independent of ground data for crop yield prediction at national level in Europe. The algorithm is based on existing crop yield models but has been modified to assimilate satellite derived global solar radiation and actual evaporation information. The algorithm simulates crop biomass. A statistical method is utilized to relate crop biomass to crop yield and to correct for regional differences in yields that are not the result of radiation or water limitation. Six years of Meteosat data were processed to predict winter wheat and spring barley yields for Spain and the UK. The predicted yields were compared to the national reported yields and to forecasts of the European Statistical Office (EUROSTAT) and the Monitoring Agriculture by Remote Sensing-Crop Growth Monitoring System (MARS-CGMS). To evaluate the timeliness of the predictions the reported yields were compared to yield predictions made at different stages of the growing season. The results presented in this paper demonstrate that crop yields predicted from meteorological satellites can be applied to provide timely and reliable crop yield forecasts.     

基于Client/Server的影像数据库管理模式

该文针对遥感影像数据的特点,结合现代网络技术、数据库技术与多媒体 ＭＩＳ技术以及 Ｗｅｂ技术,探讨了一种基于 Ｃｌｉｅｎｔ／Ｓｅｒｖｅｒ的影像数据库的管理模式,该模式主要包括客户机／服务器技术、分布式数据库技术、影像数据处理。影像数据库结构、影像数据压缩等。