从对地观测卫星到对地观测脑

21世纪以来,高分辨率对地观测卫星快速发展,对地观测系统由最初的单星模式发展为现在的轻小型卫星组建星座,实现了全天时、全天候、全方位的对地精细化观测。未来将对地观测卫星星座与通信卫星、导航卫星和飞机等空间节点通过动态组网,建立天基空间信息网络,以实现智能化空天信息的实时服务。为了进一步增强系统的智能化水平,提高系统感知、认知能力和应急响应能力,本文提出未来空间信息网络环境下对地观测脑（earth observation brain,EOB）的概念,对地观测脑是基于事件感知的智能化对地观测系统。详细介绍了对地观测脑的概念模型及需要解决的关键技术,举例说明了对地观测脑初级阶段的感知、认知过程。将来对地观测脑可以回答何时（when）、何地（where）、何目标（what object）发生了何种变化（what change）,并在规定的时间（right time）和地点（right place）把这些正确的信息（right information）推送给需要的人（right people）的手机或其他智能终端,全球用户可实时获得所需的任何数据、信息和知识。     

关于我国空间对地观测系统发展战略的若干思考

一、人类进入空间对地观测的新时代 自1957年前苏联发射第一颗人造地球卫星以来，各国已向空间发射了5000余颗卫星或空间飞行器，其中相当大部分为对地观测卫星。从1960年美国发射第一颗气象卫星之后，人类进入了一个从空间观测地球的新时代。     

对地观测与抗震救灾

2008年5月12汶川地震灾害发生后,全国相关涉灾部门充分利用空间信息技术为汶川地震救灾提供科学有效的决策支持,在灾害应急响应中发挥了巨大的作用。本文主要从对地观测以及地震救灾的空间信息技术支持两个方面,分析了空间信息技术在救灾中的作用。为今后空间信息如何更好地服务于自然灾害救助,提出了中国空间信息技术发展的思路与建议。     

对地观测微小卫星的发展现状及其应用

本文对现代微步卫星的基本概念及其技术特点进行了探讨,分析了对地观测微小卫星的 ２和应用前景,并对发展我国自己的对地观测微小卫星提出了相应的建议。     

建设国家对地观测体系,构筑"数字地球"

论述了“数字地球”的特征与重要意义,指出对地观测是“数字地球”的核心内容之一。建议中国不失时机地组织建设国家对地观测体系。该体系可在信息获取、处理与应用３个层面上构建,并提出近期中国对地观测应优先发展的领域,以持续地为“数字地球”发展作贡献     

论智能化对地观测系统

分析了不同遥感用户对遥感数据的不同需求,提出了解决遥感数据处理自动化、智能化和实时化的方案———智能对地观测系统(IEOS),分析其体系结构和关键技术,并对IEOS的前景做了展望。未来全球IEOS的用足出不出户,就可以通过终端设备,方便获取全球任何空间信息。     

微小卫星对地观测及其应用前景

微小卫星技术是当今空间技术、电子技术、计算机技术、光学技术及遥感技术高度综合的结晶。目前,世界各国都在关注这项技术的发展与应用,以英国萨瑞大学空间技术中心为代表的国外对地观测民用卫星已为十几个国家进行小卫星及微小卫星研制及技术开发服务,我国有关部门已与萨瑞大学开展了有效的合作。从现有小卫星获取的数据资料质量及特征分析,其光谱及几何分辨率都较高,在全球灾害、环境监测、农业估产及资源调查等有广阔的应用前景。发展我国的微小卫星技术,将对我国航天遥感事业起到重要推动作用。     

高分辨率对地观测技术在智慧城市中的应用

从智慧城市的概念和发展历程出发,提出数字城市、物联网、云计算等智慧城市建设的关键技术,探讨了高分辨率对地观测技术在智慧城市建设中的应用,列举了智慧城市的典型应用,指出了从数字城市发展到智慧城市的必然趋势,并展望智慧城市的挑战和美好前景。     

我国空间对地观测技术的发展与展望

经过50余年发展,我国空间对地观测技术实现了从无到有、由弱到强等巨大跨域,已在经济建设和国防安全等领域取得了广泛应用。当前,物联网、大数据、云计算、人工智能等飞速发展,空间对地观测技术正在发生深刻变革。为把握技术发展脉络,推动“十四五”我国空间对地观测领域高质量发展,本文系统梳理了我国空间对地观测技术的发展历程,从国际竞争、国内需求和技术革新等方面分析了面临的机遇和挑战,展望了巨型星座建设、海量数据处理、智能融合应用等技术发展方向。     

On the degree of polarization for SAR sea oil slick observation

A polarimetric model to relate the degree of polarization, DoP, to the sea surface scattering with and without oil slicks, under low-to-moderate wind conditions, is proposed. DoP, measured directly from the Mueller scattering matrix, is shown to be a reliable measure of the departure from Bragg scattering; a phenomenon that, under low-to-moderate wind conditions, occurs when an oil slick is present. Following this theoretical rationale, a simple filter is developed to observe oil slicks in quad-polarimetric full-resolution Synthetic Aperture Radar (SAR) data. Experiments, undertaken on a meaningful set of quad-polarization Single Look Complex (SLC) C-band RADARSAT-2 SAR data, where both well-known oil slicks and a weak-damping look-alike are in place, demonstrate the soundness of the model and its effectiveness from an operational viewpoint.     

Multi-threaded compression of Earth observation time-series data

ABSTRACT

Earth observation data are typically compressed using general-purpose single-threaded compression algorithms that operate at a fraction of the bandwidth of modern storage and processing systems. We present evidence that recently developed multi-threaded compression codecs offer substantial benefits over widely used single-threaded codecs in terms of compression efficiency when applied to a selection of moderate resolution imaging spectroradiometer (MODIS) datasets stored in the HDF5 format. Compression codecs from the LZ77 and Rice families are shown to vary in efficacy when applied to different MODIS data products, highlighting the need for compression strategies to be tailored to different classes of data. We also introduce LPC-Rice, a new multi-threaded codec, that performs particularly well when applied to time-series data.     

Earth observation data based rapid flood-extent modelling for tsunami-devastated coastal areas

Earth observation (EO)-based mapping and analysis of natural hazards plays a critical role in various aspects of post-disaster aid management. Spatial very high-resolution Earth observation data provide important information for managing post-tsunami activities on devastated land and monitoring re-cultivation and reconstruction. The automatic and fast use of high-resolution EO data for rapid mapping is, however, complicated by high spectral variability in densely populated urban areas and unpredictable textural and spectral land-surface changes. The present paper presents the results of the SENDAI project, which developed an automatic post-tsunami flood-extent modelling concept using RapidEye multispectral satellite data and ASTER Global Digital Elevation Model Version 2 (GDEM V2) data of the eastern coast of Japan (captured after the Tohoku earthquake). In this paper, the authors developed both a bathtub-modelling approach and a cost-distance approach, and integrated the roughness parameters of different land-use types to increase the accuracy of flood-extent modelling. Overall, the accuracy of the developed models reached 87–92%, depending on the analysed test site. The flood-modelling approach was explained and results were compared with published approaches. We came to the conclusion that the cost-factor-based approach reaches accuracy comparable to published results from hydrological modelling. However the proposed cost-factor approach is based on a much simpler dataset, which is available globally.     

Advancing Digital Earth: beyond the next generation

The Digital Earth (DE) movement is gaining momentum. Much of it is unstructured. This paper examines a number of recent developments including those in health sensors (Wearable Absence, Q-Sensor, and Guardian Angels) and systems frameworks (Gelernter's Mirror Worlds, Virtual Australia, and New Zealand). Consideration is given to the implications of DE for citizens and on citizen science, including those of ethics. A suite of principles to guide the development of DE is proposed.     

一种SAR图像车辆目标鉴别特征及其提取方法

该文引入差分盒维法来计算高分辨率SAR图像车辆目标的一种新的鉴别特征,即间隙度特征,可以用来定量评估车俩目标感兴趣区域内像素幅度的不规则程度和间隙尺寸,以此消除杂波虚警.基丁散射中心理论分析了车辆目标和自然地物后向散射强度分布的差异性,并从理论上推导出间隙度特征具有对相干斑噪声不敏感的特点,由此构成了SAR图像车辆目标鉴别处理的一个尺度不变特征.采用MSTAR车辆目标数据和背景杂波数据检验了所提特征的鉴别性能,并与Hausdorff维数的鉴别性能做了比较,结果显示间隙度特征具有较好的鉴别性能,可以去除大部分的自然地物虚警和非车辆类人造目标干扰,鉴别虚警率较低.     

地球观测数据共享的发展和趋势

地球观测数据共享是地球科学和相关学科科研活动中非常重要的基础性工作,是对地观测信息生命周期中的重要环节。受到由资源提供者、资源消费者和资源加工者组成的社会生态系统发展变化的影响,共享模式经历了无共享、项目共享、部门共享、社会共享等渐进的4个发展阶段,并呈现出区域差异和阶段差异。地球观测数据共享的概念体系包含数据开放、数据共享、数据互联等不同层次的问题,并受到信息技术等使能技术的驱动。其中开放性代表数据在网络中可被访问的状态,共享性是对于数据重复使用的授权和模式,互联性则是强调可共享数据资源在科学含义上的相互理解。而地球观测数据共享的技术体系则包含数据开放技术、数据共享技术和数据出版与引用技术。目前地球观测领域的数据共享正在经历巨大的文化、政策、技术和应用变革,下一代的地球观测数据设施集中体现了数据的共享和协作,并将呈现国际化、多学科化、标准化、设施化、大数据化和公众社会化等新的技术特征,将对相关科学活动产生重大影响。     

Polarimetric differential SAR interferometry in an arid natural environment

Ground deformation measurements have contributed to a better understanding of the processes and mechanisms involved in natural hazards. Those include landslides, subsidence, earthquakes and volcanic eruptions. Spaceborne Differential Interferometric Synthetic Aperture RADAR (DInSAR) is a well studied technique for measuring ground deformation. Quality of deformation measurements, however, is often degraded by decorrelation. With the advent of fully polarimetric SAR satellite sensors, polarimetric optimization techniques exploiting polarimetric diversity improve the phase quality of interferograms. In this paper, we analyzed three polarimetric optimization methods to determine the optimal one for application in an arid natural environment. We considered coherence decomposition in single and double phase center scenarios. Coherence estimation bias associated with each optimization method has been analyzed. We compared the derived displacement values with terrestrial GPS measurements. The study shows that polarimetric optimization increases the number of coherent pixels by upto 6.89% as compared with a single polarization channel. The study concludes that polarimetric optimization coupled with DInSAR analysis yields more reliable deformation results in a low coherence region.     

Big Earth data: disruptive changes in Earth observation data management and analysis?

ABSTRACT

Turning Earth observation (EO) data consistently and systematically into valuable global information layers is an ongoing challenge for the EO community. Recently, the term ‘big Earth data’ emerged to describe massive EO datasets that confronts analysts and their traditional workflows with a range of challenges. We argue that the altered circumstances must be actively intercepted by an evolution of EO to revolutionise their application in various domains. The disruptive element is that analysts and end-users increasingly rely on Web-based workflows. In this contribution we study selected systems and portals, put them in the context of challenges and opportunities and highlight selected shortcomings and possible future developments that we consider relevant for the imminent uptake of big Earth data.     

Moon-based Earth observation: scientific concept and potential applications

Although Earth’s surface parameters obtained from satellite data have become more and more precise, it is still difficult to guarantee temporal consistency and spatial continuity for large-scale geoscience phenomena. Developing new Earth observation platforms is a feasible way to improve the consistency and continuity of such data. As the planet’s only natural satellite, the Moon has special advantages as a platform for observing Earth, including long lifetime, whole disk view, tectonic stability and unique perspective. After presenting the observation geometry constructed by using the ephemeris, this paper mainly discusses the characteristics of a lunar platform and the proper Moon-based sensors, as well as the scientific objectives of Moon-based Earth observation. Solid Earth dynamics, the energy budget of Earth, Earth’s environmental elements and the Earth-space environment are four potential applications analysed in this paper.