波段选择协同表达高光谱异常探测算法

高光谱遥感影像具有光谱分辨率极高的特点,承载了大量可区分不同类型地物的诊断性光谱信息以及区分亚类相似地物之间细微差别的光谱信息,在目标探测领域具有独特的优势。与此同时,高光谱遥感影像也带来了数据维数高、邻近波段之间存在大量冗余信息的问题,高维度的数据结构往往使得高光谱影像异常目标类和背景类之间的可分性降低。为了缓解上述问题,本文提出了一种基于波段选择的协同表达高光谱异常探测算法。首先,使用最优聚类框架对高光谱波段进行选择,获得一组波段子集来表示原有的全部波段,使得高光谱影像异常目标类与背景类之间的可分性增强。然后使用协同表达对影像上的像元进行重建,由于异常目标类和背景类之间的可分性增强,对异常目标像元进行协同表达时将会得到更大的残差,异常目标像元的输出值增大,可以更好地实现异常目标和背景类的分离。本文使用了3组高光谱影像数据进行异常目标探测实验,实验结果表明,该方法与其他现有高光谱异常目标探测算法对比,曲线下面积AUC(Area Under Curve)值更高,可以更好地实现异常目标与背景分离,能够更有效地对高光谱影像进行异常目标探测。     

Satellite image analysis using crowdsourcing data for collaborative mapping: current and opportunities

ABSTRACT

Researchers are continually finding new applications of satellite images because of the growing number of high-resolution images with wide spatial coverage. However, the cost of these images is sometimes high, and their temporal resolution is relatively coarse. Crowdsourcing is an increasingly common source of data that takes advantage of local stakeholder knowledge and that provides a higher frequency of data. The complementarity of these two data sources suggests there is great potential for mutually beneficial integration. Unfortunately, there are still important gaps in crowdsourced satellite image analysis by means of crowdsourcing in areas such as land cover classification and emergency management. In this paper, we summarize recent efforts, and discuss the challenges and prospects of satellite image analysis for geospatial applications using crowdsourcing. Crowdsourcing can be used to improve satellite image analysis and satellite images can be used to organize crowdsourced efforts for collaborative mapping.     

粤港澳大湾区知识网络空间结构演化特征与影响机制

以2000—2018年国内外期刊数据库合作论文数据为基础,借助社会网络分析和空间结构指数法分析了粤港澳大湾区知识空间网络结构演化特征与影响因素,结果发现：1）知识网络格局由广州的“一家独大”逐渐演变为广州、深圳、香港“齐头并进”的发展态势。香港虽然处于知识网络的核心位置,但受行政壁垒的影响,主要与广州、深圳高等级的城市建立紧密的知识合作联系。2）粤港澳大湾区知识联系网络呈现“核心—边缘”结构,西部地区知识联系远低于东部地区,虽然研究期内湾区的知识网络的极化特征得到一定的缓解,但不均衡性仍然显著。3）湾区知识活动主体的自身需求是促进城市间知识合作的内在驱动力,知识环境和知识联系通道是区域知识合作网络外在推动力,在内生作用和外生作用的共同影响下,知识合作产出得以实现,粤港澳大湾区知识网络得以发展。     

海岸带及其调查技术进展

海岸带是重要海陆过渡带地貌单元与区域,兼受海陆动力双重作用与影响,包括不同类型的沉积相,经历复杂的动力沉积、地貌演变及灾变过程。海岸带调查涉及学科交叉融合,调查要素相对独立与内容多学科交叉并存。我国曾分别于1960年、1981年和2003年组织开展过全国海岸带综合调查工作,调查获取了大量丰硕成果。当前海岸带调查与研究过程中亦暴露出一些亟需突破问题,包括:1)海岸带存在大范围"盲区",浅水易陷、礁石养殖等区域难以到达,成为海岸带数据"空白区"、调查"禁区";2)我国海岸带观测平台数量少、分布零散,未形成综合有效观测网,导致长时间序列、多源准同步调查数据缺乏,难以准确把握海岸带变化规律,破解资源环境有关问题;3)海岸带数据获取智能化程度低,严重阻碍制约有关对策及时有效性;4)海岸带不同学科协同调查、交叉融合研究模式尚未建立,不能及时发现海岸带科学问题。今后海岸带调查将在海岸带高分辨率过程数据、全覆盖无死角实时动态数据获取技术,长时间序列综合数据采集平台建设,陆海空全天候立体化数据采集传输及快速智能决策,以及海岸带多学科交叉攻关研究等方面取得突破。     

面向协同式森林灭火决策的领域本体构建及其解析

森林灭火决策的参与人员可能来自不同的组织、不同领域,他们有不同知识结构、专业背景、学识和各自的经验、偏好,这往往不利于决策过程中的交流、协同进行。本文把本体引入协同式森林灭火决策中,解决决策成员在协作中对他人所述的内容理解一致问题。分析了现有建立领域本体的主要方法,并借鉴软件开发的生命周期理论,提出建立面向森林火灾的领域本体的具体实现方法。以森林灭火决策为应用导向,通过对森林灭火决策的内容分析及与领域专家相互交流,根据领域中概念分类体系和概念的组合结构,从相关领域(林业、气象学、消防工程、地理学)抽象出概念术语集、关系集、函数集、规则集等,建立可共享、理解、重用、互操作的概念模型;利用本体建模工具,建立森林灭火本体库;设计与实现了本体的解析与可视化工具,用户可以交互式的查询术语的概念内涵,利用可视化工具,显示概念之间的关系。研究成果将为学科或领域间的高效协作打下通信与交流的基础,为林业、消防的信息化研究、林火本体服务提供可借鉴的框架和成果,为林火管理和应急指挥决策提供一个语义层级次上的重要途径。     

Towards a collaborative global land cover information service

ABSTRACT

The need and critical importance of global land cover and change information has been well recognized. Although rich collection of such information has been made available, the lack of necessary information services to support its easy access, analysis and validation makes it difficult to find, evaluate, select and reuse them through well-designed workflows. Aiming at promoting the development of the needed global land cover information services, this paper presents a conceptual framework for developing a Collaborative Global Land Cover Information Service (CoGland), followed by discussions on its implementation strategies. The framework supports connected and shared land cover and change web services around the world to address resource sharing, community service and cross-board collaboration needs. CoGland can benefit several recent international initiatives such as Future Earth, and many societal benefit areas. The paper further proposes that CoGland be developed within the framework of the Group on Earth Observations with the support of a number of key organizations such as the United Nations Expert Committee on Global Geospatial Information Management, the International Society for Photogrammetry and Remote Sensing, and International Society of Digital Earth. It is hoped that this paper can serve as a starting point for further discussions on CoGland developments.     

Developing a Web-based flood forecasting system for reservoirs with J2EE / Développement sur Internet avec J2EE d’un système de prévision de crue pour barrages

Abstract

Abstract A flood forecasting system is a crucial component in flood mitigation. For certain important large-scale reservoirs, cooperation and communication among federal, state, and local stakeholders are required when heavy flood events are encountered. The Web-based environment is emerging as a very important development and delivery platform for real-time flood forecasting systems. In this paper, the findings of a case study are presented of the development of a Web-based flood forecasting system for reservoirs using Java 2 platform Enterprise Edition (J2EE). J2EE of Sun Microsystems is chosen as the development solution for the Web-based flood forecasting system, Weblogic 6.0 of BEA as the container provider, and JBuilder 7.0 of Borland as the development tool. One of the key objectives in this project is to establish a collaborative platform for flood forecasting via Web technology in order to render hydrological models and data available to stakeholders and experts involved and thus offer an efficient medium for transferring and sharing information, knowledge and experiences among them. Compared with general Web-based query systems and traditional flood forecasting systems, the Web-based flood forecasting system is more focused on the on-line analysis of model-based forecasting of floods and provides opportunities for improving the transfer of information and knowledge from the hydrological scientists and managers to decision makers. Finally, a prototype system is used to demonstrate the system application.     

Evaluating the Process and Outcomes of Collaborative Conservation: Tools,Techniques, and Strategies

Abstract

Collaborative conservation has been touted as a viable option for addressing contentious natural resource stewardship issues in a way that represents the diverse voices impacted by, and involved in, conservation decisions. Engaging meaningfully in collaborative conservation involves overcoming a unique set of challenges while also realizing opportunities. In this special issue, we use the term collaborative conservation evaluation to encompass research and evaluation related to collaborative governance and collaborative natural resource management projects, programs, or decision-making processes that leverage a participatory approach, involve multiple stakeholders, and incorporate a range of contemporary evaluation approaches. Here, we provide a series of articles and tools intended to highlight different approaches to evaluation that utilize a variety of methodologies adapted for different contexts. We intend for these articles to spark further conversation and inspire future directions in evaluating collaborative conservation for researchers and practitioners.     

苏州市区多种地下地质资源协同开发利用研究

地下空间、地下水、浅层地热能和地质材料是重要的地下地质资源,协同开发利用是大势所趋。苏州既是历史文化名城又是现代国际大都市,城市发展至今对地下地质资源的需求相当迫切。通过对苏州各类地下地质资源的的识别分析,表明其具备分别开发地下空间、地下水、浅层地热能和地质材料资源的能力。若多种资源协同开发,平面上开发利用条件较好,竖向尺度地下浅层到次深层适宜地下空间和地质材料的协同开发,而深层适宜以浅层地热能为主的协同开发。结合苏州国土空间发展格局和地下资源的优势分布特征,城镇空间建议采取“地下空间+浅层地热能”的协同利用模式;农业空间建议采取以“浅层地热能”为主的协同利用模式;生态空间予以生态环境保护。     

基于Fabric区块链的智能合约协同开发系统

针对传统协同开发系统普遍采用"中心化"存储架构带来的单点故障、数据不可信、故障难以追责等安全问题,以及传统协同办公系统仅支持单一企业内部办公的问题,本文借助超级账本Fabric区块链技术以及业务流程管理和服务组合技术实现了一款基于Fabric区块链的智能合约协同开发系统.系统架构中首先结合传统中心化存储技术和区块链去中心化存储技术,通过将系统核心业务数据信息存储在区块链分布式账本中而把业务流程管理等不重要的数据存储在传统数据库中解决了"中心化"存储管理带来的安全信任问题.其次系统通过结合超级账本联盟链技术提供的企业联盟的特点使得系统可以应用于企业联盟办公中,解决了单一办公的问题.