SegOptim—A new R package for optimizing object-based image analyses of high-spatial resolution remotely-sensed data

Geographic Object-based Image Analysis (GEOBIA) is increasingly used to process high-spatial resolution imagery, with applications ranging from single species detection to habitat and land cover mapping. Image segmentation plays a key role in GEOBIA workflows, allowing to partition images into homogenous and mutually exclusive regions. Nonetheless, segmentation techniques require a robust parameterization to achieve the best results. Frequently, inappropriate parameterization leads to sub-optimal results and difficulties in comparing distinct methods.Here, we present an approach based on Genetic Algorithms (GA) to optimize image segmentation parameters by using the performance scores from object-based classification, thus allowing to assess the adequacy of a segmented image in relation to the classification problem. This approach was implemented in a new R package called SegOptim, in which several segmentation algorithms are interfaced, mostly from open-source software (GRASS GIS, Orfeo Toolbox, RSGISLib, SAGA GIS, TerraLib), but also from proprietary software (ESRI ArcGIS). SegOptim also provides access to several machine-learning classification algorithms currently available in R, including Gradient Boosted Modelling, Support Vector Machines, and Random Forest.We tested our approach using very-high to high spatial resolution images collected from an Unmanned Aerial Vehicle (0.03 – 0.10 m), WorldView-2 (2 m), RapidEye (5 m) and Sentinel-2 (10 – 20 m) in six different test sites located in northern Portugal with varying environmental conditions and for different purposes, including invasive species detection and land cover mapping. The results highlight the added value of our novel comparison of image segmentation and classification algorithms. Overall classification performances (assessed through cross-validation with the Kappa index) ranged from 0.85 to 1.00. Pilot-tests show that our GA-based approach is capable of providing sound results for optimizing the parameters of different segmentation algorithms, with benefits for classification accuracy and for comparison across techniques. We also verified that no particular combination of an image segmentation and a classification algorithm is suited for all the tasks/objectives. Consequently, it is crucial to compare and optimize available methods to understand which one is more suited for a certain objective.Our approach allows a closer integration between the segmentation and classification stages, which is of high importance for GEOBIA workflows. The results from our tests confirm that this integration has benefits for comparing and optimizing both processes. We discuss some limitations of the SegOptim approach (and potential solutions) as well as a future roadmap to expand its current functionalities.     

基于三维实景的警用应急指挥系统设计与实现

随着网络通信、三维仿真技术和地理信息系统的发展,传统的警用二维地理信息系统在三维可视化、复杂空间分析、业务数据共享等方面的不足日益显著。为进一步提高公共安全服务能力,深化警用公共安全信息体系的建设,本文基于三维实景建模技术和WebGIS技术,研究设计以高精度的三维实景模型数据为基础的公安应急指挥系统,实现对公共安全事件业务处理、信息联动、指挥决策等功能。     

基于监督与非监督分割评价方法提取高分辨率遥感影像特定目标地物的对比研究

基于地理对象的影像分析方法已成为高分辨率遥感影像分析的重要手段。影像分割作为其关键步骤,如何设置合适的分割算法参数对后续分割和分类结果有重要的影响。目前分割参数优选方法的探讨分别从非监督与监督分割质量评价2个方面展开,而何者更适合高分辨率遥感影像特定目标地物分析仍缺乏对比研究。本文以城镇和乡村为例,选取多源遥感数据Quickbird、WorldView-2和ALOS影像中共有的3种典型土地覆被为研究对象,基于2种具有代表性的非监督与监督方法ESP2 (Estimation of Scale Parameter 2)与ED2 (Euclidean distance 2) 进行实验,对最优分割和分类的结果进行全面的对比分析。结果表明：① 相同实验参数下,监督方法均能以较少的分割数据集获得目标地物的最优分割结果,且与真实地理对象吻合度更高;② 非监督方法依靠影像自身特征分析进行分割参数优选,无法克服不同景观格局和影像分辨率的影响,而监督方法可通过改变参考数据集的面积和空间分布模式等来降低其影响;③ 非监督方法往往因为欠分割而漏分小目标地物,这样会严重影响局部分类结果。虽然本文中非监督与监督方法的整体分类精度均可达90.08%以上,但非监督方法的漏分率却是监督方法的1.43~4.65倍。因此,本研究认为监督方法更适合分析高分辨率遥感影像特定小目标地物。     

基于自发地理信息的“一带一路”区域陆路交通状况分析

路网密度的研究是实施“一带一路”愿景之互联互通倡议的基础工作。“一带一路”顺应了世界经济全球化、一体化、多极化、信息化的趋势,牵连着蓬勃发展的亚太和发达的欧洲经济圈,带动中间国家的经济发展。在新形势下,如何通过交通基础设施建设推进丝绸之路经济带沿线区域间的互联互通、促进区域合作和经济发展,具有重要的现实意义。本文利用自发地理信息数据——OpenStreetMap（OSM）道路网数据,运用地理信息系统（GIS）空间分析技术,探究了“一带一路”陆路经济带辐射区域亚欧大陆的路网络密度和通行能力的空间分布格局,并分析了六大经济走廊节点城市的公路可达性空间格局。结果表明：“一带一路”陆路经济带的交通基础设施的发展存在着不平衡现象;路网密度和通行能力均呈现沿海高内陆低的空间格局;中亚、西亚地区和中南半岛地区成为道路水平落后带,限制了丝绸之路经济带资源整合与贸易畅通,建议在建设新跨国公路铁路同时,对原有老旧道路进行加宽加固等升级改造;全区域道路等级级配不合理;节点城市可达性具有明显的分异状况,六大经济走廊中83%的区域可达性在10 h以内。研究产出亚欧大陆1 km分辨率路网密度和通行能力数据集,发现了“一带一路”陆路经济带道路水平的薄弱区域,为“一带一路”陆路经济带的交通基础设施建设以及进一步的道路网研究提供了基础数据。     

2019年度国家自然科学基金天文学科常规项目申请和资助情况分析

LIU Qiang;DONG Guo-xuan;CHANG Xiang(NSFC), Beijing 100085, China)     

面向可持续发展的冰冻圈科学

21世纪以来, 在全球气候变暖的大背景下, 冰冻圈科学发展快速。在梳理国际冰冻圈相关研究态势、 分析中国相关研究动向的基础上, 总结了“冰冻圈科学”发展的历程并简要介绍了冰冻圈科学的基本框架。研究指出, 自20世纪70年代冰冻圈概念正式提出以来, 国际社会以推出气候与冰冻圈（WCRP-CliC）计划和成立国际冰冻圈科学协会（IACS）为标志, 并在深化冰冻圈自身机理、 过程认识的同时, 更加关注与其他圈层之间相互作用中的冰冻圈效应, 表明冰冻圈研究趋向变化 - 影响 - 适应这一主线发展, 在一定程度显现出了“冰冻圈科学”的核心特征。中国冰冻圈研究近20年、 尤其是近10年发展迅猛, 沿着冰冻圈科学的主体思路, 在冰冻圈变化, 冰冻圈变化对生态、 水文、 气候、 地表环境以及社会经济的影响等方面取得了系统性成果, 对冰冻圈科学的内涵和外延有了系统的认识。在分析国际冰冻圈科学孕育和发展背景并简要总结中国冰冻圈研究近况基础上, 对冰冻圈科学学科框架体系从科学内涵和外延、 研究构架和学科组成等方面进行了论述, 冰冻圈科学已经成为一门涉及广泛、 过程机理研究与可持续发展密切关联的全新学科。     

Two new species of Mesozoic tree ferns (Osmundaceae: Osmundacaulis) in Eurasia as evidence of long-term geographic isolation

The fossil trunks and rhizomes of Osmundaceae provide important information about its evolutionary history. Due to limited records of the Mesozoic trunks and rhizomes in the Eurasia of the Northern Hemisphere, our understanding on the fossil diversity of the Osmundaceae is hindered. Two new species of the Osmundaceae trunks, Osmundacaulis asiatica sp. nov. and Osmundacaulis sinica sp. nov. representing the first discovery of the Mesozoic tree fern genus Osmundacaulis in Eurasia, are described from Wudalianchi and Qiqihar, Heilongjiang Province, Northeast China, which enriches the plant diversity of the Osmundaceae in the Eurasia, and provides vital evidence for studying the distribution, radiation and evolution of the genus during the Cretaceous. The fossil records suggest that Osmundacaulis species may have evolved from a common ancestor, which first appeared in the Australian portion of Pangaea, and then spread to ancient northern North America and ancient East Asia. Since then, they developed into different species through their own evolutionary lines. The Chinese species have a special local feature that the outer cortex is thicker than the inner cortex, in contrast with reported Osmundacaulis species having thinner outer cortex and thicker inner cortex. Long-term geographic isolation may have led to the radiation of diverse Osmundacaulis species and the appearance of region-specific features, such as the thick outer cortex and the thin inner cortex of the Chinese species. Among all reported Osmundacaulis species, the two new species found in China, O. nerii from the Jurassic of Australia and the O. lemonii from the Jurassic of the USA, have special groups of mucilage-sacs inside sclerenchyma ring of petiole base. Mucilage sacs probably originated independently among taxonomic groups, representing convergent adaptations to similar habitats, rather than indicating genetic inheritance from a common ancestor.     

自发地理信息在灾后恢复监测中的应用研究框架

文章探讨了如何有效利用自发地理信息（Volunteered Geographic Information, VGI）大数据促进灾后恢复监测工作。首先概述了国内外VGI相关研究的发展现状,明确了VGI用于灾后恢复监测研究的不足,然后提出了一个基于VGI大数据的灾后恢复监测应用的研究框架,助力于灾后恢复监测各类具体恢复目标（如旅游业恢复、工商业恢复、生活常态恢复）的实现。该研究框架包含数据获取、数据质量控制和数据挖掘3个核心组成部分。其中,数据获取对象以VGI为主,以传统官方权威数据为辅;数据质量控制主要是通过模糊逻辑专家系统和人工神经网络（深度学习）确保VGI适用性;数据挖掘则是以变革式范例为理论基础,利用定量和定性结合的方法调查灾区基建、经济和安全3个灾后恢复主要方面的状态。最后,文章还讨论了当前利用VGI大数据促进灾后恢复监测所存在的一些局限性,包括VGI来源的可持续性问题、各VGI平台应用程序接口的数据获取限制问题和VGI应用所涉及的用户隐私问题。     

粤港澳大湾区建设国际科技创新中心的战略思考

基于对全球创新格局与趋势的探讨,以及对国际科技创新中心内涵与特性的解读,剖析了粤港澳大湾区当前建设国际科技创新中心所具备的优势与面临的挑战,并对科技创新中心建设提出几点战略性的思考。当前粤港澳大湾区正处于整体迈进知识经济时期,创新要素在地理空间上高度集聚,创新生态条件不断完善,创新全球化的影响在区域内初显,拥有雄厚的制造业基础,市场对创新的需求极为可观,基本具备建设国际科技创新中心的条件。但同时,我们应该看到由于粤港澳一体化的制度障碍以及巨大的区域内部差距,粤港澳大湾区的创新发展还存在创新要素聚而不联、创新要素流动不畅、体制机制转换对接困难、关键核心技术受制于人等现实挑战。在充分发挥粤港澳互补优势、补齐短板的基础上,粤港澳大湾区应立足源头创新,将建设国际产业创新策源地作为立区之本;实施产业驱动,将建设国际产业科技创新中心作为核心功能;推进制度创新,将建设协同创新示范区作为关键突破。以源头创新促产业创新,以制度改革推协同创新,最终实现粤港澳大湾区创新协同与一体化融合发展。     

国外旅游风险研究综述——基于Web of Science的统计分析

西方国家对风险的研究已较为成熟,但旅游风险作为关注点在2001年“9?11”事件后才逐渐被学界所重视,相关综述较少且多侧重于旅游风险感知,对旅游风险研究整体把握的成果较少。近年来,一些研究已应用文献计量可视化来探索旅游学科的网络结构,但在旅游风险、安全研究领域运用此方法的成果不多。回溯相关概念后,以2001—2018年“Web of Science核心合集”中296篇与国外旅游风险研究高度相关的论文、会议文章、综述为基础,利用科学计量工具CiteSpace为研究工具,对国外旅游风险研究发文数量、期刊分布、知识基础、关键词进行可视化分析。研究发现：①国外旅游风险研究可分为三个阶段,各时期研究区域、对象、主体、热点不断演进;②文献数据库的期刊分布表明,目前国外旅游风险研究涉及多个学科,主力军是旅游类和医学类;③发现了7篇高突现性文献,可分为医学及传染病、风险感知、风险容忍度3类。对深入认识国外旅游风险研究领域的知识基础及其演化关系具有一定价值,同时也能为国内旅游风险研究与实践提供参考。