基于多源信息融合的浅海超低频声源目标探测关键技术及实现

以多传感器信息融合理论为指导,结合现代信息处理技术与数据驱动建模及科学计算技术,研究浅海超低频声源目标激发共存地震波的复合声场中超低频声波传播特性和数据驱动建模的水下目标深度识别等关键技术,并论证了技术实现方案及路径。结果表明:以复合矢量水听器、地震波监测仪等多传感器信息融合理论为指导研究前海超低频声源目标可以克服传统声场建模存在的问题,有助于浅海超低频声源目标探测及改善海洋水下声学监测手段。在提高声呐探测设备的测量准确度、精度方面具有重要的理论意义,对周边海域为浅海的我国海防具有实战价值。     

结合深度学习和图割法的遥感影像建筑物检测

提出一种基于卷积神经网络和图割法的自动提取高分影像建筑物的方法。首先,通过卷积神经网络定位与检测建筑物的位置,逐一提取单个建筑物轮廓,利用检测结果分别建立建筑物和非建筑物的高斯混合模型（GMM）,然后结合最大流最小割的图像分割方式实现全局优化,完成建筑物初步提取,最后用形态学进行优化。通过试验证明了该方法的可行性。     

对基础测绘"十四五"规划的若干思考

着眼于明确机构改革后基础测绘在自然资源管理业务格局中的职责定位、工作重点,以及如何按照新《测绘法》更好地履行"为经济建设、国防建设、社会发展和生态保护服务"的法定要求,分析了"十四五"基础测绘发展的基本形势,据此提出"十四五"规划工作的基本思路和主要遵循,明确了工作重点和相关措施,相关观点已经在"十四五"基础测绘规划编制工作中得到体现。     

兼顾志愿者地理信息的国家应急测绘公众服务平台设计

随着互联网技术的进步和新一代网络信息传播模式的深入发展,志愿者地理信息的研究和应用日益广泛,但由于其规范性和均一性方面的缺陷,在应急公共服务领域,志愿者信息的有效利用依旧是亟需突破的难题。本文将重点介绍国家应急测绘公众服务平台设计思路和总体架构,并结合志愿者地理信息特点,探讨该类信息在国家应急测绘公众服务平台建设中的处理流程和应用模式,力求在应急信息资源共享和服务平台共建方面进行新的尝试,为我国突发事件应急体系建设提供有益实践。     

A novel spatial index using spatial analyses and hierarchical fuzzy expert system for obtaining green TOD: a case study in Tehran city

Sustainable development is a vital and challenging factor for managing urban growth smartly. This factor contains three main components, namely economic growth, ecological protection and social justice. Green Transit-Oriented Development (GTOD) is a consummate planning approach in line with those components. Implementation of GTOD in an urban area is underpinned by its quantification. Therefore, a quantitative spatial index based on several indicators related to TOD and Green urbanism concepts should be developed. In this study, Geo-spatial Information Science and hierarchical fuzzy inference system (HFIS) were employed to calculate the indicators and aggregate them, respectively. In order to showcase the feasibility of the proposed method, it was implemented in a case study area in the City of Tehran, Iran. The result of this method is an integrated spatial GTOD index, which measures the neighbourhoods’ GTOD levels. These measurements specify weaknesses and strengths of neighbourhoods’ factors. Therefore, this index helps decision-makers to plan neighbourhoods based on land use and public transit views. Additionally, the HFIS method helps decision-makers to consider criteria and indicators with their inherent uncertainties and aggregate them with much fewer rules. For evaluating the results, the developed GTOD index was assessed with municipal action planning and attraction maps. According to the outcomes of the assessment, it is concluded that the proposed method is adequately robust and efficient for smart and sustainable urban planning.     

一体化综合减灾智能服务系统研究

针对目前我国减灾服务重决策轻预警,减灾服务技术、系统、应用集成不够,尚缺乏完善的一体化综合减灾智能服务体系现状。该文从测绘地理信息视角,分析了室内外一体化应急定位、多源应急数据融合、灾害场景可视化、灾害模型分析服务等关键技术,构建了一体化综合减灾智能服务原型系统,并在国家基础地理信息中心和陕西省的相关应急部门进行了实际应用,实现了应急信息的一体化感知、定位、融合、分析、服务,为我国综合减灾决策分析提供了技术支撑。     

Semantic segmentation of high spatial resolution images with deep neural networks

Availability of reliable delineation of urban lands is fundamental to applications such as infrastructure management and urban planning. An accurate semantic segmentation approach can assign each pixel of remotely sensed imagery a reliable ground object class. In this paper, we propose an end-to-end deep learning architecture to perform the pixel-level understanding of high spatial resolution remote sensing images. Both local and global contextual information are considered. The local contexts are learned by the deep residual net, and the multi-scale global contexts are extracted by a pyramid pooling module. These contextual features are concatenated to predict labels for each pixel. In addition, multiple additional losses are proposed to enhance our deep learning network to optimize multi-level features from different resolution images simultaneously. Two public datasets, including Vaihingen and Potsdam datasets, are used to assess the performance of the proposed deep neural network. Comparison with the results from the published state-of-the-art algorithms demonstrates the effectiveness of our approach.     

基于CityEngine的校园三维建模

针对平面地图描述建筑物不直观、复杂且具有限制性的缺点,以CityEngine软件为平台,选取铜陵学院为研究区域,对其进行三维可视化研究。利用ArcMap软件对铜陵学院的Google影像图进行矢量化,通过Cityengine软件创建新场景,基于CGA语言建立了研究区主要建筑物、道路、运动场、绿化区的三维模型。实验结果表明,虚拟三维场景地图相较二维平面图更直观、完整,对三维城市建模具有较好的应用与参考价值。     

武汉城市圈经济与环境协调性分析和评价研究

以用地现状、人口调查、经济统计等信息为基础,搭建了武汉城市圈生态环境分析和评价信息平台,设计了统计分析、指标评价、决策支持等模块。按照区县单元分析了武汉城市圈人口、经济与生态环境相关性和协调性,其研究结果对开展武汉城市圈“两型”社会建设具有重要意义,可为武汉城市圈的社会经济与生态环境协调发展提供科学的决策参考。     

大比例尺地理信息数据服务模式的研究

大比例尺地理信息数据由于详尽的数据内容和精准的位置信息,在城市经济社会发展中发挥着重要作用。然而由于传统的服务方式的限制,数据的使用效率并不高。地理空间框架数据结合GIS技术和网络技术,将大比例尺地理信息数据使用方式从线下转到线上,提高了数据使用效率。而本文提出的主动式地理信息服务模式是一种全新的地理信息服务模式,将大比例尺地理信息服务数据与用户业务数据深度融合,最大限度地满足用户的业务需求,将是地理信息服务模式未来的发展方向。