Mapping 3D visibility in an urban street environment from mobile LiDAR point clouds

ABSTRACT

Visibility determination is a key requirement in a wide range of national and urban applications, such as national security, landscape management, and urban design. Mobile LiDAR point clouds can depict the urban built environment with a high level of details and accuracy. However, few three-dimensional visibility approaches have been developed for the street-level point-cloud data. Accordingly, an approach based on mobile LiDAR point clouds has been developed to map the three-dimensional visibility at the street level. The method consists of five steps: voxelization of point-cloud data, construction of lines-of-sight, construction of sectors of sight, construction of three-dimensional visible space, and calculation of volume index. The proposed approach is able to automatically measure the volume of visible space and openness at any viewpoint along a street. This approach has been applied to three study areas. The results indicated that the proposed approach enables accurate simulation of visible space as well as high-resolution (1 m × 1 m) mapping of the visible volume index. The proposed approach can make a contribution to the improvement of urban planning and design processes that aim at developing more sustainable built environments.     

A hierarchical indexing strategy for optimizing Apache Spark with HDFS to efficiently query big geospatial raster data

ABSTRACT

Earth observations and model simulations are generating big multidimensional array-based raster data. However, it is difficult to efficiently query these big raster data due to the inconsistency among the geospatial raster data model, distributed physical data storage model, and the data pipeline in distributed computing frameworks. To efficiently process big geospatial data, this paper proposes a three-layer hierarchical indexing strategy to optimize Apache Spark with Hadoop Distributed File System (HDFS) from the following aspects: (1) improve I/O efficiency by adopting the chunking data structure; (2) keep the workload balance and high data locality by building the global index (k-d tree); (3) enable Spark and HDFS to natively support geospatial raster data formats (e.g., HDF4, NetCDF4, GeoTiff) by building the local index (hash table); (4) index the in-memory data to further improve geospatial data queries; (5) develop a data repartition strategy to tune the query parallelism while keeping high data locality. The above strategies are implemented by developing the customized RDDs, and evaluated by comparing the performance with that of Spark SQL and SciSpark. The proposed indexing strategy can be applied to other distributed frameworks or cloud-based computing systems to natively support big geospatial data query with high efficiency.     

无人机技术在海岛测绘中的应用

为提高海岛测绘的技术手段,将无人机引入海岛地形调查中,以Swallow-P小型固定翼无人机开展惠州市大亚湾虎洲海岛大比例尺测图为例,系统归纳了无人机外业数据采集与内业数据处理的具体流程,并制作了DEM和DOM成果;经过实测地面点精度分析得出虎洲无人机大比例尺测图成果平面位置中误差和高程中误差符合1∶1000测图精度要求。     

Understanding geographical patterns of a city’s diurnal rhythm from aggregate data of location‐aware services

Do collective behaviors of the daily routine of a city's inhabitants form the periodical cycling of human activity at the city level (here termed the “city's diurnal rhythm”)? If the answer is yes, do there exist geographical patterns in the city's diurnal rhythm? Using a nationwide dataset of observed uses of location‐aware services in the largest Chinese social media platform, we first confirm the significant periodicity in city‐level human activity from the perspective of the aggregate degree of social media uses over a day. We then investigate geographical changes in the diurnal rhythm of human activity and its local variations in different parts of the city, and between weekdays and weekend days, over 340 Chinese cities. Our results show that a city's diurnal rhythm across the whole country exhibits both regular, nationally conspicuous shifts along geographical gradients and locally distinct spatiotemporal changes within the city. Our findings could provide insights into the characterization of the daily routine of city‐level human activity and its geographical patterns, and have potential for several issues in terms of planning, management, and decision‐making related to human population dynamics.     

MicroStation 95在测绘领域的应用开发

介绍了利用Microstation 95开发测绘应用系统、定制用户界面、建立地形图符号库和制作应用软件安装程序的方法和技术.还介绍了具体操作中的一些经验和技巧.     

角锥棱镜直角误差斜入射法检测的理论分析

以矢量形式的折射、反射定律为基础,详细推导了角锥棱镜直角误差δ与分划板自准直双像间距t之间的关系,提出了基于斜入射法、利用自准直平行光管直接测量角锥棱镜直角误差的光电检测系统,并进行了测量精度的理论分析。     

Feasibility of Re-injecting the Production Effluent from Alkali–Surfactant–Polymer Flooding Systems Back into a Reservoir to Further Improve Oil Recovery

Natural Resources Research - Alkali–surfactant–polymer (ASP)-produced effluent contains polymer, alkali and surfactant, and it has higher content of suspended oil droplets and suspended...     

气候系统预测:基础创新和集成应用

随着全球变暖,极端天气气候事件增强,天气气候灾害造成的损失也愈发严重。当前气候预测的准确性远远不能满足社会需要,气候系统预测理论和方法面临着众多挑战性问题。为提档气候预测科学水平和准确率,由南京信息工程大学和中山大学承担的“气候系统预测研究中心”获得国家自然科学基金基础科学中心项目支持(2021年1月—2025年12月)。在该项目执行的前三年,项目团队开展了大量深入系统的研究,并取得了若干重要进展:1)揭示了气候系统的若干关键变化、驱动力和机制;2)剖析了海-陆-冰-气相互作用对我国重大极端气候事件的影响;3)在气候系统数值模式研发和预测系统集成方面取得重要进展;4)发展了延伸期-S2S-年代际的气候系统预测理论和方法。本文对这些进展作了扼要介绍,并针对气候与环境变化归因、古今气候环境研究融合、跨时空气候系统变异和极端气候、人工智能与气候科学、年代际预测和风险应对体系等关键科学问题做了展望。     

西昆仑-喀喇昆仑造山带锂矿成矿特征与成矿规律初探

西昆仑- 喀喇昆仑造山带中生代花岗伟晶岩相当发育,主要分布于麻扎- 康西瓦缝合带以南的喀喇昆仑造山带,构成了西自木吉—塔什库尔干,东到大红柳滩长达600 km的喀喇昆仑稀有金属成矿带。通过多年的研究,本文对西昆仑- 喀喇昆仑造山带37处稀有金属矿床(点)进行了全面系统的梳理,认为喀喇昆仑- 喀喇昆仑造山带表现为“西铍东锂”的格局,稀有金属成矿年龄集中213~206 Ma。将喀喇昆仑造山带稀有金属成矿带划分为木吉- 塔什库尔干稀有金属成矿亚带、赛图拉- 大红柳滩稀有金属成矿亚带,从西向东可划定4个矿化集中区：木吉- 布伦口稀有金属集中区、塔什库尔干- 塔吐鲁沟稀有金属矿化集中区、康西瓦稀有金属矿化集中区、大红柳滩- 白龙山稀有金属矿化集中区。同时,认为西昆仑- 喀喇昆仑造山带西段下一阶段的找矿可放在西合休南锂铍找矿远景区、阿然保泰铍找矿远景区、木吉西锂铍找矿远景区。     

莱西市以科学发展观推进国土资源管理工作

莱西市国土资源局在学习实践科学发展观活动中突出实践特色,紧密联系思想工作和发展实际,以支持发展更加科学,保护资源更加坚决,服务社会更加主动,维护权益更加务实,自身建设更加自觉为目标,努力把学习实践活动的成效转化为保障和促进当地经济社会平稳较快发展的动力,取得了显著成效。