Measured and perceived visual complexity: a comparative study among three online map providers

We present a study on human perception of map complexity, with the objective of better understanding design decisions that may lead to undesirable levels of complexity in web maps. We compare three complexity metrics to human ratings of complexity obtained through a user survey. Specifically, we use two algorithmic approaches published by others, which measure feature congestion (FC) and subband entropy (SE), as well as our own approach of counting object types rather than individual objects. We compare these metrics with each other as well as with human complexity ratings for three maps of the same area from map providers Google Maps, Bing Maps, and OpenStreetMap. Each map design is assessed at three different scales (levels of detail). We find that (1) the FC and SE metrics appear to be adequate predictors of what humans consider complex; (2) object-type counts are slightly less successful at predicting human-rated complexity, implying that clutter is more important in perceived complexity than diversity of symbology; and (3) generalization choices do impact human complexity ratings. These findings contribute to our understanding of what makes a map complex, with implications for designing maps that are easy to use.     

A workflow for Sustainable Development Goals indicators assessment based on high-resolution satellite data

ABSTRACT

For evaluating the progresses towards achieving the Sustainable Development Goals (SDGs), a global indicator framework was developed by the UN Inter-Agency and Expert Group on Sustainable Development Goals Indicators. In this paper, we propose an improved methodology and a set of workflows for calculating SDGs indicators. The main improvements consist of using moderate and high spatial resolution satellite data and state-of-the-art deep learning methodology for land cover classification and for assessing land productivity. Within the European Network for Observing our Changing Planet (ERA-PLANET), three SDGs indicators are calculated. In this research, harmonized Landsat and Sentinel-2 data are analyzed and used for land productivity analysis and yield assessment, as well as Landsat 8, Sentinel-2 and Sentinel-1 time series are utilized for crop mapping. We calculate for the whole territory of Ukraine SDG indicators: 15.1.1 – ‘Forest area as proportion of total land area’; 15.3.1 – ‘Proportion of land that is degraded over total land area’; and 2.4.1 – ‘Proportion of agricultural area under productive and sustainable agriculture’. Workflows for calculating these indicators were implemented in a Virtual Laboratory Platform. We conclude that newly available high-resolution remote sensing products can significantly improve our capacity to assess several SDGs indicators through dedicated workflows.     

建立影像地图集生产系统,提高实践性教学质量

结合《苏州市影像地图集》的设计和研制,着重讨论基于新技术进行影像地图集生产的软硬件环境,以及通过对新技术的生产流程、过程控制方法等关键环节的技术研究和实践,建立了影像地图集生产实践教学系统。该系统为教师提供了先进的科学研究、技术开发和技术应用环境和条件,为开展实践性教学和进行地图集设计、生产提供理论和技术指导。     

中国古代地图的数学基础与地理空间维度认知

从几个典型的中国古地图的数学基础出发,结合相关的数学方法,探讨了中国古人在地理空间维度认知方面走过的历程。认为,当中国古代地图发展到以"计里画方"进行地图绘制时,已经实现了3维地理空间的科学认知。这也是"计里画方"的制图方法可以持续1 000多年的理论依据。     

基于Flash技术的综合电子地图集制作技术

重点介绍了基于Flash平台制作多媒体综合电子地图集的开发集成方法以及具体功能的实现。     

Self-organised clustering for road extraction in classified imagery

The extraction of road networks from digital imagery is a fundamental image analysis operation. Common problems encountered in automated road extraction include high sensitivity to typical scene clutter in high-resolution imagery, and inefficiency to meaningfully exploit multispectral imagery (MSI). With a ground sample distance (GSD) of less than 2 m per pixel, roads can be broadly described as elongated regions. We propose an approach of elongated region-based analysis for 2D road extraction from high-resolution imagery, which is suitable for MSI, and is insensitive to conventional edge definition. A self-organising road map (SORM) algorithm is presented, inspired from a specialised variation of Kohonen's self-organising map (SOM) neural network algorithm. A spectrally classified high-resolution image is assumed to be the input for our analysis. Our approach proceeds by performing spatial cluster analysis as a mid-level processing technique. This allows us to improve tolerance to road clutter in high-resolution images, and to minimise the effect on road extraction of common classification errors. This approach is designed in consideration of the emerging trend towards high-resolution multispectral sensors. Preliminary results demonstrate robust road extraction ability due to the non-local approach, when presented with noisy input.     

北京市地形图图式应用研究

城市建设出现了地形图图式未规定的地物要素,地形测量、地理信息系统、数字制图技术的应用给图式的设计提出了新的课题,本文旨在探讨设计和修订图式的思路和方法。     

广州市第二次全国土地调查1：2000土地利用现状图输出

标准分幅土地利用现状图制作与输出是广州市第二次全国土地调查的一项重要工作。由于国家、省没有1：2000土地利用现状图的标准或技术规程,根据我市作业模式、数据特点,制定了技术要求,开发了由建库数据到制图数据的转换程序,依据上交给国家、省的数据库成果,完成了全市十区两市10225幅图的电子数据制作,并打印纸质图件归档。     

超文本电子地图集系统

介绍了超文本电子地图集系统HEAS的若干概念,分析了现有地理信息系统的优点和弱点,介绍了超文本电子地图集系统的特性和武测超文本电子地图集实验系统方面的研究成果。     

4D一体化多媒体电子地图集理论方法和技术研究与开发--以《云南省生态环境多媒体电子地图集》为例

本文首先研究了4D数据一体化多媒体电子地图集的理论和信息机理,包括4D数据在电子地图集中的集成、融合和应用的信息机理,多源多类信息交互认知和传输机理,4D信息的查询、分析、模拟、调控和表达的信息机理,以及4D数据一体化电子地图集的理论框架。其次,文章深入研究和解决了建立4D一体化多媒体电子地图集过程中的诸多技术方法问题,例如多源多类数据的集成和融合、基于主导数据库的多重表达、多媒体地图动画、基于4D数据的信息分析和量算、生态环境信息动态仿真和虚拟表达等。在论文第三部分,文章介绍了作者研发的《云南省生态环境多媒体电子地图集》成果,包括其结构、功能、内容、超媒体链接等方面的设计,查询功能和分析量算功能的开发,以及本电子地图集的分析应用成果。