线状目标地图空间信息定量度量方法研究综述

地图信息的定量度量是地图制图学领域中的一个重要问题,也是评价制图质量、地图综合算法以及实现空间信息有效传输的基础.它不仅有助于理解空间信息的特征,而且对有效地利用空间信息也是十分重要的.本文回顾了国内外相关研究成果,指出现有研究中存在的主要问题和不足,围绕地图信息度量,从地图空间信息复杂性的角度和地图目标空间分布的角度...     

Land cover classification with multi-source data using evidential reasoning approach

Land cover classification is the core of converting satellite imagery to available geographic data.However,spectral signatures do not always provide enough information in classification decisions.Thus,the application of multi-source data becomes necessary.This paper presents an evidential reasoning (ER) approach to incorporate Landsat TM imagery,altitude and slope data.Results show that multi-source data contribute to the classification accuracy achieved by the ER method,whereas play a negative role to that...     

土地利用变化预测CBR方法的适应性分析

研究土地利用变化的方法很多,常见的有统计回归方法、概率统计方法、系统动力学方法、元胞自动机方法以及贝叶斯网络方法等。这些方法都各具特点,并得到了实际应用。虽然有些研究指出了一些方法的优点和不足,但是对其在土地利用变化问题上的适应性研究还比较有限。案例推理（Case Based Reasoning,简称CBR）作为研究土地利用变化的一种新方法,目前同样缺乏适应性方面的研究。因此,本文在土地利用的CBR方法的研究基础上,具体探讨该方法在土地利用变化预测上的适应性问题。研究分别从案例的选取方式、模型指标的选取以及指标权重的设定3个方面开展,通过对比试验以深入讨论3个方面的因素对预测精度的影响。研究结果显示,在历史案例丰富的情况下,通过选择重要的指标,并对其赋予较高权重,可以保证CBR方法在预测土地利用变化时的稳定性。此外,CBR中＂地理环境＂组分的引入,有效地提高了土地利用变化预测的精度。研究表明,CBR在解决土地利用变化问题上具有简单灵活、适用范围广、预测精度高以及保持形态稳定的特点,是一种解决地学问题的新方法。     

当前网络空间信息技术发展的战略需求分析和建议

国家三大科技发展战略要求地理信息系统瞄准市场提出新的标准和专利。网络基础设施传输能力的提高，使空间信息的互操作和应用成为可能，网络空间信息应用技术成为新的发展方向和市场。蓬勃的经济增长和市场需求尤其是民族特色的应用为具有中国特色的标准的产生提供了机会。我国网络空间信息系统的发展应当瞄准这个目标。网络空间信息系统发展的关键在于瞄向市场营销的技术创新，既有地理信息系统自身的市场营销。更包括地理信息系统对于市场营销方式改革的推动。     

A geospatial hybrid cloud platform based on multi-sourced computing and model resources for geosciences

Cloud computing has been considered as the next-generation computing platform with the potential to address the data and computing challenges in geosciences. However, only a limited number of geoscientists have been adapting this platform for their scientific research mainly due to two barriers: 1) selecting an appropriate cloud platform for a specific application could be challenging, as various cloud services are available and 2) existing general cloud platforms are not designed to support geoscience applications, algorithms and models. To tackle such barriers, this research aims to design a hybrid cloud computing (HCC) platform that can utilize and integrate the computing resources across different organizations to build a unified geospatial cloud computing platform. This platform can manage different types of underlying cloud infrastructure (e.g., private or public clouds), and enables geoscientists to test and leverage the cloud capabilities through a web interface. Additionally, the platform also provides different geospatial cloud services, such as workflow as a service, on the top of common cloud services (e.g., infrastructure as a service) provided by general cloud platforms. Therefore, geoscientists can easily create a model workflow by recruiting the needed models for a geospatial application or task on the fly. A HCC prototype is developed and dust storm simulation is used to demonstrate the capability and feasibility of such platform in facilitating geosciences by leveraging across-organization computing and model resources.     

“You know you can do this,right?”: developing geospatial technological pedagogical content knowledge and enhancing teachers’ cartographic practices with socio-environmental science investigations

Many barriers exist to K–12 classroom teachers’ adoption and implementation of geospatial technologies with their students. To address this circumstance, we have developed and implemented a geospatial curriculum approach to promote teachers’ professional growth with curriculum-linked professional development (PD) to support the adoption of socio-environmental science investigations (SESI) in an urban school environment that includes reluctant learners. SESI focus on social issues related to environmental science. The pedagogy is inquiry-driven, with students engaged in map-based mobile data collection and subsequent analysis with Web-based dynamic mapping software to answer open-ended questions. Working with four science and social studies teachers, we designed and implemented a sequence of three locally oriented, geospatial inquiry projects that were implemented with 140 9th grade students. We investigated how the geospatial curriculum approach impacted the teachers’ geospatial pedagogical content knowledge (PCK), their cartographic practices, and promoted geospatial thinking and analysis skills with their students. Findings revealed strong growth in teachers’ geospatial PCK, increased map use by teachers, use of maps as media for inquiry and not didactic instruction, and modeling to guide students’ geospatial analysis using GIS. Implications for PD to promote teachers’ geospatial PCK and in-class cartographic practices are discussed.     

浅谈移动测量系统未来发展

随着移动测量系统的不断发展,人们越来越关注该系统。本文主要通过介绍移动测量系统的组成和工作原理,分析了该系统与传统测量方式相比所具有的优点,并结合当前移动测量技术在地理空间数据采集中的应用,对未来移动测量技术的发展进行了展望。     

城市基础地理信息矢量数据的动态更新研究

城市地理空间基础数据作为各城市各专题系统和综合系统的空间定位基础和公共要素基础,基础地理信息数据库的生命力在于其数据的现势性和准确性,数据库建立后的更新维护非常重要。本文通过佛山市"基于数字城市建设的"一张图"应用模式研究"成果在顺德区具体应用阐述城市基础地理信息矢量数据的动态更新。     

国际地理信息产业内涵与分类研究综述

通过研究国际地理信息产业的相关表达,对国际地理信息产业内涵进行了综述。在此基础上,分析了国际市场研究机构对地理信息产业及相关产业分支的研究范围和相关产值规模,为我国地理信息产业内涵研究和分类方法的确定提供参考。     

Spatial cloud computing: how can the geospatial sciences use and help shape cloud computing?

Abstract

The geospatial sciences face grand information technology (IT) challenges in the twenty-first century: data intensity, computing intensity, concurrent access intensity and spatiotemporal intensity. These challenges require the readiness of a computing infrastructure that can: (1) better support discovery, access and utilization of data and data processing so as to relieve scientists and engineers of IT tasks and focus on scientific discoveries; (2) provide real-time IT resources to enable real-time applications, such as emergency response; (3) deal with access spikes; and (4) provide more reliable and scalable service for massive numbers of concurrent users to advance public knowledge. The emergence of cloud computing provides a potential solution with an elastic, on-demand computing platform to integrate – observation systems, parameter extracting algorithms, phenomena simulations, analytical visualization and decision support, and to provide social impact and user feedback – the essential elements of the geospatial sciences. We discuss the utilization of cloud computing to support the intensities of geospatial sciences by reporting from our investigations on how cloud computing could enable the geospatial sciences and how spatiotemporal principles, the kernel of the geospatial sciences, could be utilized to ensure the benefits of cloud computing. Four research examples are presented to analyze how to: (1) search, access and utilize geospatial data; (2) configure computing infrastructure to enable the computability of intensive simulation models; (3) disseminate and utilize research results for massive numbers of concurrent users; and (4) adopt spatiotemporal principles to support spatiotemporal intensive applications. The paper concludes with a discussion of opportunities and challenges for spatial cloud computing (SCC).