国土资源行业“3S”技术集成研究及实用技术体系构建

本文面向国土资源信息化建设的实际需求,通过关键技术研究和技术集成,建立基于“3S”的国土资源数据获取、更新、管理、交换与应用的技术体系,通过应用示范研究,形成实用、可推广的技术流程和应用软件。研究结果表明,基于“3S”的技术体系,以其精确的空间定位、快速准确的数据获取、强大的数据管理能力,能够满足国土资源信息化建设的实际需要。     

全国资源与生态环境遥感监测数据管理与应用服务系统设计

为推动资源与生态环境遥感监测数据的应用与服务,为国家、相关行业管理决策和社会公众提供有价值的信息,需要在资源与生态环境遥感监测成果数据基础上,开发数据管理与应用服务系统。本文从国家资源与生态环境建设的实际需求出发,结合国土资源部实施的环北京地区资源与生态环境遥感监测成果,探讨资源与生态环境遥感监测数据管理与应用服务的技术解决方案,搭建资源与生态环境遥感监测数据管理与应用服务技术平台,并实现网络环境下对资源与生态环境监测形成的各种类型数据的集成化管理。     

广东省特色农作物标准波谱数据库框架设计与示范应用

本研究着眼于广东省典型特色农作物的波谱，建立了波谱数据库，该库分为知识库、遥感实测波谱库、模型库、波谱分析和 荔枝园示范5大部分。 在波谱分析模块设计上提供了波谱数据查询、分析等功能，通过对荔枝园种植面积应用示范，给用户提供了极 大方便。     

测绘职业教育教学改革探讨

随着空间科学技术和计算机技术的发展，以“3S”技术为代表的测绘高新技术已普遍应用于测绘生产中。作为培养测绘实用型人才的测绘职业学校，测绘专业如何重新划分、测绘教育与教学内容如何改革，是测绘教育界普遍关注的问题，本文从教学的角度对有关问题进行了探讨。     

附加系统参数平差法在导线网中的应用

本文探讨了附加系统参数平差法在带有测距系统误差的导线网中的应用，说明了当系统误差比较显著时．采用附加系统参数平差法的可行性、必要性及其优越性。     

GPS新近发展及其军事应用

本文简述了GPS的最新发展动态，着重分析了GPS在精确制导武器上的应用形式和效果，指出了GPS制导技术存在的局限性及其未来发展趋势。     

法国国家测绘局（IGN）述评

法国是世界测绘强国之一。法国国家测绘局（IGN）是法国测绘的领导机构。本文介绍了IGN的概况，并对IGN大地测量、地图制图、对外服务、研究机构等情况作了较详细的描述。在此基础上对IGN的未来发展特点提出了几点看法。     

测绘情报工作发展战略思考

本文通过对“十五”期间测绘情报工作的回顾，分析了目前测绘情报研究存在的主要问题，讨论了今后测绘情报工作的发展对策。     

Mining Association Rules in Spatio-Temporal Data: An Analysis of Urban Socioeconomic and Land Cover Change

This research demonstrates the application of association rule mining to spatio‐temporal data. Association rule mining seeks to discover associations among transactions encoded in a database. An association rule takes the form A→B where A (the antecedent) and B (the consequent) are sets of predicates. A spatio‐temporal association rule occurs when there is a spatio‐temporal relationship in the antecedent or consequent of the rule. As a case study, association rule mining is used to explore the spatial and temporal relationships among a set of variables that characterize socioeconomic and land cover change in the Denver, Colorado, USA region from 1970–1990. Geographic Information Systems (GIS)‐based data pre‐processing is used to integrate diverse data sets, extract spatio‐temporal relationships, classify numeric data into ordinal categories, and encode spatio‐temporal relationship data in tabular format for use by conventional (non‐spatio‐temporal) association rule mining software. Multiple level association rule mining is supported by the development of a hierarchical classification scheme (concept hierarchy) for each variable. Further research in spatio‐temporal association rule mining should address issues of data integration, data classification, the representation and calculation of spatial relationships, and strategies for finding ‘interesting’ rules.     

Quality Assessment Of Digital Surface Models Generated From IKONOS Imagery

The growing applications of digital surface models (DSMs) for object detection, segmentation and representation of terrestrial landscapes have provided impetus for further automation of 3D spatial information extraction processes. While new technologies such as lidar are available for almost instant DSM generation, the use of stereoscopic high-resolution satellite imagery (HRSI), coupled with image matching, affords cost-effective measurement of surface topography over large coverage areas. This investigation explores the potential of IKONOS Geo stereo imagery for producing DSMs using an alternative sensor orientation model, namely bias-corrected rational polynomial coefficients (RPCs), and a hybrid image-matching algorithm. To serve both as a reference surface and a basis for comparison, a lidar DSM was employed in the Hobart testfield, a region of differing terrain types and slope. In order to take topographic variation within the modelled surface into account, the lidar strip was divided into separate sub-areas representing differing land cover types. It is shown that over topographically diverse areas, heighting accuracy to better than 3 pixels can be readily achieved. Results improve markedly in feature-rich open and relatively flat terrain, with sub-pixel accuracy being achieved at check points surveyed using the global positioning system (GPS). This assessment demonstrates that the outlook for DSM generation from HRSI is very promising.