基于ArcEngine的城市房产信息查询系统设计与实现

以推进城市房地产业的信息化建设为目标,研究了城市房产信息查询系统的设计与实现。该系统以VS.NET为开发平台,选用ArcGIS Engine-组件式GIS作为地理信息系统软件,采用Visual C#编程语言作为开发设计工具,实现了高效便捷的对城市房地产信息的查询管理。本文着重介绍了系统功能设计和功能实现的过程。     

Use of satellite images for geographical localization of livestock holdings in Brazil

Google Earth^® provides free access to satellite images and has been used in several areas that require cartographic information. The present study assessed the inconsistencies between geo-referencing of livestock premises by GPS and the acquisition of geographic coordinates by remote sensing (RS) images provided by Google Earth^® in the Brazilian states of Bahia, Distrito Federal, Minas Gerais and Parana. The overall mean and standard deviation of the distances in the study were 30.98 ± 19.89 m. The mean distance differences between the two techniques were, for these states, 37.20 ± 19.75 m, 28.38 ± 17.38 m, 31.61 ± 15.72 m, 28.43 ± 24.30 m, respectively. Despite the fact that there is variation between the geo-referencing points using GPS and RS, geographical localization of health inspections should be useful as long as the errors between the results of the two methodologies are considered.     

Google图书计划背景下高校图书馆应加强的几个工作方面

介绍了当前Google的网络图书馆发展状况,分析了其迅速发展的背景和原因,以及对传统高校图书馆的冲击,提出了在新形式下高校图书馆要挖掘潜力,发挥自身优势的思路.     

发动机-测功机试验台电磁加载控制系统的研究

发动机-测功机系统具有非线性、强耦合等特点,无法建立精确的数学模型,将模糊控制和PID控制结合起来运用于发动机-测功机的测控系统中,建立了发动机-测功机传动系统动力学模型、测功机加载励磁电流模型,对发动机的转矩、转速进行了控制试验研究,结果表明控制精度高、动态响应快、超调量低,较好地解决了试验台控制的稳定性及测量的实时准确性问题,控制精度为4%。     

基于GoogleEarth的仰天岗实习基地的数字化教学模型研究

运用GoogleEarth免费提供的高分辨率卫星影像,对仰天岗实习基地进行了数字化教学模型研究,详细阐述了数字化教学模型的建立,其中包括仰天岗的数字化数学模型建立的特点、实习教学路线的数字化设计、实习教学点数字化设计、实习教学内容目录管理的数字化设计。     

基于Google Maps API的沙漠化地理信息系统设计方案

基于Google Maps API的Web地图服务的应用范围已经从大的门户网站扩展到小的个性社区、博客站点,成为网站构建者十分青睐的一种方式,但在备受关注的沙漠化研究领域却很少涉足。沙漠化是人类当今所面临的重大环境与社会问题之一,已经成为制约地区经济可持续发展的主要限制因素。本研究以四川西北部若尔盖地区为例,提出以Google Maps Web地图做为信息平台的地理信息系统。系统拥有视图、属性表、统计图表和图形等功能,为研究沙漠化的现状及危害程度,预测沙漠化发展趋势并规划防沙治沙措施提供了数据和图表参考依据。     

基于Google Earth的三峡库区地质灾害专业监测预警信息集成应用

监测预警是三峡库区地质灾害防治的主要措施,对其产生的海量信息进行有效管理是对库区进行有效防灾减灾和管理决策的基础。Google Earth作为一款免费提供全球三维遥感影像数据的虚拟地球软件平台,在对地质灾害专业监测预警信息集成管理和展示方面具有成本低、实施快、展示逼真等优点。在分析三峡库区地质灾害专业监测数据组成及其安全性、用户可视化的空间认知过程和习惯等的基础上,提出了三峡库区地质灾害专业监测预警信息集成方案,并利用Google Earth提供的功能予以实现,取得了较好的效果,也表明Google Earth在地质灾害信息集成、管理和展示等方面具有广阔的应用前景。     

基于3S的江西省森林防火指挥辅助决策系统

以Com GIS出发,基于先进的ArcGIS技术平台,使用ArcGIS Engine 9.3技术开发的江西省森林防火指挥辅助决策系统,阐述本系统在林火数据库管理,火险预防、火点定位、最佳扑火路线分析,火灾模拟、指挥决策、灾后评估等方面的功能和设计,系统的建设和使用将大大提高江西省森林防火的科学化和自动化管理水平,为进一步提高江西省森林防火和林火扑救的科学性和合理性,打下了良好的基础。     

学术搜索引擎Google Scholar与国学百度的比较研究

GOOGLE SCHOLAR和国学百度是两个重要的搜索引擎,本文介绍了他们各自的特点,并分析了其在学术检索中各自的作用。并从使用者的角度分析了两个引擎的不足之处。     

Global patterns in urban green space are strongly linked to human development and population density

Urban green space is important for alleviating high temperatures, pollution, and flooding in cities. Furthermore, it is becoming increasingly clear that urban green space is important for the mental and physical health of humans residing in cities and that urban green space may harbor unique biodiversity. Understanding the extent and drivers of urban green space is thus important. While urban green space has been mapped and studied at local to national scales, the global patterns and drivers of urban green space remain unknown, potentially hampering effective planning and allocation of resources toward reaching sustainable development goals. Here, we quantified the effect of environmental and socio-economic drivers (temperature, precipitation, human development, and population density) on urban green space globally by focusing on national capital cities. We used satellite imagery to map urban green space using two measures: the Normalized Difference Vegetation Index (NDVI), and the fractional cover of “green” land cover classes. NDVI is useful as it includes all vegetated surfaces, also small ones like gardens. However, land cover classes allow the exclusion of certain classes such as sports fields or cropland. We used boosted regression trees to show that climatic variables accounted for 75 % of the relative influence in urban green space, with a positive effect of precipitation and a negative effect of temperature. Importantly, socioeconomic variables accounted for 25 % of the influence on global urban green space, with a positive effect of human development index (HDI) and a negative effect of population density. HDI in relation to urban green space has not previously been tested globally, and our study shows that significantly affects urban greenspace. The results demonstrate that cities where development status is low and population densities are high, typically in the Global South, have less urban green space than the climate would predict. The results therefore suggest that human wellbeing does not only benefit directly from increasing human development and decreasing population densities in urban areas, but that these effects may be compounded by also improving nature’s contribution to people.