场认知方式、性别和惯用空间语对地理空间定向能力影响的实验研究

目前人们对空间定向能力影响因素的研究多关注性别与空间定向能力的关系,较少涉及场认知方式、惯用空间语等因素对空间定向能力的影响。本文以空间认知眼动实验的方式展开研究,通过国内版镶嵌图形测验（EFT）、问卷调查等途径获取被试的场认知方式、性别和惯用空间语等基本信息,使其在控制单一环境变量的虚拟三维空间中完成不同难度的定向任务。进而构建正确率和效率2个指标来衡量空间定向能力,通过统计分析确定空间定向能力的影响因素。研究结果表明：（1）不同场认知方式和不同惯用空间语人群的定向正确率和效率差异统计结果均不显著,场认知方式和惯用空间语对空间定向能力无显著影响;（2）不同性别人群之间定向效率无显著差异而正确率存在显著差异,性别对空间定向能力具有显著影响,男性的空间定向能力较女性更强。     

RZCORS在莒县数字地形图测绘中的应用

结合项目实际工作,介绍基于日照市连续运行参考站系统（RZCORS）的网络RTK在莒县大比例尺测图中的应用方式和工作效率,并与传统GPS实时差分系统RTK技术进行比较,进而说明RZCORS系统的优势及发展前景。     

基于Flash技术的网络地图发布研究与应用

分析了网络地图的特点与功能,回顾了网络地图的发展历程,并对现今较为成熟的国内、外网络地图发布技术及其实现方式做了比较研究。在此基础上,结合“深圳市资源节约与综合利用网”企业信息发布的实际需要,采用“Flash”技术,实现了真正意义上的“瘦客户端”的网络地图发布系统。     

数字正射影像拼接的研究

介绍了数字正射影像,详细探讨了数字正射影像的拼接,并介绍了一种处理影像重叠区域过渡的方法,以消除拼接后影像的接缝。     

Groupers on the Edge: Shelf Edge Spawning Habitat in and Around Marine Reserves of the Northeastern Gulf of Mexico

The northeastern Gulf of Mexico contains some of the most diverse and productive marine habitat in the United States. Much of this habitat, located on the shelf edge in depths of 50 to 120 m, supports spawning for many economically important species, including groupers. Here, we couple acoustic surveys with georeferenced videography to describe the primary spatial and geologic features of spawning aggregation sites for four economically important species: gag (Mycteroperca microlepis), scamp (M. phenax), red grouper (Epinephelus morio), and red snapper (Lutjanus campechanus), with notes on fish distribution and abundance and spawning activities. We provide information on movement patterns of reef fish determined using acoustic telemetry. Finally, we discuss the possible coupling of geomorphology with hydrographic features to influence the overall productivity of the region and the importance of spatial fishery management in sustaining that productivity.     

A GEOGRAPHICAL ANALYSIS OF IMAGE INTERPRETATION METHODS

Image interpretation methods, procedures for relating image pattern to ground conditions, are essential to our use of remote sensing imagery. These methods can be analyzed in respect to the role of ancillary information in the image interpretation process. In general, those procedures that are comparatively independent of ancillary information can be applied in varied geographic settings. Because almost all interpretation procedures depend to some extent upon ancillary information, a detailed and integrated knowledge of the cultural and physical landscape is a prerequisite for both manual and automated interpretation procedures.     

Forest Fire Alert System: a Geo Web GIS prioritization model considering land susceptibility and hotspots – a case study in the Carajás National Forest,Brazilian Amazon

To increase the monitoring potential of forest fires, an alert classification methodology using satellite-mapped hotspots has been established to help forest managers in the prioritization of which hotspot to be verified in the field, thus potentially improving the distribution of fire-fighting resources. A computer application was developed based on web-distributed geographical information technology whose main function is to interact automatically generated satellite hotspots and risk areas indicated in fire-susceptibility maps and classify them into five alert levels. The location of the hotspots is available continuously every 4 h, and a susceptibility map is produced daily through map algebra algorithm, which uses static (topography, vegetation and land use) and dynamic (weather) variables. Every process runs through automated geoprocessing routines. The methodology was tested during the dry period of 2007 in the Carajás National Forest, in the Brazilian Amazon, within an area of 400,000 ha. It is a critical area constantly threatened by fires caused by invasions and deforestation owing to intense agribusiness advances and mining activities in its surroundings. This situation results in observations of many hotspots inside the study area for the same day and almost the same time period, in places of extreme opposites, demanding complex rapid analysis and hindering the decision of the displacement of fire-fighting teams. Further, a major mining company operates within the National Forest area, maintaining actions of protection as part of its environmental mining license. Results are presented under three aspects: (i) the credibility of the daily susceptibility map (algorithm), which showed strong correlation between areas of greatest risks and the confirmed forest fires; (ii) the reliability of hotspots (alert levels), confirming 71% of fires; (iii) accuracy in the decision of which hotspot to be checked, which revealed the same number of verifications at different alert levels, 82% confirmed alert 5 hotspots (maximum) and only 50% from alert 1 (minimum), resulting in faster fire-fighting actions, minimizing burned areas and, in some cases, allowing fire control before its spreading. Therefore, the methodology demonstrated that GIS routines are able to determine the relationship between a reality-based, interpreted susceptibility map of the area and satellite-generated hotspots, highlighting the ones of highest hazard level through the alert classification, becoming an important tool to help decisions from the fire-control center, especially for high-risk regions. The methodology may be extrapolated to other forested areas.     

Integrated assessment for establishing an oil environmental vulnerability map: Case study for the Santos Basin region,Brazil

The growth of maritime transport and oil exploitation activities may increase the risk of oil spills. Thus, plans and actions to prevent or mitigate impacts are needed to minimize the effects caused by oil. However, tools used worldwide to support contingency plans have not been integrated, thus leading to failure in establishing priority areas. This investigation aimed to develop indices of environmental vulnerability to oil (IEVO), by combining information about environmental sensibility to oil and results of numerical modeling of spilled oil. To achieve that, a case study concerning to oil spills scenarios in a subtropical coastal area was designed, and IEVOs were calculated and presented in maps, in order to make the information about the areas’ vulnerability more easily visualized. For summer, the extension of coastline potentially affected by oil was approximately 150 km, and most of the coastline presented medium to high vulnerability. For winter, 230 km coastline would be affected, from which 75% were classified as medium to high vulnerability. Thus, IEVO maps allowed a rapid and clearer interpretation of the vulnerability of the mapped region, facilitating the planning process and the actions in response to an oil spill.