Developing a Remote Sensing/GIS Information System

新汉普郡大学复杂系统研究中心将获得必要的计算机设备，以创建一个统一的遥感/地理参考计算机工作站，用于区域到全球范围的生态系统建模。该工作站将加强该大学地球、海洋和空间研究所的现有设施。全球生态系统研究和景观生态学的新研究举措需要具有更高空间分辨率的数学模型和具有地理参考特征的数据。遥感系统和地理信息系统为获得必要的数据提供了可能。然而，这些组件只是一个潜在的集成系统中不相关的离散部分。该项目将把这些部分结合在一起，形成一个高效的遥感地理参考建模系统。计算机工作站将具有以下能力：a)栅格和栅格地理信息系统，b)矢量地理信息系统，c)遥感和图像处理，d)点数据管理，e)阵列处理，f)大型数据库管理(例如。窗口)g)图形，h)数据捕获和分析，以及i)数学建模。该机构的支持和设施都很好，将利用这些设施的主要科学家群体也是如此。该设施能够加强的研究将在基础层面上具有根本性的重要性。此外，气候变化、生物多样性和酸雨等全球考虑因素将通过新的能力得到解决。生态系统研究项目强烈建议设立一个奖项。

The Complex Systems Research Center of the University of New Hampshire will acquire the computer equipment necessary to create a unified remote sensing/georeferenced computer workstation for regional to global scale ecosystem modeling. The workstation will enhance existing facilities in the Institute for the Study of Earth, Oceans and Space at the university. New research initiatives in global ecosystem studies and landscape ecology demand mathematical models with improved spatial resolution and data with georeferenced characteristics. Remote sensing systems and Geographic Information Systems offer the possibility for obtaining the necessary data. Yet, these components remain only discrete unrelated pieces of a potentially integrated system. This project will bring these pieces together into a highly effective remote sensing georeferenced modeling system. The computer workstation will have capabilities for: a) grid and raster GIS, b) vector GIS, c) remote sensing and image processing, d) point data management, e) array process, f) large database management (eg. windowing) g) graphics, h) data capture and analysis, and i) mathematical modeling. Support and facilities at the institution are excellent as is the primary group of scientists who will make use of the facilities. The research that the facility is capable of enhancing will be of fundamental importance at a basic level. Additionally, global considerations such as climate change, biological diversity and acid precipitation will be addressable by the newcapabilities. An award is strongly recommended by the Ecosystem Studies Program.