Land-use classification using ASTER data and self-organized neutral networks

Operationally AVHRR and TM/TM+ data were used and a supervised maximum likelihood classification (MLH) was applied to depict land use changes in Beijing, providing basic maps for planning and development. With rapid growth of the city these are helpful to deal with higher resolution data, whereas new classification algorithms produce land use maps more accurate. In the paper, new sensor ASTER data and the Kohonen self-organized neural network feature map (KSOM) were tested.The TSOM classified 7% more accurately than the maximum likelihood algorithm in general, and 50% more accurately for the classes ‘residential area’ and ‘roads’. The results suggest that ASTER data and the Kohonen self-organized neural network classification can be used as an alternative data and method in a land use update operational system.     

数字地震仪的发展历史及展望

地震仪经历了光点，模拟和数字的变化，数字地震仪本身由16位发展到24位，其附属设备（电缆，检波器）也是到了不同程度的发展。近年来，I／O等公司利用MEMS技术研制了新型地震检波器，这一新的发展对于地震采集尤其是多分量采集带来重要影响。     

The global rainforest mapping project JERS-1:a paradigm of international collaboration for monitoring land cover change

The Global Rainforest Mapping (GRFM) project was initiated in 1995 and, through a dedicated data acquisition policy by the National Space Development Agency of Japan (NASDA), data acquisitions could be completed within a 1.5-year period, resulting in a spatially and temporally homogeneous coverage to contain the entire Amazon Basin from the Atlantic to the Pacific; Central America up to the Yucatan Peninsular in Mexico; equatorial Africa from Madagascar and Kenya in the east to Sierra Leone in the west; and Southeast Asia, including Papua New Guinea. To some extent, GRFM project is an international endeavor led by NASDA, with the goal of producing spatially and temporally contiguous Synthetic Aperture Radar (SAR) data sets over the tropical belt on the Earth by use of the JERS-1 L-band SAR, through the generation of semi-continental, 100m resolution, image mosaics. The GRFM project relies on extensive collaboration with the National Aeronautics and Space Administration (NASA), the Joint Research Center of the European Commission (JRC) and the Japanese Ministry of International Trade and Industry (MITI) for data acquisition, processing, validation and product generation. A science program is underway in parallel with product generation. This involves the agencies mentioned above, as well as a large number of international organizations, universities and individuals to perform field activities and data analysis at different levels.     

GIS专题数据综合的研究

随着GIS技术在各种应用领域的推广使用，各领域的专业数据与G1S的空间数据相结合，形成描述特定地理现象的各种专题数据。与GIS空间数据一样，专题数据的应用也由微观的、较为详细地描述小区域地理现象特征，转向宏观的、较为概略地描述较大范围地理现象特征，这是专题数据综合的主要任务。该文在讨论GIS专题数据类型及特征的基础上，着重分析了专题数据综合的基本类型，并提出了专题数据综合的概念模型，为GIS专题数据自动综合的实施提供理论依据和实施方案。     

区域土壤环境地球化学研究——异常成因判别·环境质量·污染程度评价的思路与方法

从概念内涵和应用目标出发,认为土壤环境地球化学质量评价应该分为质量现状和污染程度两个方面.在此基础上探讨了区域地球化学资料在土壤环境现状质量评价、异常成因识别、污染元素累积速率和土壤污染程度评价研究的基本思路和方法.     

新疆乌鲁木齐地区多年水氡观测资料的统计与分析

通过对乌鲁木齐地区1980—7．001年的水氡观测资料进行全时域扫描分析，以乌鲁木齐为中心300km范围内Ms≥5．0的地震事件为研究对象，挑选出观测资料中异常时段，用地震预报效能评价评分的方法对水氡观测资料预报地震的能力进行评价。     

陕西省地下水水质监测发展探析

本文针对陕西省地下水水质监测控制范围局限于农灌区，监测项目单一的现状，通过分析研究，提出水质监测的发展思路，剖析实现新思路的相关条件。     

无拓扑矢量数据快速压缩算法的研究与实现

首先论述传统矢量数据压缩算法：道格拉斯—普克法，分析将其应用于多边形边界数据压缩所造成的图形失真现象，在此基础上提出一种针对无拓扑矢量数据的快速压缩算法，并在MapInfo环境中实现该算法。     

地下管线源数据处理方法的研究

为了保障顺利建设上海市地下管线数据库．需要对现存的地下管线的源数据进行一些技术处理，以满足数据入库的要求。本文主要个绍：笔者在从事地下管线源数据处理工作中，碰到的现存的上海市地下管线源数据对于建设上海市地下管线数据库所存在的一些问题：以及笔者利用Autodesk公司的AutoCAD二次开发工具开发的应用程序来处理这些问题的方法。