GIS支持下青海湖地区草地蝗虫发生的地形分析

草地蝗虫发生的地形分析是建立草地蝗虫发生预报模型的基础，以青海湖地区为实验区，在Arc/Info和ArcView地理信息系统的支持下，进行草地蝗虫发生与各地形变量（包括海拔高度、坡度与坡向）的叠置分析，提取草地蝗虫发生的地形信息数据库，然后，分别采用T－检验（对连续变量－海拔高度和坡度）和卡方（Chisquare)检验（对类变量－坡向类型）进行各地形变量对草地蝗虫发生的差异显著性检验，结果表明，海拔高度和坡度对草地蝗虫发生的影响极为显著（显著性水平p=0.000)，而坡向地草地蝗虫发生的影响不是特别明显（显著性水平p=0.039)。     

21世纪黄河系统工程方略

该文指出 :王化云的治黄思想 ,“上拦下排、两岸分滞、蓄水拦沙、宽河固堤、除害兴利、综合利用” ,实际上是治理黄河的系统工程 ,2 1世纪应该继承和发展黄河系统工程的方略。黄河地处中国腹地 ,是中华民族的摇篮 ,当今高新科技的发展 ,足以从更大的范围 ,以全国的水资源、土资源为核心来考虑黄河的建设。统一计算水资源中的大气水、地表水、地下水、壤中水、生态水、环境水、生产水、生活水 ;统一计算土资源中的土壤资源、沙资源、沙石资源 ,真正按照地理系统工程来建设黄河。     

断裂构造的遥感研究方法综述

断裂构造是一种基本的构造型式。断裂构造遥感研究是高新探测技术与地球科学的有机结合 ,是断裂构造常规研究方法的有益补充和向纵深拓展的必然趋势。该文从总体思路、具体内容、操作方法等各个不同角度系统地论述了断裂构造遥感研究的现状和发展趋势 ,并在断裂构造信息提取、光谱特征分析、空间结构分析 (包括分形分析 )等方面提出了一些观点。     

旅游信息系统建设模式探讨——以佛山市为例

作为当前旅游信息系统开发的两种主要基础平台，地理信息系统和多媒体制作系统都存在一定的缺陷。多媒体制作系统缺乏旅游地图的有效管理，空间查询，分析和统计功能，旅游地理信息系统则缺乏旅游信息的多媒体表达能力。从实用性和普及性出发，集合二者优点开发模式具有更大的推广应用价值。因此，论文提出在同一界面下基于GIS和多媒体集成的旅游信息系统开发模式；（1）在GIS中增加多媒体信息表达能力，以关系数据库为核心，把多媒体文件名信息存储在地理信息系统属性库，依靠多媒休段实现多媒体数据与地理信息系统图形和属性的关联，实现查询的基本概念；（2）在多媒体系统中开发部分GIS空间查询功能。以此思路，佛山科技学院GIS技术实验室利用VB进行GIS和多媒体二次开发，成功地完成了佛山旅游信息系统的设计和开发。     

基于GIS的滑坡CF多元回归模型及其应用

目前基于GIS滑坡变形失稳危险性评价方法均有各自的局限性。本文在基于数据的数学统计模型的基础上提出CF多元回归模型。通过将滑坡确定性稳定系数与回归模型的融合，在一定程度以解决了滑坡评价过程中影响因子的选择和量化的问题，有利于建立准确的滑坡分析模型。最后，将模型应用于云南小江流域，进行了该区的滑坡空间分布及稳定性分析。     

Public environmental information: understanding requirements and patterns of likely public use

Public access to environmental information received much attention in the last decade. Recent developments promote access to this information through public telecommunication networks. This paper describes a Web-based survey that explored the requirements and needs of likely users of public environmental information systems for London: educated middle-class members of the public, with high interest in environmental issues and computer literacy. The survey demonstrated current information consumption patterns and the reasons to gather and use such information.     

On the spatial relationship between landslides and causative factors on Lantau Island, Hong Kong

This paper presents a statistical approach to study the spatial relationship between landslides and their causative factors at the regional level. The approach is based on digital databases, and incorporates such methods as statistics, spatial pattern analysis, and interactive mapping. Firstly, the authors propose an object-oriented conceptual model for describing a landslide event, and a combined database of landslides and environmental factors is constructed by integrating the various databases within such a conceptual framework. The statistical histogram, spatial overlay, and dynamic mapping methods are linked together to interactively evaluate the spatial pattern of the relationship between landslides and their causative factors. A case study of an extreme event in 1993 on Lantau Island indicates that rainfall intensity and the migration of the center of the rainstorm greatly influence the occurrence of landslides on Lantau Island. A regional difference in the relationship between landslides and topography is identified. Most of the landslides in the middle and western parts of the island occurred on slopes with slope angles of 25–35°, while in the eastern part, the corresponding range is 30–35°. Overlaying landslide data with land cover reveals that a large number of landslides occurred in the bareland and shrub-covered area, and in the transition zones between different vegetation types. The proposed approach can be used not only to analyze the general characteristics of such a relationship, but also to depict its spatial distribution and variation, thereby providing a sound basis for regional landslide prediction.     

Use of Noise to Augment Training Data: A Neural Network Method of Mineral–Potential Mapping in Regions of Limited Known Deposit Examples

One of the main factors that affects the performance of MLP neural networks trained using the backpropagation algorithm in mineral-potential mapping isthe paucity of deposit relative to barren training patterns. To overcome this problem, random noise is added to the original training patterns in order to create additional synthetic deposit training data. Experiments on the effect of the number of deposits available for training in the Kalgoorlie Terrane orogenic gold province show that both the classification performance of a trained network and the quality of the resultant prospectivity map increasesignificantly with increased numbers of deposit patterns. Experiments are conducted to determine the optimum amount of noise using both uniform and normally distributed random noise. Through the addition of noise to the original deposit training data, the number of deposit training patterns is increased from approximately 50 to 1000. The percentage of correct classifications significantly improves for the independent test set as well as for deposit patterns in the test set. For example, using ±40% uniform random noise, the test-set classification performance increases from 67.9% and 68.0% to 72.8% and 77.1% (for test-set overall and test-set deposit patterns, respectively). Indices for the quality of the resultant prospectivity map, (i.e. D/A, D × (D/A), where D is the percentage of deposits and A is the percentage of the total area for the highest prospectivity map-class, and area under an ROC curve) also increase from 8.2, 105, 0.79 to 17.9, 226, 0.87, respectively. Increasing the size of the training-stop data set results in a further increase in classification performance to 73.5%, 77.4%, 14.7, 296, 0.87 for test-set overall and test-set deposit patterns, D/A, D × (D/A), and area under the ROC curve, respectively.     

Use of Fuzzy Membership Input Layers to Combine Subjective Geological Knowledge and Empirical Data in a Neural Network Method for Mineral-Potential Mapping

Use of GIS layers, in which the cell values represent fuzzy membership variables, is an effective method of combining subjective geological knowledge with empirical data in a neural network approach to mineral-prospectivity mapping. In this study, multilayer perceptron (MLP), neural networks are used to combine up to 17 regional exploration variables to predict the potential for orogenic gold deposits in the form of prospectivity maps in the Archean Kalgoorlie Terrane of Western Australia. Two types of fuzzy membership layers are used. In the first type of layer, the statistical relationships between known gold deposits and variables in the GIS thematic layer are used to determine fuzzy membership values. For example, GIS layers depicting solid geology and rock-type combinations of categorical data at the nearest lithological boundary for each cell are converted to fuzzy membership layers representing favorable lithologies and favorable lithological boundaries, respectively. This type of fuzzy-membership input is a useful alternative to the 1-of-N coding used for categorical inputs, particularly if there are a large number of classes. Rheological contrast at lithological boundaries is modeled using a second type of fuzzy membership layer, in which the assignment of fuzzy membership value, although based on geological field data, is subjective. The methods used here could be applied to a large range of subjective data (e.g., favorability of tectonic environment, host stratigraphy, or reactivation along major faults) currently used in regional exploration programs, but which normally would not be included as inputs in an empirical neural network approach.     

基于遥感数据的常熟市耕地资源数量动态变化分析

采用RS和GIS技术，对常熟市1984—2001年间土地利用进行调查，获得了1984、1992、1999、2001年四个时期的土地利用状况及其变化资料。通过多时期对比分析发现：1984—1992年，居民点工矿占用耕地、耕地变成水域和耕地变成交通用地，分别占耕地转出总面积的56．7％、36．6％和5．4％。1992—1999年上述各项则分别占耕地转出总面积的47．3％、45．7％和7．0％。1999——2001年分别占耕地转出总面积的2．4％、95．6％和1．3％。1999年以后农村农业结构调整已经成为耕地面积减少的主要原因，应通过制定区域农业中长期发展规划和法规进行宏观调控。