APPLICATIONS OF ARTIFICIAL INTELLIGENCE TECHNIQUES TO REMOTE SENSING*

Remote sensing is a geographic analysis tool capable of producing large quantities of data in the spectral, temporal and spatial domains. Techniques for automating the image analysis process would be advanced by the inclusion of artificial intelligence techniques in the design of image processing systems. The remote sensing application which show promise for successful implementation of artificial intelligence techniques are intelligent onboard processing, advanced database interrogation, and the automated analysis of multispectral imagery.     

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.     

Connecting Local to Global: Geographic Information Systems and Ecological Footprints as Tools for Sustainability

Tools that support public engagement with sustainability are essential for local sustainability planning. This research investigates the ability of two geographic information system (GIS)-based tools to promote discussion of sustainability in a suburban context. A local ecological footprint tool and a community environmental atlas (an environmentally themed online mapping system) were created for seven suburban boroughs of Montreal. Variations of both tools have been used to support sustainability efforts, but their use has not been widely evaluated. Working from a public participation GIS (PPGIS) framework that recognizes the powerful influence of data representation, this research uses focus groups to evaluate how well these tools address three criteria that have emerged from the literature on public engagement in sustainability: interdependency across systems, reflexivity about personal and social decision making, and interactions across spatial scales. Whereas the atlas remains advantageous for discussing local spatial specifics, it was found that the ecological footprint helped people see the interconnections among systems, integrate local and global aspects of sustainability, and reflect on the values and assumptions underlying current social and economic structures.     

Human and Environmental Factors Affect Patterns of Crop Diversity in an Ethiopian Highland Agroecosystem

The Ethiopian highlands are a center of diversity for numerous globally important crops. Heterogeneous landscapes, traditional agricultural practices, and inaccessibility have created and maintained diverse subsistence agroecosystems. We surveyed sixty-three farms in twelve communities of the Gamo highlands and found high levels of on-farm diversity of crop species and varieties. The extent and nature of this diversity are related to both ecological factors, namely elevation, and anthropogenic factors such as land-use history, accessibility to markets and extension, and strength and scale of farmer exchange networks. These human landscape features have the potential to both enhance and mediate effects of elevation and other environmental factors on crop diversity. The interaction of environmental and anthropogenic forces on the diversity of crops grown by farmers affects the strategies farmers employ to adapt their farming to changing conditions.     

Rapid generation of Digital Elevation Models from topographic maps

Abstract

In this article we demonstrate that substantial gains in time can be made when using point sampling rather than contour line digitising for generation of Digital Elevation Models (DEMs). A simple sampling scheme, based on regularly distributed points, was used supplemented with points near break-lines in the terrain. An evaluation of surfaces created with three different interpolation methods at three different resolutions shows that the statistical distribution was better when using points as opposed to contours, and that the accuracy was comparable despite the much smaller amount of input data.     

LOCATING EMPLOYMENT GROWTH IN URBAN AREAS TO MINIMIZE TRAVEL TIME

The transportation requirements of an urban area are, in part, a function of its land use pattern. Reducing travel in an urban area by effective land use design appears to be a worthwhile public policy objective. The planning model derived in this article uses as its core the matrix version of the Lowry model developed by Garin. The model allocates basic employment to the zones of an urban area in order to minimize work and service trips. A hypothetical planning problem for Metropolitan Toronto illustrates use of the model.     

主体功能区情景下的土地系统变化模拟

主体功能区要求对国土实施相对严格的空间管制措施,以实现资源生态和社会经济发展的协调。选择黑龙江省哈大齐(哈尔滨-大庆-齐齐哈尔)地区为研究案例,以CLUE-S模型模拟了两种情景下的未来土地系统变化情况,结果表明,在不实施任何空间管制措施的情景下,耕地对草地的蚕食将延续,生态功能持续降低;而在主体功能区建设的情景下,居民地将大幅度扩展,且主要占用盐碱地,同时保持了耕地和生态用地的安全,在一定程度上可缓解土地利用冲突,优化土地利用结构和国土开发格局。     

一种无线数据传输接口及控制装置

本文介绍一种无线数据传接口及控制装置。装置中采用计算机软件实现串—并、并—串变换及频率调制、其硬件成本低廉,工作可靠,可用于速率为50、300、600或1200bps的数传通信。     

Comparative analysis of fuzzy inference systems for water consumption time series prediction

Two types of fuzzy inference systems (FIS) are used for predicting municipal water consumption time series. The FISs used include an adaptive neuro-fuzzy inference system (ANFIS) and a Mamdani fuzzy inference systems (MFIS). The prediction models are constructed based on the combination of the antecedent values of water consumptions. The performance of ANFIS and MFIS models in training and testing phases are compared with the observations and the best fit model is identified according to the selected performance criteria. The results demonstrated that the ANFIS model is superior to MFIS models and can be successfully applied for prediction of water consumption time series.