Slope instability of San Miniato hill (Florence, Italy): possible deformation patterns

The hill of San Miniato (Florence, Italy) has been repeatedly identified in the past as the site of a slow moving, intermittent landslide. Possible hypotheses regarding the mechanisms responsible for past movements and for cracks and fissures present today are formulated based on the comparison of historical information and processed monitoring data. Although it is not possible to completely exclude a large inactive landslide that involves the entire northern slope, it seems more probable that the slide, if it does exist, is no longer active and that present-day damage is due to separate shallow movements concentrated in man-made deposits. This hypothesis can only be verified with a temporal extension of the monitoring activities, necessary in any case for planning possible safeguarding measures for the cultural heritage in the area.     

Spatial assessment and redesign of a groundwater quality monitoring network using entropy theory, Gaza Strip, Palestine

Using entropy theory, a methodology was developed for the evaluation and redesign of groundwater quality monitoring wells in the Gaza Strip in Palestine. Essential to the methodology is the development of a Transinformation Model (TM) which yields the amount of information transfer and the dependency between the wells as a function of distance. The TM parameters, such as the minimum transinformation and the range, were employed for evaluating the network which revealed that most of the distances between wells were less than the range. It also indicated that a high percentage of redundant information existed in the network. Therefore, the network was reduced by superimposing a square pattern over the monitored area and selecting one well per square block in a stratified pattern. The methodology was tested using the chloride data collected from 1972–2000 from 417 groundwater quality monitoring wells in the Gaza Strip. The number of the groundwater quality monitoring wells in the Gaza Strip was reduced by 53%, while there was 26% redundant information based on the minimum existing distance between wells. This methodology is meant to help monitor the groundwater quality (salinity) in the Gaza Strip.     

Some Observations on the Use of Data from Historical Documents in Debris-Flow Studies

The knowledge of past events is important for the assessment of debris-flow hazard. Amongst the sources of information, documents from historical archives are particularly important in sites where the debris flows cause damage to urban areas and transportation routes. The paper analyses the availability of historical documents on debris flows in Northeastern Italy and discusses factors that can influence the building of time series from archive data both at regional and single basin scales. An increased number of debris flows was observed in the studied region for the last decades. This could be due both to an increased frequency of the events and to a larger availability of information: the analysis carried out indicates that the latter factor is probably the most influencing. The importance of factors, which affect the collection of data, including the conservation of documents and the presence and fragility of the elements at risk, is stressed in view of a wise use of historical data on debris flows.     

全国资源与生态环境遥感监测数据管理与应用服务系统设计

为推动资源与生态环境遥感监测数据的应用与服务,为国家、相关行业管理决策和社会公众提供有价值的信息,需要在资源与生态环境遥感监测成果数据基础上,开发数据管理与应用服务系统。本文从国家资源与生态环境建设的实际需求出发,结合国土资源部实施的环北京地区资源与生态环境遥感监测成果,探讨资源与生态环境遥感监测数据管理与应用服务的技术解决方案,搭建资源与生态环境遥感监测数据管理与应用服务技术平台,并实现网络环境下对资源与生态环境监测形成的各种类型数据的集成化管理。     

Hyper Redundancy for Accuracy Enhancement in Automated Close Range Photogrammetry

A generic network design in close range photogrammetry is one where optimal multi-ray intersection geometry is obtained with as few camera stations as practicable. Hyper redundancy is a concept whereby, once the generic network is in place, many additional images are recorded, with the beneficial impact upon object point precision being equivalent to the presence of multiple exposures at each camera position within the generic network. The effective number of images per station within a hyper redundant network might well be in the range of 10 to 20 or more. As is apparent when it is considered that a hyper redundant network may comprise hundreds of images, the concept is only applicable in practice to fully automatic vision metrology systems, where it proves to be a very effective means of enhancing measurement accuracy at the cost of minimal additional work in the image recording phase. This paper briefly reviews the network design and accuracy aspects of hyper redundancy and illustrates the technique by way of the photogrammetric measurement of surface deformation of a radio telescope of 26 m diameter. This project required an object point measurement accuracy of σ  = 0·065 mm, or 1/400 000 of the diameter of the reflector.     

对江西农经网如何更好地提供信息服务的探讨

分析了江西农村经济信息网(www.jxagriec.gov.cn)的现状,指出农经网信息服务正面临着挑战,并在此基础上阐述了农经网信息服务的发展思路。     

广西新一代"区-地-县"三级气象信息网络系统

介绍广西新一代“区 -地 -县”三级气象信息网络系统在拓扑结构、业务软件和运行管理等方面的基本情况 ,总结了建设、运行管理过程中成功经验以及存在的问题 ,指出 :充分利用现有通讯网络资源 ,强化业务软件的开发应用 ,提高网络传输监控管理水平 ,是经济欠发达地区扩展气象信息网络业务能力的重要途径     

Modelling evaporation using an artificial neural network algorithm

This paper investigates the prediction of Class A pan evaporation using the artificial neural network (ANN) technique. The ANN back propagation algorithm has been evaluated for its applicability for predicting evaporation from minimum climatic data. Four combinations of input data were considered and the resulting values of evaporation were analysed and compared with those of existing models. The results from this study suggest that the neural computing technique could be employed successfully in modelling the evaporation process from the available climatic data set. However, an analysis of the residuals from the ANN models developed revealed that the models showed significant error in predictions during the validation, implying loss of generalization properties of ANN models unless trained carefully. The study indicated that evaporation values could be reasonably estimated using temperature data only through the ANN technique. This would be of much use in instances where data availability is limited. Copyright © 2002 John Wiley & Sons, Ltd.     

Fuzzy neural network models for liquefaction prediction

Integrated fuzzy neural network models are developed for the assessment of liquefaction potential of a site. The models are trained with large databases of liquefaction case histories. A two-stage training algorithm is used to develop a fuzzy neural network model. In the preliminary training stage, the training case histories are used to determine initial network parameters. In the final training stage, the training case histories are processed one by one to develop membership functions for the network parameters. During the testing phase, input variables are described in linguistic terms such as ‘high’ and ‘low’. The prediction is made in terms of a liquefaction index representing the degree of liquefaction described in fuzzy terms such as ‘highly likely’, ‘likely’, or ‘unlikely’. The results from the model are compared with actual field observations and misclassified cases are identified. The models are found to have good predictive ability and are expected to be very useful for a preliminary evaluation of liquefaction potential of a site for which the input parameters are not well defined.     

ARTIFICIAL NEURAL NETWORK CORRECTION OF ROUGH ERRORS OF OBSERVATIONS*

In the context of tower measured radiation datasets.following the correction principle meeting a diagnostic equation in data quality control and in terms of a technique for model construction on data and ANN (artificial neural network) retrieval for BP correction of radiation measurements with rough errors available,a BP model is presented.Evidence suggests that the developed model works well and is superior to a convenient multivariate linear regression model,indicating its wide applications.