GIS及其在植物检疫中的应用研究

GIS是一种决策支持系统,吸取了计算机地图制图、计算机图形学、航空摄影测量与遥感、数字图象处理、数据库管理系统等技术的成果,具有信息系统的各种特点,已取代地图成为地理学的第三代语言。GIS由于其具有强大的空间信息管理和空间分析功能,被广泛地应用于几乎一切与空间信息相关的领域,如城市规划、军事、测绘、农业和商业等。近年来,随着微型计算机系统的普及和图形     

湖北省植物保护信息化发展构想

湖北植保信息系统的建设,对提高全省植保信息覆盖率,加快植保信息和病虫数据传递,提高植保工作的影响力和植保系统的社会地位起到了重要作用.进一步建设湖北植保信息系统,发展gis系统、自动化处理、可视化发布、信息咨询服务、防控指挥、网络管理是适应绿色植保公共植保工作有效手段.     

农药行政审批服务系统的简介与应用

1前言＂金农工程＂属于国家＂十二金＂工程之一,是国家农业电子政务工程,也是农业部信息化工作的一项重要内容。＂金农工程＂一期建设的应用系统主要包括：农业监测预警系统、农产品和农业生产资料市场监管信息系统、农村市场与科技信息服务系统三大应用系统与国家综合门户系统。其中农产品和农业生产资料市场监管信息系统,由农药监管子系统等九个应用子系统及一个行政审批平台组成。     

乌梁素海湿地环境与资源地理信息系统的研究

本系统建立乌梁素海湿地基础地形库、生态库、资源库、工程档案库、遥感影像库等基础数据库及信息发布系统 ,使 GPS、GIS、RS紧密结合 ,同时实现了专家决策支持系统与地理信息系统之间的一体化集成。本系统可以为乌梁素海湿地生态治理与资源开发提供全方位的数据信息及其管理 ,对生态工程规划与实施方案进行优化设计 ,并提供实时监控服务。     

中国西北荒漠植物区系信息系统

在对中国西北荒漠植物区系的 ６８ 个科、３６１ 个属、１０７９ 个种植物的分布区类型、性状、生境、产地等进行系统调查及研究的基础上,建立中国西北荒漠植物区系信息系统。本文介绍了该信息系统的结构及其功能,对该系统的使用范围及使用方法作了详细的说明     

基于GIS的松嫩平原重要湿地信息系统研究

本文系统论述了松嫩平原重要湿地信息系统的重要性,系统建设的目标、原则,系统结构设计与数据库建库,以及湿地信息系统建成后的功能和意义。松嫩平原重要湿地保护区生态环境基础数据平台的建立,实现了重要湿地生态环境信息查询、更新和信息共享,为深入开展保护区重要水禽生境专题研究提供了数据基础和技术支撑,提高了濒危物种和湿地环境的监测能力和保护效率。     

基于COMGIS和Matlab的泾惠渠灌区灌溉决策支持系统

以泾惠渠灌区为研究对象,采用动态规划、神经网络、遗传算法等多种优化算法基于Matlab完成了系统优化模型,并采用GIS的三维可视化和空间分析技术基于COMGIS完成了灌溉仿真模型,同时利用COM技术,建立了系统与MatlabArcGIS无缝集成的泾惠渠灌区灌溉决策支持系统。系统能够有效地协助决策人员解决泾惠渠灌区灌溉水资源优化调度的难题,显著提高了灌溉水资源的管理水平。通过将2008年实际数据输入运行结果分析来看,系统能够胜任辅助灌溉决策之重任。     

中国西北荒漠植物区信息系统

在对中国西北荒植物区系的68个科、361属、1079个种植物的分布区类型、性状、生境、产地等进行系统调查及研究的基础上，建立中国西北荒漠植物区系信息系统。本文介绍了该信息系统的结构及其功能，对该系统的使用范围及使用方法作了详细的说明     

河南省农作物有害生物监控信息系统建设现状及改进对策

介绍了河南省农作物有害生物监控信息系统研发情况、主要功能及特点;分析了此监控系统建设及应用中存在的突出问题,提出了下步升级、改进对策。     

面向果园的苹果、梨病虫害防治决策支持系统

为了改变果农在果园病虫害防治中存在的盲目使用化学药剂,以致于造成成本高,防效低和污染重的现象,特研制了苹果、梨病虫害防治决策支持系统。本系统包含了果园管理数据库,病虫害生物学数据库,１２种常发病虫害的中短期预测模型库,专家经验库以及药剂库。本系统可根据未来１周的天气预报,针对果园的具体特点作出病虫害的预测和防治建议,这些建议能够以决策表和咨询电话的方式传送给果农。该系统运行１年多来受到了广大用户的     

基于地理信息系统的全国主要粮食作物病虫害实时监测预警系统的研制

为提高病虫害防治的准确性和科学性，依据植保知识、专家经验，采用人工智能、自行开发的具地理信息系统基本功能及决策支持系统（DSS）的相关技术，研制了基于Internet网络传输的全国主要粮食作物病虫害实时监测预警系统。本系统能够对小麦、玉米、水稻、马铃薯、高粱和谷子6种主要粮食作物的60余种病虫害进行实时监测、预警、诊断、提供植保知识，能够对年度间同期病情、虫情做出图形比较，可将抽象的预警数据转化成清晰简明的点图式电子地图，直观明了地显示病虫害发生点数及地域分布，可根据品种的抗病虫性、病虫害发生基数和未来天气预报等信息对小麦白粉病、赤霉病、纹枯病、稻瘟病、稻曲病、马铃薯晚疫病、麦蚜、小麦吸浆虫和玉米螟9种重要病虫害做出短期防治决策，系统的运行有助于提高人们对主要粮食作物病虫害管理的科学水平。     

Model based decision support system for land use changes and socio-economic assessments

Hydrological models are often linked with other models in cognate sciences to understand the interactions among climate, earth, water, ecosystem, and human society. This paper presents the development and implementation of a decision support system(DSS) that links the outputs of hydrological models with real-time decision making on social-economic assessments and land use management. Discharge and glacier geometry changes were simulated with hydrological model, water availability in semiarid environments. Irrigation and ecological water were simulated by a new commercial software MIKE HYDRO. Groundwater was simulated by MODFLOW. All the outputs of theses hydrological models were taken as inputs into the DSS in three types of links: regression equations, stationary data inputs, or dynamic data inputs as the models running parallel in the simulation periods. The DSS integrates the hydrological data, geographic data, social and economic statistical data, and establishes the relationships with equations, conditional statements and fuzzy logics. The programming is realized in C++. The DSS has four remarkable features:(1) editable land use maps to assist decision-making;(2) conjunctive use of surface and groundwater resources;(3) interactions among water, earth, ecosystem, and humans; and(4) links with hydrological models. The overall goal of the DSS is to combine the outputs of scientific models, knowledge of experts, and perspectives of stakeholders, into a computer-based system, which allows sustainability impact assessment within regional planning; and to understand ecosystem services and integrate them into land and water management.     

基于Web的融雪洪水预警模型库系统研究与实现

在总结前人研究的基础上,建立并实现了基于Web的融雪洪水预警模型库系统。该模型库系统将成熟的关系型数据库系统技术与模型库理论集成在一起,提供对模型及其数据的各种操作。并且充分利用面向对象技术,从根本上解决了模型的表示、管理、组合运行、复用以及模型与参数的相互独立等关键性问题,与传统模型库系统最大的不同是实现了完全基于Web方式的管理和运行。     

A quantitative interpretation of the entry section of the EPPO decision‐support scheme for pest risk analysis

The development of methods to combine components of risk and their associated uncertainty in Pest Risk Analysis (PRA) has received attention in a number of recent European projects. Many of the risk components distinguished in the EPPO Decision‐support scheme (DSS) for PRA are usually difficult to quantify, but when there is detailed knowledge of the pest and pathway, quantification may be possible to a limited extent for the pest entry section of the scheme. The European Food Safety Authority has recently commissioned a project to investigate approaches to quantitative pathway analysis for pests of commodities entering and moving within the EU (QPA‐Food); a sister project concerns non‐food commodities. This paper illustrates the potential for a quantitative pathway model based closely on the Entry Section of the EPPO DSS for PRA, where existing quantitative definitions of rating categories have been used as a basis to estimate the proportion and number of infested lots on a pathway. Such quantification may provide additional insights without requiring substantial changes to the information elicited via the DSS.     

Consistency in pest risk analysis – how can it be achieved and what are the benefits?*

This paper describes the efforts in the PRATIQUE EU project to increase consistency that were integrated into the revised EPPO Decision‐support scheme (DSS) for Pest Risk Analysis (PRA). The establishment section is used here to illustrate the changes and improvements of the DSS, as it has undergone the most comprehensive changes with reformulation and restructuring of many questions and detailed rating guidance. When revising the establishment section of the EPPO DSS for PRA, there were three principal objectives that influenced the revision: (i) to focus the assessment on the most relevant factors influencing establishment; (ii) to identify the area where establishment is possible before assessing the suitability of that area, and (iii) to enhance the consistency of the establishment section by providing rating guidance with sub‐questions and examples. To simplify the process, some questions were rephrased as closed questions (answer is either yes or no). Clearer notes were provided to explain what information is needed to answer the questions. Furthermore, consistency has been enhanced by developing tools to help assessors when deciding on an appropriate overall risk rating and uncertainty score by providing a visual summary of the risk ratings and uncertainty scores (‘Visualizer’) and a method for integrating all the responses to the questions to provide a summary score for each major section and an overall assessment of risk (‘Rule based matrix model’).     

A web‐based decision support system to enhance IPM programs in Washington tree fruit

BACKGROUND: Integrated pest management (IPM) decision‐making has become more information intensive in Washington State tree crops in response to changes in pesticide availability, the development of new control tactics (such as mating disruption) and the development of new information on pest and natural enemy biology. The time‐sensitive nature of the information means that growers must have constant access to a single source of verified information to guide management decisions. RESULTS: The authors developed a decision support system for Washington tree fruit growers that integrates environmental data [140 Washington State University (WSU) stations plus weather forecasts from NOAA], model predictions (ten insects, four diseases and a horticultural model), management recommendations triggered by model status and a pesticide database that provides information on non‐target impacts on other pests and natural enemies. A user survey in 2008 found that the user base was providing recommendations for most of the orchards and acreage in the state, and that users estimated the value at $ 16 million per year. CONCLUSIONS: The design of the system facilitates education on a range of time‐sensitive topics and will make it possible easily to incorporate other models, new management recommendations or information from new sensors as they are developed. Copyright © 2010 Society of Chemical Industry     

云南省稻瘟病,小麦锈病预测专家系统

基于稻瘟病、小麦锈病预测领域专家知识,以及借助模式识别势函数法实现的自学习、自提取的知识,采用正向和反向精确推理控制策略,首次建立云南省水稻穗瘟病、小麦条锈病预测专家系统,1994～1995年预测结果与实际情况基本一致。系统创造性地采用全屏幕编辑树图的知识输入法和森林表示技术对知识库进行管理,便于知识库的扩充和维护。推理结果、推理路径及知识查询以彩色图形方式显示,对于学习领域专家的实践经验具有独特优点。     

A decision‐support scheme that generates contingency plans and prioritizes action during pest outbreaks*

The decision‐support scheme (DSS) for action at outbreaks developed under PRATIQUE (Enhancements of Pest Risk Analysis Techniques) brings together a set of guidance and tools, using the CAPRA application. The DSS is initiated by the collation of key information on the current outbreak situation, and then compares candidate measures in order to derive a strategy for action and/or contingency. It is hoped that this deliverable will assist national plant protection organizations (NPPOs) to address and justify eradication campaigns effectively. The rationale behind the DSS and its key features are presented and discussed.     

Development of an interactive decision‐support system on a Web site for control of Mycosphaerella graminicola in winter wheat*

A decision‐support system (DSS) has been developed in Belgium to help farmers and advisers to manage Mycosphaerella graminicola in winter wheat during stem elongation. The system calculates in real time the interactions between winter wheat and M. graminicola development to simulate disease progression in the canopy in order to guide field observations on the different leaf layers and determine the risks for the crop. It has been structured to run with individual field input and local hourly meteorological data. An interactive Internet version of the system has been developed to facilitate the delivery of information. It allows users to base their decisions on advice tailored to conditions in their own fields, as well as to recent and validated hourly local meteorological data that is regularly updated on the server computer.