基于GIS/GPS的印度精准农业模式研究

S. K. Mudda
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摘要

在农民不断变化的信息需求和多样化生产系统的当今背景下,迫切需要为印度等发展中国家的小农和边缘农民寻找有效的推广支持系统。利用全球定位系统和地理信息系统等空间技术收集和分析实地数据方面的迅速发展,为推广工作人员和客户提供了多样化的信息需求。本文介绍了基于GIS和GPS的资源贫困农民精准农业决策支持系统。精准农业技术用于提高产量,降低生产成本,并尽量减少对环境的负面影响。通过基于GPS和GIS的应用程序,可以评估影响作物产量的参数、异常因素和管理实践的变化。地理信息系统技术的空间可视化能力与关系数据库相结合,为分析和显示推广教育和推广项目对精准农业中小农和边缘农民的影响提供了一种有效的方法。这种方法主要得益于几项技术的出现和融合,包括全球定位系统(GPS)、地理信息系统(GIS)、小型化计算机组件、自动控制、现场和遥感、移动计算、先进信息处理和电信。这个决策支持模型将更好地解决人(农民)、项目(操作领域)和像素(与领域和领域种植的作物相关的数字图像)的PPP融合问题。因此,这些信息的汇集和出现将进一步为生产系统的分类和分组铺平道路,以便更好地推广交付。在像印度这样的大国,农民和财产数量众多,种类繁多,这种分组是不可避免的,也是经济的。在这个前提下,人们尝试开发一种适合印度等发展中国家的精准农业模式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
GIS/GPS based Precision Agriculture Model in India –A Case study
In the present day context of changing information needs of the farmers and diversified production systems there is an urgent need to look for the effective extension support system for the small and marginal farmers in the developing countries like India. The rapid developments in the collection and analysis of field data by using the spatial technologies like GPS&GIS were made available for the extension functionaries and clientele for the diversified information needs. This article describes the GIS and GPS based decision support system in precision agriculture for the resource poor farmers. Precision farming techniques are employed to increase yield, reduce production costs, and minimize negative impacts to the environment. The parameters those can affect the crop yields, anomalous factors and variations in management practices can be evaluated through this GPS and GIS based applications. The spatial visualisation capabilities of GIS technology interfaced with a relational database provide an effective method for analysing and displaying the impacts of Extension education and outreach projects for small and marginal farmers in precision agriculture. This approach mainly benefits from the emergence and convergence of several technologies, including the Global Positioning System (GPS), geographic information system (GIS), miniaturised computer components, automatic control, in-field and remote sensing, mobile computing, advanced information processing, and telecommunications. The PPP convergence of person (farmer), project (the operational field) and pixel (the digital images related to the field and the crop grown in the field) will better be addressed by this decision support model. So the convergence and emergence of such information will further pave the way for categorisation and grouping of the production systems for the better extension delivery. In a big country like India where the farmers and holdings are many in number and diversified categorically such grouping is inevitable and also economical. With this premise an attempt has been made to develop a precision farming model suitable for the developing countries like India.
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