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Titlebook: Geostatistical Applications for Precision Agriculture; M.A. Oliver Book 2010 Springer Science+Business Media B.V. 2010 Precision Agricultu

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发表于 2025-3-21 17:13:03 | 显示全部楼层 |阅读模式
书目名称Geostatistical Applications for Precision Agriculture
编辑M.A. Oliver
视频video
概述A single-volume source for a range of methods, with practical advice on their application.Includes numerous case studies with examples.Presents new subject areas on spatio-temporal geostatistics, desi
图书封面Titlebook: Geostatistical Applications for Precision Agriculture;  M.A. Oliver Book 2010 Springer Science+Business Media B.V. 2010 Precision Agricultu
描述The aim of this book is to bring together a series of contributions from experts in the field to cover the major aspects of the application of geostatistics in precision agriculture.The focus will not be on theory, although there is a need for some theory to set the methods in their appropriate context.The subject areas identified and the authors selected have applied the methods in a precision agriculture framework.The papers will reflect the wide range of methods available and how they can be applied practically in the context of precision agriculture. This book is likely to have more impact as it becomes increasingly possible to obtain data cheaply and more farmers use onboard digital maps of soil and crops to manage their land.It might also stimulate more software development for geostatistics in PA.
出版日期Book 2010
关键词Precision Agriculture; Site-specific Management; Variogram; geostatistics; kriging; paper; simulation
版次1
doihttps://doi.org/10.1007/978-90-481-9133-8
isbn_softcover978-94-017-8370-5
isbn_ebook978-90-481-9133-8
copyrightSpringer Science+Business Media B.V. 2010
The information of publication is updating

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发表于 2025-3-22 00:07:22 | 显示全部楼层
Sampling in Precision Agriculture, appropriate sampling scheme or interval for grid sampling. When no prior information is available on the scale of variation, and the variable of interest is unlikely to be strongly correlated to available ancillary data, a nested survey and analysis provides a first approximation to the variogram a
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Sampling in Precision Agriculture, Optimal Designs from Uncertain Models,thin-field variation of soil properties. To ensure that precision agriculture is cost-effective, soil sampling must be as efficient as possible. This chapter demonstrates the potential to optimize the design of soil sampling schemes if the variation of the target property is represented by a linear
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Weeds, Worms and Geostatistics,vent competition (from weeds) and predation (by nematodes) provided they know where the pests are early in the lives of their crops or before sowing or planting them. Standard geostatistical methods have been used successfully to analyse counts of both weed seedlings and nematodes in the soil and to
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The Analysis of Spatial Experiments,e of experimentation is to test this hypothesis. Geostatistics can play an important role in analysing experiments for site-specific crop management: put simply, spatial autocorrelation must be accounted for if one is to draw valid inferences. We provide here some background to the basic concepts of
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