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Spatial Sampling with R
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Spatial Sampling with R

Book Details

Format Hardback or Cased Book
ISBN-10 1032193859
ISBN-13 9781032193854
Publisher Taylor & Francis Ltd
Imprint Chapman & Hall/CRC
Country of Manufacture GB
Country of Publication GB
Publication Date Sep 26th, 2022
Print length 534 Pages
Weight 1,026 grams
Dimensions 16.30 x 24.10 x 3.40 cms
Product Classification: Probability & statisticsGeochemistry
Ksh 22,500.00
Werezi Extended Catalogue 0 in stock

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Scientific research often starts with data collection. However, many researchers pay insufficient attention to this first step in their research. The author, researcher at Wageningen University and Research, often had to conclude that the data collected by fellow researchers were suboptimal, or in some cases even unsuitable for their aim.

Scientific research often starts with data collection. However, many researchers pay insufficient attention to this first step in their research. The author, researcher at Wageningen University and Research, often had to conclude that the data collected by fellow researchers were suboptimal, or in some cases even unsuitable for their aim. One reason is that sampling is frequently overlooked in statistics courses. Another reason is the lack of practical textbooks on sampling. Numerous books have been published on the statistical analysis and modelling of data using R, but to date no book has been published in this series on how these data can best be collected. This book fills this gap. Spatial Sampling with R presents an overview of sampling designs for spatial sample survey and monitoring. It shows how to implement the sampling designs and how to estimate (sub)population- and space-time parameters in R.

Key features

  • Describes classical, basic sampling designs for spatial survey, as well as recently developed, advanced sampling designs and estimators
  • Presents probability sampling designs for estimating parameters for a (sub)population, as well as non-probability sampling designs for mapping
  • Gives comprehensive overview of model-assisted estimators
  • Covers Bayesian approach to sampling design
  • Illustrates sampling designs with surveys of soil organic carbon, above-ground biomass, air temperature, opium poppy
  • Explains integration of wall-to-wall data sets (e.g. remote sensing images) and sample data
  • Data and R code available on github
  • Exercises added making the book suitable as a textbook for students

The target group of this book are researchers and practitioners of sample surveys, as well as students in environmental, ecological, agricultural science or any other science in which knowledge about a population of interest is collected through spatial sampling. This book helps to implement proper sampling designs, tailored to their problems at hand, so that valuable data are collected that can be used to answer the research questions.


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