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Autor(en): 
  • Dick J Brus
  • Spatial Sampling with R 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Vorankündigung
    Veröffentlichung:  ANGEKÜNDIGT (Juli 2026)  
    Genre:  Schulbücher 
     
    Approximated Sampling Distributions / Bayesian sampling methods / CDF / Cluster Random Sampling / Code Chunk / Data Sets / ecological monitoring techniques / Elementary Sampling Units
    ISBN:  9781032193861 
    EAN-Code: 
    9781032193861 
    Verlag:  Taylor and Francis 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 234 mm / B 156 mm / D 28 mm 
    Gewicht:  762 gr 
    Seiten:  534 
    Illustration:  farbige Illustrationen, Raster, farbig, Zeichnungen, farbig, Tabellen, farbig 
    Bewertung: Keine Bewertung vor Veröffentlichung möglich.
    Inhalt:

    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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