Spatial Sampling with R

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
• 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.

科學研究通常從數據收集開始。然而，許多研究人員在研究的第一步上付出不足的注意。作者是瓦赫寧根大學和研究機構的研究人員，經常不得不得出結論，同事收集的數據是次優的，或者在某些情況下甚至不適合他們的目的。其中一個原因是在統計課程中經常忽視了抽樣。另一個原因是缺乏關於抽樣的實用教材。已經出版了許多關於使用R進行數據統計分析和建模的書籍，但迄今為止，該系列中還沒有一本關於如何最好地收集這些數據的書籍。這本書填補了這一空白。《使用R進行空間抽樣》概述了空間樣本調查和監測的抽樣設計。它展示了如何實施抽樣設計以及如何在R中估計（次）人口和時空參數。

主要特點：
- 描述了傳統的基本空間調查抽樣設計，以及最近開發的高級抽樣設計和估計器
- 提供了用於估計（次）人口參數的概率抽樣設計，以及用於制圖的非概率抽樣設計
- 全面介紹了模型輔助估計器
- 通過土壤有機碳、地上生物量、空氣溫度、鴉片等調查展示了抽樣設計
- 解釋了全面數據集（例如遙感圖像）和樣本數據的整合
- 在github上提供數據和R代碼
- 添加了練習題，使該書適合作為學生的教科書

本書的目標讀者是抽樣調查的研究人員和從業人員，以及環境、生態、農業科學或任何其他通過空間抽樣收集感興趣人群的知識的科學的學生。本書幫助他們實施適合他們手頭問題的正確抽樣設計，從而收集到有價值的數據，可以用來回答研究問題。

Dick J. Brus worked as a researcher and statistics teacher at the Wageningen University and Research (Netherlands) for 38 years. His main fields of interest are sampling theory and geostatistics. He has gathered rich research experience in developing and applying statistical methods for natural resources inventory and monitoring. In 2015, he was appointed Adjunct Professor at Nanjing Normal University, Nanjing, China. He has published about 100 papers in peer-reviewed, international journals. He is second co-author of the book 'Sampling for Natural Resource Monitoring', published in 2006 by Springer. This book is widely acclaimed in soil, earth, environmental, agricultural and statistical science. Since January 1, 2022 he is retired and lives a joyful life in the countryside, where he grows vegetables in the garden, goes on cycling tours and sings in a choir. Every now and then, during rainy days, he works as a private contractor for the sole proprietorship Spatial Sampling registered with the Chamber of Commerce in the Netherlands.

Dick J. Brus 在荷蘭的瓦赫寧根大學和研究機構擔任研究員和統計學教師長達38年。他的主要研究領域是抽樣理論和地理統計學。他在開發和應用統計方法進行自然資源監測和監測方面積累了豐富的研究經驗。2015年，他被任命為中國南京師範大學的兼職教授。他在同行評審的國際期刊上發表了約100篇論文。他是2006年由Springer出版的《自然資源監測抽樣》一書的第二共同作者。該書在土壤、地球、環境、農業和統計科學領域廣受好評。自2022年1月1日起，他已退休並在鄉村過著愉快的生活，他在花園裡種植蔬菜，進行自行車旅行並參加合唱團。偶爾在下雨天，他會作為私人承包商為荷蘭商會註冊的空間抽樣獨資企業工作。