The research and its outcomes presented here focus on spatial sampling of agricultural resources. The authors introduce sampling designs and methods for producing accurate estimates of crop production for harvests across different regions and countries. With the help of real and simulated examples performed with the open-source software R, readers will learn about the different phases of spatial data collection. The agricultural data analyzed in this book help policymakers and market stakeholders to monitor the production of agricultural goods and its effects on environment and food safety.
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"This monograph presents a contemporary study of sample surveys by geographically distributed data in the agricultural sector. ... Each chapter contains many dozen references up to the most recent sources. The monograph can be very helpful for lecturers, graduate students, and researchers using survey methods in general, and particularly in spatial agricultural studies." (Stan Lipovetsky, Technometrics, Vol. 59 (1), February, 2017)
"This book is a meticulously organized treatise of applying spatial data methods to sample surveys (primarily in agriculture), with the computational engine powered by the R software. ... It is mainly an intermediate-level reference book for graduate students and (agricultural) researchers to get introduced to the nuances of spatial statistics in survey sampling, and quickly move to hands-on computing. ... If you are enamoured withthe versatility of R, I highly recommend buying it." (Dipankar Bandyopadhyay, Journal of Statistical Software, Vol. 6, February, 2016)
"This book is a meticulously organized treatise of applying spatial data methods to sample surveys (primarily in agriculture), with the computational engine powered by the R software. ... It is mainly an intermediate-level reference book for graduate students and (agricultural) researchers to get introduced to the nuances of spatial statistics in survey sampling, and quickly move to hands-on computing. ... If you are enamoured withthe versatility of R, I highly recommend buying it." (Dipankar Bandyopadhyay, Journal of Statistical Software, Vol. 6, February, 2016)