GIS for Science, Volume 2 (Esri Press)
Monday, 11 January 2021

This book, subtitled Applying Mapping and Spatial Analytics, is a collection of current, real-world examples of scientists using geographic information systems (GIS) and spatial data science. Co-edited by Esri Chief Scientist Dawn Wright and Esri Technology Writer and Information Designer Christian Harder and with a foreword by Pulitzer Prize winner Jared Diamond, these case studies are part of a global effort to find ways to sustain a livable environment for all life on this planet.

<ASIN:1589485874>

The contributors represent a cross section of scientists who employ data gathered from satellites, aircraft, ships, drones, and other remote-sensing and on-site technologies. This collected data is brought to life with GIS and the broader realm of spatial data science to study a range of issues including epidemiology in light of the COVID-19 pandemic; sustainable precision agriculture; predicting geological processes below the surface of the earth; using GIS near-realtime disaster response, recovery, resilience and reporting; and the latest innovations in monitoring air quality.

Editors: Dawn Wright and Christian Harder
Publisher: Esri Press
Date: December 2020
Pages: 232
ISBN: 978-1589485877
Print: 1589485874
Audience: General
Level: Intermediate
Category :Data Science  

gisforscience

 

For recommendations of Big Data books see Reading Your Way Into Big Data in our Programmer's Bookshelf section.

 

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Author: Len Bass, Dr. Paul Clements and Rick Kazman
Publisher: Addison-Wesley Professional
Pages: 464
ISBN: 978-0136886099
Print: 0136886094
Kindle: B094CPJ96B
Audience: Software architects
Rating: 4.5
Reviewer: Kay Ewbank

This is the fourth edition of a book widely regarded as a classic since its firs [ ... ]



SQL Query Design Patterns and Best Practices

Author: Steve Hughes et al
Publisher: Packt Publishing
Pages: 270
ISBN: 978-1837633289
Print: 1837633282
Kindle: B0BWRD7HQ7
Audience: Query writers
Rating: 2.5
Reviewer: Ian Stirk

This book aims to improve your SQL queries using design patterns, how does it fare? 


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