Tags
Language
Tags
June 2025
Su Mo Tu We Th Fr Sa
1 2 3 4 5 6 7
8 9 10 11 12 13 14
15 16 17 18 19 20 21
22 23 24 25 26 27 28
29 30 1 2 3 4 5
    Attention❗ To save your time, in order to download anything on this site, you must be registered 👉 HERE. If you do not have a registration yet, it is better to do it right away. ✌

    ( • )( • ) ( ͡⚆ ͜ʖ ͡⚆ ) (‿ˠ‿)
    SpicyMags.xyz

    Learning R for Geospatial Analysis

    Posted By: nebulae
    Learning R for Geospatial Analysis

    Michael Dorman, "Learning R for Geospatial Analysis"
    English | ISBN: 1783984368 | 2015 | 364 pages | PDF + EPUB | 9 + 11 MB

    Leverage the power of R to elegantly manage crucial geospatial analysis tasks
    About This Book
    Write powerful R scripts to manipulate your spatial data
    Gain insight from spatial patterns utilizing R's advanced computation and visualization capabilities
    Work within a single spatial analysis environment from start to finish
    Who This Book Is For

    This book is intended for anyone who wants to learn how to efficiently analyze geospatial data with R, including GIS analysts, researchers, educators, and students who work with spatial data and who are interested in expanding their capabilities through programming. The book assumes familiarity with the basic geographic information concepts (such as spatial coordinates), but no prior experience with R and/or programming is required. By focusing on R exclusively, you will not need to depend on any external software—a working installation of R is all that is necessary to begin.
    In Detail

    R is a simple, effective, and comprehensive programming language and environment that is gaining ever-increasing popularity among data analysts.

    This book provides you with the necessary skills to successfully carry out complete geospatial data analyses, from data import to presentation of results.

    Learning R for Geospatial Analysis is composed of step-by-step tutorials, starting with the language basics before proceeding to cover the main GIS operations and data types. Visualization of spatial data is vital either during the various analysis steps and/or as the final product, and this book shows you how to get the most out of R's visualization capabilities. The book culminates with examples of cutting-edge applications utilizing R's strengths as a statistical and graphical tool.
    Download from nitroflare