Spatial Data Analysis In Ecology And Agriculture Using R

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Spatial Data Analysis In Ecology And Agriculture Using R

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Author : Richard E. Plant
language : en
Publisher: CRC Press
Release Date : 2012-03-07

Spatial Data Analysis In Ecology And Agriculture Using R written by Richard E. Plant and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-03-07 with Mathematics categories.

Assuming no prior knowledge of R, Spatial Data Analysis in Ecology and Agriculture Using R provides practical instruction on the use of the R programming language to analyze spatial data arising from research in ecology and agriculture. Written in terms of four data sets easily accessible online, this book guides the reader through the analysis of each data set, including setting research objectives, designing the sampling plan, data quality control, exploratory and confirmatory data analysis, and drawing scientific conclusions. Based on the author’s spatial data analysis course at the University of California, Davis, the book is intended for classroom use or self-study by graduate students and researchers in ecology, geography, and agricultural science with an interest in the analysis of spatial data.

Spatial Data Analysis In Ecology And Agriculture Using R

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Author : Richard E. Plant
language : en
Publisher: CRC Press
Release Date : 2018-12-07

Spatial Data Analysis In Ecology And Agriculture Using R written by Richard E. Plant and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-07 with Science categories.

Key features: Unique in its combination of serving as an introduction to spatial statistics and to modeling agricultural and ecological data using R Provides exercises in each chapter to facilitate the book's use as a course textbook or for self-study Adds new material on generalized additive models, point pattern analysis, and new methods of Bayesian analysis of spatial data. Includes a completely revised chapter on the analysis of spatiotemporal data featuring recently introduced software and methods Updates its coverage of R software including newly introduced packages Spatial Data Analysis in Ecology and Agriculture Using R, 2nd Edition provides practical instruction on the use of the R programming language to analyze spatial data arising from research in ecology, agriculture, and environmental science. Readers have praised the book's practical coverage of spatial statistics, real-world examples, and user-friendly approach in presenting and explaining R code, aspects maintained in this update. Using data sets from cultivated and uncultivated ecosystems, the book guides the reader through the analysis of each data set, including setting research objectives, designing the sampling plan, data quality control, exploratory and confirmatory data analysis, and drawing scientific conclusions. Additional material to accompany the book, on both analyzing satellite data and on multivariate analysis, can be accessed at https://www.plantsciences.ucdavis.edu/plant/additionaltopics.htm.

Precision Agriculture 19

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Author : John V. Stafford
language : en
Publisher: BRILL
Release Date : 2023-08-07

Precision Agriculture 19 written by John V. Stafford and has been published by BRILL this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-07 with Technology & Engineering categories.

Precision agriculture is a reality in agriculture and is playing a key role as the industry comes to terms with the environment, market forces, quality requirements, traceability, vehicle guidance and crop management. Research continues to be necessary, and needs to be reported and disseminated to a wide audience. These proceedings contain reviewed papers presented at the 12th European Conference on Precision Agriculture, held at Montpellier SupAgro, France. The papers reflect the wide range of disciplines that impinge on precision agriculture - technology, crop science, soil science, agronomy, information technology, decision support, remote sensing and others. The broad range of research topics reported will be a valuable resource for researchers, advisors, teachers and professionals in agriculture long after the conference has finished.

Ecological Statistics

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Author : Gordon A. Fox
language : en
Publisher: Oxford University Press
Release Date : 2015

Ecological Statistics written by Gordon A. Fox and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Computers categories.

The application and interpretation of statistics are central to ecological study and practice. Ecologists are now asking more sophisticated questions than in the past. These new questions, together with the continued growth of computing power and the availability of new software, have created a new generation of statistical techniques. These have resulted in major recent developments in both our understanding and practice of ecological statistics. This novel book synthesizes a number of these changes, addressing key approaches and issues that tend to be overlooked in other books such as missing/censored data, correlation structure of data, heterogeneous data, and complex causal relationships. These issues characterize a large proportion of ecological data, but most ecologists' training in traditional statistics simply does not provide them with adequate preparation to handle the associated challenges. Uniquely, Ecological Statistics highlights the underlying links among many statistical approaches that attempt to tackle these issues. In particular, it gives readers an introduction to approaches to inference, likelihoods, generalized linear (mixed) models, spatially or phylogenetically-structured data, and data synthesis, with a strong emphasis on conceptual understanding and subsequent application to data analysis. Written by a team of practicing ecologists, mathematical explanations have been kept to the minimum necessary. This user-friendly textbook will be suitable for graduate students, researchers, and practitioners in the fields of ecology, evolution, environmental studies, and computational biology who are interested in updating their statistical tool kits. A companion web site provides example data sets and commented code in the R language.

Spatial Analysis

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Author : Mark R. T. Dale
language : en
Publisher: Cambridge University Press
Release Date : 2014-09-11

Spatial Analysis written by Mark R. T. Dale and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-11 with Mathematics categories.

An essential guide for graduates, researchers and professionals to spatial analysis and the fast-growing range of methods available.

Proceedings Of Mac Emmt 2014

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Author : Collective of authors
language : en
Publisher: MAC Prague consulting
Release Date : 2014-04-25

Proceedings Of Mac Emmt 2014 written by Collective of authors and has been published by MAC Prague consulting this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-04-25 with categories.

Proceedings of the scientific conference on economics, management, marketing and transportation.

Practical Mathematics For Precision Farming

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Author : David E. Clay
language : en
Publisher: John Wiley & Sons
Release Date : 2020-01-22

Practical Mathematics For Precision Farming written by David E. Clay and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-22 with Technology & Engineering categories.

As the public and producers becomes more aware of the environmental and economic benefits of precision farming, there has been increased demand for quality training to accurately evaluate spatial variability within fields. Practical Mathematics in Precision Farming provides hand-on training and examples for certified crop consultants (CCAs), farmers, crop consultants, and students (both undergraduate and graduate) on how to conduct to conduct and analyze on-farm studies, write simple programs, use precision techniques to scout for pests and collect soil samples, develop management zones, determine the cost of production, assess the environmental consequences of precision techniques, understand soil test results, and develop site-specific nutrient and plant population algorithms. Using real agronomic examples, the reader is taught the crucial task of managing products and inputs for application at the right rate, place, and time.

Landscape Ecology

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Author : Dean L Urban
language : en
Publisher: Springer Nature
Release Date : 2024-12-01

Landscape Ecology written by Dean L Urban and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-01 with Science categories.

This is methods/tools textbook that covers the fundamental tasks in research and management at the landscape scale. It brings together tools from a range of disciplines and presents them in a natural workflow that a practitioner can appreciate. Alternative texts cover a narrower range of topics and/or present the information without reference to a natural workflow. The book begins with 2 fundamental applications that introduce the scope and challenges of working at the landscape scales (sampling design and species distribution modeling). These motivate several chapters that ‘digress’ to cover the primary tools that ecologists use to work with multivariate and spatial data. The book then returns to applications including site prioritization, interpreting (and forecasting) landscape change, and integrated assessment. The tasks themselves follow a logical workflow of collecting and analyzing data, applying the analyses to management decisions, and interpreting the outcomes of these decisions in an integrated framework. This book stems from two graduate-level courses in Landscape Ecology taught at the Nicholas School of the Environment at Duke University. The subject has evolved over time, from a concepts-based overview of what landscape ecology is, to a more applied practicum on how one does landscape ecology. As landscape ecology has matured as a discipline, its perspectives on spatial heterogeneity and scale have begun to permeate into a wide range of other fields including conservation biology, ecosystem management, and ecological restoration. Thus, this textbook will bring students from diverse backgrounds to a common level of understanding and will prepare them with the practical knowledge for a career in conservation and ecosystem management.

Advanced Introduction To Spatial Statistics

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Author : Griffith, Daniel A.
language : en
Publisher: Edward Elgar Publishing
Release Date : 2022-08-12

Advanced Introduction To Spatial Statistics written by Griffith, Daniel A. and has been published by Edward Elgar Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-12 with Social Science categories.

This Advanced Introduction provides a critical review and discussion of research concerning spatial statistics, differentiating between it and spatial econometrics, to answer a set of core questions covering the geographic-tagging-of-data origins of the concept and its theoretical underpinnings, conceptual advances, and challenges for future scholarly work. It offers a vital tool for understanding spatial statistics and surveys how concerns about violating the independent observations assumption of statistical analysis developed into this discipline.

Introduction To Machine Learning With Applications In Information Security

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Author : Mark Stamp
language : en
Publisher: CRC Press
Release Date : 2022-09-27

Introduction To Machine Learning With Applications In Information Security written by Mark Stamp and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-27 with Business & Economics categories.

Introduction to Machine Learning with Applications in Information Security, Second Edition provides a classroom-tested introduction to a wide variety of machine learning and deep learning algorithms and techniques, reinforced via realistic applications. The book is accessible and doesn’t prove theorems, or dwell on mathematical theory. The goal is to present topics at an intuitive level, with just enough detail to clarify the underlying concepts. The book covers core classic machine learning topics in depth, including Hidden Markov Models (HMM), Support Vector Machines (SVM), and clustering. Additional machine learning topics include k-Nearest Neighbor (k-NN), boosting, Random Forests, and Linear Discriminant Analysis (LDA). The fundamental deep learning topics of backpropagation, Convolutional Neural Networks (CNN), Multilayer Perceptrons (MLP), and Recurrent Neural Networks (RNN) are covered in depth. A broad range of advanced deep learning architectures are also presented, including Long Short-Term Memory (LSTM), Generative Adversarial Networks (GAN), Extreme Learning Machines (ELM), Residual Networks (ResNet), Deep Belief Networks (DBN), Bidirectional Encoder Representations from Transformers (BERT), and Word2Vec. Finally, several cutting-edge deep learning topics are discussed, including dropout regularization, attention, explainability, and adversarial attacks. Most of the examples in the book are drawn from the field of information security, with many of the machine learning and deep learning applications focused on malware. The applications presented serve to demystify the topics by illustrating the use of various learning techniques in straightforward scenarios. Some of the exercises in this book require programming, and elementary computing concepts are assumed in a few of the application sections. However, anyone with a modest amount of computing experience should have no trouble with this aspect of the book. Instructor resources, including PowerPoint slides, lecture videos, and other relevant material are provided on an accompanying website: http://www.cs.sjsu.edu/~stamp/ML/.