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Data Treatment in Environmental Sciences

Data Treatment in Environmental Sciences presents the various methods used in the analysis of databases-obtained in the field or in a;

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Machine Learning Methods in the Environmental Sciences

Machine learning methods originated from artificial intelligence and are now used in various fields in environmental sciences today. This;

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Machine Learning Methods in the Environmental Sciences

Machine learning methods originated from artificial intelligence and are now used in various fields in environmental sciences today. This;

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Applied Directional Statistics

of attention due to demands from disciplines such as life sciences or machine learning, the availability of massive data sets requiring adapted;

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Statistical Computation for Environmental Sciences in R

The environmental sciences are undergoing a revolution in the use of models and data. Facing ecological data sets of unprecedented size and;

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Biometry for Forestry and Environmental Data

Biometry for Forestry and Environmental Data with Examples in R focuses on statistical methods that are widely applicable in forestry and;

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Spatial Data Analysis in the Social and Environmental Sciences

Within both the social and environmental sciences, much of the data collected is within a spatial context and requires statistical analysis;

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Environmental Data Analysis

analyze, interpret and model data from various sources, and is also an ideal graduate-level textbook for courses in environmental sciences and;

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Ecological Data

and implementing ecological research, as well as students who are entering the environmental sciences. Chapters focus on the design;

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Statistics for Earth and Environmental Scientists

approaches to the environmental sciences, including Bayesian and nonparametric methodologies. The book begins with an introduction to types of data;

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Environmental Data Exchange Network for Inland Water

that first discusses the importance of data exchange and describes why it is essential for gathering data in the environmental sciences. Part;

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Advances in Environmental Sciences and Engineering

Treatment, Environmental Biotechnology, Climate Change, Application of Remote Sensing and GIS in Environmental Monitoring, Forest Ecology etc. The;

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Models for Ecological Data

The environmental sciences are undergoing a revolution in the use of models and data. Facing ecological data sets of unprecedented size and;

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Statistical Data Analysis Explained

Few books on statistical data analysis in the natural sciences are written at a level that a non-statistician will easily understand. This;

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Data Analysis for Omic Sciences: Methods and Applications

Data Analysis for Omic Sciences: Methods and Applications, Volume 82, shows how these types of challenging datasets can be analyzed;

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Statistics in Environmental Sciences

Statistical tools are indispensable for the environmental sciences. They have become an integral part of the scientific process, from the;

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Cambridge Studies in Comparative Politics

The ultimate goal of environmental policy is reducing pollution. Attention to environmental problems in the social sciences has brought;

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Sustaining Abundance

The ultimate goal of environmental policy is reducing pollution. Attention to environmental problems in the social sciences has brought;

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Extinction Rates

projections of extinction rates for the centuries to come. This book provides a more wide-ranging and data-driven treatment of present and likely;

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Computational Ecology: Graphs, Networks And Agent-based Modeling

Graphs, networks and agent-based modeling are the most thriving and attracting sciences used in ecology and environmental sciences. As such;

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Environmental Data Analysis with MatLab or Python

to analyze real data sets in the environmental sciences. The work teaches the basics of the underlying theory of data analysis and then;

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Geospatial Applications for Natural Resources Management

of environmental spatio-temporal data. Presents examples of applications for spatial information sciences regarding the assessment, monitoring, and;

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Artificial Intelligence

understanding of complex research phenomena in the environmental sciences, encompassing heterogeneous, noisy, inaccurate, uncertain, diverse spatio;

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Numerical Methods in Environmental Data Analysis

Numerical Methods in Environmental Data Analysis introduces environmental scientists to the numerical methods available to help answer;

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C for Environmental Scientists and Engineers

to the practical use of C programming for the Environmental Management degree course, as well as students of other natural sciences and;

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Environmental Protection at the State Level

environmental quality in these states? This work seeks to answer these question by means of combining data, methods and theory from the natural and;

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Environmental Protection at the State Level

environmental quality in these states? This work seeks to answer these question by means of combining data, methods and theory from the natural and;

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