دانلود کتاب روش های عددی در تجزیه و تحلیل داده های محیطی

Environmental data may be described in terms of quantitative, qualitative, or geographically referenced facts that represent the state of the environment and its changes. Quantitative environmental data consist of data, statistics and indicators of databases, spreadsheets, compendia, and yearbook type products. Qualitative environment data are descriptions (e.g., textual, pictorial) of the environment or its constituent parts that cannot be adequately represented by accurate quantitative or geographically referenced descriptors. Geographically referenced environmental data are described in digital maps, satellite imagery, and other sources linked to a location or map feature. Summarily, it can be postulated that dataset in environmental studies is like blood to the human body. All decisions in environmental studies are based on observables that are measurable, reliable, realistic, and consistent with theories. Environmental theories are formulated from observables. Hence, a faulty observable can lead to a colossal failure in processes, prediction, model formulation, and decision. The inevitable outcomes of climate change have redefined observables such that new theories and models are necessary due to data inconsistency, noise, and spikes. Aside from just getting dataset and simulating, it is now expedient that the integrity of a dataset be the first line of operation in data analytics. This feat can be achieved through the guidance of proven theories. The knowledge of this theory, when to apply it on a dataset, how to apply it, and ways to validate emerging results are salient in any field of environmental sciences. Hence, the focus of this book is to educate beginners and professionals on the above.