Aboveground Tree Biomass on Productive Forest Land in Alaska PDF Download
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Author: John Yarie
Publisher:
ISBN:
Category : Biomass energy
Languages : en
Pages : 20
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Book Description
Author: John Yarie
Publisher:
ISBN:
Category : Biomass energy
Languages : en
Pages : 20
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Book Description
Author: John Yarie
Publisher:
ISBN:
Category : Biomass energy
Languages : en
Pages : 28
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Author: Bert R. Mead
Publisher:
ISBN:
Category : Forest biomass
Languages : en
Pages : 88
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Book Description
Author: Nick Pears
Publisher: Springer Science & Business Media
ISBN: 144714063X
Category : Computers
Languages : en
Pages : 506
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Book Description
3D Imaging, Analysis and Applications brings together core topics, both in terms of well-established fundamental techniques and the most promising recent techniques in the exciting field of 3D imaging and analysis. Many similar techniques are being used in a variety of subject areas and applications and the authors attempt to unify a range of related ideas. With contributions from high profile researchers and practitioners, the material presented is informative and authoritative and represents mainstream work and opinions within the community. Composed of three sections, the first examines 3D imaging and shape representation, the second, 3D shape analysis and processing, and the last section covers 3D imaging applications. Although 3D Imaging, Analysis and Applications is primarily a graduate text, aimed at masters-level and doctoral-level research students, much material is accessible to final-year undergraduate students. It will also serve as a reference text for professional academics, people working in commercial research and development labs and industrial practitioners.
Author:
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ISBN:
Category : Forests and forestry
Languages : en
Pages : 418
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Author:
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ISBN:
Category : Agriculture
Languages : en
Pages : 18
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Author: Grant Humphries
Publisher: Springer
ISBN: 3319969781
Category : Science
Languages : en
Pages : 442
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Book Description
Ecologists and natural resource managers are charged with making complex management decisions in the face of a rapidly changing environment resulting from climate change, energy development, urban sprawl, invasive species and globalization. Advances in Geographic Information System (GIS) technology, digitization, online data availability, historic legacy datasets, remote sensors and the ability to collect data on animal movements via satellite and GPS have given rise to large, highly complex datasets. These datasets could be utilized for making critical management decisions, but are often “messy” and difficult to interpret. Basic artificial intelligence algorithms (i.e., machine learning) are powerful tools that are shaping the world and must be taken advantage of in the life sciences. In ecology, machine learning algorithms are critical to helping resource managers synthesize information to better understand complex ecological systems. Machine Learning has a wide variety of powerful applications, with three general uses that are of particular interest to ecologists: (1) data exploration to gain system knowledge and generate new hypotheses, (2) predicting ecological patterns in space and time, and (3) pattern recognition for ecological sampling. Machine learning can be used to make predictive assessments even when relationships between variables are poorly understood. When traditional techniques fail to capture the relationship between variables, effective use of machine learning can unearth and capture previously unattainable insights into an ecosystem's complexity. Currently, many ecologists do not utilize machine learning as a part of the scientific process. This volume highlights how machine learning techniques can complement the traditional methodologies currently applied in this field.
Author:
Publisher:
ISBN:
Category : Forests and forestry
Languages : en
Pages : 136
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Author:
Publisher:
ISBN:
Category : Agriculture
Languages : en
Pages : 40
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Author: Victor A. Rudis
Publisher:
ISBN:
Category : Electronic books
Languages : en
Pages : 136
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Book Description
