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GIS-based Analysis of Coastal Lidar Time-Series, Eric Hardin; Helena Mitasova; Laura Tateosian; Mar


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Автор: Eric Hardin; Helena Mitasova; Laura Tateosian; Mar
Название:  GIS-based Analysis of Coastal Lidar Time-Series
ISBN: 9781493918348
Издательство: Springer
Классификация:



ISBN-10: 1493918346
Обложка/Формат: Soft cover
Страницы: 84
Вес: 0.16 кг.
Дата издания: 13.09.2014
Серия: SpringerBriefs in Computer Science
Язык: English
Иллюстрации: 1 black & white illustrations, 34 colour illustrations, 2 black & white tables, biography
Размер: 234 x 156 x 5
Читательская аудитория: Professional & vocational
Основная тема: Geographical Information Systems/Cartography
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This SpringerBrief presents the principles, methods, and workflows for processing and analyzing coastal LiDAR data time-series. Simple methods for potential storm impacts and inundation pattern analysis are also covered, along with visualization techniques to support analysis of coastal terrain feature and surface dynamics.


Spatial Analysis of Coastal Environments

Автор: Hamylton
Название: Spatial Analysis of Coastal Environments
ISBN: 1107070473 ISBN-13(EAN): 9781107070479
Издательство: Cambridge Academ
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Цена: 8554.00 р.
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Описание: This book covers the spatial analytical tools needed to map, monitor and explain or predict coastal features. Presenting empirical geographical approaches using recent technological developments, while providing detailed case studies on a range of coastal environments, it is an ideal resource for undergraduates studying spatial science.

Pattern-Based Compression of Multi-Band Image Data for Landscape Analysis

Автор: Wayne L. Myers; Ganapati P. Patil
Название: Pattern-Based Compression of Multi-Band Image Data for Landscape Analysis
ISBN: 1441942718 ISBN-13(EAN): 9781441942715
Издательство: Springer
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Цена: 23757.00 р.
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Описание: This book describes an integrated approach to using remotely sensed data in conjunction with geographic information systems for landscape analysis. Remotely sensed data are compressed into an analytical image-map that is compatible with the most popular geographic information systems as well as freeware viewers.

Improving GIS-based Wildlife-Habitat Analysis

Автор: Jeffrey K. Keller; Charles R. Smith
Название: Improving GIS-based Wildlife-Habitat Analysis
ISBN: 3319096079 ISBN-13(EAN): 9783319096070
Издательство: Springer
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Цена: 8384.00 р.
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Описание: Geographic Information Systems (GIS) provide a powerful tool for the investigation of species-habitat relationships and the development of wildlife management and conservation programs. However, the relative ease of data manipulation and analysis using GIS, associated landscape metrics packages, and sophisticated statistical tests may sometimes cause investigators to overlook important species-habitat functional relationships. Additionally, underlying assumptions of the study design or technology may have unrecognized consequences. This volume examines how initial researcher choices of image resolution, scale(s) of analysis, response and explanatory variables, and location and area of samples can influence analysis results, interpretation, predictive capability, and study-derived management prescriptions. Overall, most studies in this realm employ relatively low resolution imagery that allows neither identification nor accurate classification of habitat components. Additionally, the landscape metrics typically employed do not adequately quantify component spatial arrangement associated with species occupation. To address this latter issue, the authors introduce two novel landscape metrics that measure the functional size and location in the landscape of taxon-specific ‘solid’ and ‘edge’ habitat types. Keller and Smith conclude that investigators conducting GIS-based analyses of species-habitat relationships should more carefully 1) match the resolution of remotely sensed imagery to the scale of habitat functional relationships of the focal taxon, 2) identify attributes (explanatory variables) of habitat architecture, size, configuration, quality, and context that reflect the way the focal taxon uses the subset of the landscape it occupies, and 3) match the location and scale of habitat samples, whether GIS- or ground-based, to corresponding species’ detection locations and scales of habitat use.


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