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Advances in Spatial Data Handling and GIS, Anthony G.O. Yeh; Wenzhong Shi; Yee Leung; Chenghu


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При оформлении заказа до: 2025-07-28
Ориентировочная дата поставки: Август-начало Сентября
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Автор: Anthony G.O. Yeh; Wenzhong Shi; Yee Leung; Chenghu
Название:  Advances in Spatial Data Handling and GIS
ISBN: 9783642445538
Издательство: Springer
Классификация:

ISBN-10: 3642445535
Обложка/Формат: Paperback
Страницы: 242
Вес: 0.41 кг.
Дата издания: 2012
Серия: Lecture Notes in Geoinformation and Cartography
Язык: English
Иллюстрации: Biography
Размер: 234 x 156 x 14
Читательская аудитория: Professional & vocational
Подзаголовок: 14th international symposium on spatial data handling
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: Containing selected papers from the 14th International Symposium on Spatial Data Handling, this book offers a cross-section of cutting-edge research currently under way, and features topics ranging from digital cartography to GIS for sustainable development.


Adjustment Computations: Spatial Data Analysis, 5th Edition

Автор: Charles D. Ghilani
Название: Adjustment Computations: Spatial Data Analysis, 5th Edition
ISBN: 0470464917 ISBN-13(EAN): 9780470464915
Издательство: Wiley
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Цена: 23760.00 р.
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Описание: the complete guide to adjusting for measurement error—expanded and updated no measurement is ever exact. Adjustment Computations updates a classic, definitive text on surveying with the latest methodologies and tools for analyzing and adjusting errors with a focus on least squares adjustments, the most rigorous methodology available and the one on which accuracy standards for surveys are based. This extensively updated Fifth Edition shares new information on advances in modern software and GNSS-acquired data. Expanded sections offer a greater amount of computable problems and their worked solutions, while new screenshots guide readers through the exercises. Continuing its legacy as a reliable primer, Adjustment Computations covers the basic terms and fundamentals of errors and methods of analyzing them and progresses to specific adjustment computations and spatial information analysis. Current and comprehensive, the book features: •Easy-to-understand language and an emphasis on real-world applications •Analyzing data in three dimensions, confidence intervals, statistical testing, and more •An updated support web page containing a 150-page solutions manual, software (STATS, ADJUST, and MATRIX for Windows computers), MathCAD worksheets, and more at http://www.wiley.com/college/ghilani •The latest information on advanced topics such as the tau criterion used in post-adjustment statistical blunder detection Adjustment Computations, Fifth Edition is an invaluable reference and self-study resource for working surveyors, photogrammetrists, and professionals who use GNSS and GIS for data collection and analysis, including oceanographers, urban planners, foresters, geographers, and transportation planners. It's also an indispensable resource for students preparing for licensing exams and the ideal textbook for courses in surveying, civil engineering, forestry, cartography, and geology.

Advances in environmental remote sensing

Название: Advances in environmental remote sensing
ISBN: 1420091751 ISBN-13(EAN): 9781420091755
Издательство: Taylor&Francis
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Цена: 31390.00 р.
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Описание: Featuring contributors from 17 countries, this book presents the advances in environmental remote sensing. It provides the developments in remote sensing data and sensor systems, paying attention to LIDAR, high spatial-resolution sensing, hyperspectral sensing, and data fusion of various sensors.

The Rise of Big Spatial Data

Автор: Ivan
Название: The Rise of Big Spatial Data
ISBN: 3319451227 ISBN-13(EAN): 9783319451220
Издательство: Springer
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Цена: 30745.00 р.
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Описание: This edited volume gathers the proceedings of the Symposium GIS Ostrava 2016, the Rise of Big Spatial Data, held at the Technical University of Ostrava, Czech Republic, March 16–18, 2016. Combining theoretical papers and applications by authors from around the globe, it summarises the latest research findings in the area of big spatial data and key problems related to its utilisation.Welcome to dawn of the big data era: though it’s in sight, it isn’t quite here yet. Big spatial data is characterised by three main features: volume beyond the limit of usual geo-processing, velocity higher than that available using conventional processes, and variety, combining more diverse geodata sources than usual. The popular term denotes a situation in which one or more of these key properties reaches a point at which traditional methods for geodata collection, storage, processing, control, analysis, modelling, validation and visualisation fail to provide effective solutions. >Entering the era of big spatial data calls for finding solutions that address all “small data” issues that soon create “big data” troubles. Resilience for big spatial data means solving the heterogeneity of spatial data sources (in topics, purpose, completeness, guarantee, licensing, coverage etc.), large volumes (from gigabytes to terabytes and more), undue complexity of geo-applications and systems (i.e. combination of standalone applications with web services, mobile platforms and sensor networks), neglected automation of geodata preparation (i.e. harmonisation, fusion), insufficient control of geodata collection and distribution processes (i.e. scarcity and poor quality of metadata and metadata systems), limited analytical tool capacity (i.e. domination of traditional causal-driven analysis), low visual system performance, inefficient knowledge-discovery techniques (for transformation of vast amounts of information into tiny and essential outputs) and much more. These trends are accelerating as sensors become more ubiquitous around the world.

Fundamentals of Spatial Data Quality

Автор: Devillers
Название: Fundamentals of Spatial Data Quality
ISBN: 1905209568 ISBN-13(EAN): 9781905209569
Издательство: Wiley
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Цена: 22010.00 р.
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Описание: This book explains the concept of spatial data quality, a key theory for minimizing the risks of data misuse in a specific decision-making context.


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