Scale Issues in Remote Sensing

Scale Issues in Remote Sensing
Авторы книги: id книги: 884636     Оценка: 0.0     Голосов: 0     Отзывы, комментарии: 0 14542,4 руб.     (141,77$) Купить и читать книгу Купить бумажную книгу Электронная книга Жанр: Техническая литература Правообладатель и/или издательство: John Wiley & Sons Limited Дата добавления в каталог КнигаЛит: ISBN: 9781118801550 Возрастное ограничение: 0+

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Provides up-to-date developments in the field of remote sensing by assessing scale issues in land surface, properties, patterns, and processes Scale is a fundamental and crucial issue in remote sensing studies and image analysis. GIS and remote sensing scientists use various scaling techniques depending on the types of remotely sensed images and geospatial data used. Scaling techniques affect image analysis such as object identification and change detection. This book offers up-to-date developments, methods, and techniques in the field of GIS and remote sensing and features articles from internationally renowned authorities on three interrelated perspectives of scaling issues: scale in land surface properties, land surface patterns, and land surface processes. It also visits and reexamines the fundamental theories of scale and scaling by well-known experts who have done substantial research on the topics. Edited by a prominent authority in the geographic information science community, Scale Issues in Remote Sensing: Offers an extensive examination of the fundamental theories of scale issues along with current scaling techniques Studies scale issues from three interrelated perspectives: land surface properties, patterns, and processes Addresses the impact of new frontiers in Earth observation technology (high-resolution, hyperspectral, Lidar sensing, and their synergy with existing technologies) and advances in remote sensing imaging science (object-oriented image analysis and data fusion) Prospects emerging and future trends in remote sensing and their relationship with scale Scale Issues in Remote Sensing is ideal as a professional reference for practicing geographic information scientists and remote sensing engineers as well as supplemental reading for graduate level students.

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