Satellite image analysis : clustering and classification /

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Bibliographic Details
Author / Creator:Borra, Surekha, author.
Imprint:Singapore : Springer, [2019]
Description:1 online resource
Series:SpringerBriefs in applied sciences and technology, Computational intelligence, 2625-3704
SpringerBriefs in applied sciences and technology. Computational intelligence.
Subject:Remote-sensing images.
Image analysis.
Image analysis.
Remote-sensing images.
Electronic books.
Format: E-Resource Book
URL for this record:
Hidden Bibliographic Details
Other authors / contributors:Thanki, Rohit, author.
Dey, Nilanjan, 1984- author.
Digital file characteristics:text file PDF
Notes:Includes bibliographical references.
Online resource; title from PDF title page (SpringerLink, viewed February 14, 2019).
Summary:Thanks to recent advances in sensors, communication and satellite technology, data storage, processing and networking capabilities, satellite image acquisition and mining are now on the rise. In turn, satellite images play a vital role in providing essential geographical information. Highly accurate automatic classification and decision support systems can facilitate the efforts of data analysts, reduce human error, and allow the rapid and rigorous analysis of land use and land cover information. Integrating Machine Learning (ML) technology with the human visual psychometric can help meet geologists' demands for more efficient and higher-quality classification in real time. This book introduces readers to key concepts, methods and models for satellite image analysis; highlights state-of-the-art classification and clustering techniques; discusses recent developments and remaining challenges; and addresses various applications, making it a valuable asset for engineers, data analysts and researchers in the fields of geographic information systems and remote sensing engineering.
Other form:Print version: Borra, Surekha. Satellite image analysis. Singapore : Springer, [2019] 9811364230 9789811364235
Standard no.:10.1007/978-981-13-6424-2