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Books > Computing & IT > Applications of computing > Image processing
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Assessing the Accuracy of Remotely Sensed Data - Principles and Practices, Third Edition (Hardcover, 3rd edition)
Loot Price: R4,388
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Assessing the Accuracy of Remotely Sensed Data - Principles and Practices, Third Edition (Hardcover, 3rd edition)
Expected to ship within 12 - 17 working days
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The past 10 years have brought amazing changes to the technologies
used to turn remotely sensed data into maps. As a result, the
principles and practices necessary for assessing the accuracy of
those maps have also evolved and matured. This third edition of
Assessing the Accuracy of Remotely Sensed Data: Principles and
Practices is thoroughly updated and includes five new chapters. Now
15 chapters long, this text is the only one of its kind to provide
geospatial analysts with the requisite considerations, tools, and
theory necessary to conduct successful and efficient map accuracy
assessments; and map users with the knowledge to fully understand
the assessment process to ensure effective use of maps. See What's
New in the Third Edition: All original chapters have been updated
to include new standards, practices, and methodologies. A new
chapter on planning accuracy assessments. A new chapter on
assessing maps created using object-based technologies. Two case
study chapters - one showcasing the assessment of maps created from
traditional methods, and one on the assessment of object-based
maps. Emphasis on considering and planning for positional accuracy
in concert with thematic accuracy. An appendix containing the
internationally recognized ASPRS Positional Accuracy Standards. A
new final chapter summarizing the key concepts, considerations and
lessons learned by the authors in their decades of implementing and
evaluating accuracy assessments. Assessing map accuracy is complex;
however, the discussions in this book, together with the many
figures, tables, and case studies, clearly present the necessary
concepts and considerations for conducting an assessment that is
both is practical, statistically reliable, and achievable.
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