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Titlebook: Optical and SAR Remote Sensing of Urban Areas; A Practical Guide Courage Kamusoko Book 2022 The Editor(s) (if applicable) and The Author(s)

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發(fā)表于 2025-3-21 18:50:23 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Optical and SAR Remote Sensing of Urban Areas
副標題A Practical Guide
編輯Courage Kamusoko
視頻videohttp://file.papertrans.cn/703/702724/702724.mp4
概述Is designed to be a workbook for students, researchers, and practitioners.Includes step-by-step reference tutorials for processing optical and SAR data.Uses free and open source software such as QGIS
叢書名稱Springer Geography
圖書封面Titlebook: Optical and SAR Remote Sensing of Urban Areas; A Practical Guide Courage Kamusoko Book 2022 The Editor(s) (if applicable) and The Author(s)
描述.This book introduces remotely sensed image processing for urban areas using optical and synthetic aperture radar (SAR) data and assists students, researchers, and remote sensing practitioners who are interested in land cover mapping using such data. There are many introductory and advanced books on optical and SAR remote sensing image processing, but most of them do not serve as good practical guides. However, this book is designed as a practical guide and a hands-on workbook, where users can explore data and methods to improve their land cover mapping skills for urban areas. Although there are many freely available earth observation data, the focus is on land cover mapping using Sentinel-1 C-band SAR and Sentinel-2 data. All remotely sensed image processing and classification procedures are based on open-source software applications such QGIS and R as well as cloud-based platforms such as Google Earth Engine (GEE)...The book is organized into six chapters. Chapter 1 introduces geospatial machine learning, and Chapter 2 covers exploratory image analysis and transformation. Chapters 3 and 4 focus on mapping urban land cover using multi-seasonal Sentinel-2 imagery and multi-seasonal
出版日期Book 2022
關(guān)鍵詞Urban remote sensing; Optical and synthetic aperture radar (SAR) data; Geospatial machine learning; Lan
版次1
doihttps://doi.org/10.1007/978-981-16-5149-6
isbn_softcover978-981-16-5151-9
isbn_ebook978-981-16-5149-6Series ISSN 2194-315X Series E-ISSN 2194-3168
issn_series 2194-315X
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
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發(fā)表于 2025-3-21 20:23:52 | 只看該作者
Land Cover Classification Accuracy Assessment,der to implement rigorous accuracy assessment. The good practice recommendations encourage estimation of area based on the reference classification and analysis of information contained in the confusion or error matrix. In this chapter, we are going to use the good practice recommendations based on sampling design, response design, and analysis.
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發(fā)表于 2025-3-22 03:41:29 | 只看該作者
地板
發(fā)表于 2025-3-22 07:17:52 | 只看該作者
2194-315X nd SAR data.Uses free and open source software such as QGIS .This book introduces remotely sensed image processing for urban areas using optical and synthetic aperture radar (SAR) data and assists students, researchers, and remote sensing practitioners who are interested in land cover mapping using
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發(fā)表于 2025-3-22 10:36:26 | 只看該作者
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發(fā)表于 2025-3-22 13:49:34 | 只看該作者
Book 2022earchers, and remote sensing practitioners who are interested in land cover mapping using such data. There are many introductory and advanced books on optical and SAR remote sensing image processing, but most of them do not serve as good practical guides. However, this book is designed as a practica
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發(fā)表于 2025-3-22 20:24:32 | 只看該作者
Springer Geographyhttp://image.papertrans.cn/o/image/702724.jpg
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發(fā)表于 2025-3-23 01:10:28 | 只看該作者
https://doi.org/10.1007/978-981-16-5149-6Urban remote sensing; Optical and synthetic aperture radar (SAR) data; Geospatial machine learning; Lan
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發(fā)表于 2025-3-23 02:52:07 | 只看該作者
978-981-16-5151-9The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
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發(fā)表于 2025-3-23 09:16:01 | 只看該作者
Optical and SAR Remote Sensing of Urban Areas978-981-16-5149-6Series ISSN 2194-315X Series E-ISSN 2194-3168
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