Remote Sensing and Digital Image Processing with R

This new textbook on remote sensing and digital image processing of natural resources includes numerous practical, problem-solving exercises, applications of sensors and satellite systems using remote sensing data collection resources with emphasis on free and open-source platform R. It explains basic concepts of remote sensing and multidisciplinary applications using R language and R packages, by engaging students in learning theory through hands-on, real-life projects. All chapters are structured with learning objectives, computation, questions, solved exercises, resources and research suggestions.

Features

1. Explains the theory of passive and active remote sensing and its applications in water, soil, vegetation, and atmosphere.

2. Covers data analysis in free and open-source (FOSS) R platform, which makes remote sensing accessible to anyone with a computer.

3. Includes case studies from different environments with free software algorithm and R toolset for active learning and learn-by-doing.

4. Provides hands-on exercises at the end of each chapter and encourages readers to understand the potential and the limitations of the environments, remote sensing targets and process.

5. Explores current trends and developments in remote sensing in homework assignments with data to further explore the use of free multispectral remote sensing data, including very high spatial resolution data sources for target recognition with image processing techniques.

While the focus of the book is on environmental and agriculture engineering, it can be applied widely to a variety of subjects such as physical, natural, and social sciences. Students in upper-level undergraduate or graduate programs, taking courses in Remote Sensing, Geoprocessing, Civil and Environmental Engineering, Geosciences, Environmental Sciences, Electrical Engineering, Biology, and Hydrology will also benefit from the learning objectives in the book. Professionals who use remote sensing and digital processing will also find this text enlightening.

這本關於遙感和自然資源的數字影像處理的新教科書包含了許多實際的問題解決練習，運用遙感數據收集資源的儀器和衛星系統應用，並強調使用免費和開源平台R。它通過讓學生參與實際項目的理論學習，解釋了遙感的基本概念和多學科應用，並使用R語言和R套件進行教學。所有章節都有學習目標、計算、問題、解答練習、資源和研究建議。

特點：
1. 解釋了被動和主動遙感的理論以及其在水、土壤、植被和大氣中的應用。
2. 使用免費和開源（FOSS）R平台進行數據分析，使遙感對任何有電腦的人都可用。
3. 包含來自不同環境的案例研究，使用免費軟體算法和R工具集進行主動學習和實踐。
4. 在每章結尾提供實踐練習，鼓勵讀者了解環境、遙感目標和過程的潛力和限制。
5. 通過作業任務探索遙感的當前趨勢和發展，使用免費多光譜遙感數據，包括非常高的空間分辨率數據源，進行目標識別和影像處理技術。

雖然這本書的重點是環境和農業工程，但它也可以廣泛應用於物理、自然和社會科學等各種學科。上級本科或研究生課程的學生，修讀遙感、地理處理、土木和環境工程、地球科學、環境科學、電氣工程、生物學和水文學等課程的學生，也會從本書的學習目標中受益。使用遙感和數字處理的專業人士也會發現這本書很有啟發性。

Marcelo de Carvalho Alves

Dr. Alves is an associate professor at the Federal University de Lavras, Brazil. His education includes master's, doctoral, and post-doctoral degrees in Agricultural Engineering at Federal University of Lavras, Brazil. He has varied research interests and has published on surveying, remote sensing, geocomputation, and agriculture applications. He has over 20 years of extensive experience in data science, digital image processing, and modeling using multiscale, multidisciplinary, multispectral, and multitemporal concepts applied to different environments. Experimental field sites included a tropical forest, savanna, wetland, and agricultural fields in Brazil. His research has been predominantly funded by CNPq, CAPES, FAPEMIG, and FAPEMAT. Over the years, he has built a large portfolio of research grants, mostly relating to applied and theoretical remote sensing, broadly in the context of vegetation cover, plant diseases, and related impacts of climate change.

Luciana Sanches

Dr. Sanches graduated with a degree in Sanitary Engineering from the Federal University of Mato Grosso, Brazil, a master's degree in Sanitation, Environment, and Water Resources from the Federal University of Minas Gerais, a PhD in Road Engineering, Hydraulic Channels, and Ports from Universidad de Cantabria, Spain, a post-doctorate degree in Environmental Physics, Brazil, and a post-doctorate degree in Environmental Sciences from the University of Reading, United Kingdom. Her education includes postgraduate degreees in Workplace Safety Engineering at Federal University of Mato Grosso, Brazil, and in Project Development and Management for Municipal Water Resources Management by the National Water Agency, Brazil. She is currently an associate professor at the Federal University of Mato Grosso, and worked for more than 20 years in research on atmosphere-biosphere interaction, hydrometeorology in various temporal-spatial scales with interpretation based in environmental modeling and remote sensing. She has been applying remote sensing in teaching and research activities to support the interpretation of environmental dynamics.

Marcelo de Carvalho Alves

Dr. Alves是巴西拉夫拉斯聯邦大學的副教授。他在巴西拉夫拉斯聯邦大學獲得了農業工程的碩士、博士和博士後學位。他的研究興趣廣泛，並在測量、遙感、地理計算和農業應用等領域發表了論文。他在數據科學、數字影像處理和建模方面擁有超過20年的豐富經驗，並應用多尺度、多學科、多光譜和多時序的概念在不同環境中進行研究。他的實驗場地包括巴西的熱帶雨林、大草原、濕地和農田。他的研究主要由CNPq、CAPES、FAPEMIG和FAPEMAT資助。多年來，他建立了一個龐大的研究項目組合，主要涉及應用和理論遙感，廣泛涉及植被覆蓋、植物疾病和氣候變化相關影響。

Luciana Sanches

Dr. Sanches畢業於巴西馬托格羅索聯邦大學的衛生工程學士學位，獲得了巴西米納斯吉拉斯聯邦大學的衛生、環境和水資源碩士學位，西班牙坎塔布里亞大學的道路工程、水利渠道和港口博士學位，巴西的環境物理學博士後學位，以及英國雷丁大學的環境科學博士後學位。她的教育背景還包括巴西馬托格羅索聯邦大學的職場安全工程研究生學位，以及巴西國家水資源管理局的市政水資源管理項目開發和管理研究生學位。她目前是巴西馬托格羅索聯邦大學的副教授，並在大氣-生物圈相互作用、各種時空尺度的水文氣象學研究中應用環境建模和遙感技術進行解釋。她一直在教學和研究活動中應用遙感技術，以支持對環境動態的解釋。