Multi-Sensor and Multi-Temporal Remote Sensing: Specific Single Class Mapping

This book brings consolidated information in the form of fuzzy machine and deep learning models for single class mapping from multi-sensor multi-temporal remote sensing images at one place. It provides information about capabilities of multi-spectral and hyperspectral images, importance of dimensionality reduction, various spectral and texture-based indices, single, dual, or multi-sensor temporal sensor concepts, fuzzy machine learning models capable for single class mapping and associated deep learning-based models supported by case studies.

Provides detailed exposition to (hyperspectral and multispectral) remote sensing and related image processing, fuzzy set theoretic image processing and deep learning methods

Focusses on use of single, dual, multi-sensor multi-temporal data application for specific single class mapping

Reviews pre-processing of multi-sensor multi-temporal remote sensing data set and hyperspectral data set

Discusses both traditional machine learning and deep learning approaches

Includes case studies from crop mapping, forest species mapping, and stubble burnt paddy fields

This book is aimed at researchers and graduate students in remote sensing, image processing, environmental engineering, geomatics, and geoinformatics.

本書將模糊機器學習和深度學習模型的結合，提供了一個地方來進行多傳感器多時序遙感影像的單類別映射的綜合信息。它提供了關於多光譜和高光譜影像的能力、降維的重要性、各種基於光譜和紋理的指標、單一、雙重或多傳感器時序傳感器概念、用於單類別映射的模糊機器學習模型以及相關的基於深度學習的模型的信息，並支持案例研究。

提供了對（高光譜和多光譜）遙感和相關影像處理、模糊集理論影像處理和深度學習方法的詳細闡述。

專注於使用單一、雙重、多傳感器多時序數據應用於特定單類別映射。

回顧了多傳感器多時序遙感數據集和高光譜數據集的預處理。

討論了傳統機器學習和深度學習方法。

包括了作物映射、森林物種映射和燒稻田的案例研究。

本書針對遙感、影像處理、環境工程、測繪學和地理信息學等領域的研究人員和研究生。

Anil Kumar is a scientist/engineer "SG" and the head of photogrammetry and remote sensing department of Indian Institute of Remote Sensing (IIRS), ISRO, Dehradun, India. He received his B.Tech degree in civil engineering from IET affiliated to the University of Lucknow, India, and M.E. degree as well as Ph.D in soft computing from the Indian Institute of Technology, Roorkee, India. So far, he has guided eight PhD thesis and eight more are in progress. He has also guided several dissertations of MTech, MSc, BTech, and postgraduate diploma courses. He always love to work with PhD scholars, Master and Graduate students for their research work, and motivate them to adopt research oriented professional carrier. He received the Pisharoth Rama Pisharoty award for contributing state of the art fuzzy based algorithms for earth observation data. His current research interests are in the area of soft computing based machine learning, deep learning for single date and temporal multi-sensor remote sensing data for specific class identification and mapping through in-house development of the SMIC tool. He also works in the area of digital photogrammetry, GPS/GNSS, and LiDAR. He is the author of book 'Fuzzy Machine Learning Algorithms for Remote Sensing Image Classification' with CRC Press.

PriyadarshiUpadhyay is working as a Scientist/ Engineer in Uttarakhand Space Application Centre (USAC), Department of Information & Science Technology, Government of Uttarakhand, Dehradun, India. He received his BSc and Msc degree in Physics from Kumaun University, Nainital, India. He completed his M-Tech degree in Remote Sensing from Birla Institute of Technology Mesra, Ranchi, India. He completed his Ph.D. in Geomatics Engineering under Civil Engineering from IIT Roorkee, India. He has guided several graduate and post graduate dissertations in the application area of image processing. He has various research paper in SCI listed peer reviewed journals. He has written book on 'Fuzzy Machine Learning Algorithms for Remote Sensing Image Classification' with CRC Press. His research areas are related to application of time series remote sensing, soft computing, machine learning algorithm for specific land cover extraction. He is a life member of 'Indian Society of Remote Sensing' and an associate member of 'The Institution of Engineers, India'.

Uttara Singh an alumna from the University of Allahabad, Prayagraj, is presently working as an Assistant Professor at CMP Degree College, University of Allahabad based in Prayagraj, Uttar Pradesh. Though being a native of U.P., she has travelled far and wide. She has contributed to numerous national and international publications, but her interests lie mainly in urban planning issues and synthesis. She is a life member of several academic societies of repute. She has also guided many PG and UG project dissertations and guiding Post-Doctoral research. Presently she is also holding the office as the course coordinator for ISRO's sponsored EDUSAT Outreach program for learning Geospatial Techniques and course coordinator for soft skill development programs in the same field in Prayagraj.

Anil Kumar是印度遙感研究所（IIRS）的科學家/工程師“SG”，並擔任遙感測量和遙感部門的負責人。他在印度Dehradun的ISRO（印度太空研究組織）的印度遙感研究所（IIRS）獲得了土木工程學士學位，並在印度羅爾基爾的印度理工學院獲得了碩士和博士學位。到目前為止，他指導了八個博士論文，還有八個正在進行中。他還指導了多個碩士、學士和研究生文憑課程的論文。他喜歡與博士研究生、碩士和研究生合作進行研究工作，並鼓勵他們選擇以研究為導向的職業生涯。他因為為地球觀測數據貢獻了最先進的模糊算法而獲得了Pisharoth Rama Pisharoty獎。他目前的研究興趣是基於軟計算的機器學習，深度學習用於單一日期和時間多傳感器遙感數據的特定類別識別和映射，通過內部開發的SMIC工具。他還從事數字攝影測量、GPS/GNSS和LiDAR領域的研究。他是CRC Press出版的書籍《模糊機器學習算法用於遙感圖像分類》的作者。

PriyadarshiUpadhyay在印度德拉敦的Uttarakhand Space Application Centre（USAC）擔任科學家/工程師，該中心隸屬於Uttarakhand政府的信息和科學技術部。他在印度Nainital的Kumaun大學獲得了物理學學士和碩士學位。他在印度Ranchi的Birla理工學院完成了遙感碩士學位。他在印度羅爾基爾的印度理工學院完成了土木工程的測繪工程博士學位。他指導了多個研究生和碩士論文，涉及圖像處理應用領域。他在SCI收錄的同行評審期刊上發表了多篇研究論文。他與CRC Press合作撰寫了關於《模糊機器學習算法用於遙感圖像分類》的書籍。他的研究領域涉及時間序列遙感應用、軟計算、機器學習算法用於特定土地覆蓋提取。他是“印度遙感學會”的終身會員，也是“印度工程師學會”的副會員。

Uttara Singh畢業於印度Prayagraj的Allahabad大學，目前在Uttar Pradesh的Prayagraj的CMP Degree College擔任助理教授。儘管她是U.P.的本地人，但她遊歷過很多地方。她對城市規劃問題和綜合研究特別感興趣，並為許多國內外出版物做出了貢獻。她是幾個有聲望的學術社團的終身會員。她還指導了許多研究生和本科項目論文，並指導博士後研究。目前，她還擔任ISRO贊助的EDUSAT Outreach計劃的課程協調員，該計劃旨在學習地理空間技術，並擔任Prayagraj相同領域軟技能發展計劃的課程協調員。