Big Data Analytics for Satellite Image Processing and Remote Sensing

Big Data Analytics for Satellite Image Processing and Remote Sensing

P. Swarnalatha, Prabu Sevugan

Copyright: © 2018 |Pages: 253

ISBN13: 9781522536437|ISBN10: 1522536434|EISBN13: 9781522536444

DOI: 10.4018/978-1-5225-3643-7

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MLA

Swarnalatha, P., and Prabu Sevugan, editors. Big Data Analytics for Satellite Image Processing and Remote Sensing. IGI Global, 2018. https://doi.org/10.4018/978-1-5225-3643-7

APA

Swarnalatha, P. & Sevugan, P. (Eds.). (2018). Big Data Analytics for Satellite Image Processing and Remote Sensing. IGI Global. https://doi.org/10.4018/978-1-5225-3643-7

Chicago

Swarnalatha, P., and Prabu Sevugan, eds. Big Data Analytics for Satellite Image Processing and Remote Sensing. Hershey, PA: IGI Global, 2018. https://doi.org/10.4018/978-1-5225-3643-7

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The scope of image processing and recognition has broadened due to the gap in scientific visualization. Thus, new imaging techniques have developed, and it is imperative to study this progression for optimal utilization.

Big Data Analytics for Satellite Image Processing and Remote Sensing is a critical scholarly resource that examines the challenges and difficulties of implementing big data in image processing for remote sensing and related areas. Featuring coverage on a broad range of topics, such as distributed computing, parallel processing, and spatial data, this book is geared towards scientists, professionals, researchers, and academicians seeking current research on the use of big data analytics in satellite image processing and remote sensing.

Table of Contents

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Front Materials

Title Page

Copyright Page

Advances in Computer and Electrical Engineering (ACEE) Book Series

Foreword

Preface

Acknowledgment

Chapters

Chapter 1

New Computational Models for Image Remote Sensing and Big Data (pages 1-21)

Dhanasekaran K. Pillai

This chapter focuses on the development of new computational models for remote sensing applications with big data handling method using image data. Furthermore, this chapter presents an overview of the process of developing systems...

Chapter 2

Big Data Computation Model for Landslide Risk Analysis Using Remote Sensing Data (pages 22-33)

Venkatesan M., Prabhavathy P.

Effective and efficient strategies to acquire, manage, and analyze data leads to better decision making and competitive advantage. The development of cloud computing and the big data era brings up challenges to traditional data...

Chapter 3

Modified Support Vector Machine Algorithm to Reduce Misclassification and Optimizing Time Complexity (pages 34-56)

Aditya Ashvin Doshi, Prabu Sevugan, P. Swarnalatha

A number of methodologies are available in the field of data mining, machine learning, and pattern recognition for solving classification problems. In past few years, retrieval and extraction of information from a large amount of...

Chapter 4

An Analysis of Usage-Induced Big Data (pages 57-71)

Sameera K., P. Swarnalatha

With the predominance of administration registering and distributed computing, an ever-increasing number of administrations are developing on the internet, producing tremendous volume of information. The mind-boggling...

Chapter 5

Glorified Secure Search Schema Over Encrypted Secure Cloud Storage With a Hierarchical Clustering Computation (pages 72-98)

Shweta Annasaheb Shinde, Prabu Sevugan

This chapter improves the SE scheme to grasp these contest difficulties. In the development, prototypical, hierarchical clustering technique is intended to lead additional search semantics with a supplementary feature of making the...

Chapter 6

Research Analysis of Development Pipelines in Augmented and Virtual Reality Technologies (pages 99-116)

Pronay Peddiraju, P. Swarnalatha

The purpose of this chapter is to observe the 3D asset development and product development process for creating real-world solutions using augmented and virtual reality technologies. To do this, the authors create simulative software...

Chapter 7

Iterative MapReduce: i-MapReduce on Medical Dataset Using Hadoop (pages 117-132)

Utkarsh Srivastava, Ramanathan L.

Diabetes Mellitus has turned into a noteworthy general wellbeing issue in India. Most recent measurements on diabetes uncover that 63 million individuals in India are experiencing diabetes, and this figure is probably going to go up...

Chapter 8

Big Data for Satellite Image Processing: Analytics, Tools, Modeling, and Challenges (pages 133-150)

Remya S., Ramasubbareddy Somula, Sravani Nalluri, Vaishali R., Sasikala R.

This chapter presents an introduction to the basics in big data including architecture, modeling, and the tools used. Big data is a term that is used for serving the high volume of data that can be used as an alternative to RDBMS and...

Chapter 9

Big Data Processing: Application of Parallel Processing Technique to Big Data by Using MapReduce (pages 151-165)

Abhishek Mukherjee, Chetan Kumar, Leonid Datta

This chapter is a description of MapReduce, which serves as a programming algorithm for distributed computing in a parallel manner on huge chunks of data that can easily execute on commodity servers thus reducing the costs for server...

Chapter 10

Image Processing CSE-4019 Distinction Between Fake Note and a Real Note (pages 166-180)

Shreya Tuli, Gaurav Sharma, Nayan Mishr

Big data is a term for data sets that are so large or complex that traditional data processing application software is inadequate to deal with them. Its challenges include capturing data, data storage, data analysis, search, sharing...

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