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Use of space-based night-time light data for societal and environmental applications Use of space-based night-time light data for societal and environmental applications (Softcopy is also available)

By: Contributor(s): Material type: TextTextPublication details: 2021Description: xxi,54pDDC classification:
  • MG TH-0223 SHA
Contents:
Contents Certificate of original authorship vii Certificate of Dissertation Advisor’s consent iii Certificate of Internship v Acknowledgments vii Abstract ix List of figures xi List of tables xv 1 Chapter 1: Introduction 1 1.1 Introduction 1 1.2 Background 2 1.3 Research Identification 3 1.4 Objectives of the Study 4 1.5 Thesis Outline 4 2 Chapter 2: Literature Review 5 2.1 Brief about Remote Sensing 5 2.2 Night-Time Light Remote Sensing (NLRS) 6 2.3 Overview & Brief of Major NTL Datasets 6 2.3.1 DMSP-OLS 7 2.3.2 Suomi NPP-VIIRS 9 2.3.3 Other Satellites 10 2.4 Applications associated with Nighttime Light Remote Sensing 11 2.4.1 Socioeconomic Activities 12 2.4.2 Urbanization and regional development 12 2.4.3 Energy and Greenhouse Gas 12 2.4.4 Disasters and conflicts 13 2.4.5 Fisheries 13 2.5 Power Sector of India 14 3 Chapter 3: Working Methodology 17 3.1 Methodology Workflow 17 3.2 Study Area 19 3.3 Data Used 21 3.4 Data Pre-Processing 24 3.4.1 Masking Based on Low Cloud-Free Coverages 24 3.4.2 Masking based on low average radiance 25 4 Chapter 4: Results and Discussions 27 4.1 Spatio-Temporal Analysis of changes in luminosity using satellite-derived Night-Time light data for the year 2012 to 2020 27 4.1.1 Generation of Radiance Images 27 4.1.2 Generation of Colourized Difference Images 28 4.2 Deriving Remote Sensing based Index 31 4.2.1 Space Value Index (SVI) 31 4.2.2 Population Density of India 33 4.2.3 Regression between Space Value & Population Density 34 4.3 Dimming of Lights during Covid-19 Pandemic 35 4.3.1 Generation of Radiance Images 35 4.3.2 Generation of Colourized Difference Images of India 36 4.3.3 Generation of Colourized Difference Images of different cities 37 4.4 Impact on fossil fuel-driven CO2 emissions (environmental emissions) from Thermal Power Plants during Covid-19 Pandemic 40 5 Chapter 5: Conclusions & Recommendations 43 5.1 Conclusions 43 5.2 Limitations & Recommendations 44 References xlvii Appendix 1: Space Value Index (Year 2020) li Appendix 2: Population Density of India (Census 2021) lii Plagiarism Report Copy 53
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Thesis CEPT Library Faculty of Technology MG TH-0223 SHA Not For Loan 023723
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Contents
Certificate of original authorship vii
Certificate of Dissertation Advisor’s consent iii
Certificate of Internship v
Acknowledgments vii
Abstract ix
List of figures xi
List of tables xv
1 Chapter 1: Introduction 1
1.1 Introduction 1
1.2 Background 2
1.3 Research Identification 3
1.4 Objectives of the Study 4
1.5 Thesis Outline 4
2 Chapter 2: Literature Review 5
2.1 Brief about Remote Sensing 5
2.2 Night-Time Light Remote Sensing (NLRS) 6
2.3 Overview & Brief of Major NTL Datasets 6
2.3.1 DMSP-OLS 7
2.3.2 Suomi NPP-VIIRS 9
2.3.3 Other Satellites 10
2.4 Applications associated with Nighttime Light Remote Sensing 11
2.4.1 Socioeconomic Activities 12
2.4.2 Urbanization and regional development 12
2.4.3 Energy and Greenhouse Gas 12
2.4.4 Disasters and conflicts 13
2.4.5 Fisheries 13
2.5 Power Sector of India 14
3 Chapter 3: Working Methodology 17
3.1 Methodology Workflow 17
3.2 Study Area 19
3.3 Data Used 21
3.4 Data Pre-Processing 24
3.4.1 Masking Based on Low Cloud-Free Coverages 24
3.4.2 Masking based on low average radiance 25
4 Chapter 4: Results and Discussions 27
4.1 Spatio-Temporal Analysis of changes in luminosity using satellite-derived Night-Time light data for the year 2012 to 2020 27
4.1.1 Generation of Radiance Images 27
4.1.2 Generation of Colourized Difference Images 28
4.2 Deriving Remote Sensing based Index 31
4.2.1 Space Value Index (SVI) 31
4.2.2 Population Density of India 33
4.2.3 Regression between Space Value & Population Density 34
4.3 Dimming of Lights during Covid-19 Pandemic 35
4.3.1 Generation of Radiance Images 35
4.3.2 Generation of Colourized Difference Images of India 36
4.3.3 Generation of Colourized Difference Images of different cities 37
4.4 Impact on fossil fuel-driven CO2 emissions (environmental emissions) from Thermal Power Plants during Covid-19 Pandemic 40
5 Chapter 5: Conclusions & Recommendations 43
5.1 Conclusions 43
5.2 Limitations & Recommendations 44
References xlvii
Appendix 1: Space Value Index (Year 2020) li
Appendix 2: Population Density of India (Census 2021) lii
Plagiarism Report Copy 53

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