Remote Sensing Satellite Image Acquisition Planning

119 Pages·2015·1.95 MB·English

by  Shufan Liu

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Theses and Dissertations
12-15-2014
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Shufan Liu
University of South Carolina - Columbia
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Liu, S.(2014). Remote Sensing Satellite Image Acquisition Planning: Framework, Methods and
Application. (Doctoral dissertation). Retrieved from https://scholarcommons.sc.edu/etd/2938
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REMOTE SENSING SATELLITE IMAGE ACQUISITION PLANNING:
FRAMEWORK, METHODS AND APPLICATION

By

Shufan Liu

Bachelor of Information Engineering
Wuhan University 2004

Master of Cartography and Geographic Information System
Wuhan University 2008

Submitted in Partial Fulfillment of the Requirements

For the Degree of Doctor of Philosophy in

Geography

College of Arts and Sciences

University of South Carolina

2014

Accepted by:

Michael E. Hodgson, Major Professor

Diansheng Guo, Committee Member

Sarah E. Battersby, Committee Member

Csilla Farkas, Committee Member

Lacy Ford, Vice Provost and Dean of Graduate Studies
© Copyright by Shufan Liu, 2014
All Rights Reserved.
ii
Acknowledgements
During my study in Department of Geography, University of South Carolina,
many people have helped me in different ways. I would like to express my sincere
gratitude to my advisor, Dr. Michael E. Hodgson for his guidance, patience,
encouragement, and endless support throughout my degree program. I am grateful to my
committee members, Dr. John R. Jensen, Dr. Diansheng Guo, Dr. Sarah E. Battersby, and
Dr. Csilla Farkas for their assistance and committee work.
I wish to especially thank my wife and best friend, Shiqing Zhao for her endless
love and encouragement. Lots of thanks give to my parents, my sister, my brother in law,
and my uncle for their continuous support and encouragement. My thanks also give to my
parents in law for their support and understanding. My relatives and friends in China and
the U.S. have been an integral part of my study here.
Additionally, I would like to acknowledge all of the faculty, staff, and my fellow
graduate students of the USC Geography department.

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Abstract
This dissertation explores the theories and methods of satellite remote sensing
image acquisition planning within a spatial temporal context. For many time sensitive
applications, such as disaster emergency response, timely acquisition of critical
information is the key to intelligent and effective decision making. Remote sensing plays
an important role in information collection for these time sensitive applications. Imagery
collected from hundreds of remote sensing satellite sensors offer accurate, frequent and
almost instantaneous data covering the Earth in a relatively short time. However,
determining which satellite sensors can provide an appropriated kind of imageries during
a restricted collection window for the analysis is problematic. Satellite image acquisition
planning is developed to solve the problem. In this research, we explore the design and
implementation of s spatial decision support system (SDSS) for satellite image
acquisition planning. A SDSS framework is proposed, and several novel models and
algorithms are developed to derive optimized satellite image acquisition solutions.
Chapter 2 describes the components of the framework; Chapter 3 and Chapter 4 present
several models including composite satellite image collection opportunities modeling,
collection opportunities evaluation model, and a spatial optimization model. Based on the
framework, models, and algorithm, Chapter 5 presents an application of satellite image
acquisition planning for tidally influenced salt marshes for vegetation mapping.
Collectively, this research provides a foundation for research and development towards
the satellite image acquisition planning.
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Table of Contents
Acknowledgements ............................................................................................................ iii
Abstract .............................................................................................................................. iv
List of Tables ................................................................................................................... viii
List of Figures .................................................................................................................... ix
CHAPTER 1 Introduction................................................................................................... 1
1.1 Introduction ............................................................................................................... 1
1.2 Dissertation Structure ................................................................................................ 3
CHAPTER 2 The SDSS Framework .................................................................................. 5
2.1 Overview ................................................................................................................... 5
2.2 SDSS Framework ...................................................................................................... 9
2.3 Databases ................................................................................................................. 10
2.4 GIS-based models ................................................................................................... 12
CHAPTER 3 Optimizing Large Area Coverage from Multiple Satellite Sensors ............ 18
Abstract ......................................................................................................................... 18
3.1 Introduction ............................................................................................................. 19
3.2 Background ............................................................................................................. 20
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3.3 Modeling the satellite image collection opportunities for a large area ................... 23
3.4 Modeling the best satellite image acquisition plan ................................................. 25
3.5 Solving the optimization problem ........................................................................... 27
3.6 Results ..................................................................................................................... 29
3.7 Conclusions ............................................................................................................. 31
CHAPTER 4 Satellite Image Acquisition Planning for Large Area
Disaster Emergency Response ...................................................................................... 43
Abstract ......................................................................................................................... 43
4.1 Introduction ............................................................................................................. 44
4.2 Background ............................................................................................................. 45
4.3 Methodology ........................................................................................................... 48
4.4 Results ..................................................................................................................... 54
4.5 Conclusion and Discussion ..................................................................................... 55
CHAPTER 5 Remote Sensing Image Acquisition Planning for Salt-Marsh Vegetation . 66
Abstract ......................................................................................................................... 66
5.1 Introduction ............................................................................................................. 67
5.2 Tide Prediction Stations and Data Description ....................................................... 72
5.3 Methodology ........................................................................................................... 72
5.4 Results ..................................................................................................................... 76
5.5 Conclusion ............................................................................................................... 78
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CHAPTER 6 Conclusions................................................................................................. 90
6.1 Summary of results.................................................................................................. 90
6.2 Future research ........................................................................................................ 92
References ......................................................................................................................... 94
Appendix A - Permission to Reprint ............................................................................... 108

vii
List of Tables
Table 3.1 Example high spatial resolution satellite sensors revisit frequency ................. 32
Table 3.2 Working assumptions of the application case ................................................... 33
Table 3.3 Example satellite image collection opportunity ................................................ 34
Table 4.1 Example EEIs and their minimum spatial/spectral resolution requirements .... 57
Table 5.1 Example satellite image collection opportunity on 07/08/2014 ....................... 80
Table 5.2 Tide prediction results of 07/08/2014 ............................................................... 81
Table 5.3 Working assumption variables .......................................................................... 82

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List of Figures
Figure 2.1 Sprague’s three-level framework for developing a SDSS ............................... 13
Figure 2.2 Amstrong and Densham’s architecture for a SDSS ........................................ 14
Figure 2.3 Proposed SDSS framework for remote sensing image acquisition planning .. 15
Figure 2.4 1:N relationship between satellite, sensor, and band in the database .............. 16
Figure 2.5 The primary tables used to support the satellite-sensor-band database ........... 17
Figure 3.1 Relatively large disaster impact area requires multiple satellite images
to be fully covered ............................................................................................................ 35
Figure 3.2 CIPS (small squares) as potential satellite pointing angles
representative points ......................................................................................................... 36
Figure 3.3 Basic flow of the optimization model ............................................................. 37
Figure 3.4 Algorithm structure for optimization model.................................................... 38
Figure 3.5 493 CIPS and 11 RCIPS representing the multitude of satellite
pointing angles for the study area ..................................................................................... 39
Figure 3.6 (a) Spatial coverage of the example satellite image collection opportunity.
(b) Spatial coverage detail of 143 daytime collection opportunities ................................ 40
Figure 3.7 Best three image collection plans derived from the optimization model ........ 41
Figure 3.8 Top three image collection plans derived from the optimization model, (a), (b)
and (c) represents #1, #2 and #3 solution in Figure 7 respectively. (d) shows the spatial
coverage of the first solution over 143 available image collection opportunities ............ 42
Figure 4.1 Satellite image requirements identification via Spatial/Spectral
resolution specification or EEI selection .......................................................................... 58
Figure 4.2 Multiple polygons are interpolated with points to derive RCIPS for
future collection opportunities prediction ......................................................................... 59
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