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Classifying Land Use/Land Cover Change Over Time Within the Watershed

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Classifying Land Use/Land Cover Change Over Time Within the Watershed CLASSIFYING LAND USE/LAND COVER CHANGE OVER TIME WITHIN THE WATERSHED BOUNDARY OF KEENJHAR LAKE USING SUPERVISED, UNSUPERVISED, AND HYBRID CLASSIFICATION METHODS by KATHERINE R. HENRY LUOHE NG HAN, COMMITTEE CHAIR HONGXING LIU JULIA CHERRY A THESIS Submitted in partial fulfillment of the requirements for the degree of Master of Science in the Department of Geography in the Graduate School of The University of Alabama TUSCALOOSA, ALABAMA 2021 Copyright Katherine Henry 2021 ALL RIGHTS RESERVED ABSTRACT This study determined the change of land use/land cover over time within the watershed boundary of Keenjhar Lake through the usage of remote sensing thematic classification methods, and, assessed if the changes occurring related to statements made in other studies about wetland and biodiversity decline. The three thematic classification methods utilized and compared in this study were the supervised, unsupervised, and hybrid classifications. Due to its higher overall accuracy, the supervised classification method was chosen to classify the March 07, 2020 Landsat 8 image and for post classifications from 1997 to 2002, 2002 to 2008, and 2002 to 2020. The results of this study did not support the hypotheses that there was a decline in wetland percent cover over time and that the hybrid classification was more accurate in comparison to other algorithms. The results did support the hypothesis that there was an increase in urban/agricultural land over time. The utilization of remote sensing in this study to assess land use/land cover did not indicate there was a decline in wetland size due to the 1998-2002 drought and other more recent droughts. For future studies, finer spatial resolution imagery is needed to further break down the land use/land cover classes and to determine minor changes that were not recognized in this study. ii ACKNOWLEDGEMENTS I would like to first off thank my family and friends for their never-ending support and encouragement throughout the development of this thesis. They have shown me nothing but support throughout my journey in college. I would also like to thank my undergraduate professor Dr. Dale Lightfoot at Oklahoma State University. Without him convincing and inspiring me, I never would have dropped pre-med halfway through my junior year and instead got double bachelor’s degrees in sociology and geography. My geography cowboy family at Oklahoma State University I owe dearly for making me fall in love with the discipline which led me to the University of Alabama to pursue my dream. I would also like to express my greatest thanks to Dr. Luoheng Han for his guidance and assistance as my committee chair. My committee members Dr. Hongxing Liu and Dr. Julia Cherry have greatly contributed to the development and improvement of my thesis and for that I am truly thankful. I would also like to express my thanks to Sabrina Anderson who helped me get my student license for ERDAS Imagine set up. iii CONTENTS ABSTRACT .................................................................................................................................... ii ACKNOWLEDGEMENTS ........................................................................................................... iii LIST OF TABLES ......................................................................................................................... vi LIST OF FIGURES ....................................................................................................................... ix INTRODUCTION .......................................................................................................................... 1 Purpose of Study ......................................................................................................................... 5 Hypotheses: ................................................................................................................................. 6 OBJECTIVES ............................................................................................................................... 11 BACKGROUND .......................................................................................................................... 13 Point Sources and Nonpoint Source Pollution .......................................................................... 13 Environmental Degradation of Keenjhar Lake ......................................................................... 15 Application of Supervised and Unsupervised Classification for Land Use/Land Cover.......... 21 Application of Hybrid Classification for Land Use/Land Cover in Semi-Arid Regions .......... 25 METHODOLOGY ....................................................................................................................... 27 Study Area ................................................................................................................................ 27 Process Methodology ................................................................................................................ 30 Processing and Analysis of Remote Sensing Data ................................................................... 31 iv Creating Land Use/Land Cover Maps Using Supervised Classification .................................. 48 Creating Land Use/Land Cover Maps Using Unsupervised Classification .............................. 52 Creating Land Use/Land Cover Maps Using Hybrid Classification ........................................ 54 Post Classification Change Detection Analysis ........................................................................ 56 Classifying and Post-Classification for November 01, 2008 .................................................... 57 Classifying and Post-Classification for March 07, 2020 .......................................................... 59 RESULTS/DISCUSSION............................................................................................................. 61 Supervised Classification .......................................................................................................... 61 Unsupervised Classification...................................................................................................... 70 Hybrid Classification ................................................................................................................ 78 Post-Classification for Landsat 4-5 Imagery ............................................................................ 86 Classifying and Post-Classification for November 01, 2008 .................................................... 90 Classifying and Post-Classification for March 07, 2020 .......................................................... 97 Transition Matrix for 1997 to 2002 ........................................................................................ 105 Transition Matrix for 2002 to 2008 ........................................................................................ 107 Transition Matrix for 2002 to 2020 ........................................................................................ 110 CONCLUSION ........................................................................................................................... 113 REFERENCES ........................................................................................................................... 118 APPENDIX ................................................................................................................................. 124 v LIST OF TABLES Table 1. GCPs and their RMS error for geometric correction of the Landsat 4-5 March 24, 1997 image. ................................................................................................................. 45 Table 2. GCPs and their RMS error for geometric correction of the Landsat 4-5 March 22, 2002 image. ................................................................................................................. 46 Table 3. GCPs and their RMS error for geometric correction of the Landsat 4-5 November 01, 2008 image. ........................................................................................................... 46 Table 4. GCPs and their RMS error for geometric correction of the Landsat 8 March 07, 2020 image. ................................................................................................................. 47 Table 5. Descriptions of the land use/land cover classes to be classified in this study are based upon the USGS land use classification system (Anderson et al. 1976). .. 50 Table 6. Timetable........................................................................................................................ 60 Table 7. Total percent (%) of each cover land use/land cover type within the watershed boundary of Keenjhar Lake on March 24, 1997 for the supervised classification. 64 Table 8. Overall classification accuracy and Kappa coefficient for within the watershed boundary of Keenjhar Lake on March 24, 1997 for the supervised classification. ........................................................................................................ 64 Table 9. Error matrix, producer accuracies, and user accuracies for the supervised classification of the Landsat 4-5 image of within Keenjhar Lake’s watershed boundary on March 24, 1997. ...................................................................................... 64 Table 10. Reference pixel totals and classified pixel totals for the supervised classification of the March 24, 1997 Landsat 4-5
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