Terrain Cover and Shadow Discrimination from Landsat Data of the Great Smoky Mountains National Park
Total Page:16
File Type:pdf, Size:1020Kb
University of Tennessee, Knoxville TRACE: Tennessee Research and Creative Exchange Masters Theses Graduate School 3-1981 Terrain Cover and Shadow Discrimination from Landsat Data of the Great Smoky Mountains National Park Vincent Gerard Ambrosia University of Tennessee - Knoxville Follow this and additional works at: https://trace.tennessee.edu/utk_gradthes Part of the Geography Commons Recommended Citation Ambrosia, Vincent Gerard, "Terrain Cover and Shadow Discrimination from Landsat Data of the Great Smoky Mountains National Park. " Master's Thesis, University of Tennessee, 1981. https://trace.tennessee.edu/utk_gradthes/1456 This Thesis is brought to you for free and open access by the Graduate School at TRACE: Tennessee Research and Creative Exchange. It has been accepted for inclusion in Masters Theses by an authorized administrator of TRACE: Tennessee Research and Creative Exchange. For more information, please contact [email protected]. To the Graduate Council: I am submitting herewith a thesis written by Vincent Gerard Ambrosia entitled "Terrain Cover and Shadow Discrimination from Landsat Data of the Great Smoky Mountains National Park." I have examined the final electronic copy of this thesis for form and content and recommend that it be accepted in partial fulfillment of the equirr ements for the degree of Master of Science, with a major in Geography. John B. Rehder, Major Professor We have read this thesis and recommend its acceptance: James R. Carter, Edwin H. Hammond Accepted for the Council: Carolyn R. Hodges Vice Provost and Dean of the Graduate School (Original signatures are on file with official studentecor r ds.) To the Graduate Council: I am submitting herewith a thesis written by Vincent Gerard Ambrosia entitled "Terrain Cover and Shadow Discrimination from Landsat Data of the Great Smoky Mountains National Park." I recommend that it be accepted in partial fulfillment of the requirements for the degree of Master of Science, with a major in Geography. �>ie have read this thesis and recomnend its acceptance: E.L.:.b{)J. <;) ..... • Accepted for the Council: £��6;3:! �-Vice- Chancellor-:-- Graduate Studies and Research TERRAIN COVER AND SHADOW DISCRIMINATION FROM LANDSAT DATA OF THE GREAT SMOKY HOUNTAINS NATIONAL PAH.K A Thesis Presented for the Master of Science Degree The University of Tennessee, Knoxville Vincent Gerard Ambrosia March 1981 ..., t�·-4()587 v•.... / -v " · Copyright by Vincent Gerard Ambrosia 1980 All Rights Reserved ACKNOWLEDGMENTS I am grateful for the assistance and guidance of Dr. John B. Rehder who helped di rect this project . The subject of my research was , in part , developed from hia suggestion that I investigate unique Landsat signatures . I also greatly appreciate the guidance of Dr . Edwin H. Hammond who , in Dr. John B. Rehder's absence, encouraged my research and helped me solidi fy my analysis techniques . I also appreciate the critical suggestions and encourage ment offered by Dr. James R. Carter. I appreciate the cooperation and continual support of my dear friend an d colleague , Dr. Benjamin F. Richason of Carroll College , Waukesha, Wisconsin . Without Professor Richason's continual encouragement through both my un der graduate and graduate careers , this project could not have been undertaken . I also wish to thank the computer science department staff members of Carroll College for their in valuable help. I would like to thank my parents for their help and guidance throughout my entire life, but particularly wh ile I attended The University of Tennessee, Knoxville . Without their continual help this work would have been greatly hin dered. I thank them for the strength they have given me to help me meet my goals. I sincerely hope I have fu lfilled their expectations . iii iv In the Department of Geography of The University of Tennessee , Knoxville, I appreciate the support and sugges tions of my fellow graduate students , particularly those of Thomas Maertens , Neal Cyganiak, and David Williams . Finally, I wish to thank my fiancee , Mary Ann Murray , for her understanding and encouragement during the research and writing of this project . Fo r her dedication in typing and correcting the numerous drafts of this thesis, I am most grateful . ABST��CT Landsat satellite imagery of the Great Smoky Mountains in East Tennessee and Western North Carolina exhibits dark tonal reflectances within the Blue Ridge physiographic province unlike any other reflectance patterns found on the remainder of the imagery . Repetitive, seasonal imagery indicate that these unique patterns are dynamic. There also appear to be definable, minute reflectance var iations wi thin the patterns themselves, indicating that there are nQ�erous factors accounting for the anomaly. Among the factors discussed are the cover characteristics of the red spruce ( picea rubens) and Fraser fir or southern balsam fir ( abies fraseri) , effects of topography , slope , aspect and ridge orientation, effects of solar angle and azimuth , and shadow zones . Data were collected for three test sites within the boundary of the Great Smoky Mountains National Park between January 1980 and October 1980. The selected areas were easily accessible a�d were studied in the field by the author. Landform charact�ristics were obtained from United States Geological Survey topographic maps of the region . Cover characteristics were obt ained from field research and from ancillan• data of the National Park Service , the Upl ands Research Laboratory , and the University of Tennessee Department of Forestry. v vi Landsat spectral data were analyzed in a two step method. The first step consisted of visual and photo-mechan ical enhancement techniques. This included obtaining Landsat image scenes from the Earth Resources Observations Systems Data Center ( EROS) . It was hoped that by utilizing numerous photo-processing techniques previously obscurred data could be enhanced, analyzed, an d classified. The second step consisted of applying a supervised computer classification program to a Landsat digital tape of the study area. The supervised classification program analyzes a Landsat scene on the basis of established train ing sites that correspond to known locations studied in the field. The computer classificat ion proved more adaptable to enhancing and class ifying discrete regions than did photo-mechan ical techniques. This study suggests that more research into the feasibility of utilizing Landsat multispectral data in areas of low accessibility or mountainous terrain needs to be developed. It also suggests that numerous factors influence scene spectral levels and that the best me ans of examining these factors is through computer classifications based on selected test sites . TABLE OF CONTENTS CHAPTER I. INTRODUCTION . 1 The Problem • 1 Study Area Characteri stics . 9 Location . 9 • Geology . 12 Vegetation Cover, Soils , an d Climatic Factors •• 14 • II . i-iETHODS OF ANALYSIS . 20 • Manual Techniques . 20 • Computer Techniques . 32 Minicomputer System • • 32 First Four-Band Transformation . 38 Band Cosine Trans formation . 41 Band Ratio Transformation • . 42 Band Sum Trans formation • . 43 Second Four-Band Trans formation • 44 Test Sites. 46 • • • 49 III. RESULTS . Manual Interpretation and Classification . • • • • • . 49 Computer Interpretation and Classification ••••• . 60 First Four-Band Transformation Results • • • • • • • • • • • • • 65 Band Ratio Transformation Results 72 vii viii CHAPTER PAGE III. (Continued) Band Sum Trans formation Results 73 Second Four-Band Transformation Results • • • • • • • • • • 86 IV. CONCLUSIONS AND RECOMMENDAT IONS • • • • 107 BIBLIOGRAPHY •• 111 VITA. • • • • . • • 120 LIST OF TABLES TABLE PAGE 1 • GSM77F2 Statistics • • • 71 2. First Band Sum Signature Limits •• 77 3. Single Band Sum Statistics .••• 80 4. Second Five Band Sum Statistics . 83 5 . Signature Limits for First Test: Second Four-Band Transformation •• 87 6 . Signature Limits for Second Test: Second Four-Band Transformation •• 89 7. Signature Limits for Third Test: Second Four-Band Transformation •• 92 8. Signature Limits for Fourth Test: Second Four-Band Transformation •• 95 9. Statistics for Fourth Test: Second Four-Band Trans formation . 97 10 . Accuracy of Manual and Computer Techniques • • • • • • • • • • • • • • • • • • 106 ix LIST OF FIGURES FIGURE PAGE 1. Dark-Toned Signat ure Patterns in the Higher Elevations of the Great Smoky Mountains National Park •••.••• 2 2. Location Map of the Great Smoky Mountains National Park and Vicinity . • • • . • 10 3. Topography of the Great Smoky Mountains National Park and Vicinity • • . • • 13 4 . Red Spruce and Fraser Fir Vegetation Along the Trail Leading From the Forney Ridge Parking Area to Clingmans Dome • • • • • • • • • 19 5. Landsat Scene E2692-151927, Band 7, 14 December 1976 •••••••• 22 6. Lands at Scene E2800-151457, Band 7, 1 April 1977 •••••••••• 23 7. Landsat Scene E2908-150927, Band 7, 18 July 1977 • • • • • • • • • • 24 8. Landsat Scene E5899-141427, Band 7, 4 October 1977 • • • • • •• 25 9. Landsat Scene E21178-150627, Band 7, 14 April 1978 ••.••••••••• 26 10 . Landsat Scene E30283-153247, Band 7, 13 December 1978 •••••••••• 27 11. Enlarged Landsat Scene E5899-141427, Band 7, 4 October 1977 • • • • • • • 30 12. A Section of the u.s.G.s. 1:62,500 Great Smoky Mountains ( East Half ) Topographic Map Identifying Some of the One Hundred Selecte d Ridges and Slopes • • . • • . 31 13. Circular Grid Plotting Slope Aspect Against Elevation . • • • • • • • • • 33 14. Circular Grid