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Airborne Multispectral Imagery for Classification Of AIRBORNE MULTISPECTRAL IMAGERY FOR CLASSIFICATION OF INTERTIDAL HABITAT, FRASER RIVER, BRITISH COLUMBIA by JENNIFER ANTHEA AITKEN B. A., Geography, The University of Texas, 1990 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE STUDIES Department of Oceanography We accept this thesis as conforming to the required standard THE UNIVERSITY OF BRITISH COLUMBIA December 1994 © Jennifer Anthea Aitken, 1994 In presenting this thesis in partial fulfilment of the requirements for an advanced degree at the University of British Columbia, I agree that the Library shall make it freely available for reference and study. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by the head of my department or by his or her representatives. It is understood that copying or publication of this thesis for financial gain shall not be allowed without my written permission. Department The Universitty of British Columbia \ Vancouver, Canada Date DE-6 (2/88) ABSTRACT In intertidal environments, complex vegetation associations, hydrodynamics, and substrate variabilities make accurate mapping and monitoring difficult. Airborne multispectral imaging systems offer a synoptic view with the advantage of programmable handset selection in the visible and near infrared (NIR), increased spatial resolution compared to satellite imaging systems and greater spectral resolution compared with aerial photographs. Eight flight lines of image data of an island marsh complex in the Main Arm of the Fraser River, British Columbia were collected on June 19, 1992 with a Compact Airborne Spectrographic Imager (CASI). An eleven channel handset was configured in the visible and NIR with a spatial resolution (pixel size) of 3.5 m^. Spectral signatures of dominant vegetation communities (forest, willow, cattail, sedge, bulrush) and tidal flat, drift logs and necrotic biomass were generated from the image and used in a supervised classification to produce a habitat map. Close coexistence and similar spectral response complicated differentiation of sedge and cattail. Vertical growth of bulrush increased contribution of soil background and affected spectral response. The vegetation index (NIR-red/NIR+red) was found to be insufficient in estimating green biomass in areas containing a high percentage of necrotic biomass or silt covered vegetation. ii Results of the classification are presented in an error matrix. Vegetation communities and substrate classify 70%-82% correct, individual training areas 61% to 89% correct. Lower accuracies were found in mixed sedge communities (70%) and the dead biomass class (74%). Nonvegetated areas (tidal flat and drift logs) exhibit the most distinct spectral response, 81% and 82% correct. Two surveys of the marsh were conducted on foot in Ladner Marsh in spring and summer to field test the classified map. Fourteen sites were visited, of which three indicated some degree of misclassification, providing a field test accuracy of 78%. Spatial accuracy is determined by an overlay of GPS-referenced ground truth with the classified map. Spatial agreement between cattail, sedge and bulrush ground truth was 20.4 m., 14.4 m., and 53.5 m. respectively. Sedge had the greatest number of classified pixels and bulrush the least, suggesting the influence of population size in the agreement. Poor geometric rectification of imagery degraded agreement. iii TABLE OF CONTENTS ABSTRACT ii TABLE OF CONTENTS iv LIST OF TABLES v LIST OF FIGURES vi ACKNOWLEDGMENTS viii 1. INTRODUCTION 1 2. THE SOUTH ARM ESTUARY 6 2.1 Historical Development 6 2.2. Physical Environment 10 3. HABITAT CLASSIFICATION SCHEME 12 3.1 Vegetation Communities 12 3.1.1. Floodplain forest 12 3.1.2. Willow 12 3.1.3. Cattail 13 3.1.4 Sedge 14 3.1.5. Bulrush 14 3.2. Tidal flats 15 3.3. Drift logs 15 3.4. Dead biomass 16 4. DATA COLLECTION 17 4.1. Flight Parameters and Instrument Bandset 17 4.2. Image Geocorrection and Registration 22 4.3. Ground Truth 23 5. ANALYSIS OF MULTISPECTRAL IMAGERY 25 5.1. Spectral response patterns 25 5.2. Spectral response generation 33 5.3. Classification signatures 35 6. RESULTS and DISCUSSION: MAP ACCURACY 44 6.1. The Error Matrix 44 6.2 Field Test of Classified Map, Spring and Summer 48 6.3 The Vegetation Index 51 6.4. Spatial Agreement with Spatially Referenced Ground Truth 53 7. SUMMARY AND CONCLUSIONS 58 BIBLIOGRAPHY 60 APPENDIX A: TERMS 65 APPENDIX B: CASI OVERVIEW 69 iv LIST OF TABLES Table page 1. CASI image bandset for wetland habitat mapping, June 1993. The instrument is calibrated for vegetation discrimination with several narrow bands in the visible and near infrared. The flight parameters are designed for large scale mapping, approximately 1:5000 18 2. Spectral relationships relevant to the NIR:red ratio for vegetation biomass estimates. All relationships result in a high contrast ratio, diminishing the effectiveness of the ratio for green biomass estimation 30 3. Error matrix for training areas used in supervised classi• fication. The user accuracy is the probability that a site visited in the field is actually correctly classed. Producer accuracy is the probability that a reference sample is correctly classed in the map. Values are given in pixels; one pixel = 3.5 meters 45 4. Spatial agreement between classified image and GPS referenced ground survey positions of cattail 54 5. Spatial agreement between classified image and GPS referenced ground survey positions of sedge grass 55 6. Spatial agreement between classified image and GPS referenced ground survey positions of bulrush 56 v LIST OF FIGURES Figure page 1 Map showing the South Arm Estuary, Fraser River, British Columbia. The South Arm Estuary includes Ladner Marsh, Kirkland, Rose, Duck, Gunn and Barber Islands 7 2 Map of the Fraser River foreshore, 1827, prior to the natural development of the South Arm Estuary. (From Tamburi and Hays 1978) 8 3. Map of the Fraser River foreshore, 1860, when Sea Reach was still the main navigation channel. Woodward Reach was developed as the main navigation channel in 1922. (From Tamburi and Hays 1978) 9 4. Image mosaic of the South Arm Estuary, June 1992. Image bands displayed are 6 (658-670 nm), 3 (545- 556 nm), and 1 (450-503) 19 5. Spectral response of healthy green vegetation in the visible, near infrared and mid infrared regions of the electromagnetic spectrum. CASI is sensitive to the 403-913 nm, or .403- .913 urn. Visible spectrum response of vegetation is dominated by leaf pigments, particularly chlorophyll, near infrared response determined primarily by cell structure, and mid infrared spectrum response related to moisture content 27 6. Spectral response of sand of different degrees of moisture saturation. The Fraser River is a sand dominated river. An increase in moisture decreases reflectance in the visible, near infrared and mid infrared. Water absorption bands are seen at 1.4 urn and 1.9 urn in the mid infrared. (Note CASI sensitivity range of .403-.913 u,m) 31 VI LIST OF FIGURES (CON'T) Figure page 7. Spectral response of vegetation categories. Note categories represent vegetation communities dominated by a single species. Categories contain the effects of intermixed and adjacent vegetation and / or soil and water backgrounds 36 8. Spectral response of dead biomass and non vegetated areas. Drift logs and tidal flats show a high reflectance in the visible. The low NIR response of tidal flat areas is attributed to potholed water or adjacent water body. Dead biomass has a form similar to vegetation, but exhibits a depressed chlorophyll peak and a much lower NIR response 37 9. Spectral response of cattail and sedge communities. A total of 11 cattail and sedge samples were examined and the most well defined difference is a lower visible and higher NIR response for cattail respective to sedge 39 10. Supervised classification results for cattail and sedge illustrating differentiation, despite similar spectral response 40 11. Supervised classification results for South Arm Estuary, Fraser River British Columbia. All habitat classes are represented 42 12. Sites visited in Ladner Marsh for field test of classified map, spring and summer 49 13. Vegetation index for Ladner Marsh (NIR-red)/(NIR+red). NIR bands=10,l 1 and red=bands 7,8 52 vii ACKNOWLEDGMENTS The author would like to express gratitude to Dr. P.H. LeBlond who provided advice, encouragement and funds for field work; to Dr. Gary Borstad and Borstad Associates for providing image data and invaluable expertise; and to Dr. Peter Murtha for use of the FIRMS laboratory, an oasis for orphaned remote sensers. Many thanks to the Department of Fisheries and Oceans and the Canadian Wildlife Service for initiating this project under the Fraser River Environmental Innovations Program (EIP). The author especially wishes to thank Dr. Alexander P. Aitken. viii I. INTRODUCTION The Fraser River of British Columbia is one of the richest salmon streams in the world and supports a multitude of bird species in the path of the Pacific fly way. From its headwaters in the northern Rocky Mountains of British Columbia the Fraser River flows to the Strait of Georgia. Where the river water mixes with the saline tidal waters of the Pacific there exists the Fraser River delta, of which 2813 hectares is estuarine marsh (Ward et al. 1992). Urban, industrial, and residential development in the Fraser River delta began 150 years ago and is expected to continue in the future. To best manage the Fraser River's natural estuarine resources, fish and wildlife agencies require an accurate and up to date inventory of key wildlife and fisheries habitat. Large, difficult to access areas of marsh must be mapped in detail (approximately 1:5,000 scale), and frequently updated via a precise and efficient monitoring method. Wetlands are difficult areas to map using remotely sensed data due to hetereogeneity in the environment.
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