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Estimation of Scots Pine Defoliation by the Common Pine Sawfly (Diprion Pini L.) Using Multi-Temporal Radar Data

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Estimation of Scots Pine Defoliation by the Common Pine Sawfly (Diprion Pini L.) Using Multi-Temporal Radar Data Michigan Technological University Digital Commons @ Michigan Tech Dissertations, Master's Theses and Master's Dissertations, Master's Theses and Master's Reports - Open Reports 2011 Estimation of scots pine defoliation by the common pine sawfly (Diprion pini L.) using multi-temporal radar data Petri T. Latva-Käyrä Michigan Technological University Follow this and additional works at: https://digitalcommons.mtu.edu/etds Part of the Forest Sciences Commons Copyright 2011 Petri T. Latva-Käyrä Recommended Citation Latva-Käyrä, Petri T., "Estimation of scots pine defoliation by the common pine sawfly (Diprion pini L.) using multi-temporal radar data", Master's Thesis, Michigan Technological University, 2011. https://doi.org/10.37099/mtu.dc.etds/148 Follow this and additional works at: https://digitalcommons.mtu.edu/etds Part of the Forest Sciences Commons ESTIMATION OF SCOTS PINE DEFOLIATION BY THE COMMON PINE SAWFLY (DIPRION PINI L.) USING MULTI-TEMPORAL RADAR DATA By Petri T. Latva-Käyrä A THESIS Submitted in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE Forestry MICHIGAN TECHNOLOGICAL UNIVERSITY 2011 © 2011 Petri T. Latva-Käyrä This thesis, “Estimation of Scots pine defoliation by the Common pine sawfly (Diprion pini L.) using multi-temporal radar data” is hereby approved in partial fulfillment of the requirements for the Degree of MASTER OF SCIENCE IN FORESTRY. School of Forest Resources and Environmental Science Signatures: Thesis Advisor ______________________________________ Assistant Professor Michael Falkowski Thesis Co-Advisor ______________________________________ Adjunct professor Markus Holopainen Dean ______________________________________ Margaret Gale Date ____________________________________ TABLE OF CONTENTS LIST OF FIGURES ............................................................................................................ v LIST OF TABLES ............................................................................................................. vi ACKNOWLEDGEMENTS .............................................................................................. vii LIST OF ABBREVIATIONS .......................................................................................... viii ABSTRACT ....................................................................................................................... ix 1. INTRODUCTION .......................................................................................................... 1 1.1. Background .............................................................................................................. 1 1.2. Study object ............................................................................................................. 2 1.3. Assessment of defoliation ........................................................................................ 4 1.4. Remote sensing in insect damage recognition ......................................................... 6 1.5. Radar images in forestry .......................................................................................... 9 1.6. Research questions and objectives ......................................................................... 13 2. METHODS ................................................................................................................... 14 2.1. Study area............................................................................................................... 14 2.2. Field data ................................................................................................................ 15 2.3. Remote sensing data .............................................................................................. 20 2.4. Testing individual image features .......................................................................... 22 2.5. Defoliation classification ....................................................................................... 24 2.5.1. Supervised classification ................................................................................. 24 2.5.2. Unsupervised classification ............................................................................ 25 2.5.3. Logistic regression .......................................................................................... 26 2.6. Accuracy assessment ............................................................................................. 27 3. RESULTS ..................................................................................................................... 29 iii 3.1. Individual SAR features ......................................................................................... 29 3.2. Supervised classification ........................................................................................ 30 3.3. Unsupervised classification ................................................................................... 33 3.4. Logistic regression ................................................................................................. 35 4. DISCUSSION ............................................................................................................... 39 4.1. Starting point of the study ...................................................................................... 39 4.2. Classification of defoliation and fellings ............................................................... 39 4.3. Speckle filtering ..................................................................................................... 42 4.4. Limitations and usability of the method ................................................................ 43 4.5. Comparing SAR and other remote sensing tools ................................................... 45 5. CONCLUSIONS........................................................................................................... 49 6. REFERENCES ............................................................................................................. 51 iv LIST OF FIGURES Figure 2.1 Location of the study area ....................................................................... 14 Figure 2.2 Palokangas area and the sample plots ...................................................... 15 Figure 2.3 Defoliation distribution of sample plots .................................................. 18 Figure 2.4 The effect of speckle filtering on SAR images ....................................... 23 Figure 3.1 Individual 5x5 pixel window image features against defoliation ............ 31 Figure 3.2 The accuracy of the estimation with k-means an lda methods ................ 34 Figure 3.3 Kappa values of the estimation with k-means and lda methods .............. 35 Figure 3.4 The accuracy of the estimation using different methods and 2 classes ... 37 Figure 3.5 Kappa values of the estimation using different methods and 2 classes ... 38 v LIST OF TABLES Table 2.1 Sample plot characteristic . ..................................................................... 17 Table 2.2 Class combinations and distributions of sample plots in them ............... 19 Table 2.3 Parameters of the SAR instruments ........................................................ 20 Table 2.4 Image acquisition dates ........................................................................... 21 Table 2.5 Interpretation of the kappa statistic ......................................................... 28 Table 3.1 Coefficients of determination and correlation for individual features .... 29 Table 3.2 Classification accuracies and kappa values for LDA method ................. 32 Table 3.3 Classification accuracies and kappa values for k-means method ........... 33 Table 3.4 Classification accuracies and kappa values for logistic regression method...................................................................................................... 37 Table 4.1 Summary of studies made about defoliation classification as well as pros and cons of each remote sensing material................................................ 47 vi ACKNOWLEDGEMENTS I would like to thank both of my advisors, Mike Falkowski from Michigan Technological University and Markus Holopainen from the University of Helsinki, and my committee (Andrew Storer and Simon Carn) in Michigan Tech. I would like to thank also those from University of Helsinki that have helped me during this process, Päivi Lyytikäinen-Saarenmaa, Mika Karjalainen and especially Tuula Kantola who has helped me a great deal during this project. Extra thanks for Päivi for the collection of the field data and for sharing it. Also, I thank Tornator Ltd. for providing data for this study and making this and other studies possible. Finally, I thank my family and all the great friends from two different continents who have supported me and have made my time in the US unforgettable. vii LIST OF ABBREVIATIONS ACS Adaptive Cluster Sampling ALS Airborne Laser Scanning ENVISAT Environmental Satellite ERS European Remote Sensing ESA European Space Agency ETM Enhanced Thematic Mapper glm generalized linear model H Horizontal JERS Japanese Earth Resource Satellite kNN k-Nearest Neighbor LAI Leaf Area Index LDA Linear Discriminant Analysis LiDAR Light Detection and Ranging MSS Multi-Spectral Scanner NDMI Normalized Difference Moisture Index NDVI Normalized Difference Vegetation Index PCA Principal Component Analysis Radar Radio Detection and Ranging RAR Real Aperture Radar RMSE Root Mean Square Error RVI Ratio Vegetation Index SAR Synthetic
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