Differentiating crested wheatgrass (agropyron cristatum) in saskatchewan landing provincial park, canada with remote sensing

ACKNOWLEDGEMENT First and foremost, I wish to express my endless thanks and gratefulness to my supervisor Dr Xulin Guo Her kind support and continuous advices went through the process of completion of my thesis at University of Saskatchewan I thank Saskatchewan Landing Provincial Park for their cooperation and support with this project in providing an ideal location for field data collection Moreover, I want to express my gratefulness to Ms Thuy Doan for her enthusiastic help in providing valuable documents Last but not least, I would like to give my special thanks to my parents for their endless love, care and having the mental assistance and motivation throughout my whole life Thai Nguyen, May 2020 TRAN HOANG SON iii TABLE OF CONTENT LIST OF FIGURES vi LIST OF ABBREVIATIONS viii CHAPTER I INTRONDUCTION 1.1 Rationale 1.2 Objectives CHAPTER II LITERATURE REVIEW 2.1 Remote sensing technique 2.1.1 Remote Sensing 2.1.2 Hyperspectral data 2.1.3 Reflectance 2.1.4 Wavelength 2.1.5 Vegetation Indices 2.2 Crested Wheatgrass characteristics CHAPTER III METHODS 10 3.1 Study area 10 3.2 Data collection 11 3.2.1 Instruments 11 3.2.2 Sampling Design 12 3.2.3 Ground hyperspectral data 15 3.3 Pre – processing 15 3.4 Data processing 16 3.4.1 Hyperspectral data analysis 16 iv 3.4.2 Vegetation Indices calculation 17 3.4.3 Hypothesis testing 19 CHAPTER IV: RESULTS AND DISCUSSION 20 4.1 Spectral characteristics of Crested Wheatgrass 20 4.2 The best vegetation indices to differentiate Crested Wheatgrass 21 4.3 The behavior of Crested Wheatgrass in different Grazing regimes 26 CHAPTER V CONCLUSION 32 5.1 Limitation and futher study 32 5.2 Conclusion 33 REFERENCES 34 APPENDIX A 41 APPENDIX B 44 v CHAPTER I INTRODUCTION 1.1 Rationale Non-native species are a threat to agricultural and native prairie communities around the world The existence of invasive species affected negatively on the native species population, crowding out the existence of native plants Invasive species are any species that not originate from that ecosystem and are capable of self-propagation, have introduced or likely caused harm to the environment and other factors (Pejchar and Mooney, 2009) Non-native species are also affected by climate change Predicted environmental changes, such as changes in rainfall and temperature, nutrient content and soil disturbance, may increase habitat sensitivity to non-native plants (Hufnagel and Garamvölgyi, 2014) When non-native plants invade the environment, they are able to overcome native plants through direct or indirect competition (Robert et al., 2013) A study by Driscoll et al (2014) shows that environmental weeds are non-native plants that establish in natural areas, often harming to the native plants, damage to ecosystem function and cost billions of dollars to manage each year Crested Wheatgrass (CW) (Agropyron cristatum) is known as a species that occupied – 11 million hectares of grassland in the North American Great Plains (DeLuca and Lesica, 1996) Crested Wheatgrass threatens native ecosystems, which are important reservoirs of biodiversity (Mooney and Drake, 1989; D’Antonio and Vitousek, 1992) This species impacts both fauna and flora (Sutter and Brigham, 1998; Heidinga and Wilson, 2002) They also affect nutrition and energy sources (Christian and Wilson, 1999) Non-native species are a threat to agricultural and native prairie communities around the world The existence of invasive species affected negatively on the native species population, crowding out the existence of native plants Invasive species are any species that not originate from that ecosystem and are capable of self-propagation, have introduced or likely caused harm to the environment and other factors (Pejchar and Mooney, 2009) Nonnative species are also affected by climate change Predicted environmental changes, such as changes in rainfall and temperature, nutrient content and soil disturbance, may increase habitat sensitivity to non-native plants (Hufnagel and Garamvölgyi, 2014) When non-native plants invade the environment, they are able to overcome native plants through direct or indirect competition (Robert et al., 2013) A study by Driscoll et al (2014) shows that environmental weeds are non-native plants that establish in natural areas, often harming to the native plants, damage to ecosystem function and cost billions of dollars to manage each year Crested Wheatgrass (CW) (Agropyron cristatum) is known as a species that occupied – 11 million hectares of grassland in the North American Great Plains (DeLuca and Lesica, 1996) Crested Wheatgrass threatens native ecosystems, which are important reservoirs of biodiversity (Mooney and Drake, 1989; D’Antonio and Vitousek, 1992) This species impacts both fauna and flora (Sutter and Brigham, 1998; Heidinga and Wilson, 2002) They also affect nutrition and energy sources (Christian and Wilson, 1999) 1.2 Objectives The purpose of this study is to see whether remote sensing can be an effective method for detecting Crested Wheatgrass in native mixed-grass prairies Until now, an effective method has not been developed to detect nonnative plants in mixed grassland ecosystems with medium-resolution imagery At an affordable cost, it will be suitable for resource managers to work with The objectives are: a Investigate the spectral characteristics of crested wheatgrass from ground hyperspectral data; b Find the best vegetation indices to differentiate Crested Wheatgrass; c Investigate the behavior of Crested Wheatgrass in different Grazing regimes CHAPTER II LITERATURE REVIEW 2.1 Remote sensing technique 2.1.1 Remote Sensing Remote sensing is the collection of information about an object or phenomenon that does not physically contact the object and is therefore the opposite of local observation In modern use, this term often refers to the use of aerial sensor technologies to detect and classify objects on Earth (both on the surface and in the atmosphere and oceans) by means of signal transmission (for example, electromagnetic radiation) It can be divided into active remote sensing (when the first signal is emitted from aircraft or satellites) or passively (for example, sunlight) when information is only recorded (Curran, 1985) Figure Remote sensing process (researchgate.net) An advanced image synthesis technique recently developed to provide a means to detect the structure and functional properties of invasive plants at different canopy levels is the integration of passive energy and actively collected at the same time by image spectrometer and scanning-waveform light detection and ranging system (LiDAR) (Huang and Gregory, 2009) A study by Ustin et al show map based on high spectral (224 10 nm bands) and spatial (/ spl sim / m) resolution spectra of several invasive species, including eggplant, jubata, fennel and giant reed from a range of habitats at Camp Pendleton and Vandenberg Air Force Base in California using AVIRIS data (2002) Through the advent and dissemination of imaging systems born in air and space, researchers have been able to measure the physical and chemical properties of surface geology of the earth and planets, monitoring changes in plant biomass of continents, monitoring global migration of water, measuring surface heat flux, visualizing deformation of the earth's surface due to human processes and nature and many other applications (Beasley and Barnhart, 2017) In the study of northern mixed-grass prairie in Canada, Zhou and Guo used SPOT-5 imagery to detect Crested Wheatgrass invasion The results of their study showed that a single-date SPOT-5 imagery with a resolution of 10 m would be useful in distinguishing CW from native species in mixed grasslands (2007) Using remote sensing can be a cost effective strategy to detect invasive weeds Historically, invasive species have often been identified by natural resource managers and volunteers who manually scouted (Shaw, 2005) 2.1.2 Hyperspectral data Hyperspectral data refers to the analysis and measurement of the reflection, transmission or absorption of electromagnetic radiation with very high spectral resolution (Lukas et al., 2018) According to Zebin et al., the large dimensions and mass and hundreds of contiguous spectral channels are characteristic of hyperspectral remote sensing images These images obtained from the Earth's surface contain a variety of information about space, radiation and spectrum, which helped a lot for researchers in analyzing, processing and monitoring information on the Earth's surface (2016) Hyperspectral remote sensing can form a ground surface reflection images at several hundred wavelengths simultaneously, with wavelengths ranging from 0.4 to 2.5 µm and spatial resolution 10 - 30m Applications of this technology include environmental monitoring and mineral exploration and mining The benefit of super spectral imagery is that many different objects and types of terrain can be characterized by their spectral signature (Lucas et al., 2000) The spectral information contained in hyperspectral images allows characterization, identification and classification of overlays with improved accuracy and certainty (Wang, 2019) Hyperspectral images are volumetric image cubes that consist of hundreds of spatial images Each spatial image, or spectral band, records the response of objects on the ground at a specific wavelength (Cheung and Antonio, 2009) Hyperspectral images contain large amounts of autocorrelation data Principal component analysis (PCA) is often used to solve this problem (Bartold, 2008; Olesiuk and Zagajewski, 2008; Zagajewski, 2010) 2.1.3 Reflectance Reflectance is the ratio of energy reflected with the total energy breakdown per body, expressed as a percentage An object appears green because it only reflects the wavelengths corresponding to green in the visible spectrum Therefore, blue objects absorb all light waves except blue-related objects, and so on Spectral reflectance is the ratio of reflected energy to incident radiation (ɸr/ɸ) as a function of the wavelength (Jain and Singh, 2003) Reflectance is typically measured with a specular reflectometer The reflectance of the sun mirror has a direct and powerful impact on thermal efficiency, because 1% reduction in reflectivity leads to a near 1% reduction in efficiency (Herrmann et al., 2017) Different types of reflectance can be defined respecting the direction of the reflection (specular, diffuse, or hemispherical reflectance) or to λ (spectral or solar-weighted reflectance) (García et al., 2017) 2.1.4 Wavelength Wavelengths are important for physical phenomena, while frequencies are connected to energy and are therefore greatly related to radiation transmission (Anne, 2019) Visible wavelengths (0.40 - 0.67 μm) electromagnetic radiation interacts with the outer electronic shell of transition metal ions in pigments and thermal infrared wavelengths (4 – 14 μm) emanating from objects on the Earth's surface interacting with ions linked to ions on the surface of the Earth interact with ions bound in crystalline lattices (Vincent, 2015) The shortest wavelengths are in the gamma, X-ray, and ultraviolet (UV) parts of the EM spectrum (William and Adriano, 2017) 2.1.5 Vegetation Indices The vegetation indices (VIs) obtained from canopy based on remote sensing is a fairly simple and effective algorithm for quantitative and quantitative SAVI MSAVI 190843279394677* 029139097730381 000 108758116616959 272928442172395 42 157649722545357* 025988653808802 000 084439395375720 230860049714995 * The mean difference is significant at the 0.05 level 43 APPENDIX B Multiple Comparisons Table (10 sites study) Multiple Comparisons Tukey HSD Dependent Variable (I) Code NDVI 058292991041983 019858501673780 103 -.005288310246190 121874292330156 040719811212641 019858501673780 565 -.022861490075532 104301112500814 060005114729675 019858501673780 082 -.003576186558498 123586416017848 -.039006106417781 019858501673780 625 -.102587407705954 024575194870392 -.044475549673604 019858501673780 434 -.108056850961778 019105751614569 44 45 10 RDVI -.006488840416655 011773027585746 1.000 -.044182742318209 46 031205061484899 47 10 SAVI 48 49 10 MSAVI 50 51 10 10 10 10 10 10 -.058842920865595 020229316659047 110 -.123611466775123 52 005925625043934 PSRI 53 54 10 * The mean difference is significant at the 0.05 level 55 ... Wheatgrass; c Investigate the behavior of Crested Wheatgrass in different Grazing regimes CHAPTER II LITERATURE REVIEW 2.1 Remote sensing technique 2.1.1 Remote Sensing Remote sensing is the collection... 1984 Grazing crested wheatgrass range in the Inter-mountain West Rangelands 6: 29-31 Figure1 Remote sensing process Source: https://www.researchgate.net/figure/Stages -in- a -remote- sensingprocess_fig2_316473726... remaining axis indicates Reflectance The main subject of the study is Crested Wheatgrass with gray curves Examining the spectral curve can provide insight into the spectral properties of Crested