mapping nonnative plants using hyper spectral imagery emma underwood susan ustin deanne dipietro
TRANSCRIPT
![Page 1: Mapping nonnative plants using hyper spectral imagery Emma Underwood Susan Ustin Deanne Dipietro](https://reader036.vdocuments.net/reader036/viewer/2022062423/56649d095503460f949daaa5/html5/thumbnails/1.jpg)
Mapping nonnative plants using hyper spectral imagery
Emma UnderwoodSusan Ustin
Deanne Dipietro
![Page 2: Mapping nonnative plants using hyper spectral imagery Emma Underwood Susan Ustin Deanne Dipietro](https://reader036.vdocuments.net/reader036/viewer/2022062423/56649d095503460f949daaa5/html5/thumbnails/2.jpg)
Outline
Introduction Methodology Results Discussion Conclusions
![Page 3: Mapping nonnative plants using hyper spectral imagery Emma Underwood Susan Ustin Deanne Dipietro](https://reader036.vdocuments.net/reader036/viewer/2022062423/56649d095503460f949daaa5/html5/thumbnails/3.jpg)
Introduction
Nonnative plants : are plants that have been introduced in to the environment intentionally or accidentally by human activity.
Threaten - global diversity - ecosystem functioning
Pimentel et al (2000) estimated that 50,000 invasive species have been introduced into the U.S. causing economic losses of $137 billion per year; approximately $35 billion annual cost for plant invasions alone.
![Page 4: Mapping nonnative plants using hyper spectral imagery Emma Underwood Susan Ustin Deanne Dipietro](https://reader036.vdocuments.net/reader036/viewer/2022062423/56649d095503460f949daaa5/html5/thumbnails/4.jpg)
The global extent and rapid increase in invasive species is recognized as a primary cause of global biodiversity loss.
Nowhere is the ecological threat more clearly seen than in California where more than 1025 plant species have been added to the flora (Rejmánek & Randall, 1994).
![Page 5: Mapping nonnative plants using hyper spectral imagery Emma Underwood Susan Ustin Deanne Dipietro](https://reader036.vdocuments.net/reader036/viewer/2022062423/56649d095503460f949daaa5/html5/thumbnails/5.jpg)
Ice plant(Carpobrotus edulis)
Common ice plant (Carpobrotus edulis), is an exotic plant species that invades coastal plant communities from the North Coast of California to Mexico.
CalEPPC (1999) rated C. edulis as an A-1 species (The Most Invasive Wild land Pest Plant: Widespread).
![Page 6: Mapping nonnative plants using hyper spectral imagery Emma Underwood Susan Ustin Deanne Dipietro](https://reader036.vdocuments.net/reader036/viewer/2022062423/56649d095503460f949daaa5/html5/thumbnails/6.jpg)
Jubata grass (Cortaderia jubata)
Poses a significant threat to mediterranen ecosystems prolific wind
dispersed seeds tolerance of a broad
range of habitats and its competitiveness
for light,moisture,and nutrients(Cowen,1976).
![Page 7: Mapping nonnative plants using hyper spectral imagery Emma Underwood Susan Ustin Deanne Dipietro](https://reader036.vdocuments.net/reader036/viewer/2022062423/56649d095503460f949daaa5/html5/thumbnails/7.jpg)
Key requirement Delineation the spatial extent Severity or intensity of invasion
Provides baseline for monitoring future expansion assists in identifying targets for control
activities
![Page 8: Mapping nonnative plants using hyper spectral imagery Emma Underwood Susan Ustin Deanne Dipietro](https://reader036.vdocuments.net/reader036/viewer/2022062423/56649d095503460f949daaa5/html5/thumbnails/8.jpg)
Offers significant opportunities for providing timely information on invasions of nonnative species into native habitats.
Larger spatial area Short period of time
Researchers exploit unique phenological, spectral, or structural characteristics of the nonnative species in the image to distinguish them from the mosaic of species around them.
Remote sensing-invasive plants mapping
![Page 9: Mapping nonnative plants using hyper spectral imagery Emma Underwood Susan Ustin Deanne Dipietro](https://reader036.vdocuments.net/reader036/viewer/2022062423/56649d095503460f949daaa5/html5/thumbnails/9.jpg)
Two ways High spatial ,but low spectral resolution-black &white or color infrared aerial
photographs Digital images with greater spectral resolution although coarser spatial
resolution.
Aerial photography - inexpensive, - large amount of archival
data - very fine spatial resolution
But - relies on nonnative plant
possessing visually detectable unique characteristics
- Extensive manual labor - Can collect data over a
relatively small spatial area
![Page 10: Mapping nonnative plants using hyper spectral imagery Emma Underwood Susan Ustin Deanne Dipietro](https://reader036.vdocuments.net/reader036/viewer/2022062423/56649d095503460f949daaa5/html5/thumbnails/10.jpg)
Digital multispectral imagery- automated image processing
- large spatial coverage
Successful applications of AVHRR, TM and ADAR
However, invasive species populations Can be detected only after they become dense and widespread.
![Page 11: Mapping nonnative plants using hyper spectral imagery Emma Underwood Susan Ustin Deanne Dipietro](https://reader036.vdocuments.net/reader036/viewer/2022062423/56649d095503460f949daaa5/html5/thumbnails/11.jpg)
AVIRIS (Airborne Visible/infrared imaging spectrometer)
Increased spatial resolution
Fine spectral resolution
224 spectral bands 400-2500nm at
10nm resolution 20 m spatial
resolution when flying at 11km.
![Page 12: Mapping nonnative plants using hyper spectral imagery Emma Underwood Susan Ustin Deanne Dipietro](https://reader036.vdocuments.net/reader036/viewer/2022062423/56649d095503460f949daaa5/html5/thumbnails/12.jpg)
Limitations of using traditionally available wavebands
- with color infrared green vegetation is observed as shades of red.
![Page 13: Mapping nonnative plants using hyper spectral imagery Emma Underwood Susan Ustin Deanne Dipietro](https://reader036.vdocuments.net/reader036/viewer/2022062423/56649d095503460f949daaa5/html5/thumbnails/13.jpg)
Objective
To investigate the use of AVIRIS imagery to detect the invasive species ice plant (Carpobrotus edulis) and Jubata grass(Cortaderia jubata).
To compare three techniques for processing the imagery : minimum noise fraction(MNF),Continuum removal ,and band ratio indices.
![Page 14: Mapping nonnative plants using hyper spectral imagery Emma Underwood Susan Ustin Deanne Dipietro](https://reader036.vdocuments.net/reader036/viewer/2022062423/56649d095503460f949daaa5/html5/thumbnails/14.jpg)
Study site
VAFB is used primarily for developing and testing missiles and satellite launches for the Department of Defense and NASA.
836 Vascular plants-quarter of them are invasive species.
C.edulis and C.jubata have invaded two native community types :coastal dune scrub community and maritime chaparral.
![Page 15: Mapping nonnative plants using hyper spectral imagery Emma Underwood Susan Ustin Deanne Dipietro](https://reader036.vdocuments.net/reader036/viewer/2022062423/56649d095503460f949daaa5/html5/thumbnails/15.jpg)
The focus of this research is the encroachment of ice plant and jubata grass in to these native communities and specifically on the ability of AVIRIS to identify pixels of different densities of these species.
![Page 16: Mapping nonnative plants using hyper spectral imagery Emma Underwood Susan Ustin Deanne Dipietro](https://reader036.vdocuments.net/reader036/viewer/2022062423/56649d095503460f949daaa5/html5/thumbnails/16.jpg)
Field work at VAFB
Coastal Scrub-iceplant
Intact Coastal Scrub
Chaparral-iceplant
Intact chaparral
Pampas-chaparral
5 community types
![Page 17: Mapping nonnative plants using hyper spectral imagery Emma Underwood Susan Ustin Deanne Dipietro](https://reader036.vdocuments.net/reader036/viewer/2022062423/56649d095503460f949daaa5/html5/thumbnails/17.jpg)
MethodologyPre-processing
- Atmospheric correction- Masks( NDVI > 0.2)
Processing - Minimum Noise Fraction
- Continuum Removal- Band Ratios
Compared processing techniques- Ability to delineate iceplant extent
- Detect iceplant density- Assess ease of processing and repeatability
![Page 18: Mapping nonnative plants using hyper spectral imagery Emma Underwood Susan Ustin Deanne Dipietro](https://reader036.vdocuments.net/reader036/viewer/2022062423/56649d095503460f949daaa5/html5/thumbnails/18.jpg)
Image Classification
Supervised Classification : requires the user to decide which classes exist in the
image, and then These samples known as training areas and are then input into a classification program, which produces a classified image.
Type of supervised Classification:Maximum likelihood classifierMaximum likelihood classification calculates the
probability that a given pixel belongs to a specific class.
![Page 19: Mapping nonnative plants using hyper spectral imagery Emma Underwood Susan Ustin Deanne Dipietro](https://reader036.vdocuments.net/reader036/viewer/2022062423/56649d095503460f949daaa5/html5/thumbnails/19.jpg)
Unsupervised Classification: when features are separated solely on their spectral properties .
Processing Techniques
Minimum Noise fraction(MNF) : Often used method for reducing redundancy of information between bands
reduce and compress the data increase speed of processing
![Page 20: Mapping nonnative plants using hyper spectral imagery Emma Underwood Susan Ustin Deanne Dipietro](https://reader036.vdocuments.net/reader036/viewer/2022062423/56649d095503460f949daaa5/html5/thumbnails/20.jpg)
Continuum removal: is a procedure that facilitates the distinction of similar absorption bands in hyper spectral curves.
![Page 21: Mapping nonnative plants using hyper spectral imagery Emma Underwood Susan Ustin Deanne Dipietro](https://reader036.vdocuments.net/reader036/viewer/2022062423/56649d095503460f949daaa5/html5/thumbnails/21.jpg)
Band ratio indices
Emphasize the biochemical and the biophysical properties of the vegetation contained in physiologically important bands.
![Page 22: Mapping nonnative plants using hyper spectral imagery Emma Underwood Susan Ustin Deanne Dipietro](https://reader036.vdocuments.net/reader036/viewer/2022062423/56649d095503460f949daaa5/html5/thumbnails/22.jpg)
Definitions
Confusion matrix : is a square array of numbers set out in rows and columns which express the number of sample units(i.e.,pixels,clusters of pixels etc..) assigned to a particular category relative to the actual category as verified on the ground.
Overall accuracy-the total number of correctly classified samples( i.e,the major diagonal) divided by the total number of sample units in the entire matrix.
![Page 23: Mapping nonnative plants using hyper spectral imagery Emma Underwood Susan Ustin Deanne Dipietro](https://reader036.vdocuments.net/reader036/viewer/2022062423/56649d095503460f949daaa5/html5/thumbnails/23.jpg)
Producer’s accuracy :is the number of correctly classified samples of a particular category divided by the total number of reference samples from that category.
User’s accuracy : is the number of correctly classified samples of a particular category divided by the total number of samples being classified as that category.
![Page 24: Mapping nonnative plants using hyper spectral imagery Emma Underwood Susan Ustin Deanne Dipietro](https://reader036.vdocuments.net/reader036/viewer/2022062423/56649d095503460f949daaa5/html5/thumbnails/24.jpg)
Results
Comparison of 3 processing techniques
![Page 25: Mapping nonnative plants using hyper spectral imagery Emma Underwood Susan Ustin Deanne Dipietro](https://reader036.vdocuments.net/reader036/viewer/2022062423/56649d095503460f949daaa5/html5/thumbnails/25.jpg)
Results
Overall accuracy-MNF performed best User’s accuracy-is important
User’s accuracy-MNF lowest MNF is able to produce a more accurate map
of multiple vegetation classes Continuum removal and band ratio techniques
are suited for detecting species with distinct characteristics.
![Page 26: Mapping nonnative plants using hyper spectral imagery Emma Underwood Susan Ustin Deanne Dipietro](https://reader036.vdocuments.net/reader036/viewer/2022062423/56649d095503460f949daaa5/html5/thumbnails/26.jpg)
Discussion
Evaluated three approaches- accuracy - logistics of
processing - ease of
interpretation Confusion matrices demonstrated that MNF
performed best for classifying all five vegetation communities.
– However,in terms of classifying one of the target species,ice plant,the continuum removal and the band ratio methods performed better.
![Page 27: Mapping nonnative plants using hyper spectral imagery Emma Underwood Susan Ustin Deanne Dipietro](https://reader036.vdocuments.net/reader036/viewer/2022062423/56649d095503460f949daaa5/html5/thumbnails/27.jpg)
Key findings..MNF
Worked well identifying different densities of ice plant
X Difficult to interpret
Band Ratio Intuitive
Continuum Removal Good results for presence / absence of ice plant Easy to useX Speckled result, accuracy not improved when
lumped
![Page 28: Mapping nonnative plants using hyper spectral imagery Emma Underwood Susan Ustin Deanne Dipietro](https://reader036.vdocuments.net/reader036/viewer/2022062423/56649d095503460f949daaa5/html5/thumbnails/28.jpg)
Conclusions
The benefit of this research has been to contribute to the knowledge base of land managers at VAFB by providing improved information on the
spatial extent and the density of the ice plant and jubata grass, which will lead to better protection of the native biodiversity.