Identification of Invasive guava Psidium guajava on Isabela Island, Gal pagos Archipelago using Object Based Image Analy

1. Identification of Invasive guava (Psidium guajava) on Isabela Island, Gal�pagos Archipelago using Object Based Image Analysis Techniques Amy L. McCleary Department of Geography & Carolina Population Center University of North Carolina at Chapel Hill

2. Introduction Galapagos Islands are a site of world renowned biodiversity Increasing human impact on the islands� fragile ecosystems Tourism Population growth Mounting pressure on native plant and animal species

3. Introduction (cont) Introduced & Invasive species indicative of human impacts Guava (Psidium guajava) is one such invasive species Spatial distribution and pattern of invasive plants in Galapagos is often not well understood

4. Research Goals Characterize the occurrence and spatial pattern of guava (Psidium guajava) for a test site on Isabela Island, Galapagos using Object Based Image Analysis methods. Evaluate whether OBIA methods are well suited to characterization of an invasive plant at the species level.

5. Galapagos Archipelago 1,000 km off the coast of Ecuador 19 large islands, 200 small islands and rocks 97% of the archipelago is protected; 3% is comprised of agricultural zones and small communities Rapid growth of human population in last 20 years

6. Isabela Island, Galapagos Study area is positioned on the southeastern slope of Sierra Negra volcano Straddles agricultural zone and Galapagos National Park Guava has become a highly conspicuous invasive plant on Isabela Island

7. Guava (Psidium guajava) Cultivated shrub/small tree grown for its edible fruit 3-10 m tall Intentionally introduced into humid highlands Has become invasive and is replacing native species Costly and time-consuming to eradicate

8. QuickBird Multispectral Data Acquired October 22, 2004 2.4 m spatial resolution 4 bands, 0.45-0.90 micrometers 20-40 km swath width

9. QuickBird Multispectral Data Acquired October 22, 2004 2.4 m spatial resolution 4 bands, 0.45-0.90 micrometers 20-40 km swath width

10. QuickBird Multispectral Data Acquired October 22, 2004 2.4 m spatial resolution 4 bands, 0.45-0.90 micrometers 20-40 km swath width

11. Object Oriented Image Analysis Well suited to the classification of high spatial resolution imagery E.g., QuickBird, Ikonos, Aster Relies on knowledge-based membership functions that explicitly define rules to classify regions (i.e., contiguous groups of pixels), rather than traditional methods that apply a single decision-rule on a per-pixel basis Segmentation and classification algorithms are available in Definiens Professional 5

12. OBIA Workflow Load image data.

13. OBIA Workflow Load image data. Create image objects.

14. OBIA Workflow Load image data. Create image objects. Define classification scheme.

15. OBIA Workflow Load image data. Create image objects. Define classification scheme. Apply classification to image objects.

16. Methods: Image Segmentation Multiresolution segmentation. Top-down approach. 5 levels of analysis.

17. Methods: Define Classification Scheme Created class scheme: Guava Green vegetation Soil & dry vegetation Defined membership functions for each of the classes Based on spectral response of landscape features within objects

18. Methods: Apply Classification Applied to all 5 levels of analysis.

19. Methods: Re-Define Classification Scheme Altered class scheme: Guava Green vegetation Soil & dry vegetation Trees Non-photosynthesizing Photosynthesizing

20. Methods: Apply New Classification Applied to all 5 levels of analysis.

21. Landscape Pattern Metrics Total Area Total area of guava for the defined study area Patch Density Number of patches of guava per 100 hectares Contagion Landscape fragmentation These metrics were used to quantify the degree of land fragmentation of guava

22. Summary of Findings Guava exists across a large proportion of the test area. Nearly 1,600 Ha (of 8700 Ha) Guava occurs mainly in large patches that are moderately connected. Abandoned agricultural plots Young patches are difficult to identify as the are spectrally similar to grasslands Present both in the agricultural zone and within the Galapagos National Park boundary. Largest patches mostly restricted to the agricultural zone Individual trees/shrubs in transition zone along GNP

23. Summary of Findings (cont) In general, OBIA methods are well suited to the identification of invasive guava at the species level. However, there are some drawbacks Time consuming Requires good understanding of landscape Software is expensive, as is high-spatial resolution imagery And benefits also Processes can be automated Integrates RS and GIS functionality Flexibility in defining classes

24. Future Research Work with fuzzy membership classes to improve overall LULC classification. Expand the membership functions to include textural measures of target classes, as well as spatial-spectral relationships between neighboring classes. Include non-spectral attributes in the segmentation and classification processes Terrain characteristics Land ownership information

25. Acknowledgements People Dr. Stephen J. Walsh Carlos F. Mena Julie P. Tuttle Yang Shao Institutions Carolina Population Center Department of Geography, UNC-CH Galapagos National Park Service Charles Darwin Foundation CLIRSEN THANKS!