Habitat Mapping using Remote Sensing for Green Infrastructure Planning in Anguilla

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1 Habitat Mapping using Remote Sensing for Green Infrastructure Planning in Anguilla Dr Katie Medcalf Cenv MIEEM

2 Context Introduction to Anguilla Habitat mapping using Earth Observation data Using the data within the context of green economy modelling Ecosystem service monitoring of the island Opportunities for this approach

3 Anguilla North most of the Leeward Islands lying east of Puerto Rico and directly north of Saint Martin Total land area of 90 sq. km, including the main island and offshore Cays Population of approximately 14,000 Main vegetation types; scrub and thicket on limestone pavement, fallow agricultural areas, mangrove and salt water ponds

4 Why is habitat and green economy data needed in Anguilla The terrestrial environments of the Anguillan archipelago are considered fragile. The tourism industry and the associated infrastructure development fuels the socio economic development in the country. This has led to the degradation and loss of valuable habitats in Anguilla. It necessary to monitor the island s biodiversity. To feed biodiversity information into decision making to help ensure the sustainable management of the natural resources of the country.

5 Government of Anguilla desk based survey Identified key habitats and vegetation cover types Recorded species and zonation of occurrence of endemic scrub: Rondeletia anguillensis Identified key risk factors: Invasive species Development activities

6 This project Aims of this stage of the project To build on the existing work, producing more detailed habitat mapping Provide information on the role of the habitats and biodiversity Build understanding about the value of the green economy to the island

7 Habitat mapping using Earth Observation Earth Observation allows us to: Obtain reliable information over large areas and extended time periods Map inaccessible or hard to reach areas Monitor community changes, but not individual species Monitor both backward and forward in time with suitable data Track changes in functional relationships

8 Seeing the world differently We are used to looking at images and making a visual interpretation Loblolly Pisonia subcordata Imagery can be similarly interpreted using colour and form.

9 Seeing the world differently Ref: Lillesand and Kiefer, 2004

10 Productivity is related to NIR light and leaf properties

11 Satellite image resolution SPOT Landsat NIR/SWIR/Green (10m resolution) (30m resolution) World View RGB 1.84 m resolution bands

12 Remote sensing can identify Productivity (e.g. Vegetation indices) Wetness of vegetation (e.g. SWIR reflectance) Photosynthetic and non photosynthetic (dead or living) vegetation Angles of leaf incidence canopy structure type features Vegetation communities

13 Data used

14 Anguilla classification Imagery Habitat Urban mask Coast Agriculture & Bare Ground Beach High NIR High Red Med NDVI Ironshore Med High NIR High Red Med Low NDVI Agriculture Med High Red Med NDVI Low SWIR/NIR Bare Ground High Red High NIR Med NDVI Anthropogenic Very High Red Low NDVI Main Habitats Pond Low NIR Low SWIR Low NDVI Mangrove Med Low SWIR Med Low Red NDVI range Limestone Scrub Med SWIR Limestone Thicket High SWIR Dry Forest Med High Shade NDVI difference High SWIR/NIR Scrub w. Cacti High SWIR Med NDVI Med NIR Sub Types Scattered Scrub High StDev Red Limestone Pment Low Shade Mid High Red Low SWIR/NIR Dune Scrub Proximity to Beach Dune Thicket Proximity to Beach Fuzzy Gradations Scrub with Thicket Characteristics Fuzzy Dune Scrub with Thicket Characteristics Fuzzy Thicket with Dry Forest Characteristics Relaxed thresholds Subdivide by Soil Type Overlap with thematic layer: mineral soils

15 Functional classification

16 Habitat Map

17 Features relevant to green economy Unauthorised sand mining leading to beach loss and enhanced hurricane damage, with knock on effects on tourism. Goat grazing on vulnerable areas

18 Four key factors What the habitat is Where the habitat is Four key influencing factors How the habitat is managed

19 Simple model of 3m storm surge Modelling storm surges

20 Ecosystem services Regulation of surface water run off Rule Base Considered Vegetation Slope Soil Rainfall (proxy)

21 Opportunities of this approach -Build Understanding Opportunities to build understanding through use of the data layers and scenario modelling Green infrastructure development Economically Environmentally Culturally

22 The way ahead Earth Observation is an ideal tool for monitoring The habitat map and other layers are a good starting point for other ecosystem service mapping Using open sources GIS to make layers / map and green economy features more accessible Work on offshore environment and the health and features of the coral reefs

23 Thank you Questions?