0 Riparian Zone Health Project Agriculture and Agri-Food Canada Grant S. Wiseman, BS.c, MSc. World Congress of Agroforestry Nairobi, Kenya August 23-28, 2009

1 Riparian Health Identification Project Riparian zones are natural vegetative buffers along water corridors separating agricultural land from water Benefits of Riparian Zones  Absorption of excess nutrient excess runoff  Carbon Sequestration  Provides habitat for biodiversity Currently no riparian zones data layers exist Province wide ground surveys too costly, time consuming OBJECTIVE Develop a remote sensing methodology to:  1) Identify riparian zones by vegetative classes  2) Infer riparian zone health indicators

2 Riparian Project: Data Sets High resolution true colour orthophotos  1:40,000 scale (62.5 cm pixel resolution) Synthetic Apeture Radar (SAR) Radarsat-2 quad polarization imagery  All four polarization sending\receiving (1 m resolution) Surface validation data from is being collected to identify riparian zone health by riparian project experts  Cows and Fish Survey METHODOLOGY Analyze the spectral, spatial and relational characteristics derived from Radarsat-2 satellite imagery and high resolution colour orthophotos using Object Image Analysis (OBIA) Correlate to surface validation data using multivariate analysis

3 Project Study Area Found in Manitoba, Canada within the Upper Assiniboine River Conservation District (UARCD) Approximately 35 km in length. 300 meter buffers on both sides of creek. Selected for diversity in riparian zone vegetation, health and management practices

4 Level 1

5 Level 2

6 Level 3

7 Visit segmented polygons on ground using GPS and hand held GIS equipment Collect detailed habitat, vegetation, agricultural usage, vegetation and health information riparian areas Over 150 ecological survey questions at 100+ sites Surface Validation

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9 96.5% Accuracy (based on 3,600+ objects)

10 Synthetic Aperture Radar (SAR) Frequency X-Band TerraSAR-X: 9.7 GHz (3.1 cm) C-Band RADARSAT-1 and ASAR: 5.3GHz (5.6 cm) RADARSAT-2: GHz (5.6 cm) L-Band ALOS PALSAR: 1.27 GHz (23.6 cm) The Electromagnetic Spectrum

11 Polarimetric SARs Active sensor, sends energy to earth’s surface, receives reflected energy Transmit and receive all 4 mutually orthogonal polarizations H = Horizontal, V = Vertical (HH,HV, VV and VH)

12 Radarsat 2: Health Indicators Acquire Fine Beam Mode R-2 imagery Summer 2009  Quad-polarization – HH, HV, VH, VV Use Band Ratios to generate Health Indicators CS (average Cross-Polarized magnitude) = HV + VH / 2 CSI (Canopy Structure Index) = VV / VV + HH BMI (Biomass Index) = VV + HH / 2 VSI (Volume Scattering Index) = CS / CS + BMI Summarize band ratio layers with existing image objects to generate spatial, spectral and relational SAR attributes Pope, et al., 1993

13 Multivariate Analyses Multiple Discriminate Analysis (MDA) and Canonical Correlations Analysis (CanCor) to identify relationships between:  Intensive ecological data collection survey  High resolution imagery objects  Radarsat-2 objects Determine what remotely sensed information correlates with riparian zone health surface validation information

14 Once the riparian zone health information gap can be addressed effective agroforestry management practices can be implemented on a watershed scale

15 Thank you