A change detection tool for vegetation disturbances on Irish Peatlands
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A change detection tool for vegetation disturbances on Irish Peatlands

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Dr Jerome O Connell - presentation made at various conferences throughout Europe as part of PhD which was funded by the EPA under the STRIVE Research Programme 2007-2013 (2007-PhD-ET-2)

Dr Jerome O Connell - presentation made at various conferences throughout Europe as part of PhD which was funded by the EPA under the STRIVE Research Programme 2007-2013 (2007-PhD-ET-2)

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A change detection tool for vegetation disturbances on Irish Peatlands A change detection tool for vegetation disturbances on Irish Peatlands Presentation Transcript

  • A Change Detection Tool for Vegetation Disturbance on Irish Peatlands SPIE Remote Sensing 2011 Jerome O Connell, Nick Holden, John Connolly Biosystems Engineering University College Dublin Ireland
  • Funded by the EPA, STRIVE under the National Development Plan (2007 – 2013) Introduction• Peatlands – Peatlands: 4-6% land surface: over 33% soil carbon stock – Peatlands cover ~20% of Ireland – Over 85% of Irish peatlands disturbed – Need for RS based change detection process for Irish peatlands • RS based change detection process – Multispectral • Optimum spatial, spectral and temporal resolution – Multi temporal • Peatlands can be dynamic • Disturbance seasonal and inter-seasonal – Multi platform • Over 78% cloud cover in summer, 82% in winter • Project Outline – 5 sites, 3 assessed to-date • Kerryhead (Commonage) – Upland Heath (642 ha) – Burning, conversion to pasture • Slieve Bloom Mountains (SPA) – Blanket Bog (3845 ha) – Drainage, peat extraction, burning, afforestation, bog bursts • Clara (SAC) – Raised Bog (460 ha) – Drainage, peat extraction, burning – Data • > 240GB of multispectral data • 10 to 30m resolution • SPOT 2, 4 and 5; Landsat TM, ETM+, Aster VNIR, IRS P6 LISS • Auxiliary data – MODIS, Ikonos, Kompsat, Quickbird, aerial photography, habitat maps, disturbance records.
  • 0.00 0.20 0.40 0.60 0.80 1.00 1.20 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 TIC 6s Normalised6s 0.00 0.20 0.40 0.60 0.80 1.00 1.20 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 TIC 6s Normalised6s 0.00 0.20 0.40 0.60 0.80 1.00 1.20 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 TIC 6s Normalised6s Methods • Pre-processing – Geo-rectification to master image • RMSE 0.25 – DN to TOA reflectance to EVI2 • Atmospheric scattering: DOS (mean from lowest 5% of pixels) • Cloud mask (unsupervised) • Topographical normalisation • Automated in Spatial Modeller – TIC normalisation • Density slicing • Regional growth tool • Urban and water – Cross calibration • Difference images (5% ± mean) • Water urban, peatland and conifer pixels • Random sampling for regional growth tool • Change detection – Spatial Modeller • Image differencing • Spatial threshold • Spectral threshold Funded by the EPA, STRIVE under the National Development Plan (2007 – 2013)
  • Cross Calibration • Pixel Extraction – Difference image • ± 5% change – Spectral threshold • ± 0.015 EVI2 – Spatial threshold • 300 – 1000 pixels • Validation – Histograms • Before • After – Statistics • Mean, SD • Kolmogorov Smirnov (KS) Test Funded by the EPA, STRIVE under the National Development Plan (2007 – 2013) D = 0.63 D = 0.08 0 500 1000 1500 2000 2500 3000 3500 4000 0 0.2 0.4 0.6 0.8 1 Count EVI2 Slieve Bloom Histograms TM TM Cross Cal Master
  • Model Calibration • Clara Bog – Burn in April 2008 (35.93ha) • SD Threshold Analysis – 0.5 SD = 4.47% error – 1.0 SD = 5.31% error – 1.5 SD = 0.19% error – 2.0 SD = 3.70% error – 2.5 SD = 24.08% error Funded by the EPA, STRIVE under the National Development Plan (2007 – 2013)
  • Model Validation • Error matrices – Random sampling • Approx 1 point/ 2ha – Ground truth data • OSi aerial photos • Ikonos, Kompsat – Validation of 1.5 SD for optimum user, producer, overall and Kappa. – High omission (Producer) of Change at > 1.5 SD – High commission (User) of Change at < 1.5 SD Funded by the EPA, STRIVE under the National Development Plan (2007 – 2013)
  • Slieve Bloom Change Funded by the EPA, STRIVE under the National Development Plan (2007 – 2013) Conlawn Hill Glenlahan Valley Spot4_2003_04_18 Spot4_2004_06_14 Spot4_2006_04_05 Spot5_2007_06_07 Spot5_2010_06_20 Spot2_2009_06_03
  • Conclusions • Negative and positive change assessed – Disturbance indicated by initial increase (vegetation removal) and post disturbance decrease (re- colonisation of non-native species) • Success of image TIC normalisation and cross calibration – Typically 0.05± EVI2 • To date, error matrices have given high (> 80%) Kappa values at 1.5 SD • Use of Erdas spatial models combined with batch processing – potential to process large databases Funded by the EPA, STRIVE under the National Development Plan (2007 – 2013) Kerryhead Change Detection 2000 to 2010
  • Further Work Funded by the EPA, STRIVE under the National Development Plan (2007 – 2013) • Assess the detection accuracy of various disturbance types • Verify change detection model in other sites – Ground based LAI data • Sun elevation may still be an issue <16° – Hill shade overlay • Non-spatial ground truth data – Slieve Bloom and Wicklow Mountains Acknowledgements • Environmental Protection Agency under STRIVE program • National Parks and Wildlife Service / Coillte • European Space Agency (Cat 1) • CNES (ISIS) • OSi