EO Information Services in support of West Africa Coastal vulnerability - Service Utility Review -

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1 EO Information Services in support of West Africa Coastal vulnerability - Service Utility Review - Christian Hoffmann, GeoVille World Bank HQ, Washington DC Date : 24 February 2012

2 Content - Project background & Challenges - Coastal change maps Result Overview - Initial product validation - Service benefits and limitations

3 Introduction - Coastal areas with high population densities are those with the most shoreline degradation or alteration Published in UNEP Global Environment Outlook 4, 2009

4 Background : The World Bank Project - Service 1 Coastal change maps: understand coastal degradation and erosion over the last 20 years - Project users: - World Bank - Environmental & marine resources authorities - Regional planning agencies - Project context: - Estimate coastal changes - Support assessments of urban coastal vulnerability in critical coastal areas of Africa

5 Background : The World Bank Project - Project Information requirements - Historical maps of the coastline (last 20 years) in vector format to allow an overlay of different dates - Map of coastal changes derived from the analysis of the historical coastlines maps Senegal & The Gambia Sao Tome & Principe Image copyright: Microsoft Maps / Google Earth Cotonou (Benin) Lagos (Nigeria)

6 Satellite data for generation of historical coastline maps - LANDSAT 30m / SPOT 20m (all AOIs) - SPOT 10m (high resolution cases The Gambia & northern Sao Tome) AOI-A: São Tomé and Príncipe AOI-B: Senegal & The Gambia AOI-C: Cotonou (Benin) AOI-D: Lagos (Nigeria) Image copyright: USGS, Spotimage Processing: GeoVille for ESA / World Bank

7 Uncertainty of coastline length & location the coastline paradox of Benoit Mandelbrot Great Britain as measured by rods: Landsat Uncertainty of coastline location Spot 2350 km 2775 km 3425 km Mandelbrot s fractals: the measured length of a coastline depends on the scale of measurement - Scale of measurement (=resolution) - Geographic accuracy of base data - Tidal effects - Coastal morphology not discernible from imagery (sand vs. bare rock)

8 Explaining image resolution 30m/Landsat 10m/SPOT 1m/Ikonos Large-area coverage for regional overview maps & statistics Scale: 1: Accuracy: +/- 30m Availability: from 1970s Medium-area coverage for local maps & statistics Scale: 1: Accuracy: +/- 10m Availability: from 1990s Coverage of hot spots, incl. maps & statistics for individual beach areas Scale: 1: Accuracy: +/- 1m Availability: from 2000s

9 Satellite data for coastline mapping 30m/Landsat 10m/SPOT 1m/Ikonos Image data: USGS, Spotimage, SpaceImaging

10 Satellites used Satellite image resolution Landsat 1990 Landsat m / 30 m Up to 75 m Resulting maximal deviation of coastline for both dates* Landsat 1990 SPOT m / 10 m Up to 35 m SPOT 1990 SPOT m / 10 m Up to 25 m SPOT 1990 IKONOS 1m 10 m / 1 m Up to 10 m Historic map / satellite data 1990 IKONOS 1m ~ 10 m / 1 m Up to 10 m * Not accounting for coastal morphology & tidal variations State-of-art Earth Observation techniques result in: +/-1 pixel for absolute geometric accuracy (first date, higher resolution coverage) & +/- 0.5 pixel co-registration accuracy (second date)

11 Sao Tome - Coastal change (VHR, Google Earth) (VHR, Google Earth) Map 2005 Example of a topographic map providing too less detail to verify coastline location & changes

12 Sao Tome - Coastal change near Fernão Dias (low tide) (high tide) (medium tide) Old jetty under water, detected as land in historical map due to low tide Tidal change influencing location of the shoreline No tidal information & VHR images used in eoworld Coastal change map Red = land transformed to water

13 04/06/2011 Coastal change maps Sao Tome - Coastal change near Micolo (1954, 1990, 2010) Map 1954 SPOT 1990 Heavy erosion between 1954 and 1990 due to beach sand mining Micolo SPOT 2010 Obvious signs of sand build-up between 1990 and 2010 after local community decision to forbid sand extraction in mid-1994 (following a joint STP government / ECOFAC awareness campaign) Micolo

14 30m/Landsat 10m/SPOT 1m/Ikonos Historic Recent Historic Recent Historic Recent Image data: USGS, Spotimage, SpaceImaging Identification of large change hot-spots on regional level Only trend statistics possible (not for individual patches) Localised mapping of changes Area statistics of change patches possible Detailed mapping of rapidly changing areas High reliability of area statistics for single hot-spots

15 Choosing the right satellite sensor depends on... - area of interest (large-area vs. local) - scale of application (regional trends vs. hot-spot assessment) - image availability (archive / programming) - type of satellite & bands (multi-spectral, panchromatic) - limiting factors (cloud coverage / haze) Number of satellite scenes needed ( ) SPOT 10m Landsat 30m Sao Tomé & Príncipe Senegal & The Gambia Cotonou (Benin) & Lagos (Nigeria) 22 7 TOTAL

16 Historical maps of the coastline - Methodology - Automated pixel-based change detection from multi-temporal satellite imagery Result - Vector maps to allow an overlay of different dates for change analysis Bakau, The Gambia Delta du Saloum National Park, Senegal Image copyright: USGS / Spotimage; Processing: GeoVille for ESA / World Bank

17 Maps of coastal changes - Methodology - Spatial analysis of historical coastline maps - Result - Quantification of coastal changes (erosion / aggradation) Bakau, The Gambia Erosion : 47 ha lost 13 ha lost Delta du Saloum National Park, Senegal 370 m lost 320 m lost Image copyright: USGS / Spotimage; Processing: GeoVille for ESA / World Bank

18 Lagos (Nigeria) / Eko Atlantic first signs of Africa s new financial epicentre expanding into the Atlantic ocean 03/21/ /08/2011 Significant land reclamation Eko atlantic Image copyright: Spotimage; Processing: GeoVille for ESA / World Bank

19 Land reclamation by aquafarming and stilt housing Ganvié Lake Nokoue(Benin) 01/20/ /23/2002 Image copyright: Spotimage; Processing: GeoVille for ESA / World Bank

20 Service 1: Coastal change maps Coastal erosion severely threatening urban areas & infrastructure Cotonou (Benin) 12/23/ /20/2010 Image copyright: USGS / Spotimage; Processing: GeoVille for ESA / World Bank

21 Land erosion / aggradation trends in natural environments Estuary of Casamance river / Senegal 06/19/ /10/1988 Image copyright: USGS; Processing: GeoVille for ESA / World Bank

22 Coastal erosion caused by beach sand mining Near Micolo (São Tomé) 04/06/ /21/1990 Fernao Dias Praia do Micolo Praia Diogo Nunes Micolo Image copyright: Spotimage; Processing: GeoVille for ESA / World Bank

23 Initial product validaton (by service provider) - Method: Random point sampling (n = 5.000) inside 300m buffer of coastline Sample points - Criterion: correct classification of land / water at reference point - Reference data - High- to very high resolution imagery (SPOT, ALOS-AVNIR, IKONOS, GeoEye) - Topographic maps - Product accuracy: Coastline map (Landsat-based): 83.9 % Image copyright: Spotimage Processing: GeoVille for ESA / World Bank Coastline maps (Spot-based): 87.6 %

24 Limitations of Google Earth for verification of changes - Unknown geometric accuracy & geometric inconsistencies (example: Lagos lagoon, Nigeria) - Inhomogeneity of timeliness (example: Principe) Acquisition date: 08/25/2006 Geometric inaccuracy ~200m Acquisition date: UNKNOWN Image copyright: Google Earth / DigitalGlobe;

25 Challenges & constraints - Individual hot-spot assessment (beach-level) requires very high resolution data (1m) to verify trends detected on regional level - Maximal deviation of coastline (i.e. false changes) can be up to 75m for Landsat 30m data - Atmospheric conditions (clouds & haze) - Lack of in-situ data for calibration / validation - Coastal geomorphology - Tidal heights

26 Added value of Earth Observation - Synoptic, consistent, timely and periodic information source for coastal change monitoring - Large-area trend analysis & detailed hot-spot assessments of coastal erosion & aggradation processes - Cost-efficient image processing algorithms - Quality controlled geo-information to quantify what is happening Image copyright: Spotimage; Processing: GeoVille for ESA / World Bank

27 Thank you Questions & Discussion

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