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Date : 24 February 2012
EO Information Services in support of
West Africa Coastal vulnerability - Service Utility Review -
Christian Hoffmann, GeoVille
World Bank HQ, Washington DC
Content
- Project background & Challenges
- Coastal change maps – Result Overview
- Initial product validation
- Service benefits and limitations
- Coastal areas with high population densities are those with the most shoreline degradation or alteration
Published in UNEP Global Environment Outlook 4, 2009
Introduction
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
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
Cotonou (Benin)
Lagos (Nigeria)
Sao Tome & Principe
Image copyright: Microsoft Maps / Google Earth
Satellite data for generation of historical coastline maps
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
- LANDSAT 30m / SPOT 20m (all AOIs)
- SPOT 10m (high resolution cases The Gambia & northern Sao Tome)
Coastal change maps
Uncertainty of coastline length & location
… the „coastline paradox“ of Benoit Mandelbrot
Coastal change maps
Uncertainty of
coastline location
Spot Landsat
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)
2350 km 2775 km 3425 km
Great Britain as measured by rods:
Explaining image resolution
30m/Landsat 10m/SPOT 1m/Ikonos
Large-area coverage for
regional overview maps & statistics
Scale: 1: 200.000
Accuracy: +/- 30m
Availability: from 1970s
Medium-area coverage for
local maps & statistics
Scale: 1: 50.000
Accuracy: +/- 10m
Availability: from 1990s
Coverage of hot spots, incl. maps & statistics
for individual beach areas
Scale: 1: 10.000
Accuracy: +/- 1m
Availability: from 2000s
Coastal change maps
Satellite data for coastline mapping
30m/Landsat 10m/SPOT 1m/Ikonos
Image data: USGS, Spotimage, SpaceImaging
Coastal change maps
Satellites used Satellite image resolution
Resulting maximal deviation of coastline for both dates*
Landsat 1990 – Landsat 2010 30 m / 30 m Up to 75 m
Landsat 1990 – SPOT 2010 30 m / 10 m Up to 35 m
SPOT 1990 – SPOT 2010 10 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)
Coastal change maps
21.12.2002 (VHR, Google Earth) 10.12.2009 (VHR, Google Earth)
Coastal change maps
Map 2005
Example of a topographic map providing too less detail to verify coastline location & changes
Sao Tome - Coastal change
21.12.2002 (low tide) 06.11.2009 (medium tide) 26.07.2009 (high tide)
Coastal change maps
Coastal change map 1990-2010 Red = land transformed to water
Tidal change influencing location of the shoreline
No tidal information & VHR images used in eoworld
Old jetty under water, detected as land in historical map due to low tide
Sao Tome - Coastal change near Fernão Dias
Coastal change maps
Sao Tome - Coastal change near Micolo (1954, 1990, 2010)
04/06/2011
Map 1954 SPOT 1990
SPOT 2010
Micolo
Micolo
Heavy erosion between 1954 and 1990 due to
beach sand mining
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)
http://www.csiwisepractices.org/?read=49
30m/Landsat 10m/SPOT 1m/Ikonos
Image data: USGS, Spotimage, SpaceImaging
Coastal change maps
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
Recent Recent Recent Historic Historic Historic
Number of satellite scenes needed (1990 – 2000 –2010)
SPOT 10m Landsat 30m
Sao Tomé & Príncipe 15 15
Senegal & The Gambia 66 15
Cotonou (Benin) & Lagos (Nigeria) 22 7
TOTAL 103 37
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)
Coastal change maps
Historical maps of the coastline
- Methodology
- Automated pixel-based change detection from multi-temporal satellite imagery 1990 – 2000 – 2010
- Result
- Vector maps to allow an overlay of different dates for change analysis
Coastal change maps
Image copyright: USGS / Spotimage; Processing: GeoVille for ESA / World Bank
Bakau, The Gambia Delta du Saloum National Park, Senegal
Maps of coastal changes
Image copyright: USGS / Spotimage; Processing: GeoVille for ESA / World Bank
Erosion 1990-2010:
47 ha lost 13 ha lost
Coastal change maps
- Methodology
- Spatial analysis of historical coastline maps
- Result
- Quantification of coastal changes (erosion / aggradation)
370 m lost
320 m lost
Bakau, The Gambia Delta du Saloum National Park, Senegal
Lagos (Nigeria) / „Eko Atlantic“ – first signs of Africa‘s new financial epicentre expanding into the Atlantic ocean
Coastal change maps
01/08/2011 03/21/2000
Eko atlantic
Significant land reclamation
Image copyright: Spotimage; Processing: GeoVille for ESA / World Bank
Land reclamation by aquafarming and stilt housing
Ganvié – Lake Nokoue(Benin)
Coastal change maps
01/20/2010 12/23/2002
Image copyright: Spotimage; Processing: GeoVille for ESA / World Bank
Coastal erosion severely threatening urban areas & infrastructure
Cotonou (Benin)
Service 1: Coastal change maps
01/20/2010 12/23/2002
Image copyright: USGS / Spotimage; Processing: GeoVille for ESA / World Bank
Land erosion / aggradation trends in natural environments
Estuary of Casamance river / Senegal
Coastal change maps
06/19/2010 03/10/1988
Image copyright: USGS; Processing: GeoVille for ESA / World Bank
Micolo
Coastal erosion caused by beach sand mining
Near Micolo (São Tomé)
Coastal change maps
04/06/2011 03/21/1990
Praia Diogo Nunes
Praia do Micolo
Fernao Dias
Image copyright: Spotimage; Processing: GeoVille for ESA / World Bank
Initial product validaton (by service provider)
- Method: Random point sampling (n = 5.000) inside 300m buffer of coastline
- 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 %
Coastline maps (Spot-based): 87.6 %
Sample points
Image copyright: Spotimage Processing: GeoVille for ESA / World Bank
Coastal change maps
Limitations of Google Earth for verification of changes
Geometric inaccuracy ~200m
Acquisition date: 08/25/2006
Acquisition date: UNKNOWN
- Unknown geometric accuracy & geometric inconsistencies (example: Lagos lagoon, Nigeria)
- Inhomogeneity of timeliness (example: Principe)
Coastal change maps
Image copyright: Google Earth / DigitalGlobe;
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
Coastal change maps
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
Coastal change maps
Thank you
Questions & Discussion