Earth Observation & Mapping

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Emory Potter
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1 Coastal bathymetry from Wordview-2 satellite data 2012 Thomas Heege EOMAP Germany Magnus Wettle EOMAP Asia Pacific Dave Benson DigitalGlobe London David Chritchley Proteus Abu Dhabi Susanne Lehner German Aerospace Center DLR ESA Earth Observation & Mapping NASA

2 EOMAP business: Mapping of aquatic environments EO based service lines Monitoring services Applications Water quality monitoring Oil- and gas industry Dredging Turbidity monitoring Offshore construction impact monitoring Water depth mapping Water ways Pipeline routing Sea floor monitoring Biodiversity baseline

3 EOMAP business: Mapping of aquatic environments Commercial mapping services for coastal engineering and environmental monitoring Offshore and Oil & Gas companies in Australia, Mexico, Netherlands, VAE, Italy,.. International project participation Vietnam, Mexico, ESA World Bank EU wide inland water monitoring GMES

4 Competence EOMAP Core Competence Multi- and hyperspectral remote sensing of deep and shallow aquatic systems Physics based data processing Sensor Independent data processing technology Atmospheric correction & data inversion

5 Core Technology Water Quality and Water Depth Product generation workflow Input satellite radiance image L Proces ssing Atmosphere vertical profiles of optical properties Sensor sensor parameters Optical models specific opt. properties of water, sea floor, land Land-water-cloud detection Adjacency correction Sunglitter correction Atmospheric correction coupled with retrieval of water constituents subsurface reflectance R Water column inversion coupled retrieval Radiative transfer database Global and regional land-water database water constituents: Suspended matter S Phytoplankton (CHL-a) P Yellow Substances Y Output Water depth z Sea floor albedo

6 Satellite raw data - Quintana Roo coast, Mexico Word View 2,

7 Subsurface reflectance. Channels 4, 3, 2 (RGB) World View 2. MIP data processing. Product after atmospheric and sea surface correction

8 Sea floor albedo. Channels 3, 2, 1 (RGB) World View 2. MIP data processing. Processing: water column correction & depth retrieval

9 Seafloor Classification - Quintana Roo coast, Mexico World View 2. MIP data processing. Spectral classes (Processing: clustering, classification) Spectral Classes Class 1 Class 2 Class 3 Class 4 Class 5 Class 6 Class 7 Class 8 Class 9 Class 10 Class 11 Class 12 Class 13 Class 14 Class 15 Class 16

10 Sea floor classification Yucatan World View 2 This image illustrates which or rather how many channels are available for each pixel: Cerdeira-Estrada et al. 2012

11 Qatar: Satellite derived bathymetry isoline map, Chart Datum Word View 2

12 Qatar: Satellite derived bathymetry isoline map, Chart Datum Word View 2

13 Validation examples at different sites worldwide Mexico, Australia, Gulf of Arabia, Indonesia. Sensors WordView, IKONOS, QuickBird Product generation by: EOMAP data processing system Bathymetry measurements from space, processed by MIP/EOMAP WV-2 in comparison with echo soundings Water depth [m] WV-2 / MIP N=4774 soundings R=0.98 RMS = 11% Water depth [m] (echo sounding)

14 Red Sea, Saudi Arabia Sensor WordView 2.Product generation by MIP

15 Red Sea, Saudi Arabia Sensor WordView Nov 6..Product generation by MIP Depth [m]

16 Reliability map and ongoing improvements of the depth calculation for small scale objects Sensor WordView 2.Product generation by MIP

17 Impact on product quality Bathymetry and benthic habitat mapping Sensor calibration, sensor artefacts, sensor noise Atmospheric condition, aerosols Recording geometry, sun glint In-water optical conditions Interference between in-water optical conditions and sea floor albedo Sea floor albedo properties, total portion of seafloor contribution Relation between spatial sensor resolution and spatial heterogeneity => Next step: Quantitative pixel based total quality estimates

Feasibility study and quality forecasts Bathymetry and benthic habitat mapping Coverage of AOI with archived suitable satellite data Calculation of sunglint probability estimates worldwide WV-2 meta

18 Feasibility study and quality forecasts Bathymetry and benthic habitat mapping Coverage of AOI with archived suitable satellite data Calculation of sunglint probability estimates worldwide WV-2 meta data archive Tasking optimization in collaboration with Digitalglobe Monitoring of turbidity in the target area using different satellite resources, up to several records per day Seasonal forecast based on MODIS time series

19 Partner network to improve service Bathymetry from space DIGITALGLOBE: High resolution satellite data provider EOMAP: Production PROTEUS: Worldwide sales Upcomming business models will reduce risks for clients Network of ground segments with fully automated EOMAP water quality processors on top

20 Conclusion Bathymetry from space ACCURACY: In comparison to validation data sets: RMS 8 30 % DEPTH RANGE: Clear water conditions: Intermediate conditions: 0 25 m 0 5 m RESTRICTIONS: Increased turbidity results in underestimation of water depth No retrieval possible under optical deep conditions (any depth) Visual quality control of multispectral remote sensing data still needed ADVANTAGE: Shallow water areas inaccessibly by echo-sounding are covered Wide coastal areas accessibly OUTLOOK: Synergy with radar methods to cover depth up to 80m also under turbid conditions

21 Advantages Bathymetry from space Product delivery in a fraction of time and for a fraction of costs in comparison to traditional methods for extended, also inaccessible areas in various spatial resolutions optimal in synergy with echo sounding or lidar surveys optimal in integration with further satellite data resources

22 Bathymetry from space: fusion optic/radar Synergethic water depth product using QuickBird and TerraSAR-X data Pleskachevsky et al. 2011

23 Bathymetry from space: fusion optic/radar Synergethic water depth product using QuickBird and TerraSAR-X data Pleskachevsky et al. 2011

24 THANK YOU

Satellite based inland and coastal water quality monitoring

Satellite based inland and coastal water quality monitoring Harmonized transnational, long-term and near-real time space based solutions. Thomas Heege CEO EOMAP Germany Earth Observation & Mapping Inland