Mapping small reservoirs in semi-arid regions using multitemporal SAR: methods and applications
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1 Mapping small reservoirs in semi-arid regions using multitemporal SAR: methods and applications Donato Amitrano Gerardo Di Martino Antonio Iodice Daniele Riccio Giuseppe Ruello University of Napoli, Italy Maria Nicolina Papa Francesco Mitidieri University of Salerno, Italy
2 outline motivations case study multitemporal approach
3 motivations The problem \\ semiarid climate Sahel region
4 motivations The problem \\ small reservoirs Used for Livestock Irrigation Groundwater recharge Human consumption Characteristics Small capacity (less than 1Mm 3 ) Low depth (rarely > 5m)
5 motivations The case study \\ Burkina Faso - population: 15 million - capital : Ouagadougou - life expectation: < 50 years Sahel region
6 motivations The user needs 1. DEM via Interferomatric processing 3. Hydrological modeling 2,E+04 Ouhigouya 2,E+04 1,E Surface water monitoring 5,E+03 0,E+00 02/10 04/10 06/10 08/10 10/10 model estimates 12/10 02/11 04/11 06/11 08/11 10/11 SAR estimates 12/11
7 motivations The approach 1. development of hydrologic models 2. development of remote sensing models 3. integration of models and generation of value added products 1. hydrologic models 3. integration and new product generation 2. remote sensing models
8 multitemporal approach Available dataset \\ The Cosmo SkyMed data The mission Constellation of 4 satellites, equipped with microwave high-resolution synthetic aperture radar (SAR) The products 16 stripmap images 3 m resolution HH polarization Stripmap 3m resolution 40 km coverage
9 Methodology multitemporal approach
10 multitemporal approach 1. DEM via Interferomatric processing 3. Hydrological modeling 2,E+04 Ouhigouya 2,E+04 1,E Surface water monitoring 5,E+03 0,E+00 02/10 04/10 06/10 08/10 10/10 model estimates 12/10 02/11 04/11 06/11 08/11 10/11 SAR estimates 12/11
11 1. Digital Elevation Model Input: appropriate SAR image pair Methodology: SAR Interferometry Original validation Goals : creation of DEM with improved resolution erosion estimation creation of 3D classification maps
12 DEM generation Master Image: Coherence Image: 28/
13 DEM generation N Interferometric fringes E Obtained DEM
14 Comparison with available DEMs Koumbri SRTM: resolution 90 m ASTER: resolution 30 m COSMO: resolution 9 m
15 Comparison with GPS points Point id GPS SRTM ASTER COSMO (3) 307 (-2) 312 (3) (4) 306 (-6) 314 (2) (1) 354 (-4) 356 (-2) (2) 327 (-6) 332 (-1)
16 A new DEM verification via amplitude measurements
17 2. Surface water monitoring Input: set of SAR images Methodology: spatial registration radiometric calibration multi-temporal image analysis Goals: erosion monitoring Inland water monitoring crop monitoring monitoring of reservoirs
18 Block diagram
19 Climate-guided RGB images June, 2011 August, 2011
20 Vegetation Bidi basin \\ Green band Bands: red: 27/03/2011 coherence green: 12/06/2010 tested image blue: 28/04/2011 dry season
21 Vegetation Goal: land cover monitoring Bidi basin \\ Green band Bands: red: 27/03/2011 coherence green: 12/06/2010 tested image blue: 28/04/2011 dry season
22 Vegetation Goal: land cover monitoring Green Bands: 12/06/ /07/2010
23 Vegetation Goal: land cover monitoring Green Bands: 12/06/ /07/ /08/2010
24 Vegetation Crop monitoring Goal: land cover monitoring Green Bands: 12/06/ /07/ /08/ /09/2010
25
26 Crop monitoring Available water volume monitoring
27 3. Hydrological modeling Input: SAR products Methodology: water balance supported by data acquired by multi-temporal SAR images Goals: Water availability monitoring crop monitoring monitoring of reservoirs
28 Modelling the time evolution of water storage A pseudo-probability of presence of seasonal water SWPP (Seasonal Water Pseudo- Probability) is defined as: RGB GT SWPP Mask SWPP = Gˆ B B + G G where Gˆ = 1 G 255
29 Modelling the time evolution of water storage
30 Derivation of the volumes- areas relationship Reservoir area estimates are more easy to obtain than volume estimates. The area-volume relation may be used in the area thanks to its homogenous morphology
31 conclusions Thank you Work opportunities and culture Value added products at no costs for populations
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