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Kussul Nataliia, Shelestov Andrii, Skakun Sergii Space Research Institute of NAS of Ukraine and SSA of Ukraine Kyiv National University of Environmental and Life Science WGISS-37, 14-28 April 2014, Cocoa-Beach, Florida, USA SSAU: JECAM & GEOGLAM activities – big data challenge
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Cocoa- Beach 2014 JECAM-test sites in Ukraine Test sites (officially established in 2011) –Kyiv oblast (SRI) Crop area estimation In-situ measurements –crop types, along the roads and segment surveys –Lviv oblast (The State Science- Technological Centre of Soil Fertility Protective) Crop rotation identification –Pshenychne (National University of Life and Environmental Sciences of Ukraine) Biopar parameters retrieval and crop growth model calibration In-situ measurements –crop types, crop height, LAI, fCover, soil parameters Administrative map of Ukraine and location of Kyiv and Lviv region Map of intensive observation sub-site Relationship between humus and satellite-derived biomass
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Cocoa- Beach 2014 Crop mapping: Ukraine Crop mixture (winter,spring,summer), important minor crops Uneven crop proportions distribution Large territory – big data problem
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Cocoa- Beach 2014 Ground data availability Crop type ~5500 fields: May 2013 (2000 fields); August 2013 (3000 fields); March 2014 (500 fields) Crop state (DHP) –~20 fields –30 ESU, 3 times per season –LAI, fAPAR, fCover Crop damage –~50 fields
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Cocoa- Beach 2014 ESA Sentinel-2 for Agriculture, 2013 Satellite data –SPOT4 (17 images, 8 cloud&snow free) –RapidEye (29, images, 7 cloud&snow free) –RADARSAT2 (12 images) –Landsat -8 (4 images) Ground data (June) –320 fields (crop type) –Maize (30%) –Wheat (20%), Soya(20%) –Sunflower (10%) –Rapeseed (2.5%) –Barley (2%)
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Cocoa- Beach 2014 Preprocessing for classification 1. Conversion to top-of- atmosphere (TOA) reflectance. 2. Atmospheric corrections (from TOA to surface reflectance (SR)) using the SMAC model 3. Clouds and shadows identification 4. Filling in missing data due to cloud and shadow areas (restoration).
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Cocoa- Beach 2014 Crop map for Kyiv oblast (2013), overall accuracy 86%
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Cocoa- Beach 2014 Validation of global products For JECAM test site in Ukraine Within FP7 ImagineS (Dr. Roselyne Lacaze HYGEOS,FRANCE) Follows ESA VALERI protocol (30 ESU – elementary sampling units) compliant with CEOS Land Product Validation (LPV) guidelines CAN-EYE software Biophysical parameters: LAI, FAPAR, FCover
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Cocoa- Beach 2014 LAI maps derived from Landsat- 8, SPOT-4 and RapidEye
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Cocoa- Beach 2014 LAI (RapidEye, NDVI) vs. LAI (SPOT5, transfer function) RapidEye, 11.06.2013 SPOT5, 15.06.2013 These values are correspondent to village and road Ejection Mask
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Cocoa- Beach 2014 Plans –Winter & summer crop maps PROBA-V, MODIS Sentinel-1 and Landsat-7,8, Sentinel-2 3 oblasts (NUTS2) validated, whole Ukraine – provisional –More research in 2014 on the assessment of integration of SAR and optical images for crop mapping in Ukraine. –Special attention will be paid to sequential crop mapping, i.e. producing crops as satellite images become available.
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Cocoa- Beach 2014 Thank you!
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