H2020 SENSAGRI project: developing prototypes for new Copernicus services for agriculture

Transcription

1 GEOINT for Environmental Compliance Assurance in rural areas/agriculture H2020 SENSAGRI project: developing prototypes for new Copernicus services for agriculture Antonio Ruiz Verdú University of Valencia IPL (Spain) The research leading to these results has received funding from the European Union s Horizon 2020 Research and Innovation Programme, under Grant Agreement no

2 Sentinels Synergy for Agriculture H2020 EO : Evolution of Copernicus services HORIZON 2020 Inspire Conference Antwerp (Belgium) 18/09/2018 1

3 SENSAGRI goals Combine Copernicus Sentinel-1 radar with Sentinel-2 optical and in-situ data, to develop new EO applications for the European agricultural sector Develop prototype Copernicus services of SSM, green and brown LAI and seasonal crop type mapping and use those for proof-of-concept services of advanced agricultural monitoring products Validate delivered services and establish service demonstration cases to show the large application potential of the new upstream data products Disseminate prototype and proof-ofconcept services and interact services with the agricultural sector HORIZON 2020 Inspire Conference Antwerp (Belgium) 18/09/2018 2

4 Positioning of SENSAGRI HORIZON 2020 Inspire Conference Antwerp (Belgium) 18/09/2018 3

5 Overview of SENSAGRI services Prototypes Surface soil moisture Green and brown LAI Seasonal crop mapping service Proof-of-concepts Dry Biomass and Yield Irrigated/not irrigated area Tillage change Added-value crop classification Background and methods Based on the SMOSAR SSM retrieval algorithm (CNR-ISSIA) developed for S1 mission. Based on ARTMO s retrieval toolboxes (UVEG), datasets from previous campaigns and from RTM simulations. Based on the Sen2-Agri service, improved to predict early crop mapping with the minimum ground truth reference data and integrating S1 data Background and methods Based on the use of a semi-empirical crop model (SAFYE-CO 2 ), S1 and S2 time series. Derived from the SSM product prototyped in WP3 Provided as a complementary product of the SMOSAR SSM product Detailed crop mapping based on currently operational service in Castillla y Leon region (ES) HORIZON 2020 Inspire Conference Antwerp (Belgium) 18/09/2018 4

6 Validation strategy Four European agricultural test sites Spain: ITACYL - Duero River-basin France: UPS-CESBIO - OSR Auradé and Lamasqère Italy: CREA/CNR - Apulian Tavoliere Poland: IPP/NRI Winna Góra Services Ground Variable Time Volumetric Soil Continuous monitoring SSM Moisture at 0-5 cm 3 measurement campaigns at critical depth stages and during irrigation season LAI Seasonal Crop Mapping Irrigated areas Tilled areas Yield Intermediate crops Leaf Area Index, with LAI-2000 Plant Canopy Analyzer Crop types Irrigated and not irrigated fields Tilled and not tilled fields Commercial yield Crop types 3 measurement campaigns at critical stages and during growing season 3 measurement campaigns in March, June and September 3 measurement campaigns in March, June and September 1 measurement campaign at crop harvest 2 measurement campaigns in March and July CLC agricultural classes. Source: EEA Three non-european test sites Argentina: INTA Hilario Ascasubi Two JECAM sites (South Africa and Ukraine) HORIZON 2020 Inspire Conference Antwerp (Belgium) 18/09/2018 5

7 Improvements to Copernicus SENSAGRI products Current Copernicus products Prototype services (widely applicable) Target Spatial resolution Surface soil moisture (SSM) m weekly* Green and brown LAI 20 m weekly* Target Temporal resolution Product Soil Water Index Surface Soil moisture (in dev) Leaf Area Index (Proba-V) Spatial resolution 0.1 (resolution grid) TBD Temporal resolution Daily TBD 300 m 10-daily Seasonal crop mapping 20 m** 2 or 3 per year None available Proof-of concept services (limited applicability outside test areas) Dry Biomass & Yield 20 m Dry biomass: weekly at season end Yield: yearly Dry matter productivity (SPOT-VGT, Proba-V) 1000 m 10-daily Irrigated/not irrigated area 100 m 3 or 4 per year Corine Land Cover (three classes) MMU of 5 to 25 ha bi-yearly yearly Tillage change 100 m 5 or 6 per year None available Added-value crop classification 10 m 2 or 3 per year Corine Land Cover (limited crop legend) MMU of 5 to 25 ha bi-yearly yearly * In ideal situation, i.e. in case of the two S1 and S2 satellites operational. Otherwise biweekly. ** 10 m spatial resolution shall be tested. HORIZON 2020 Inspire Conference Antwerp (Belgium) 18/09/2018 6

8 Soil Surface Moisture (SSM) SMOSAR processor. Algorithm based on Short Term Change Detection (STCD) approach using S1 S2 (NDVI) allows masking abrupt changes (harvest, fire ) At 1 km spatial resolution. Up to 100 m or higher if parcel map is available 12/09/2017 Land cover Time series of N-S1 IW Pre-processing: calibration, coregistration, multilooking, geocoding Soil texture map Masking block N-masked VV images Retrieving block Time series of N-SSM products HORIZON 2020 Inspire Conference Antwerp (Belgium) 18/09/2018 7

9 Soil Surface Moisture (SSM) S-1 SSM map on August, (520m pixel & ~1 km resolution) SSM average at field scale 0.05 m 3 /m Fused SSM product (50m pixel) HORIZON 2020 Inspire Conference Antwerp (Belgium) 18/09/2018 8

10 Leaf Area Index (LAI) LAI (green & brown) processor based on Gaussian processes regression (GPR) Initial validation: LAI green R 2 =0.89 and LAI brown R 2 =0.75 Maps produced with uncertainties and pixel classification CV = SD μ * 100 MASK Uncertainty threshold = CV<50 % GPR model LAI green µ [m 2 /m 2 ] SD [m 2 /m 2 ] CV [%] MASK CV<50% Composite map S2 image µ [m 2 /m 2 ] GPR model LAI brown SD [m 2 /m 2 ] CV [%] MASK CV<50% HORIZON 2020 Inspire Conference Antwerp (Belgium) 18/09/2018 9

11 Leaf Area Index (LAI) HORIZON 2020 Inspire Conference Antwerp (Belgium) 18/09/

12 Seasonal crop maps (Pan-European) Automatic supervised classification (Random Forest): S1+S2 + limited training data Seasonal maps during agricultural year (feb jun ago ) 20 m spatial resolution Sentinel s data Land cover map Binary crop mask Crop type map Supervised classification Cropland detection Supervised classification Reference data All classes Reference data Crop classes HORIZON 2020 Inspire Conference Antwerp (Belgium) 18/09/

13 Seasonal crop maps: Crop mask Crop Mask No Crop Recall (Italy 2017) Crop Mask Crop Recall (Italy 2017) Crop Mask Product (ROI Italy 2017) Corresponding Confidence Map Legend: Crop No Crop Legend: Hotmap from: 0% 100% HORIZON 2020 Inspire Conference Antwerp (Belgium) 18/09/

14 Seasonal crop maps: Crop type F-score for the Winter and spring class (Spain 2017 classifications) Crop Type Product (ROI Spain 2017) Legend: Corresponding Confidence Map Legend: Hotmap from: 0% 100% HORIZON 2020 Inspire Conference Antwerp (Belgium) 18/09/

15 Detailed crop maps (regional-national) Automatic supervised clasification (Data mining - ML): S1+S2 + ground truth (LPIS, CAP farmers applications PAC, LUCAS*, DEM ) Annual detailed maps of crop types and land use Operational in Castile and Leon región (94,200 km2). Tested in SENSAGRI core sites (France, Italy, Poland) * Land Use/Cover Area Frame Survey (EUROSTAT) HORIZON 2020 Inspire Conference Antwerp (Belgium) 18/09/

16 Detailed crop maps (regional-national) HORIZON 2020 Inspire Conference Antwerp (Belgium) 18/09/

17 Tillage change detection Multiscale thresholding approach applied to the temporal change of VH S1 backscatter of bare or scarcely vegetated fields (i.e. S2 NDVI < 0.3) 40 m spatial resolution Tillage / vegetation changes Left panel: overview of the cloud masked- NDVI map from S-2 on 18/05/2017, the VV S-1 image and the tillage or vegetation abrupt changes from VH S-1 changes (12-20/05/2017) at 40m. Right Panel: details over the Capitanata plain. HORIZON 2020 Inspire Conference Antwerp (Belgium) 18/09/

18 SSM contrast SSM contrast Irrigated/not irrigated area Based on the thresholding of the SSM contrast existing between irrigated fields and the surrounding area & ancillary information on the parcel boundaries. 1,9 1,7 Example irrigated alfalfa field irrigation dates 1,9 1,7 Example non-irrigated field CO = SSM field SSM 4x4 km scale 1,5 1,3 1,1 0,9 1,5 1,3 1,1 0,9 0,7 0,7 0,5 10/5 9/6 9/7 8/8 7/9 7/10 dates 0,5 10/5 9/6 9/7 8/8 7/9 7/10 dates HORIZON 2020 Inspire Conference Antwerp (Belgium) 18/09/

19 Biomass / crop yield Proof-of-concept. SAFYE-CO2 model LAI maps (or FAPAR) Images (NDVI) Radiative transfer Model Or empirical relationship Crop species maps Meteorological Data (SAFRAN, ERA-INTERIM) Soil texture Maps (optional) 8 km SAFYE-CO 2 Monteith + FAO56 Veloso 2014 Biomass, yield, irrigation LAI (comparing simulation/obs) Validation with regional statistics (yield /irrigation), farmers network, intensive field campaigns Validation with eddy-covariance data Fluxes /budgets CO 2 et H 2 O Mapping soil water holding capacity/ validation with geophysical data HORIZON 2020 Inspire Conference Antwerp (Belgium) 18/09/

20 Summary H2020 SENSAGRI ( ) is developing and validating three prototypes for Copernicus Pan-European Land core services, for agricultural applications Surface soil moisture (SSM), green and brown LAI and seasonal crop type mapping prototypes are based in the combined use of Sentinel-1 and Sentinel-2 Four proof-of-concept for agricultural monitoring services are also being developed and validated: Regional-national detailed crop maps, tillage change detection, actual irrigation and yield estimation HORIZON 2020 Inspire Conference Antwerp (Belgium) 18/09/

21 GEOINT for Environmental Compliance Assurance in rural areas/agriculture H2020 SENSAGRI project: developing prototypes for new Copernicus services for agriculture Antonio Ruiz Verdú University of Valencia IPL (Spain) The research leading to these results has received funding from the European Union s Horizon 2020 Research and Innovation Programme, under Grant Agreement no