IEEE IGARSS Vancouver, July 27, 2011 Monitoring and Retrieving Rice Phenology by means of Satellite SAR Polarimetry at X-band Juan M. Lopez-Sanchez J. David Ballester-Berman Signals, Systems & Telecommunications Group University of Alicante Shane R. Cloude AEL Consultants

IEEE IGARSS Vancouver, July 27, 2011 Motivation Remote sensing for agriculture: a tool for management and optimization of resources End usersDemandObjective Authorities or agencies at national-regional-local level Crop-type mapping and classification Justification of subsidies, fraud detection, acreages, insurance claims, etc. Water resources consumption Control in regions suffering droughts or with scarce water resources Yield prediction Economic and market predictions, price regulations, etc. Farmers with extensive fields Timely information about crop condition Planning and triggering of farming practices according to specific phenological stages Water requirementsIrrigation only when and where necessary Final crop productivityBenefits

IEEE IGARSS Vancouver, July 27, 2011 Motivation Motivation: examples of known demands from rice farmers in Spain – Timely information for: Effective germination measurements When all plants have emerged they count their number. If low, more seeds are added Nitrogen fertillization stop Once all panicles in a field have appeared, fertilization is not longer needed Excessive fertilization may cause an increase in pests – Detection of cultivation problems due to water salinity: areas with delayed development Objective: Is it possible to retrieve the current phenological stage from a single acquisition? Approach: – Analysis and interpretation of the polarimetric behavior of rice at different phenological stages – If possible, proposal of a retrieval approach based on scattering properties

IEEE IGARSS Vancouver, July 27, 2011 Site Mouth of the Guadalquivir river, Sevilla (SW Spain) 30km x 30km

IEEE IGARSS Vancouver, July 27, 2011 Ground campaign Campaigns: 2008 and 2009 Ground measurements over 5-8 parcels provided by the local association of rice farmers (Federación de Arroceros de Sevilla) – Weekly (defined at field level): Phenology: BBCH stage (0-99) Vegetation height – Additional information: Sowing and harvest dates Plantation density: plants/m 2, panicles/m 2 Yield (kg/ha) Important: – A water layer is always present at ground during the campaign – Sowing is carried out by spreading seeds (from a plane) randomly over flooded fields

IEEE IGARSS Vancouver, July 27, 2011 Satellite data TerraSAR-X images provided by DLR in the framework of projects LAN0021 and LAN0234 Failed orders Available images

IEEE IGARSS Vancouver, July 27, 2011 Analysis of observations TerraSAR-X, 30 deg, 2009: Temporal evolution HH VV HH-VV

IEEE IGARSS Vancouver, July 27, 2011 Coherent acquisition of co-pol channels Analysis of observations TerraSAR-X HHVV dual-pol images: List of observables – Backscattering coefficients and HH/VV ratio – Backscattering coefficients at the Pauli basis (HH+VV, HH-VV) – Correlation between HH and VV: magnitude and phase (PPD) – Correlation between 1st and 2nd Pauli channels: mag. and phase – Eigenvector decomposition (H2  ): Entropy and alpha – Model-based decomposition: Random volume + polarized term (rank1)

IEEE IGARSS Vancouver, July 27, 2011 Coherent acquisition of co-pol channels Analysis of observations TerraSAR-X HHVV dual-pol images: List of observables – Backscattering coefficients and HH/VV ratio – Backscattering coefficients at the Pauli basis (HH+VV, HH-VV) – Correlation between HH and VV: magnitude and phase (PPD) – Correlation between 1st and 2nd Pauli channels: mag. and phase – Eigenvector decomposition (H2  ): Entropy and alpha – Model-based decomposition: Random volume + polarized term (rank1) Single-pol (ERS, Radarsat1) Quad-pol (ALOS-PALSAR, Radarsat-2) Incoherent dual-pol (Envisat) Coherent dual-pol (TerraSAR-X)

IEEE IGARSS Vancouver, July 27, 2011 Power Analysis of observations vs phenology HH and VV power Wind induced roughness Double-bounce Vertical orientation: differential extinction Development Increasing randomness Nearly random volume Vegetative phase Reproductive phase Maturation

IEEE IGARSS Vancouver, July 27, 2011 Power Analysis of observations vs phenology HH and VV powerHH / VV Vegetative phase Reproductive phase Maturation Vegetative phase Reproductive phase Maturation

IEEE IGARSS Vancouver, July 27, 2011 Correlation between HH and VV Analysis of observations vs phenology MagnitudePhase (PPD) Vegetative phase Reproductive phase Maturation Vegetative phase Reproductive phase Maturation

IEEE IGARSS Vancouver, July 27, 2011 Eigenvalue decomposition Analysis of observations vs phenology EntropyAlpha (dominant) Vegetative phase Reproductive phase Maturation Wind induced roughness Double-bounce +

IEEE IGARSS Vancouver, July 27, 2011 Decomposition: Random volume + rank-1 mechanism Analysis of observations vs phenology Volume componentPolarized component Vegetative phase Reproductive phase Maturation Vegetative phase Reproductive phase Maturation

IEEE IGARSS Vancouver, July 27, 2011 Retrieval of phenology from TSX data Basic retrieval approach with a single acquisition (TSX) – Four parameters HHVV coherence and phase difference Entropy and alpha1

IEEE IGARSS Vancouver, July 27, 2011 Retrieval of phenology from TSX data Basic retrieval approach with a single acquisition (TSX) – Five phenological intervals – Decision plane

IEEE IGARSS Vancouver, July 27, 2011 Retrieval of phenology from TSX data Retrieval results (parcel F)

IEEE IGARSS Vancouver, July 27, 2011 Retrieval of phenology from TSX data Retrieval results: Comparison against ground data – Percentage of pixels assigned to each stage within a parcel Parcel B Parcel C

IEEE IGARSS Vancouver, July 27, 2011 Retrieval of phenology from TSX data Retrieval results in an area without external information

IEEE IGARSS Vancouver, July 27, 2011 Retrieval of phenology from TSX data Comments on the approach – Useful tracking of phenology: At parcel level: BBCH agrees with the stage assigned to the majority of pixels inside the parcels (with some exceptions) At (multi-looked) pixel level: parts with different development within a parcel are well identified – But not perfect.. The algorithm is very ‘simple’: parameters and thresholds have been selected manually (it could be optimized) An ambiguity between plant emergence (BBCH 18-21) and last stages (BBCH +50) is still present at some areas. Both are characterized by high entropies

IEEE IGARSS Vancouver, July 27, 2011 Conclusions Coherent dual-pol data provided by TerraSAR-X have been useful for retrieving phenology of rice fields with a single acquisition – Advantages when compared to other possible approaches: 11-days revisit rate with the same sensor & mode High spatial resolution Retrieval with a single pass is possible (single-pol and incoherent dual-pol are not enough) – Limitations: There remain some ambiguities that might be solved with full-pol data (e.g. using anisotropy), but not in operational mode with TSX Low coverage: TSX dual-pol swath is 15 km on ground Some measurements are below or close to the noise level of TSX (-19 dB)

IEEE IGARSS Vancouver, July 27, 2011 Future lines of research Multi-temporal approaches (time series) – Time coordinate provides extra information Multi-angular (and multi-temporal) integration – Ideal to reduce refresh time or increase spatial coverage Development of an operational scheme with farmers Pending issues: – Presence of rain – Other species within the rice fields (mixture) Application to rice under different farming practices: – Plantation procedures and arrangements – Dry ground at some moments