IEEE IGARSSVancouver, July 27, 2011

Monitoring and Retrieving Rice Phenology by means of Satellite SAR Polarimetry at X-band

Juan M. Lopez-SanchezJ. David Ballester-Berman

Signals, Systems & Telecommunications GroupUniversity of Alicante

Shane R. Cloude

AEL Consultants

IEEE IGARSSVancouver, July 27, 2011

Motivation• Remote sensing for agriculture: a tool for management and

optimization of resources

End users Demand Objective

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 requirements Irrigation only when and where necessary

Final crop productivity Benefits

IEEE IGARSSVancouver, 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 IGARSSVancouver, July 27, 2011

Site

• Mouth of the Guadalquivir river, Sevilla (SW Spain)

30km x 30km

IEEE IGARSSVancouver, 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/m2, panicles/m2

• 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 IGARSSVancouver, July 27, 2011

Satellite data

2008

2009

TerraSAR-X images provided by DLR in the framework of projects LAN0021 and LAN0234

Failed orders

Available images

IEEE IGARSSVancouver, July 27, 2011

Analysis of observations• TerraSAR-X, 30 deg, 2009: Temporal evolution

HH VV HH-VV

IEEE IGARSSVancouver, 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 (H2α): Entropy and alpha– Model-based decomposition: Random volume + polarized term (rank1)

IEEE IGARSSVancouver, 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 (H2α): Entropy and alpha– Model-based decomposition: Random volume + polarized term (rank1)

2

2*

*2

200

0

0

HV

VVVVHH

VVHHHH

S

SSS

SSS

Single-pol (ERS, Radarsat1)

Quad-pol (ALOS-PALSAR, Radarsat-2)

Incoherent dual-pol (Envisat)

Coherent dual-pol (TerraSAR-X)

IEEE IGARSSVancouver, July 27, 2011

• Power

Analysis of observations vs phenologyHH and VV power

Wind induced roughness

Double-bounce

Vertical orientation:differential extinction

Development

Increasing randomness

Nearly random volume

Vegetative phase

Reproductive phase

Maturation

IEEE IGARSSVancouver, July 27, 2011

• Power

Analysis of observations vs phenology

HH and VV power HH / VV

Vegetative phase

Reproductive phase

Maturation Vegetative phase

Reproductive phase

Maturation

IEEE IGARSSVancouver, July 27, 2011

• Correlation between HH and VV

Analysis of observations vs phenology

Magnitude Phase (PPD)

Vegetative phase

Reproductive phase

Maturation Vegetative phase

Reproductive phase

Maturation

IEEE IGARSSVancouver, July 27, 2011

• Eigenvalue decomposition

Analysis of observations vs phenology

Entropy Alpha (dominant)

Vegetative phase

Reproductive phase

Maturation

Wind induced roughness

Double-bounce+

IEEE IGARSSVancouver, July 27, 2011

• Decomposition: Random volume + rank-1 mechanism

Analysis of observations vs phenology

Volume component Polarized component

Vegetative phase

Reproductive phase

Maturation Vegetative phase

Reproductive phase

Maturation

IEEE IGARSSVancouver, 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 IGARSSVancouver, July 27, 2011

Retrieval of phenology from TSX data• Basic retrieval approach with a single acquisition (TSX)

– Five phenological intervals

– Decision plane

IEEE IGARSSVancouver, July 27, 2011

Retrieval of phenology from TSX data• Retrieval results (parcel F)

IEEE IGARSSVancouver, 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 IGARSSVancouver, July 27, 2011

Retrieval of phenology from TSX data• Retrieval results in an area without external information

IEEE IGARSSVancouver, 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 IGARSSVancouver, 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 IGARSSVancouver, 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