ontheuseofmultitemporalseriesofcosmodataforclassificationandsurfaceparameterretrievaloveragriculturalsites.ppt...

2011 IEEE International Geoscience and Remote Sensing Symposium, Vancouver, Canada, 24-29 July 2011

Politecnico di Bari Dipartimento di Ingegneria delle

Acque e di Chimica


Acque e di Chimica

Università degli Studi di Napoli Federico II

Dipartimento di Ingegneria Agraria ed Agronomia del

Territorio



Territorio

“On the use of multi-temporal series of COSMO-SkyMed data for LANDcover classification and surface parameter

retrieval over agricultural sites (COSMOLAND)”Anna Balenzano (1), Giuseppe Satalino (1), Antonella Belmonte (1), Guido

D’Urso (2), Fulvio Capodici (2), Vito Iacobellis (3), Andrea Gioia (3), Michele Rinaldi (4), Sergio Ruggieri (4) and Francesco Mattia (1)

(1) Consiglio Nazionale delle Ricerche (CNR) – Istituto di Studi sui Sistemi Intelligenti per l’Automazione (ISSIA), Bari, Italy

(2) Dipartimento di Ingegneria Agraria e Agronomia del Territorio - Università Federico II (UniNa)

(3) Politecnico di Bari (PoliBa) – Dipartimento di Ingegneria delle Acque e di Chimica (4) Consiglio per la Ricerca e la Sperimentazione in Agricoltura, Unità di Ricerca sui Sistemi Colturali per

Ambienti Caldo-Aridi (CRA-SCA)

Acknowledgement: the research is supported by the Italian Space Agency under contract I/051/09/0. COSMO-SkyMed data were provided by ©ASI in the framework of ©CSK AO 2161. SPOT data were obtained from CNES (2010) Distribution Spot Image ISIS-368



Acque e di Chimica


Acque e di Chimica



Territorio



Territorio

to present the activities carried out during the first year of COSMOLAND project on land cover classification and the retrieval of surface parameters (i.e. Leaf Area Index and soil moisture content) using temporal series of COSMO-SkyMed data

Objective

Application context COSMO SkyMed & ground data collected over an agricultural site, Foggia (Italy), during the COSMOLAND campaign in 2010 Sensitivity of multi-temporal X band SAR data to crops:

classification algorithm

Sensitivity of multi-temporal X band SAR data to vegetation and soil moisture content

Leaf Area Index retrieval algorithm Soil moisture content retrieval algorithm (SMOSAR algorithm)

Summary and future work

Outline



Acque e di Chimica


Acque e di Chimica



Territorio



Territorio

Application context

Crucial information for the land process model performances:

Land use maps (at medium/low resolution, e.g. monthly)

Leaf area index maps(at high temporal resolution, e.g. weekly)

Soil moisture content maps (at high/very high temporal resolution during alert periods, e.g. daily or hourly)

The project intends to contribute to the COSMO-SkyMed objectives in agriculture and hydrology application domains, combining SAR-derived information and hydrological/crop growth models to improve land and water resource managment.

A limitation of land process models is the need for numerous input parameters, which are seldom available at the appropriate temporal scale. This lack of information often leads to erroneous model predictions.

COSMO-SkyMed constellation characterized by a short revisiting time gives a chance to monitor the surface parameters at high temporal resolution and to demonstrate the use of EO data for improving land process model forecasts



Acque e di Chimica


Acque e di Chimica



Territorio



Territorio

Puglia

Product derived from SPOT images (2010)

2010 COSMOLAND campaign over Foggia (Italy)

Classified image from multi-temporal SPOT data (Maximum likelihood algorithm on SPOT4 04/07/2010, 25/07/2010).

Overall accuracy in test: 95% for the test fields

In situ measurements from March to September:

soil moisture with gravimetric method fresh & dry biomass, plant density and height, Leaf Area Index, yield

Foggia site (Apulia region)

Series of 1C-Geocoded Ellipsoid Corrected COSMO Sky-Med StripMap PingPong products

Main crops (% of cultivated area):

Wheat (48%) Sugar beet (3%)

Tomatao ( 7%) Vineyard (8%)

Olives ( 5%)




Olives ( 5%)




Olives ( 5%)

Main crops of the area of approx. 700km2


Tomato ( 8%) Vineyard (4%)

Olives ( 4%)

Limitation: lack of planned dense temporal series of COSMO SkyMed data (average revisiting time ∆T=18 days)

8

8

16

40

8

24

24

∆T

HH/HV26StripMap PP0209/08/10D8








PolarizationMean incidence angle [°]

Mode swathDateID



Acque e di Chimica


Acque e di Chimica



Territorio



Territorio

RGB compositions of the COSMO HH images (left) and of HV images (right) over Foggia. R: 20100403, G:20100427, B:20100521

Sensitivity of multi-temporal X band data to crops

Product derived from original COSMO-SkyMed products ©ASI- Agenzia Spaziale Italiana (2010)

Temporal X-band backscatter signature of crops is significantly different and provides useful information for classification.

HH pol. HV pol.



Acque e di Chimica


Acque e di Chimica



Territorio



Territorio

Accuracy of the land use classification using multi-temporal COSMO data over Foggia in 2010

Overall classification accuracy of multi-temporal, single/multi-polarization COSMO images vs the number of the SAR images

T es t

50

60

70

80

90

100

1 2 3 4 5 6 7 8

N r images

H H

H V

H H H V

Product derived from original COSMO-SkyMed products ©ASI- Agenzia Spaziale Italiana (2010)

Land use image from COSMO ping-pong Strip Map HH+HV (acquisition dates 03/04/10, 21/05/10, 08/07/10, 09/08/10 )

Details in Satalino et al., Proc. of Multitemp, July 2011

Overall classification accuracy of multi-temporal, single/multi-polarization COSMO images vs the number of the SAR images

T es t

50

60

70

80

90

100

1 2 3 4 5 6 7 8

N r images

H H

H V

H H H V

Based on the Maximum Likelihood algorithm

T es t

50

60

70

80

90

100

1 2 3 4

N r images

H H

H V

H H H V

Temporal information during the growing season is important to improve the crop classification accuracy.

Overall classification accuracy of selected (close to the time of full development of crops) multi-temporal, single/multi-polarization COSMO images vs the number of the SAR images



Acque e di Chimica


Acque e di Chimica



Territorio



Territorio

Temporal behaviour of E-SAR σ0 at X-band (HH polarization and 33° incidence angle) and mv and 1/fb of wheat field (N=11)

Sensitivity of X band backscatter to soil moisture (mv) and vegetation of wheat fields

The radar signal is strongly affected by the canopy, which attenuates the backscatter and reduces the sensitivity to the soil moisture.

X band SAR data are suited to retrieve vegetation parameters (fb&LAI) of wheat fields and soil moisture content over low vegetated or bare soils.

soil moisture fresh biomass

0.55 (< 7.8%) -0.77 (<0.6%)Correlation coefficients

X band

data set collected during the ESA AgriSAR 2006 campaign, DEMMIN site (Germany):

dense temporal series of X band E-SAR data from April to August

well-documented ground data



Acque e di Chimica


Acque e di Chimica



Territorio



Territorio

Empirical approach for Leaf Area Index retrieval

The rmse is 1.1 m 2/m 2 for LAI derived by COSMO SkyMed data.

29/05/2010

2 LAI [m2/m2 ] 6

The rmse is 0.8 or 1.0 m2/m2 using LAI derived by SPOT or MERIS data acquired over Foggia from 2006 to 2008

y = -0.28x + 0.32

R2 = 0.69

0

1

2

3

4

5

-20 -15 -10 -5

Backscatter [dB]

LA

I [m

2/m

2]

Experimental relationship between LAI and backscatter of wheat field (derived by the ESA AgriSAR’06

campaign data set)

Example of LAI map obtained applying the experimental

relashionship to 2010 COSMO data over Foggia



Acque e di Chimica


Acque e di Chimica



Territorio



Territorio

Soil moisture retrieval based on σ0 temporal changes using dense time series of SAR data

The alpha approximation is appealing as it simplifies the backscatter ratio between two subsequent and closed SAR observations into a quantity that depends only on soil moisture changes (θ constant)

Soil roughness and vegetation from DoY → DoY+1 constant (e.g. 1 week revisiting time)

s0

20 στσ ≈

( )( )

( )( ) 2

2

1

0

10

,

,

doy

rpp

doy

rpp

doy

doy

εϑα

εϑα

σσ ++ ≈

( ) [ ]22sincos

)1(,

ϑεϑ

εϑεα−+

−=r

rr

HH

dominant scattering mechanism:

The rational of this approach is that temporal changes of soil roughness and vegetation take place at longer temporal scales than soil moisture changes

soil scattering

soil attenuated by the canopy

s00 σσ ≈

( ) ( )ACFlsFrpp

s ,,,,2

0 ϑεϑασ •= SPM & SSA & PO



Acque e di Chimica


Acque e di Chimica



Territorio



Territorio

Quantitative retrieval of mv

N SAR acquisitions ⇒ N-1 linear equations in N unknown αpp coefficients

( )( ) ji

idoy

jdoy S=)(0

)(0

σσ

( ) ( ){ } 0,, )()( =−kidoy

rppjijdoy

rpp SS εϑαεϑα

1+= ij11 −≤≤ Ni

11 −≤≤ Nk

Under determined linear system ⇒ infinite number of solutions

Solution found through Least Square minimization subject to the linear constraints:

( ) maxmin , ppr

pppp αεϑαα ≤≤Details in Balenzano et al., IEEE JSTARS 2011



Acque e di Chimica


Acque e di Chimica



Territorio



Territorio

Soil moisture maps over bare fields of Foggia site using COSMO data at HH pol. in 2010

Doy 205 Doy 213

Rain event on DoY 212

A quantitative assessment of the soil moisture retrieval accuracy comparing retrieved and hydrologically modeled m v maps is in progress



Acque e di Chimica


Acque e di Chimica



Territorio



Territorio

Fast Delivered mv maps

Off-line processor Averaging procedure

Precision mv - error maps

On-line processor

Retrieving block Masking block N-masked Co-Pol images

Time series of N-mv maps

Time series of N-SAR images

Cross-Pol SAR images

Co-Pol SAR

images

Inc. angles images

NDVI maps

Land cover maps

Texture maps

Ancillary data

N-FD mv maps of the same DoY

1-P mv map & 1-error map of the same DoY

SMOSAR transforms dense time series of N SAR images into N-m v maps over agricultural areas with vegetation cover not dominated by volume scattering

SMOSAR (Soil Moisture retrieval

from multi-temporal SAR data) algorithm based on the alpha

approximation

European Space Agency project "GMES Sentinel-1 Soil Moisture Algorithm Development“poster section in area K on Wed.



Acque e di Chimica


Acque e di Chimica



Territorio



Territorio

II year of the COSMOLAND project: validation of the retrieval/classification algorithms and assessment of the improvement due to the coupling of the land process models with SAR-derived information

Summary

Future work

classification, LAI and soil moisture retrieval algorithms, based on

maximum likelihood, empirical approach and temporal backscatter changes, respectively, have been illustrated and applied to temporal series of X band SAR data the experimental data set consists of 8 COSMO SkyMed images, at HH/HV polarization, acquired in 2010 over an agricultural site in Italy.

Results show that: classification accuracy improves as a function of the number of the SAR images. Accuracy of 87% when 4 COSMO images on dates close to the full development of crops are used. potential to retrieve LAI of wheat fields and soil moisture content of bare or low vegetated soils using multi-temporal SAR data at X band

ontheuseofmultitemporalseriesofcosmodataforclassificationandsurfaceparameterretrievaloveragriculturalsites.ppt...

Technology

ingegneria delle acque

ingegneria agraria e

bari dipartimento

napoli federico iidipartimento

bari poliba dipartimento

ricerca e

chimicauniversit degli

cosmoskymed data