CHRIS / PROBA Data Analysis at the Swiss Midlands Testsiteearth.esa.int/workshops/4th_chris_proba/CHRIS_WS4_KNEUBUHLER.… · 4th CHRIS / PROBA Workshop Frascati 19 - 21 September

CHRIS / PROBA Data Analysis at theSwiss Midlands Testsite

4th CHRIS / PROBA WorkshopFrascati

19 - 21 September 2006

Mathias Kneubühler, RSL, Univ. Zürich, CHBenjamin Koetz, Silvia Huber, Juerg Schopfer,

Rolf Richter, Klaus Itten

Outline

• Description of test site and field data• Research goals at the Swiss midlands test site• Anisotropy in multiangular vegetation data• Available CHRIS data sets

• Data processing• Geometric and atmospheric correction

• Data analysis• Spectrodirectional variation in vegetation over time (phenology)

• Conclusions and outlook

Site Description

• Swiss Midlands Testsite• Hilly area dominated by agricultural fields in the

lower parts and mixed forests mainly on the hilltops• Two main test sites within the scene

• Agricultural test site (barley, maize, wheat, sugar beet)• Forest test site (core test site for the Long-term

Forest Ecosystem Research Programme (LWF)of the Swiss Federal Institute for Forest, Snow andLandscape Research (WSL)

• Various data sets since 2004:HyMap, CHRIS, SPOT-5, ADS-40, Lidar

Forest test siteForest test site

Agricultural Agricultural test sitetest site

Research Goals at the Swiss Midlands Test Site

• AgricultureAssess the spectro-directional information contained in a multitemporal set of CHRIS data over an agricultural area.The spectro-directional behaviour of crops varies over time as a function of vegetation stages (phenology).

• ForestInvestigate if the added information in multi-angular data improves biochemistry retrievalInvestigate if certain view angles emerge to be superior for forest biochemical retrieval

• (Inter-) Calibration / Validation of Leica Geosystems ADS-40 Airborne Digital Sensor (nadir, forward and backward looking RGB and NIR channels) with CHRIS.

Anisotropy in Multiangular Data

• Reflectance of a vegetation canopy is primarily a function of foliage optical properties, canopy structure, illumination conditions and viewing geometry.

• Multiangular measurements have shown the potential to distinguish different land cover and surface types of different structural characteristics [Barnsley et al., IEEE TGARS 42(7), 2004].

• Multiangular measurements in agriculture contain crop specific information that varies over time as a function of phenology.

• In the red, the directional pattern of solar radiation scattered byvegetation is largely controlled by the plants’ physical properties and geometrical arrangements [Pinty et al.,IEEE TGARS 40(7), 2002], [Widlowski et al., Climatic Change 76(2-3), 2004].

• The degree of anisotropy can be described by e.g. the Minnaert function parameter k in the parametric RPV model [Rahman et al., JGR 98, 1993]

• Heterogeneous canopies of medium density over a bright backgroundshow a bell-shaped Bidirectional Reflectance Factor in the red domain.

CHRIS Acquisitions 2005

CHRIS AcquisitionMode 5 Quality Used scenes

(agriculture)

26 May 2005 5 angles,-55 mispointing +55°, +36°, 0°, -36°

20 June 2005 5 angles,-55°, +55° mispointing +36°, 0°, -36°

+55°

+36°, 0°, -36°, -55°

+55°

+55°, +36°, 0°,-36°, -55°

+55°, +36°, 0°,-36°, -55°

21 June 2005 5 angles, haze

15 July 2005 5 angles, partly cloudy,+55° cloud covered

16 July 2005 3 angles, -36° and -55°missing, partly cloudy

17. August 2005 5 angles

22. September 2005 5 angles

Corresponding Ground TruthCorresponding Ground Truth

-- Spectroradiometric Spectroradiometric measurementsmeasurements

-- LAILAI (maize, winter barley,(maize, winter barley,forest stands)forest stands)

-- Leaf water contentLeaf water content-- Absolute Absolute chlchl. content. content-- Relative Relative chlchl.. content (SPAD)content (SPAD)-- Phenological Phenological characterizationcharacterization-- Land cover mappingLand cover mapping

Agricultural Test Site: Maize

26 May 200526 May 2005 20 June 200520 June 2005

15 July 200515 July 2005 17 August 200517 August 2005

*15 July data processed, but not yet included in this presentati*15 July data processed, but not yet included in this presentation on

Agricultural Test Site: Winter Barley

26 May 200526 May 2005 2020 June 2005June 2005

15. July 200515. July 2005

*15 July data processed, but not yet included in this presentati*15 July data processed, but not yet included in this presentation on

Geometric Processing

• Parametric GeocodingUse of a 3D physical model (parametric approach) [Toutin 1985, 1992] as implemented in PCI / Geomatica

• A physical model can mathematically describe all distortions of• the platform (position, velocity, orientation)• the sensor (view angles, IFOV, panoramic effect)• the Earth (ellipsoid, relief)• the cartographic projection

• Needs orbit and sensor information and a small number of GCP’s to compute / refine the parameters of the mathematical model

• Number of GCP’s depend on orbit and sensor information availability, GCP accuracy and final expected accuracy (iterative least-square method)

Parametric Geocoding Information

Typical information required for parametric geocoding approach:

• Orbit and sensor information [Barnsley et al. IEEE TGARS Vol. 42(7), 2004] or TLE Data from e.g., http://www.space-track.org• Sensor altitude• Orbital period• Eccentricity• Actual inclination• Across and along track angle (HDF info)• IFOV

• Imge information• Pixel spacing• Approx. scene centre• Ellipsoid (DEM)

Geometric Processing

Geocorrected Geocorrected subset of the 26 May 2005 CHRISsubset of the 26 May 2005 CHRISnadir scene with overlying pixel mapnadir scene with overlying pixel map(1:25(1:25’’000,000, ©© swisstoposwisstopo))

CHRIS scene RMS X RMS Y RMS mean

26 May 05 0.76 0.74 1.12

20 June 05 1.37 1.01 1.95

15 July 05 0.29 0.33 0.44

17 August 05 0.73 0.62 0.99

22 September 05 1.02 1.28 1.67

Mean Mean rms rms errors of all CHRIS scenes per errors of all CHRIS scenes per acquisition dateacquisition date

A: maizeA: maizeB: winter barleyB: winter barley

Accurate Accurate geolocation geolocation is a prerequisite foris a prerequisite formultitemporal multitemporal studies on smallstudies on small--scale scale testsites.testsites.

CHRIS Image Acquisition Geometry

CHRIS Mode 5 FZA +55° FZA +36° FZA 0° FZA -36° FZA -55° Solar zen./az.

Obs. zen. 50.61 29.70 -8.83 -34.65 -54.01;26 May 2005

Obs. az.* 187.35 79.91 44.82 24.68 20.26;

Obs. zen. 54.08 31.89 -3.90 -37.43 -57.25;20 June

2005

15 July2005

17 August 2005

22 September

2005

Obs. az.* 192.90 192.50 22.32 14.37 14.37;

Obs. zen. 53.35 31.40 -9.76 -36.65 -55.69

Obs. az.* 196.06 205.37 321.31 1.00 6.88

Obs. zen. 50.82 34.59 -24.79 -38.12 -53.52

Obs. az.* 209.40 218.80 316.56 337.28 350.79

Obs. zen. 52.97 33.29 16.70 -37.95 -56.27

Obs. az.* 181.80 168.82 135.06 31.84 25.25

-46.90 / 171.70

-35.88 / 153.31

-28.00 / 152.00

-25.37 / 157.26

-27.10 / 162.94

* sensor to target viewing direction,* sensor to target viewing direction, negative observation zenith isnegative observation zenith is a sensor position in the south,a sensor position in the south, ; agricultural test sites not covered ; agricultural test sites not covered

CHRIS Image Acquisition Geometry

17 August 200517 August 2005

QuickTime™ and a decompressor

are needed to see this picture.

HotHot--spot constellationspot constellation

Atmospheric Processing

• Atmospheric correction of the CHRIS radiance data is performed using ATCOR2/3 [Richter, Applied Optics 37, 1998], which is based on MODTRAN-4

• Different CHRIS modes are implemented in ATCOR2/3

• ATCOR3 is a radiative transfer code for atmospheric correction of optical spaceborne sensors, including the option to process tilted sensors (accounts for varying path length and transmittance)

• ATCOR3 supports atmospheric correction over rugged terrain by including digital elevation models (elevation, slope, aspect, sky view factor, cast shadow)

Geocorrected CHRIS Subset

Nadir scene, 26 May 2005


Nadir scene, 22 June 2005


Nadir scene, 15 July 2005


Nadir scene, 17 August 2005


Nadir scene, 22 September 2005

Results - Temporal Changes in Canopy Reflectance

CHRIS nadir reflectances for maize (HDRF Hemispherical Directional Reflectance Factor)

22/09/2005

20/06/200517/08/2005

26/05/2005

17/08/200517/08/2005

20/06/200520/06/2005

26/05/200526/05/2005

*15 July data not yet included*15 July data not yet included

Results - Temporal Changes in Canopy Reflectance

CHRIS nadir reflectances for winter barley (HDRF Hemispherical Directional Reflectance Factor)

22/09/2005

26/05/2005

20/06/2005

17/08/2005

Bare soil after harvestBare soil after harvest

GrassGrass

26/05/200526/05/2005

20/06/200520/06/2005


Results - Multiangular Behaviour of Canopy Reflectance

HDRF data for maize, 17 August 2005

FZA -36°FZA -55°

FZA +55°FZA 0°FZA +36°

•• FZA = FZA = --3636°° shows highestshows highestreflectance values (closest toreflectance values (closest tohotspot)hotspot)

•• FZA = +36FZA = +36°° and FZA = +55and FZA = +55°°(forward scatter direction) are(forward scatter direction) aredarkest in VIS [Bach et al.,darkest in VIS [Bach et al.,3rd CHRIS / PROBA WS, 2005]3rd CHRIS / PROBA WS, 2005]



HDRF data for winter barley, 26 May 2005

FZA -36°FZA +55°FZA +36°FZA 0°

•• FZA = FZA = --3636°° shows highestshows highestreflectance values (closest toreflectance values (closest tohotspot)hotspot)

•• FZA = +36FZA = +36°° and FZA = +55and FZA = +55°°(forward scatter direction) are(forward scatter direction) aredarker than backward scatterdarker than backward scatteranglesangles

•• In the NIRIn the NIR region, increasedregion, increasedmultipe multipe scattering within thescattering within thecanopy for larger FZA maycanopy for larger FZA mayincrease HDRFincrease HDRF in forwardin forwardscatter directionscatter direction(e.g. FZA = +55(e.g. FZA = +55°°))



Multiangular and multitemporal HDRF patterns measured with CHRIS at672 nm (red domain) for maize.

26/05/2005

20/06/2005

22/09/2005

17/08/2005

•• Actual view zenith anglesActual view zenith angles usedusedinstead of FZAinstead of FZA

•• Bare soil shows a linearBare soil shows a linearincrease in reflectance fromincrease in reflectance fromforward scatter directions (+)forward scatter directions (+)to backscatter geometries (to backscatter geometries (--))

•• Trend in HDRF patterns visible,Trend in HDRF patterns visible,but difficult to interpret (changebut difficult to interpret (changein in zenit zenit / azimuth angles and/ azimuth angles andsun illumination geometrysun illumination geometry

•• Hotspot situations andHotspot situations anddeviations from nadir viewdeviations from nadir viewfor FZA = 0for FZA = 0°° disturb thisdisturb thispatternpattern

FZA=0FZA=0°°

hotspothotspot



Multiangular and multitemporal HDRF patterns measured with CHRIS at672 nm (red domain) for winter barley.

17/08/2005

20/06/200522/09/2005

26/05/2005


•• Large effect of hotspot visibleLarge effect of hotspot visible(bare soil) (bare soil)

•• Trend in HDRF patterns visible,Trend in HDRF patterns visible,however no data for earlyhowever no data for earlyphenological phenological stagesstages

•• The spectral contribution ofThe spectral contribution ofmaturing ears becomes morematuring ears becomes moredominantdominant for large FZA (e.g.,for large FZA (e.g.,20 June 2006 [20 June 2006 [Bach et al.,Bach et al.,3rd CHRIS / PROBA WS, 2005]3rd CHRIS / PROBA WS, 2005]

hotspothotspot

Influence ofInfluence ofmaturing ears?maturing ears?

bare soilbare soil

young grassyoung grass



Multiangular and multitemporal HDRF patterns measured with CHRIS at672 nm (red domain) for sugar beet.

26/05/2005

20/06/2005

22/09/2005

17/08/2005

hotspothotspot


•• Bare soil shows a linearBare soil shows a linearincrease in reflectance fromincrease in reflectance fromforward scatter directions (+)forward scatter directions (+)to backscatter geometries (to backscatter geometries (--))

•• Trend in HDRF patternsTrend in HDRF patternsvisible, however no data forvisible, however no data forintermediate intermediate phenological phenological stagesstages


Conclusions

• Multitemporal CHRIS data show the spectro-directional variation of crops in relation to phenology

• Preprocessing of CHRIS data includes geometric (3D physical model) and atmospheric correction (physically based on MODTRAN)

• Multiangular and multitemporal HDRF patterns of crops show trends in HDRF anisotropy in the red domain with phenological development (bare soil, early and late phenological stages). These patterns may be disturbed by• Close-to-hotspot constellations • Deviations from nadir view for FZA = 0°• Individual plant parts (e.g., ears)

• Understanding of the HDRF anisotropy effect may improve agricultural monitoring and crop classification

Outlook

• Study the temporal evolution of the Minnaert function parameter k, retrievable by the RPV model

• Observe more phenological stages to furtherstudy the effects of heterogeneity onHDRF bowl/bell shape (CHRIS 2006 data)

• Biophysical/chemical parameter retrieval of forests and agricultural fields• Based on Radiative Transfer Models (SAIL, Prospect)• Coupling of an RTM and a canopy structure dynamic model (CSDM)

to exploit the complementary content in the spectral and temporal information dimensions for LAI

• Exploitation and integration of the directional information content• Verification with available ground truth data

• (Inter-) Calibration / Validation of Leica Geosystems ADS-40 Airborne Digital Sensor (nadir looking RGB and NIR channels) with CHRIS

3-D

Bell-shape

k=1.18

Pinty et al. 2002

OutlookEstimation of Nitrogen Content from HyMap Data

RMSE: 0.379 RMSE: 0.087

RMSE: 0.095

11 species11 species Abies, Picea, Pinus

European Beech

Future workFuture work

•• Apply methods to multiApply methods to multi--angular CHRIS dataangular CHRIS data•• Assess the upAssess the up--scalingscaling issue (issue (GeoSAILGeoSAIL))•• Compare biochemistry products from different Compare biochemistry products from different

sensors, spatial and spectral scalessensors, spatial and spectral scales

HyMap HyMap 2004 Data2004 Data

Outlook ADS-40 Airborne Digital Sensor

17 August 2005:17 August 2005: Nearly simultaneous data take of CHRIS andNearly simultaneous data take of CHRIS andLeica Leica ADSADS--40 Airborne Digital Sensor40 Airborne Digital Sensor

(Inter(Inter--) Calibration /) Calibration /ValidationValidation

OutlookADS-40 Airborne Digital Sensor (Inter-) Cal / Val

ADSADS--40 Airborne Digital Sensor40 Airborne Digital Sensor•• ThreeThree--line PAN scanner forline PAN scanner for photogrammetric photogrammetric

imaging (+26imaging (+26°°, 0, 0°° --1616°°))•• Red:Red: 608 608 -- 662 nm662 nm

GreenGreen 533 533 -- 587 nm587 nmBlueBlue 428 428 -- 492 nm492 nmNIR1NIR1 703 703 -- 757 nm757 nmNIR2NIR2 833 833 -- 887 nm (optional)887 nm (optional)

•• RGB and NIR lines: 12RGB and NIR lines: 12’’000 pixels000 pixels•• GSD GSD multispectralmultispectral: 16 cm (3000 m : 16 cm (3000 m aslasl))•• GSD PAN: 5 cm (3000 m GSD PAN: 5 cm (3000 m aslasl))

•• ADSADS--40 mainly used for 40 mainly used for photogrammetricphotogrammetricpurposes so farpurposes so far

•• SwisstopoSwisstopo interested in increasingly servinginterested in increasingly servingthe remote sensing communitythe remote sensing community(e.g. vegetation(e.g. vegetation products (LAI, NDVI etc.)products (LAI, NDVI etc.)

•• Radiometric calibration (RGB, NIR) neededRadiometric calibration (RGB, NIR) needed

•• Cal / Val relative to CHRIS data plannedCal / Val relative to CHRIS data planned

Source:Source:Leica GeosystemsLeica Geosystems

ADS-40 (Inter-) Cal / Val

17 August 200517 August 2005

Acknowledgments

We would like to thank

• The CHRIS / PROBA team for data acquisition

• Rolf Richter (DLR) for implementing CHRIS into ATCOR-3

• You, for your attention!

Documents

CHRIS / PROBA Data Analysis at the Swiss Midlands Testsiteearth.esa.int/workshops/4th_chris_proba/CHRIS_WS4_KNEUBUHLER.… · 4th CHRIS / PROBA Workshop Frascati 19 - 21 September