Imaging Spectroscopy for Soil Applicationswebdocs.dow.wur.nl/...Imaging_Spectroscopy/11_BenDor_Soil/BenDor_Soil.pdf · IGARSS and 27th Canadian Symposium on Remote Sensing , Denver,

__________________________________________________________________________________________________________IGARSS and 27th Canadian Symposium on Remote Sensing , Denver, Colorado August 2, 2006: State of Science of Environmental Application of Imaging Spectroscopy in honor of Prof. A..Goetz

Imaging Spectroscopy for Soil Imaging Spectroscopy for Soil ApplicationsApplications

Ben-Dor1* E., Taylor R.G2., Hill J3., Demattê J.AM4., Whiting M.L5., Chabrillat, S6., and Sommer S. 7

*1 Department of Geography and Human Environment, Tel Aviv University, Israel 2 School of Biological, Earth and Environmental Science, University of New South

Wales, Sydney, Australia3 Remote Sensing Department, Faculty of Geography./Geosciences, Trier

University, Germany 4 Department of Soil Science, São Paulo University, ESALQ, Piracicaba, Brazil

5 CalSpace, University of California, Davis, California, USA. 6 GeoResearch. Center (GFZ) Potsdam, Section 1.4: Remote Sensing, Potsdam,

Germany 7 European Commission – DG Joint Research Centre, Institute for Environment

and Sustainability, Ispra, Italy


1983- AIS – Van G., and A.F.H. Goetz and J.B. Wellman 1984 Airborne Imaging Spectrometer: A new tool for remote sensing: IEEE Trans Geosciences Remote Sensing 22(6): 546-549

1984-AVIRIS 1987-GER1992-CASI1994- AISA1994-MIVIS1996- HYMAP1997- DAIS1999, 2000 - MODIS, ASTER2000-HYPERION2001-CHRIS-PROBA2003-AISA-ES2006- AVIRIS* 2007-ARES2010-EnMAP

Image Spectroscopy Image Spectroscopy –– Some Mile stones Some Mile stones


7.6%10.6%

24.1%

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

חאזו

מ לכ למה

מאירם

1 2 3

הנש

11989 20001989 1994

From

all

pape

rs

Year

IS in Science (1)


11989 20051995 2000

IS in Science (2)


IS in IGARSS IS in IGARSS

First met with Alex

5%

Image Spectroscopy Sessions• 1990, Maryland US – 0/80= 0%

• 2006, Denver US – 7/80= 9%(not including other sessions with IS oriented issues)

RADAR & SAR sessionsRADAR & SAR sessions• 1990,Mariland US -15/120=12.5%• 2006, Denver US – 21/120=17.5%

Honor to Alex


Soil :Soil : ""The upper layer of the earth which may be dug, plowed, The upper layer of the earth which may be dug, plowed, specifically, the loose surface material of the earth in which pspecifically, the loose surface material of the earth in which plants grow.lants grow." " (Thompson 1957)(Thompson 1957)

Claysilt sand organic mattercarbonatesiron oxideswaterparticle sizeair Return Impact

Soil is composed of


length

width

spectral

IS:IS: The acquisition of images in hundreds of registered, contiguous The acquisition of images in hundreds of registered, contiguous spectral bands such that for each picture element it is possiblespectral bands such that for each picture element it is possible to to complete reflectance spectrum (Goetz 1994)complete reflectance spectrum (Goetz 1994)


Figure 2

Stoner, E.R. and M.F., Baumgardner, 1981. Characteristic variations in reflectance of surface soils. Soil Science Society of American Journal 45: 1161-1165

5 spectral types in USA

Main Soil Chromophores

Iron Oxides

Hygroscopic Water

Clays

OrganicMatter

Particle Size

Organic Matter

Calcite

Ben-Dor E., and A. Banin 1995b, Near infrared analysis (NIRA) as a Simultaneously method to evaluate spectral featureless constituents in soils., Soil Science 159:259-269

Soil Spectroscopy Soil Spectroscopy


Spectral Assignments for Soil Constituents Soil Soil ChromophoresChromophores


MLRA 9

MLRA 67

MLRA 77

MLRA 105

Matter properties expressed as a linear function of its reflectance spectral data:Principal components methodology

1301119119300130130 1 XXXXX ebCby ++=

Cheng-Wen et al. (2001)

Quantitative Method for spectral based matter properties (1) Quantitative Method for spectral based matter properties (1)


Quantitative Method for spectral based material properties (2)Quantitative Method for spectral based material properties (2)

Ben-Gera, I., and K.H. Norris, 1968, Determination of moisture content in soybeans by direct spectrophotometry. Israeli Journal of Agriculture Research. 18:124-132.

First developed for Food Sceince:


NIRS is a chemomtrics method where NIR-SWIR spectral region is used to predict chemical constituents of a given matter.

NIRS NIRS Dalal, R.C., and R.J. Henry. 1986. Simultaneous determination of moisture, organic carbon and total nitrogen by near infrared reflectance spectroscopy. Soil Science Society of America Journal 50:120-12

Quantitative Method for spectral based SOIL properties Quantitative Method for spectral based SOIL properties


Soil- NIRS summary • Malley D. Martin P.D. and E. Ben-Dor., 2004, Application in

Analysis of Soils. Chapter 26 In Near Infrared Spectroscopy in Agriculture. Craig R., Windham R., and Workman J., (eds). A three Societies Monograph (ASA, SSSA, CSSA) 44: 729-784.

• Viscarra Rossel R.A.., D.J.J Walvoort, A.B. McBratney, L.J. Janikand J.O. Skjemstad 2005 Visible, near infrared, mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties Geoderma 131:59-75.

• Demattê, J.A.M., Campos, R. C., Alves, M. C., Fiorio, P. R. and Nanni, M. R. 2004c. Visible-NIR reflectance: a new approach on soil evaluation. Geoderma, 121: 95-112.





ConclusionsConclusions

• Soil Spectra consists of many interesting chromophores

• Quantitative analysis of soil spectra is possible (NIRS)

• Soil is a complex system


Idea: to apply NIRS or related methods to Idea: to apply NIRS or related methods to precision agriculture domain precision agriculture domain

Idea

s rat

her a

pplic

atio

ns


Idea: to apply NIRSIdea: to apply NIRSor related methods for RS dataor related methods for RS data

Question (1) : Does NIRS work within 6 bands? Answer (1) : Yes

(Ben-Dor E., and A. Banin, 1995c, Quantitative analysis of convolved TM spectra of soils in the visible, near infrared and short-wave infrared spectral regions (0.4-2.5mm). International Journal of Remote Sensing 18:3509-3528).

Question (2) : Does TM- NIRS work?Answer (2) : Yes

(Nanni, M.R. and Demattê, J.A.M. 2006. Spectral reflectance methodology in Comparison to traditional soil analysis. Soil Science Society of America Journal, 70:393-407).


NIRS in 6 TM bandsNIRS in 6 TM bands

Ben-Dor E. and A. Banin, 1995, Quantitative analysis of convolved TM spectra of soils in the visible, near infrared and short-wave infrared spectral regions (0.4-2.5mm). International Journal of Remote Sensing,18:3509-3528.

Question (1)


Landsat-5, TM

0

5

10

15

20

25

30

35

40

45

1 2 3 4 5 7 TM Bands

Ref

lect

ance

fact

or (%

) CD1CD2LV1LV2PV1TE1TE2LV2

Hight intensity variation

Loss intensity variation

Spectral curves

High iron and clay contents

Low iron and sandy soil

30 m

30 mNanni and Demattê (2005)

Soil Mapping from Orbit using TMSoil Mapping from Orbit using TMQuestion (2)


Idea: to apply NIRSIdea: to apply NIRSor related methods for HRS dataor related methods for HRS data

Question (3) : Does NIRS work within real IS data? Answer (3) : Yes

(Ben-Dor E., K. Patkin, A. Banin and A. Karnieli 2002b, Mapping of several soil properties using DAIS-7915 hyperspectral scanner data. A case study over clayey soils in Israel. International Journal of Remote Sensing 23:1043-1062)

Question (4) : Is it straight forward? Answer (4) : No


NIRS on IS (1) NIRS on IS (1) Ben-Dor et al., 2004

Vegetation Question (3)


N

c

60

km

3

EC

OM

SM

PM

Ben-Dor et al., 2004

NIRS on IS (2) NIRS on IS (2) Question (3)


Why it is not (yet) straight forward?Why it is not (yet) straight forward?

• Atmospheric attenuation: requires perfect removal of atmospheric chromophors

(Ben-Dor E.,. Kindel B. and A.F.H Goetz 2004 Quality Assessment of Several Methods to Recover Surface Reflectance I using Synthetic Imaging Spectroscopy (IS) Data, Remote Sensing of Environment 90: 389-404)

• Signal to Noise: NIRS requires high SNR data base(Kruse F.A. Comparison of AVIRIS and Hyperion for Hyperspectral Mineral MappingIn proceedings 11th JPL Airborne Geoscience Workshop, 4-8 March 2002,

Pasadena, CA, Jet Propulsion Laboratory Publication 03

• Subsurface detection: Still problematic, Requires supplementation from other methods

(Heller D., and Ben-Dor E. 2006, A Novel Method of Classifying Soil Profiles in the Field Using Optical Mean Soil Science Society of American Journal

Question (4)- NO


Quantitative IS of soil properties Quantitative IS of soil properties

• Soil Salinity: (gypsum, sodium)• Soil properties: (iron oxides, organic

matter, clay, carbonates)• Soil infiltration: (crust, classes)• Soil Formation: (clay, iron oxides)• Soil Contamination: (heavy metals)• Soil Moisture: (H2O)


Soil Salinity (1)Soil Salinity (1)Dehaan and Taylor 2003


a b

Soil Salinity (2)Soil Salinity (2)Ben-Dor et al., 2004


הים התיכון

הדי ונההגד ולה

מחצבת חול

וכו רכ ר

שטח מיוש ר לבנייה

12

3 4

5

67

8

9

10

11

14

15

16 1

7

12

13

2121

2021

19

18

2221

AshdodcityBeach

BlowoutDune in slacksDeflation zoneBare dunesOther

Sand samples

LandsatLandsat CASICASI

Iron oxides as indicator for soil formation Iron oxides as indicator for soil formation

clay

Iron

Oxi

des

Soil Formation Soil Formation Ben-Dor et al., 2005


1st D

eriv

ativ

e

Re f

lec t

anc e

Clay Accumulation

2.2um 1.7um

Particle Size Changes

Crust I

Crust I Crust I

Crust I

Clay

w

asho

ut

fine particle

coarse particleHigh clay

Low clay

0 joule 1842 joule650 joule

Soil Infiltration and Erosion : Physical Crust (1)Soil Infiltration and Erosion : Physical Crust (1)


ABD

C

Vegetation

high low

NBen-Dor et al., 2004

Soil Infiltration and Erosion : Physical Crust (2)Soil Infiltration and Erosion : Physical Crust (2)


: Map of four soil degradation (erosion) classes derived from AVIRIS data over S-France (I: undisturbed, II: slightly degraded, III: severely degraded - classes IV and V refer to exposed bedrock of marls and limestone) (after Hill et al., 1995).

Soil Erosion Soil Erosion


400420440460480500520540560580600

0 200 400 600 800 1000 1200 1400

1-LR2-LR

3-LR4-LR

5-LE6-PE

7-Liv

vv

v

v

vv

vv

v vv

vv v

v

v

v

vv

v

v

v

v

vv

vv

v

vvv

vv

v

vv

vvv

v v

vv v

- --- ------- - --- -- ---- -

- -----

8-Al

0

0,1

0,2

0,3

0,4

0,5

0,6

350 438 523 606 686 764 839 912 983 1068 1230 1392 1549 1700 1889 2129 2366

"1A" "1B" "1C"

0

0.1

0.2

0.3

0.4

0.5

0.6

350 438 523 606 686 764 839 912 983 1068 1230 1392 1549 1700 1889 2129 2366

0

0.1

0.2

0.3

0.4

0.5

0.6

350 438 523 606 686 764 839 912 983 1068 1230 1392 1549 1700 1889 2129 2366

0

0.1

0.2

0.3

0.4

0.5

0.6

350 438 523 606 686 764 839 912 983 1068 1230 1392 1549 1700 1889 2129 2366

0

0.1

0.2

0.3

0.4

0.5

0.6

350 438 523 606 686 764 839 912 983 1068 1230 1392 1549 1700 1889 2129 2366

0

0.1

0.2

0.3

0.4

0.5

0.6

350 438 523 606 686 764 839 912 983 1068 1230 1392 1549 1700 1889 2129 2366

0

0.1

0.2

0.3

0.4

0.5

0.6

350 438 523 606 686 764 839 912 983 1068 1230 1392 1549 1700 1889 2129 2366

0

0.1

0.2

0.3

0.4

0.5

0.6

350 438 523 606 686 764 839 912 983 1068 1230 1392 1549 1700 1889 2129 2366

Basaltic rocks

-v

v

v

Shale

Distance, m

Alti

tud,

m

.

Depth A (0-20 cm)_______

Depth B (40-60 cm)______

Depth C (80-100 cm) _____

Soil Soil ToposequenceToposequence (from field spectroscopy) (from field spectroscopy)


Gonçalves et al. (2005)

Clay CEC

Sand SiltSoil Properties Soil Properties


Detailed soil map constructed by traditional methods

Detailed soil map constructed by aerial photographs and

spectral radiometry data

Soil mapping from field spectroscopy Soil mapping from field spectroscopy


Soil Age Soil Age

Cruvi et al., 2006


0 As [ppm] 370

Residual Sludge

Potential Acidification Risk

Arsenic Contamination

Calcite-Buffering Need

0 CaCO3 [g/kg] 90

0 H2SO4 [g/kg] 120

0 Weight [g/kg] 140

Lead Contamination

0 Pb [ppm] 2500

Soil Contamination Soil Contamination Kemper and Sommer (2002, 2003)


30

40

50

2000 2100 2200 2300 2400

Wavelength, nm

Ref

lect

ance

, %

SmectiteKaoliniteSmectite/Illite

a b

Swelling SoilSwelling Soil

Chabrillat and Goetz, 1999, 2006

Chabrillat et al., 2002

Goetz et al., 2001

b

SmectiteIllite/SmectiteKaoliniteNo clay


Soil MoistureSoil Moisture

1.4μm1.9μm

Water is significant chromophors


Soil ClaySoil Clay (Montmorillonite) and Relative Humidity

slope

OH-clayOH-water OH-water

Ben-Dor et al 1999


Clayey Soil and Soil Moisture

Bowers and Hanks, 1965


Rd

σ

λi

λ0

A

++ ++

++++++

+++

+ +

+

+

OH- Fundamental

Whiting et al., 2004

Inverted Gaussian function is fitted to the fundamental water absorption center at 2800 nm to the convex hull boundary points of a logarithmic transformed SWIR region


Water ContentRed <1%

Green <2%Blue <5%

Yellow <10%Cyan <15%

Magenta <20%Sea Green <32%

Purple >32%Black = Vegetated

or No Data

Water ContentRed <1%

Green <2%Blue <5%

Yellow <10%Cyan <15%

Magenta <20%Sea Green <32%

Purple >32%Black = Vegetated

or No Data

Whiting (unpublished results)

Soil Water content Soil Water content


N

S

EW

N

S

EW

a b

Haubrock et al., 2006b

Soil Water content Soil Water content


Merge with other remote sensing Merge with other remote sensing technique technique

Surface Gypsum Correlated with 60 cm depth EC

y = 0.3568x - 1.98R2 = 0.9566

0102030405060708090

0 50 100 150 200 250

Surface CaSO4 (meq/l)

60 c

m d

epth

EC

(ds/

m)

Field Spectroscopy

Salinity as an Example


East Line

Buried River

Field GPRField GPR

Salinity as an Example


Soil map production Soil map production Air photograph

Soil map

IS

λRNIRS

Ben-Dor and Heller , Submitted to SSSAJ


Vision: IS should be commercially and Vision: IS should be commercially and economically operated (rather than economically operated (rather than onlyonly

scientifically used)scientifically used)

Example: NIRS Commercially Covers: food, textile, tobacco, pharmacological, medicine, vegetation, soil and more….


Quantitative Reflectance Spectroscopy (1) Quantitative Reflectance Spectroscopy (1)


Quantitative Reflectance Spectroscopy (2) Quantitative Reflectance Spectroscopy (2)


Vision (1)Vision (1)

Ben-Dor E., Taylor R.G., Hill J., Demattê J.AM., Whiting M.L., Chabrillat, S., and Sommer S. 2006 Imaging Spectrometry for Soil Applications

…………By means of this paper, we will have the privilege of making the entire soil science community aware of this important field and saying: ““(Soil) Imaging (Soil) Imaging Analysis: Time for the Giant Wake up Call". Analysis: Time for the Giant Wake up Call".

A paper based on this presentation submitted to the special issue of :


similaritiesIS -NIRS

NIRS• 1968- Ben-Gera and Norrish (first paper)

• 1987- Davies paper (let the giant…)

• 2000- Commercially operated

IS• 1984- Van and Goetz (first paper)

• 2006-Ben-Dor’s paper (let the giant..)

• 2010- Commercially operated

19 y

ears

13 y

ears

22 y

ears

14 y

ears

Vision (2) Vision (2)


Conclusion remarks Conclusion remarks • The Imaging Spectroscopy has reached a point of no return….

• Imaging Spectroscopy in the soil environment has a bright future…..

• Commercializing Imaging spectroscopy for soil and other applications may be a key for success….

• A new Journal covering Imaging Spectroscopy applications (such as NIRJ for NIRS) is missing: We suggest to establish a new journal entitled : Journal of Imaging Spectroscopy


We thank Alex for opening the ISWe thank Alex for opening the IS window for the scientific community window for the scientific community and hope to see in IGARSS 2015 >20% and hope to see in IGARSS 2015 >20% of the sessions of the sessions -- IS orientedIS oriented…….. ..

We thank all of you for your attentionWe thank all of you for your attention

Documents

Imaging Spectroscopy for Soil Applicationswebdocs.dow.wur.nl/...Imaging_Spectroscopy/11_BenDor_Soil/BenDor_Soil.pdf · IGARSS and 27th Canadian Symposium on Remote Sensing , Denver,