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Spectral signature studies in optical region
Adv. Space Rca. Vol.1, pp.221—224.
© COSPAR, 1981.
0273—1177/8]./040l—0221$05.OO/O
Printed in Great Britain.
SPECTRAL SIGNATURE STUDIES IN OPTICAL REGION Baldev Sahai, R.R. Nava!gund, N.K. Pate! and T.P. Singh Space Applications Centre, Ahmedabad-380 053, India
ABSTRACT Reflectance spectra of a large number of rock, vegetation and soil samples have been measured in the laboratory in the visible and near infrared wavelength regions. Procedures have been evolved to find 1 ref lectan— optimum spectral bands for rock discrimination. ‘In situ ce measurements on different crops like wheat, paddy, millet, cotton, maize, groundnut etc. during their various growth stages have been carried out using hand—held r&ianeters. Recently measurements have been conducted over six wheat plots subjected to different irrigation schedules to see the effect of water stress on the signatures. Results show that the best period for monitoring water stress in wheat through remote sensing is 45—80 days after sowing. INIROWCTI ON Identification and classification of various earth surface objects through remote sensing requires an understanding of their spectral responses in different parts of the electromajnetic spectrum. Spectra]. signature studies provide such an understanding, enable one to make an optimal choice of spectral bands and band widths, and to identify the type of sensor best suited for any specific application. In view of this, systematic signature studies of different earth sur— f ace objects have been taken up at the Space ~plications Centre (SAC), as part of its remote sensing activities. LABORATORY STUDIES Laboratory measurements provide a useful insight into the intrinsic spectral behaviour of objects under study, though they may not exactly correspond to the realistic situations encountered in aircraft and/or spacecraft based remote sensing operations. Reflectance Spectra of a large number of 1leaves’ of different crops, soil samples with Varying moisture content and various kinds of rock saaples have bean measured using a spectrophotometer in the wavelength range 0.4 to 2.4 um. Reflectance spectra of most of the rock samples studied are featureless in the visible region and show narrow absorption 221
222
B. Sahai at al.
bands perhaps due to OW radical at 1.4, 1.9, 2.2 and 2.36 Alrn[l,2]. Statistical analysis on reflectance data of 24 rock specimens was carried out. Results show that there is very little to Choose among different spectral bands each of 0.04 ~irnbandwidth in the 0.46 to 1.06 ..um range. However, in the range from 1.08 to 2.28 Aim, spectral bands centered at 1.32 urn, 1.64 turn and 2.12 ~m, each of 0.08 ~um bandwidth, show discriminating ability. It is interesting to note that spectral bands centered at 1.6 ..&im and 2.2 ~im have been recommended by the Geosat Committee for geological applications[3]. These conclusions specifically apply only to the intrinsic spectral behaviour of the objects. FIELD S’flJDI~S ‘In situ’ spectral measurements yield data more akin to the data gathered by airborne or spaceborne sensors. Extensive reflectance measurements of various crops during their different growth stages have been carried out using hand—held radiometers. These studies on wheat, cotton, baj ra (pearl millet), paddy, maize (corn) and groundnut all lead to the conclusions that reflectances ~n near infrared (NIR) (0.7—1.1 AIm) is higher when the crops reach maximum vegetative cover. However, the reflectance in the red band (0.6-0.7 ~um) comes down at this stage. This indicates that the ratio of NIR/RED will be higher and hence discriminability of crops will be higher at maximum vegetative cover. Stress One of the major constraints in agrIcultural production is the mad— equate water supply. If a relationship could be established between the spectral response of crop canopies and their conditions under water stress, remote sensing technio-ues can play a very useful role in the assessment of water stress of crops. With this view in mind, an experiment was designed to carry out signature studies over six wheat plots subjected to different irrigation schedules. Similar studies have been carried out by Idso et al L4,5:1. The e~eriment was conducted on wheat (Junagadh—24) at the agricultural farm of Bhav Nirjhar near the SAC Campus. The area was divided into six plots (1, lA, 2—5) each of size 5 m x 4 in. The plots 1 and 1A were given normal irrigation, plot 2 more—than—normal irrigation and the plots 3,4 and 5 were given progressively less irrigation. Details of the irrigation schedule are given in Table 1. Plot 1A was similar to 1 in all respects except that fertilizer treatnent was given before second irrigation. Plot 2 was disturbed by animals and hence abandoned. Spectral signature measurencnts were carried out over al] the plots every week throughout the growth cycle of the crop usIng a four—band portable radiometer (Ezotech) with the same spectral bands as those of Laridsat. Irradiance was measured using a BaW4 reflectance panel. Tho measurements were taken every hour from 2.000 to 1400 hours. Leaf Area Index (LAI) was determined. Reflectance measurements of • leaves’ from all the plots were carried out in the laboratory using the spectrophotometer (Fig. 1) • Grain yield per unit area from each plot was determined by a crop-cutting experiment.
Spectral Signature Studies in Optical Region — ——
70
TAELE 1 Irrigation
223 PLOT I PLOT 3 PGOT4
Schedule FEB7.1910.
~
Plot No.
1
2
3
4
5
&
Date 13 Dec.’79 28 Dec.’79 4 Jan.’80 11 Jan.’80 28 Jan,80 25 Jan.’80 8 Feb. • 80 15 Feb.’80
1k x
x x
x
x
x
x
x
x x x
x
x
X
x
x
I9thOR0AFTOT
Days after sowing 23 38 45 52 59 66
~l4O
I
I
~
4
I ~I
4 /
-
o
GA WNVELENGTH MICROMETEN)
87
Pig. 1 Spectral reflectanceafter of leaves on 79th day sowing.
Pig. 2 shows the behaviour of vegetation index V I ~6] defined as (Mss7—~is~)/(r.~57+~s5)for the four plots against days after sowing. In the early stages of growth, V I is almost same for all the plots. There is a general increase in V I in early stages and a decrease with senescence, Plot 1 has a distinctly higher V I than the other plots during maximum vegetative cover. V I values for the plots 3,4,5 are not much different. Thç water stress is expected to reduce the chlorophyll concentration 17] • The difference in per cent reflectance of different plots is more pronounced during the period 45 to 80 days after sowing. This suggests that the optimum period for the discrimination of wheat plots under water stress would be 45—80 days after sowing.
•PLOT I
•PLOTT OPIOT 14 XPLOTS
78 0
~.PIO1$
7.6
a
0
o
04
.
.
•
,~T.2
a •
~a ~
•o
~o
.~
4
.
A ~~O4QSOI67ORO96IGO aSS AFTER SOWING
asS AFTER SOWING
Fig. 2 (Left) Temporal variation of the vegetation index (sS7—S5)/(i~ss7+~S5).The data were taken at sun zenith angle ..~..45O Fig. 3 (Right) Variation of LAX during the growth cycle for the plots 1,1k and 5. Fig. 4 shows a linear relationship between final yield and maximum LAX and suggests a method of directly relatin yield with the LAX whidi can be determined using remote sensing techniques [8J . Fig. 5
224
B. Sahai at al. / /
,/
/
1.
OPLOTIA OPLOT3 ..P10t4 LOT S
/
IS 1
~ :~:
~ P
a
a
to
~
£0 DAYS ~0 AFTER 60 70SOWING lET
00
Fig. 4 (Left) Wheat yield as a function of Maximum LAX. The numbers indicate the plot numbers. Fig. 5 (Right) (T -T,) as a function of days after sowing for Various plots, a shows the difference between the canopy temperature T~and the amhient temperature T~plotted as a function of crop—growth cycle. T~was measured between 1300 and 1400 hours making use of KT 24 radiation thermometer looking at the plant canopy from an angle so that soil background is avoided, It is Obvious that stressed plants have a higher TC-TA whereas for normal plants PC—TA is near zero or negative in agreement with Idso et al [9] CC~CLUSICNS As discussed earlier extensive studies of various earth surface objects have been done in the laboratory and also using four—band radiometers under field conditions, All these studies point to the capability for discriminating various objects provided suitable spectral bands are chosen. ‘In situ’ spectral measurements have been initiated using a mobile laboratory housing a spectror&J.cxneter (0.4—1.15 Aim continuously variable) and also using indigenously developed radiometers with narrow spectral bands. Using an indigenously developed multispectra]. scanner and a Linear Imaging Scanner Sensor, both with selectable filters, signatures from the aircraft altitude are being collected. These form part of the Joint EWeriments Programme of the Indian Space Research Organization with other Government ministries/departments/agencies. It is hoped that all these studies would help in defining the spectral bands for future Indian Remote Sensing Satellite Missions. RE ~E~ENC~ 1. G.R. Hunt, Geophysics 42, 501 (1977) 2. G.R. Hunt and J.W. Salistury, Geophysics 43, 738 (1978). 3. F.B. Henderson III and R.J. Ondrejka, Photogrammetric Engineer-ET1 w316 188 m4 ing and Remote Sensing ~j, 165 (1978). 4. S.B. Idso, R.J. Reginato and R.D. Jackson, Nature 266, 625 (1977). 5. SB. Idso, R, D, Jackson and R.J. Reginato, Science ~ 19 (197~). 6, J.w. Rouse, R.H. Haas, J,A. Schell, and D.W. Deering Third ER1~ Symposium NASA SP—327, 1973. 7. C.J. Tucker, J.H. Elgin Jr. and J.E. Mc Murtrey, III N3~ATechnical Memorandum 80272, i979, 8. R,B. Pollock and E,T, Kanemasu, Remote Sensing of Environment Q, 307 (1979). 9. R,D. Jackson, R.J, Reginato and S.B. Idso, Water Resources Research 2.3, 651 (1977). -
© COSPAR, 1981.
0273—1177/8]./040l—0221$05.OO/O
Printed in Great Britain.
SPECTRAL SIGNATURE STUDIES IN OPTICAL REGION Baldev Sahai, R.R. Nava!gund, N.K. Pate! and T.P. Singh Space Applications Centre, Ahmedabad-380 053, India
ABSTRACT Reflectance spectra of a large number of rock, vegetation and soil samples have been measured in the laboratory in the visible and near infrared wavelength regions. Procedures have been evolved to find 1 ref lectan— optimum spectral bands for rock discrimination. ‘In situ ce measurements on different crops like wheat, paddy, millet, cotton, maize, groundnut etc. during their various growth stages have been carried out using hand—held r&ianeters. Recently measurements have been conducted over six wheat plots subjected to different irrigation schedules to see the effect of water stress on the signatures. Results show that the best period for monitoring water stress in wheat through remote sensing is 45—80 days after sowing. INIROWCTI ON Identification and classification of various earth surface objects through remote sensing requires an understanding of their spectral responses in different parts of the electromajnetic spectrum. Spectra]. signature studies provide such an understanding, enable one to make an optimal choice of spectral bands and band widths, and to identify the type of sensor best suited for any specific application. In view of this, systematic signature studies of different earth sur— f ace objects have been taken up at the Space ~plications Centre (SAC), as part of its remote sensing activities. LABORATORY STUDIES Laboratory measurements provide a useful insight into the intrinsic spectral behaviour of objects under study, though they may not exactly correspond to the realistic situations encountered in aircraft and/or spacecraft based remote sensing operations. Reflectance Spectra of a large number of 1leaves’ of different crops, soil samples with Varying moisture content and various kinds of rock saaples have bean measured using a spectrophotometer in the wavelength range 0.4 to 2.4 um. Reflectance spectra of most of the rock samples studied are featureless in the visible region and show narrow absorption 221
222
B. Sahai at al.
bands perhaps due to OW radical at 1.4, 1.9, 2.2 and 2.36 Alrn[l,2]. Statistical analysis on reflectance data of 24 rock specimens was carried out. Results show that there is very little to Choose among different spectral bands each of 0.04 ~irnbandwidth in the 0.46 to 1.06 ..um range. However, in the range from 1.08 to 2.28 Aim, spectral bands centered at 1.32 urn, 1.64 turn and 2.12 ~m, each of 0.08 ~um bandwidth, show discriminating ability. It is interesting to note that spectral bands centered at 1.6 ..&im and 2.2 ~im have been recommended by the Geosat Committee for geological applications[3]. These conclusions specifically apply only to the intrinsic spectral behaviour of the objects. FIELD S’flJDI~S ‘In situ’ spectral measurements yield data more akin to the data gathered by airborne or spaceborne sensors. Extensive reflectance measurements of various crops during their different growth stages have been carried out using hand—held radiometers. These studies on wheat, cotton, baj ra (pearl millet), paddy, maize (corn) and groundnut all lead to the conclusions that reflectances ~n near infrared (NIR) (0.7—1.1 AIm) is higher when the crops reach maximum vegetative cover. However, the reflectance in the red band (0.6-0.7 ~um) comes down at this stage. This indicates that the ratio of NIR/RED will be higher and hence discriminability of crops will be higher at maximum vegetative cover. Stress One of the major constraints in agrIcultural production is the mad— equate water supply. If a relationship could be established between the spectral response of crop canopies and their conditions under water stress, remote sensing technio-ues can play a very useful role in the assessment of water stress of crops. With this view in mind, an experiment was designed to carry out signature studies over six wheat plots subjected to different irrigation schedules. Similar studies have been carried out by Idso et al L4,5:1. The e~eriment was conducted on wheat (Junagadh—24) at the agricultural farm of Bhav Nirjhar near the SAC Campus. The area was divided into six plots (1, lA, 2—5) each of size 5 m x 4 in. The plots 1 and 1A were given normal irrigation, plot 2 more—than—normal irrigation and the plots 3,4 and 5 were given progressively less irrigation. Details of the irrigation schedule are given in Table 1. Plot 1A was similar to 1 in all respects except that fertilizer treatnent was given before second irrigation. Plot 2 was disturbed by animals and hence abandoned. Spectral signature measurencnts were carried out over al] the plots every week throughout the growth cycle of the crop usIng a four—band portable radiometer (Ezotech) with the same spectral bands as those of Laridsat. Irradiance was measured using a BaW4 reflectance panel. Tho measurements were taken every hour from 2.000 to 1400 hours. Leaf Area Index (LAI) was determined. Reflectance measurements of • leaves’ from all the plots were carried out in the laboratory using the spectrophotometer (Fig. 1) • Grain yield per unit area from each plot was determined by a crop-cutting experiment.
Spectral Signature Studies in Optical Region — ——
70
TAELE 1 Irrigation
223 PLOT I PLOT 3 PGOT4
Schedule FEB7.1910.
~
Plot No.
1
2
3
4
5
&
Date 13 Dec.’79 28 Dec.’79 4 Jan.’80 11 Jan.’80 28 Jan,80 25 Jan.’80 8 Feb. • 80 15 Feb.’80
1k x
x x
x
x
x
x
x
x x x
x
x
X
x
x
I9thOR0AFTOT
Days after sowing 23 38 45 52 59 66
~l4O
I
I
~
4
I ~I
4 /
-
o
GA WNVELENGTH MICROMETEN)
87
Pig. 1 Spectral reflectanceafter of leaves on 79th day sowing.
Pig. 2 shows the behaviour of vegetation index V I ~6] defined as (Mss7—~is~)/(r.~57+~s5)for the four plots against days after sowing. In the early stages of growth, V I is almost same for all the plots. There is a general increase in V I in early stages and a decrease with senescence, Plot 1 has a distinctly higher V I than the other plots during maximum vegetative cover. V I values for the plots 3,4,5 are not much different. Thç water stress is expected to reduce the chlorophyll concentration 17] • The difference in per cent reflectance of different plots is more pronounced during the period 45 to 80 days after sowing. This suggests that the optimum period for the discrimination of wheat plots under water stress would be 45—80 days after sowing.
•PLOT I
•PLOTT OPIOT 14 XPLOTS
78 0
~.PIO1$
7.6
a
0
o
04
.
.
•
,~T.2
a •
~a ~
•o
~o
.~
4
.
A ~~O4QSOI67ORO96IGO aSS AFTER SOWING
asS AFTER SOWING
Fig. 2 (Left) Temporal variation of the vegetation index (sS7—S5)/(i~ss7+~S5).The data were taken at sun zenith angle ..~..45O Fig. 3 (Right) Variation of LAX during the growth cycle for the plots 1,1k and 5. Fig. 4 shows a linear relationship between final yield and maximum LAX and suggests a method of directly relatin yield with the LAX whidi can be determined using remote sensing techniques [8J . Fig. 5
224
B. Sahai at al. / /
,/
/
1.
OPLOTIA OPLOT3 ..P10t4 LOT S
/
IS 1
~ :~:
~ P
a
a
to
~
£0 DAYS ~0 AFTER 60 70SOWING lET
00
Fig. 4 (Left) Wheat yield as a function of Maximum LAX. The numbers indicate the plot numbers. Fig. 5 (Right) (T -T,) as a function of days after sowing for Various plots, a shows the difference between the canopy temperature T~and the amhient temperature T~plotted as a function of crop—growth cycle. T~was measured between 1300 and 1400 hours making use of KT 24 radiation thermometer looking at the plant canopy from an angle so that soil background is avoided, It is Obvious that stressed plants have a higher TC-TA whereas for normal plants PC—TA is near zero or negative in agreement with Idso et al [9] CC~CLUSICNS As discussed earlier extensive studies of various earth surface objects have been done in the laboratory and also using four—band radiometers under field conditions, All these studies point to the capability for discriminating various objects provided suitable spectral bands are chosen. ‘In situ’ spectral measurements have been initiated using a mobile laboratory housing a spectror&J.cxneter (0.4—1.15 Aim continuously variable) and also using indigenously developed radiometers with narrow spectral bands. Using an indigenously developed multispectra]. scanner and a Linear Imaging Scanner Sensor, both with selectable filters, signatures from the aircraft altitude are being collected. These form part of the Joint EWeriments Programme of the Indian Space Research Organization with other Government ministries/departments/agencies. It is hoped that all these studies would help in defining the spectral bands for future Indian Remote Sensing Satellite Missions. RE ~E~ENC~ 1. G.R. Hunt, Geophysics 42, 501 (1977) 2. G.R. Hunt and J.W. Salistury, Geophysics 43, 738 (1978). 3. F.B. Henderson III and R.J. Ondrejka, Photogrammetric Engineer-ET1 w316 188 m4 ing and Remote Sensing ~j, 165 (1978). 4. S.B. Idso, R.J. Reginato and R.D. Jackson, Nature 266, 625 (1977). 5. SB. Idso, R, D, Jackson and R.J. Reginato, Science ~ 19 (197~). 6, J.w. Rouse, R.H. Haas, J,A. Schell, and D.W. Deering Third ER1~ Symposium NASA SP—327, 1973. 7. C.J. Tucker, J.H. Elgin Jr. and J.E. Mc Murtrey, III N3~ATechnical Memorandum 80272, i979, 8. R,B. Pollock and E,T, Kanemasu, Remote Sensing of Environment Q, 307 (1979). 9. R,D. Jackson, R.J, Reginato and S.B. Idso, Water Resources Research 2.3, 651 (1977). -