OW AND 
| developed for the 
ility in incorporating 
for any other remote 
logger. Its software 
ormalized difference 
rated on the basis of 
fferent, which would 
t has been found that 
dimalayas. 
iD SPECTRAL 
\TIONALE 
ied as the ratio of the 
d in the directions 
to that reflected into 
reflecting diffuser 
Illuminated (Bowker, 
994). The reflectance 
lowing equation (1). 
(1) 
indard reference. 
g target surface. 
hen viewing standard 
it is essential that 
> specified. Based on 
> measured with nine 
llows: 
lement, for the part of 
1 cone with the apex 
f a given composition 
distribution. 
In the field, amount of spectral radiance reflected by various 
terrain surfaces depends upon several factors, which have to 
consider carefully. These factors are sun zenith angle, sun-earth 
distance, instrument viewing angle and field of view, azimuth 
angle, relative humidity, cloud cover, surface pressure, 
atmospheric turbidity, target size, target reflectance, 
background reflectance and chemical composition of target etc. 
As the incident solar radiations is composed of direct and 
diffused components, the measurement task requires further 
considerations (Bowker, David L., et. al., 1985; Egan Walter 
G., 1985; Hall, Dorothy K., and Martinec, Jaroslav, 1985; Ross 
McCluney, 1994; Thopmson, Brian. J., 1997; Toselli, F., and 
Bodechtel, J., 1992). 
In present model, two spectral bands with central wavelengths 
550 nm and 1625 have been incorporated. The selection is 
made on the basis of standard available spectral reflectance data 
of about 100 samples covering most of the terrain surfaces of 
vegetation, rocks and soils, water bodies, clouds, and snow 
(Bowker, David L., et. al, 1985). At these wavelengths, the 
spectral reflectances are unique and different, which would 
differentiate the snow packs with respect to other terrain 
surfaces. 
Ratio index (RI) and normalized difference index (NDI) are 
computed by using spectral reflectance factors (R) at the two 
specified wavelengths with the help of formulae in equation (2) 
and (3) respectively. The two central wavelengths are 550 nm 
and 1625 nm respectively. 
Rat 550 nm 
RI = ———— (2). 
Ra 1625 nm 
Rat 550nm ^ Ra 1625 nm 
NDI = : (3). 
Rat 550nm t Rat 1625 nm 
  
The spectral values of some of the samples are given in Table 
1. Based of individual values of RI and NDI, ranges of these 
spectral indices for individual target have been computed. The 
Table 2 shows the ranges of RI and NDI for various terrain 
surfaces. 
In general, data presented in Table 1-2 show that the spectral 
reflectance of snow is high at 550 nm and is low at 1500 nm 
and the absorption coefficient varies by several orders by 
magnitude between 550 nm and 1500 nm. At these 
wavelengths, the spectral reflectance values of snow are 
significantly different than that of other targets like water 
bodies, soil, vegetation, rocks. Thus the behavior of the snow at 
these wavelengths is unique and different from all other natural 
targets. However, the difference between spectral reflectance of 
ice and water is not significant for the wavelength nearer to 
1500 nm. The values of ratio indices at these wavelengths for 
snow and water are very high and the range is overlapping. 
However, comparing their individual reflectance values at 550 
nm, it is possible to identify snow and water surfaces. 
In short, from above discussion, it is clear that it is could be 
possible to identify terrain surfaces with and without snow 
cover by ratio indices at wavelengths 550 nm and 1625 nm and 
individual values of spectral reflectances at 550 nm. 
i 
  
IAPRS & SIS, Vol.34, Part 7, "Resource and Environmental Monitoring", Hyderabad, India,2002 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
TARGET. | o Brat. I NDI Rl? | 
| 550 1620 | | 
| Vegetatiomo-... 155.10: : boss] 
| CottonLeaf | 14| 338 [04 | 041 | 
| Dehydrated | 24 | 60 | -0. 42 | | 040 | 
| | Cotton Leaf si a 
| Peanuts 131€ 5: 22, 9| zm, | 0: S6. 
| Potatoes 87| 167] -031| 0.2 | 
| Rapeseed 22 |e 51561 | 0. nj 1.41 | 
Soybeans 195 26. 4 | 1.01 Bf 70. ).73 | 
| Sugarcane Leaf [TT 309] 047 | 035 | 
Sugarcane 9 1931 -0.36 | 0.46 | 
Tobacco 12.2 [7° 393 | 0521031] 
Tomatoes | SA ull | -0.13 | 0.75 | 
Watermelon Leaf | 14.1 | a 1.31. 2.37 |. 0.45 | 
HWhoat LA 0.34 | 
Seedling Wheat 12.3. 1.32 1| -043] 039 
Young Wheat 72] 23241... 2052] 0.31 | 
Matured Wheat 7.6; 262 4 .-0.55 ^ [ 30,29. 
Matured Wheat 62.1 1c<117.5-1.11-0,47-110035 | 
Live Oak -7:{-11»109-| 14021 | 064 | | 
Orange Leaf 9.7 39 | -0.60| 024 | 
Peach Leaf 10 39.3 | 70.59 F 0.25 | 
| Ponderosa Pine 11:3 25.3 -0.38 0.44 
Needles ii. ui 
Sycamore Leaf 14.1 | 46.99 | -0.53 | 0.30 | 
Dehydrated 99 604) -071| 0.16 | 
Sycamore Leaf | | 
Grass $2 244 | -064 | 021 
Silver Leaf 10 18:9.|-—0.30 1 —0.52..| 
Sunflower | E] 
Rocks and Soils | 4 a men 
Basalt Sample 18.8 25.4 -0. 14 | 0.74 
Red Cinder 8 70-19. 79 | EE 
Basalt Sample | | 
Gray Basalt 17.9 222] -010 | 080 | 
Sample | i 
Dry Red Clay 17 52.7 | -051 [ 0.32 
| Sample da | | 
Wet Red Clay $51 252% 040 70.33 | 
Sample | | | 
| Quartz Diorite 17.5 341 | -032 051] 
Granite 31 58.5 0.30.4, 0.53 | 
Biotite Granite 54 ar] gt 074 
Sample | | | 
Limestone 19.5 54.8 | 0.47 | | 035 | 
Sample dc a. 
| Monzonite 19/28. = I 1-0. CE = E 67 | 
| Quartz 19 324] 0. 2 | 0 58 | 
| Monzonite Ian 1d in|. X 
| Obsidian [Sample |. 53] 67. 3| | "OTi T- 078. 
| Unaltered Rocks | 195] 297 | -020| 0465 
[AlerdRoks |  26|  504| -031| - 51 
[Rhyolite sample | 323| 823] 022] 063. 
| Beach Sand a Lou A 20 | 0.65 
| Sample | |: bud Pa 
| Carbonate Beach | — 45 |  448| 000 | 1.00 | 
| San | | | | 
| Sample — He e 0 pants, yn 
| | QuarzBeach | 44 | 501 | -006| 0.87 | 
i A rd mee a 
| Quartz Beach 1871251 OUI 0791