IAPRS & SIS, Vol.34, Part 7; "Resource and Environmental Monitoring", Hyderabad, India,2002 
  
  
  
altitude of 860 km and an inclination of 98.8°. The orbital 
period is 102 minutes and the orbit provides a complete 
coverage of the Earth, except for two small circular 
sectors 2.4° centered on the North and South poles. The 
SSM/I is a seven-channel, four-frequency, linearly 
polarized, passive microwave radiometric system, which 
measures atmospheric, ocean and terrain microwave 
brightness temperatures at 19.35, 22.235, 37.0, and 85.5 
GHz at constant incident angle of about 53°. The SSM/I 
rotates continuously about an axis parallel to the local 
spacecraft vertical and measures the upwelling scene 
brightness temperatures. The absolute brightness 
temperature of the scene, incident upon the antenna is 
received and spatially filtered by the antenna to produce 
an effective input signal or antenna temperature at the 
input of the feed horn antenna (Wentz, 1988). 
Table 1:Description of the data used along with their date 
of acquisition. 
  
  
  
  
  
  
  
  
  
S.No | Sensor Path Date of Pass 
1 SSM/I 152- 161 June, 1-10, 
(DMSP-F13) | Descending 1999 
2 SSM/I 182-191 July, 1-10, 
(DMSP-F13) | Descending 1999 
3 SSM/I 244-253 Sept., 1-10, 
(DMSP-F13) | Descending 1999 
4 SSM/I 264-273 Sept. 21-30, 
(DMSP-F13) | Descending 1999 
5 SSM/I 274-283 Oct. 1-10, . 
(DMSP-F13) | Descending 1999 
6 SSM/I 305-314 Nov.1-10, 
(DMSP-F13) | Descending 1999 
7 SSM/I 325-334 Nov. 21-30, 
(DMSP-F13) | Descending 1999 
  
  
  
  
  
The data was available at two spatial resolutions viz. 
Low spatial resolution (25 km) brightness temperature 
data of 19, 22, 37 GHz as well as high spatial resolution 
(12.5 km) data of 85 GHz along with their respective 
geo-location information (latitude and longitude). The 
3db footprint size in along and cross track of SSM/I 
sensor is 69 x 43 km, 50 x 40 km, 37 x 29 km, 15 x 13 
km for 19,22,37 and 85 GHz channels respectively. The 
duration of the analysis covered total kharif season, 
which starts, with the onset of monsoon in India and is 
associated with variety of crops and natural vegetation. 
The study period covered the different crop growth stages 
as well as their various growing environment in terms of 
soil wetness. 
3. DATA ANALYSIS 
The passive microwave SSM/I radiometer data over India 
was analyzed in combination to the Optical NOAA- 
AVHRR PAL NDVI (Agbu and James, 1994) data during 
Kharif season. Brightness Temperatures (files available 
in hdf format) were geo-referenced and re-sampled over 
the Indian region (5-40? North and 65-100? East) at a cell 
resolution of 0.1 degree. Microwave Polarization 
Difference Index was computed for 19, 37 and 85 GHz 
channels using their vertical and horizontal polarization 
brightness temperatures. The MPDI is defined as: 
MPDI = (Tev-Tean)/ (Toy + Tan) (1) 
Where the Tgy and Tgy are brightness temperatures of 
vertical and horizontal polarization of the given 
frequency. The MPDI values were scaled by multiplying 
100. NOAA — AVHRR 8 k.m. Pathfinder geo- 
referenced data was used to locate different land cover 
classes based on ground information and NDVI temporal 
profile The NDVI and corresponding MPDI values were 
extracted for different land cover classes representing, 
rice, soyabean, cotton, sugarcane dominated region and 
other natural vegetation (forest). The scaled NDVI values 
of the NOAA-AVHRR data (in Digital Number (DN)) 
was converted to crop NDVI as: 
NDVI = (NDVI py — 128.0 ) * 0.008 (2) 
The surface wetness was calculated using multi 
channel approach from 19, 37 and 85 GHz over different 
dates. Multiple frequencies available on the SSM/I 
instrument have different responses to the liquid water on 
the land, and this response across the microwave 
spectrum indicates the percentage of the ‘radiating 
surface’ that is water. Wang and Schmugge (1980) 
developed a model for computing the emissivity of wet 
surface based on the dielectric constant of water (which 
increases with frequency) and the field capacity of soil. 
The lowest emissivity occurs when the surface becomes 
saturated with water, as in case of flooded land. As the 
fractional amount of wetland increases, the emissivity 
decreases and the slope of the emissivity between low 
and high frequency increases. The above observations 
indicate that the decrease in emissivity is related to the 
slope of the emissivity between two or more frequencies 
and is approximated as: 
Ae = peo[e(f) -e(f)] * Bi[e (£) -£(5)]. (3) 
Where, fj, £, and f; represent the 19, 37 and 85 GHz 
vertical channels, respectively, and Bo, PB; are 
proportionality constants. Based on the above principle, 
Basist et. al. (1998) have defined wetness index (WI) as: 
WI= Ae T “) 
Where, T is surface temperature. 
For land surfaces such as dense vegetation with 
high uniform emissivity, the temperature of the emitting 
layer, without atmospheric effects, is directly 
proportional to the passive microwave brightness 
temperatures and the proportionality constant is inverse 
of the emissivity. The emission from soil is polarized and 
it decreases with increase in vegetation cover. The 19 
GHz channel is preferred for screen air temperature 
estimation as it is least affected by atmosphere. For 
estimation of temperature over land with surface moisture 
present, additional terms other than 19 GHz are required 
to correct or compensate for the influence of surface 
water and atmosphere. Physically the screen air