loaded into SARscape in ENVI using the ASAR product 
standard format reader. The processing of the multi- 
temporal ASAR APS data involved several steps including: 
l. Data import of the original ESA datasets. 
2. Data multilooking (number of looks: 1 and 5 
respectively in azimuth and range), 
Data coregistration. 
4. Data multitemporal Filtering (using a De Grandi 
method). 
5. Extraction of SRTM-3 version 4 DEMs for use 
with geocoding. 
6. Data geocoding with radiometric calibration and 
normalization (using a grid size 25 m to match the 
resolution of the ASAR data). 
Ww 
These steps roughly consist of image calibration or 
conversion to the radar backscattering coefficient sigma 
nought (co), image registration or geocoding, and image 
spatial filtering (Nguyen, Armando, Thuy, Young, Trung, & 
Bouvet, 2009). Image calibration consists of correcting SAR 
images for incidence angle effect and for replica pulse power 
variations to derive physical values (Nguyen, Armando, 
Thuy, Young, Trung, & Bouvet, 2009). 
The processed SAR datasets were then fused with Landsat 
ETM+ scenes from 2011, and ENVI was used to classify the 
images in order to quantify the area covered by the rice 
Crops. 
3. RESULTS 
The processed SAR images for each of the dates during the 
growing season are represented in Figure 1 below. The rice 
crops are represented by the darker areas at the beginning of 
the growing season (Figure 1a) as the backscatter coefficient 
for water is lower. Once the plants emerge from the water, 
the backscatter coefficient gets higher and these areas 
become brighter in the images from August through October 
(Figure 1: b), c) and d)). As the crops mature and are 
harvested starting in November (Figure 1: e), the areas begin 
to appear darker again. 
  
  
    
k Bs 
a) July 2011 
    
  
September 2011 
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012 
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia 
  
   
  
    
  
“ e) November 2011 
Figure 1. Processed SAR Multi-temporal Images; HH 
Polarization 
After the ENVISAT ASAR data was processed, SARscape in 
ENVI was used to produce an RGB color composites using 
HH and HV bands in order to improve the visualization of 
the objects in the images. In the series of RGB color 
composites shown in Figure 2 below, red = (input 1 - input 2) 
/ (input 1 + input 2), green = input 2, and blue = input 1. 
This type of color composite enhances the differences in the 
backscatter results of the rice crops during different periods 
of the growing season. The forests (green) are more easily 
distinguished from the rice crop fields (red to purple 
depending on water content). 
  
) July 2011 
   
     
  
c) September 2011 d) October 2011 
- €) November 2011. 
Figure 2. Processed SAR Multi-temporal Images; Color 
Composites 
In the ETM+ image from Figure 3 below, at the end of the 
growing season in November, the light green areas represent 
the forested areas, the pink/purple areas represent the fields 
where the rice has been harvested, and the blue areas 
represent water.