JAPRS & SIS. Vol.34, Part 7, “Resource and Environmental Monitoring”, Hyderabad. India,2002 
  
A CONTRIBUTION TOWARDS DEVELOPMENT OF AN OBJECTIVE TECHNIQUE FOR 
PFZ FORECAST USING REMOTELY SENSED DATA: PATTERN ANALYSIS OF 
FEATURES 
H. U. Solanki* and Shailesh Nayak" 
Marine and water resources group, 
Remote Sensing Applications Area, 
Space Applications Centre, (ISRO), 
Ahmedabad 380 015, India. 
Emial: himmatsinh ? yahoo.com 
"Commission VII 
(Keywords: Fisheries, chlorophyll, PFZ, surface and spatial profiles, patterns) 
ABSTRACT 
The variability in chlorophyll concentration is considered to hold a key to understand the relative importance of physical and biological 
factors in structuring the food web. The different types of oceanographic features are known to play a key role in distribution fishery 
resources. IRS P4 OCM (Ocean colour Monitor) data have been used in this study to retrieve chlorophyll concentration. The ocean 
colour features were delineated on chlorophyll concentration images. The different types of features were selected for generating surface 
and spatial profiles. The three-dimension surface and two dimension spatial profiles were generated based on the chlorophyll 
concentration to understand the surface and spatial patterns of features, respectively. The plots exhibited clear appearance of the shape of 
the feature with chlorophyll concentration variation. The plots visualize the feature types available in the scene as well as patterns of their 
shape, chlorophyll concentration and the gradient. An attempt has been made to extract oceanic features using texture algorithms. 
Variance algorithm was found more suitable for feature extraction among three algorithms used. This study contributes towards 
development of an objective technique through pattern analysis of surface and spatial profiles of different types of features observed on 
chlorophyll concentration images. This paper discuss different type chlorophyll features important for identifying the PFZs, pattern 
analysis of their surface as well as spatial profiles based on chlorophyll concentration and their application to develop an automated 
technique for PFZs identification. This study suggests selection and extraction of features using pattern recognition system for PFZs 
  
generation. 
1. INTRODUCTION 
Synoptic estimates of chlorophyll are important because 
phytoplankton variability in space and time is important feature of 
marine environment. The variability in chlorophyll is considered 
to hold a key to understand the relative importance of physical 
and biological factors in structuring the food web. The different 
types of oceanographic features are known to play a key role in 
distribution fishery resources (Laurs el al. 1984, Lasker et al. 
1981, Fiedler et al. 1987, Solanki et al. 2001b). The features form 
due to different type of circulation patterns contributed by 
different sources of energy like wind, current, tides in 
combination with bottom friction. An approach for integration of 
chlorophyll concentration image and SST image was developed 
by Solanki et al. (2000). At present features like front, meander, 
eddy, ring, upwelling are being considered for locating potential 
fishing zones in India (Solanki et al. 2001a). The technique for 
PFZs forecast using integration of SST and chlorophyll has been 
transferred to Indian National Centre for Ocean Information 
Services (INCOIS), Hyderabad for operational use to make 
country wide PFZs forecast. The identification and application of 
these features for locating PFZs is highly subjective and person 
dependent. Therefore, there is a need to develop an objective 
method for potential feature identification and extraction for 
exploring fishery resources. Majumdar and Bahttacharya (1991) 
have used aerial data for extraction of shore line change and to 
study drainage patterns. The objective technique would help the 
464 
users in generating PFZs automatically. This is the background 
study to understand the problem and develop the approach for 
objective technique. 
2. METHODOLOGY 
IRS P4 OCM (Ocean Colour Monitor) data was utilized for 
retrieval chlorophyll concentration. Atmospheric correction of 
OCM data was carried out using method suggested by Gordon 
and Clark (1980). OC2 algorithm was applied for retrieval of 
chlorophyll concentration (O'Reilly et al, 1998) from 
atmospherically corrected radiance values. Different types of 
important features for fisheries applications (Solanki et al. 2001a) 
like eddies, rings, meanders, fronts (Figurel) were considered for 
generating surface and spatial profiles. A window of 50x50 pixel 
or 100x100 covering the feature was taken for generating surface 
profiles depending on the area covered by the selected feature. 
The surface profiles were in three dimensions indicating the 
column (pixel no) on X axis, rows (pixel number) on z axis and 
pixel value (chlorophyll concentration) on y axis. The plots give 
clear appearance the shape of the feature with chlorophyll 
concentration variation. The poly lines were taken for generating 
spatial profiles were in two dimensions showing pixel number 
(distance) x axis and chlorophyll concentration on y axis. The 
patterns of different type of features were compared as per the 
shape of the feature and concentrations of chlorophyll pigment in 
the area the feature.