Suitability of Multidate ERS - 1 SAR Data for
Crop Acreage Estimation
Groundtruth Collection and Data Processing :
Near synchronous ground truth for soil moisture, surface roughness conditions, crop parameters such crop height, density, growth stage have been collected for three ERS-1, SAR scenes acquired on 17th Dec 1992, 21st Jan 1993 and 25th February 1993. The IRS-1, LISS-II data of 2 Jan 93 was also acquired for validation of results obtained by SAR data analysis. Figure 1a shows a multidate colour composite image of SAR data and figure 1b shows standard FCC image of IRS LISS II data of the study area. The data sets were rectified for geometric distortions by registering tot eh topmap with the help of ground control point and a polynomial equation. The ten revenue mandal boundaries were digitized and overlayed on the ERS and IRS data sets. The ERS-1 SAR data were filtered for speckle as well as image texture suppression using a 5 x 5 moving window median filter. Training area were identified on the IRS 1 LISS II standard FCC image and purified. The spectral Major Classes covered have been paddy, pulses (green gram and black gram), tobacco, cashew and mango plantation, coconut and nurseries, settlements, paddy fallow and permanent fallow fields and fodder crop of subhemp, the training area statistics were used to compute Jetfried-Matusita distance (measure 1). For single dimensional data sets, seperability had been computed as difference in class means over the products of class standard deviation (measure 20. Subsequently, multidate ERS-1, SAR data and single date and multiband IRS-1 LISS II data were separately classifieds by maximum likelihood classification algorithms. Figure 2a shows classified image of the study area, generated from LISS II data and figure 2b shows the same area as classified by multidate SAR data.
Figure 1 Multidate ERS - 1 Sar ECC image (left) and standard IRS LISS - II ECC image of 2nd Jan'93 (right)
Figure 2 Classified imagery of IRS LISS - II data (left) and multidate ERS - 1 SAR data (rught)
Results and Discussion
Among the single date ERS-1 SAR data sets, data acquired 21st Jan 93 was found to have highest average seperability (S) of 0.925 (S >= 1.0, the classes are separable) compared to data acquired on 17th Dec 92 (S=0.668) and 25th Feb 93 (S = 0.666). Greater seperability in Jan 93 data set may be attributed to the maturity of crops during the mid crop season and minimal background influence. Paddy crop was seperable from other major crops like tobacco, pulses and sunhemp (with S = 1.347) but has a overlap with fallow fields with an average seperability of s = 0.438. However, separability was poor in the Jan 93 data set among tobacco pulses and sunhemp crops.
The seperability as computed by JM distance (measure 2) for three date ERS-1 SAR data showed that paddy is separable from all classes with JM distance being higher than 1292 (with upper limit being 1414). However, average seperability among crops tobacco, pulses, sunhemp and plantation was only 908 with an overlap of nearly 36%. A similar observation was made with single date, three band (band s2,3 and 4) LISS II data with the seperablity of 1140 and an overlap of 20% for these crops. A combination of LISS II bands 3 & d and ERS-1 SAR data of Jan 93 showed that overall seperability had increased to an average of 1355 with an overlap of only 5% among all classes.
Table 1 shows results of maximum likelihood classification, obtained for LISS II data set of bands 2,3 and 4 and three date ERS-1 SAR data set of Dec'92 Jan 93 and Feb 93 and BES values wherever available. It is clear from the table that identification and acreage estimation of paddy crop is possible sensor data. However it is necessary to validate these findings considering the data set acquired during kharif season. It can also be noted that fallow fields are under classified wit most of the unclassified pixels being otherwise those of fallow fields.
Table 1 Acreage of major classes in the study area as obtained form classification of ERS-1 SAR and IRS LISS II data.
| Class |
Area (in acres) |
| IRS LISS II data |
ERS - 1 SAR data |
BES figures |
| Tobacco |
41616 |
21996 |
-- |
| Paddy |
42880 |
42632 |
49251 |
| Pulses |
26969 |
32419 |
74182 |
| Fallow fields |
56466 |
16315 |
65743 |
| Mixed crops (Pulses/tobacco/sunhemp |
7166 |
17732 |
-- |
| Unclassified |
55798 |
96620 |
-- |
In the present study, to realize best of the classification by per classifier like maximum likelihood algorithm, the SAR data were processed for speckle and texture suppression. This might have resulted in loss of seprability to some extent in discriminating classes like fallow fields from paddy. In view of this it is felt that classification of SAR data by per pixel classifiers should follow texture segmentation for better classification accuracies.
Conclusions
In the present study attempts were focused on the use of ERS 1 data alone for crop identification and acreage estimation. Following conclusions may be drawn from the analysis of results.
-
Among three date ERS-1 SAR data sets used in the study, data acquired on 21st Jan 93 is observed to show maximum discrimination among various classes confirming the earlier results by visual analysis of single date data sets.
- Use of multidate ERS-1 SAR data acquired at 35 day interval during a crop season for digital classification improved classification.
- Present study showed ERS-1 SAR sensor is suitable for identification and acreage estimation of paddy crop.
- Discrimination of crops like tobacco, pulses (green and black gram) and subhemp was poor. This may be attributed to the same mean intensity associated with large standard deviation of these classes.
Acknowledgements
Authors are grateful to Prof B.L Deeskatulu, Director, NRSA and DR. D.P. Rao, Associate Director of NRSA for their continuous support and encouragement. The authors are thankful to the Department of Space, Govt. of India for sanctioning the ongoing project under the ERS-1 RSAM-MC program.
