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Agriculture / Soil
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Effect of Time of Data Acquisition on Crop Identification in North -Eastern India using NOAA -AVHRR Data
5. Results and Discussion
The morning pass images were brighter and gave better contrast among different land cover classes as observed in the false colour composite images. Univariate statistics like mean, standard deviation and entropy indicated that there was significant difference between the two images. In morning pass image the data occupied wider range in all the 3 channels compared to afternoon pass. All the channels showed more than 15% reduction in mean digital number in afternoon pass data. Similarly the entropy of each band and different band combinations were higher in the morning pass data. The range of entropy for individual bands of NOAA 11 was only from 2.271 to 2.685, where as it was from 2.958 to 3.036 or NOAA 11 was only 13.110 as compared to 15.534 for NOAA 12 data. This in turn affected the total number of spectral vectors combining channel 1, 2 and 3 for NOAA 12 was 90,000 which was more than 50% of total expected vectors. In comparison to this, in the afternoon pass images, it was only 47745 which is less than 30% of total expected vectors.
Table 3 shows the effect of morning and afternoon data acquisition on spectral signature of different land covers situated at different land covers situated at different locations as shows in Fig.1. This was for the data acquired on October 6, 1993. In channel 1, the reduction of DN value ranged from 2-3% in forest subclass to more than 35% for mangrove, sea water of sunderbans. The agriculture sites of different locations showed 25-30% reduction. Similar order of reduction was observed in channel 2 but the agricultural area showed highest reduction. In channel 3, the reduction ranged from 6-18 %.
Figure 1 Plots of mean with 1 50 to different land covers and rice-subclasses of West Bengal in band and band
2 of (a) NOAA 12 and (b) NOAA 11
Figure 2 Plots of mean with 1 50 to different land covers and rice-subclasses of West Bengal in band and band
2 of (a) NOAA 11 and (b) NOAA 12
The above observations indicate that there was significant difference in the apparent reflectance of natural surfaces as detected remotely in the morning and afternoon passes. Consequently the separability of various land cover and crop classes were affected. Fig. 1 shows the separability of training class pixel using channel 1 and 2 of NOAA 12 and NOAA 11.
The result showed that except for the urban, water (sea and river) classes, the separability of all other classes were poor in afternoon pass data. The effect was more pronounced for agricultural area. The different rice classes which were distinctly seperable as mentioned earlier were not separable from each other in the afternoon pass data. Also, the mangrove class overlapped with rice subclasses. In morning pass data out of five subclasses for rice, four were separable from each other.
The classification accuracy as observed from the confusion matrix of raining class pixels showed that the overall land cover classification was better than 90% using channel 1, 2 and 3 of morning pass data. The accuracy of rice subclasses varied from 90-95%. Using NOAA 11 data, the accuracy was below 80% for land cover classes.
The vegetation index (NDVI) of different vegetation classes overlapped with each other in NOAA 11 data. The total range was also compressed. It ranged from 0.08 to 0.21 in NOAA 11 and 0.48 to 0.29 in NOAA 12 for the subscene of West Bengal for October 6 data.
The dependence of the total reflectance of natural surfaces upon solar zenith angle is well documented (Rosenberg et al., 1983). In the present study there was change in zenith angel in observation. To asses this change, the zenith angle was calculated for the date and time of pass, as mentioned earlier. Table 4 shows the solar zenith angle of fixed locations for the study area from September 15 to November 15, 1993. It indicates significant difference in zenith angle as one proceeds from 860E onwards further to east.
The total expected insolation over the region will change from morning to evening. The decrease in isolation will be progressively more in November 15 in comparison to September 15. On September 15 it will be from 5% to nearly 50% over the region, whereas on November 15 it will go as high as 26% to close to 80% on the extreme ends of the region. The reduction in insolation over West Bengal from morning to evening passes on October 6 will be 6-28% from 860E to 880E longitude. This will be further more from the areas east of 880E and at 960E longitude it will be more than 60%. The change in isolation is expected to have significantly affected the image quality. Consequently for this region, the morning pass data from NOAA 12 is better suited for monitoring agricultural corps in Kharif and winter season.
6. Conclusion
Variability in channel 1, 2 and 3 of AVHRR data were higher in morning pass images acquired form NOAA 12 than that of afternoon pass of NOAA 1 for the nadir viewing cloud free pass for same day over north eastern Indian Region. Using morning pass data, accuracy of land cover classification was higher. The separability of field crops within agricultural area was also higher. This may be due to significant change in zenith angle which consequently cause change in insolation received by natural surfaces. Thus the morning pass data is more suitable for monitoring kharif crop for the area lying east of 860 E longitude.
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