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Agriculture / Soil
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Rice Crop Monitoring in Zhaoqing, China using RADARSAT SAR - Initial Results
4.0 Result and Observations
In a previous study of RADARSAT-simulated imagery of Zhaoqing, ground truth information provided by the Institute of Remote Sensing Application was used to classify land use and identify rice crops (Staples et al., 1994). In the 1994 study, mature wetaland rice, in the ripening growth stage and ready for harvest, and stubble (harvested rice) were identified. In addition, banana crops, urban areas, and aqaculture ponds were fish and duchs are raised were noted. Some of the aquaculture ponds are also used to grow gorgon euryale, a plant used for medical purposes. Based on the same ground-truth information, both of the RADARSAT Standard 5 images acquired in 1996, showed the same land-use classes identified in the RADARSAT-simultated imagery.
The March 5, 1996 Standard 5 RADARSAT image (subscence) is shown in Figure 1. The image size is 19 km 2 14 km. Rice paddies ®, aquaculture ponds (P), and banana crops (B) are marked. Other features in the March 5 image include the town of Gangli (G), the Lankeshan Uplands (U), the River Xijiang (X). The largest separation of DN values was between the ponds and the urban areas. The ponds were characterized with a mean DN of 30, and the urban areas with a mean DN of 185. This separation is not surprising given the characteristically strong radar backscatter due to corner-reflector response from building, and the weak backscatter due to secular reflection from the surface of the ponds (and the River Xijiang).
Figure 1. RADARSAT Standard Mode image (subscene) of Zhaoqing acquired March 5, 1996. Rice paddies ®, aquaculture ponds (P), banana crops (B), Lankeshan Uplands (UP, River Xijiang (X), and the town of Gangli (G) are indicated. Image size is 19 km x 14 km.
Subscenes of the Standard 5 imagery acquired march 5 and Jun3 10, 1996 are shown in Figure 2a and 2b. For botyh scenes, the image size is 11 km x 9 km. For comparison, these areas correspond to upper left-hand corner of Figure 1. In these images, three land-use classes were noted. Using the same lettering convening, rice crops® and aquaculture ponds (P) were identified, and in addition, aquaculture ponds, where a significant change in the backscatter occurred, were identified with the delta (D) symbol.
In the P-ponds, there was no significant change in the backscatter between the two acquisition dates. The DN remained essentially constant, with a mean value of 30 for both dates. The constant backscatter was attributed to the type of aquaculture activity, namely the production of fish and ducks. In this case, there was no (significant) change in the surface roughness, and therefore, little change in the radar backscatter. In both images, low backscatter was evident by the dark tones.
In contrast to the P-ponds, there was a significant change in the backscatter for the D-ponds. In the D-pond case, the mean DN was similar to the mean DN of P-ponds for the March 5 image, but the mean DN for the June 10 image had a value of 115. The change in the DN value was attriubuted to the growth of the gorgon euryale plant on the surface of the ponds. Presumably, this type of plant germinates in the subsurface stratum, but eventually grows through the pond surface, and also spreads across the pond surface. The plants on the pond surface produce volume scatter in, and hence increase the backscatter. In the March 5 image, the D-ponds had dark tones, but in the June 10 image, the D-ponds had brighter tones.
Figure 2a & 2b. RADARSAT Standard Mode imagery (subscenes) acquired March 5 (left) and June 10 (right), 1996. Rice paddies ® and aquaculture ponds (P-no significant change in backscatter) and aquaculture ponds (D-significant change in vackscatter) and indicated. Both images are 11 km x 9 km.
The variation of rice-crop backscatter is well documented (Le Toan et al., 1989 & 1995; Kurosu et al., 1995; Aschbacher and Paudyal, 1993). During the fallow growth stage the radar backscatter is a runction of the soil roughness, plant corner reflections between the wet soil and the stubble, creating bright image returns. During the folooding stage, specular scattering from the water surface results in low radar backscatter. As the plants tiller and grow, they expand both horizontally and vertically, eventually covering the water surface. During this vegetative growth phase the radar surface. The radar backscatter peaks during this growth stage with the plant growth is at a maximum. As the crop ripens, the plant water-content decreases with causes a decrease in the radar backscatter. The backscatter reaches a minimum just prior to harvest.
Rice paddies ® were readily identified in the RADARST imagery, largely due to tone and texture variations as compared to other crops. The change of DN values, however, for the rice paddies between the march 5 and the June acquisition. The variability was attributed to the timing of the RADARST acquisition relative to the cropping calendar, and inhomogeneous growing conditions (see Table 1.) The march 5 image was acquired during the sowing stage, when the backscatter is a function of the field and soil conditions, and therefore variable. During the transplanting stage, when the backscatter is a function of the field and soil conditions, and therefore variable. During the transplanting stage, when the fields are flooded, a significant decrease in the backscatter is expected, but the next RADARST acquisition was not until June 10 (the heading stage). Although radar backscatter should be near, or slightly below maximum at the time of the heading state, inhomogeneous growing conditions, in combination with variation in the vegetative phase, were likely a contributing factor in the observed backscatter variability. As noted by Malingreau (1986), the vegetative phase determines the total duration of the rice crop life cycle, since the reproductive phase is of more or less constant duration for all rice for all rice varieties.
5.0 Conclusion and Future Work
RADARST Standard Mode imagery of Zhaoqing, China, when merged with ground truth information was used to identify rice crops, aquaculture ponds, banana crops, and urban areas. It is evident that RADARST has both the radiometric and geometric resolution for land-use discrimination.
For rice crop monitoring, however, an adequate time
series of data is required, and is addition, knowledge of the regional cropping calendar is also required. If RADARSAT imagery is to be used to produce estimates of the total rice crop acreage for a given area, or for the production of rice crop yield forecasts, then more work is required, but the potential for rice crop monitoring is strong.
The intent of this paper was present early results on the use RADARSAT for rice crop monitoring. Although the two images analyzed provided a solid starting point, more analysis and additional image acquisitions are required. Image acquisition must be planned to coincide with the rice crop growth stages. Acquisitions during the sowing stage would allow the discrimination between ponds and rice paddies, and in particular to provide discrimination (required at a later date) between the ponds where the gorgon euryale plants are grown and the vegetating rice crops. During the flooding stages, the low backscatter would provide a benchmark to monitor the backscatter change. The key acquisition period is between the tillering and heading stage. During this time frame, the backscatter will be maximum, and if the backscatter is related to a rice-crop yield mode, then yield predictions can be calculated in advance of the rice harvest.
Acknowledgements
Dr. Chao Wang, Institute of Remote Sensing Application, Beijin, China, provided the ground truth information for interpretation of the RADARSAT imagery and the rice cropping calendar for the Zhaoqing region. The RADARSAT imagery was provided by and is a copyright of the Canadian Space Agency. Data reception was provided by the Canada Centre for Remote Sensing and data processing by RADARSAT International.
References
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