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Assessment of Multi-temporal Radar Imagery in Mapping Land System for Rainfed Lowland Rice in Northeast Thailand


Conclusions
This study demonstrates the use of multi-temporal ERS-2 data for mapping land system for rice. Even thought this temporal data set was not ideal, from two consecutive years, it was found that this data set was efficient in identifying and mapping land system units through the phenomenology of rice growth stages. The method developed employing supervised maximum likelihood classification gave good results with the necessity of applying pre-processing steps to reduce speckle, using both multitemporal and spatial filters, prior to classification.

In mapping detailed land system units for rice (7 identified classes i.e., floodplain, lower low-terrace 1, lower low-terrace 2, upper low-terrace 1, upper low-terrace 2, middle terrace and irrigated low terrace) by applying six images, floodplain, middle terrace and irrigated low terrace were found to be easily discriminated due to high temporal change in case of floodplain rice (10 dB), unique pattern of radar response at rice planting stage for middle terrace rice (delay in planting) and still moist/wet after harvesting for irrigated low terrace. The four sub-units (lower low-terrace 1 and 2, and upper low-terrace 1 and 2) of low terrace occupying majority of the study area were the focus in this study. The two profiles of lower low-terraces showed early season and normal season rice with 6 dB temporal changes in radar response (minimum in planting and maximum in maturity stage), but shifting in planting periods. The two profiles of upper low-terraces show similar radar responses within the rice season period therefore making it difficult to discriminate them. However when adding an image outside the rice growing period particularly the June image (prior to planting image), these two units were able to be separated easily (–3 dB for upper low-terrace 1and -9 dB for upper low-terrace 2). The overall accuracy of the classified image was 84.7%. In case that a number of images used were selectively decreased to five or four, the accuracy reduced to 73.8% and 55.7% respectively.

For individual mapping units, aiming at accuracy higher than 80%, the classes of floodplain, lower low-terrace 1 and middle terrace require four images, lower low-terrace 2 requires five images, and upper low-terrace 1 and 2 and irrigated low terrace require six images.

For broad categories of land system, when the number of classes reduced from 7 to 5 or 4 units, the accuracy improved significantly with the applying either 4, 5, or 6 images. The overall accuracy was higher than 90%. Selection of SAR images can be as few as four images, i.e. planting stage (July image), vegetative stage (September image), pre-harvesting stage (October) and post-harvesting stage (January image). Addition of the fifth image during land preparation stage (June image) helped to improve the classification result significantly but the sixth image at maturity stage (November image) had minor contribution.

Comments and Recommendations
The use of SAR multitemporal analysis concept for classifying land system for rainfed lowland rice seems to be promising. However a temporal data set for the same rice cycle should be tried with the same methodology and additional studies in other geographical locations should be carried out to validate the classification results. Real time ground truth will help in better understanding the backscatter behavior of rice fields.

References
  • Aschbacher J., Pongsrihadulchai A., Karnchanasutham S. Rodprom C. Paudyal D.R. and Le Toan, 1995. Assessment of ERS-1 Data for Rice Crop Mapping and Monitoring. Proceedings IGARSS, Florence, Italy, July 1995, pp. 2183-2185.
  • Junthotai K., and Mongkolsawat C., 1990. Land Ecosystem Mapping and Soil Fertility Evaluation Using Landsat TM Data: A Case Study in Upper Namphong Watershed Area. Proceeding of the Seminar on Remote Sensing and Water Management, Thailand.
  • Kurosu T., Suitz T., and Moriya T., 1993. Rice Crop Monitoring with ERS-1 SAR: A First Year Result, Proceeding Second ERS-1 Symposium, Germany, pp. 97-101, (ESA: SP-361).
  • Le Toan, T., Ribbes, F., Wang, L., Floury, N., Ding, K.H., Kong, J. A., Fujita, M., 1997. Rice Crop Mapping and Monitoring using ERS-1 Data based on Experiment and Modelling Results. IEEE Transcations on Geoscience and Remote Sensing, vol 35, no 1, January 1997, pp. 41-56.
  • Liew S. C., Kam S. P., Toung C. P., Minh V. Q., Balababa L. and Lim H., 1997.
  • Application of Multitemporal ERS Synthetic Aperture Radar in Delineating Rice Cropping Systems in the Mekong River Delta, Proceedings 3th ERS Symposium on Space at the Service of Our Environment, Italy, 1997.
Table 1: Land system units for rainfed lowland rice in the study area.
Land system Units  Vegetation conditions  Terrain types  Relief/Elevation  Surface material  Soils (Soil series)
1. Floodplain  Paddy field with bare cover of shrubs  Flood plain  Level(115-120m)  Quaternary deposit  Alluvial complex, Aeric paleaquults (Re)
2. Lower low-terrace1  Paddy field with bare/slight cover of scattered dipterocarp trees  Lower fluvial terrace  Nearly level (120-140m)  Alluvial/Eolian deposit  Vertic tropaquepts (Pm)
3. Lower low-terrace2  Aeric paleaquults, Aquic quartzipsament, (Re/Ub)
4. Irrigated low terrace  Aeric paleaquults, Oxic Plinthaquults, (Re and On)
5. Upper low-terrace1  Paddy field with moderate cover of scattered dipterocarp trees  Association of lower and upper fluvial terrace Undulating to nearly level(130-160m)  Alluvial/Eolian deposit  Oxic paleustults (Kt)
6. Upper low-terrace2  Oxic paleustults, Typicplinthustults (Kt/Pp)
7. Middle terrace  Paddy field with dense cover of scattered dipterocarp trees  Upper fluvial terrace  Gently rolling to undulating(150-170m)  Alluvial/Eolian deposit  Typicplinthustults (Pp)


Table 2: Temporal changes of signature profiles for rice classes based on within and outside rice growing season.
Rice Signature classes   Backscatter of SAR signature profile   Temporal stability
Within growing season June to November    
1) Floodplain   -16 to -6 dB (10 dB)   High temporal change (10dB)
2) Irrigated low-terrace    -11 to -8 dB ( 3 dB)   Low temporal change (3dB)
3) Lower low-terrace 1&2   -12 to -6 dB ( 6 dB)   Medium temporal change (6dB)
4) Upper low-terrace 1   -12 to -7 dB ( 5 dB)   Medium temporal change (5dB)
5) Upper low-terrace 2   -11 to -7 dB ( 4 dB)   Medium temporal change (4dB)
6) Middle terrace 3   -9 to -8 dB* ( 1 dB)   Low temporal change* (1dB)
*partial temporal curve, missed 
beginning of the season (Aug image)
Outside growing season In January     Comments
1) Floodplain   -6 dB    Wet soil condition
2) Irrigated low-terrace    -8 dB    Wet soil condition
3) The remaining 5 classes   -10 dB   Dry soil condition
In June    
1) all classes   -12 to -3 dB ( 9 dB) High variability due to water 
surface and cultivation practices
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