4.0 Large Area Rice Crop Inventory
Systematic efforts on district level rice acreage estimation using multi-date ERS SAR data for selected districts of West Bengal and Orissa during 1994-95 kharif season (Panigrahy et al., 1997). Boundary mask approach with complete enumeration of data was adopted in this case. During the year 1996-97 study was extended to larger areas with selection of districts in the states of Assam, West Bengal, Orissa and Tamil Nadu. In this case a sampling based approach was adopted for selection of multi date ERS- SAR data for digital classification.
The scope of utilising SAR data widened with the launch of RADARSAT in 1995. Investigations were carried out under the project entitled "RADARSAT data evaluation for crop identification and characterization", under Application Development and Research Opportunity (ADRO) programme (ADRO project ID 349) of RADARSAT sponsored by RADARSAT International (RSI) and Canada Centre of Remote Sensing (CCRS), Canada. In this study RADARSAT S1, S5, S6 ,S7 and ScanSAR Narrow data were used to investigate rice signature and classification (Panigrahy et al 1999). The analysis showed that rice crop retains its unique temporal backscatter profile in SAR data irrespective of incidence angle. Classification accuracy was more than 90 per cent in all the beam mode data investigated. However, the shallow incidence angle (S6, S7) were found to be less sensitive to wind induced roughness than the steep angle beam (S1). This increased the separability of water and rice field in shallow angle data. ScanSAR Narrow (SN2) data acquired at early stages of crop planting resulted 95 per cent accuracy for puddled fields in the irrigated lowland rice area. It also showed the possibility of deriving information on sowing period, growing environment etc. Due to the large swath and shallow incidence angle, SN2 data was adjudged suitable for large area monitoring.
4.1 Operational use of Sar Data for Rice Inventory
In-season rice crop monitoring was attempted in Assam, Orissa, West Bengal and Tamil Nadu states during 1998-99 kharif season using RADARSAT ScanSAR Narrow beam data. Two date data acquired early in the season were used to assess the possible crop prospects based on puddling and transplanting activities. Three and four date data were used to estimate the acreage. A stratified random sampling approach was used to analyse sample segments and estimate the area. An automated software -'SARCROPS' was developed for this purpose (Chakraborty, 1999). The objective of developing this software was to use a standardised and uniform technique for all study states, as well as fast and efficient data processing. The software consisted of three sub-modules- SAR image and ancillary header data extraction, optimal speckle suppression and conversion of digital numbers to backscatter. Besides this attempts were made to use the satellite ephemeral data to improve the map-to-image transformation model. This software improved the efficiency and timeliness of analysis This is of particular significance for the number of participants from the state user agencies like Department of Agriculture, State Remote Sensing Centre etc., who participate in the implementation of the project. A decision rule based classification algorithm was developed and used to delineate rice areas. The temporal data provided the required basis to categorise rice crop based on its planting date and growth characteristic.
During 1999-2000 kharif season - the project was extended to 13 states in India these states contribute around 92 per cent to national rice production. ScanSAR narrow beam-2 data acquired from pre-field preparation to about 45 days after transplanting was used. Multi-date registered data set of minimum three dates enabled estimation of rice acreage by middle of September, which is otherwise not possible with remotely sensed data.
4.2 Monitoring Progress in Planting of Rice
In India planting period of rice crop has a large spread. This leads to a situation where fields could be found having different stages of crop at any given time. Still in the large part of rice growing areas a definite crop calender is followed, any major deviation from this results in loss of production as well as affects the crop rotation practice. Use of multi date SAR data in the early part of crop growing season has been found useful to detect and monitor prolonged flooding of rice fields in parts of Assam state. This resulted in non-availability of seedlings by the time fields were available for planting. This type of information has potential use in, deciding about the area which can be covered by early planting of winter pulses and oilseeds.
It has also been possible to detect delay in planting caused due to late arrival and insufficient rains. In the state of Orissa, north-eastern part of state received low rains which was clearly observed in RADARSAT data of July and August months of 1998. Monitoring of the area till middle of September indicated that large tract of agricultural fields remained unplanted during the season.
4.3 Rice Crop Growth Modelling
The temporal backscatter of rice fields exhibited different pattern for differently managed system. The irrigated well managed rice fields showed a steady increase in initial growth which saturated early in season due to dense canopy cover. In poorly managed intermediate areas with slow crop growth, the profiles showed negligible increase during initial growth phase. Fields flooded after a initial crop establishment period exhibited a different profile. This indicates the possibility of modelling for crop growth assessment using shallow incidence angle SAR data.
4.4 Assessment of Damage Due to Flooding / Sea Serge
The state of Orissa was hit by a high magnitude cyclone (Super Cyclone) with wind speed exceeding 250 km/hour. This was associated with more than 400 mm of rain in a day and also sea surge. Large tract of land was submerged in the Mahanadi delta, predominantly rice growing area. Rice is planted in this region during the month of August and harvested in November and December months. Thus the rice crop was at early stage of reproductive phase or nearing maturity. ScanSAR data of November 2 and 4 was the only usable data available for assessing the areas affected by floods at the time. These were used in conjunction with the ScanSAR narrow beam 2 data of July and August months. The flood area mask generated with the November data was overlayed on the rice area map created earlier. It was found that out of 1107.4 thousand ha rice 316..36 thousand ha i.e. 28 percent of rice grown in the 8 coastal districts of Orissa state was submerged for a period of 4 days or more. This would lead to loss of production of 426.9 thousand tonnes of rice due to inundation alone.
5.0 Characterization of Rice Cropping Systems
The north eastern and eastern region belonging to the traditional rice area of India has a great potential for higher production due to the rich and favourable growing environment. A cropping system approach has been envisaged during the coming decade by the Ministry Of Agriculture, Govt. of India to increase the cropping intensity as well as yield. The analysis using multi-date SN2 data acquired from July to October months, highlighted the peculiarity and constraints of rice cropping system of this area. This information can be used to plan and adopt better productive cropping pattern in the region. The following are some of the observations made after the analysis of this data.
In Assam, only 15-20 per cent area was found to be transplanted by August 05. Large area flooding was observed in Barak valley as early as by July 12. The fields were submerged for more than a month in many parts of the state. Crop was sown as late as September in this area. Flood hazard probability was high in Barpeta, Nalbari, Lakhimpur and Sonitpur districts in Brahmputra valley. Flood in early July and August though does not affect the standing rice crop in most of the districts, however, it has adverse affect on the seed beds raised for nursery. The inundation of fields up to August delays the transplanting. This will have two effects - reduction in critical growth period, causing large reduction in yield, and delay in harvesting of rice, which will affect the sowing of mustard crop, the next immediate crop of the valley. The analysis indicates that the agro-ecology of the valley renders the present cropping pattern a vulnerable system. Flood is an annual phenomenon in early and mid monsoon period in one or other parts of the valley. The calendar of Sali rice, the major crop of the area coincide with it. This prevents achieving even the minimum targeted production of the crop. In spite of favourable climate, fertile soils and the sincere efforts made by the Department of Agriculture, the productivity has stagnated and the average yield of the state is only 1250 kg/ha, one of the lowest in the country.
In the West Bengal state, more than 60 per cent areas were sown by July end, with normal onset of monsoon. Sowing is earlier in North Bengal area compared to South Bengal. Damage due to submergence of crop early in the season exits in Maldah and Murshidabad area. The alluvial zone of South Bengal region showed very good crop management practice. Bardhaman district showed the best managed crop growing environment in the state with almost no hazards of flood or moisture stress.
In Orissa, onset of monsoon and amount of rainfall was found to control the rice sowing almost in all the districts. Even in the coastal region, with irrigation facility, the crop sowing/transplanting continues as late as, September first week. Delayed transplanting and moisture stress, late in the season are the two major constraints observed in this area.
