1.0 Introduction
Satellite remote sensing based crop inventory and monitoring has the advantage of synoptic, spatial and temporal coverage of an area. The precision of such procedures has improved over the years and now it meets the requirement of timely gathering of routine information on crop prospects. Crop Acreage and Production Estimation (CAPE) is an on-going project in India, which uses optical remote sensing data to forecast production of major cereals, oilseeds, and fibre crops (SAC, 1995). Procedures have been developed for use of single date data from Indian Remote Sensing Satellites (IRS), acquired at peak vegetative growth of the crop, to estimate the crop acreage. Attempts have been made to develop vegetation index based yield models to forecast the crop yield. These have been tested at a large number of sites, over the years and found to perform satisfactorily (Navalgund et al, 1991). After the launch of IRS-1C and 1D satellites, multi-temporal monitoring of crops at regional scales using data from WiFS sensor, also became feasible. This has been successfully demonstrated for making national level, multiple forecast of wheat crop in India.
However, multiple forecasting of crops grown in monsoon season (Kharif), like rice have not been very successful. This happens entirely due to non-availability of temporal, cloud free data. Studies of weather data and Landsat data acquired for south and south east Asia indicate that, there are fewer images available during the entire 120 day growth period of the crop, with virtually no images during the early vegetative stage (Currey et. al., 1987). Similar observations have been made in a study using NOAA-AVHRR data acquired during kharif season in India. It was found that during the months of August and September large parts of country remains cloud covered, limiting the availability of data from optical remote sensing sensors (Bhatt, 1996).
2.0 Importance of Rice Crop for India
Rice is the major food grain of world and south and south east Asia in particular. Rice is grown in almost all states in India. Kharif or rainy season is the main crop growing period in India. Rice being climatically most adaptable cereal, various types of land management systems for rice cultivation exists, these are otherwise known as cultural types. There are two predominant cultural types, the lowlands or wetlands and the uplands. The crop establishment method, the depth and duration of standing water in the fields during crop growth period and the per cent plant cover vary with the cultural practice. Lowland is the predominant cultural type in South and South-East Asia. Shallow and intermediate type of lowland rice lands are predominant in India.
Green revolution in India was the result of substantial increase in production of cereals, particularly wheat and rice. To meet the demand of growing population and to provide food security to its people in the new millennium, it is proposed to aim at doubling the food production in next ten year. Currently a variable rate of growth for different food items has been visualised. Among the cereals, rice and wheat will continue to dominate among various crops. These crops were grown in very vast regions in the country and there adoption in the non-traditional areas has been possible. Though wheat has been introduced in the parts of eastern India, but the increase in rice acreage and production in the north western parts of the country, is noteworthy. This is entirely due to adaptability of rice crop to wider range of agro-climatic conditions. Thus, rice is emerging as the principal food grain of future and management of rice crop production could emerge the key area of management in agriculture.
3.0 Early Experience in use of Sar Data for Rice Crop Inventory
Operational use of SAR data for rice area monitoring called for critical evaluation of accuracy of classification in various rice growing environments. The possibility of examining space borne radar data for large area agricultural application was realised with the successful launch of ERS-1 Synthetic Aperture Radar (SAR) in 1992. Studies were carried out to understand the signature of rice crop at different stages of growth. Early efforts were directed towards studying the classification accuracy of areas belonging to different cultural types as well as early and late sown rice. Developments in this phase are briefly described here.
3.1 Sar Signature in Relation to Rice Growing Environment
The study of SAR data showed that all low land rice irrespective of their cultural type viz. shallow, intermediate and deep water rice, exhibited a characteristic temporal backscatter profile in the SAR data. All the rice fields showed a distinct decrease in backscatter in the data which corresponded to the transplanted fields of rice. Very low backscatter was observed from rice fields during the early vegetative stage, irrespective of the cultural type. Surface scattering from the field water does not contribute much to the backscatter and the crop cover being very low, the volume scattering from the canopy was also assumed to be low at this stage of growth. Maximum contrast of rice fields was observed during this period. The field ridges, trees lining the boundaries were very bright due to corner reflection effect. The field boundaries, canals lined with trees and small drainage channels could be seen, very prominently. Rice showed the largest dynamic range of backscatter during the early stages of crop growth. In the subsequent dates, a considerable increase in backscatter was observed from all types of rice fields and it peaked around 60-80 days after transplantation. The contrast of rice fields decreased sharply and field boundaries were then no longer visible. As the crop reached near maturity, the backscatter increased significantly and the separability between classes decreased sharply. Thus, multi-temporal SAR data has emerged as a good source of remotely sensed data. The typical signature of rice crop in multi date SAR images was gainfully employed in it classification achieving over all identification and classification accuracy of more than 90 per cent (Chakraborty et al., 1997).
3.2 Rice Crop Classification with Sar Data
Preliminary analysis of C band 23 degree incidence angle SAR data of ERS were carried out during 1992-93 for rice, sugarcane, cotton and groundnut grown under different agro-climatic condition in India (SAC, 1995). These studies showed that the wetland cultivation practice of rice exhibits unique temporal backscatter in temporal ERS SAR data. Low backscatter characterised freshly transplanted rice fields due to specular returns from water in puddled fields and it increased steadily with the crop growth. Multidate data acquired at critical bio-window of the crop growth was used to identify and classify rice fields with high accuracy (Patel et. al. 1995). Similar results have been reported from other Asian rice growing areas (Kuroso et. al. 1994, ESA, 1995). Multi-date SAR data available from RADARSAT was critically examined for classification accuracy of rice crop representing varying rice culture types.
3.3 Importance of Dates Of Acquisition of Multi-Temporal Sar Data
Data acquisition period in relation to crop growth was found critical to obtain high classification accuracy. A set of combination were tried to evaluate the classification accuracy achieved. Among the set of 2,3 and 4 acquisition data sets, three date data was found to result in higher than 95 percent classification accuracy, which was considered optimum for this purpose. While selecting the dates of acquisition, it was observed that, the data acquired at field preparation stage i.e. puddling/transplanting stage was essential for rice crop estimation. The 35 day repeat cycle of ERS SAR was found to be a constraint in the selection of optimum dates of data acquisition, coinciding with proper bio-windows.
