Accounting crop output

New techniques based on remote sensing can help

Official statistics in India have long been suspected to be no better than “guesstimates”, and in more recent years, the quality of Indian statistics has, in fact, declined. This despite the fact that the administrative machinery for data collection has been refurbished with the creation of the National Statistical Commission. Several expert committees have been examining the quality of data in different sectors of the economy and recommending improvement. A committee headed by economist and former Planning Commission Member A Vaidyanathan has now mooted a two-pronged strategy to revamp the procedure of compiling agricultural estimates. It involves greater use of satellite-based remote sensing technology and restructuring of the data collection machinery. For implementation of this strategy, the committee has suggested establishment of a wholly new entity — national crop statistics centre (NCSC). The committee has itself acknowledged that there could be problems with existing remote sensing techniques and admits that a large part of the reason for existing deficiencies in official statistics could be related to the weakness of human capital engaged in data collection and analysis. The officials in charge of “girdawari” (actual field-level recording to crop sowing and projection of expected crop yields) are notorious for not doing their job properly. They often send cooked-up reports without actual field visits. Even crop cutting experiments for estimating crop yields at the end of the cropping season are often conducted improperly, resulting in glaring inaccuracies. This apart, most state governments, having abolished land revenue, which required maintenance of meticulous land-use records, do not give due priority to this task any more. Village-level staff is usually overburdened with multiple functions. Inspections of the records by higher-level officials for verifying their accuracy is usually rare. If the proposed NCSC also has to operate through similar grass roots functionaries and under similar circumstances, malpractices may be difficult to do away with.

 

Satellite-based remote sensing technology can help improve farm data collection, but it has its limitations. That is perhaps why the scope of FASAL (forecasting agricultural output using space agro-meteorology and land-based observations) is still restricted chiefly to revalidating the manually collected numbers and not for gathering primary data. Necessary models for generating state- and national-level data are currently available only for a few major crops, such as rice, wheat, potato, cotton, sugarcane, sorghum and the like. Besides, the ability of satellite imageries to differentiate between similar-looking crops is limited. So is their ability to capture areas under minor crops and mixed crops grown on small and fragmented lands. Fortunately, remote sensing technology is making rapid advances in terms of both satellite capacities and resolution of the imageries. What is lacking are reliable models which can forecast likely crop output, taking into account the large number of factors, including input-use and weather, that go into determining crop yields. However, given the inadequacy of existing data collection systems, greater reliance on remote sensing technology could help.