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Use of satellite data and farmers eye estimate for crop yield modeling

Randhir Singh
Indian Agricultural Statistics Research Institute
New Delhi 110012 India



1. Introduction
Agriculture is the backbone of Indian economy, contributing about 40 percent towards the Gross National Product (GNP) and providing livelihood to about 70 percent of the population. So for a primarily agriculture based country like India, reliable accurate and timely information on types of crops grown and their acreages, crop yield and crop growth conditions are vital components for the planners engaged in formulating and implementing appropriate prices of agricultural commodities, strengthening country's food security and distribution system and import/export policies of these commodities from time to time and in efficient management of natural resources.

India is one of the few countries which has a well established system of collection of agricultural statistics and detailed statistics of land utilization are continuously available since 1884. The agricultural crop production of principal agricultural crops in the country is usually estimated as a product of area under the crop and the average yield per unit area of the crop. The estimates of the crop acreage at a district level are obtained through complete enumeration whereas the average yield is obtained on the basis of crop cutting experiments conducted on a number of randomly selected fields in a sample of villages in the district.

The crop forecasts/advanced estimates of crops are presently developed by Ministry of Agriculture for taking policy decision relating to procurement, marketing, export, import etc. The advance estimates of kharif crops are first prepared in July/August tentatively when behaviour of South West monsoon is clear and reports of coverage of area under crops from the states are available. The advance estimates are reviewed during December/January when estimates of area under kharif crop become available under the Timely Reporting Scheme (TRS) and results of the crop cutting experiments portion from the NSSO (normally 10%) become available. The advance estimates of rabi season are also prepared at this stage. The advance estimates are again reviewed in the month of April based on information obtained from the states giving the final forecast for kharif.

With the advent of Remote Sensing Technology during 1970s, its great potential in the field of agriculture have opened new vistas of improving the agricultural system all over the world. Space borne remotely sensed spectral satellite data has been widely used in the field of agriculture for estimation of area under different major crops like wheat, paddy, groundnut and sugarcane. Studies have also been made to examine the relationship of crop growth parameters like leaf area index (LAI) representing crop vigour and the spectral data in the form of several vegetation indices developed from the spectral data of various bands. Remote sensing satellite data can also be used for improving the crop yield estimation through crop cutting experiments and also for developing models for crop yield using historical data, meteorological data, and remotely sensed satellite data.

During 1990-93 a study was conducted at the Institute to examine the usefulness of satellite spectral data for stratification of crop area based on vegetation indices for improving crop yield estimation based on yield data from crop cutting experiments under crop yield estimation surveys. The study pertained to wheat crop yield for district Sultanpur UP for 1985-86 and the satellite data was used from the USA satellite Land Sat-4. This study showed that the efficiency of crop yield estimation can be increased considerably by using the satellite data along with the survey data. The results of this study are given in Singh et. al.(1992). Another similar study was undertaken during 1996-98 for improved estimation of wheat crop yield in district Rohtak for 1995-1996 using the IRS 1B - LISS II satellite data for Feb. 17, 1996 and the crop yield data from crop yield estimation surveys for Rabi 1996. The results from this study presented in Singh et. al (1999). also showed that satellite data in the form of vegetation indices greatly improves the efficiency of crop yield estimator.

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