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

Forecasting of crop production is one of the most important aspects of agricultural statistics system. Yield forecasts in the country at present are based on the traditional approch of crop condition and the area under the crop. The main factors affecting crop yield are agricultural inputs and weath...

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Bibliographic Details
Published in:Journal of the Indian Society of Agricultural Statistics 2003-08, Vol.56 (2)
Main Author: Singh, R. (Indian Agricultural Statistic Research Institute, New Delhi (India))
Format: Article
Language:English
Subjects:
CHEF D'EXPLOITATION AGRICOLE
CROP YIELD
FARM MANAGERS
GEOGRAPHICAL INFORMATION SYSTEM
GESTORES DE EMPRESAS AGRARIAS
RENDEMENT DES CULTURES
RENDIMIENTO DE CULTIVOS
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Summary:Forecasting of crop production is one of the most important aspects of agricultural statistics system. Yield forecasts in the country at present are based on the traditional approch of crop condition and the area under the crop. The main factors affecting crop yield are agricultural inputs and weather. Use of these factors forms one class of models of forecasting crop yields. Another approach uses crop vigor through remotely sensed satellite data. In this regard several studies have been undertaken to establish relationship between spectral parameters through vegetation indices and the crop yield. Shah [12] used satellite data and geographical information system (GIS) technology for developing crop yield models. Verma et al. [22] presented a study on evaluation of crop cut method and farmers reports for estimating crop production. The results of the study showed that farmers eye estimates are remarkably close to actual production figures. In the present study an attempt is made farmers eye estimate of crop yield more objectively as an auxiliary variable along with the spectral vegetation indices obtained from satellite data to develop an improved crop yield model. The crop yield data is obtained from the general crop estimation surveys (GCES) based on crop cutting experiments. The farmer's eye estimates of the crop yield of the fields which have been selected for GCES and the satellite data of the corresponding area are obtined at the time of maximum vegetative growth stage of crop (about 4-6 weeks before harvest) when they have the highest correlation with the crop yield. The findings of this study suggest that a reliable and timely crop yield forecast may be obtained by using the NDVI from remote sensing spectral data along with the farmer's eye estimate of yield as the two eplanatory variables.
ISSN:0019-6363