Vegetation Condition Index: A Potential Yield Estimator

Abstract

<p><strong>Abstract.</strong> Early yield assessment at local, regional and national scales is a major requirement for various users such as agriculture planners, policy makers, crop insurance companies and researchers. Current study explored a remote sensing-based approach of predicting the yield of Wheat, Kharif Rice and Rabi Rice at district level, using Vegetation Condition Index (VCI), under the FASAL programme. In order to make the estimates 14-years’ historical database (2003–2016) of NDVI was used to derive the VCI. The yield estimation was carried out for 335 districts (136 districts of Wheat, 23 districts of Rabi Rice and 159 districts of Kharif Rice) for the period of 2016–17. NDVI products (MOD-13A2) of MODIS instrument on board Terra satellite at 16-day interval from first fortnight of peak growing period of crop were used to calculate the VCI. Stepwise regression technique was used to develop empirical models between VCI and historical yield of crops. Estimated yields are good in agreement with the actual district level yield with the R<sup>2</sup> of, 0.78 for Wheat, 0.52 for Rabi Rice and 0.69 for Kharif Rice. For all the districts, the empirical models were found to be statistically significant. A large number of statistical parameters were computed to evaluate the performance of VCI-based models in predicting district-level crop yield. Though there was variation in model performance in different states and crops, overall, the study showed the usefulness of VCI, which can be used as an input for operational crop yield forecasting, at district level.</p>

Evaluation of Remote Sensing and Meteorological parameters for Yield Prediction of Sugarcane (Saccharum officinarum L.) Crop

“…VCI is an NDVI-derived based index that basically isolates the short-term ecological signals from the longer ones [35,36,42]. In this present study, 18 years (2000-2018) of NDVI were derived from the VCI of a particular region.…”

“…Vol.66: e23220781, 2023 www.scielo.br/babt precipitation evapotranspirtation index (SPEI) in the North China region and outcomes revealed that the water conditions in June-July had a good estimation for August or for three months interval data [17]. Dubey S and coauthors (2019) highlighted the role of the VCI index as a potential estimator for wheat and rice yield prediction over the various districts of the States [18].…”

“…In this present study, 18 years (2000-2018) of NDVI were derived from the VCI of a particular region. This can be computed using Equation 2 [35,36].…”