Publications

More, RS; Manjunath, K; Jain, NK; Panigrahy, S; Parihar, JS (2016). Derivation of rice crop calendar and evaluation of crop phenometrics and latitudinal relationship for major south and south-east Asian countries: A remote sensing approach. COMPUTERS AND ELECTRONICS IN AGRICULTURE, 127, 336-350.

Abstract
The crop calendar varies considerably with climatic and socio-economic factors as well as farming practices of the region. In present paper we demonstrate the application of remote sensing data to derive a geospatial database for rice crop calendar for major south and south-east Asian countries. The cultural type-wise variability of rice crop calendar and crop phenometrices-latitudinal relationship was also studied. A crop growth profile equation was used to simplify the parameterization necessary for identification of rice crop phenological matrices. A curve fitting approach was adapted for fitting the spectral Normalized Difference Vegetation Index (NDVI) growth profiles for rice derived from multi-date, multi-temporal SPOT VGT NDVI data and phenometrics viz. sowing/transplantation day, crop maturity/harvest day and total duration of rice crop were derived. The global distribution of the rice along the different latitudes is due to the adaptability of the rice to the regional conditions, which should reflect in the crop calendar. As latitude is one of the controlling factors of the climate, here we investigate the existence of relation between rice crop calendar and latitude. The strength of correlation between the rice crop phenometrics and the latitude was determined by two-tailed Pearson correlation coefficient analysis and Spearman's rank correlation across a latitudinal gradient which indicates an inverse relationship, with the (P < 0.01) level of significance for Pearson linear correlation and (rho <= 0) for Spearman's rank correlation. The high temporal NDVI data enabled characterizing the rice crop phenology effectively. The crop calendar derived in this study solely relies on the remote sensing data and can be used for of methane emission assessment from different rice cultural types. (C) 2016 Elsevier B.V. All rights reserved.

DOI:
10.1016/j.compag.2016.06.026

ISSN:
0168-1699