Temporal divergence in cropping pattern and its implications on geospatial drought assessment

TL;DR

This study introduces a Cropping Pattern Dissimilarity index to analyze how changes in cropping patterns over time affect the accuracy of geospatial drought assessments using NDVI data.

Contribution

It develops a new index to quantify cropping pattern changes and demonstrates its impact on the reliability of drought assessment methods based on NDVI time series.

Findings

Cropping patterns are more similar to recent years than distant past years.

Dissimilar cropping patterns can lead to misleading NDVI-based drought assessments.

Restricting NDVI comparisons to recent years improves drought interpretation accuracy.

Abstract

Time series data on cropping pattern at disaggregated level were analysed and its implications on geospatial drought assessment were demonstrated. An index of Cropping Pattern Dissimilarity (CP-DI) between a pair of years, developed in this study, proved that the cropping pattern of a year has a higher degree of similarity with that of recent past years only and tends to be dissimilar with longer time difference. The temporal divergence in cropping pattern has direct implications on geospatial approach of drought assessment, in which, time series NDVI data are compared for drought interpretation. It was found that, seasonal NDVI profiles of drought year and normal year did not show any anomaly when the cropping patterns were dissimilar and two normal years having dissimilar cropping pattern showed different NDVI profiles. Therefore, it is suggested that such temporal comparisons of NDVI are better restricted to recent past years to achieve more objective interpretation.