Identifying Black Rice Cultivated Area Using Sentinel2

Abstract

Kalabati(Oriza Sativia L.) is a black or forbidden rice variety with rich medicinal and nutrient values. Traditionally, several studies acknowledged the unlimited potential of black rice and intensive research conducted in the laboratory environment to determine its benefits. The presence of anthocyanin(anth) content in Kalbati rice plants turns leaves into black or purple. Several studies identified rice canopy using remote sensing technologies, but none attempted to distinguish black rice areas. Understanding the existence and yield of black rice helps governments or policyholders to take appropriate decisions to promote its benefits in society for broader consumption. This study aims to evaluate the feasibility of using satellite imagery to identify the anth content of Kalabati plant leaves using leaf optical properties. Sentinel2 based indices help to identify Anth content in the leaves using its multi-spectral(MSI) instrument. A combination of Modified Anthocyanin Index(mARI), Chlorophyll Vegetation Index(CVI) and Green Leaf Index(GLI) is used to determine the complex rice canopy of the black rice that exists at a negligible percentage among other crops. The correlation of mARI with CVI has an RMSE value of 0.11314, and the same RMSE value of mARI with GLI is at 0.66441. Finally, the study concluded anth content in Kalabati rice could be interpreted using multi-spectral data from Sentinel-2.c