Analysis of NDVI and NDRE Indices Using Satellite Images for Crop Identification at Kelantan

Abstract

In Malaysia, the expansion of rubber trees, oil palm, and paddy plantations has become widely increased because of economic demands. Crop identification or monitoring is one of these applications since remote sensing provides precise, up-to-date, and cost-effective data on a range of crop kinds at various temporal and geographic resolutions. This study recommended integrating multispectral images, a tree canopy segmentation algorithm, and vegetable indicators to measure the attributes and spectral properties of crops and plants in a Kelantan region. Normalised difference vegetation index (NDVI) and normalised difference red edge (NDRE) were obtained from five spectral band images (red, green, blue, infrared (NIR), and red edge 2 (REDGE) that were processed by software into a full image map. NDVI is based on a plant’s characteristic reflection of a mix of visible red and near-infrared (NIR) light. NDVI function is to calculate the percentages of canopy cover, whereas the NDRE index is to assess leaf chlorophyll concentration or nitrogen content. The Red Edge sensors detected fluctuations in chlorophyll content within the leaf and throughout the plant canopy. Based on Landsat 8 and Sentinel 2A data, this study determined the NDVI and NDRE values for the crops in paddy fields, oil palm plantations and rubber tree plantations from different locations in Kelantan. The data was then analysed, the bar graphs and an emerging analysis of the differences between NDVI and NDRE maps for crop identification were used to present the results, respectively.