Using of Sentinel 2 Images for Tropical Economic Crops Growth Modeling

Abstract. Nowadays, a rapid advancement of remote sensing technology has led to widespread recognition of its potential to improve the efficiency and reliability of crops inspection and monitoring. The objectives of this project are 1. To create a database of annual remote sensing data of economic crops from satellite imagery, 2. To study the cultivation patterns of economic crops based on annual changes in reflectance values. 3. To study the relationship between spectral signatures and growth characteristics obtained from field surveys. The remote sensing data from Sentinel 2 were calculated vegetation indices such as Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI) and Normalized Difference Infrared Index (NDII) to study the correlation with crops growth parameters of five economic crops of Thailand such as sugarcane, cassava, pineapple, oil palm, and para rubber. The results show that spectral reflectance of each crop change all year round and synchronized with growth data such as height, canopy width, stem size, and leaves chlorophyll content. Therefore, the remote sensing data has a potential for the 5 economic tropical crops growth and health monitoring. The satellite imagery from some month can be used to create crop growth assessment models including height, canopy width, and stem size and leaves chlorophylls content. In addition, the effectiveness of the model depends on the type of vegetation index used.