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