Processing and evaluating remote sensing data from available satellite images are software dependent and space consuming tasks. This work represents a recent widely used method for processing of satellite data at an online platform named Google Earth Engine (GEE). In this platform the task can be done individually as well as a team can work in collaboration mode. GGE platform allows the various remote sensing data processing and plotting without downloading remote sensing data to the user’s system (which are mainly space constraints). Motivation of this work is to perform remote sensing time series data analysis to study the vegetation index over Sikkim state in north east part of India in the GGE platform as a case study. In this work the normalized difference vegetation index (NDVI) is estimated at regional scale using the Landsat-8 data. The index generally detect the plant canopies green pigmentation in the remote sensing data of multi-spectral nature. This is also helped in quantifying the photosynthetic strength of green vegetation. The time span is selected from 2015 to 2020 according to the availability of Landsat8 data having 30m of spatial resolution to process the NDVI. For NDVI calculation, May month period of each year has been selected because of minimum cloud cover in the data for Sikkim region and the spatial distribution of the index is generated which clearly indicates the year to year variability because of the weather variations like rainfall, humidity, temperature etc.