Vol. 12, Issue 11 (2023)

Global environmental change, along with the development of Earth observation equipment, have caused significant developments in Earth system science. In order to monitor, measure, analyse, evaluate, and simulate Earth observation data, new instruments are required. The cloud-based Google Earth Engine (GEE) technology has powerful computing capabilities. Thousands of open geospatial and remote sensing datasets can be found on Earth Engine. There are now additional chances for more precise Normalized Difference Vegetation Index (NDVI) classification thanks to cloud computing platforms, time series feature extraction methods, and machine learning classifiers. Using Sentinel-2 photos, the goal of this study was to track the NDVI development in the Sangareddy district over time. Data for the four-year period from 2018 to 2021 is extracted. Often obtained from a space platform, the Normalised Difference Vegetation Index (NDVI) is a straightforward graphical indication that may be used to interpret remote sensing information and determine whether or not the target being observed includes live, green vegetation. Water is represented by NDVI values that are negative (values close to -1). Values close to zero (-0.1 to 0.1) typically represent rocky, sandy, or snowy deserts. Finally, low, positive values (between 0.2 and 0.4) reflect shrub and grassland, whereas high values (values close to 1) represent temperate and tropical rainforests. According to the results of our study, between 2018 and 2021, the vegetation area significantly grew in 2019 and 2020 compared to 2018.Additionally, it somewhat decreased in 2021, further decreasing in 2022.