Multi-temporal Analysis of Vegetation Extent Using Google Earth Engine

Vegetation types (VTs) are a significant organizational unit and the recognition of these units is a crucial tool for maintaining the diversity of land uses. It modifies climate via altering planetary energies, the hydrological cycle, and atmospheric composition and provides a range of ecosystem services including provisioning, regulating, cultural and supporting services. The current scenario of the world’s vegetation is under threat as a direct result of anthropogenic activity as well as the unpredictable effects of climate change. Satellite technology is currently playing a significant role in the monitoring of natural resources such as the extent of vegetation, forest management, and many other aspects of the environment. According to the Indian State of Forest Report (ISFR) 2021, there is a net 2% increase in forest cover of Uttarakhand from 2019 to 2021. This study aimed to identify or analyze the multi-temporal dataset of forest cover by using the MODIS Land Cover Type (MCD12Q1) product and Hansen Global Forest Change (2000–2021) in the Indian state of Uttarakhand. Long-term changes in forest dynamics are monitored using remotely sensed data collected between 2001 and 2021. MCD12Q1 is used to monitor the dynamics of different forest types, while Hansen Global Forest Change is used to monitor the canopy cover in the study area. In addition, the presented result underlines that available open-access cloud computing platforms such as the Google Earth Engine (GEE) facilitate identifying multi-temporal imagery for vegetation types and forest cover.