Normalized Difference Vegetation Index (NDVI) is a widely used concept in many aspects such as, Agriculture, Forestry, Disasters like Droughts, Urban Planning, Land use Classification, and etc. We thought that, if there is a platform which basically calculates, visualise NDVI directly what its users area of interest and ultimately gives the option of download in few simple steps. Therefore, our project is focused on the calculation of NDVI using remotely sensed images derived from Google Earth Engine Python API.
- Primary objective of this project is to calculate and visualize NDVI according to the interest of users
- Animate a time series of NDVI, to get a comprehensive understanding of the variation of the area which is interested.
- Deriving basic meteorological variables such as, wetness and dryness to identify drought events.
- Finally provide an option of downloading the image visualization with DEM capabilities.
- Folium
- Rasterio
- Shapely
- Geemap
- Geopanda
- Streamlit
- K. M. Malinga Prabhasara (GIS/2022/40)
- S. Rangeetha (GIS/2022/21)
- D. M. Sudarshi Dissanayaka (GIS/2022/73)
- Poornima Gimhani Thennakoon (GIS/2022/09)
- K. M. T. Inu Laksith (GIS/2022/62)
- K. Ishari Dilmini (GIS/2022/26)
- J. G. U. Sewwandi Sugathapala (GIS/2022/72)
- Thilan Senewirathna