Prediction of rice yield using vegetation indices from rice growing season July - October in Jhapa district—monthly four mean vegetation indices from rice growing season trained to construct random forest model; NDVI and EVI individually—validated by remaining years unused during training—EVI based model found to be more robust in the yield prediction

Quantitative observation of Forest, Urban, Crop land and Barren land cover of Nepal using MODIS Land Cover: Correlation test with FAOSTAT and National Land Cover Monitoring System of Nepal

Learning to access the satellite data is important from different data providers is the initial step in our geospatial analysis. STAC, Spatio-Temporal Asset Catalog, is the way to organize the geospatial data in the cloud. This makes querying and accessing them easier. STAC: Spatio-Temporal Asset Catalog (STAC): common language, metadata for describing/organising geospatial data  common formats; uses JSON files; consistency and interpretation for data with spatial & temporal component flexible extensions, interoperability to search specific data types; accommodate provider needs / implementable standards.