NDVI on Landsat 9 imagery with data using IPFS#

Geospatial professionals frequently handle vast data sets, like satellite imagery, for tasks ranging from object detection to land cover classification. The Normalized Difference Vegetation Index (NDVI) is a widely-used metric for assessing vegetation health in a given area. In this blog post, we’ll walk you through calculating NDVI using Landsat 9 imagery and the IPFS network with the help of the Python library, ipfs-stac, in a Jupyter notebook. We’ll also discuss the benefits of leveraging IPFS in geospatial workflows, such as content-addressing and decentralization.

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