This repository contains a pipeline blending Python and R features, first to: download, preprocess, and compute Sentinel-1 SAR vegetation indices (all in Python); following for image sampling in R.
Unsupervised and supervised learning for satellite image classification
Sentinel Values - unique global singleton objects, akin to None, NotImplemented and Ellipsis.
Papers for Copernicus Land Monitoring Services evolution - based on H2020 ECoLaSS project
For-fun Chrome extension that swaps images on a X/Twitter feed with images promoting the Sentinels Valorant bundle
Testing Redis master / slave failover with and without Sentinels
Personal website with geospatial content
The purpose of this repository is to provide implementations of three different types of data structures: sentinel-based, dynamic using malloc, and linked using pointers. These data structures can be used in various algorithms and programs for efficient storage, retrieval, and manipulation of data.
Using Docker Compose to setup a redis cluster with sentinel.
The objective of the project is to develop a book loan system. The repository consists of two programs written in C language and its compilation in Unix-type Operating Systems is recommended because processes are handled at the kernel level.
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