Code Repository for: "Characterization of Industrial Smoke Plumes from Remote Sensing Data", presented at Tackling Climate Change with Machine Learning workshop at NeurIPS 2020.
Research Paper on the prediction of pollutants concentration in Lille using Machine Learning Methods
Build an iOS Application to Predict Air Pollution Using a Random Forest Regressor
自强不吸——基于上海市天气与交通状况的空气质量分析报告
Python tool to sense, predict and push pollution data to Firebase Realtime Database
Python script that allows to modify dates of input files of modules of CALMET/CALPUFF model
Deep Neural Network for the prediction of NO2 level in the air, using two different satellite images of a specific zone.
Light pollution analyzer - forecasting, clustering, find key factor influencing light pollution, outliers state in datasheet all with python and Google earth engine.
Data Assimilation with ML/DL methods
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