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Yenni Angraini

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Open access Aug 2026

Enhancing Prediction of Satellite-Based NO2 Concentration in ASEAN Using Random Forest Models with Spatial Coordinates and Temporal Lag Features

This study aims to quantify the marginal contributions of geographic coordinates and temporal lag features to the prediction accuracy of satellite-derived NO2 concentrations using Random Forest (RF) models and identifies the optimal feature combination for regional air quality modeling.

Nabil Naufal, Anik Djuraidah, Yenni Angraini · 0 citations

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