Environmental Analysis using Remote Sensing Data

To predict various environmental determinants using the remote sensing data becomes mandate research in the current trend. Two decades of remote sensing data (2000-2022) LANDSAT 7 images are downloaded and estimated various environmental parameters using QGIS with the help of standard formula. The extracted parameters are collected and analyzed using various machine learning algorithm. The missing data dealt by using Gradient Boost algorithm and created a cleaned datasheet. These datasets are trained and tested using nine various machine learning algorithms and predicted the future environmental determinants like NDVI, NDWI, NDMI, NDBI, and LST until 2030. SARIMAX algorithm produced 95.73% of accuracy in predicting future environmental determinants. These analysis help to have a better understand of environmental trends and changes, which could help with environmental planning and making real-time decision-making that can be shared globally via the Internet.