ML‐Based Hybrid SAR and Optical Image LULC Mapping and Change Analysis With Variations in the Air Quality of the Imphal Valley, North‐East India

Abstract

AbstractImphal Valley, situated in Manipur, India, stands as an intermontane valley of great ecological significance, notably hosting Loktak Lake. This research delves into the Land Use Land Cover Change (LULCC) within the Imphal Valley from 2016 to 2021 and assesses their impact on air quality across distinct land cover types. We used Sentinel‐1 & 2 data, ALOS PALSAR Digital Elevation Model, and applied Random Forest (RF), a machine learning algorithm for effective land use and land cover (LULC) mapping. Additionally, Sentinel‐5P data was utilized to monitor air quality parameters (CO, HCHO, NO2, SO2, Aerosol Index) spanning 2019 to 2021. The overall accuracies for the LULC maps employing a k (k = 3) fold approach for accuracy assessment varied between 88% and 92%, with corresponding Kappa coefficient ranging from 0.85 to 0.90. Noteworthy trends emerged from our analysis, revealing an increase in settlements and horticulture farms and a decline in forested areas and phumdis (floating biomass). Our findings highlight a mean concentration of CO ranging between 0.045 mol/m2 and 0.055 mol/m2 in different land cover types during February and March (2019–2021). Furthermore, we observed maximum mean HCHO, NO2, SO2, and aerosol index concentrations in March. Pollution levels surged during forest fires and shifting agriculture seasons, while aerosol levels declined during the lockdown period. This integrated approach emphasized on the comprehensive analysis of the dynamic interplay between LULCC and air quality in the Imphal Valley. This intricate relationship between LULC changes and air quality dynamics in the Imphal Valley, contribute to our understanding of the environmental dynamics in this ecologically vital region.