This work is based on leveraging of satellite-based data with an effective integration of spatial analysis for monitoring the environmental impacts of a coal-fired thermal power plant on the surrounding vegetation, land, temperature, and soil. To gain insight into the emissions’ behavior from the power plant both spatial and temporal analyses are performed, using seventy cloud-free images from Landsat-8, for 7 years (2015–2021). The products of various vegetation indices (NDVI, MSAVI, SAVI) and land surface temperature have been utilized. Coal pollutants (SO2, CO2, NO2, Hg, and PM) affect both human and plant health, and the whole environment, by percolating toxins through air, water, and soil. Seasonal analysis involved dividing the data into six observation windows to segregate response under various meteorological conditions. The results have confirmed assumptions regarding the power plant’s behavior as a point source of pollution by showing temperature increase and declining vegetation health toward the source. Looking at the improvement of vegetation health and decrease in temperature, to a distance where this variation becomes independent of the radial distance from the power plants, it is found that the emissions impact an average distance of 2000 m. Seasonal variations in the thermal influence distance were measured as 1915, 1975, 2008, 2005, 2167 and 2031 m whereas bio influence distance is measured using the most suitable parameter of MSAVI, as 1905, 1959, 1934, 1913, 1944, and 9859 m for seasonal windows of 1st January to 10th March, 11th March to 30th April, 1st May to 6th July, 7th July to 15th September, 16th September to 15th November, and 16th November to 31st December, respectively. The research concludes the importance and effectiveness of the coupling of remote sensing images and spatial analysis as an economic alternative to analyze the harmful environmental effects of anthropogenic point pollution sources.