The focus of this research has been on detecting changes in lake areas, vegetation, land surface temperatures, and the area covered by snow, using data from remote sensing in Central Siberia. Remote sensing products were used to analyze changes in water bodies, land surface temperature (LST), and leaf area index (LAI), as well as the occurrence and extent of forest fires, and the area and duration of snow cover. The remote sensing analyses (for LST, snow cover, LAI, and fire) were based on MODIS–derived NASA products (250–1000 m) for 2000 to 2011. Changes in water bodies were calculated from two mosaics of (USGS) Landsat (30 m) satellite images from 2002 and 2009. This area experienced both large scale wetting and large scale drying during the study period probably related to the nature of the substrate conditions. The land surface temperatures showed a consistent warming trend, with an average increase of about 0.12 °C/year, but ranged up to 0.49 °C/year during September–October. This is about ten times higher than the global warming rate of 0.0116 °C/year (2000 to 2014) estimated by Karl et al. (2015). The spring warming trend is very likely to be due to changes in the area covered by snow: 80% of the area showed reduction in snow coverage in spring. The warming trend observed in fall does not, however, appear to be directly related to any changes in the area of snow cover, or to the atmospheric conditions, or to the proportion of the land surface that is covered by water (i.e., to wetting and drying).