Quantifying forest degradation rates and their impact on environmental condition in Dehradun, India

Forest ecosystems play a major role in controlling the global temperature. Despite the significance of forest ecosystem services, global forest change has not been well quantified. This study focuses on assessing forest degradation, land cover dynamics, and carbon emissions in Dehradun, India, from 2000 to 2023. We utilize multi-temporal satellite datasets from Landsat and MODIS with 30 m resolution, combined with Gradient Tree Boosting for land cover classification with an accuracy of 94 %. Land cover is classified into four classes: urban, water, vegetation, and forest, using a dataset of 2000 training samples and key spectral bands. The classification accuracy is verified using a confusion matrix and a kappa coefficient. To assess plant health, plant indicators including Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index 2 (EVI2), and Normalized Burn Ratio (NBR) are calculated to assess plant vitality throughout the study period. The analysis shows that due to the continuous decline in Forest areas, Dehradun loses approximately 650 hectares (ha) of tree cover between 2001 and 2023, forest fires account for 7.7 % of the total forest area loss, which emits 430 kilotons (kt) equivalent of carbon dioxide (CO₂). This results in numerous greenhouse gas emissions and significant ecological impacts. Average annual carbon emissions from tree cover loss are determined to be 18.7 kt CO₂, revealing the significant impact of deforestation on atmospheric carbon concentrations. Analysis reveals a clear pattern of declining forest cover, increasing deforestation, and associated CO₂ emissions. Decreasing trends in NDVI, EVI2 indicate a decrease in the health and density of vegetation in the area. The proposed analysis provides key insights into the state of forests in Dehradun by integrating machine learning classification and vegetation index analysis that highlights the importance of effective forest management.