Accurately estimating aboveground biomass (AGB) remains a challenge due to the limitations of various measurement methods. While destructive sampling provides precise results, it is costly, labor-intensive, and environmentally unsustainable. Advances in remote sensing technologies offer efficient alternatives for AGB estimation. Our study highlights that airborne laser scanning (ALS) is more effective in assessing forest structure than detailed biomass composition. Orthophoto analysis, while applicable for rapid assessments, tends to overestimate AGB and carbon stock, particularly in dense forests. Differences in tree height measurements between ALS, orthophoto extraction, and field methods emphasize the varying precision of remote sensing techniques. Integrating ALS and orthophotos may enhance accuracy by using orthophotos for tree crown identification and ALS for height measurements. This combined approach could reduce errors in biomass estimation, especially in dense forests where traditional methods are challenging. Our findings suggest that ALS is more suitable for large-scale biomass assessments, while orthophoto data may be more effective in open forests. Field calibration remains essential to improve accuracy, particularly for orthophotos, which are influenced by environmental factors such as light, shadow, and seasonal changes.