In our recent GIS Fundamentals lab session, we delved into the intricacies of raster manipulation, focusing on resampling, combination, and filtering techniques to enhance Digital Elevation Model (DEM) data. DEMs often come with various errors, differing resolutions, or cell sizes, making it imperative to employ raster operations for data refinement. Our first project involved combining DEMs of varying resolutions, specifically valley3 (3-meter cell size) and valley9 (9-meter resolution), leveraging the higher resolution data where available and utilizing the lower resolution elsewhere. We began by calculating hillshades for both datasets to visualize the differences, noting the increased detail in the 3-meter DEM. Resampling the valley9 data to match the 3-meter resolution ensured compatibility for subsequent analysis. Using raster calculator functions like IsNull and Con, we seamlessly combined the datasets, prioritizing higher resolution where present. Additionally, we explored filtering techniques to mitigate noise in DEMs, applying low-pass filters to reduce spikes and pits while preserving essential details. Through a series of raster calculations and reclassifications, we refined the DEM, balancing noise reduction with detail retention. Finally, we constructed a comprehensive map layout showcasing the processed data layers, incorporating legends, scale bars, and annotations for clarity. This project provided valuable hands-on experience in raster analysis, equipping us with essential skills for spatial data manipulation and visualization. Looking forward to applying these techniques to real-world geospatial challenges in future projects!