This study investigates how graphical methodologies enhance the use of three-dimensional (3D) data in ecological research, particularly in the analysis of animal movement across complex landscapes. In traditional ecological studies, 2D terrain representations are often used, which tend to underestimate habitat areas and movement distances. To address this limitation, previous methodologies are extended by integrating 3D terrain models into ecological analyses. Graphical techniques are applied to improve the visualization, measurement, and interpretation of 3D spatial data, making it more accessible for ecological applications. As an alternative to GNSS collar tracking, which is limited by battery life and low point density, high-resolution satellite imagery and visual criteria are used to define animal movement trajectories. GIS-based geomatic techniques and high-resolution 3D LiDAR datasets are employed to develop a framework for assessing how topographic factors such as slope, terrain roughness, and altitude influence route selection. By generating and comparing alternative routes based on these parameters, it is demonstrated that graphical methods enhance the accuracy of movement path analysis. The results confirm that slope and terrain roughness significantly influence route selection, and that the integration of high-resolution 3D LiDAR data enables precise quantification of these effects. This study provides a methodological foundation for future ecological research, highlighting the role of graphical approaches in simplifying and optimizing the use of 3D terrain data for movement ecology and conservation planning.