The Earth's surface is a complex landscape that is essential for a wide range of applications, from urban planning to environmental monitoring. Digital models of the Earth's surface are generated through mathematical calculations using elevation data collected from various sources and the Digital Terrain Model (DTM) which captures the bare earth's surface topography in 2.5D. The creation of DTM is an approximation of terrain in unsample locations, by using x-y coordinates and one z value. Traditionally, terrain interpolation uses deterministic or geo-statistical methods to calculate elevation. This research would use random forest regression as an alternative method and to compare the results against traditional interpolation. Comparing different locations against traditional interpolation yields similar results overall. Feature importance, within the the points that are closest to the sampled ICESat-2 data point are more significant than other features used in Random Forest model. The correlation between these datasets and the spatial relationship established would impact on the results of the elevation. The improvement overall of using traditional interpolation compared to random forest regression is limited depending on the location and using model trained with local datasets. For model trained on other geographical locations, which shows similar differences.

Blind and visually impaired people currently have inconveniences locating themselves in the indoor environment. No standardized system exists for them yet. After an inventory of the requirements of blind people, different representations do qualify for providing specific information blind people need. The main research question is: "How can blind people localise themselves (near) real-time in indoor environments with the combination of 3 representations of reality, namely (1) LiDAR point cloud matching, (2) ArcGIS Indoors and (3) Audio dynamic tactile map as the user interface?". Room detection and positioning of the user within the room are obtained by LiDAR scanning and point cloud matching. The processed point cloud height raster grids are acquired and imported into the Esri ArcGIS platform. The rooms are geo-referenced, and data is enriched by contextual awareness. As a user interface for blind people this report proposes two deliverables: a dynamic tactile map and an added or stand-alone audible supported user interface. Preliminary results of the qualitative validation show positive outcomes. This report is a stepping stone for the possibility of integrating multiple into one device.