The Indonesian government mentioned the urge to accelerate the process of providing detailed spatial plan maps. Moreover, to have one standard of reference, detailed spatial plan maps need to use large-scale (1:5.000) base maps as reference. Furthermore, the Indonesian government established the One Map Policy agenda as a legal basis for accelerating large-scale data. The Geospatial Information Act (2011) mentioned that the National Mapping of Agency (NMA) of Indonesia is responsible for providing nationwide large-scale (1:5.000) base maps. However, until now, only 2.7% of large-scale (1:5.000) base maps are available from all over Indonesia . One issue is the gap between the budget needed and received annually from the national government. Dependent on the national government, the NMA faces budget uncertainty between the budget requested and received during the annual process. Moreover, the budget was focused on supplying a national program of large-scale (1:5.000) base maps. Therefore, the NMA tend to innovate its funding model to accelerate the production of large-scale (1:5.000) base maps. Innovative funding models are assessed by using Analytical Hierarcy Process, one of the Multi-Criteria Analysis. Moreover, to achieve categorize the stakeholder, a stakeholder analysis is conducted. This project shows that sharing financial resources between local and national authority is a viable option. However, both national and local government needs to set several parameters and create a proper relationship among stakeholders.

Indoor localisation methods are an essential part for the management of COVID-19 restrictions, social distancing, and the flow of people in the indoor environment. Moving towards an open work space in this scenario requires effective real-time localisation services and tools, along with a comprehensive understanding of the 3D indoor space. This project’s main objective is to analyse how ArcGIS Indoors can be used with location awareness methods to elaborate and develop space management tools for COVID­-19 restrictions in order to reopen the workspace for TU Delft Campus. This was accomplished by using six Arduino micro controllers, which were programmed in C++ to scan all available Wi-­Fi fingerprints in the east wing of the Faculty of Architecture and the Built Environment of TU Delft and send over the data to an ArcGIS Indoor Information Model (AIIM). The data stored on the AIIM is then accessed using the app on the user’s Android device using REST Application Programming Interface (API) where a kNN based matching algorithm then identifies the location of the user. The results show that the localisation is not consistent for rooms that are directly above each other or share common access points. However, when functioning to locate different tables inside a room, the system proved to uniquely distinguish between the specific tables. As a result, we can conclude that based on the size of the rooms, more Arduino devices should be installed to achieve an ideal accuracy. Finally, recommendations are made for the continuation of this research.