Fostering landscape transformation through iterative modeling and design using 3D point clouds

Landscapes are the material expression of the dynamic interactions of natural and socio-cultural factors in a given place. Planning and designing the landscape thus requires ways to respond to the environment. New sensing technologies in data acquisition and processing, as well as simulating and visualizing the response of our environment open new doors to perceive and shape landscapes. Iterative loops between science and design can help understand and interact with the landscape, not only making the landscape changes more salient and legitimate, but fostering a negotiated process of change. In an iterative process between science and design, quantitative information about processes and patterns of the environment can become part of the deliberative process over future development that take place within a value-driven process and design.
Particularly, LiDAR (Light Detection And Ranging) data based 3D point cloud models have shown to be highly suitable for such a process allowing to nest new designs in 3D environments. The qualities of altered or new designed landscapes can be assessed directly and the results fed back to the scientists. We illustrate such a process in a case study of the Ciliwung River in the megacity of Jakarta, Indonesia. Through an iterative process between nested hydrologic, hydrodynamic, and water quality models and point cloud based landscape designs, we demonstrate the ability to assess the impacts of a range of potential interventions to the landscape in terms of landscape aesthetics, flood events and water contamination. The 3D visualized scenarios of the new landscapes allowed critical feedback from stakeholders during the various feedback loops and fostered their participation in the landscape-shaping process. We conclude with discussing the potential of the approach to foster social learning enabling shaping and transforming our landscapes.