gis.Open Paper

Seite drucken

Using Massive Field Data for Large-size Design Action

For almost too long, we have tried to abide in the elusive academic satisfaction that we are really doing rather well concerning the in situ data capture and subsequent generation of highly detailed point cloud models of urban landscape reality. In our opinion, this approach affords an extensive physical overview of almost every kind of location in a landscape architectural or urban design related fieldwork operation. We continue to experiment with the use of portable tools to reconstruct three-dimensional digital landscapes while pro­gressive­ly improving upon the precision and density of geo-referenced data captured. Assertively, we postulate that the use of these tools and applied methods are conducive to the provision of visible, understandable, and designable spatial data within the academic con­text of urban landscape design studios. Now, we seek to address this demanding pos­tulate with much consideration. The paper marks the beginning of the presumably tedious and challenging journey into what we call digging massive field data for large-size design action. To date, we have achieved the ability to continually self-generate an infinite mass of digital sludge or virtual modelling clay for the landscape architectural designer. However, we have yet to demonstrate, in a convincing manner, the ability to put forth compelling designs which are yielded by our digital commodities. In other words, we have to make up the balance between the unassertive diggings of our remarkable field data, which has led to rather habitual design work. We began to settle this deficit by tackling a large-size academic studio project – a 26 kilometres long, abandoned railway line in Singapore that crosses the nation city. We politicize and popularize the design project by calling it The National Mall, as the expansive stretch of land is at risk of becoming real estate. The design process began with a two-week fieldwork campaign, resulting in the complete coverage of the railway line. This was achieved through mixed digital landscape capture methods: photography from stroller's perspective, drone-based aerial videography, and terrestrial laser scanning. The package of digital data – manifold, difficult to handle, and computationally expensive – was used to realise this goal. The paper describes our con­certed experimental efforts to exploit the data glut for sophisticated design outcomes.

Autor / Author: Rekittke, Joerg; Ninsalam, Yazid; Paar, Philip
Institution / Institution: National University of Singapore, Singapore; National University of Singapore, Singapore; Laubwerk GmbH, Potsdam, Germany
Seitenzahl / Pages: 10
Sprache / Language: Englisch
Veröffentlichung / Publication: Peer Reviewed Proceedings of Digital Landscape Architecture 2015 at Anhalt University of Applied Sciences
Tagung / Conference: Digital Landscape Architecture 2015 – Landscape Architecture and Planning
Veranstaltungsort, -datum / Venue, Date: Dessau, Germany 04-06-15 - 06-06-15
Schlüsselwörter (de):
Keywords (en): Teaching, design process
Paper review type: Full Paper Review
DOI:
1836 -