Columnar architecture for modern riskmanagement systems

Mon, 01 Jan 0001 00:00:00 +0000

Authors: Romulo Goncalves, Sisi Zlatanova, Kostis Kyzirakos, Pirouz Nourian, Foteini Alvanaki, Willem Robert van Hage

Abstract:

3D digital city models form the basis for flow simulations (e.g. wind flow and water runoff), urban planning, underand over- ground formation analysis, and they are very important for automated anomaly detection on man made structures. They consist of large collections of semantically rich objects which have many properties such as material and color. Such user’s data structure perception is leading to complex storage schemas. The number of table relations to manage and the large data storage footprint drawbacks are then extended with the fact that not all the systems have a “real” 3D data type. In this work we would like to show our efforts to develop a new kind of Spatial Data Management System (SDBMS) where topological and geometric functionality for 3D raster manipulation will become part of the relational kernel and not an add-on. With it spatial analysis tailored to different use case scenarios is done on-demand and fast enough to support real-time interaction in modern risk management systems.

Investigating rural public spaces with cultural significance using morphological, cognitive and behavioural data

Mon, 01 Jan 0001 00:00:00 +0000

Authors: Nan Bai, Pirouz Nourian, Ana Pereira Roders, Raoul Bunschoten, Weixin Huang, Lu Wang

Abstract:

During the rural (re)vitalization process in China, national strategies required rural public spaces with cultural significance to be identified before planning decision-making. However, places identified as culturally significant by planners and visitors can differ from the ones mostly used and valued by locals. Even if there is a growing interest in integrating local perspectives and experiences in planning, studies seldom discuss and compare openly the adequacy of spatial configuration, cognition and behaviour to support it. This study took Anyi Historic Village Cluster as a case study to empirically investigate rural public spaces with three distinct, yet related approaches: (1) Morphological: spatial network centralities based on space syntax; (2) Cognitive: Lynchian village images with semi-structured interviews; (3) Behavioural: spatiotemporal occupation patterns using Wi-Fi positioning tracking. Significant places valued and used by locals and non-locals were detected with the multi-source data. Furthermore, multivariant regression models managed to characterize the relationship among different aspects of investigated rural public spaces, which also helped diagnose places of interest to prioritize in planning, demonstrating the advantage of integrating the sources of information in practice instead of studying them apart. Results can also assist rural planning on how to identify what to preserve, what to enhance, and how to develop such spaces, without overlooking the local needs or losing the rural identity.

Big data | Genesis Lab

Columnar architecture for modern riskmanagement systems

Investigating rural public spaces with cultural significance using morphological, cognitive and behavioural data