No abstract

This contribution reports the activities carried out by LamoLab, a non-governmental organization for multi-domain and multi-scale research applied to cultural terraced landscapes. Terracing and dry-stone walling have been internationally recognized as carriers of cultural values and traditional knowledge. Lamole in Chianti (Italy) has served as a primary case study of terraced vineyards, where interdisciplinary research has been converging for almost a decade. The evolution of multi-sensor data acquisition in different spectral ranges, data-driven modelling and multi-scalar approaches performed over the years are mentioned, with specific attention to the evaluation of microclimate variations induced by dry-stone walls and how they affect plant growth, ripening, and production. The results already obtained from data processing and analysis are described, although the work is still progressing. The ongoing research and future projects of LamoLab are reported for developing methodologies to understand the parameters that are critical for the effective restoration and functioning of the dry-stone walled vineyards and construct performance-oriented design strategies to enable knowledge-based design processes.

Although voxel models have been applied to address diverse problems in computer-aided design processes, their role in multi-domain data integration in digital architecture and planning has not been extensively studied. The primary objective of this study is to map the current state of the art and to identify open questions concerning data structuring, integration, and modeling and design of multi-scale objects and systems in architecture. Focus is placed on types of voxel models that are linked with computer-aided design models. This study utilizes a semi-systematic literature review methodology that combines scoping and narrative methodology to examine different types and uses of voxel models. This is done across a range of disciplines, including architecture, spatial planning, computer vision, geomatics, geosciences, manufacturing, and mechanical and civil engineering. Voxel-model applications can be found in studies addressing generative design, geomatics, material science and computational morphogenesis. A targeted convergence of these approaches can lead to integrative, holistic, data-driven design approaches. We present (1) a summary and systematization of the research results reported in the literature in a novel manner, (2) the identification of research gaps concerning voxel-based data structures for multi-domain and trans-scalar data integration in architectural design and urban planning, and (3) any further research questions.

Understanding socio-ecological systems and the discovery, recovery and adaptation of land knowledge are key challenges for sustainable land use. The analysis of sustainable agricultural systems and practices, for instance, requires interdisciplinary and transdisciplinary research and coordinated data acquisition, data integration and analysis. However, datasets, which are acquired using remote sensing, geospatial analysis and simulation techniques, are often limited by narrow disciplinary boundaries and therefore fall short in enabling a holistic approach across multiple domains and scales. In this work, we demonstrate a new workflow for interdisciplinary data acquisition and integration, focusing on terraced vineyards in Tuscany, Italy. We used multi-modal data acquisition and performed data integration via a voxelised point cloud that we term a composite voxel model. The latter facilitates a multi-domain and multi-scale data-integrated approach for advancing the discovery and recovery of land knowledge. This approach enables integration, correlation and analysis of data pertaining to different domains and scales in a single data structure.

Anthropic activities negatively impact natural and artificial ecosystems, necessitating interdisciplinary mitigation strategies such as multi-species building envelope designs. This paper introduces a computational multi-criteria decision-making (MCDM) methodology to support these envelope designs. We also propose a nested set strategy for key performance indicators (KPI) to strategically measure architectural and ecological performances. We integrate the strategy into a proposed hybrid MCDM methodology using computational design tools. The methodology was tested using a generic volume case study described by an architectural and ecological objective with varied priorities. Initial results highlight the computational interoperability of hybrid MCDM, informed by nested KPI set priorities, as support for multi-species building envelope designs.