Integration of Remote Sensing Data into a Composite Voxel Model for Environmental Performance Analysis of Terraced Vineyards in Tuscany, Italy

• Published in: Remote sensing (Basel, Switzerland) Vol. 13; no. 17; p. 3483
• Main Authors: Tyc, Jakub, Sunguroğlu Hensel, Defne, Parisi, Erica Isabella, Tucci, Grazia, Hensel, Michael Ulrich
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-09-2021
• Subjects: Agriculture; Aircraft; Altitude; composite voxel model; Cultural heritage; Data acquisition; Data analysis; Data integration; Data structures; Datasets; Domains; Environmental performance; Farming systems; Geographic information systems; Geomorphology; geospatial analysis; Interdisciplinary aspects; Knowledge; Land use; Microclimate; Modal data; Photogrammetry; point cloud; Remote sensing; Sensory integration; Simulation; Social-ecological systems; Soil erosion; Soil sciences; Spatial analysis; Sustainable agriculture; Sustainable development; Sustainable use; Terracing; thermography; Unmanned aerial vehicles; Vineyards; Wineries & vineyards; Workflow; Italy
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs13173483

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.