Engineering Commons^™

Gis-Based Volunteer Cotton Habitat Prediction And Plant-Level Detection With Uav Remote Sensing, Tianyi Wang, Xiaohan Mei, J. Alex Thomasson, Chenghai Yang, Xiongzhe Han, Pappu Kumar Yadav, Yeyin Shi

Department of Biological Systems Engineering: Papers and Publications

Volunteer cotton plants germinate and grow at unwanted locations like transport routes and can serve as hosts for a harmful cotton pests called cotton boll weevils. The main objective of this study was to develop a geographic information system (GIS) framework to efficiently locate volunteer cotton plants in the cotton production regions in southern Texas, thus reducing time and economic cost for their removal. A GIS network analysis tool was applied to estimate the most likely routes for cotton transportation, and a GIS model was created to identify and visualize potential areas of volunteer cotton growth. The GIS model indicated …

Mapping The Light Fantastic At Newgrange, Frank Prendergast, Clare Tuffy, John Lalor, Claire Breen, Sinéad Gargan

Articles

THE WORLD HERITAGE PROPERTY of Brú na Bóinne attracts thousands of visitors from Ireland and around the globe, many drawn by the remarkable winter solstice phenomenon, when the rising sun’s rays illuminate the burial chamber. During 2020 it became clear that public health measures to combat the global pandemic were going to preclude visitor access to the chamber of the Great Mound of Newgrange, including during the annual winter solstice celebrations. When the government agencies OPW and NMS discussed how to manage Newgrange and the solstice during the restrictions, Clare Tuffy, Manager of Visitor Services at Brú na Bóinne, suggested …

A Two-Level Information Modelling Translation Methodology And Framework To Achieve Semantic Interoperability In Constrained Geoobservational Sensor Systems, Paul Stacey

Doctoral

As geographical observational data capture, storage and sharing technologies such as in situ remote monitoring systems and spatial data infrastructures evolve, the vision of a Digital Earth, first articulated by Al Gore in 1998 is getting ever closer. However, there are still many challenges and open research questions. For example, data quality, provenance and heterogeneity remain an issue due to the complexity of geo-spatial data and information representation.

Observational data are often inadequately semantically enriched by geo-observational information systems or spatial data infrastructures and so they often do not fully capture the true meaning of the associated datasets. Furthermore, data …