- 标题
- 摘要
- 关键词
- 实验方案
- 产品
-
[IEEE IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium - Yokohama, Japan (2019.7.28-2019.8.2)] IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium - A Cloud-Enabled Geospatial Big Data Platform for Disaster Information Services
摘要: Geospatial technologies have been widely used to support decision making in natural disaster responses. There have been various efforts from multiple disasters to use geospatial information and models for disaster preparation, response, and resilience. These separated efforts can be shared and re-used across various sectors using a sustained platform. This paper presents how a platform layered on big data and cloud computing technologies can help achieve this goal. The big data platform enables the accumulation of disaster data, models, services, and applications in spatial information infrastructures (SDI), and improves the capabilities of SDI in supporting disaster risk reduction.
关键词: cloud computing,big data,interoperability,disaster,spatial data infrastructure
更新于2025-09-12 10:27:22
-
The Encyclopedia of Archaeological Sciences || Laser Scanning
摘要: Laser scanning provides archaeology with a high-speed process for the acquisition of three-dimensional (3D) spatial data. The technique provides surface-based 3D measurements of any small- or large-scale, complex, irregular, standard or nonstandard real-world scene. The resulting data are visualized through the production of point clouds, with the final results depicted as line drawings, computer-aided design (CAD) models, 3D surface models, and video animations, acting as an enhanced communication tool that has the ability of visualizing real-world objects in 3D space. It is the most effective way to quickly obtain data from the observed object and it enables measurements of areas that were unable to be collected previously, such as through hand-based drawings or total station surveys.
关键词: point clouds,Laser scanning,CAD models,archaeology,3D spatial data
更新于2025-09-11 14:15:04