Search results
Results from the WOW.Com Content Network
And in the same year, the GPlates team started the development of GPlates Portal and Web Service. In 2014, the GPlates Web Portal and Web Service were launched. In 2016, the first public version of pyGPlates was released. The pyGPlates beta revision 28 was released on 8 August 2020. This is the first version which supports Python3. The latest ...
It is mainly used for the allocation of forest ecosystems and data collection during field analysis. This application is able to work with relational databases , and provides seamless communication with external devices such as GPS , laser rangefinders [ 1 ] and for national forest inventories in Ireland , Cape Verde , Czech Republic , Belgium ...
The Laboratory's Odyssey project created a geographic information system that served as a milestone in the development of integrated mapping systems. [2] The Laboratory influenced numerous computer graphic, mapping and architectural systems such as Intergraph, Computervision, and Esri. [3]
Example of hardware for mapping (GPS and laser rangefinder) and data collection (rugged computer). The current trend for geographical information system (GIS) is that accurate mapping and data analysis are completed while in the field. Depicted hardware (field-map technology) is used mainly for forest inventories, monitoring and mapping.
Choropleth map showing estimated percent of the population below 150% poverty in the Contiguous United States by county, 2020 that uses the Jenks natural breaks classification. Jenks’ goal in developing this method was to create a map that was absolutely accurate, in terms of the representation of data's spatial attributes.
Occupancy Grid Mapping refers to a family of computer algorithms in probabilistic robotics for mobile robots which address the problem of generating maps from noisy and uncertain sensor measurement data, with the assumption that the robot pose is known. Occupancy grids were first proposed by H. Moravec and A. Elfes in 1985.
2005 DARPA Grand Challenge winner Stanley performed SLAM as part of its autonomous driving system. A map generated by a SLAM Robot. Simultaneous localization and mapping (SLAM) is the computational problem of constructing or updating a map of an unknown environment while simultaneously keeping track of an agent's location within it.
Object–relational mapping (ORM, O/RM, and O/R mapping tool) in computer science is a programming technique for converting data between a relational database and the memory (usually the heap) of an object-oriented programming language.