Search results
Results from the WOW.Com Content Network
UC Merced Land Use Dataset These images were manually extracted from large images from the USGS National Map Urban Area Imagery collection for various urban areas around the US. This is a 21 class land use image dataset meant for research purposes. There are 100 images for each class. 2,100 Image chips of 256x256, 30 cm (1 foot) GSD
Lidar (/ ˈ l aɪ d ɑːr /, also LIDAR, LiDAR or LADAR, an acronym of "light detection and ranging" [1] or "laser imaging, detection, and ranging" [2]) is a method for determining ranges by targeting an object or a surface with a laser and measuring the time for the reflected light to return to the receiver.
A national lidar dataset refers to a high-resolution lidar dataset comprising most—and ideally all—of a nation's terrain. Datasets of this type typically meet specified quality standards and are publicly available for free (or at nominal cost) in one or more uniform formats from government or academic sources.
Currently, the best source for nationwide LiDAR availability from public sources is the United States Interagency Elevation Inventory (USIEI). [1] The USIEI is a collaborative effort of NOAA and the U.S. Geological Survey, with contributions from the Federal Emergency Management Agency, the Natural Resources Conservation Service, the US Army Corps of Engineers, and the National Park Service.
LiDAR receives information by discrete and full-waveform return. Full-waveform (multi-return) is often used for forest analysis by Airborne LiDAR, while discrete return (single return) is used by a ground-based laser scanning method. [19] A laser is reflected whenever it reaches any surfaces.
Atmospheric lidar is a class of instruments that uses laser light to study atmospheric properties from the ground up to the top of the atmosphere. Such instruments have been used to study, among other, atmospheric gases, aerosols, clouds, and temperature.
Image-based meshing: When using 3D image data for computational analysis (e.g. CFD and FEA), simply segmenting the data and meshing from CAD can become time-consuming, and virtually intractable for the complex topologies typical of image data. The solution is called image-based meshing, an automated process of generating an accurate and ...
Medical image computing typically operates on uniformly sampled data with regular x-y-z spatial spacing (images in 2D and volumes in 3D, generically referred to as images). At each sample point, data is commonly represented in integral form such as signed and unsigned short (16-bit), although forms from unsigned char (8-bit) to 32-bit float are ...