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Global Agriculture Lands: Raster dataset from NASA's Socioeconomic Data and Applications Center representing global extent and intensity of use of agricultural lands in 2000. Satellite data from MODIS and SPOT (satellite) image vegetation sensor were combined with agricultural inventory data. Global Irrigated Area Map (GIAM)
The National Agriculture Imagery Program (NAIP) acquires aerial imagery during the agricultural growing seasons in the continental United States. It is administered by the USDA 's Farm Service Agency (FSA) through the Aerial Photography Field Office (APFO) in Salt Lake City .
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 (/ 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.
How Cars Use Lidar to Map for Hands-Free Driving BMW For a hands-free driving system to keep a vehicle safely in its lane, the software first needs to know where that lane is and some information ...
Lidar uses lasers to produce three-dimensional images of a vehicle's surroundings which helps vehicles navigate around obstacles. The sensors are a key component of many self-driving systems being ...
Precision agriculture (PA) is a management strategy that gathers, processes and analyzes temporal, spatial and individual plant and animal data and combines it with other information to support management decisions according to estimated variability for improved resource use efficiency, productivity, quality, profitability and sustainability of ...