Although some types of land use can be observed from aerial and satellite images, this research is focused on the land cover since it can be directly derived from those images. Lu and Weng (Citation2007) comprehensively grouped classification methods into the following broad categories: supervised ...
GIS-based mapping and Remote sensing-based mapping have been widely employed in LCZ classification. GIS mapping method uses multiple data sources, such as remote sensing imagery, aerial photographs, and existing GIS databases of planning information, which allows detailed descriptions of urban forms ...
This review synthesizes recent advancements and identifies knowledge gaps in the tree growth phenology of both belowground and aboveground organs in extra-tropical forest ecosystems. Phenology, the study of periodic plant life cycle events, is crucial for understanding tree fitness, competition for ...
OpenDroneMap is a tool to postprocess small Unmanned Aerial Vehicle (sUAS), balloon, kite, and street view data to geographic data. With the current update, we are adding the ability to create orthophotos from drone, balloon, and kite imagery which has G
so you get the full story: why the excavators went there, how they made their discoveries, what they found, why it's important, and, of course, what it all means. But don't take our word for it – through the informative photographs and stunning aerial images you can see the archaeolo...
Land-use data were obtained from existing maps at 1:10,000 scale and through the interpretation of large scale, color aerial photographs. In the Tescio basin, for each slope-unit the percentage of unstable area was derived as the weighted summation of the landslide area existing in the unit...
The NASA contribution to the campaign was conducted in 2016 with the NASA LVIS (Land Vegetation and Ice Sensor) Lidar, the NASA L-band UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar). A central motivation for the AfriSAR deployment was the common AGBD estimation requirement for the...
Out of the Loop: the human free future of unmanned aerial vehicles. Hoover Institution, Stanford University, USA. Google Scholar Heinrich, J., Silver, D., 2016. Deep reinforcement learning from self-play in imperfect information games. arXiv: 1603.01121. Google Scholar Hirzinger, G., ...
structure. This wealth of data holds considerable promise for enabling measurements and estimations that surpass the capabilities of conventional methods, including traditional inventories reliant on manual tree-by-tree measurements, aerial lidar surveys, and other forms of remote sensing. It is imperative...
Simplified evaluation of cotton water stress using high resolution unmanned aerial vehicle thermal imagery. Remote Sens. 2019, 11, 267. [Google Scholar] [CrossRef] [Green Version] Zhang, Z.; Tan, C.; Xu, C.; Chen, S.; Han, W.; Li, Y. Retrieving soil moisture content in field maize...