Category Archives: Aerial/UAS
22 Young Geospatial Professionals to Watch in 2022 – 1 of 22
Throughout January, xyHt.com will feature the young geospatial professionals who are making a name for themselves in everything from surveying to geographic information systems. xyHt featured all of them in the January issue. Here we will spotlight one each day for the next 22 days. Name: Alfredo Eduardo Arzamendia Maldonado Company: Ministry of Public Works...
Riegl Officially Opens New Headquarters
On November 18th and under a persistent Florida drizzle, Dr. Johannes Riegl cut the ribbon that officially opened their new North American headquarters for business. Attended by over 150 people, Dr. Riegl and his son Johannes Riegl Jr., presided over a well-orchestrated and masterfully executed opening gala at the new Winter Garden, FL location. The...
Protecting Urban History
Maximizing the data collected from airborne lidar helps protect historic structures in older cities In Part I last month, we outlined the research performed in Dublin, Ireland, and Brooklyn, N.Y., using hyperspectral scanning to help old cities protect historically significant buildings during new construction projects. In Part II, NYU professor, Dr. Debra Laefer, explains how...
Autonomy Comes to UAVs
Trending tech has UAV software looking futuristic To a certain degree, autonomous operations are already baked into the current state of data collection (aka reality capture) software for UAVs. Pre-mission planning consists of using a map-based interface to highlight the area that needs to be mapped or inspected, the appropriate flight pattern and height (AGL)...
Protecting Urban History
Researchers demonstrate how lidar, combined with imagery and hyperspectral data, helps prevent costly damage to historic buildings in urban construction zones. With every new underground urban rail or roadway tunnel, deep foundation shaft for a new building, or even simple streetscape upgrade, historically significant architecture in older city centers can become vulnerable. Earth displacement from...
How Deep Learning For Remote Sensing Produces Quicker, Higher-Quality Results
As the volume, velocity, and variety of the data generated to address worldwide geospatial needs has steadily grown, advances in the systems and algorithms needed to produce spatial and temporal resolution data have not kept pace.