ALBERT

Description: Security applications such as management of natural disasters and man-made incidents crucially depend on the rapid availability of a situation picture of the affected area. UAV-based remote sensing systems may constitute an essential tool for capturing aerial imagery in such scenarios. While several commercial UAV solutions already provide acquisition of high quality photos or real-time video transmission via radio link, generating instant high-resolution aerial maps is still an open challenge. For this purpose, the article presents a real-time processing tool chain, enabling generation of interactive aerial maps during flight. Key element of this tool chain is the combination of the Terrain Aware Image Clipping (TAC) algorithm and 12-bit JPEG compression. As a result, the data size of a common scenery can be reduced to approximately 0.4% of the original size, while preserving full geometric and radiometric resolution. Particular attention was paid to minimize computational costs to reduce hardware requirements. The full workflow was demonstrated using the DLR Modular Airborne Camera System (MACS) operated on a conventional aircraft. In combination with a commercial radio link, the latency between image acquisition and visualization in the ground station was about 2 s. In addition, the integration of a miniaturized version of the camera system into a small fixed-wing UAV is presented. It is shown that the described workflow is efficient enough to instantly generate image maps even on small UAV hardware. Using a radio link, these maps can be broadcasted to on-site operation centers and are immediately available to the end-users.

Description: The monitoring of worldwide ship traffic is a field of high topicality. Activities like piracy, ocean dumping, and refugee transportation are in the news every day. The detection of ships in remotely sensed data from airplanes, drones, or spacecraft contributes to maritime situational awareness. However, the crucial factor is the up-to-dateness of the extracted information. With ground-based processing, the time between image acquisition and delivery of the extracted product data is in the range of several hours, mainly due to the time consumed by storing and transmission of the large image data. By processing and analyzing them on-board and transmitting the product data directly as ship position, heading, and velocity, the delay can be shortened to some minutes. Real-time connections via satellite telecommunication services allow small packets of information to be sent directly to the user without significant delay. The AMARO (Autonomous Real-Time Detection of Moving Maritime Objects) project at DLR is a feasibility study of an on-board ship detection system involving on-board processing and real-time communication. The operation of a prototype system was successfully demonstrated on an airborne platform in spring 2018. The on-ground user could be informed about detected vessels within minutes after sighting without a direct communication link. In this article, the scope, aim, and design of the AMARO system are described, and the results of the flight experiment are presented in detail.

Description: During the MOSAiC-ACA (MOSAiC-ACA (Multidisciplinary drifting Observatory for the Study of Arctic Climate - Airborne observations in the Central Arctic) campaign conducted in September 2020, a downward-looking commercial digital cameras equipped with a 180° - fisheye lens and a wide-angle camera system were installed on the aircraft Polar 5 and Polar 6. The images were used to derive the surface type fractions of snow/white ice, bare ice, melt ponds, and open water. The data set provides collocated broadband surface albedo, nadir brightness temperature, and surface type fractions along selected flight tracks of five flights.

Description: During the MOSAiC-ACA (MOSAiC-ACA (Multidisciplinary drifting Observatory for the Study of Arctic Climate - Airborne observations in the Central Arctic) campaign conducted in September 2020, a downward-looking commercial digital cameras equipped with a 180° - fisheye lens and a wide-angle camera system were installed on the aircraft Polar 5 and Polar 6. The images were used to derive the surface type fractions of snow/white ice, bare ice, melt ponds, and open water. The data set provides collocated broadband surface albedo, nadir brightness temperature, and surface type fractions along selected flight tracks of five flights.

Description: During the MOSAiC-ACA (MOSAiC-ACA (Multidisciplinary drifting Observatory for the Study of Arctic Climate - Airborne observations in the Central Arctic) campaign conducted in September 2020, a downward-looking commercial digital cameras equipped with a 180° - fisheye lens and a wide-angle camera system were installed on the aircraft Polar 5 and Polar 6. The images were used to derive the surface type fractions of snow/white ice, bare ice, melt ponds, and open water. The data set provides collocated broadband surface albedo, nadir brightness temperature, and surface type fractions along selected flight tracks of five flights.

Description: During the MOSAiC-ACA (MOSAiC-ACA (Multidisciplinary drifting Observatory for the Study of Arctic Climate - Airborne observations in the Central Arctic) campaign conducted in September 2020, a downward-looking commercial digital cameras equipped with a 180° - fisheye lens and a wide-angle camera system were installed on the aircraft Polar 5 and Polar 6. The images were used to derive the surface type fractions of snow/white ice, bare ice, melt ponds, and open water. The data set provides collocated broadband surface albedo, nadir brightness temperature, and surface type fractions along selected flight tracks of five flights.

Description: During the MOSAiC-ACA (MOSAiC-ACA (Multidisciplinary drifting Observatory for the Study of Arctic Climate - Airborne observations in the Central Arctic) campaign conducted in September 2020, a downward-looking commercial digital cameras equipped with a 180° - fisheye lens and a wide-angle camera system were installed on the aircraft Polar 5 and Polar 6. The images were used to derive the surface type fractions of snow/white ice, bare ice, melt ponds, and open water. The data set provides collocated broadband surface albedo, nadir brightness temperature, and surface type fractions along selected flight tracks of five flights.

Description: During the MOSAiC-ACA (MOSAiC-ACA (Multidisciplinary drifting Observatory for the Study of Arctic Climate - Airborne observations in the Central Arctic) campaign conducted in September 2020, a downward-looking commercial digital cameras equipped with a 180° - fisheye lens and a wide-angle camera system were installed on the aircraft Polar 5 and Polar 6. The images were used to derive the surface type fractions of snow/white ice, bare ice, melt ponds, and open water. The data set provides collocated broadband surface albedo, nadir brightness temperature, and surface type fractions along selected flight tracks of five flights.

Description: Aerial images in the human-visible spectrum red, green and blue (RGB). The 16 Megapixel images are stored in TIF format for better compatibility. The navigation (georeference) information for each image can be found in the “Navigation files” dataset. The raw imagery can be requested by contacting the author.

Description: Aerial images in the human-visible spectrum red, green and blue (RGB). The 16 Megapixel images are stored in TIF format for better compatibility. The navigation (georeference) information for each image can be found in the “Navigation files” dataset. The raw imagery can be requested by contacting the author.