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The state-of-the-art in airborne coastal mapping and charting technology is the Compact Hydrographic Airborne Rapid Total Survey (CHARTS) system. CHARTS is the U.S. Naval Oceanographic Office program name for an Optech, Inc. SHOALS 3000T20-E. CHARTS comprises a 3 kHz bathymetric lidar, a 20 kHz topographic lidar, a DuncanTech DT4000 high-resolution digital camera, and a Compact Airborne Spectrographic Imager(CASI)-1500. The integrated sensor suite has the capability to collect lidar bathymetry, lidar topography, RGB imagery, and hyperspectral imagery. Beyond these products, the diffuse attenuation coefficient and seafloor reflectance at multiple wavelengths may be estimated by combining information from the bathymetric lidar waveform and the hyperspectral imagery.The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) specified development of the CHARTS system and currently manages its operations for Department of Defense customers. CHARTS data collection rate of 21 square nautical miles per survey hour enables rapid completion of large nautical charting work for the U.S. Naval Oceanographic Office. The U.S. Army Corps of Engineers National Coastal Mapping Program uses CHARTS to collect engineering scale data for the entire U.S. coastline. JALBTCX continues to lead development in the field of airborne lidar and integrated technologies for coastal mapping and charting. Future research efforts include mining the individual data sets collected by CHARTS for information beyond elevation, combining data sets to further identify physical and environmental characteristics of the coastal zone, and integrating additional complementary sensors with CHARTS.

Real-time semantic image segmentation on platforms subject to size, weight and power (SWaP) constraints is a key area of interest for air surveillance and inspection. In this work, we propose MAVNet: a small, light-weight, deep neural network for real-time semantic segmentation on micro Aerial Vehicles (MAVs). MAVNet, inspired by ERFNet [1], features 400 times fewer parameters and achieves comparable performance with some reference models in empirical experiments. Our model achieves a trade-off between speed and accuracy, achieving up to 48 FPS on an NVIDIA 1080Ti and 9 FPS on the NVIDIA Jetson Xavier when processing high resolution imagery. Additionally, we provide two novel datasets that represent challenges in semantic segmentation for real-time MAV tracking and infrastructure inspection tasks and verify MAVNet on these datasets. Our algorithm and datasets are made publicly available.

CZMIL is a new airborne mapping and imaging system designed to simultaneously produce high resolution 3D images of the beach and shallow water seafloor, and to achieve benthic classification and water column characterization. It is designed to have high performance in shallow, turbid waters. The Data Acquisition System (DAS) is composed of a new bathymetric lidar integrated with a commercial imaging spectrometer and digital metric camera. The Data Processing System (DPS) employs new algorithms and software designed to automatically produce environmental image products by combining data from the three sensors within a data fusion paradigm. CZMIL is specifically designed to meet the requirements of the USACE Coastal Mapping Program, and is scheduled to enter field trials in the spring of 2011.