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The design and the development of a hyperspectral and multispectral airborne mapping system
Authors:Pece V Gorsevski  Paul E Gessler
Institution:1. School of Earth, Environment & Society, Bowling Green State University, Bowling Green, OH 43403, USA;2. Department of Forest Resources, College of Natural Resources, University of Idaho, Moscow, ID 83843, USA;1. CEA, LIST, LNHB, 91191 Gif-sur-Yvette, France;2. IPHC, DRS, Ramses, 23 rue du Loess F-67037 Strasbourg, France;1. German Aerospace Center, Oberpfaffenhofen, 82234 Weßling, Germany;2. Chair of Remote Sensing Technology, Technische Universität München, Arcisstr. 21, 80333 München, Germany;3. Photogrammetry and Remote Sensing, Technische Universität München, Arcisstr. 21, 80333 München, Germany;1. Fujian Key Laboratory of Sensing and Computing for Smart City, Fujian, China;2. School of Information Science and Engineering, Xiamen University, Xiamen, China
Abstract:Flexible and cost-effective tools for rapid image acquisition and natural resource mapping are needed by land managers. This paper describes the hardware and software architecture of a low-cost system that can be deployed on a light aircraft for rapid data acquisition. The Hyperspectral and Multispectral Cameras for Airborne Mapping (HAMCAM) was designed and developed in the Geospatial Laboratory for Environmental Dynamics at the University of Idaho as a student-learning tool, and to enhance the existing curriculum currently offered. The system integrates a hyperspectral sensor with four multispectral cameras, an Inertial Navigation System (INS), a Wide Area Augmentation System (WAAS)-capable Global Positioning System (GPS), a data acquisition computer, and custom software for running the sensors in a variety of different modes. The outputs include very high resolution imagery obtained in four adjustable visible and near-infrared bands from the multispectral imager. The hyperspectral sensor acquires 240 spectral bands along 2.7 nm intervals within the 445–900 nm range. The INS provides aircraft pitch, roll and yaw information for rapid geo-registration of the imagery. This paper will discuss the challenges associated with the development of the system and the integration of components and software for implementation of this system for natural resource management applications. In addition, sample imagery acquired by the sensor will be presented.
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