ASQ-MPHAAS: Multi-Payload Observation System From High Altitude Airship

One of the critical advantages of a high-altitude airship (HAA) is its ability to carry multiple-task payloads for remote sensing monitoring on the plateau. We developed a multi-payload observation system based on the HAA (ASQ-MPHAAS) for remote sensing monitoring of the Qinghai plateau. In this paper, we demonstrate the design, development, implementation of the ASQ-MPHAAS. The ASQ-MPHAAS includes two parts; one part is our HAA (ASQ-HAA380), and the other part is our multi-payload observation system (ASQ-MPOS-1). The ASQ-MPOS-1 consists of two hyperspectral push-broom imaging sensors, a multispectral imaging sensor, a high-resolution RGB camera, a video sensor, a Position and Orientation System (POS), and other components. The ASQ-MPOS-1 is installed under the ASQ-HAA380. We also introduce some key methods of data processing we propose to solve unique problems brought by HAA. Four real-world field experiments are presented in this paper to demonstrate that the ASQ-MPHAAS can capture different kinds of remote sensing data at a high spatial resolution of a few or dozen centimeters.

[1]  Amr H. Abd-Elrahman,et al.  Design and Development of a Multi-Purpose Low-Cost Hyperspectral Imaging System , 2011, Remote. Sens..

[2]  Arko Lucieer,et al.  HyperUAS—Imaging Spectroscopy from a Multirotor Unmanned Aircraft System , 2014, J. Field Robotics.

[3]  Tsehaie Woldai,et al.  Multi- and hyperspectral geologic remote sensing: A review , 2012, Int. J. Appl. Earth Obs. Geoinformation.

[4]  Arko Lucieer,et al.  Sensor Correction of a 6-Band Multispectral Imaging Sensor for UAV Remote Sensing , 2012, Remote. Sens..

[5]  Xiuping Jia,et al.  Mixed Pixel Analysis for Flood Mapping Using Extended Support Vector Machine , 2009, 2009 Digital Image Computing: Techniques and Applications.

[6]  Michael G. Grant,et al.  Data processing of remotely sensed airborne hyperspectral data using the Airborne Processing Library (APL): Geocorrection algorithm descriptions and spatial accuracy assessment , 2014, Comput. Geosci..

[7]  David L. Mills,et al.  Computer network time synchronization : the network time protocol on earth and in space , 2006 .

[8]  Wolfram Mauser,et al.  Airborne Visible / Infrared Imaging Spectrometer AVIS: Design, Characterization and Calibration , 2007, Sensors.

[9]  Aiwu Zhang,et al.  A Registration Scheme for Multispectral Systems Using Phase Correlation and Scale Invariant Feature Matching , 2016, J. Sensors.

[10]  David L. Mills,et al.  Internet Engineering Task Force (ietf) Network Time Protocol Version 4: Protocol and Algorithms Specification , 2010 .

[11]  Matthew O. Anderson,et al.  Radiometric and Geometric Analysis of Hyperspectral Imagery Acquired from an Unmanned Aerial Vehicle , 2012, Remote. Sens..

[12]  Charles K. Toth,et al.  Remote sensing platforms and sensors: A survey , 2016 .

[13]  Lingbo Yang,et al.  Toward High Altitude Airship Ground-Based Boresight Calibration of Hyperspectral Pushbroom Imaging Sensors , 2015, Remote. Sens..

[14]  I. Colomina,et al.  Unmanned aerial systems for photogrammetry and remote sensing: A review , 2014 .