Real-time and post-processed georeferencing for hyperpspectral drone remote sensing

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http://hdl.handle.net/10138/299870

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Oliveira , R A , Khoramshahi , E , Suomalainen , J , Hakala , T , Viljanen , N , Honkavaara , E , F. , R (ed.) , I. , T (ed.) & T. , F (ed.) 2018 , ' Real-time and post-processed georeferencing for hyperpspectral drone remote sensing ' , The international archives of the photogrammetry, remote sensing and spatial information sciences , vol. 42 , no. 2 , pp. 789-795 . https://doi.org/10.5194/isprs-archives-XLII-2-789-2018

Title: Real-time and post-processed georeferencing for hyperpspectral drone remote sensing
Author: Oliveira, R.A.; Khoramshahi, E.; Suomalainen, J.; Hakala, T.; Viljanen, N.; Honkavaara, E.
Editor: F., Remondino; I., Toschi; T., Fuse
Contributor: University of Helsinki, Department of Computer Science
Date: 2018
Language: eng
Number of pages: 7
Belongs to series: The international archives of the photogrammetry, remote sensing and spatial information sciences
ISSN: 1682-1750
URI: http://hdl.handle.net/10138/299870
Abstract: The use of drones and photogrammetric technologies are increasing rapidly in different applications. Currently, drone processing workflow is in most cases based on sequential image acquisition and post-processing, but there are great interests towards real-time solutions. Fast and reliable real-time drone data processing can benefit, for instance, environmental monitoring tasks in precision agriculture and in forest. Recent developments in miniaturized and low-cost inertial measurement systems and GNSS sensors, and Real-time kinematic (RTK) position data are offering new perspectives for the comprehensive remote sensing applications. The combination of these sensors and light-weight and low-cost multi- or hyperspectral frame sensors in drones provides the opportunity of creating near real-time or real-time remote sensing data of target object. We have developed a system with direct georeferencing onboard drone to be used combined with hyperspectral frame cameras in real-time remote sensing applications. The objective of this study is to evaluate the real-time georeferencing comparing with post-processing solutions. Experimental data sets were captured in agricultural and forested test sites using the system. The accuracy of onboard georeferencing data were better than 0.5 m. The results showed that the real-time remote sensing is promising and feasible in both test sites. © Authors 2018. CC BY 4.0 License.
Subject: Drone
Hyperspectral frame camera
Photogrammetry
Real-time georeferencing
Remote sensing
Cameras
Data handling
Drones
Forestry
Direct georeferencing
Environmental Monitoring
Georeferencing
HyperSpectral
Inertial measurement system
Real time kinematic
Remote sensing applications
Remote sensing data
Real time systems
113 Computer and information sciences
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