Abstract
Abstract. The unmanned airborne system (UAS) remote sensing using lightweight multi- and hyperspectral imaging sensors offer new possibilities for the environmental monitoring applications. Based on the accurate measurements of the way in which the object reflect and emit energy, wide range of affecting variables can be monitored. Condition for reliable applications is reliable and accurate input data. In many applications, installation of geometric and radiometric reference targets in the object area is challenging, for instance, in forest or water areas. On the other hand, UASs are often operated in very poor conditions, under clouds or under variable cloud cover. Our objective is to develop an autonomous hyperspectral UAS imaging system and data processing chain that does not require any ground reference targets. Prerequisites for this kind of a system are an appropriate sensor setup, stable and wellcalibrated instruments and rigorous data processing. In this paper, we will describe the new hyperspectral UAS imaging system that is under development. Important applications for the proposed system include precision agriculture, forest monitoring and water quality monitoring. Finally, we will consider the use of the system in forest inventory application and present the first results of the summer 2014 campaigns.
Highlights
Unmanned airborne systems (UAS) are increasingly utilized in wide variety of environmental monitoring applications
The objective in the campaign was to study the applicability of a measurement tactic, where small Unmanned aerial vehicle (UAV) image blocks are used to provide in situ data for the national forest inventory purposes
The RTK GPS trajectory was processed with a 10 Hz frequency using the virtual reference station generated in the area using the Geotrim GNSS station network
Summary
Unmanned airborne systems (UAS) are increasingly utilized in wide variety of environmental monitoring applications. The latest developments in sensors have made the hyperspectral UAS remote sensing possible. In quantitative remote sensing applications, a fundamental requirement is data that is characterizing the physical geometric and reflectance characteristics of objects. A novel Fabry-Perot interferometer based frame-format, lightweight hyperspectral camera is highly relevant technology in many environmental applications (Mäkynen et al, 2011; Saari et al, 2011; Honkavaara et al, 2012; 2013). When images are collected continuously with stereoscopic and multiview setups in a block structure, 3D surface information based on stereoscopy and spectral, bidirectional reflectance signatures can be produced. Area format imaging principle has many attractive features in comparison to pushbroom imaging that is the conventional technique used in hyperspectral sensors (Hruska et al, 2012)
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