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Remote Sens. 2016, 8(12), 1029; doi:10.3390/rs8121029

Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics

1
Department Computational Landscape Ecology, Helmholtz Centre for Environmental Research—UFZ, Permoserstr. 15, D-04318 Leipzig, Germany
2
Institute of Geography, Cartography GIS & Remote Sensing Sect, Georg-August-University Göttingen, Goldschmidtstr. 5, D-37077 Göttingen, Germany
3
Depterment of Geography and Environmental Studies, Geomatics and Landscape Ecology Lab, Carleton University, 1125 Colonel By Drive, K1S 5B6 Ottawa, ON, Canada
4
Chair of Forest Inventory and Remote Sensing, Georg-August-University Göttingen, Büsgenweg 5, D-37077 Göttingen, Germany
5
Bavarian Forest National Park, Department of Conservation and Research, Freyunger Straße 2, D-94481 Grafenau, Germany
*
Author to whom correspondence should be addressed.
Academic Editors: Lars T. Waser, Clement Atzberger and Prasad S. Thenkabail
Received: 6 September 2016 / Revised: 1 December 2016 / Accepted: 5 December 2016 / Published: 18 December 2016
(This article belongs to the Special Issue Remote Sensing of Forest Health)
View Full-Text   |   Download PDF [3399 KB, uploaded 19 December 2016]   |  

Abstract

Anthropogenic stress and disturbance of forest ecosystems (FES) has been increasing at all scales from local to global. In rapidly changing environments, in-situ terrestrial FES monitoring approaches have made tremendous progress but they are intensive and often integrate subjective indicators for forest health (FH). Remote sensing (RS) bridges the gaps of these limitations, by monitoring indicators of FH on different spatio-temporal scales, and in a cost-effective, rapid, repetitive and objective manner. In this paper, we provide an overview of the definitions of FH, discussing the drivers, processes, stress and adaptation mechanisms of forest plants, and how we can observe FH with RS. We introduce the concept of spectral traits (ST) and spectral trait variations (STV) in the context of FH monitoring and discuss the prospects, limitations and constraints. Stress, disturbances and resource limitations can cause changes in FES taxonomic, structural and functional diversity; we provide examples how the ST/STV approach can be used for monitoring these FES characteristics. We show that RS based assessments of FH indicators using the ST/STV approach is a competent, affordable, repetitive and objective technique for monitoring. Even though the possibilities for observing the taxonomic diversity of animal species is limited with RS, the taxonomy of forest tree species can be recorded with RS, even though its accuracy is subject to certain constraints. RS has proved successful for monitoring the impacts from stress on structural and functional diversity. In particular, it has proven to be very suitable for recording the short-term dynamics of stress on FH, which cannot be cost-effectively recorded using in-situ methods. This paper gives an overview of the ST/STV approach, whereas the second paper of this series concentrates on discussing in-situ terrestrial monitoring, in-situ RS approaches and RS sensors and techniques for measuring ST/STV for FH. View Full-Text
Keywords: forest health; forest ecosystem; earth observation; remote sensing; traits; spectral traits (ST); spectral trait variations (STV); non-spectral traits (N-ST) forest health; forest ecosystem; earth observation; remote sensing; traits; spectral traits (ST); spectral trait variations (STV); non-spectral traits (N-ST)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Lausch, A.; Erasmi, S.; King, D.J.; Magdon, P.; Heurich, M. Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics. Remote Sens. 2016, 8, 1029.

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