Publication Date:
2021-03-29
Description:
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.
Keywords:
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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551
Language:
English
Type:
article
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publishedVersion
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