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\begin{document}

\title{Remotely-sensed vegetation greening along a restoration gradient of a
tropical forest, Kibale National Park, Uganda}



\author[1]{Anu Valtonen}%
\author[1]{Eveliina Korkiatupa}%
\author[1]{Sille Holm}%
\author[1]{Geoffrey Malinga}%
\author[2]{Ryosuke Nakadai}%
\affil[1]{University of Eastern Finland}%
\affil[2]{The University of Tokyo}%


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  \date{May 25, 2024}


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\begin{abstract}
Restoration has now emerged as a global priority, with international
initiatives such as the ``UN Decade on Ecosystem Restoration
(2021-2030)''. To fulfil the large-scale global restoration ambitions,
an essential step is the monitoring of vegetation recovery after
restoration interventions. The aim of this study was to evaluate the
utility of remotely-sensed vegetation indices, Normalized Difference
Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), to monitor
the rate of forest regeneration across a tropical forest restoration
project area in Kibale National Park, Uganda. As a result, we observed
non-linear patterns in NDVI and EVI across the first 25 years of
recovery. Both NDVI and EVI increase for the first 10 years of forest
regeneration. This ``greening'' phase could be used as the indicator of
successful onset of forest recovery. In particular, the decline of
elephant grass, which suppresses the natural regeneration of trees in
our area, can be detected as an increase in NDVI. Primary forests
differed from the 25-year-old regenerating forests based on the unique
combination of low mean and low seasonal variation in EVI. Our results,
therefore, suggest that the long-term success of forest restoration
could be monitored by evaluating how closely the combination of mean,
and degree of seasonal variation in EVI, resembles that observed in the
primary forest.%
\end{abstract}%



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