Dry tropical forests undergo massive conversion and degradation processes.
This also holds true for the extensive Miombo forests that cover large parts
of Southern Africa. While the largest proportional area can be found in
Angola, the country still struggles with food shortages, insufficient medical
and educational supplies, as well as the ongoing reconstruction of
infrastructure after 27 years of civil war. Especially in rural areas, the
local population is therefore still heavily dependent on the consumption of
natural resources, as well as subsistence agriculture. This leads, on one
hand, to large areas of Miombo forests being converted for cultivation
purposes, but on the other hand, to degradation processes due to the selective
use of forest resources. While forest conversion in south-central rural Angola
has already been quantitatively described, information about forest
degradation is not yet available. This is due to the history of conflicts and
the therewith connected research difficulties, as well as the remote location
of this area. We apply an annual time series approach using Landsat data in
south-central Angola not only to assess the current degradation status of the
Miombo forests, but also to derive past developments reaching back to times of
armed conflicts. We use the Disturbance Index based on tasseled cap
transformation to exclude external influences like inter-annual variation of
rainfall. Based on this time series, linear regression is calculated for
forest areas unaffected by conversion, but also for the pre-conversion period
of those areas that were used for cultivation purposes during the observation
time. Metrics derived from linear regression are used to classify the study
area according to their dominant modification processes. We compare our
results to MODIS latent integral trends and to further products to derive
information on underlying drivers. Around 13% of the Miombo forests are
affected by degradation processes, especially along streets, in villages, and
close to existing agriculture. However, areas in presumably remote and dense
forest areas are also affected to a significant extent. A comparison with
MODIS derived fire ignition data shows that they are most likely affected by
recurring fires and less by selective timber extraction. We confirm that areas
that are used for agriculture are more heavily disturbed by selective use
beforehand than those that remain unaffected by conversion. The results can be
substantiated by the MODIS latent integral trends and we also show that due to
extent and location, the assessment of forest conversion is most likely not
sufficient to provide good estimates for the loss of natural resources. View
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