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Titel |
Analysing land cover and land use change in the Matobo National Park and surroundings in Zimbabwe |
VerfasserIn |
Valeska Scharsich, Kupakwashe Mtata, Michael Hauhs, Holger Lange, Christina Bogner |
Konferenz |
EGU General Assembly 2016
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Medientyp |
Artikel
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Sprache |
en
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Digitales Dokument |
PDF |
Erschienen |
In: GRA - Volume 18 (2016) |
Datensatznummer |
250131533
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Publikation (Nr.) |
EGU/EGU2016-11954.pdf |
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Zusammenfassung |
Natural forests are threatened worldwide, therefore their protection in National Parks is
essential. Here, we investigate how this protection status affects the land cover. To answer this
question, we analyse the surface reflectance of three Landsat images of Matobo
National Park and surrounding in Zimbabwe from 1989, 1998 and 2014 to detect
changes in land cover in this region. To account for the rolling countryside and the
resulting prominent shadows, a topographical correction of the surface reflectance was
required.
To infer land cover changes it is not only necessary to have some ground data for
the current satellite images but also for the old ones. In particular for the older
images no recent field study could help to reconstruct these data reliably. In our
study we follow the idea that land cover classes of pixels in current images can be
transferred to the equivalent pixels of older ones if no changes occurred meanwhile.
Therefore we combine unsupervised clustering with supervised classification as
follows.
At first, we produce a land cover map for 2014. Secondly, we cluster the images with
clara, which is similar to k-means, but suitable for large data sets. Whereby the best number
of classes were determined to be 4. Thirdly, we locate unchanged pixels with change
vector analysis in the images of 1989 and 1998. For these pixels we transfer the
corresponding cluster label from 2014 to 1989 and 1998. Subsequently, the classified pixels
serve as training data for supervised classification with random forest, which is
carried out for each image separately. Finally, we derive land cover classes from the
Landsat image in 2014, photographs and Google Earth and transfer them to the
other two images. The resulting classes are shrub land; forest/shallow waters; bare
soils/fields with some trees/shrubs; and bare light soils/rocks, fields and settlements.
Subsequently the three different classifications are compared and land changes are
mapped.
The main changes are observable in the surroundings of the National Park, especially the
common lands have lost their clear boundaries with time. In the National Park, the area of
forest increases from 1989 to 2014 from 58% to 61% whereas the area of shrub land
decreases by the same amount. The amount of each of the other two classes remains constant.
These changes indicate an actual effect of the protection status of the National
Park.
In our study remote sensing data are the main source to evaluate the effects and the
benefits of a protected area without on-side studies. This could be important for regions,
where field studies are not possible because of insecure political conditions and only remote
sensing data are available. |
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