Reference : Landslide Susceptibility Zonation in case of deforestation in Northern Negros Natural Pa...
Dissertations and theses : Master's dissertation
Physical, chemical, mathematical & earth Sciences : Earth sciences & physical geography
Landslide Susceptibility Zonation in case of deforestation in Northern Negros Natural Park (NNNP) - Philippines
[fr] Cartographie de la susceptibilité aux glissements de terrain en cas de déforestion dans le Northern Negros Natural Park (NNNP) - Philippines
Denis, Antoine mailto [Université Catholique de Louvain - UCL]
Université catholique de Louvain, ​Louvain-La-Neuve, ​​Belgique
Bio-ingénieur: sciences et technologie de l'environnement avec distinction
Defourny, Pierre
De Wasseige, Carlos
[en] Landslide ; deforestation ; remote sensing ; GIS ; Philippines ; Negros
[en] The Philippines is one of the most severely deforested countries in Southeast Asia
with around 7 percent remaining forest in 2005. Moreover, due to its geographic
circumstances, it is one of the most natural hazard prone countries in the world with
frequent occurrence of earthquakes, volcanic eruptions and typhoons, resulting notably in
an increasing occurrence of landslides and flash floods.
This work focuses on the North Negros Island and especially the recently proclaimed
Northern Negros Natural Park (NNNP) that is considered the largest remaining evergreen
forest in Negros Island and one of the largest in the Central Philippines.
Deforestation continues to be a threat for this forest. The fact that this forest is located
in mountainous area and that, due to a very high land pressure, people always creep higher
to cultivate the steep slopes of these mountains, increase the landslide susceptibility
associated with this deforestation.
As an answer to that situation, this research aimed two main objectives.
In a first time a land cover map was produced through digital classification of a 2003
SPOT 5 satellite image focusing on attempt for forest types differentiation in NNNP. Given
that conventional method using spectral characteristics of the image revealed to be
unsuccessful for this differentiation, this was finally achieved with the use of elevation and
the distance to river as classifiers. The land cover map produced has an overall accuracy of
89,2 %.
In a second time, a Landslide Susceptibility Zonation (LSZ) model was designed and
implemented in a Geographical Information System (GIS) environment. The nine selected
landslide-controlling factors were built from raw data and then combined through Weighted
Linear Combination (WLC).Two scenarios corresponding to a “stable forest scenario” and a
“deforestation scenario” were modeled. The integration of the land cover map previously
produced served successfully as the key factor that enabled to model the Landslide
Susceptibility (LS) change due to potential deforestation in NNNP. A sensitivity analysis of
the factors used for this modeling was realized by comparison with a “LSZ in case of
deforestation” map based on the four main factors only (land cover, land cover change,
slope and proximity to river). It appeared that, the LSZ model was not sensitive to the use
of other factors than these four main ones. Finally, in order to give an idea of the reliability
of the results, the LSZ maps were compared with a landslide inventory realized during the
field survey in North Negros. Some limitations in the landslide inventory did not allow
drawing pertinent conclusion from this comparison.
In parallel and in order to evaluate the feasibility of integrating the land cover
knowledge of local environmentalist into a GIS data base through field survey and 3D-GIS
activity in a remote laboratory, a participatory 3D-GIS experience was attempted in Negros.
Consistence of results between field and 3D-GIS laboratory experience validate this way of
extracting land cover information, which could revealed useful for land cover identification
of hardly accessible areas.
Unité d'environnemétrie et de Géomatique - ENGE
Commission universitaire pour le Développement - CUD

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