2010. spatial analysis and modelling of periglacial processes in hurd peninsula - poster
TRANSCRIPT
spatial analysis and modelling of periglacial processes in Hurd Peninsula, Livingston Island (Antarctic Peninsula)
Marco Jorge 1 , Gonçalo Vieira* 1, Miguel Ramos 21) CEG-IGOT - University of Lisbon , Portugal
2) Department of Physics, Universidad Alcalá de Henares, Spain
This work is the first attempt to model the spatial distribution of periglacial processes in Hurd Peninsula. As so, at this point methodologic issues are a major concern.
Both bivariate and multivariate statistical models were used to create models of susceptibility to the ocurrence (in the space domain) of solifluction lobes. The analysis was performed in the vicinity of the the Juan Carlos I Spanish Antarctic Sation, where detailed topographic information is available.
AIMSCarachterize the spatial distribution of stone-banked solifluction lobes; evaluate the environmental factors that control the spatial distribution of the lobes; and use statistical models to assess the susceptibility of the terrain to the the ocurrence of those geofeatures.
x x(1:9)
x1 x2 unique condition terrain units
bivariate weighting
multivariateweighting
SUSCEPTIBILITY MODELS
information value (Yin and Yan, 1988)
logistic regression
moraine ridgetillmoraine, vulcanic
bedrock
stone-banked solifluction lobes
rock glacier
scree / talus slopefrost-shattered debris
seasonal lake
fluvioglacial fan
sandy sediments
fluvioglacial terraceephemeral streamraised beach ridgecobble beach
lithology (surficial deposits)slopeaspect
SUSCEPTIBILITY MODEL WITHOUT THE "BEST COVARIATE" (LITHOLOGY)
BEST SUSCEPTIBILITY MODEL
\
Solifluction lobes are abundant and affect mainly frost-shattered debris. These deposits derive from the older moraine material, longer exposed to the frost weathering. Thus, their spatial distribution relates closely to the pattern of deglaciation.
Both the Logistic regression model and the Information Value model yeld very similar results, both on the success rate and on the covariates that relate the most with the distribution of the stone-banked solifluction lobes.
The statistical models of susceptibility to the ocurrence of stone-banked solifluction lobes show good results. Though, the quality of these models is limited by the small dimension of the study area and by the fact that the activity of the lobes was not mapped
The next step is to make the modelling at the scale of the Hurd Peninsula (c. 20 square km). New susceptibily models will be made following the same methods and their prediction capabitilities will be evaluated in areas not used to build the models.
Then, If climate surrogates appear as strong covariates, the dimension "time" can be added to the modelling, so that susceptibility maps can be derived for different climatic conditions.
Bibliography
Yin KL and Yan TZ (1988) Statistical prediction model for slope instability of metamorphosed rocks. In: Landslides-Glissements de Terrain. Proceedings V International Symposium on Landslides, Vol. 2, Lausanne, Switzerland, pp 1269–1272
layers / variables crossed with the dependent layer
Results, discussion
Methods
geomorphologic map
Study AreaIntroduction, aims
Lisb
on
, Po
rtu
gal