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Selection: with tag logistic-regression [4 articles] 


Modelling post-fire soil erosion hazard using ordinal logistic regression: a case study in South-eastern Spain

Geomorphology, Vol. 232 (March 2015), pp. 117-124,


[Highlights] [::] A method to identify most vulnerable areas towards soil erosion has been proposed. [::] Slope steepness, aspect and fire severity were the inputs. [::] The field data were successfully fit to the model in 60% of cases after 50 runs. [::] North-facing slopes were shown to be less prone to soil erosion than the rest. [Abstract] Treatments that minimize soil erosion after large wildfires depend, among other factors, on fire severity and landscape configuration so that, in practice, most of them are applied according to ...


(INRMM-MiD internal record) List of keywords of the INRMM meta-information database - part 20

(February 2014)
Keywords: inrmm-list-of-tags   liquidambar-styraciflua   liriodendron-spp   liriodendron-tulipifera   list   literate-programming   lithocarpus-densiflorus   lithocarpus-glaber   lithocarpus-spp   lithuania   litter   local   local-average-invariance   local-over-complication   local-scale   lodoicea-maldivica   logging   logic-programming   logics   logistic-regression   lognormal-distribution   long-distance-dispersal   long-distance-pollen-flow   long-lived-changes   long-range-transport   long-term   lonicera-alpigena   lonicera-caerulea   lonicera-nigra   lonicera-periclymenum   lonicera-spp   lonicera-tatarica   lonicera-xylosteum   loranthus-europaeus   lose-lose-solution   low-diversity   low-intensity-agriculture   low-intensity-cumulated-effect   low-pass-filtering   lpj-guess   lucanidae   lupinus-incana   lupinus-spp   lymantria-dispar   lymantria-monacha   lyonothamnus-floribundus   lysiloma-latisiliquum   macchia   macedonia   machine-learning   maclura-spp   macro-remains   macroclimate   macroecology   macrofossils   macropsis-glandacea   maghreb   magnolia-acuminata   magnolia-grandiflora   magnoliophyta   mahalanobis-distance   mahonia-spp   malta   malus-crescimannoi   malus-dasyphylla   malus-pumila   malus-spp   malus-sylvestris   mammals   mammea-americana   management   management-indicators   management-strategies   manganese   mangifera-indica   mangrove-forest   mangroves   manifesto   manilkara-zapota   manual   manual-cutting   maple   maple-ash   maple-decline   maple-linden   mapping   mapping-networks   maps   maquis   marchalina   marginal-populations   marine-ecosystem   marssonina-betulae   mass-extinction   mass-spectrometry   mast-fruiting   mastixioideae   mastrave-modelling-library   mathematical-reasoning   mathematics  


List of indexed keywords within the transdisciplinary set of domains which relate to the Integrated Natural Resources Modelling and Management (INRMM). In particular, the list of keywords maps the semantic tags in the INRMM Meta-information Database (INRMM-MiD). [\n] The INRMM-MiD records providing this list are accessible by the special tag: inrmm-list-of-tags ( ). ...


Multi-scale robust modelling of landslide susceptibility: regional rapid assessment and catchment robust fuzzy ensemble

IFIP Advances in Information and Communication Technology, Vol. 413 (2013), pp. 321-335,


Landslide susceptibility assessment is a fundamental component of effective landslide prevention. One of the main challenges in landslides forecasting is the assessment of spatial distribution of landslide susceptibility. Despite the many different approaches, landslide susceptibility assessment still remains a challenge. A semi-quantitative method is proposed combining heuristic, deterministic and probabilistic approaches for a robust catchment scale assessment. A fuzzy ensemble model has been exploited for aggregating an array of different susceptibility zonation maps. Each susceptibility zonation has been obtained by applying ...


Spatial prediction models for landslide hazards: review, comparison and evaluation

Natural Hazards and Earth System Science, Vol. 5, No. 6. (7 November 2005), pp. 853-862,


The predictive power of logistic regression, support vector machines and bootstrap-aggregated classification trees (bagging, double-bagging) is compared using misclassification error rates on independent test data sets. Based on a resampling approach that takes into account spatial autocorrelation, error rates for predicting "present" and "future" landslides are estimated within and outside the training area. In a case study from the Ecuadorian Andes, logistic regression with stepwise backward variable selection yields lowest error rates and demonstrates the best generalization capabilities. The evaluation outside ...

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Integrated Natural Resources Modelling and Management - Meta-information Database.

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Meta-information Database (INRMM-MiD).
This database integrates a dedicated meta-information database in CiteULike (the CiteULike INRMM Group) with the meta-information available in Google Scholar, CrossRef and DataCite. The Altmetric database with Article-Level Metrics is also harvested. Part of the provided semantic content (machine-readable) is made even human-readable thanks to the DCMI Dublin Core viewer. Digital preservation of the meta-information indexed within the INRMM-MiD publication records is implemented thanks to the Internet Archive.
The library of INRMM related pubblications may be quickly accessed with the following links.
Search within the whole INRMM meta-information database:
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Full-text and abstracts of the publications indexed by the INRMM meta-information database are copyrighted by the respective publishers/authors. They are subject to all applicable copyright protection. The conditions of use of each indexed publication is defined by its copyright owner. Please, be aware that the indexed meta-information entirely relies on voluntary work and constitutes a quite incomplete and not homogeneous work-in-progress.
INRMM-MiD was experimentally established by the Maieutike Research Initiative in 2008 and then improved with the help of several volunteers (with a major technical upgrade in 2011). This new integrated interface is operational since 2014.