<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Amici, Valerio</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Dealing with vagueness in complex forest landscapes: A soft classification approach through a niche-based distribution model</style></title><secondary-title><style face="normal" font="default" size="100%">Ecological Informatics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">classification uncertainty</style></keyword><keyword><style  face="normal" font="default" size="100%">Forecasting forests</style></keyword><keyword><style  face="normal" font="default" size="100%">Forest cover map</style></keyword><keyword><style  face="normal" font="default" size="100%">Fuzzy set</style></keyword><keyword><style  face="normal" font="default" size="100%">Maxent</style></keyword><keyword><style  face="normal" font="default" size="100%">Remote sensing</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2011///</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://linkinghub.elsevier.com/retrieve/pii/S1574954111000550</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">6</style></volume><pages><style face="normal" font="default" size="100%">371 - 383</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The increasing interest in biodiversity conservation has led to the development of new approaches to facilitate ecologically based conservation policies and management plans. In this context, the development of effective methods for the classiﬁcation of forest types constitutes a crucial issue as forests represent the most widespread vegetation structure and play a key role in ecosystem functioning. In this study a maximum entropy approach (Maxent) to forest type classiﬁcation in a complex Mediterranean area, has been investigated. Maxent, a niche-based model of species/habitat distribution, allowed researchers to estimate the potential distribution of four forest types: Holm oak, Mixed oak, Mixed broadleaved and Riparian forests. The Maxent model's internal tests have proved a powerful tool for estimating the model's accuracy and analyzing the effects of the most important variables in the produced models. Moreover the comparison with a spectral response-based fuzzy classiﬁcation, showed a higher accuracy in the Maxent outputs, demonstrating how the use of environmental variables, combined with spectral information in the classiﬁcation of natural or seminatural land cover classes, improves map accuracies. The modeling approach followed by this study, taking into account the uncertainty proper of the natural ecosystems and the use of environmental variables in land cover classiﬁcation, can represent a useful approach to making more efﬁcient and effective ﬁeld inventories and to developing effective conservation policies.</style></abstract><issue><style face="normal" font="default" size="100%">6</style></issue><notes><style face="normal" font="default" size="100%">The following values have no corresponding Zotero field:&lt;br/&gt;publisher: Elsevier B.V.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Amici, Valerio</style></author><author><style face="normal" font="default" size="100%">Geri, Francesco</style></author><author><style face="normal" font="default" size="100%">Battisti, Corrado</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">An integrated method to create habitat suitability models for fragmented landscapes</style></title><secondary-title><style face="normal" font="default" size="100%">Journal for Nature Conservation</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Connectivity</style></keyword><keyword><style  face="normal" font="default" size="100%">Focal species</style></keyword><keyword><style  face="normal" font="default" size="100%">Fuzzy set</style></keyword><keyword><style  face="normal" font="default" size="100%">Habitat conservation</style></keyword><keyword><style  face="normal" font="default" size="100%">Landscape planning</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2010///</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://linkinghub.elsevier.com/retrieve/pii/S1617138109000740</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">18</style></volume><pages><style face="normal" font="default" size="100%">215 - 223</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Given the pervasive inﬂuence of human induced habitat fragmentation in ecological processes, landscape models are a welcome advance. The development of GIS software has allowed a greater use of these models and of analyses of the relationship between species and habitat variables. Habitat suitability models are thus theoretical concepts that can be used for planning in fragmented landscapes and habitat conservation. The most commonly used models are based on single species and on the assignment of suitability values for some environmental variables. Generally the cartographic basis for modeling suitability are thematic maps produced by a Boolean logic. In this paper we propose a model based on a set of focal species and on maps produced by a fuzzy classiﬁcation method. Focal species, selected by an expert-based approach, provide a practical way of extending the scope of habitat suitability models to the conservation of biodiversity at landscape scale. The utilisation of a classiﬁcation method that applies a continuity criterion may allow more consideration of the connectivity of an area because it allows a better detection of ecological gradients within a landscape. We applied this methodology to the Tuscany region focusing on terrestrial mammals. Performing a fuzzy classiﬁcation we produced ﬁve land cover maps and through image processing operations we obtained a suitability model which applies a continuity criterion. The resulting suitability fuzzy model seems better for the study of connectivity and fragmentation, especially in areas with high spatial complexity</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue><notes><style face="normal" font="default" size="100%">The following values have no corresponding Zotero field:&lt;br/&gt;publisher: Elsevier</style></notes></record></records></xml>