Special Issue on Environmental Data Mining

Data Mining is the discipline for non trivial identifying of valid, novel, potentially useful, ultimately understandable patterns in data [3] and provides the opportunity to extract relevant decisional knowledge from data bases in any application field. In particular it can contribute to a better understanding of Environmental Sciences. Environmental Sciences is a wide research field with a number of open problems that require attention. The technological development occurred in the last years has significantly increased the availability of environmental data to be exploited for better addressing current challenges in the area. My interest in data mining comes from the 90s, when I was a PhD student. From then, part of my research activity has been focused on disseminating data mining in different areas of application, as well as to contribute to these areas by applying data mining to some challenging real problems. Among other activities, I’m the chair of the Data Mining Techniques for Environmental Sciences (DMTES) workshop, which we organize every two years in the frame of the Environmental Modelling and Software Society biannual meetings. The DMTES series started in 2002, with the aim of becoming a multidisciplinar discussion forum for the Data Mining and Environmental Sciences communities. From then onwards, every two years the DMTES has been celebrated all along the world (Vermont (USA), Barcelona (Spain), Otawa (Canada), Leizig (Germany), San Diego (USA), Toulouse (France)), providing a valuable opportunity for a close contact between the data mining community and the Environmental Sciences community, and discussions arising in the workshop raise current challenges in both areas and synergic opportunities. From these meetings and other collaborations in environmental applications we learned that potentials of Data Mining in Environmental Sciences are enormous, and they are still poorly exploited by many reasons, in part due to a lack of knowledge of these potentials from the environmental side, and also to a lack of knowledge of the current environmental challenges from the Data Mining side. This special issue launches with the spirit of giving a clue on how data mining can contribute to a better comprehension and management of the environment as well as the kind of environmental challenges that can be addressed from a data mining perspective. The issue contains a careful selection of 8 papers organized around different topics, with a good coverage of the different research topics currently active in Environmental Data Mining, from more theoretical to more applied, from more specific applications, to more global ones, and covering a perspective of different environmental systems and data mining methods. Two of the papers and are surveys in challenging topics for environmental data mining, one from the data mining methodologies perspective, the other from the environmental sciences perspective. The first survey [6] is about preprocessing data, which is the very first step in any data mining project. The second one [7] is about the use of data mining methods in water management decision support, which is the very last step of the data mining process. From the point of view of the environmental systems targeted in the different papers, the issue shows research on climate change, ecological systems, ichtiology, water quality, water management and land use. The papers address a variety of environmental problems like understanding the effects of water quality in freshwater macroinvertebrates occurrence, fish species