Environmental Information Systems
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Environmental information systems (EIS) are concerned with the management of data about the soil, the water, the air, and the species in the world around us. This first textbook on the topic gives a conceptual framework for EIS by structuring the data flow into 4 phases: data capture, storage, analysis, and metadata management. This flow corresponds to a complex aggregation process gradually transforming the incoming raw data into concise documents suitable for high-level decision support. All relevant concepts are covered, including statistical classification, data fusion, uncertainty managem...
Environmental information systems (EIS) are concerned with the management of data about the soil, the water, the air, and the species in the world around us. This first textbook on the topic gives a conceptual framework for EIS by structuring the data flow into 4 phases: data capture, storage, analysis, and metadata management. This flow corresponds to a complex aggregation process gradually transforming the incoming raw data into concise documents suitable for high-level decision support. All relevant concepts are covered, including statistical classification, data fusion, uncertainty management, knowledge based systems, GIS, spatial databases, multidimensional access methods, object-oriented databases, simulation models, and Internet-based information management. Several case studies present EIS in practice. Environmental information systems are concerned with the management of data about the soil, the water, the air, and the species in the world around us. This is the first textbook on the topic. It presents a conceptual framework for environmental information systems by structuring the data flow into four phases: data capture, data storage, data analysis, and metadata management. This flow corresponds to a complex aggregation process during which the incoming raw date is gradually transformed into concise documents that can be used for high-level decision support. The book covers the concepts underlying this process, including statistical classification, data fusion, uncertainty management, knowledge based systems, GIS, spatial databases, multidimensional access methods, object-oriented databases, simulation models, and Internet-based information management. It also presents several case studies of environmental information systems in practice.
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