Truy cập dữ liệu môi trường nhất quán và khách quan là một điều kiện tiên quyết cho mô hình. Rất nhiều (toàn cầu) các mô hình tồn tại đòi hỏi các dữ liệu trên mặt đất môi trường. Chúng bao gồm các mô hình tương tác đất-không khí, các mô hình quá trình hệ sinh thái, các mô hình thủy văn, và các mô hình sinh quyển động, như được giải thích trong Chương 2, các mô hình này thường được xây dựng quy nạp suy luận kết hợp. Nhà mô hình thường xuyên phải đối mặt với thâm. | 4 Geographic data for environmental modelling and assessment Bradley c. Reed Jesslyn F. Brown and Thomas R. Loveland ABSTRACT Access to consistent and objective environmental data is a prerequisite for modelling. Many global models exist that require terrestrial environmental data. They include land-atmosphere interaction models ecosystem process models hydrologic models and dynamic biosphere models as explained in Chapter 2 these models are usually of a combined inductive-deductive construction. Modellers often face a deficit of appropriate and accurate environmental data to set the initial conditions of parameters in their models as well as to validate model output. Until recently there were very few observations of global-scale environmental phenomena from which to construct consistent scientific databases of vegetation soils and climate. A significant increase in activity to fill this void has resulted in improved databases of global topography land cover soils and satellite imagery that provides information on vegetation dynamics. These data sets governed by various use and cost policies are available from national and international organizations. Gaining access to the appropriate data sets is one hurdle that modellers must clear another is incorporating the geospatial data into their numerical simulation and forecasting models. Improving the communication between environmental data providers and data users is crucial for improving access to data of the appropriate scale and thematic content refining data quality and reducing the technical barriers to working with complex geospatial data. INTRODUCTION Data are the fundamental building blocks of scientific inquiry. At the beginning of the 1990s there were few objective databases designed to support modelling especially at a global scale. There were of course interpreted maps of vegetation soils and climate often based on broad assumptions but no direct or even remote observations of global-scale .
