A. Stein – författare

This text addresses methodological issues of production ecology, and contains scientific contributions written by nine specialists. A central issue is the combination of the agricultural model with reliable data in relation to scale. A model is developed with data from a single point, whereas decisions are to be made for areas of land. Such an approach requires the use of a skilful treatment of available data and information. The book is divided into four parts: advanced information science yields the best possible models in an efficient way; geographical information systems combine various layers of spatial information; statistics upscale local information towards regions and test its reliability; and modern trends in automated modelling are identified. The book is illustrated with various practical studies, ranging from the individual model to the whole European community. It aims at a readership of graduate and post-graduate agricultural scientists, practitioners and politicians.

This title treats statistical issues that are of relevance in spatial studies for remote sensing. It consists of contributions by international experts in this field. A brief overview of basic statistics is given, followed by physical aspects of the topic. Spatial statistics addresses classification of images by supervised and unsupervised procedures, estimation of spatial structures by variograms, interpolation, simulation, sampling and issues of scale. Geographical information systems allow the integration of remote sensing with other sources of information, concentrating on the concept of the pixel. Attention is also given to decision support for a wide variety of possible and important decisions. A single data set is used throughout the book. This book therefore provides an overview of the state of the art of spatial statistics for remote sensing, highlighting new frontiers in this rapidly developing field of science. `Lunar Gravimetry: Revealing the Far-Side is a long-awaited monograph wrapping up the past decades of lunar gravimetric research. Despite a series of lunar missions and extensive research on the subject, half of the lunar globe has remained unaccessed.This text shows how this deficit impacts today's knowledge about the Moon, how to attack this problem in modern data analysis and how to ultimately solve it by dedicated inter-satellite tracking in future lunar exploration missions.

The food market is changing from a producer-controlled to a consumer-directed market. A main driving force is consumer concern about agricultural production methods and food safety. More than before, the consumer demands transparency of the production and processing chain. A food chain can be quite complex and the use of models has become indispensable to handle this complexity. Modelling tools are becoming increasingly important to guide the decisions for production of high-quality and safe agricultural foods. With the aid of models it becomes possible to control and predict quality attributes, so that product innovation can be done more efficiently. However, quality is an elusive concept, and there is always an aspect of subjectivity and uncertainty. A novel approach in the agro-food chain would be to tackle subjective elements and uncertainty in modelling by using Bayesian statistics and Bayesian Belief Networks. Bayesian approaches use prior probabilities (partly accounting for subjectivity) to estimate posterior probabilities, resulting in higher accuracy than is possible with classical statistical techniques.Thus, the variability and uncertainty in data and decisions, inherent in a complex food chain, can be dealt with.

The food market is changing from a producer-controlled to a consumer-directed market. A main driving force is consumer concern about agricultural production methods and food safety. More than before, the consumer demands transparency of the production and processing chain. A food chain can be quite complex and the use of models has become indispensable to handle this complexity. Modelling tools are becoming increasingly important to guide the decisions for production of high-quality and safe agricultural foods. With the aid of models it becomes possible to control and predict quality attributes, so that product innovation can be done more efficiently. However, quality is an elusive concept, and there is always an aspect of subjectivity and uncertainty. A novel approach in the agro-food chain would be to tackle subjective elements and uncertainty in modelling by using Bayesian statistics and Bayesian Belief Networks. Bayesian approaches use prior probabilities (partly accounting for subjectivity) to estimate posterior probabilities, resulting in higher accuracy than is possible with classical statistical techniques.Thus, the variability and uncertainty in data and decisions, inherent in a complex food chain, can be dealt with.

The determination of crustal structure by means of explo­ sion seismology has been one of the major objectives of the European Seismological Commission (ESC) over the past twenty-five years. It was decided some time ago to publish the results of regional crustal investigations in Europe in a series of monographs. This publication entitled "Ex­ plosion Seismology in Central Europe - Data and Results" is Volume 1 in a sequence of publications dealing with the crustal structure in Europe. The European seismologists are indebted to the German Geo­ physical Society (Deutsche Geophysikalische Gesellschaft) for taking the initiative to publish this book. Thanks are due to the German Research Society (Deutsche Forschungs­ gemeinschaft) for providing generous financial support of the field measurements and data evaluation. It is hoped that this publication will stimulate a continuation of in­ vestigations of the earth's lithosphere in order to eluci­ date the details which are still not fully understood.