Earth System Monitoring

Humans have difficulty thinking at the global scale. Yet as we come to understand our planet as a single, interconnected, complex system and encounter compelling evidence of human impact on Earth’s climate and biosphere, the need for a truly global effort is increasingly urgent. In this concise and accessible text, David P. Turner presents an overview of global environmental change and a synthesis of research and ideas from the rapidly evolving fields of earth system science and sustainability science that is suitable for anyone interested in humanity’s current predicaments and what we can do about them.

This volume is dedicated to the main task of mathematical geoscientists during the last forty years - to establish new frontiers and new challenges in the study and understanding of the natural world.

Global change involves complex and far-reaching variations in the Earth’s systems, and satellite observations have been widely used in global change studies. Over the past five decades, Earth observation has developed into a comprehensive system that can conduct dynamic monitoring of the land, the oceans and the atmosphere at the local, regional and even global scale. At the same time, although a large number of Earth observation satellites have been launched, very few of them are used in global change studies. The lack of scientific satellite programs greatly hinders research on global change.

This volume outlines the developments and research directions currently being made world-wide in the earth sciences. It contains invited and refereed articles by leading younger researchers on their cutting-edge research, but aimed at a general scientific audience.

Hendrik Herold explores potentials and hindrances of using retrospective geoinformation for monitoring, communicating, modeling, and eventually understanding the complex and gradually evolving processes of land cover and land use change. Based on a comprehensive review of literature, available data sets, and suggested algorithms, the author proposes approaches for the two major challenges: To address the diversity of geographical entity representations over space and time, image segmentation is considered a global non-linear optimization problem, which is solved by applying a metaheuristic algorithm. To address the uncertainty inherent to both the data source itself as well as its utilization for change detection, a probabilistic model is developed. Experimental results demonstrate the capabilities of the methodology, e.g., for geospatial data science and earth system modeling.