Die Cordillera Central der Dominikanischen Republik ist eine Quelle wichtiger natürlicher Ressourcen – vor allem Wasser – für dieses karibische Land. Im oberen Einzugsgebiet des Río Yaque del Norte wurde im Laufe des 20. Jahrhunderts ein großer Teil der natürlichen Wälder abgeholzt und durch Weide- und Ackerland sowie Sekundärvegetation ersetzt. Entwaldung und nicht nachhaltige Landnutzung auf den steilen Hängen dieses Gebietes haben zu Erosion und Landdegradierung geführt. Es gibt aber auch noch verschiedene primäre Bergwälder, darunter kleine Nebelwaldbereiche mit bedrohten endemischen Arten. Fernerkundungsdaten sind eine unverzichtbare Quelle für flächendeckende räumliche Informationen, die als Basis für Raumnutzungspläne und den Schutz bedrohter Ökosysteme benötigt werden. Die Nutzbarkeit von Satellitendaten mittlerer Auflösung (z.B. Landsat) für die Kartierung der Vegetationstypen des Untersuchungsgebietes ist begrenzt, weil das kleinräumige Mosaik verschiedener Landbedeckungstypen (wie in vielen tropischen Gebirgsbereichen) zu einem großen Anteil von Mischpixeln in diesen Daten führt. Die neue Generation kommerzieller hochauflösender Satelliten wie IKONOS (1 m bis 4 m Auflösung) ermöglicht eine detailliertere Kartierung von kleineren Interessensgebieten, aber die automatische Klassifizierung räumlich hochaufgelöster Daten beinhaltet auch neue Herausforderungen. Diese Arbeit beschäftigt sich daher hauptsächlich mit der Optimierung von Methoden zur Ausnutzung der räumlichen Information in hochauflösenden Satellitendaten für die Kartierung von tropischen Bergwäldern und anderen Landoberflächen.

Over the last decades, the rapid growth of the world population has led to a large number of emerging megacities. The 1999 Izmit (Turkey) earthquake is a striking example of the impact of natural hazards on megacities. On August 17, 1999, a magnitude 7.6 earthquake struck the area of Izmit, Turkey, resulting in 18,000 fatalities and US$ 18 billion in economic losses. The probability of a magnitude 7 earthquake striking Istanbul within the next 30 years ranges between 30% to 70%. In order to reduce the impact of natural hazards on human lives, emergency management plans are essential. The development of these plans strongly relies on up-to-date population and inventory data. However, existing techniques for population data generation do not meet the requirements of today’s dynamic cities. In this context, remote sensing has become an important source of information in the last years. However, detailed analyses on the suitability of remote sensing for urban applications are still rare.For her study, Julia Kubanek conducted a quantitative evaluation of the suitability of Ikonos imagery (1m resolution) for population modeling in the district of Zeytinburnu (Istanbul, Turkey). The results show that Ikonos images can be used for complementing existing inventory data sets. The automated extraction of single buildings was identified as the major source of error in the estimation of the population. Kubanek's study discusses the replacement of traditional, time-consuming and cost-intensive techniques for population estimation with remotely sensed imagery as a relatively new data source in an increasingly urbanized and fast-changing world. Her book addresses scientists and professionals in geography, remote sensing, urban planning, and natural hazards research.

Tropical rain forests are the most complex, varied, and species-rich terrestrial ecosystems on earth. However, these unique forests are more and more threatened by human activities. About half of the originally forested area has been deforested in the past decades and the pressure on today’s remaining rain forests is still growing.The German-Indonesian research project STORMA (“Stability of Rainforest Margins in Indonesia”) analyses the causes, circumstances, and consequences of rain forest conversion. In its survey area in Central Sulawesi (Indonesia), vast areas of intact rain forest still exist but are currently facing increasing exploitation by the rural population. Especially the expansion of cultivation area for cocoa and maize represents a major threat for local rain forests.Remote sensing plays an important role in the examination of rain forest loss, because it allows the regionalisation and quantification of spatial developments at different scales. In his book, Christian Knieper gains information about land cover and land cover change in Central Sulawesi on the basis of a Landsat 7/ETM+ time series. He applies a modern object-oriented approach which allows the analysis of non-spectral features (e.g. shape, spatial relations, thematic data) and goes beyond the pure isolated statistical examination of each pixel’s spectral values offered by traditional remote sensing techniques. The gathered results on land cover change provide essential information for socio-economic as well as ecological research activities within STORMA.

The natural environment of drylands is highly vulnerable and fra¬gile, variations of climate conditions here are the highest among all terrestrial ecosystems and that is why they are expected to be strongly influenced by the current climate change. Remote sensing and GIS play an important role in a better understanding about the nature of climate impacts on the drylands as a whole system and on the vegetation cover as the most important component of this ecosystem at all scales from global to regional and local. This book is one of the first to examine the dynamics of drylands in Kazakhstan using time series of remote sensing derived data and climate records over the last 20 years. The author investigated the problem from different views and combined analyses at multiple time and spatial scales. The entire spectrum of the interrelationship between climate and vegetation cover - spatial and temporal, on the regional, subregional and local scale, interannual and within the growing season -, has been analysed, described and discussed. A new monitoring approach was presented which enables discrimination between climatic and anthropogenic forces in the complex of dryland dynamics. The text improves the understanding of the nature and mechanisms of the ecosystem dynamics in the internal Eurasia and provides the basis for predicting changes in vegetation productivity that accompany changes in climate and human activities. Taken as a whole, the results of this study present indispensable information for ecological and socio-economic research and may be used by scientists, landscape managers, and decision makers interested in this region.

Advanced Remote Sensing is an application-based reference that provides a single source of mathematical concepts necessary for remote sensing data gathering and assimilation. It presents state-of-the-art techniques for estimating land surface variables from a variety of data types, including optical sensors such as RADAR and LIDAR. Scientists in a number of different fields including geography, geology, atmospheric science, environmental science, planetary science and ecology will have access to critically-important data extraction techniques and their virtually unlimited applications. While rigorous enough for the most experienced of scientists, the techniques are well designed and integrated, making the book's content intuitive, clearly presented, and practical in its implementation. - Comprehensive overview of various practical methods and algorithms - Detailed description of the principles and procedures of the state-of-the-art algorithms - Real-world case studies open several chapters - More than 500 full-color figures and tables - Edited by top remote sensing experts with contributions from authors across the geosciences