Heiko Balzter – författare

Hyperspectral Remote Sensing: Theory and Applications offers the latest information on the techniques, advances and wide-ranging applications of hyperspectral remote sensing, such as forestry, agriculture, water resources, soil and geology, among others. The book also presents hyperspectral data integration with other sources, such as LiDAR, Multi-spectral data, and other remote sensing techniques. Researchers who use this resource will be able to understand and implement the technology and data in their respective fields. As such, it is a valuable reference for researchers and data analysts in remote sensing and Earth Observation fields and those in ecology, agriculture, hydrology and geology.

Includes the theory of hyperspectral remote sensing, along with techniques and applications across a variety of disciplines Presents the processing, methods and techniques utilized for hyperspectral remote sensing and in-situ data collection Provides an overview of the state-of-the-art, including algorithms, techniques and case studies

Earth Observation Science (EOS) is the study of the global Earth land-ocean-atmosphere system through observations. The principal tools for such studies are measurements from space since these provide the coverage of the planet that is necessary to capture the behaviour of the entire coupled system. In addition, surface observations, and measurements from aircraft, balloons and sounding rockets provide valuable contributors to what are now termed "integrated, global observing systems.” Coupled with models, the EOS measurement suites provide powerful tools for research into the factors controlling and changing the Earth system in which we live. The objectives of this book are to describe new methods and applications of satellite technology in the fields of land and emergency monitoring. It draws on new research outcomes from the European FP7 project GIONET (European Centre of Excellence in Earth Observation Research Training). GIONET combines industrial partners with universities and research institutes, and this book provides a perspective on Earth Observation applications that is motivated by the cross-fertilisation of both sectors. Hence, this book will find readers in both industry and academia.This book highlights a broad range of innovative uses of Earth Observation technology to support environmental management, decision making, crisis management and climate policies. It uses advanced concepts of multi-sensor image integration, multi-temporal analysis and synergies between data and models. This is a truly interdisciplinary subject that encompasses a range of applications in various fields which are discussed in detail throughout the text. If you are interested in remote sensing applications and looking for inspiration, this is the book for you.

The Siberian environment is a unique region of the world that is both very strongly affected by global climate change and at the same time particularly vulnerable to its consequences. The news about the melting of sea ice in the Arctic Ocean and the prospect of an ice-free shipping passage from Scandinavia to Alaska along the Russian north coast has sparked an international debate about natural resource exploitation, national boundaries and the impacts of the rapid changes on people, animals and plants. Over the last decades Siberia has also witnessed severe forest fires to an extent that is hard to imagine in other parts of the world where the po- lation density is higher, the fire-prone ecosystems cover much smaller areas and the systems of fire control are better resourced. The acceleration of the fire regime poses the question of the future of the boreal forest in the taiga region. Vegetation models have already predicted a shift of vegetation zones to the north under s- narios of global climate change. The implications of a large-scale expansion of the grassland steppe ecosystems in the south of Siberia and a retreat of the taiga forest into the tundra systems that expand towards the Arctic Ocean would be very signi- cant for the local population and the economy. I have studied Russian forests from remote sensing and modelling for about 11 years now and still find it a fascinating subject to investigate.