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Presents papers from a forum on computer-assisted methods of forest interpretation and parameter extraction from high resolution digital imagery. Data sources of interest include airborne digital frame cameras, multi-spectral imagers, imaging spectrometers, digitized aerial photography, videography, and next-generation high resolution satellite imagery. The focus was on forestry requirements, current capabilities, and future activities. Papers are arranged under the following broad session topics: single tree isolation, regeneration & forest health, species classification, stand structure/crown closure & gaps, computer-assisted interpretation systems, and other applications.
Wildland fires are occurring more frequently and affecting more of Earth's surface than ever before. These fires affect the properties of soils and the processes by which they form, but the nature of these impacts has not been well understood. Given that healthy soil is necessary to sustain biodiversity, ecosystems and agriculture, the impact of fire on soil is a vital field of research. Fire Effects on Soil Properties brings together current research on the effects of fire on the physical, biological and chemical properties of soil. Written by over 60 international experts in the field, it includes examples from fire-prone areas across the world, dealing with ash, meso and macrofauna, smouldering fires, recurrent fires and management of fire-affected soils. It also describes current best practice methodologies for research and monitoring of fire effects and new methodologies for future research. This is the first time information on this topic has been presented in a single volume and the book will be an important reference for students, practitioners, managers and academics interested in the effects of fire on ecosystems, including soil scientists, geologists, forestry researchers and environmentalists.
Monitoring forest regrowth following major fires is important for understanding controls on forest regeneration and succession and detecting change in postfire plant communities. In this study we examined the extent to which forest regrowth following the 1988 Yellowstone National Park fires can be characterized by optical remote sensing data, and the spatial patterns associated with regrowth. Using a near-annual time series of Landsat satellite imagery, several satellite-based metrics were compared with field-based data of burn extent and post-fire stand structure and function. While there was little correlation between lodgepole pine density and our satellite metrics, single year regressions produced results over 80% and trend analysis of multiyear sites were able to explain 60 to 70% of the variability found between the ground collected data and the satellite metrics.
Covering recent developments in satellite observation data undertaken for monitoring forest areas from global to national levels, this book highlights operational tools and systems for monitoring forest ecosystems. It also tackles the technical issues surrounding the ability to produce accurate and consistent estimates of forest area changes, which are needed to report greenhouse gas emissions and removals from land use changes. Written by leading global experts in the field, this book offers a launch point for future advances in satellite-based monitoring of global forest resources. It gives readers a deeper understanding of monitoring methods and shows how state-of-art technologies may soon provide key data for creating more balanced policies.
Recently, growing interest in the use of remote sensing imagery has appeared to provide synoptic maps of water quality parameters in coastal and inner water ecosystems;, monitoring of complex land ecosystems for biodiversity conservation; precision agriculture for the management of soils, crops, and pests; urban planning; disaster monitoring, etc. However, for these maps to achieve their full potential, it is important to engage in periodic monitoring and analysis of multi-temporal changes. In this context, very high resolution (VHR) satellite-based optical, infrared, and radar imaging instruments provide reliable information to implement spatially-based conservation actions. Moreover, they enable observations of parameters of our environment at greater broader spatial and finer temporal scales than those allowed through field observation alone. In this sense, recent very high resolution satellite technologies and image processing algorithms present the opportunity to develop quantitative techniques that have the potential to improve upon traditional techniques in terms of cost, mapping fidelity, and objectivity. Typical applications include multi-temporal classification, recognition and tracking of specific patterns, multisensor data fusion, analysis of land/marine ecosystem processes and environment monitoring, etc. This book aims to collect new developments, methodologies, and applications of very high resolution satellite data for remote sensing. The works selected provide to the research community the most recent advances on all aspects of VHR satellite remote sensing.
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.