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This book demonstrates the measurement, monitoring, mapping, and modeling of forest resources. It explores state-of-the-art techniques based on open-source software & R statistical programming and modeling specifically, with a focus on the recent trends in data mining/machine learning techniques and robust modeling in forest resources. Discusses major topics such as forest health assessment, estimating forest biomass & carbon stock, land use forest cover (LUFC), dynamic vegetation modeling (DVM) approaches, forest-based rural livelihood, habitat suitability analysis, biodiversity and ecology, and biodiversity, the book presents novel advances and applications of RS-GIS and R in a precise and clear manner. By offering insights into various concepts and their importance for real-world applications, it equips researchers, professionals, and policy-makers with the knowledge and skills to tackle a wide range of issues related to geographic data, including those with scientific, societal, and environmental implications.
The rapidly increasing global population has dramatically increased the demands for natural resources and has caused significant changes in quantity and quality of natural resources. To achieve sustainable resource management, it is essential to obtain insightful guidance from emerging disciplines such as landscape ecology. This text addresses the links between landscape ecology and natural resource management. These links are discussed in the context of various landscape types, a diverse set of resources and a wide range of management issues. A large number of landscape ecology concepts, principles and methods are introduced. Critical reviews of past management practices and a number of case studies are presented. This text provides many guidelines for managing natural resources from a landscape perspective and offers useful suggestions for landscape ecologists to carry out research relevant to natural resource management. In addition, it will be an ideal supplemental text for graduate and advanced undergraduate ecology courses.
Remote sensing and GIS are increasingly used as tools for monitoring and managing forests. Remotely sensed and GIS data are now the data sources of choice for capturing, documenting, and understanding forest disturbance and landscape pattern. Sitting astride the fields of ecology, forestry, and remote sensing/GIS, Understanding Forest Disturbanc
A selection of annotated references to unclassified reports and journal articles that were introduced into the NASA scientific and technical information system and announced in Scientific and technical aerospace reports (STAR) and International Aerospace Abstracts (IAA).