Multi-source national forest inventory: methods and applications

Building on more than a decade of innovative research into multi-source forest inventory (MS-NFI) this book presents full details of the development, outputs and applications of the improved k-NN method. The method, which was pioneered in Finland in 1990, is rapidly becoming a world standard in forest inventory, having been adopted as standard in Finland and Sweden, and recently introduced in Austria and across the US. The book describes in detail the full MS-NFIprocess, and the input data used – including field data, satellite images, and digital map data, as well as coarse-scale variation of forest variables. It also presents comprehensive information on the types of outputs which can be derived, including maps and statistics, describing, for example, stock volumes and development, dominant tree species, age-class distribution, and large and small-scale variation. Includes fully updated details of the k-nn method and its applications Author (Erkki Tomppo) 1997 Marcus Wallenberg prize for the initial development of this method K-nn method in operative use in Finland, Sweden, US and Austria and rapidly becoming the ‘world standard’ in forest inventory and earth observation INDICE: List of abbreviations.- Preface.- 1. Introduction.- 2. Materials. 2.1 Field data. 2.2 Satellite images. 2.3 Digital map data. 2.4 Digital elevation model. 2.5 Large area forest resource data.- 3. Methods. 3.1 Image rectification and pre-processing of data. 3.2 Estimation.- 4. Results. 4.1 Forest resources by municipalities. 4.2 Comparison of the results by regions and to MS-NFI8 results. 4.3 Accuracy of small-area estimates from MS-NFI8 and MS-NFI9. 4.4 Digital thematic output maps.- 5. Discussion.- Acknowledgements.- References.- Appendix 1. Forest resource tables 1–8.- Appendix 2. Examples of forest resource maps.- Index.

• ISBN: 978-1-4020-8712-7
• Editorial: Springer
• Encuadernacion: Cartoné
• Páginas: 374
• Fecha Publicación: 01/10/2008
• Nº Volúmenes: 1
• Idioma: Inglés