Inventory Techniques in Participatory Forest Management

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Abstract

This chapter describes the classic techniques for sampling static populations (i.e., sampling by means of surveys, plots, or trees). It discusses information technologies such as geographic information system and remote sensing, and examines the main algorithms for spatial interpolation of data. The chapter explores the foundations of remote sensing and its potentialities for capturing and generating spatial information. It pays special attention to object-based image classifications and light detection and ranging (LiDAR) data and their applications in forest management. The aim of the current work is twofold: to map homogeneous forest areas for forest management purposes in the mountain area of the Madrid region using LiDAR data and to evaluate the role of forest expert opinion in this mapping process. For the manual approach, forestry experts visually inspected the manually delineated polygons and assigned each one into a forest structure class.

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Pascual, C., Mauro, F., Hernando, A., & Martín-Fernández, S. (2016). Inventory Techniques in Participatory Forest Management. In Quantitative Techniques in Participatory Forest Management (pp. 53–134). CRC Press. https://doi.org/10.1201/b15366-2

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