Remote Sensing Tools for Monitoring Forests and Tracking Their Dynamics

Abstract Remote sensing augments field data and facilitates foresight required for forest management by providing spatial temporal observations of characteristics at landscape regional scales. Statistical machine-learning models derived from plot-level can be extrapolated to larger areas using remote data. For example, instruments such as light detection ranging (LiDAR) hyperspectral sensors are frequently used quantify the stand level. Moreover, multispectral imagery synthetic aperture radar (SAR) sets satellite platforms extrapolate resource large regions. The combination novel technologies, expanding computing capabilities, emerging geospatial methods ensures a data-rich environment effective strategic, tactical, operational planning monitoring in management.