Name: Highlights of Satellite-Based Forest Change Recognition and Tracking Using the ForWarn System (en Inglés)
Price: 24.23 USD
Availability: InStock
Author: United States Department of Agriculture
ISBN: 9781508580874

portada Highlights of Satellite-Based Forest Change Recognition and Tracking Using the ForWarn System (en Inglés)

Formato

Libro Físico

Editorial

Createspace Independent Publishing Platform

Autor

United States Department of Agriculture

Idioma

Inglés

N° páginas

Encuadernación

Tapa Blanda

Dimensiones

28.0 x 21.6 x 0.2 cm

Peso

0.11 kg.

ISBN13

9781508580874

Categorías

Bibliografias

Highlights of Satellite-Based Forest Change Recognition and Tracking Using the ForWarn System (en Inglés)

United States Department Of Agriculture (Autor) · Createspace Independent Publishing Platform · Tapa Blanda

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Reseña del libro "Highlights of Satellite-Based Forest Change Recognition and Tracking Using the ForWarn System (en Inglés)"

Satellite-based remote sensing can assist forest managers with their need to recognize disturbances and track recovery. Despite the long standing availability of raw imagery, the systematic delivery of spatially continuous, ready-to-use, processed products has evaded us until recently. The web-based ForWarn system moves us a step forward by generating forest change maps at high frequency in a format that is usable to forest managers, planners, and the public. The ForWarn system shows change in the Normalized Difference Vegetation Index derived from moderate resolution imagery according to a range of baseline normals. Expectations of normal derive from previously observed changes in seasonal leaf phenology; this adjustment is critical for forests dominated by deciduous vegetation that vary in greenness through the year. After these seasonal adjustments are made behind the scene, the remaining forest change that ForWarn users see may result from an array of climatic and disturbance causes. These include insects and disease, wildland fire, wind, hail, human development, drought, or variation in the timing of spring and fall. This publication outlines the data and methods that underlie this technology, and provides examples that illustrate selected capabilities of this system for coarse-scale forest monitoring.