Open AccessConservation impacts of a near real‐time forest monitoring and alert system for the tropics
Author(s) -
Musinsky John,
Tabor Karyn,
Cano Carlos A.,
Ledezma Juan Carlos,
Mendoza Eddy,
Rasolohery Andriambolantsoa,
Sajudin Ermayanti R.
Publication year - 2018
Publication title -
remote sensing in ecology and conservation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.191
H-Index - 21
ISSN - 2056-3485
DOI - 10.1002/rse2.78
Subject(s) - deforestation (computer science) , environmental resource management , tropics , environmental monitoring , remote sensing , work (physics) , forest ecology , ecosystem , environmental protection , environmental science , geography , computer science , ecology , engineering , mechanical engineering , environmental engineering , biology , programming language
Near real‐time (NRT) forest monitoring and alert systems based on remotely sensed data are among the most recently developed tools to help manage and protect forest resources. The use of satellite and airborne remote sensing to quickly and accurately detect activities associated with deforestation has great potential for catalyzing local response teams responsible for assessing and interdicting threats to tropical forest ecosystems. To better understand the utility of NRT monitoring technologies in improving environmental protection and management, from 2008 to 2016 Conservation International conducted a series of surveys and interviews with users of these systems in four countries where wildfires threaten tropical forest ecosystems: Madagascar, Indonesia, Bolivia and Peru. Users reported that NRT forest monitoring systems made significant contributions to improving the ability of conservation and forest management organizations to respond to and reduce the impacts of fire, deforestation and other illegal or undesirable forest activity. Understanding the types of applications for which users successfully employed forest monitoring data, the challenges they faced in accessing, analyzing or disseminating these data, and the lessons learned from our attempts to develop and deploy NRT forest monitoring systems is useful to institutions interested in successfully incorporating NRT monitoring into their work.