Abstract
Satellite monitoring of forests plays a relevant role in the agendas of tropical countries, mainly in the framework of international negotiations to implement a mechanism that ensures a reduction in global CO2 emissions from deforestation. An efficient way to approach this monitoring is to avoid duplication of efforts, generating products in a regional context that are subsequently adopted at the national level. In this effort, you should take advantage of the different data sources available by integrating geospatial tools and satellite image classification algorithms. In this research, a methodological framework was developed to generate cost-efficient national maps of forest cover and its dynamics for the countries of Central America, and its scalability and replicability was explored in the Democratic Republic of the Congo (DRC) and the State of Pará in Brazil. The maps were generated from Landsat images from the years 2000, 2012, and 2017. New geoprocessing elements have been incorporated into the digital classification procedures for satellite images, such as the automated extraction of training samples from secondary sources, the use of official national reference maps that respond to nationally adopted forest definitions, and automation of post-classification adjustments incorporating expert criteria. The applied regional approach offers advantages in terms of reducing costs and time, as well as improving the consistency and coherence of reports at different territorial levels (regional and national), reducing duplication of efforts and optimizing technical and financial resources. In Central America, the percentage of forest area decreased from 44% in 2000 to 38% in 2017. Average deforestation in the 2000–2012 period was 197,443 ha/year and that of 2012–2017 was 332,243 ha/year. Average deforestation for the complete period 2000–2017 was 264,843 ha/year. The tropical forests in both the State of Pará, Brazil, and the DRC have decreased over time.
Highlights
Satellite monitoring, as a tool to support decision making aimed at halting forest destruction, has been prioritized in the last decade under the mechanism known by its initials REDD+
REDD+ is an initiative of the United Nations Framework Convention on Climate Change (UNFCCC) that requires the implementation of consistent, transparent, and robust national monitoring systems, maintaining a balance between the costs required for monitoring and the resources that are necessary to allocate for the execution of direct actions to reduce deforestation
Forest maps were generated considering the Central American region as a whole, with the expectation that later the regional classification will be adopted to the country level for multitemporal forest cover changes study
Summary
As a tool to support decision making aimed at halting forest destruction, has been prioritized in the last decade under the mechanism known by its initials REDD+ (reducing emissions from deforestation and forest degradation). One of the ways to reduce monitoring costs is to take advantage of the economy of scale to generate useful global or regional protocols and products at the national level. The objective of the research was to develop and apply a theoretical–methodological framework (as a technical input in the decision-making process to curb deforestation) in order to cost-efficiently prepare national cartography on forest cover, which is temporarily consistent, scalable at the supranational level for the Central American region, and applicable to other tropical regions. STEP (System for Terrestrial Ecosystem Parameterization), developed from the Global Observation for Forest Cover and Land Dynamics (GOFC/GOLD), was one of the first vegetation mapping experiences at a regional level in Central America with Advanced Very High Resolution Radiometer (AVHRR) images
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