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Monitoring Approach for Tropical Coniferous Forest Degradation Using Remote Sensing and Field Data
 
 
Article

Integration of Geospatial Tools and Multi-source Geospatial Data to Evaluate the Tropical Forest Cover Change in Central America and Its Methodological Replicability in Brazil and the DRC

1
Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH, San Salvador 1101, El Salvador
2
Wildland Resources Department, Utah State University, Logan, UT 84322-5230, USA
3
Department of Geology, Geography and Environment, University of Alcalá, 28801 Alcalá de Henares, Spain
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(17), 2705; https://doi.org/10.3390/rs12172705
Received: 28 June 2020 / Revised: 3 August 2020 / Accepted: 6 August 2020 / Published: 21 August 2020
(This article belongs to the Special Issue Forest Degradation Monitoring)
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. View Full-Text
Keywords: tropical forest; forest cover dynamics; deforestation; remote sensing tropical forest; forest cover dynamics; deforestation; remote sensing
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MDPI and ACS Style

Jiménez, A.; Hernández, A.J.; Rodríguez-Espinosa, V.M. Integration of Geospatial Tools and Multi-source Geospatial Data to Evaluate the Tropical Forest Cover Change in Central America and Its Methodological Replicability in Brazil and the DRC. Remote Sens. 2020, 12, 2705. https://doi.org/10.3390/rs12172705

AMA Style

Jiménez A, Hernández AJ, Rodríguez-Espinosa VM. Integration of Geospatial Tools and Multi-source Geospatial Data to Evaluate the Tropical Forest Cover Change in Central America and Its Methodological Replicability in Brazil and the DRC. Remote Sensing. 2020; 12(17):2705. https://doi.org/10.3390/rs12172705

Chicago/Turabian Style

Jiménez, Abner, Alexander J. Hernández, and Víctor M Rodríguez-Espinosa. 2020. "Integration of Geospatial Tools and Multi-source Geospatial Data to Evaluate the Tropical Forest Cover Change in Central America and Its Methodological Replicability in Brazil and the DRC" Remote Sensing 12, no. 17: 2705. https://doi.org/10.3390/rs12172705

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