The Time to Act is Now! Forecasting Change in El Salvador‰Ûªs Pine-Oak Forests

EarthzineDEVELOP 2015 Fall VPS, DEVELOP Virtual Poster Session, Monitoring Change for Resource Management, Original

The results of an ArcGIS maximum likelihood classification; a Land Use Land Cover (LULC) map of La Moncomunidad La Monta̱ona with five classes: Water, Urban, Pasture, Forest, and Crop. Image Credit: El Salvador Ecological Forecasting Team

The results of an ArcGIS maximum likelihood classification; a Land Use Land Cover (LULC) map of La Moncomunidad La Monta̱ona with five classes: Water, Urban, Pasture, Forest, and Crop. Image Credit: El Salvador Ecological Forecasting Team

This is a part of the 2015 Fall VPS. For more VPS articles, click here

Category:åÊMonitoring Change for Resource Management

Project Team: El Salvador Ecological Forecasting

Team Location: NASA Langley Research Center ‰ÛÒ Hampton, Virginia

Authors:

Jordan Ped (Project Lead)

Courtney Duquette

Clarence Kimbrell

Susannah Miller

Stephen Zimmerman

Mentors/Advisors:

Dr. Kenton Ross (NASA DEVELOP National Program)

Abstract:

Tropical rainforests have been recognized as a major contributor to maintaining the global carbon budget and contain a significant portion of the world’s biodiversity. However, these ecosystems are threatened by deforestation and forest degradation and require careful management to retain their ecosystem services. La Mancomunidad La Monta̱ona in Chalatenango, El Salvador is home to the critical Rio Lempa watershed where small scale farmers and pastoralists commonly practice slash and burn agriculture. Using NASA Earth observations in collaboration with Ministerio de Medio Ambiente y Recursos Naturales (MARN) and the Earth Institute of Columbia University, Agroforestry for Biodiversity and Ecosystem Services (ABES) Project, a methodology was developed for stakeholders and policymakers to monitor long-term changes in forest cover and identify indicators of forest degradation. A baseline time series showing forest cover and land use/land cover from December 1986 to January 2015 was used to forecast forest cover change. These predictions and tools will help assess priority areas for conservation and development of sustainable agricultural practices.

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