El Salvador Ecological Forecasting - NASA DEVELOP Fall 2015 @ Langley Research Center - Lake Harding Association

El Salvador Ecological Forecasting – NASA DEVELOP Fall 2015 @ Langley Research Center

El Salvador Ecological Forecasting – NASA DEVELOP Fall 2015 @ Langley Research Center

By Micah Moen 0 Comment March 25, 2020


>>Stephen Zimmerman: A mountainous tropical
forest region in Northern El Salvador, La Mancomunidad La Montañona, Chalatenango has
been experiencing forest degradation and deforestation for many years. This region is home to many
small scale subsistence farmers whose main crops include corn, rice, beans, and sorghum.
The old growth forests, known as primary forests of La Montañona, are pine-oak dominant and
were subject to low levels of slash and burn agriculture for many years before the outbreak
of civil war in 1979. As people fled the conflict, secondary forests dominated by broadleaf oaks,
were given a chance to regrow until peace settled over the region in 1992. As farmers
and community members began immigrating back to El Salvador.>>Courtney Duquette: The forests of the La
Mancomunidad La Montañona are crucial to the health of this region. These forests remove
carbon from the atmosphere, filter rivers and streams that locals use for their only
water source, and provide soil stability to the more mountainous regions.>>Stephen Zimmerman: In collaboration with
the Earth Institute at Columbia University ABES Project, the DEVELOP Fall 2015 El Salvador
Ecological Forecasting team has set out to make a Land Use/Land Cover map and a forecast
model using TerrSet Land Change Modeler that will allow the community in La Mancomunidad
La Montañona and the project end-users, MARN, to monitor the condition of their forests,
anticipate changes, and mitigate potential issues.>>Jordan Ped: To accomplish these tasks, a
combination of Landsat CDR 4 and 5 TM and Landsat CDR 8 OLI were obtained from USGS
for the years 1986 through 2014. Additional data was provided by our partners including
higher resolution imagery from Rapid Eye and QuickBird Satellites and field surveys of
small plots throughout the area. Beginning by identifying the most critical land cover
and land use types in the region, and using the most recent landsat image from 2014, ‘training
sites’ were created for each land cover type. ArcGIS and Earth Engine were used to
test multiple supervised classification methods. The results aren’t always very accurate
the first time in any classification. This is partially a result of simplifying complicated
land use patterns into a limited number of categories. And so the 2014 training sites
were refined using plot data and high resolution imagery to create the most accurate classification
possible. The classifications from 1986 and 2014 were
used as the baseline inputs for the development of a forecast model over the longest historical
time period available.>>Susannah Miller: Using a more accurate classification
created with high resolution RapidEye to validate our classifications, a percent similar statistic
comparing land classes on a pixel-by-pixel scale was calculated. A more robust accuracy
assessment was performed using ABES plot level data for forest, crop, and pasture. This ground
truth combined with 60 randomly selected points from the urban and water classes were compared
to ArcGIS Maximum Likelihood Classification. The overall accuracy was determined to be
60.1%. This is not the land use or land cover we expected to see in La Mancomunidad La Montañona
in 2030. With further refinement of training sites and better change variables the model
could be greatly improved during the spring 2016 term.>>Courtney Duquette: Determining the most
accurate classification algorithm will help to build a baseline for future classifications,
allowing for long term monitoring of the region and throughout El Salvador. The future of
the forests of La Mancomunidad La Montañona depend on the decisions being made today.
This project will help MARN build a better understanding of the current trends. Information
can be passed all the way down to the subsistence farming level and help safeguard forests,
agricultural traditions, and the livelihoods in La Mancomunidad La Montañona.

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