“Tren Maya” Railway and its Home: An Analysis of the Land Change occurring in the Southern Yucatan
Organization: The Climate and Land Use Alliance: Overseen by Dr. Denise Humphreys-Bebbington
Project: Capstone for the Department of International Development and Independent Research Study: Mega Development in the Yucatán
Date:
Project: Capstone for the Department of International Development and Independent Research Study: Mega Development in the Yucatán
Date:
Background: Incorporated a portion of the analysis for my Advanced Raster course. My partner, Kyle Pecsok, and I created maps that simulated land change in the Yucatan Peninsula in Mexico. This was done in order to examine the impacts of a mega development project “Tren Maya” proposed by Mexico’s AMLO administration in 2018 plans to construct a 1,500 km railway connecting key points of the Yucatan Peninsula. This project focused primarily on the environmental impacts of the Tren Maya and agricultural clearing using TerrSet’s Land Change Modeler to predict deforestation trends in 2026 for the area. Using driver variables such as elevation, population density, the human influence index, and more this assessment predicted future trends of land use change and the potential for transition to artificial surfaces and cropland in 2026 based on land change patterns from 2010-2018. The area of focus in this study is the southern Yucatán peninsula in Mexico, which is the location for the Tren Maya Railway project. Two sites that this project will examine on a more in-depth level are both the Tren Maya route that runs through the Calakmul Biosphere Reserve and the Tren Maya station of Bacalar. Bacalar is an urban hot spot, with potential for growth in artificial/impervious surfaces. Located in the south-central part of the Yucatán Peninsula, Calakmul is the third largest biosphere in the world. It was established as a Natural Protected Area in 1989, as 90% of this area is federally owned and managed (Turner, 2004).
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Data:
Variable |
Source |
Year |
Description |
ESRI Climate Change Index Land Cover Data (Two Images) |
Clark Labs |
2010 and 2018 |
Land cover data of the southern Yucatán region. |
Population Density |
Clark Labs |
2013 |
Population density image. |
Elevation |
SRTM |
2000 |
Elevation raster |
Human Influence Index |
NASA SEDAC |
2004 |
Image of Human Influence based on the following factors: population density, human land use and infrastructure (built-up areas, nighttime lights, land use/land cover), and human access infrastructure systems. |
Protected Areas |
World Database on Protected Areas |
2010 |
Polygons of Protected Areas |
Distance to Primary Roads |
2016 |
Distance to roads classified as primary. |
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Distance to Railroads |
2016 |
Distance to railroads. |
Methods: Transition potential images in the Land Change Modeler (LCM) were created for each possible transition to either Artificial Surface/Urban Area land cover (infrastructure expansion) or Mostly Cropland (agricultural expansion) based on land cover change from 2010 to 2018. Transition potential images were not produced for transitions that consisted of one or no pixels. The transition potential images created for transitions to Mostly Cropland were from Grassland/Scrub/Shrub and Needleleaf/Evergreen Forest, and the ones created to Artificial Surface/Urban Area were from Mostly Cropland, Grassland/Scrub/Shrub, and Needleleaf/Evergreen Forest. A soft classification to 2026 was produced using the change allocation feature in the change prediction tab of LCM. While creating the 2026 land cover image we also created the potential for transition images for Cropland and Artificial Surface for 2026.
Outcome: When envisioning the current state of this ecosystem using the Land Change Modeler’s change analysis and prediction, evidence shows that the southern Yucatán region is highly vulnerable to perturbation. Perturbation refers to not only natural disturbances that occur as a result of forest succession, but to disturbances caused by humans (CICY, 2019). The “Tren Maya” project must include an official Environmental Impact Assessment in order to continue, because this forest ecosystem will have a more difficult time regenerating than other ecosystems. This paper emphasizes the current fragility of this study area and the possible repercussions of an area already impacted by climate change and disorganized infrastructure development. |
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