There‰Ûªs Not a Lot of Ocelots: The Search for an Endangered Feline

EarthzineDetecting Habitat Conservation and Species Distribution, DEVELOP 2015 Summer VPS, DEVELOP Virtual Poster Session

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The Normalized Difference in Vegetation Index (NDVI), which indicates varietals in vegetation, aided in the finding of suitable ocelot habitat. Image Credit: Texas and Arizona Ecological Forecasting Team

The Normalized Difference in Vegetation Index (NDVI), which indicates varietals in vegetation, aided in the finding of suitable ocelot habitat. Image Credit: Texas and Arizona Ecological Forecasting Team

Category:åÊDetecting Habitat Conservation and Species Distribution

Project Team: Texas and Arizona Ecological Forecasting

Team Location: NASA Marshall Space Flight Center – Huntsville, Alabama

Authors:

Daryl Ann Winstead

Kaushik Narasimhan

Christina Fischer

Amberle Keith

Mentors/Advisors:

Dr. Jeffrey Luvall (NASA MSFC at the National Space Science Technology Center)

Dr. Robert Griffin (University of Alabama in Huntsville)

Abstract:

Although ocelot (Leopardus pardalis) habitat is found throughout Central America, portions of South America, and the United States, the species is currently listed as endangered with less than 100 remaining in the United States. This cat requires a minimum home range of 6.5 square kilometers, which aids in deadly interactions with humans on roadways. Many conservation efforts have been attempted, from ocelot translocation to habitat restoration. In this project, a remote sensing approach was developed, using NASA Earth-observing sensors. Landsat 8 Operational Land Imager (OLI) and Landsat 5 Thematic Mapper (TM) imagery were used to create supervised land cover classifications for 1996, 2005, and 2014 from January through March to assess land use and cover over time. Surface reflectance imagery from Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) were then used to derive Normalized Difference Vegetation Index (NDVI) values to verify the results from the land cover classification layer. The verified land cover classification was then used with in-situ data in the Princeton Maximum Entropy model to identify suitable ocelot habitat. A proximity risk map to roads and urban areas was created using multiband buffer zones over this habitat. The products were delivered to the Pittsburgh Zoo & PPG Aquarium, Caesar Kleberg Wildlife Research Institute, Denver Zoo, Texas Department of Transportation, South Texas Refuge Complex, and the SecretarÌ_a de Medio Ambiente y Rescursos Naturales (SEMARNAT) of Mexico. The use of Geographic Information Systems (GIS) and remote sensing will greatly aid the project partner‰Ûªs decision-making process in directing conservation efforts for this endangered species.

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