Image from TERRA
Mon, 30 Oct 2017 12:25 EDT

Former Tropical Storm Saola transitioned into an extra-tropical storm on Oct. 29 as it tracked southeast of the big island of Japan.

Image from TERRA
Tue, 24 Oct 2017 11:36 EDT

When Typhoon Lan made landfall in Japan on Oct. 22, the Global Precipitation Measurement mission core satellite or GPM analyzed the storm and added up the high rainfall that it generated.

Image from TERRA
Tue, 24 Oct 2017 09:22 EDT

A new image from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument on NASA's Terra satellite shows the growing fire scar on the landscape.

Terra Data Used to Understand Risk Factors for Rift Valley Fever

Reported Rift Valley fever (RVF) case locations in relation to Land Use/Land Cover. Image courtesy of: Margaret M. Glancey, et al., 2015; Published by Mary Ann Liebert, Inc.

Reported Rift Valley fever (RVF) case locations in relation to Land Use/Land Cover. Image courtesy of: Margaret M. Glancey, et al., 2015; Published by Mary Ann Liebert, Inc.

Moderate Imaging Spectroradiometer (MODIS) data in the Normalized Difference Vegetation Index (NDVI), an index that shows plants “greenness” or photosynthetic activity, is helping better understand risk factors associated with Rift Valley Fever outbreaks in Southern Africa.

A recent study published in the National Center for Biotechnology Information’s Pub Med looked at epidemiological and environmental risk factors from 2008 – 2011, the worst outbreak of Rift Valley fever in almost 40 years.

Periods of widespread and above-normal rainfall are associated with Rift Valley Fever outbreaks. Researchers combined data from the World Animal Health Information Database (WAHID) on what types of species were affected, where and when with environmental factors including rainfall and NDVI.

The results of the study show that these environmental factors along with geographic factors (topography, drainage, and land use) do play a role in the emergence of Rift Valley Fever.

This study will help the accuracy of future models of areas at risk, allowing more time to adequately prepare and prevent future outbreaks.

Read the full article at http://www.ncbi.nlm.nih.gov/pubmed/26273812

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