Image from TERRA
Wed, 28 Nov 2018 13:49 EST

Central Africa is still on fire a month after the October 30 image of the fire was posted. Most likely these fires are agricultural in nature.

Image from TERRA
Tue, 27 Nov 2018 10:47 EST

Just like the Woolsey Fire's scar which was highlighted on the NASA Fire page on November 16, the Camp Fire scar is visible from space in this image taken by the Terra satellite on November 26, 2018.

Image from TERRA
Thu, 15 Nov 2018 11:55 EST

In the wake of a fire, a burn scar appears which takes a long time to heal. This scar is from the Woolsey fire which has taken its toll around Thousand Oaks, California.

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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