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Computer Optics, 2017, Volume 41, Issue 4, Pages 552–558 (Mi co419)  

IMAGE PROCESSING, PATTERN RECOGNITION

Food vulnerability analysis in the central dry zone of Myanmar

M. Booriabc, K. Choudharya, R. A. Paringerda, M. Eversc

a Samara National Research University, Samara, Russia
b American Sentinel University, Denver, Colorado, USA
c Bonn University, Bonn, Germany
d Image Processing Systems Institute of the RAS - Branch of the FSRC "Crystallography and Photonics" RAS, Samara, Russia

Abstract: The central dry zone of Myanmar is the most water stressed and also one of the most food insecure regions in the country. In the Dry Zone, the total population is 10.1 million people in 54 townships, in which approximately 43 % of people live below the poverty line and 40–50 % of the rural population is landless. Agriculture is the most important economic sector in Myanmar as it is essential for the national food security and a major source of livelihood of the people. In this region the adverse effects of climate change such as a late or early onset of the monsoon season, longer dry spells, erratic rainfall, increasing temperatures, heavy rains, stronger typhoons, extreme spatial-temporal variability of rainfall, high intensities, limited rainfall events in the growing season, heat stress, drought, flooding, sea water intrusion, land degradation, desertification, deforestation, and other natural disasters are believed to be major constraints to food security. Theses extreme climatic events are likely to increase in frequency and magnitude, leading to serious drought periods and extreme floods. Food insecurity is an important thing that must be reviewed because it affects the lives of many people. For food vulnerability, we use the following indicators: slope, precipitation, vegetation, soil, erosion, land degradation and harvest failure in ArcGIS software. The erosion is influenced by rainfall and slope, while land degradation is directly related to vegetation, drainage and soil. In the meantime, the harvest failure can be generated by rainfall and flood potential zones. The results show that around 45 % of the area studied comes under a very high erosion danger level, 70 % are in the average harvest failure zone, 59 % are in the intermediate land degradation area, and overall around 45 % of the studied area comes under the insecure food vulnerability zone. Our analysis shows that an increase in the alluvial farming by 1745.33 km$^2$ since 1988 has helped reduce the insecure food vulnerability. The food vulnerability map is also relevant to increased population and low income areas. This paper is helpful for identifying the areas of food needs in central dry zone of Myanmar.

Keywords: food vulnerability, alluvial farming, remote sensing, GIS.

Funding Agency Grant Number
Russian Science Foundation 14-31-00014
This work was financially supported by the Russian Science Foundation (RSF), grant no. 14-31-00014 “Establishment of a Laboratory of Advanced Technology for Earth Remote Sensing”.


DOI: https://doi.org/10.18287/2412-6179-2017-41-4-552-558

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Received: 28.04.2017
Accepted:27.06.2017
Language:

Citation: M. Boori, K. Choudhary, R. A. Paringer, M. Evers, “Food vulnerability analysis in the central dry zone of Myanmar”, Computer Optics, 41:4 (2017), 552–558

Citation in format AMSBIB
\Bibitem{BooChoPar17}
\by M.~Boori, K.~Choudhary, R.~A.~Paringer, M.~Evers
\paper Food vulnerability analysis in the central dry zone of Myanmar
\jour Computer Optics
\yr 2017
\vol 41
\issue 4
\pages 552--558
\mathnet{http://mi.mathnet.ru/co419}
\crossref{https://doi.org/10.18287/2412-6179-2017-41-4-552-558}


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