INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15
Study of Poverty Prediction using Remote Sensing Data
Authors Name:
Rekha S. Thorat
, Dr. Praveen Shetiye , Dr. Avinash K. Gulve
Unique Id:
IJSDR1907057
Published In:
Volume 4 Issue 7, July-2019
Abstract:
In this paper, a study on poverty prediction using remote sensing data is done. Remote sensing method of prediction poverty is an efficient method in terms of time consumption, cost, and effort required than the household survey method. For this approach various machine learning methods like classification, regression, clustering and dimension reduction are used to train the model. In the training phase, household survey data is used. This GDP, school enrollment, CO2 emissions, poverty headcount ratio, life expectancy at birth, GNI per capita and census data is made freely available for research purpose by World Bank Group in the form of statistics, and DHS (demographic health survey) data is available on DHS program’s site. Satellite daytime and nighttime data can be taken from public and private domains of the satellite. After data collection and execution of model with machine learning methods, various results are computed with different and maximum accuracy.
Keywords:
Remote sensing data, Machine Learning, DHS data.
Cite Article:
"Study of Poverty Prediction using Remote Sensing Data", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.4, Issue 7, page no.338 - 341, July-2019, Available :http://www.ijsdr.org/papers/IJSDR1907057.pdf
Downloads:
000337353
Publication Details:
Published Paper ID: IJSDR1907057
Registration ID:190818
Published In: Volume 4 Issue 7, July-2019
DOI (Digital Object Identifier):
Page No: 338 - 341
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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