Population Estimation Using Geographic Information System and Remote Sensing for Unorganized Areas
Population estimation using remotely sensed data has been largely discussed in the literature relative to human geography. However, the previously established models can be applied on organized areas (mainly urban areas) but they are not suitable for unorganized areas which already suffer from a lac...
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Diponegoro University
2020-11-01
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Series: | Geoplanning: Journal of Geomatics and Planning |
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Online Access: | https://ejournal.undip.ac.id/index.php/geoplanning/article/view/26600 |
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doaj-1ea5bf524bf7444998363fa1e90dbaa52021-03-12T09:12:36ZengDiponegoro UniversityGeoplanning: Journal of Geomatics and Planning2355-65442020-11-0172758610.14710/geoplanning.7.2.75-8617875Population Estimation Using Geographic Information System and Remote Sensing for Unorganized AreasKamel Allaw0Jocelyne Adjizian Gerard1Makram Zouheir Chehayeb2Nada Badaro Saliba3Abbas Rammal4Zainab Jaber5Islamic University of Lebanon Saint Joseph UniversitySaint Joseph UniversityLebanese UniversitySaint Joseph UniversityIslamic University of Lebanon Saint Joseph UniversityIslamic University of Lebanon Saint Joseph UniversityPopulation estimation using remotely sensed data has been largely discussed in the literature relative to human geography. However, the previously established models can be applied on organized areas (mainly urban areas) but they are not suitable for unorganized areas which already suffer from a lack of population data. So, the aim of this study is the establish a statistical model for population estimation based on remote sensing data and suitable for unorganized areas. To do so, the morphological characteristics have been studied and a bivariate analysis was carried out to determine factors having a strong relationship with population data as a first step. Second, factors with strongest correlations have been chosen to establish the required model. As a result, an equation has been generated which relates the population data to building volume, density of roads, number of nodes, actual urban areas, and urban trend.https://ejournal.undip.ac.id/index.php/geoplanning/article/view/26600population estimationremote sensinggisunorganized areaslebanon |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Kamel Allaw Jocelyne Adjizian Gerard Makram Zouheir Chehayeb Nada Badaro Saliba Abbas Rammal Zainab Jaber |
spellingShingle |
Kamel Allaw Jocelyne Adjizian Gerard Makram Zouheir Chehayeb Nada Badaro Saliba Abbas Rammal Zainab Jaber Population Estimation Using Geographic Information System and Remote Sensing for Unorganized Areas Geoplanning: Journal of Geomatics and Planning population estimation remote sensing gis unorganized areas lebanon |
author_facet |
Kamel Allaw Jocelyne Adjizian Gerard Makram Zouheir Chehayeb Nada Badaro Saliba Abbas Rammal Zainab Jaber |
author_sort |
Kamel Allaw |
title |
Population Estimation Using Geographic Information System and Remote Sensing for Unorganized Areas |
title_short |
Population Estimation Using Geographic Information System and Remote Sensing for Unorganized Areas |
title_full |
Population Estimation Using Geographic Information System and Remote Sensing for Unorganized Areas |
title_fullStr |
Population Estimation Using Geographic Information System and Remote Sensing for Unorganized Areas |
title_full_unstemmed |
Population Estimation Using Geographic Information System and Remote Sensing for Unorganized Areas |
title_sort |
population estimation using geographic information system and remote sensing for unorganized areas |
publisher |
Diponegoro University |
series |
Geoplanning: Journal of Geomatics and Planning |
issn |
2355-6544 |
publishDate |
2020-11-01 |
description |
Population estimation using remotely sensed data has been largely discussed in the literature relative to human geography. However, the previously established models can be applied on organized areas (mainly urban areas) but they are not suitable for unorganized areas which already suffer from a lack of population data. So, the aim of this study is the establish a statistical model for population estimation based on remote sensing data and suitable for unorganized areas. To do so, the morphological characteristics have been studied and a bivariate analysis was carried out to determine factors having a strong relationship with population data as a first step. Second, factors with strongest correlations have been chosen to establish the required model. As a result, an equation has been generated which relates the population data to building volume, density of roads, number of nodes, actual urban areas, and urban trend. |
topic |
population estimation remote sensing gis unorganized areas lebanon |
url |
https://ejournal.undip.ac.id/index.php/geoplanning/article/view/26600 |
work_keys_str_mv |
AT kamelallaw populationestimationusinggeographicinformationsystemandremotesensingforunorganizedareas AT jocelyneadjiziangerard populationestimationusinggeographicinformationsystemandremotesensingforunorganizedareas AT makramzouheirchehayeb populationestimationusinggeographicinformationsystemandremotesensingforunorganizedareas AT nadabadarosaliba populationestimationusinggeographicinformationsystemandremotesensingforunorganizedareas AT abbasrammal populationestimationusinggeographicinformationsystemandremotesensingforunorganizedareas AT zainabjaber populationestimationusinggeographicinformationsystemandremotesensingforunorganizedareas |
_version_ |
1724223023675867136 |