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...

Full description

Bibliographic Details
Main Authors: Kamel Allaw, Jocelyne Adjizian Gerard, Makram Zouheir Chehayeb, Nada Badaro Saliba, Abbas Rammal, Zainab Jaber
Format: Article
Language:English
Published: Diponegoro University 2020-11-01
Series:Geoplanning: Journal of Geomatics and Planning
Subjects:
gis
Online Access:https://ejournal.undip.ac.id/index.php/geoplanning/article/view/26600
id doaj-1ea5bf524bf7444998363fa1e90dbaa5
record_format Article
spelling 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