Evidence map›Paper›PMID 33242161›Full record

ArticleEnvironmental monitoring and assessment2020

Determination of the nighttime light imagery for urban city population using DMSP-OLS methods in Istanbul.

Zeynep Ortakavak, Saye Nihan Çabuk, Mehmet Cetin, Muzeyyen Anil Senyel Kurkcuoglu, Alper Cabuk

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Article in Environmental monitoring and assessment, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
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4citing papers in PubMed
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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

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3 · Its place in the literature

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4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Zeynep OrtakavakInstitute of Social Sciences, Anadolu University, Eskisehir, Turkey.
Saye Nihan ÇabukInstitute of Earth and Space Sciences, Eskisehir Technical University, Eskisehir, Turkey.
Mehmet CetinFaculty of Engineering and Architecture, Kastamonu University, Kastamonu, Turkey. mcetin@kastamonu.edu.tr.
Muzeyyen Anil Senyel KurkcuogluFaculty of Architecture, Middle East Technical University, Ankara, Turkey.
Alper CabukFaculty of Architecture and Design, Eskisehir Technical University, Eskisehir, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Demography researchers and scientists have been effectively utilizing advanced technologies and methods such as geographical information systems, spatial statistics, georeferenced data, and satellite images for the last 25 years. Areal interpolation methods have also been adopted for the development of population density maps which are essential for a variety of social and environmental studies. Still, a good number of social scientists are skeptical about such technologies due to the complexity of methods and analyses. In this regard, a practical intelligent dasymetric mapping (IDM) tool that facilitates the implementation of the statistical analyses was used in this study to develop the population distribution map for the Istanbul metropolitan area via night light data provided by the Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS) and the census records of the study area. A population density map was also produced using the choropleth mapping method to enable to make a comparison of the traditional and intelligent population density mapping implementations. According to the dasymetric population density map, 38.5% of the study area fell into sparse density category while low, moderate, high, and very high population density class percentages were found to be 9.4%, 5.5%, 2.9%, and 0.1% respectively. On the other hand, the percentages of the same population density classes ranking from sparse to very high in the choropleth map were determined to be 90.7%, 7.3%, 1.7%, 0.3%, and 0%. In the change analysis made as a result of the classification, the changes between the city area and the population were revealed. During this period, the city area and population grew. Spatial change has also been interpreted by comparing it with population changes. There appears to be a remarkable increase in both surface area and population. It is observed that the increase is especially in the south and northwest of the city. With the population increase, the number of new residential areas has increased. It is thought that behind this growth, there are different reasons besides the effect of the increase in residential areas. When the environmental awareness of people has increased more than in the past centuries, new solutions should be produced in order to be more controlled, smart, and sustainable while planning the cities of the future. Considering that the development of technology and remote sensing techniques is progressing in parallel with this technology, this study in which GIS technologies integrated with satellite images are used, it is thought that it will contribute positively to the studies in this area in terms of regular development of urban areas, increasing the opportunity to make fast and correct decisions, and creating infrastructure for studies such as monitoring and prevention of illegal housing.

Indexed as

Environmental MonitoringGeographic Information SystemsCitiesGeographic MappingHumansUrban PopulationAreal interpolationIntelligent dasymetric mapping (IDM)Night light dataPopulation density

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.