Population Estimation in an Urban Area with Remote Sensing and Geographical Information Systems

Abstract

Population estimation with questionnaires and demographic models is time consuming and usually accompanied by high costs. Geoinformation tools constitute key tools towards the solution of this problem, and, therefore, studies have started to emerge in the early 70s. In this paper a brief reference to the methods of population estimation, which are based totally or in combination with statistical analysis methods on products of Remote Sensing and their processing with GIS is cited. Afterwards, the capability of stereoscopic satellite images of high spatial resolution for the determining of the height of buildings and the performance of their plans, which are essential data for the estimation of the population of each building is highlighted. The study area is the municipality of Thessaloniki (Northern Greece, Region of Central Macedonia), and the estimation accuracy of the population reaches 97.06%.

Population Estimation Using Land-Use Change Data from Multi-Sensor Images in Maha Sarakham Province, Thailand

“…The use of significantly high-spatial resolution imagery considerably improved the accuracy of the estimates (Alahmadi et al, 2013, Dong et al, 2010, Guo et al, 2017and Mossoux et al, 2018. The estimated population of the built-up area type, identified using the VII method, was in good agreement with the actual population (Kaimaris and Patias, 2016). This result was verified and coincides with the results of previous studies (Guo et al, 2017 andSaberifar, 2013).…”

“…A similar area-based approach was also found to be effective for population estimation in a complex land-use area around the university of the Philippines (Galeon, 2008). Some limitations concerning the use of land-use maps to estimate population were identified, which led to inaccuracies in the estimated population (Galeon, 2008, Kaimaris and Patias, 2016and Deng et al, 2010. In contrast, aerial remote sensing data (i.e., UAV images) provided high-quality land information for the visual interpretation of built-up structures in this study.…”