Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 29978
A Remote Sensing Approach to Calculate Population Using Roads Network Data in Lebanon

Authors: Kamel Allaw, Jocelyne Adjizian Gerard, Makram Chehayeb, Nada Badaro Saliba

Abstract:

In developing countries, such as Lebanon, the demographic data are hardly available due to the absence of the mechanization of population system. The aim of this study is to evaluate, using only remote sensing data, the correlations between the number of population and the characteristics of roads network (length of primary roads, length of secondary roads, total length of roads, density and percentage of roads and the number of intersections). In order to find the influence of the different factors on the demographic data, we studied the degree of correlation between each factor and the number of population. The results of this study have shown a strong correlation between the number of population and the density of roads and the number of intersections.

Keywords: Population, road network, statistical correlations, remote sensing.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF

References:


[1] Liu, X., and K. C. Clarke, 2002, "Estimation of residential population using high resolution satellite imagery." Proceedings of the 3rd Symposium on Remote Sensing of Urban Areas.
[2] Anderson, D., and Anderson, P., 1973. Population estimates by humans and machines. Photogrammetric Engineering, 39, 147–154.
[3] Stewart, Wartnz J. Q and W., 1958, “Physics of Population Distribution,” Journal of Regional Science, 1:99-113.
[4] Clark, C., 1951, “Urban Population Densities,” Journal of the Royal Statistical Society, 114:490-496.
[5] Sutton, P., 1997. Modeling population density with night-time satellite imagery and GIS, Computing, Environment and Urban Systems, 21:227–244.
[6] Parr, J. B., 1985, “A Population-Density Approach to Regional Spatial Structure,” Urban Studies, 22(4):289-303.
[7] Weiss, H. K., 1961, “The Distribution of Urban Population and an Application to a Servicing Problem,” Operations Research, 9(6):860-874.
[8] Newling, B. E., 1965, “Urban Growth and Spatial Structure—Mathematical Models and Empirical Evidence,” Annals of the Association of American Geographers,55(4):637-637.
[9] Lam, N. S., 1983, “Spatial Interpolation Methods: A Review,” The American Cartographer, 10(2):129-149.
[10] Eicher, C. L. and C. A. Brewer, 2001, “Dasymetric Mapping and Areal Interpolation: Implementation and Evaluation,” Cartography and Geographic Information Science, 28(2): 125-138.
[11] Sutton, P., D. Roberts, C. Elvidge, and K. Baugh, 2001. Census from heaven: an estimate of the global human population using night-time satellite imagery. International Journal of Remote Sensing, 1-16, Preview article.
[12] Kraus, S. P., Senger, L. W. and J. M. Ryerson, 1974, “Estimating Population from Photographically Determined Residential Land Use Types,” Remote Sensing of Environment, 3(1):35-42.
[13] Clayton, C. and Estes J., 1980, “Image Analysis as a Check on Census Enumeration Accuracy” Photogrammetric Engineering and Remote Sensing, 46:757-764.
[14] Batty, M. and Longley P., 1994, Fractal Cities: A Geometry of Form and Function, London, UK/San Diego, CA: Academic Press, 394 p.
[15] Lo, C. P. and Welch R., 1977, “Chinese Urban Population Estimates,” Annals of the Association of American Geographers, 67(2):246-253.
[16] Lee, Y., 1989, An Allometric Analysis of the United States Urban System: 1960-80, Environment and Planning A, 21(4):463-476.
[17] Weber, C., 1994, “Per-zone Classification of Urban Land Use Cover for Urban Population estimation,” in Environmental Remote Sensing from Regional to Global
[18] Green, N. E., 1956, “Aerial Photographic Analysis of Residential Neighborhoods: An Evaluation of Data Accuracy,” Social Forces, 35:142-147.
[19] Porter, P. W., 1956, Population Distribution and Land Use in Liberia, Ph.D. thesis, London School of Economics and Political Science, London, UK, 213 p.
[20] Hsu, S. Y., 1971, “Population Estimation,” Photogrammetric Engineering, 37:449-454.
[21] Lo, C. P. and H. F. Chan, 1980, “Rural Population Estimation from Aerial Photographs,” Photogrammetric Engineering and Remote Sensing, 46:337-345.
[22] Iisaka, J. and Hegedus E., 1982, “Population Estimation from Landsat Imagery,” Remote Sensing of the Environment, 12:259-272.
[23] Webster, C. J., 1996, “Population and Dwelling Unit Estimation from Space,” Third World Planning Review, 18(2):155-176.
[24] Dobson, J.E., Bright E. A., Coleman P. R. , Durfee R. C. , and Worley B. A. , 2000. LandScan: A global population database for estimating populations at risk, Photogrammetric Engineering & Remote Sensing, 66:849–857.
[25] Liu, X. and Clarke K. C., 2002, “Estimation of Residential Population Using High Resolution Satellite Imagery,” Proceedings of the 3rd Symposium in Remote Sensing of Urban Areas.
[26] Green, N. E., 1957, “Aerial Photographic Interpretation and the Social Structure of the City,” Photogrammetric Engineering, 23:89-96.
[27] Green, N. E. and Monier R. B., 1959, “Aerial Photographic Interpretation of the Human Ecology of the City,” Photogrammetric Engineering, 25:770-773.
[28] Monmonier, M. S. and Schnell G. S., 1984, “Land-Use and Land-Cover Data and the Mapping of Population Density,” The International Yearbook of Cartography, 24:115-121.
[29] Kaimaris, Dimitris, and Petros Patias. "Population Estimation in an Urban Area with Remote Sensing and Geographical Information Systems." International Journal of Advanced Remote Sensing and GIS (2016): pp-1795.
[30] Karume, K., et al. "Use of Remote Sensing for Population Number Determination." The Open Access Journal of Science and Technology 5 (2017).
[31] Dong, P., Ramesh, S. and Nepali, A., 2010, Evaluation of small-area population estimation using LiDAR, Landsat TM and parcel data. International Journal of Remote Sensing, 31, pp. 5571–5586.
[32] Cycle route planner, https://www.bbbike.org/ Accessible online: November 12, 2018.
[33] Jabbari, S. E., 2016, Node modeling for congested urban networks, 91, 229-249.