References
- Adeniyi, P. (1983). An aerial photographic method for estimating urban population. Photogrammetric Engineering and Remote Sensing, 49, 545–560.
- Akaike, H. (1998). Information theory and an extension of the maximum likelihood principle. Selected Papers of Hirotugu Akaike, 199-213) New York: Springer. doi:10.1007/978-1-4612-1694-0_15
- Alexander, E. R., Reed, K. D., & Murphy, P. (1988). Density measures and their relation to urban form center for architecture and urban planning research. Milwaukee: University of Wisconsin.
- Anderson, D., & Burnham, K. (2004). Model selection and multi-model inference (2nd ed., pp. 63). New York: Springer.
- Bakillah, M., Liang, S., Mobasheri, A., Jokar Arsanjani, J., & Zipf, A. (2014). Fine-resolution population mapping using OpenStreetMap points-of-interest. International Journal of Geographical Information Science, 28(9), 1940–1963. doi:10.1080/13658816.2014.909045
- Balakrishnan, K. (2016). Heterogeneity within indian cities: Methods for empirical analysis. Berkeley: University of California.
- Bast, H., Storandt, S., & Weidner, S. (2015). Fine-grained population estimation. In M. Ali & J. Huang (Eds.) Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems, New York: ACM. doi:10.1145/2820783.2820828
- Baud, I., Kuffer, M., Pfeffer, K., Sliuzas, R., & Karuppannan, S. (2010). Understanding heterogeneity in metropolitan india: The added value of remote sensing data for analyzing sub-standard residential areas. International Journal of Applied Earth Observation and Geoinformation, 12(5), 359–374. doi:10.1016/j.jag.2010.04.008
- Bertaud, A., & Brueckner, J. K. (2005). Analyzing building-height restrictions: Predicted impacts and welfare costs. Regional Science and Urban Economics, 35(2), 109–125. doi:10.1016/j.regsciurbeco.2004.02.004
- Boyko, C. T., & Cooper, R. (2011). Clarifying and re-conceptualising density. Progress in Planning, 76(1), 1–61. doi:10.1016/j.progress.2011.07.001
- Bracken, I. (1993). An extensive surface model database for population-related information: Concept and application. Environment and Planning B: Planning and Design, 20(1), 13–27. doi:10.1068/b200013
- Breusch, T. S., & Pagan, A. R. (1979). A simple test for heteroscedasticity and random coefficient variation. Econometrica: Journal of the Econometric Society, 47, 1287–1294. doi:10.2307/1911963
- Brueckner, J. K., & Sridhar, K. S. (2012). Measuring welfare gains from relaxation of land use restrictions: The case of India’s building-height limits. Regional Science and Urban Economics, 42(6), 1061–1067. doi:10.1016/j.regsciurbeco.2012.08.003
- Brunsdon, C., Fotheringham, A. S., & Charlton, M. E. (1996). Geographically weighted regression: A method for exploring spatial nonstationarity. Geographical Analysis, 28(4), 281–298. doi:10.1111/j.1538-4632.1996.tb00936.x
- Census of India. (2001). Primary census abstract data tables. New Delhi: Ministry of Home Affairs, Government of India.
- Census of India. (2011a). District census handbook, bangalore: Village and town wise primary census abstract. Bangalore, Karnataka: Directorate of Census Operations.
- Census of India. (2011b). Houselisting and housing data tables. New Delhi: Ministry of Home Affairs, Government of India.
- Census of India. (2011c). Primary census abstract data tables. New Delhi: Ministry of Home Affairs, Government of India.
- Chrisman, N. R. (1998). Rethinking levels of measurement for cartography. Cartography and Geographic Information Systems, 25(4), 231–242. doi:10.1559/152304098782383043
- Churchman, A. (1999). Disentangling the concept of density. Journal of Planning Literature, 13(4), 389–411. doi:10.1177/08854129922092478
- de Franchis, C., Meinhardt-Llopis, E., Michel, J., Morel, J., & Facciolo, G. (2014). An automatic and modular stereo pipeline for pushbroom images. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2(3), 49. doi:10.5194/isprsannals-ii-3-49-2014
- Dempster, A. P., Laird, N. M., & Rubin, D. B. (1977). Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society: Series B (Methodological), 39(1), 1–22. http://www.jstor.org/stable/2984875
- Dobson, J. E., Bright, E. A., Coleman, P. R., Durfee, R. C., & Worley, B. A. (2000). LandScan: A global population database for estimating populations at risk. Photogrammetric Engineering and Remote Sensing, 66(7), 849–857.
- Dong, P., Ramesh, S., & Nepali, A. (2010). Evaluation of small-area population estimation using LiDAR, landsat TM and parcel data. International Journal of Remote Sensing, 31(21), 5571–5586. doi:10.1080/01431161.2010.496804
- Eicher, C. L., & Brewer, C. A. (2001). Dasymetric mapping and areal interpolation: Implementation and evaluation. Cartography and Geographic Information Science, 28(2), 125–138. doi:10.1559/152304001782173727
- Farr, T. G., Rosen, P. A., Caro, E., Crippen, R., Duren, R., Hensley, S., … Roth, L. (2007). The shuttle radar topography mission. Reviews of Geophysics, 45(2), RG2004. doi:10.1029/2005RG000183
- Flowerdew, R., Green, M., & Kehris, E. (1991). Using areal interpolation methods in geographic information systems. Papers in Regional Science, 70(3), 303–315. doi:10.1111/j.1435-5597.1991.tb01734.x
- Foody, G. M. (2002). Status of land cover classification accuracy assessment. Remote Sensing of Environment, 80(1), 185–201. doi:10.1016/s0034-4257(01)00295-4
- Geological Survey, U. S. (2015). Landsat—Earth observation satellites: U.S. Geological Survey fact sheet 2015–3081. doi:10.3133/fs20153081.
- Goodchild, M. F., Anselin, L., & Deichmann, U. (1993). A framework for the areal interpolation of socioeconomic data. Environment and Planning A, 25(3), 383–397. doi:10.1068/a250383
- Goodchild, M. F., & Lam, N. S. (1980). Areal interpolation: A variant of the traditional spatial problem. Geo-Processing, 1(3), 297–312.
- Google Earth 7.1. (2011). Bangalore, 12°58ʹ23.81”N 77°35ʹ57.04”E
- Gotway, C. A., & Young, L. J. (2002). Combining incompatible spatial data. Journal of the American Statistical Association, 97(458), 632–648. doi:10.1198/016214502760047140
- Government of Karnataka. (2007). Notification of areas under bruhat bangalore mahanagara palike. Bangalore.
- Harvey, J. T. (2002). Population estimation models based on individual TM pixels. Photogrammetric Engineering and Remote Sensing, 68(11), 1181–1192.
- Hawley, K., & Moellering, H. (2005). A comparative analysis of areal interpolation methods. Cartography and Geographic Information Science, 32(4), 411–423. doi:10.1559/152304005775194818
- Holt, J. B., Lo, C., & Hodler, T. W. (2004). Dasymetric estimation of population density and areal interpolation of census data. Cartography and Geographic Information Science, 31(2), 103–121. doi:10.1559/1523040041649407
- Hurvich, C. M., & Tsai, C. (1989). Regression and time series model selection in small samples. Biometrika, 76(2), 297–307. doi:10.2307/2336663
- Iisaka, J., & Hegedus, E. (1982). Population estimation from landsat imagery. Remote Sensing of Environment, 12(4), 259–272. doi:10.1016/0034-4257(82)90039-6
- Koenker, R. (1981). A note on studentizing a test for heteroscedasticity. Journal of Econometrics, 17(1), 107–112. doi:10.1016/0304-4076(81)90062-2
- KSDB. (2014). District-wise/town-wise slum ownership details. Bangalore: Karnataka Slum Development Board.
- Lajaunie, C., & Wackernagel, H. (2000). Geostatistical approaches to change of support problems-theoretical framework. Technical Report N–30/01/G ENSMP - ARMINES, Fontainebleau, France: Centre de Géostatistique.
- Lam, N. S. (1983). Spatial interpolation methods: A review. The American Cartographer, 10(2), 129–150. doi:10.1559/152304083783914958
- Langford, M., & Unwin, D. J. (1994). Generating and mapping population density surfaces within a geographical information system. The Cartographic Journal, 31(1), 21–26. doi:10.1179/000870494787073718
- Lo, C. P. (2003). Zone-based estimation of population and housing units from satellite-generated land use/land cover maps. In V. Mesev (Ed.), Remotely sensed cities (pp. 157–180). London: CRC Press.
- Lu, Z., Im, J., & Quackenbush, L. (2011). A volumetric approach to population estimation using LiDAR remote sensing. Photogrammetric Engineering & Remote Sensing, 77(11), 1145–1156. doi:10.14358/pers.77.11.1145
- Lwin, K., & Murayama, Y. (2009). A GIS approach to estimation of building population for micro‐spatial analysis. Transactions in GIS, 13(4), 401–414. doi:10.1111/j.1467-9671.2009.01171.x
- Maantay, J. A., Maroko, A. R., & Herrmann, C. (2007). Mapping population distribution in the urban environment: The cadastral-based expert dasymetric system (CEDS). Cartography and Geographic Information Science, 34(2), 77–102. doi:10.1559/152304007781002190
- Maniadakis, D., & Varoutas, D. (2013). Structural properties of urban street networks of varying population density. Paper presented at the 10th European Conference on Complex Systems (ECCS’13), Barcelona, 1–6.
- Mennis, J. (2003). Generating surface models of population using dasymetric mapping. The Professional Geographer, 55(1), 31–42.
- Mennis, J. (2009). Dasymetric mapping for estimating population in small areas. Geography Compass, 3(2), 727–745. doi:10.1111/j.1749-8198.2009.00220.x
- Mennis, J., & Hultgren, T. (2006). Intelligent dasymetric mapping and its application to areal interpolation. Cartography and Geographic Information Science, 33(3), 179–194. doi:10.1559/152304006779077309
- Monier, R. B., & Green, N. E. (1957). Aerial photographic interpretation and the human geography of the city. The Professional Geographer, 9(5), 2–5. doi:10.1111/j.0033-0124.1957.095_2.x
- Moran, P. A. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23. doi:10.2307/2332142
- Olorunfemi, J. (1982). Applications of aerial photography to population estimation in Nigeria. Geojournal, 6(3), 225–230. doi:10.1007/bf00210654
- Openshaw, S. (1984). CATMOG 38: The modifiable areal unit problem. Norwich, UK: Geo Abstracts. Retrieved from http://qmrg.org.uk/files/2008/11/38-maup-openshaw.pdf
- Patel, S. (2013). Life between buildings: The use and abuse of FSI. Economic and Political Weekly, 48(36), 68–74.
- Peponis, J., Allen, D., French, S., Scoppa, M., & Brown, J. (2007). Street connectivity and urban density: Spatial measures and their correlation. 6th International Space Syntax Symposium Istanbul: ITU Faculty of Architecture. http://www.spacesyntaxistanbul.itu.edu.tr/papers/longpapers/004%20-%20Peponis%20Allen%20French%20Scoppa%20Brown.pdf
- Qiu, F., Sridharan, H., & Chun, Y. (2010). Spatial autoregressive model for population estimation at the census block level using LIDAR-derived building volume information. Cartography and Geographic Information Science, 37(3), 239–257. doi:10.1559/152304010792194949
- Reibel, M., & Agrawal, A. (2007). Areal interpolation of population counts using pre-classified land cover data. Population Research and Policy Review, 26(5–6), 619–633. doi:10.1007/s11113-007-9050-9
- Reibel, M., & Bufalino, M. E. (2005). Street-weighted interpolation techniques for demographic count estimation in incompatible zone systems. Environment and Planning A, 37(1), 127–139. doi:10.1068/a36202
- Robinson, W. S. (1950). Ecological correlations and the behavior of individuals. American Sociological Review, 15(3), 351–357. doi:10.2307/2087176
- Shaker, I. F., Abd-Elrahman, A., Abdel-Gawad, A. K., & Sherief, M. A. (2011). Building extraction from high resolution space images in high density residential areas in the great Cairo region. Remote Sensing, 3(4), 781–791. doi:10.3390/rs3040781
- Shirgaokar, M. (2013). Limitations of the anti-floor space index position. Economic and Political Weekly, 48(29), 123–125.
- Silván-Cárdenas, J. L., Wang, L., Rogerson, P., Wu, C., Feng, T., & Kamphaus, B. D. (2010). Assessing fine-spatial-resolution remote sensing for small-area population estimation. International Journal of Remote Sensing, 31(21), 5605–5634. doi:10.1080/01431161.2010.496800
- Sinton, D. (1978). The inherent structure of information as a constraint to analysis: Mapped thematic data as a case study. In G. Dutton (ed.) First International Advanced Study Symposium on Topological Data Structures for Geographic Information Systems 7, Reading MA: Addison-Wesley, 1–17. Retrieved from https://www.oicrf.org/-/the-inherent-structure-of-information-as-a-constraint-to-analysis-mapped-thematic-data-as-a-case-study
- Sridharan, H., & Qiu, F. (2013). A spatially disaggregated areal interpolation model using light detection and Ranging‐Derived building volumes. Geographical Analysis, 45(3), 238–258. doi:10.1111/gean.12010
- Stevens, F. R., Gaughan, A. E., Linard, C., & Tatem, A. J. (2015). Disaggregating census data for population mapping using random forests with remotely-sensed and ancillary data. PloS One, 10(2), e0107042. doi:10.1371/journal.pone.0107042
- Thorndike, E. L. (1939). On the fallacy of imputing the correlations found for groups to the individuals or smaller groups composing them. The American Journal of Psychology, 52(1), 122–124. doi:10.2307/1416673
- Tobler, W. R. (1979). Smooth pycnophylactic interpolation for geographical regions. Journal of the American Statistical Association, 74(367), 519–530. doi:10.2307/2286968
- Tomás, L., Fonseca, L., Almeida, C., Leonardi, F., & Pereira, M. (2016). Urban population estimation based on residential buildings volume using IKONOS-2 images and lidar data. International Journal of Remote Sensing, 37(sup1), 1–28. doi:10.1080/01431161.2015.1121301
- Ural, S., Hussain, E., & Shan, J. (2011). Building population mapping with aerial imagery and GIS data. International Journal of Applied Earth Observation and Geoinformation, 13(6), 841–852. doi:10.1016/j.jag.2011.06.004
- Wright, J. K. (1936). A method of mapping densities of population: With cape cod as an example. Geographical Review, 26(1), 103–110. doi:10.2307/209467
- Wright, J. K. (1955). Crossbreeding geographical quantities. Geographical Review, 45(1), 52–65. doi:10.2307/211729
- Wu, C., & Murray, A. T. (2007). Population estimation using landsat enhanced thematic mapper imagery. Geographical Analysis, 39(1), 26–43. doi:10.1111/j.1538-4632.2006.00694.x
- Wu, S., Qiu, X., & Wang, L. (2005). Population estimation methods in GIS and remote sensing: A review. GIScience & Remote Sensing, 42(1), 80–96. doi:10.2747/1548-1603.42.1.80
- Wu, S., Wang, L., & Qiu, X. (2008). Incorporating GIS building data and census housing statistics for sub-block-level population estimation. The Professional Geographer, 60(1), 121–135. doi:10.1080/00330120701724251
- Xie, Y. (1995). The overlaid network algorithms for areal interpolation problem. Computers, Environment and Urban Systems, 19(4), 287–306. doi:10.1016/0198-9715(95)00028-3
- Xie, Z. (2006). A framework for interpolating the population surface at the residential-housing-unit level. GIScience & Remote Sensing, 43(3), 233–251. doi:10.2747/1548-1603.43.3.233
- Yao, Y., Liu, X., Li, X., Zhang, J., Liang, Z., Mai, K., & Zhang, Y. (2017). Mapping fine-scale population distributions at the building level by integrating multisource geospatial big data. International Journal of Geographical Information Science, 31(6), 1220–1244. doi:10.1080/13658816.2017.1290252
- Ye, T., Zhao, N., Yang, X., Ouyang, Z., Liu, X., Chen, Q., … Li, Z. (2019). Improved population mapping for China using remotely sensed and points-of-interest data within a random forests model. Science of the Total Environment, 658, 936–946. doi:10.1016/j.scitotenv.2018.12.276
- Yoo, E., Kyriakidis, P. C., & Tobler, W. (2010). Reconstructing population density surfaces from areal data: A comparison of Tobler’s pycnophylactic interpolation method and Area‐to‐Point kriging. Geographical Analysis, 42(1), 78–98. doi:10.1111/j.1538-4632.2009.00783.x
- Yuan, Y., Smith, R. M., & Limp, W. F. (1997). Remodeling census population with spatial information from Landsat TM imagery. Computers, Environment and Urban Systems, 21(3–4), 245–258. doi:10.1016/s0198-9715(97)01003-x