Abstract
Census data provides an important source of information with respect to decision makers operating in many different fields. However, census collection is a time consuming and resource intensive task. This is especially the case in rural areas where the communication and transportation infrastructure is not as robust as in urban areas. In this paper the authors propose the use of satellite imagery for census collection. The proposed method is not as accurate as “on ground” census collection, but requires very little resource. The proposed method is founded on the idea of collecting census data using classification techniques applied to relevant satellite imagery. The objective is to build a classifier that can label households according to “family” size. More specifically the idea is to segment satellite images so as to obtain pixel collections describing individual households and represent these collections using some appropriate representation to which a classifier generator can be applied. Two representations are considered, histograms and Local Binary Patterns (LBPs). The paper describes the overall method and compares the operation of the two representation techniques using labelled data obtained from two villages lying some 300km to the northwest of Addis Ababa in Ethiopia.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Abdelfattah, R., Nicolas, J.M.: Interferometric synthetic aperture radar coherence histogram analysis for land cover classification. In: Proc. Information and Communication Technologies (ICTTA 2006), vol. 1, pp. 343–348. IEEE (2006)
Atkinson, P.M.: Super-resolution land cover classification using the two-point histogram. In: Sanchez-Vila, X., Carrera, J., Gmez-Hernndez, J. (eds.) Proc. Geostatistics for Environmental Applications (geoENV VI), vol. 13, pp. 15–28. Springer, Netherlands (2004)
Beumier, C., Idrissa, M.: Building change detection by histogram classification. In: Proc. Signal-Image Technology and Internet-Based Systems (SITIS 2011), pp. 409–415. IEEE (2011)
Chakravarti, R., Meng, X.: A study of color histogram based image retrieval. In: Proc. Information Technology: New Generations (ITNG 2009), pp. 1323–1328. IEEE (2009)
Cheng, L., Zhou, Y., Wang, L., Wang, S., Du., C.: An estimate of the city population in china using dmsp night-time satellite imagery. In: Proc. IEEE International on Geoscience and Remote Sensing Symposium (IGARSS 2007), pp. 691–694. IEEE (2007)
Demirel, H., Anbarjafari, G.: Satellite image resolution enhancement using complex wavelet transform. IEEE Geoscience and Remote Sensing Letters 7(1), 123–126 (2010)
Dittakan, K., Coenen, F., Christley, R.: Towards the collection of census data from satellite imagery using data mining: A study with respect to the ethiopian hinterland. In: Bramer, M., Petridis, M. (eds.) Proc. Research and Development in Intelligent Systems XXIX, pp. 405–418. Springer, London (2012)
Fanoe, J.A.X.: Lessons from census taking in south africa: Budgeting and accounting experiences. The African Statistical 13(3), 82–109 (2011)
Gonzalez, R.C., Woods, R.E.: Digital Image Processing (3rd Edition), 3rd edn. Pearson Prentice Hall (2007)
Hadid, A.: The local binary pattern approach and its applications to face analysis. In: Proc. First Workshop on Image Processing Theory, Tools and Applications (IPTA 2008), pp. 1–9. IEEE (2008)
Hijazi, M.H.A., Coenen, F., Zheng, Y.: Retinal image classification using a histogram based approach. In: Proc. International Joint Conference on Neural Network (Special Session on Soft Computing in Medical Imaging), part of IEEE World Congress on Computational Intelligence (WCCI 2010), pp. 3501–3507 (2010)
Jang, J.H., Kim, S.D., Ra, J.B.: Enhancement of optical remote sensing images by subband-decomposed multiscale retinex with hybrid intensity transfer function. IEEE Geoscience and Remote Sensing Letters 8(5), 983–987 (2011)
Jeong, S., Won, C.S., Gray, R.M.: Image retrieval using color histograms generated by gauss mixture vector quantization. Computer Vision and Image Understanding 94(1-3), 44–66 (2004)
Kita, Y.: A study of change detection from satellite images using joint intensity histogram. In: Proc. International Conference on Pattern Recognition (ICPR 2008), pp. 1–4. IEEE (2008)
Li, G., Weng, Q.: Using landsat etm+ imagery to measure population density in indianapolis, indiana, usa. Photogrammetric Engineering and Remote Sensing 71(8), 947 (2005)
Ojala, T., Pietikainen, M., Maenpaa, T.: Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(7), 971–987 (2002)
Pietikäinen, M.: Image analysis with local binary patterns. In: Kalviainen, H., Parkkinen, J., Kaarna, A. (eds.) SCIA 2005. LNCS, vol. 3540, pp. 115–118. Springer, Heidelberg (2005)
Song, C., Li, P., Yang, F.: Multivariate texture measured by local binary pattern for multispectral image classification. In: Proc. IEEE International Conference on Geoscience and Remote Sensing Symposium (IGARSS 2006), pp. 2145–2148 (2006)
Vasconcelos, N., Lippman, A.: Feature representations for image retrieval: beyond the color histogram. In: Proc. IEEE International Conference on Multimedia and Expo (ICME 2000), vol. 2, pp. 899–902. IEEE (2000)
Zhao, G., Pietikainen, M.: Dynamic texture recognition using local binary patterns with an application to facial expressions. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI 2007) 29(6), 915–928 (2007)
Zhao, G., Wu, G., Liu, Y., Chen, J.: Texture classification based on completed modeling of local binary pattern. In: Proc. International Conference on Computational and Information Sciences (ICCIS 2011), pp. 268–271. IEEE (2011)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Dittakan, K., Coenen, F., Christley, R. (2013). Satellite Image Mining for Census Collection: A Comparative Study with Respect to the Ethiopian Hinterland. In: Perner, P. (eds) Machine Learning and Data Mining in Pattern Recognition. MLDM 2013. Lecture Notes in Computer Science(), vol 7988. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39712-7_20
Download citation
DOI: https://doi.org/10.1007/978-3-642-39712-7_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-39711-0
Online ISBN: 978-3-642-39712-7
eBook Packages: Computer ScienceComputer Science (R0)