Change detection for map updating using ‎very high resolution satellite images

Document Type : Research Paper

Authors

1 Civil Engineering Department, Faculty of Engineering, Sohag University

2 Prof. of Surveying and Photogrammetry, Civil Engineering Department, Faculty of Engineering, Assiut University.

Abstract

ABSTRACT
The earth surface changes continuously due to the natural causes and ‎human activities. New generations of satellite sensors, such as WorldView and ‎GeoEye, provide new data to better delineate, track and visualise changes in land ‎cover. A number of classes are used in the satellite images. All artefacts with ‎elevations greater than the ground surface (buildings in particular) may appear in ‎a wrong location. The correction of buildings position is an important task for ‎mapping applications. The main aim of this study is to introduce a change ‎detection approach using very high resolution satellite images (VHR) for map ‎updating. In this approach, an approximated method for building relief ‎displacement correction was developed.‎
In this paper, image preprocessing was carried out and information content ‎of the satellite image was evaluated. Then change detection between GeoEye-1 ‎image and Sohag map was carried out using post-classification comparison ‎technique. After that the change map result was divided into two classes: building ‎and non-building. All objects were transformed from raster to vector format. For ‎building objects, the height was estimated. A python code was written to calculate ‎relief displacement using buildings height and shadow length. The vector layer ‎was added to update the reference map. The results showed the ability of very ‎high-resolution satellites images for updating large scale maps in Egypt. Also, the ‎approximated method for building relief displacement correction is a promising ‎method. It has RMSE accuracy of 0.95m.‎

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Main Subjects


[1].         Hegazy, I.R. and Kaloop, M.R., 2015. Monitoring urban growth and land use change detection with GIS and remote sensing techniques in Daqahlia governorate Egypt. International Journal of Sustainable Built Environment, 4(1), pp.117-124.
[2].         Jin, S., Yang, L., Danielson, P., Homer, C., Fry, J. and Xian, G., 2013. A comprehensive change detection method for updating the National Land Cover Database to circa 2011. Remote Sensing of Environment, 132, pp.159-175.
[3].         Hu, Q., Zhen, L., Mao, Y., Zhou, X. and Zhou, G., 2021. Automated building extraction using satellite remote sensing imagery. Automation in Construction, 123, p.103509.
[4].         Chen, H., Zhang, K., Xiao, W., Sheng, Y., Cheng, L., Zhou, W., Wang, P., Su, D., Ye, L. and Zhang, S., 2021. Building change detection in very high-resolution remote sensing image based on pseudo-orthorectification. International Journal of Remote Sensing, 42(7), pp.2686-2705.
[5].         Chen, L.C., Lo, C.Y. and Rau, J.Y., 2003. Generation of digital orthophotos from IKONOS satellite images. Journal of surveying engineering, 129(2), pp.73-78.
[6].         Comber, A., Umezaki, M., Zhou, R., Ding, Y., Li, Y., Fu, H., Jiang, H. and Tewkesbury, A., 2012. Using shadows in high-resolution imagery to determine building height. Remote sensing letters, 3(7), pp.551-556.
[7].         Benarchid, O., Raissouni, N., El Adib, S., Abbous, A., Azyat, A., Achhab, N.B., Lahraoua, M. and Chahboun, A., 2013. Building extraction using object-based classification and shadow information in very high-resolution multispectral images, a case study: Tetuan, Morocco. Canadian Journal on Image Processing and Computer Vision, 4(1), pp.1-8.
[8].         Zhang, L., B. Zhong, and A. Yang. 2019. Building change detection using object-oriented lbp feature map in very high spatial resolution imagery. In Proceedings of 2019 10th International Workshop on the Analysis of Multitemporal Remote Sensing Images (Multitemp), 1–4. Shanghai, China.
[9].         Technical specifications for the products and services of the Egyptian Survey Authority, Part 1: Topography and Geodesy, 2020.
[10].     Dahiya, S., Garg, P.K. and Jat, M.K., 2013. A comparative study of various pixel-based image fusion techniques as applied to an urban environment. International Journal of Image and Data Fusion, 4(3), pp.197-213.
[11].     Mostafa, Y., and A. Abedehafez. 2017a. Shadow Identification in High Resolution Satellite Images in the Presence of Water Regions. Photogrammetric Engineering and Remote Sensing 83 (2): 87–94
[12].     Mostafa, Y., and A. Abedehafez. 2017b. Accurate Shadow Detection from High-Resolution Satellite Images. IEEE Geoscience and Remote Sensing Letters 14 (4): 494-498.
[13].     Mostafa, Y. 2017. A Review on Various Shadow Detection and Compensation Techniques in Remote Sensing Images. Canadian Journal of Remote Sensing 43 (6): 545–562.
[14].     Aguilar, M.A., Aguilar, F.J. and Agüera, F., 2008. Assessing geometric reliability of corrected images from very high-resolution satellites. Photogrammetric Engineering and Remote Sensing, 74(12), pp.1551-1560.
[15].     Gungor, O. and Shan, J., 2004, July. Evaluation of satellite image fusion using wavelet transform. In proceedings of 20th Congress ISPRS “Geo-Imagery Bridging Continents (pp. 12-13), 12 - 23 July, Istanbul, Turkey.
[16].     Alkan, M., Buyuksalih, G., Sefercik, U.G. and Jacobsen, K., 2013. Geometric accuracy and information content of WorldView-1 images. Optical engineering, 52(2), p.026201.
[17].     Farrag, F.A., Mostafa, Y.G. and Mohamed, N.A., 2020. Detecting land cover changes using VHR satellite images: a comparative study. journal of engineering science, 48, pp.200-211.
[18].     Li, J., Cao, J., Feyissa, M.E. and Yang, X., 2020. Automatic building detection from very high-resolution images using multiscale morphological attribute profiles. Remote Sensing Letters, 11(7), pp.640-649.
[19].     Aguilar, M.A., del Mar Saldaña, M. and Aguilar, F.J., 2013. Assessing geometric accuracy of the orthorectification process from GeoEye-1 and WorldView-2 panchromatic images. International Journal of Applied Earth Observation and Geoinformation, 21, pp.427-435.
[20].     Raju, P.L.N., Chaudhary, H. and Jha, A.K., 2014. Shadow analysis technique for extraction of building height using high resolution satellite single image and accuracy assessment. International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences.
[21].      Zhang, L., Zhong, B. and Yang, A., 2019, August. Building Change Detection using Object-Oriented LBP Feature Map in Very High Spatial Resolution Imagery. In 2019 10th International Workshop on the Analysis of Multitemporal Remote Sensing Images (MultiTemp) (pp. 1-4). IEEE.
[22].     Feng, W., Sui, H., Hua, L., Xu, C., Ma, G. and Huang, W., 2020. Building extraction from VHR remote sensing imagery by combining an improved deep convolutional encoder-decoder architecture and historical land use vector map. International Journal of Remote Sensing, 41(17), pp.6595-6617.
[23].     Ma, W., Wan, Y., Li, J., Zhu, S. and Wang, M., 2019. An automatic morphological attribute building extraction approach for satellite high spatial resolution imagery. Remote Sensing11(3), p.337.