Change detection for map updating using very high resolution satellite images | ||||
| JES. Journal of Engineering Sciences | ||||
| Article 4, Volume 49, No 4, July and August 2021, Page 424-445 PDF (1.58 MB) | ||||
| Document Type: Research Paper | ||||
| DOI: 10.21608/jesaun.2021.67949.1039 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Yasser Gaber 1; Nasser Ahmed  1; Farrag Ali Farrag2
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| 1Civil Engineering Department, Faculty of Engineering, Sohag University | ||||
| 2Prof. 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. | ||||
| Keywords | ||||
| map updating; change detection; relief displacement | ||||
| References | ||||
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[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 Sensing, 11(3), p.337. | ||||
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