Assessment of Urban Changes at the Residential Neighbourhood Level Based on Satellite Imageries
Abstract
Doi: 10.28991/CEJ-2025-011-01-05
Full Text: PDF
Keywords
References
Xiao, P., Zhang, X., Wang, D., Yuan, M., Feng, X., & Kelly, M. (2016). Change detection of built-up land: A framework of combining pixel-based detection and object-based recognition. ISPRS Journal of Photogrammetry and Remote Sensing, 119, 402–414. doi:10.1016/j.isprsjprs.2016.07.003.
Negeri, M. D., Guta, M. S., & Erena, S. H. (2023). Determinant factors hinder urban structure plan implementation: The case of Nekemte Town, Ethiopia. Heliyon, 9(3). doi:10.1016/j.heliyon.2023.e13448.
Kadhim, N., Ismael, N. T., & Kadhim, N. M. (2022). Urban Landscape Fragmentation as an Indicator of Urban Expansion Using Sentinel-2 Imageries. Civil Engineering Journal (Iran), 8(9), 1799–1814. doi:10.28991/CEJ-2022-08-09-04.
Kadhim, N., Mourshed, M., & Bray, M. (2016). Advances in remote sensing applications for urban sustainability. Euro-Mediterranean Journal for Environmental Integration, 1(1), 7. doi:10.1007/s41207-016-0007-4.
Kalfas, D., Kalogiannidis, S., Chatzitheodoridis, F., & Toska, E. (2023). Urbanization and Land Use Planning for Achieving the Sustainable Development Goals (SDGs): A Case Study of Greece. Urban Science, 7(2), 43. doi:10.3390/urbansci7020043.
Hussain, M., Chen, D., Cheng, A., Wei, H., & Stanley, D. (2013). Change detection from remotely sensed images: From pixel-based to object-based approaches. ISPRS Journal of Photogrammetry and Remote Sensing, 80, 91–106. doi:10.1016/j.isprsjprs.2013.03.006.
Kadhim, N., & Mourshed, M. (2018). A shadow-overlapping algorithm for estimating building heights from VHR satellite images. IEEE Geoscience and Remote Sensing Letters, 15(1), 8–12. doi:10.1109/LGRS.2017.2762424.
Du, P., Liu, S., Gamba, P., Tan, K., & Xia, J. (2012). Fusion of difference images for change detection over urban areas. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 5(4), 1076–1086. doi:10.1109/JSTARS.2012.2200879.
Bruzzone, L., & Bovolo, F. (2013). A novel framework for the design of change-detection systems for very-high-resolution remote sensing images. Proceedings of the IEEE, 101(3), 609–630. doi:10.1109/JPROC.2012.2197169.
Li, J., Yuan, Q., Shen, H., Meng, X., & Zhang, L. (2016). Hyperspectral Image Super-Resolution by Spectral Mixture Analysis and Spatial-Spectral Group Sparsity. IEEE Geoscience and Remote Sensing Letters, 13(9), 1250–1254. doi:10.1109/LGRS.2016.2579661.
Singh, A., & Singh, K. K. (2018). Unsupervised change detection in remote sensing images using fusion of spectral and statistical indices. Egyptian Journal of Remote Sensing and Space Science, 21(3), 345–351. doi:10.1016/j.ejrs.2018.01.006.
Liu, T., Yang, L., & Lunga, D. (2021). Change detection using deep learning approach with object-based image analysis. Remote Sensing of Environment, 256, 112308. doi:10.1016/j.rse.2021.112308.
Yang, X., Chen, R., Zhang, F., Zhang, L., Fan, X., Ye, Q., & Fu, L. (2021). Pixel-level automatic annotation for forest fire image. Engineering Applications of Artificial Intelligence, 104, 104353. doi:10.1016/j.engappai.2021.104353.
Gandhi, G. M., Parthiban, S., Thummalu, N., & Christy, A. (2015). NDVI: Vegetation Change Detection Using Remote Sensing and GIS - A Case Study of Vellore District. Procedia Computer Science, 57, 1199–1210. doi:10.1016/j.procs.2015.07.415.
Leichtle, T., Geiß, C., Wurm, M., Lakes, T., & Taubenböck, H. (2017). Unsupervised change detection in VHR remote sensing imagery – an object-based clustering approach in a dynamic urban environment. International Journal of Applied Earth Observation and Geoinformation, 54, 15–27. doi:10.1016/j.jag.2016.08.010.
Chen, D., Loboda, T. V., Silva, J. A., & Tonellato, M. R. (2021). Characterizing small-town development using very high-resolution imagery within remote rural settings of Mozambique. Remote Sensing, 13(17), 3385. doi:10.3390/rs13173385.
Liu, H., Yang, M., Chen, J., Hou, J., & Deng, M. (2018). Line-constrained shape feature for building change detection in VHR remote sensing imagery. ISPRS International Journal of Geo-Information, 7(10), 410. doi:10.3390/ijgi7100410.
Zhang, C., Wei, S., Ji, S., & Lu, M. (2019). Detecting large-scale urban land cover changes from very high-resolution remote sensing images using CNN-based classification. ISPRS International Journal of Geo-Information, 8(4), 189. doi:10.3390/ijgi8040189.
Warth, G., Braun, A., Assmann, O., Fleckenstein, K., & Hochschild, V. (2020). Prediction of socio-economic indicators for urban planning using VHR satellite imagery and spatial analysis. Remote Sensing, 12(11). doi:10.3390/rs12111730.
Chen, H., Zhang, K., Xiao, W., Sheng, Y., Cheng, L., Zhou, W., Wang, P., Su, D., Ye, L., & Zhang, S. (2021). Building change detection in very high-resolution remote sensing image based on pseudo-orthorectification. International Journal of Remote Sensing, 42(7), 2686–2705. doi:10.1080/01431161.2020.1862437.
Afaq, Y., & Manocha, A. (2021). Analysis on change detection techniques for remote sensing applications: A review. Ecological Informatics, 63, 101310. doi:10.1016/j.ecoinf.2021.101310.
Baker, F., Smith, C. L., & Cavan, G. (2018). A combined approach to classifying land surface cover of urban domestic gardens using citizen science data and high-resolution image analysis. Remote Sensing, 10(4), 537. doi:10.3390/rs10040537.
Setiowati, R., & Koestoer, R. H. (2024). Valuation of Urban Green Open Spaces Using the Life Satisfaction Approach. Civil Engineering Journal (Iran), 10(4), 1159–1181. doi:10.28991/CEJ-2024-010-04-010.
Kim, Y., & Yoon, H. (2024). Accurate and efficient feature classification of urban public open spaces: A deep learning-based multivariate time-series approach. International Journal of Applied Earth Observation and Geoinformation, 133, 104113. doi:10.1016/j.jag.2024.104113.
Villaverde, A., Álvarez, I., Rojí, E., & Garmendia, L. (2024). Categorisation of urban open spaces for heat adaptation: A cluster based approach. Building and Environment, 263, 111861. doi:10.1016/j.buildenv.2024.111861.
Odhengo, P., Lutta, A. I., Osano, P., & Opiyo, R. (2024). Urban green spaces in rapidly urbanizing cities: A socio-economic valuation of Nairobi City, Kenya. Cities, 155, 105430. doi:10.1016/j.cities.2024.105430.
Hou, Y., Liu, Y., Wu, Y., & Zhang, B. (2024). Assessment of spatial and socioeconomic disparities in urban green space accessibility based on a Physical Activity Diversity Index (PADI). Ecological Indicators, 166, 112478. doi:10.1016/j.ecolind.2024.112478.
Shepherd, J. D., Bunting, P., & Dymond, J. R. (2019). Operational large-scale segmentation of imagery based on iterative elimination. Remote Sensing, 11(6), 658. doi:10.3390/RS11060658.
Wessel, M., Brandmeier, M., & Tiede, D. (2018). Evaluation of different machine learning algorithms for scalable classification of tree types and tree species based on Sentinel-2 data. Remote Sensing, 10(9), 1419. doi:10.3390/rs10091419.
Antonelli, L., De Simone, V., & di Serafino, D. (2020). Spatially adaptive regularization in image segmentation. Algorithms, 13(9), 226. doi:10.3390/A13090226.
Saha, S., Bovolo, F., & Bruzzone, L. (2019). Unsupervised deep change vector analysis for multiple-change detection in VHR Images. IEEE Transactions on Geoscience and Remote Sensing, 57(6), 3677–3693. doi:10.1109/TGRS.2018.2886643.
Touati, R., Mignotte, M., & Dahmane, M. (2020). Anomaly Feature Learning for Unsupervised Change Detection in Heterogeneous Images: A Deep Sparse Residual Model. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13, 588–600. doi:10.1109/JSTARS.2020.2964409.
Zhou, L., Gong, Y., López-Carr, D., & Huang, C. (2024). A critical role of the capital green belt in constraining urban sprawl and its fragmentation measurement. Land Use Policy, 141, 107148. doi:10.1016/j.landusepol.2024.107148.
Grover, A., Vadakkuveettil, A., Chen, R., & Wu, J. (2024). Warming reality of Kozhikode Urban Area: Uncovering the heat of built-up expansion and vegetation loss. Environmental Challenges, 17, 101016. doi:10.1016/j.envc.2024.101016.
DOI: 10.28991/CEJ-2025-011-01-05
Refbacks
- There are currently no refbacks.
Copyright (c) 2025 Nada Kadhim, Nabil M. Kadhim

This work is licensed under a Creative Commons Attribution 4.0 International License.