ANALYSIS AND PREDICTION OF SPATIOTEMPORAL CHANGES OF URBAN AREAS USING NEURAL NETWORKS
DOI:
https://doi.org/10.7251/STP2215191GAbstract
Land use/Land cover (LULC) is crucial for land management. This study shows the spatiotemporal dynamics of LULC for a wide area of Novi Sad with the emphasis on the urban area analysis. Results presented in this study aim to estimate LULC changes and predict future trends of urban area expansion in Novi Sad. Conducted study shows that in the years to come there will be a decrease in the urban area expansion compared to last 35 years.
References
Z. Abbas, G. Yang, Y. Zhong, and Y. Zhao, “Spatiotemporal Change Analysis and Future Scenario of LULC Using the CA-ANN Approach: A Case Study of the Greater Bay Area, China,” Land, vol. 10, no. 6, pp. 584, 2021.
R. Wang, A. Derdouri, and Y. Murayama, “Spatiotemporal Simulation of Future Land Use/Cover Change Scenarios in the Tokyo Metropolitan Area,” Sustainability, vol. 10, no. 6, pp. 2056, 2018.
Z. Qiao, L. Liu, Y. Qin, X. Xu, B. Wang, and Z. Liu, “The Impact of Urban Renewal on Land Surface Temperature Changes: A Case Study in the Main City of Guangzhou, China,” Remote Sensing, vol. 12, no. 5, pp. 794, 2020.
L. Jiang, Y. Liu, S. Wu, and C. Yang, “Study on Urban Spatial Pattern Based on DMSP/OLS and NPP/VIIRS in Democratic People’s Republic of Korea,” Remote Sensing, vol. 13, no. 23, pp. 4879, 2021.
Z. Wu, R. Zhou, and Z. Zeng, “Identifying and Mapping the Responses of Ecosystem Services to Land Use Change in Rapidly Urbanizing Regions: A Case Study in Foshan City, China,” Remote Sensing, vol. 13, no. 21, pp. 4374, 2021.
S. Gao, W. Li, K. Sun, J. Wei, Y. Chen, and X. Wang, “Built-Up Area Change Detection Using Multi-Task Network with Object-Level Refinement,” Remote Sensing, vol. 14, no. 4, pp. 957, 2022.
D. Jovanović, M. Gavrilović, D. Sladić, A. Radulović, and M. Govedarica, “Building Change Detection Method to Support Register of Identified Changes on Buildings,” Remote Sensing, vol. 13, no. 16, pp. 3150, 2021.
C. Corbane, V. Syrris, F. Sabo, P. Politis, M. Melchiorri, M. Pesaresi, P. Soille and T. Kemper, “Convolutional neural networks for global human settlements mapping from Sentinel-2 satellite imagery,“ Neural Computing and Applications, vol. 33, pp. 6697, 2021.
D. Jovanović, M. Govedarica, F. Sabo, Ž. Bugarinović, O. Novović, T. Beker and M. Lauter, “Land cover change detection by using remote sensing: A case study of Zlatibor (Serbia),” Geographica Pannonica, vol. 19, no. 4, pp. 162, 2015.
N. Alam, S. Saha, S. Gupta, and S. Chakraborty, “Prediction modelling of riverine landscape dynamics in the context of sustainable management of floodplain: a Geospatial approach,” Annals of GIS, vol. 27, no. 3, pp. 299, 2021.
C. Liping, S. Yujun and S. Saeed, “Monitoring and predicting land use and land cover changes using remote sensing and GIS techniques—A case study of a hilly area, Jiangle, China,” PLOS ONE vol. 13, no. 7, 2018.
C. Başnou, E. Álvarez, G. Bagaria, M. Guardiola, R. Isern, P. Vicente and J. Pino, “Spatial Patterns of Land Use Changes Across a Mediterranean Metropolitan Landscape: Implications for Biodiversity Management,” Environmental Management, vol. 52, pp. 971, 2013.
X. Jianchu, J. Fox, J. B. Vogler, Z. P. F. Yongshou, Y. Lixin, Q. Jie and S. Leisz, “Land-Use and Land-Cover Change and Farmer Vulnerability in Xishuangbanna Prefecture in Southwestern China,” Environmental Management, vol. 36, pp. 404, 2005.
N. Gamboa-Badilla, A. Segura, G. Bagaria, C. Basnou and J. Pino, “Contrasting time-scale effects of land-use legacy on species richness, diversity and composition in Mediterranean scrubland communities,” Landscape Ecology, vol. 35, pp. 2745 ,2020.
S. W. Wang, B. M. Gebru, M. Lamchin, R. B. Kayastha, and W. K. Lee, “Land Use and Land Cover Change Detection and Prediction in the Kathmandu District of Nepal Using Remote Sensing and GIS,” Sustainability, vol. 12, no. 9, pp. 3925, 2020.
M. Kamaraj and S. Rangarajan, “Predicting the Future Land Use and Land Cover Changes for Bhavani Basin, Tamil Nadu, India Using QGIS MOLUSCE Plugin,” Environmental Science and Pollution Research, 2022.
Statistical Office of the Republic of Serbia, https://www.stat.gov.rs/en-US/, [12.02.2022.].
D. Jovanović, M. Govedarica, F. Sabo and D. Sladić, “Open Satellite Data for the area of Serbia,” in ICIST 2015 5th International Conference on Information Society and Technology, 2015.
Landsat 5, https://www.usgs.gov/landsat-missions/landsat-5, [15.02.2022.].
A. Sekertekin and S. Bonafoni, “Land Surface Temperature Retrieval from Landsat 5, 7, and 8 over Rural Areas: Assessment of Different Retrieval Algorithms and Emissivity Models and Toolbox Implementation,” Remote Sensing, vol. 12, no. 2, pp. 294, 2020.
Landsat 8, https://landsat.gsfc.nasa.gov/satellites/landsat-8/, [15.02.2022.].
M. A. Ridwan, N. A. M. Radzi, W. S. H. M. W. Ahmad, I. S. Mustafa, N. M. Din, Y. E. Jalil, A. M. Isa, N. S. Othman and W. M. D. W. Zaki, “Applications of Landsat-8 Data: a Survey,” International Journal of Engineering & Technology, vol. 7, no. 4, pp. 436, 2018.
A. Šiljeg, M. Barda, I. Marić, Digitalno modeliranje reljefa. Sveučilište u Zadru, Alfa d.d., Zadar, Zagreb, 2018.
EU-DEM, https://land.copernicus.eu/imagery-in-situ/eu-dem, [17.02.2022.].
M. Belgiu and L. Drăguţ, “Random forest in remote sensing: A review of applications and future directions,” ISPRS Journal of Photogrammetry and Remote Sensing, vol. 114, pp. 24, 2016.
G. Jakovljević, D. Sekulović and M. Govedarica, “Land use / land cover mapping from sentinel 2 data using machine learning algorithms,” in STEPGRAD International scientific conference on contemporary theory and practice in construction XIII, pp. 247, 2018.
F. Murtagh, “Multilayer perceptrons for classification and regression,” Neurocomputing, vol. 2, no. 5–6, pp. 193, 1991.
S. Abirami and P. Chitra, “Chapter Fourteen - Energy-efficient edge based real-time healthcare support system,” Advances in Computers, Elsevier, vol. 117, no. 1, pp. 339, 2020.
Abd. R. As-syakur, I. W. S. Adnyana, I. W. Arthana, and I. W. Nuarsa, “Enhanced Built-Up and Bareness Index (EBBI) for Mapping Built-Up and Bare Land in an Urban Area,” Remote Sensing, vol. 4, no. 10, pp. 2957, 2012.
A. Taufik and S. S. S. Ahmad, “Land cover classification of Landsat 8 satellite data based on Fuzzy Logic approach,” in 8th IGRSM International Conference and Exhibition on Remote Sensing & GIS, 2018.
M. Ukhnaa, X. Huo and G. Gaudel, “Modification of urban built-up area extraction method based on the thematic index-derived bands,” in IOP Conference Series Earth and Environmental Science 227, 2019.
M.T.U. Rahman, F. Tabassum, M. Rasheduzzaman, H. Saba, L. Sarkar, J. Ferdous, S.Z. Uddin and A.Z. Islam, “Temporal dynamics of land use/land cover change and its prediction using CA-ANN model for southwestern coastal Bangladesh,” Environmental Monitoring and Assessment, vol. 189, 2017.
A.M. El-Tantawi, A. Bao, C. Chang and Y. Liu, “Monitoring and predicting land use/cover changes in the Aksu-Tarim River Basin, Xinjiang-China (1990–2030),” Environmental Monitoring and Assessment, vol. 191, 2019.
