Ivan Potić

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© The Authors. Published by the Institute of Social Sciences – Center for Demographic Research under a Creative Com mons Attribution-NonCommercial 4.0 | https://stnv.idn.org.rsIntegrating advanced technologies for enhanced demographic research and urban planningRecent technological advancements in optical, thermal, and Synthetic Ap-erture Radar (SAR) satellite imagery, Light Detection and Ranging (LiDAR) point clouds, and Unmanned Aerial Vehicle (UAV or drone) imagery have significantly impacted demographic research. These technologies facilitate detailed mapping and monitoring of environmental features crucial for un-derstanding vector-borne diseases, pre-dicting socio-economic outcomes in ur-ban areas, enhancing geo-demographic studies, and supporting real-time popu-lation estimation, significantly reducing time and costs compared to tradition-al methods. Models developed using these technologies integrate various factors to assess and manage public health risks, aiding the authorities and decision-makers (Catry et al. 2016; Potić et al. 2023; Singh and Sisodia 2019; Ste-venson, Mues, and Bravo 2022).Remote sensing technologies via satellite and aerial aeroplane/UAV im-agery are transforming urban planning and demographic studies, offering tools that significantly surpass traditional methods in scope and capability. LiDAR technology provides detailed three-di-mensional elevation maps and is piv-otal in capturing urban and rural areas’ complex topography and structure. This high-resolution data is crucial for planning infrastructure and housing developments, enhancing socio-eco-nomic analysis. Moreover, integrating LiDAR data with other demographic features affords a more comprehensive view of urban environments, which aids informed decision-making and policy development.Similarly, UAVs provide detailed aerial views and high-resolution data essen-tial for urban modelling and planning, greatly enhancing spatial planning and knowledge of territories. UAVs facilitate rapid data collection over areas of inter-est, significantly reducing the time and costs associated with traditional survey methods. This technology is beneficial for creating detailed 3D models of ur-ban areas, supporting large-scale urban planning and studies (Tenedório et al. 2016). Additionally, the UAV technology supports the dynamic monitoring of ur-ban development, allowing for real-time insights into demographic changes and urban extension, making it an invaluable tool in urban planning and development measures (Preethi Latha et al. 2019). This technology also facilitates enhanced population dynamics mapping, critical for urban management and planning in rapidly changing environments, and offers insights into the evolving legal 170 | Osvrti i komentari: Integrating advanced technologies for enhanced demographic research and planninghttps://doi.org/10.59954/stnv.563When applied to population estima-tion, remote sensing data demonstrate an enviable accuracy comparable to tra-ditional methods, and offer the advan-tage of more frequent and cost-effective updates. High-resolution remote sensing data can enable a detailed analysis of population distribution on a fine scale. Integrating remote sensing data with traditional census data allows pol-icymakers to significantly improve ur-ban planning, census operations, and resource allocation. Combining the data facilitates the creation of more detailed and dynamic urban models, thus improving urban planning deci-sion-making. By merging data from var-ious sources, such as satellite imagery, mobile data, and traditional surveys, policymakers can enhance the planning of infrastructure projects, urban renew-al, and land use changes, thereby sup-porting sustainable urban development (Hensel and Bier 2022). In the context of emergency response in urbanisation, demography, and popu-lation protection, spatial information is crucial, primarily through remote sensing and advanced GIS processing. Identifying and integrating informal structures into urban planning processes significantly enhances risk management and sustainable development. Mapping informal settlements in the areas sus-ceptible to natural hazards, including floods, landslides, and forest fires, al-lows urban planners and demographers to anticipate and mitigate risks effective-ly, ensuring a safer and more resilient urban environment (Šimunić and Potić 2021). Similarly, detecting, mapping and analysing unexploded ordnance’s (UXO) effects on the environment us-ing optical satellite imagery and digital terrain models via complex GIS analysis, facilitate targeted demining operations and regulatory framework concerning its use, ensuring that urban planning integrates the latest technological ap-proaches and complies with local and international standards (Noor and Rosni 2017; Zhao et al. 2021).Modern remote sensing technol-ogies offer broader coverage, high-er frequency, and potentially lower costs than traditional population cen-sus methods. These technologies pro-vide broader spatial coverage for pop-ulation estimation, which is especially beneficial in remote areas, or where conducting traditional census surveys is challenging. Using high-resolution satellite imagery to estimate popula-tion densities in the regions with poor transportation and communication in-frastructure enables effective planning and resource allocation without the high costs and logistical complexities associated with door-to-door survey methods. This approach is particularly crucial in rapidly urbanising regions, or in contexts requiring up-to-date demo-graphic data for emergency response and development planning (Yagoub et al. 2024). Furthermore, the integra-tion of machine learning with remote sensing data for population estimation shows promising results, offering de-tailed insights comparable with tra-ditional census data, but with added granularity and frequency (Robinson, Hohman, and Dilkina 2017).Integrating remote sensing data with traditional census data can further enhance demographic analyses and resource management. Such integra-tion can be effectively implemented by using a multi-criteria spatial decision support system, where satellite imagery integrated with census data aids in land use planning and conflict resolution (De Marinis et al. 2018).I. Potić  | 171STANOVNIŠTVO, 2024, 62(1), 169–173CONCLUSIONCombining advanced remote sensing technologies with traditional demo-graphic methods offers transformative potential for urban planning and public health. By enabling high-resolution map-ping and dynamic monitoring of demo-graphic changes, these technologies provide policymakers with robust tools for making informed decisions. Howev-er, challenges such as data integration, resolution limitations, and the need for specialised skills must be addressed to fully leverage these technologies in demographic research. Future efforts should focus on developing interdis-ciplinary approaches and enhancing data integration frameworks to support sustainable urban development and ef-fective resource management.This review not only highlights the capabilities of modern remote sensing in demographic research, but also un-derscores the necessity for continued innovation and integration of techno-logical advancements in urban planning processes.Ivan Potić Military Geographical Institute –  “General Stevan Bošković”, Belgrade, SerbiaCorrespondence:Ivan Potić, Military Geographical Institute – “General Stevan Bošković”, Mije Kovačevića 5, 11000 Belgrade, SerbiaEmail: ipotic@gmail.comand resource allocation. This approach enables authorities to first address the most hazardous zones, reducing risks to human populations. GIS analyses reveal high-risk areas with a concentration of hazardous zones, supporting effective prioritisation of protection efforts. En-vironmental impact assessments further evaluate potential contamination of soil and water sources by UXO com-ponents, including depleted uranium. This comprehensive evaluation aids in understanding long-term environmental risks and informs strategies for envi-ronmental remediation and protection (Potić et al. 2023).However, remote sensing technolo-gies are not without limitations. They often face challenges such as spatial and temporal resolution limitations, which can restrict the effectiveness of the data for dynamic population analysis and ur-ban planning (Liu et al. 2023). Accuracy and reliability issues may arise due to atmospheric conditions such as cloud cover and lighting, which can obscure and distort the imagery used in popula-tion estimates. Additionally, the reliance on ancillary data for calibration, such as ground truth data from surveys, may not always be up-to-date or available, par-ticularly in remote or conflict-affected regions (Yang et al. 2019). The need for advanced analytical techniques and soft-ware also poses a barrier in the regions lacking technological infrastructure or technical expertise.ACKNOWLEDGEMENTSThis review paper is part of Project 1.16/2024 of the Ministry of Defense and the Serbian Army.172 | Osvrti i komentari: Integrating advanced technologies for enhanced demographic research and planninghttps://doi.org/10.59954/stnv.563REFERENCESCatry, T., Li, Z., Roux, E., Herreteau, V., Revillion, C., & Dessay, N. (2016). Fusion of SAR and Optical Imagery for Studying the Eco-Epidemiology of Vector-Borne Diseases in Tropical Countries (Vol. 740, 8). Paper presented at Living Planet Symposium, Prague: ESA-SP. https://ui.adsabs.harvard.edu/abs/2016ESASP.740E...8C. Accessed 12 May 2024De Marinis, P., Manfron, G., Sali, C., Provolo, G., Facchi, A., & Sali, G. (2018). INTEGRATING REMOTE SENSING AND CENSUS INFORMATION FOR LAND SECURING IN NORD KIVU, DRC. Journal of Universities and international development Cooperation, (1), 288–310.  https://air.unimi.it/retrieve/dfa8b9a1-6019-748b-e053-3a05fe0a3a96/Paper_CUCS2017_DRC_SDT_final.pdfHensel, M., & Bier, H. (2022). Interdisciplinary Data-integrated Approaches. SPOOL, 9(1), 3–4. https://doi.org/10.47982/spool.2022.1.00Liu, C., Chen, Y., Wei, Y., & Chen, F. (2023). Spatial Population Distribution Data Disaggregation Based on SDGSAT-1 Nighttime Light and Land Use Data Using Guilin, China, as an Example. Remote Sensing, 15(11), 2926. https://doi.org/10.3390/rs15112926Noor, N., & Rosni, N. A. (2017, June). The evolution of UAVs applications in urban planning. Coordinates, XIII(06), 36–40. https://mycoordinates.org/the-evolution-of-uavs-applications-in-urban-planning/Potić, I., Komazec, N., Mihajlović, L., Milić, A., & Bakrač, S. (2023). Risk management of unexploded ordnance in the Republic of Serbia for environmental protection: Borovac case study. 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In Back to the Sense of the City: International Monograph Book (1118–1128). Paper presented at Virtual City and Territory, Centre de Política de Sòl i Valoracions. https://doi.org/10.5821/ctv.8147I. Potić  | 173STANOVNIŠTVO, 2024, 62(1), 169–173Yagoub, M. M., Tesfaldet, Y. T., AlSumaiti, T., Al Hosani, N., & Elmubarak, M. G. (2024). Estimating population density using open-access satellite images and geographic information system: Case of Al Ain city, UAE. Remote Sensing Applications: Society and Environment, 33, 101122. https://doi.org/10.1016/j.rsase.2023.101122Yang, X., Ye, T., Zhao, N., Chen, Q., Yue, W., Qi, J., … Jia, P. (2019). Population Mapping with Multisensor Remote Sensing Images and Point-Of-Interest Data. Remote Sensing, 11(5), 574. https://doi.org/10.3390/rs11050574Zhao, X., Zhou, Y., Chen, W., Li, X., Li, X., & Li, D. (2021). Mapping hourly population dynamics using remotely sensed and geospatial data: a case study in Beijing, China. GIScience & Remote Sensing, 58(5), 717–732. https://doi.org/10.1080/15481603.2021.1935128Data Availability StatementData sharing not applicable to this article as no datasets were generated or analysed.How to cite: Potić, I. (2024). Integrating Advanced Technologies for Enhanced Demographic Research and Urban Planning. Stanovništvo, 61(2), 169–173. https://doi.org/10.59954/stnv.628

Integrating advanced technologies for enhanced demographic research and urban planning

Potić, Ivan

Integrisanje naprednih tehnologija u cilju unapređenja demografskih istraživanja i urbanističkog planiranja

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Integrating advanced technologies for enhanced demographic research and urban planning

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