Main Article Content
Abstract
Indonesia is one of the countries with the highest level of geospatial disaster risk due to its position on the Pacific Ring of Fire and its exposure to earthquakes, tsunamis, volcanic eruptions, floods, and landslides. The increasing complexity and frequency of disasters, exacerbated by climate change, demands a faster, more accurate, and integrated monitoring system. However, previous studies have focused more on the technical aspects of disaster monitoring without comprehensively examining the strategic role of satellite technology in strengthening Indonesia's national resilience. This gap is the basis for this study. This study aims to analyze the contribution of satellite technology in disaster mitigation and assess how satellite data integration can strengthen national resilience to geospatial threats. The method used is a systematic literature review of reputable international publications from 2014 to 2025 that discuss remote sensing technology, InSAR, damage mapping, early warning systems, and geospatial integration for disaster risk management. The results of the study show that satellite technology plays an important role in three main aspects: (1) real-time disaster monitoring through multisensor data capable of covering a wide area; (2) improving the accuracy of early warning systems for various geospatial disasters; and (3) strengthening national resilience through support for damage mapping, rapid response, strategic decision-making, and inter-agency coordination. The novelty of this research lies in the development of an integrative synthesis that links the use of satellite data with Indonesia's national resilience framework, as well as the affirmation of the need to integrate satellite technology into national disaster management policies. These findings have important implications for strengthening modern mitigation systems and adapting to the escalation of geospatial risks in the future.
Keywords
Article Details
Copyright (c) 2025 Mulya Afriyanto, Asep Adang Supriyadi, Syachrul Arief, Dangan Waluyo

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
The journal allows the author(s) to hold the copyright without restrictions.
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
References
- Ajmar, A., Annunziato, A., Boccardo, P., Tonolo, F. G., & Wania, A. (2019). Tsunami Modeling and Satellite-Based Emergency Mapping: Workflow Integration opportunities. Geosciences, 9(7), 314. https://doi.org/10.3390/geosciences9070314
- Alamdar, F., Kalantari, M., & Rajabifard, A. (2015). Towards multi-agency sensor information integration for disaster management. Computers Environment and Urban Systems, 56, 68–85. https://doi.org/10.1016/j.compenvurbsys.2015.11.005
- Baraldo, M., & Di Giuseppantonio Di Franco, P. (2024). Place-centred emerging Technologies for Disaster Management: a Scoping Review. International Journal of Disaster Risk Reduction, 112, 104782. https://doi.org/10.1016/j.ijdrr.2024.104782
- Bilașco, Ș., Hognogi, G., Roșca, S., Pop, A., Iuliu, V., Fodorean, I., Marian-Potra, A., & Sestras, P. (2022). Flash flood risk assessment and mitigation in Digital-ERA Governance using unmanned aerial vehicle and GIS spatial analyses Case study: Small River Basins. Remote Sensing, 14(10), 2481. https://doi.org/10.3390/rs14102481
- Chen, S., Huang, W., Chen, Y., & Feng, M. (2021). An Adaptive Thresholding Approach toward Rapid Flood Coverage Extraction from Sentinel-1 SAR Imagery. Remote Sensing, 13(23), 4899. https://doi.org/10.3390/rs13234899
- Chen, Z., & Zhao, S. (2022). Automatic monitoring of surface water dynamics using Sentinel-1 and Sentinel-2 data with Google Earth Engine. International Journal of Applied Earth Observation and Geoinformation, 113, 103010. https://doi.org/10.1016/j.jag.2022.103010
- Cozannet, G. L., Kervyn, M., Russo, S., Speranza, C. I., Ferrier, P., Foumelis, M., Lopez, T., & Modaressi, H. (2020). Space-Based Earth observations for disaster risk management. Surveys in Geophysics, 41(6), 1209–1235. https://doi.org/10.1007/s10712-020-09586-5
- Delmonteil, F., & Rancourt, M. (2017). The role of satellite technologies in relief logistics. Journal of Humanitarian Logistics and Supply Chain Management, 7(1), 57–78. https://doi.org/10.1108/jhlscm-07-2016-0031
- Diehr, J., Ogunyiola, A., & Dada, O. (2025). Artificial intelligence and machine learning-powered GIS for proactive disaster resilience in a changing climate. Annals of GIS, 1–14. https://doi.org/10.1080/19475683.2025.2473596
- Ding, Y., Fan, Y., Du, Z., Zhu, Q., Wang, W., Liu, S., & Lin, H. (2014). An integrated geospatial information service system for disaster management in China. International Journal of Digital Earth, 8(11), 918–945. https://doi.org/10.1080/17538947.2014.955540
- Dritsas, E., & Trigka, M. (2025). Remote sensing and Geospatial analysis in the Big Data Era: A survey. Remote Sensing, 17(3), 550. https://doi.org/10.3390/rs17030550
- Duan, X., Jahangir, Z., Lu, L., Yasir, Q. M., Aslam, R. W., Ahmed, R., Naz, I., Liaquat, M. A., Jamil, A., & Alzahrani, H. (2025). Enhanced Land-Surface Temperature Recovery through Multi-Sensor Data Fusion and Spatial Resolution Improvement. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 1–18. https://doi.org/10.1109/jstars.2025.3548428
- Fan, Y., Wen, Q., & Chen, S. (2012). Engineering survey of the Environment and Disaster Monitoring and Forecasting Small Satellite Constellation. International Journal of Digital Earth, 5(3), 217–227. https://doi.org/10.1080/17538947.2011.648540
- Fang, Z., Yue, P., Zhang, M., Xie, J., Wu, D., & Jiang, L. (2023). A service-oriented collaborative approach to disaster decision support by integrating geospatial resources and task chain. International Journal of Applied Earth Observation and Geoinformation, 117, 103217. https://doi.org/10.1016/j.jag.2023.103217
- Fischer-Preßler, D., Bonaretti, D., & Bunker, D. (2024). Digital transformation in disaster management: A literature review. The Journal of Strategic Information Systems, 33(4), 101865. https://doi.org/10.1016/j.jsis.2024.101865
- Fitriani, W. R., Sutanto, J., Handayani, P. W., & Hidayanto, A. N. (2023). User Compliance with the Health Emergency and Disaster Management System: Systematic Literature review. Journal of Medical Internet Research, 25, e41168. https://doi.org/10.2196/41168
- Hossin, M. A., Chen, L., Asante, I. O., Boadi, E. A., & Adu-Yeboah, S. S. (2023). Climate change and COP26: role of information technologies in disaster management and resilience. Environment Development and Sustainability. https://doi.org/10.1007/s10668-023-04134-8
- Hu, L., Zhang, C., Zhang, M., Shi, Y., Lu, J., & Fang, Z. (2023). Enhancing FAIR data Services in Agricultural Disaster: A review. Remote Sensing, 15(8), 2024. https://doi.org/10.3390/rs15082024
- Ibrahim, T., & Mishra, A. (2021). A conceptual design of smart management system for flooding disaster. International Journal of Environmental Research and Public Health, 18(16), 8632. https://doi.org/10.3390/ijerph18168632
- Kaku, K. (2018). Satellite remote sensing for disaster management support: A holistic and staged approach based on case studies in Sentinel Asia. International Journal of Disaster Risk Reduction, 33, 417–432. https://doi.org/10.1016/j.ijdrr.2018.09.015
- Khan, M. T. I., Anwar, S., & Batool, Z. (2022). The role of infrastructure, socio-economic development, and food security to mitigate the loss of natural disasters. Environmental Science and Pollution Research, 29(35), 52412–52437. https://doi.org/10.1007/s11356-022-19293-w
- Kumari, S., Agarwal, S., Agrawal, N. K., Agarwal, A., & Garg, M. C. (2024). A comprehensive review of remote sensing technologies for improved geological disaster management. Geological Journal. https://doi.org/10.1002/gj.5072
- Li, X., Xie, Y., Guo, Y., Wang, T., & Lin, T. (2025). Toward Climate-Resilient freight Systems: Measuring regional truck resilience to extreme rainfall via integrated flood demand modeling. Sustainability, 17(5), 1783. https://doi.org/10.3390/su17051783
- Liang, R., Dai, K., Xu, Q., Pirasteh, S., Li, Z., Li, T., Wen, N., Deng, J., & Fan, X. (2024). Utilizing a single-temporal full polarimetric Gaofen-3 SAR image to map coseismic landslide inventory following the 2017 Mw 7.0 Jiuzhaigou earthquake (China). International Journal of Applied Earth Observation and Geoinformation, 127, 103657. https://doi.org/10.1016/j.jag.2024.103657
- Liu, J., Zhang, J., Tian, Q., & Wu, B. (2024). Resilience evaluation of multi-feature system based on hidden Markov model. Reliability Engineering & System Safety, 253, 110561. https://doi.org/10.1016/j.ress.2024.110561
- Peixoto, J. P. J., Costa, D. G., Portugal, P., & Vasques, F. (2023). A geospatial dataset of urban infrastructure for emergency response in Portugal. Data in Brief, 50, 109593. https://doi.org/10.1016/j.dib.2023.109593
- Prasertsoong, N., & Puttanapong, N. (2024). An integrated framework for satellite-based flood mapping and socioeconomic risk analysis: A case of Thailand. Progress in Disaster Science, 100393. https://doi.org/10.1016/j.pdisas.2024.100393
- Prasetyo, A., Sumarno, S., Jayaputra, A., Benedictus, M., Murni, R., Nainggolan, T., Purwasantana, D., Miftah, M., Wahab, N., Taruna, M. M., & Wibowo, A. (2024). Critical communication of disaster preparedness areas for informational strategies in disaster management in Indonesia. Progress in Disaster Science, 100368. https://doi.org/10.1016/j.pdisas.2024.100368
- Robinson, T. R., Rosser, N., & Walters, R. J. (2019). The spatial and temporal influence of cloud cover on Satellite-Based Emergency Mapping of earthquake disasters. Scientific Reports, 9(1). https://doi.org/10.1038/s41598-019-49008-0
- Rokvić, V., & Stanojević, P. (2024). Disaster Risk reduction Education through Digital Technologies in the context of Education for Sustainable Development: A Curricula Analysis of security and defense studies in Serbia. Sustainability, 16(22), 9777. https://doi.org/10.3390/su16229777
- Roth, F., Tupas, M. E., Navacchi, C., Zhao, J., Wagner, W., & Bauer-Marschallinger, B. (2025). Evaluating the robustness of Bayesian flood mapping with Sentinel-1 data: A multi-event validation study. Science of Remote Sensing, 100210. https://doi.org/10.1016/j.srs.2025.100210
- Sarker, M. N. I., Peng, Y., Yiran, C., & Shouse, R. C. (2020). Disaster resilience through big data: Way to environmental sustainability. International Journal of Disaster Risk Reduction, 51, 101769. https://doi.org/10.1016/j.ijdrr.2020.101769
- Singla, A., & Agrawal, R. (2023). iStage: a deep learning based framework to determine the stage of disaster management cycle from a social media message. Global Knowledge Memory and Communication. https://doi.org/10.1108/gkmc-10-2022-0239
- Shukla, A., Adwani, N., Choudhury, T., & Dewangan, B. (2021). Geospatial analysis for natural disaster estimation through arduino and node MCU approach. GeoJournal, 88(S1), 29–45. https://doi.org/10.1007/s10708-021-10496-1
- Voigt, S., Giulio-Tonolo, F., Lyons, J., Kučera, J., Jones, B., Schneiderhan, T., Platzeck, G., Kaku, K., Hazarika, M. K., Czaran, L., Li, S., Pedersen, W., James, G. K., Proy, C., Muthike, D. M., Bequignon, J., & Guha-Sapir, D. (2016). Global trends in satellite-based emergency mapping. Science, 353(6296), 247–252. https://doi.org/10.1126/science.aad8728
- Voigt, S., Kemper, T., Riedlinger, T., Kiefl, R., Scholte, K., & Mehl, H. (2007). Satellite image analysis for disaster and Crisis-Management support. IEEE Transactions on Geoscience and Remote Sensing, 45(6), 1520–1528. https://doi.org/10.1109/tgrs.2007.895830
- Wang, L., Yang, T., Wang, T., Wang, C., Li, N., & Li, X. (2025). Technical Design of a Low-Latitude Satellite Constellation for Ocean Observation with a Focus on Hainan Province, China. Sensors, 25(6), 1710. https://doi.org/10.3390/s25061710
- Wang, Z., Wang, X., Wu, W., & Li, G. (2023). Continuous change detection of flood extents with multisource heterogeneous satellite image time series. IEEE Transactions on Geoscience and Remote Sensing, 61, 1–18. https://doi.org/10.1109/tgrs.2023.3281792
- Wania, A., Joubert-Boitat, I., Dottori, F., Kalas, M., & Salamon, P. (2021). Increasing timeliness of Satellite-Based flood mapping using early warning systems in the Copernicus Emergency Management Service. Remote Sensing, 13(11), 2114. https://doi.org/10.3390/rs13112114
- Wormenor, S. D., & Asibey, M. O. (2024). Digital technologies for climate-induced disaster risk reduction and management in Ghana: Applicability and operational challenges. Land Use Policy, 150, 107459. https://doi.org/10.1016/j.landusepol.2024.107459
- Yulianto, E., Utari, P., & Satyawan, I. A. (2020). Communication technology support in disaster-prone areas: Case study of earthquake, tsunami and liquefaction in Palu, Indonesia. International Journal of Disaster Risk Reduction, 45, 101457. https://doi.org/10.1016/j.ijdrr.2019.101457
- Zhang, Y., Chen, W., Huang, B., Zhang, Z., Li, J., Gao, R., Wang, K., & Hu, C. (2024). An event logic graph for geographic environment observation planning in disaster chain monitoring. International Journal of Applied Earth Observation and Geoinformation, 134, 104220. https://doi.org/10.1016/j.jag.2024.104220
References
Ajmar, A., Annunziato, A., Boccardo, P., Tonolo, F. G., & Wania, A. (2019). Tsunami Modeling and Satellite-Based Emergency Mapping: Workflow Integration opportunities. Geosciences, 9(7), 314. https://doi.org/10.3390/geosciences9070314
Alamdar, F., Kalantari, M., & Rajabifard, A. (2015). Towards multi-agency sensor information integration for disaster management. Computers Environment and Urban Systems, 56, 68–85. https://doi.org/10.1016/j.compenvurbsys.2015.11.005
Baraldo, M., & Di Giuseppantonio Di Franco, P. (2024). Place-centred emerging Technologies for Disaster Management: a Scoping Review. International Journal of Disaster Risk Reduction, 112, 104782. https://doi.org/10.1016/j.ijdrr.2024.104782
Bilașco, Ș., Hognogi, G., Roșca, S., Pop, A., Iuliu, V., Fodorean, I., Marian-Potra, A., & Sestras, P. (2022). Flash flood risk assessment and mitigation in Digital-ERA Governance using unmanned aerial vehicle and GIS spatial analyses Case study: Small River Basins. Remote Sensing, 14(10), 2481. https://doi.org/10.3390/rs14102481
Chen, S., Huang, W., Chen, Y., & Feng, M. (2021). An Adaptive Thresholding Approach toward Rapid Flood Coverage Extraction from Sentinel-1 SAR Imagery. Remote Sensing, 13(23), 4899. https://doi.org/10.3390/rs13234899
Chen, Z., & Zhao, S. (2022). Automatic monitoring of surface water dynamics using Sentinel-1 and Sentinel-2 data with Google Earth Engine. International Journal of Applied Earth Observation and Geoinformation, 113, 103010. https://doi.org/10.1016/j.jag.2022.103010
Cozannet, G. L., Kervyn, M., Russo, S., Speranza, C. I., Ferrier, P., Foumelis, M., Lopez, T., & Modaressi, H. (2020). Space-Based Earth observations for disaster risk management. Surveys in Geophysics, 41(6), 1209–1235. https://doi.org/10.1007/s10712-020-09586-5
Delmonteil, F., & Rancourt, M. (2017). The role of satellite technologies in relief logistics. Journal of Humanitarian Logistics and Supply Chain Management, 7(1), 57–78. https://doi.org/10.1108/jhlscm-07-2016-0031
Diehr, J., Ogunyiola, A., & Dada, O. (2025). Artificial intelligence and machine learning-powered GIS for proactive disaster resilience in a changing climate. Annals of GIS, 1–14. https://doi.org/10.1080/19475683.2025.2473596
Ding, Y., Fan, Y., Du, Z., Zhu, Q., Wang, W., Liu, S., & Lin, H. (2014). An integrated geospatial information service system for disaster management in China. International Journal of Digital Earth, 8(11), 918–945. https://doi.org/10.1080/17538947.2014.955540
Dritsas, E., & Trigka, M. (2025). Remote sensing and Geospatial analysis in the Big Data Era: A survey. Remote Sensing, 17(3), 550. https://doi.org/10.3390/rs17030550
Duan, X., Jahangir, Z., Lu, L., Yasir, Q. M., Aslam, R. W., Ahmed, R., Naz, I., Liaquat, M. A., Jamil, A., & Alzahrani, H. (2025). Enhanced Land-Surface Temperature Recovery through Multi-Sensor Data Fusion and Spatial Resolution Improvement. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 1–18. https://doi.org/10.1109/jstars.2025.3548428
Fan, Y., Wen, Q., & Chen, S. (2012). Engineering survey of the Environment and Disaster Monitoring and Forecasting Small Satellite Constellation. International Journal of Digital Earth, 5(3), 217–227. https://doi.org/10.1080/17538947.2011.648540
Fang, Z., Yue, P., Zhang, M., Xie, J., Wu, D., & Jiang, L. (2023). A service-oriented collaborative approach to disaster decision support by integrating geospatial resources and task chain. International Journal of Applied Earth Observation and Geoinformation, 117, 103217. https://doi.org/10.1016/j.jag.2023.103217
Fischer-Preßler, D., Bonaretti, D., & Bunker, D. (2024). Digital transformation in disaster management: A literature review. The Journal of Strategic Information Systems, 33(4), 101865. https://doi.org/10.1016/j.jsis.2024.101865
Fitriani, W. R., Sutanto, J., Handayani, P. W., & Hidayanto, A. N. (2023). User Compliance with the Health Emergency and Disaster Management System: Systematic Literature review. Journal of Medical Internet Research, 25, e41168. https://doi.org/10.2196/41168
Hossin, M. A., Chen, L., Asante, I. O., Boadi, E. A., & Adu-Yeboah, S. S. (2023). Climate change and COP26: role of information technologies in disaster management and resilience. Environment Development and Sustainability. https://doi.org/10.1007/s10668-023-04134-8
Hu, L., Zhang, C., Zhang, M., Shi, Y., Lu, J., & Fang, Z. (2023). Enhancing FAIR data Services in Agricultural Disaster: A review. Remote Sensing, 15(8), 2024. https://doi.org/10.3390/rs15082024
Ibrahim, T., & Mishra, A. (2021). A conceptual design of smart management system for flooding disaster. International Journal of Environmental Research and Public Health, 18(16), 8632. https://doi.org/10.3390/ijerph18168632
Kaku, K. (2018). Satellite remote sensing for disaster management support: A holistic and staged approach based on case studies in Sentinel Asia. International Journal of Disaster Risk Reduction, 33, 417–432. https://doi.org/10.1016/j.ijdrr.2018.09.015
Khan, M. T. I., Anwar, S., & Batool, Z. (2022). The role of infrastructure, socio-economic development, and food security to mitigate the loss of natural disasters. Environmental Science and Pollution Research, 29(35), 52412–52437. https://doi.org/10.1007/s11356-022-19293-w
Kumari, S., Agarwal, S., Agrawal, N. K., Agarwal, A., & Garg, M. C. (2024). A comprehensive review of remote sensing technologies for improved geological disaster management. Geological Journal. https://doi.org/10.1002/gj.5072
Li, X., Xie, Y., Guo, Y., Wang, T., & Lin, T. (2025). Toward Climate-Resilient freight Systems: Measuring regional truck resilience to extreme rainfall via integrated flood demand modeling. Sustainability, 17(5), 1783. https://doi.org/10.3390/su17051783
Liang, R., Dai, K., Xu, Q., Pirasteh, S., Li, Z., Li, T., Wen, N., Deng, J., & Fan, X. (2024). Utilizing a single-temporal full polarimetric Gaofen-3 SAR image to map coseismic landslide inventory following the 2017 Mw 7.0 Jiuzhaigou earthquake (China). International Journal of Applied Earth Observation and Geoinformation, 127, 103657. https://doi.org/10.1016/j.jag.2024.103657
Liu, J., Zhang, J., Tian, Q., & Wu, B. (2024). Resilience evaluation of multi-feature system based on hidden Markov model. Reliability Engineering & System Safety, 253, 110561. https://doi.org/10.1016/j.ress.2024.110561
Peixoto, J. P. J., Costa, D. G., Portugal, P., & Vasques, F. (2023). A geospatial dataset of urban infrastructure for emergency response in Portugal. Data in Brief, 50, 109593. https://doi.org/10.1016/j.dib.2023.109593
Prasertsoong, N., & Puttanapong, N. (2024). An integrated framework for satellite-based flood mapping and socioeconomic risk analysis: A case of Thailand. Progress in Disaster Science, 100393. https://doi.org/10.1016/j.pdisas.2024.100393
Prasetyo, A., Sumarno, S., Jayaputra, A., Benedictus, M., Murni, R., Nainggolan, T., Purwasantana, D., Miftah, M., Wahab, N., Taruna, M. M., & Wibowo, A. (2024). Critical communication of disaster preparedness areas for informational strategies in disaster management in Indonesia. Progress in Disaster Science, 100368. https://doi.org/10.1016/j.pdisas.2024.100368
Robinson, T. R., Rosser, N., & Walters, R. J. (2019). The spatial and temporal influence of cloud cover on Satellite-Based Emergency Mapping of earthquake disasters. Scientific Reports, 9(1). https://doi.org/10.1038/s41598-019-49008-0
Rokvić, V., & Stanojević, P. (2024). Disaster Risk reduction Education through Digital Technologies in the context of Education for Sustainable Development: A Curricula Analysis of security and defense studies in Serbia. Sustainability, 16(22), 9777. https://doi.org/10.3390/su16229777
Roth, F., Tupas, M. E., Navacchi, C., Zhao, J., Wagner, W., & Bauer-Marschallinger, B. (2025). Evaluating the robustness of Bayesian flood mapping with Sentinel-1 data: A multi-event validation study. Science of Remote Sensing, 100210. https://doi.org/10.1016/j.srs.2025.100210
Sarker, M. N. I., Peng, Y., Yiran, C., & Shouse, R. C. (2020). Disaster resilience through big data: Way to environmental sustainability. International Journal of Disaster Risk Reduction, 51, 101769. https://doi.org/10.1016/j.ijdrr.2020.101769
Singla, A., & Agrawal, R. (2023). iStage: a deep learning based framework to determine the stage of disaster management cycle from a social media message. Global Knowledge Memory and Communication. https://doi.org/10.1108/gkmc-10-2022-0239
Shukla, A., Adwani, N., Choudhury, T., & Dewangan, B. (2021). Geospatial analysis for natural disaster estimation through arduino and node MCU approach. GeoJournal, 88(S1), 29–45. https://doi.org/10.1007/s10708-021-10496-1
Voigt, S., Giulio-Tonolo, F., Lyons, J., Kučera, J., Jones, B., Schneiderhan, T., Platzeck, G., Kaku, K., Hazarika, M. K., Czaran, L., Li, S., Pedersen, W., James, G. K., Proy, C., Muthike, D. M., Bequignon, J., & Guha-Sapir, D. (2016). Global trends in satellite-based emergency mapping. Science, 353(6296), 247–252. https://doi.org/10.1126/science.aad8728
Voigt, S., Kemper, T., Riedlinger, T., Kiefl, R., Scholte, K., & Mehl, H. (2007). Satellite image analysis for disaster and Crisis-Management support. IEEE Transactions on Geoscience and Remote Sensing, 45(6), 1520–1528. https://doi.org/10.1109/tgrs.2007.895830
Wang, L., Yang, T., Wang, T., Wang, C., Li, N., & Li, X. (2025). Technical Design of a Low-Latitude Satellite Constellation for Ocean Observation with a Focus on Hainan Province, China. Sensors, 25(6), 1710. https://doi.org/10.3390/s25061710
Wang, Z., Wang, X., Wu, W., & Li, G. (2023). Continuous change detection of flood extents with multisource heterogeneous satellite image time series. IEEE Transactions on Geoscience and Remote Sensing, 61, 1–18. https://doi.org/10.1109/tgrs.2023.3281792
Wania, A., Joubert-Boitat, I., Dottori, F., Kalas, M., & Salamon, P. (2021). Increasing timeliness of Satellite-Based flood mapping using early warning systems in the Copernicus Emergency Management Service. Remote Sensing, 13(11), 2114. https://doi.org/10.3390/rs13112114
Wormenor, S. D., & Asibey, M. O. (2024). Digital technologies for climate-induced disaster risk reduction and management in Ghana: Applicability and operational challenges. Land Use Policy, 150, 107459. https://doi.org/10.1016/j.landusepol.2024.107459
Yulianto, E., Utari, P., & Satyawan, I. A. (2020). Communication technology support in disaster-prone areas: Case study of earthquake, tsunami and liquefaction in Palu, Indonesia. International Journal of Disaster Risk Reduction, 45, 101457. https://doi.org/10.1016/j.ijdrr.2019.101457
Zhang, Y., Chen, W., Huang, B., Zhang, Z., Li, J., Gao, R., Wang, K., & Hu, C. (2024). An event logic graph for geographic environment observation planning in disaster chain monitoring. International Journal of Applied Earth Observation and Geoinformation, 134, 104220. https://doi.org/10.1016/j.jag.2024.104220
