Implementation of rapid application development for spatio-temporal database management
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Published:
Feb 28, 2024
Keywords:
RAD, Spatial, Temporal, Database, Management
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Informtion System
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Abstract
This study aims to investigate the application of Rapid Application Development (RAD) in developing a spatio-temporal database management system, focusing on a case study in North Halmahera Regency. The primary objective is to assess the effectiveness of RAD in expediting the development process and enhancing the adaptability of the system to the dynamic spatial data requirements in the region. The methodology involves iterative development cycles, encompassing requirements planning, user design, construction, and cutover phases. The results demonstrate the successful implementation of RAD principles, showcasing accelerated development timelines and flexibility in accommodating changes. The system, tailored to the specific needs of North Halmahera, proves to be a valuable tool for urban planning, land management, and decision-making. In conclusion, using RAD to develop the spatio-temporal database management system presents a promising approach for swiftly adapting to evolving spatial data demands, ultimately contributing to more effective and responsive governance in North Halmahera Regency
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How to Cite
Singgalen, Y. A. (2024) “Implementation of rapid application development for spatio-temporal database management”, Jurnal Mantik, 7(4), pp. 2974-2984. doi: 10.35335/mantik.v7i4.4525.
References
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Li, J., Huang, X., Tu, L., Zhang, T., & Wang, L. (2022). A review of building detection from very high resolution optical remote sensing images. GIScience and Remote Sensing, 59(1), 1199–1225. https://doi.org/10.1080/15481603.2022.2101727
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Nuraini, L., Nugraha, A. S. A., Yanti, R. A., & Janah, L. (2022). Comparison Normalized Dryness Built-Up Index (NDBI) with Enhanced Built-Up and Bareness Index (EBBI) for Identification Urban in Buleleng Sub-District. Media Komunikasi FPIPS, 21(1), 74–82. https://doi.org/10.23887/mkfis.v21i1.43007
Pamungkas, S. (2023). Analysis Of Vegetation Index For Ndvi, Evi-2, And Savi For Mangrove Forest Density Using Google Earth Engine In Lembar Bay, Lombok Island. IOP Conference Series: Earth and Environmental Science, 1–9. https://doi.org/10.1088/1755-1315/1127/1/012034
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Sjoukema, J. W., Samia, J., Bregt, A. K., & Crompvoets, J. (2021). Governance interactions of spatial data infrastructures: an agent-based modelling approach. International Journal of Digital Earth, 14(6), 696–713. https://doi.org/10.1080/17538947.2020.1868585
Sun, C., Li, J., Liu, Y., Cao, L., Zheng, J., Yang, Z., Ye, J., & Li, Y. (2022). Ecological quality assessment and monitoring using a time-series remote sensing-based ecological index (ts-RSEI). GIScience and Remote Sensing, 59(1), 1793–1816. https://doi.org/10.1080/15481603.2022.2138010
Torres, Y., Martínez-Cuevas, S., Molina-Palacios, S., Arranz, J. J., & Arredondo, Á. (2023). Using remote sensing for exposure and seismic vulnerability evaluation: is it reliable? GIScience and Remote Sensing, 60(1). https://doi.org/10.1080/15481603.2023.2196162
Wang, S., Li, G., Yu, W., & Ma, Y. (2022). Requirement-driven remote sensing metadata planning and online acquisition method for large-scale heterogeneous data. Geo-Spatial Information Science, 25(2), 169–181. https://doi.org/10.1080/10095020.2021.1994358
Weck, S., Madanipour, A., & Schmitt, P. (2022). Place-based development and spatial justice. European Planning Studies, 30(5), 791–806. https://doi.org/10.1080/09654313.2021.1928038
Wei, Y., Sun, S., Liang, D., & Jia, Z. (2022). Spatial–temporal variations of NDVI and its response to climate in China from 2001 to 2020. International Journal of Digital Earth, 15(1), 1463–1484. https://doi.org/10.1080/17538947.2022.2116118
Yao, R., Zhang, Y., Wang, L., Li, J., & Yang, Q. (2023). Reconstructed NDVI and EVI datasets in China (ReVIChina) generated by a spatial-interannual reconstruction method. International Journal of Digital Earth, 16(2), 4749–4768. https://doi.org/10.1080/17538947.2023.2283492
Yu, J., Li, X., Guan, X., & Shen, H. (2022). A remote sensing assessment index for urban ecological livability and its application. Geo-Spatial Information Science, 00(00), 1–22. https://doi.org/10.1080/10095020.2022.2072775.
Bao, Y., Gui, Z., Sun, Z., An, Z., & Huang, Z. (2023). Spatial Blockchain: Enhancing Spatial Queries and Applications through Integrating Blockchain and Spatial Database Technologies. Electronics (Switzerland), 12(20), 1–19. https://doi.org/10.3390/electronics12204287
Cao, Z., Jiang, L., Yue, P., Gong, J., Hu, X., Liu, S., Tan, H., Liu, C., Shangguan, B., & Yu, D. (2023a). A large scale training sample database system for intelligent interpretation of remote sensing imagery. Geo-Spatial Information Science, 00(00), 1–20. https://doi.org/10.1080/10095020.2023.2244005
Cao, Z., Jiang, L., Yue, P., Gong, J., Hu, X., Liu, S., Tan, H., Liu, C., Shangguan, B., & Yu, D. (2023b). A large scale training sample database system for intelligent interpretation of remote sensing imagery. Geo-Spatial Information Science, 00(00), 1–20. https://doi.org/10.1080/10095020.2023.2244005
Chang, M. E., Zhao, Z. Q., Chang, H. T., & Shu, B. (2021). Urban green infrastructure health assessment, based on landsat 8 remote sensing and entropy landscape metrics. European Journal of Remote Sensing, 54(1), 417–430. https://doi.org/10.1080/22797254.2021.1948357
Degerli, B., & Çetin, M. (2022). Evaluation from Rural to Urban Scale for the Effect of NDVI-NDBI Indices on Land Surface Temperature, in Samsun, Türkiye. Turkish Journal of Agriculture - Food Science and Technology, 10(12), 2446–2452. https://doi.org/10.24925/turjaf.v10i12.2446-2452.5535
Flynn, S., Meaney, W., Leadbetter, A. M., Fisher, J. P., & Nic Aonghusa, C. (2021). Lessons from a Marine Spatial Planning data management process for Ireland. International Journal of Digital Earth, 14(2), 139–157. https://doi.org/10.1080/17538947.2020.1808720
Gupta, N., Blair, S., & Nicholas, R. (2020). What We See, What We Don’t See: Data Governance, Archaeological Spatial Databases and the Rights of Indigenous Peoples in an Age of Big Data. Journal of Field Archaeology, 45(1), S39–S50. https://doi.org/10.1080/00934690.2020.1713969
Harris, A. (2023). The expertise of urban expertise. Urban Geography, 44(3), 562–565. https://doi.org/10.1080/02723638.2022.2163102
Hussain, S., & Karuppannan, S. (2023). Land use/land cover changes and their impact on land surface temperature using remote sensing technique in district Khanewal, Punjab Pakistan. Geology, Ecology, and Landscapes, 7(1), 46–58. https://doi.org/10.1080/24749508.2021.1923272
Istiyanto, B., Unzilatirrizqi, Y. E. R. D., De Rizka Dewantoro, M., & Ahmad, R. (2022). Geographic Information System (GIS-T) database design for transportation safety system (case study: Spatial database for road transportation system in Indonesia). IOP Conference Series: Earth and Environmental Science, 1–6. https://doi.org/10.1088/1755-1315/1117/1/012023
Jitkajornwanich, K., Pant, N., Fouladgar, M., & Elmasri, R. (2020). A survey on spatial, temporal, and spatio-temporal database research and an original example of relevant applications using sql ecosystem and deep learning. Journal of Information and Telecommunication, 4(4), 524–559. https://doi.org/10.1080/24751839.2020.1774153
Li, J., Huang, X., Tu, L., Zhang, T., & Wang, L. (2022). A review of building detection from very high resolution optical remote sensing images. GIScience and Remote Sensing, 59(1), 1199–1225. https://doi.org/10.1080/15481603.2022.2101727
Lidskog, R., Standring, A., & White, J. M. (2022). Environmental expertise for social transformation: roles and responsibilities for social science. Environmental Sociology, 8(3), 255–266. https://doi.org/10.1080/23251042.2022.2048237
Ngolo, A. M. E., & Watanabe, T. (2023). Integrating geographical information systems, remote sensing, and machine learning techniques to monitor urban expansion: an application to Luanda, Angola. Geo-Spatial Information Science, 26(3), 446–464. https://doi.org/10.1080/10095020.2022.2066574
Nuraini, L., Nugraha, A. S. A., Yanti, R. A., & Janah, L. (2022). Comparison Normalized Dryness Built-Up Index (NDBI) with Enhanced Built-Up and Bareness Index (EBBI) for Identification Urban in Buleleng Sub-District. Media Komunikasi FPIPS, 21(1), 74–82. https://doi.org/10.23887/mkfis.v21i1.43007
Pamungkas, S. (2023). Analysis Of Vegetation Index For Ndvi, Evi-2, And Savi For Mangrove Forest Density Using Google Earth Engine In Lembar Bay, Lombok Island. IOP Conference Series: Earth and Environmental Science, 1–9. https://doi.org/10.1088/1755-1315/1127/1/012034
Radosevic, N., Duckham, M., Saiedur Rahaman, M., Ho, S., Williams, K., Hashem, T., & Tao, Y. (2023). Spatial data trusts: an emerging governance framework for sharing spatial data. International Journal of Digital Earth, 16(1), 1607–1639. https://doi.org/10.1080/17538947.2023.2200042
Singgalen, Y. A. (2023). Analisis Indeks Vegetasi dan Perancangan Sistem Monitoring Kawasan Ekowisata Mangrove Berbasis Hyper Spectral of Remote Sensing dan Design Thinking Framework. Journal of Information System Research, 5(1), 1–13. https://doi.org/10.47065/josh.v5i1.4005
Singgalen, Y. A., & Manongga, D. (2022). Monitoring of Mangrove Ecotourism Area Using Ndvi, Ndwi, and Cmri in Dodola Island, Morotai Island Regency, Indonesia. Jurnal Ilmu Dan Teknologi Kelautan Tropis, 14(1), 95–108. https://doi.org/10.29244/jitkt.v14i1.37605
Sjoukema, J. W., Samia, J., Bregt, A. K., & Crompvoets, J. (2021). Governance interactions of spatial data infrastructures: an agent-based modelling approach. International Journal of Digital Earth, 14(6), 696–713. https://doi.org/10.1080/17538947.2020.1868585
Sun, C., Li, J., Liu, Y., Cao, L., Zheng, J., Yang, Z., Ye, J., & Li, Y. (2022). Ecological quality assessment and monitoring using a time-series remote sensing-based ecological index (ts-RSEI). GIScience and Remote Sensing, 59(1), 1793–1816. https://doi.org/10.1080/15481603.2022.2138010
Torres, Y., Martínez-Cuevas, S., Molina-Palacios, S., Arranz, J. J., & Arredondo, Á. (2023). Using remote sensing for exposure and seismic vulnerability evaluation: is it reliable? GIScience and Remote Sensing, 60(1). https://doi.org/10.1080/15481603.2023.2196162
Wang, S., Li, G., Yu, W., & Ma, Y. (2022). Requirement-driven remote sensing metadata planning and online acquisition method for large-scale heterogeneous data. Geo-Spatial Information Science, 25(2), 169–181. https://doi.org/10.1080/10095020.2021.1994358
Weck, S., Madanipour, A., & Schmitt, P. (2022). Place-based development and spatial justice. European Planning Studies, 30(5), 791–806. https://doi.org/10.1080/09654313.2021.1928038
Wei, Y., Sun, S., Liang, D., & Jia, Z. (2022). Spatial–temporal variations of NDVI and its response to climate in China from 2001 to 2020. International Journal of Digital Earth, 15(1), 1463–1484. https://doi.org/10.1080/17538947.2022.2116118
Yao, R., Zhang, Y., Wang, L., Li, J., & Yang, Q. (2023). Reconstructed NDVI and EVI datasets in China (ReVIChina) generated by a spatial-interannual reconstruction method. International Journal of Digital Earth, 16(2), 4749–4768. https://doi.org/10.1080/17538947.2023.2283492
Yu, J., Li, X., Guan, X., & Shen, H. (2022). A remote sensing assessment index for urban ecological livability and its application. Geo-Spatial Information Science, 00(00), 1–22. https://doi.org/10.1080/10095020.2022.2072775.
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