Time-based Geospatial Analysis of Night-Time Light Data and Citizen Movement Restriction During Covid-19 Period

Penulis

  • Samuel Ady Sanjaya Universitas Multimedia Nusantara
  • Melissa Indah Fianty Universitas Multimedia Nusantara

DOI:

https://doi.org/10.33379/gtech.v7i2.2397

Kata Kunci:

Analisis Geospasial, Night Time Light Data, Pembatasan Kegiatan Masyarakat

Abstrak

Pembatasan kegiatan masyarakat atau di beberapa daerah disebut juga dengan lockdown sudah banyak dijalankan oleh beberapa negara demi menekan angka penyebaran Covid-19. Dalam penelitian ini, menggunakan foto satelit di malam hari, atau biasa disebut dengan Night Time Light (NTL) Data. Setelah itu diambil sample titik koordinat sebanyak 381 tempat umum di Jakarta dan diambil datanya menggunakan dataset VIIRS Stray Light Corrected Nighttime Day/Night Band Composites Version 1 selama kurun waktu Q1 2019 sampai dengan Q2 2022. Dari hasil foto satelit ini kemudian dikonversikan ke dalam bentuk numerik, dikorelasikan dengan timeline pembatasan kegiatan masyarakat di Indonesia dan juga data mobility untuk wilayah Jakarta. Hasilnya adalah ditemukan penurunan intensitas cahaya saat memasuki masa pembatasan kegiatann masyarakat sebanyak 1% - 16% di berbagai sektor. Penurunan intensitas ini tidak berkorelasi dengan kuat dengan data mobility untuk beberapa sektor yang menunjukkan perubahan penurunan aktivitas hingga 60%.

Unduhan

Data unduhan belum tersedia.

Referensi

Alzu’bi, A., & Alsmadi, L. (2022). Monitoring deforestation in Jordan using deep semantic segmentation with satellite imagery. Ecological Informatics, 70, 101745. https://doi.org/10.1016/j.ecoinf.2022.101745

Ch, R., Martin, D. A., & Vargas, J. F. (2021). Measuring the size and growth of cities using nighttime light. Journal of Urban Economics, 125, 103254. https://doi.org/10.1016/j.jue.2020.103254

Chen, X., & Nordhaus, W. D. (2019). VIIRS Nighttime Lights in the Estimation of Cross-Sectional and Time-Series GDP. Remote Sensing, 11(9), 1057. https://doi.org/10.3390/rs11091057

Elvidge, C. D., Baugh, K. E., Zhizhin, M., & Hsu, F.-C. (2013). Why VIIRS data are superior to DMSP for mapping nighttime lights. Proceedings of the Asia-Pacific Advanced Network, 35, 62. https://doi.org/10.7125/APAN.35.7

Elvidge, C. D., Baugh, K., Zhizhin, M., Hsu, F. C., & Ghosh, T. (2017). VIIRS night-time lights. International Journal of Remote Sensing, 38(21), 5860–5879. https://doi.org/10.1080/01431161.2017.1342050

Elvidge, C. D., Zhizhin, M., Ghosh, T., Hsu, F.-C., & Taneja, J. (2021). Annual Time Series of Global VIIRS Nighttime Lights Derived from Monthly Averages: 2012 to 2019. Remote Sensing, 13(5), 922. https://doi.org/10.3390/rs13050922

Eskandari, S., & Ali Mahmoudi Sarab, S. (2022). Mapping land cover and forest density in Zagros forests of Khuzestan province in Iran: A study based on Sentinel-2, Google Earth and field data. Ecological Informatics, 70, 101727. https://doi.org/10.1016/j.ecoinf.2022.101727

Gao, S., Chen, Y., Liang, L., & Gong, A. (2020). Post-Earthquake Night-Time Light Piecewise (PNLP) Pattern Based on NPP/VIIRS Night-Time Light Data - A Case Study of the 2015 Nepal Earthquake. Remote Sensing, 12(12), 2009. https://doi.org/10.3390/rs12122009

Gibson, J., Olivia, S., & Boe-Gibson, G. (2019). A test of DMPS and VIIRS night lights data for estimating GDP and spatial inequality for rural and urban areas. 1–18.

Google. (n.d.). COVID-19 Community Mobility Reports. Retrieved July 3, 2022, from https://www.google.com/covid19/mobility/

Han, G., Zhou, T., Sun, Y., & Zhu, S. (2022). The relationship between night-time light and socioeconomic factors in China and India. PLOS ONE, 17(1), e0262503. https://doi.org/10.1371/journal.pone.0262503

Hu, T., Wang, T., Yan, Q., Chen, T., Jin, S., & Hu, J. (2022). Modeling the spatiotemporal dynamics of global electric power consumption (1992–2019) by utilizing consistent nighttime light data from DMSP-OLS and NPP-VIIRS. Applied Energy, 322, 119473. https://doi.org/10.1016/j.apenergy.2022.119473

Jakob, A., Hasibuan, S., & Fiantis, D. (2022). Empirical evidence shows that air quality changes during COVID-19 pandemic lockdown in Jakarta, Indonesia are due to seasonal variation, not restricted movements. Environmental Research, 208, 112391. https://doi.org/10.1016/j.envres.2021.112391

Lv, Q., Liu, H., Wang, J., Liu, H., & Shang, Y. (2020). Multiscale analysis on spatiotemporal dynamics of energy consumption CO2 emissions in China: Utilizing the integrated of DMSP-OLS and NPP-VIIRS nighttime light datasets. Science of The Total Environment, 703, 134394. https://doi.org/10.1016/j.scitotenv.2019.134394

Ouyang, Y., Zhang, Y., Chi, J., Sun, Q., & Du, Y. (2023). Deviations of satellite-measured sea surface salinity caused by environmental factors and their regional dependence. Remote Sensing of Environment, 285, 113411. https://doi.org/10.1016/j.rse.2022.113411

Ouyang, Z., Chen, S., Lai, Y., & Yang, X. (2022). The correlations among COVID-19, the effect of public opinion, and the systemic risks of China’s financial industries. Physica A: Statistical Mechanics and Its Applications, 600, 127518. https://doi.org/10.1016/j.physa.2022.127518

Samuel Ady, S., & Suyoto. (2022). The transformation from Pandemic to Endemic of Covid-19: Spatio-temporal Analysis of Citizen Mobility in Asia Countries. 2022 13th International Conference on Information and Communication Technology Convergence (ICTC), 420–424. https://doi.org/10.1109/ICTC55196.2022.9952506

Syuhada, K., Wibisono, A., Hakim, A., & Addini, F. (2021). Covid-19 risk data during lockdown-like policy in Indonesia. Data in Brief, 35, 106801. https://doi.org/10.1016/j.dib.2021.106801

Tveit, T., Skoufias, E., & Strobl, E. (2022). Using VIIRS nightlights to estimate the impact of the 2015 Nepal earthquakes. Geoenvironmental Disasters, 9(1), 2. https://doi.org/10.1186/s40677-021-00204-z

Zhao, M., Zhou, Y., Li, X., Cheng, W., Zhou, C., Ma, T., Li, M., & Huang, K. (2020). Mapping urban dynamics (1992–2018) in Southeast Asia using consistent nighttime light data from DMSP and VIIRS. Remote Sensing of Environment, 248, 111980. https://doi.org/10.1016/j.rse.2020.11198

Unduhan

Diterbitkan

2023-03-29

Cara Mengutip

Sanjaya, S. A., & Fianty, M. I. (2023). Time-based Geospatial Analysis of Night-Time Light Data and Citizen Movement Restriction During Covid-19 Period. G-Tech: Jurnal Teknologi Terapan, 7(2), 664–673. https://doi.org/10.33379/gtech.v7i2.2397

Artikel paling banyak dibaca berdasarkan penulis yang sama