Socioeconomic impact of COVID-19 restrictions in Bali: A nighttime light analysis
Keywords:
nighttime light, COVID-19, proxy indicator, ARIMA intervention
Abstract
This study investigates the socio-economic impacts of COVID-19 pandemic restrictions in Bali using nighttime light remote sensing as a proxy for socio-economic activity. The monthly NTL data from the Suomi-NPP VIIRS instrument, spanning from 2014 to 2021, are analyzed. This study focuses on changes in NTL trends before and after the restrictions, specifically the Large-Scale Social Restriction and Welfare Activity Restriction programs. To ensure that the NTL used in this study accurately measures human activity, we integrate the data with built-up area maps from the Global Human Settlement Layer. An ARIMA intervention model is employed to assess the impact of the restrictions on NTL, revealing a significant decrease in certain regions. Furthermore, we find a moderate correlation between NTL and Bali's quarterly GDP data. This study also highlights the potential of NTL remote sensing as a near-real-time proxy for socioeconomic change, allowing for the early evaluation of policy effectiveness.
Keywords: nighttime light, COVID-19, proxy indicator, ARIMA intervention
JEL Classification: C22; I18; R11
References
[1] Almutaqi, A. (2020). Kekacauan Respons terhadap COVID-19 di Indonesia. pp. 1-7. Retrieved from https://www.habibiecenter.or.id/img/publication/66f28c42de71fefe1c6fcdee37a5c1a6.pdf
[2] As-syakur, A. R., Ariastina, W. G., Kumara, N. I., Antara, I. M., Osawa, T., & Cahyani, D. A. (2021). Impact of Covid-19 Pandemic on Electricity Consumption and Nighttime Lights Based on NPP-VIIRS DNB Image Products. 2021 International Conference on Smart-Green Technology in Electrical and Information Systems (ICSGTEIS) (pp. 161-164). IEEE.
[3] Awirya, A., Novita, D., Irawadi, C., & Wilandari, R. (2022). Workers Adaptation during Pandemic, Evidence from Bali Province as Main Tourist Destination in Indonesia. e-Journal Ekonomi Bisnis dan Akuntansi, 14-22.
[4] Box, G., Jenkins, G., Reinsel, G., & Ljung, G. (2015). Time series analysis: forecasting and control. John Wiley and Sons.
[5] BPS. (2022). Banyaknya Wisatawan Mancanegara ke Bali Menurut Kawasan. Retrieved from https://bali.bps.go.id/indicator/16/129/1/banyaknya-wisatawan-mancanegara-ke-bali-menurut-kawasan.html
[6] Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Lawrence Erlbaum Associates.
[7] Devkota, B., Miyazaki, H., Witayangkurn, A., & Kim, S. (2019). Using Volunteered Geographic Information and Nighttime Light Remote Sensing Data to Identify Tourism Areas of Interest. Sustainability, 11(17), 4718.
[8] Elvidge, C., Baugh, K., Zhizhin, M., Hsu, F., & Tilottama, G. (2017). VIIRS Night-Time Lights. International Journal of Remote Sensing, 5860-5879.
[9] Field, A. (2018). Discovering statistics using IBM SPSS statistics. Sage publications.
[10] Gorelick, N., Hancher, M., Dixon, M., Ilyuschenko, S., Thau, D., & Moore, R. (2017). Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment, 18-27. Retrieved from https://www.sciencedirect.com/science/article/pii/S0034425717302900
[11] Haavelmo, T., & Hansen, S. (1991). On the Strategy of Trying to Reduce Economic Inequality by Expanding the Scale of Human Activity. In Environmentally Sustainable Economic Development: Building on Brundtland (pp. 41-49). Retrieved from https://documents1.worldbank.org/curated/en/332821467989482335/pdf/multi-page.pdf
[12] 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.
[13] Hyndman, R. J., & Khandakar, Y. (2008). Automatic Time Series Forecasting: The forecast Package for R. Journal of Statistical Software, 27(3), 1–22.
[14] Karimah, I. D., & Yudhistira, M. H. (2020). Does small-scale port investment affect local economic activity? Evidence from small-port development in Indonesia. Economic of Transportation 23.
[15] Kopp, T. J., Thomas, W., Heidinger, A. K., Botambekov, D., Frey, R. A., Hutchinson, K. D., . . . Reed, B. (2014). The VIIRS Cloud Mask: Progress in the first year of S-NPP toward a common cloud detection scheme. JGR Atmosphere, 2441-2456. doi:https://doi.org/10.1002/2013JD020458
[16] Levin, N., Kyba, C., Zhang, Q., de Miguel, A., Roman, M., Xi, L., & Elvidge, C. (2020). Remote sensing of night lights: a review and an outlook for the future. Remote Sensing of Environment, 111443. Retrieved from https://www.sciencedirect.com/science/article/abs/pii/S0034425719304626?via%3Dihub
[17] Li, X., Li, D., Xu, H., & Wu, C. (2017). Intercalibration between DMSP/OLS and VIIRS night-time light images to evaluate city light dynamics of Syria’s major human settlement during Syrian Civil War. International Journal of Remote Sensing, 5934-5951.
[18] Makridakis, S. G., Wheelwright, S. C., & Hyndman, R. J. (1997). Forecasting Methods and Applications Third Edition. Hoboken: Wiley.
[19] Makridakis, S., Wheelwright, S., & Hyndman, R. (1997). Forecasting Methods and Applications (Third Edition ed.). Hoboken: Wiley.
[20] Mardika, I. M., Putra, I. B., & Wisnumurti, A. A. (2020). Pemberdayaan Pecalang Desa Adat Sumerta dalam Penanggulangan Covid-19. Postgraduated Community Service Journal, 1 (2), 37-42.
[21] Mellander, C., Lobo, J., Stolarick, K., & Matheson, Z. (2015). Night-Time Light Data: A Good Proxy Measure for Economic Activity? PLOS ONE 10(10): e0139779.
[22] Montgomery, D. C., Jennings, C. L., & Kulahci, M. (2015). Introduction to Time Series Analysis and Forecasting Second Edition. New Jersey: Wiley.
[23] Montgomery, D., Jennings, C., & Kulahci, M. (2015). Introduction to Time Series Analysis and Forecasting (Second Edition ed.). New Jersey: Wiley.
[24] Pankratz, A. (1983). Forecasting with Univariate Box-Jenkins Models: Concepts and Cases. Greencastle: John Wiley and Sons.
[25] Pesaresi, M., Corbane, C., Julea, A., Florczyk, A. J., Syrris, V., & Soille, P. (2016). Assessment of the Added-Value of Sentinel-2 for Detecting Built-up Areas. Remote Sensing, 299. Retrieved from https://www.mdpi.com/2072-4292/8/4/299
[26] Pesaresi, M., Ehrlich, D., Ferry, S., Florczyk, A. J., Freire, S., Halkia, M., . . . Syrris, V. (2016). Operating procedure for the production of the Global Human Settlement Layer from Landsat data of the epochs 1975, 1990, 2000, and 2014. Italy: European Commission.
[27] Pesaresi, M., Ehrlich, D., Ferry, S., Florczyk, A., Freire, S., Halkia, M., & Syrris, V. (2016). Operating procedure for the production of the Global Human Settlement Layer from Landsat data of the epochs 1975, 1990, 2000, and 2014. Italy: European Commission.
[28] Shmueli, G., & Lichtendahl Jr., K. (2016). Practical Time Series Forecasting with R: A Hands-on Guide. Axelrod Schnall.
[29] Shmueli, G., & Lichtendahl Jr., K. C. (2016). Practical Time Series Forecasting with R: A Hands-on Guide. Axelrod Schnall.
[30] WHO. (2020). Novel Coronavirus (2019-ncov) Situation Report - 1. Retrieved from https://apps.who.int/iris/bitstream/handle/10665/330760/nCoVsitrep21Jan2020-eng.pdf?sequence=3'isAllowed=y
[31] World Bank. (n.d.). 1. Time Series Charts. Retrieved from Open Night Light: https://worldbank.github.io/OpenNightLights/tutorials/mod4_1_time_series_charts.html
[32] Ye, J., Xiao, C., Esteves, R., & Rong, C. (2015). Time series similarity evaluation based on Spearman’s correlation coefficients and distance measures. Cloud Computing and Big Data: Second International Conference, CloudCom-Asia 2015, Huangshan, China, June 17-19, 2015, Revised Selected Papers 2 (pp. 319-331). Springer International Publishing.
[33] Zhao, N., Liu, Y., Hsu, F., Samson, E., Letu, H., Liang, D., & Cao, G. (2020). Time series analysis of VIIRS-DNB nighttime lights imagery for change detection in urban areas: A case study of devastation in Puerto Rico from hurricanes Irma and Maria. ScienceDirect.
[2] As-syakur, A. R., Ariastina, W. G., Kumara, N. I., Antara, I. M., Osawa, T., & Cahyani, D. A. (2021). Impact of Covid-19 Pandemic on Electricity Consumption and Nighttime Lights Based on NPP-VIIRS DNB Image Products. 2021 International Conference on Smart-Green Technology in Electrical and Information Systems (ICSGTEIS) (pp. 161-164). IEEE.
[3] Awirya, A., Novita, D., Irawadi, C., & Wilandari, R. (2022). Workers Adaptation during Pandemic, Evidence from Bali Province as Main Tourist Destination in Indonesia. e-Journal Ekonomi Bisnis dan Akuntansi, 14-22.
[4] Box, G., Jenkins, G., Reinsel, G., & Ljung, G. (2015). Time series analysis: forecasting and control. John Wiley and Sons.
[5] BPS. (2022). Banyaknya Wisatawan Mancanegara ke Bali Menurut Kawasan. Retrieved from https://bali.bps.go.id/indicator/16/129/1/banyaknya-wisatawan-mancanegara-ke-bali-menurut-kawasan.html
[6] Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Lawrence Erlbaum Associates.
[7] Devkota, B., Miyazaki, H., Witayangkurn, A., & Kim, S. (2019). Using Volunteered Geographic Information and Nighttime Light Remote Sensing Data to Identify Tourism Areas of Interest. Sustainability, 11(17), 4718.
[8] Elvidge, C., Baugh, K., Zhizhin, M., Hsu, F., & Tilottama, G. (2017). VIIRS Night-Time Lights. International Journal of Remote Sensing, 5860-5879.
[9] Field, A. (2018). Discovering statistics using IBM SPSS statistics. Sage publications.
[10] Gorelick, N., Hancher, M., Dixon, M., Ilyuschenko, S., Thau, D., & Moore, R. (2017). Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment, 18-27. Retrieved from https://www.sciencedirect.com/science/article/pii/S0034425717302900
[11] Haavelmo, T., & Hansen, S. (1991). On the Strategy of Trying to Reduce Economic Inequality by Expanding the Scale of Human Activity. In Environmentally Sustainable Economic Development: Building on Brundtland (pp. 41-49). Retrieved from https://documents1.worldbank.org/curated/en/332821467989482335/pdf/multi-page.pdf
[12] 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.
[13] Hyndman, R. J., & Khandakar, Y. (2008). Automatic Time Series Forecasting: The forecast Package for R. Journal of Statistical Software, 27(3), 1–22.
[14] Karimah, I. D., & Yudhistira, M. H. (2020). Does small-scale port investment affect local economic activity? Evidence from small-port development in Indonesia. Economic of Transportation 23.
[15] Kopp, T. J., Thomas, W., Heidinger, A. K., Botambekov, D., Frey, R. A., Hutchinson, K. D., . . . Reed, B. (2014). The VIIRS Cloud Mask: Progress in the first year of S-NPP toward a common cloud detection scheme. JGR Atmosphere, 2441-2456. doi:https://doi.org/10.1002/2013JD020458
[16] Levin, N., Kyba, C., Zhang, Q., de Miguel, A., Roman, M., Xi, L., & Elvidge, C. (2020). Remote sensing of night lights: a review and an outlook for the future. Remote Sensing of Environment, 111443. Retrieved from https://www.sciencedirect.com/science/article/abs/pii/S0034425719304626?via%3Dihub
[17] Li, X., Li, D., Xu, H., & Wu, C. (2017). Intercalibration between DMSP/OLS and VIIRS night-time light images to evaluate city light dynamics of Syria’s major human settlement during Syrian Civil War. International Journal of Remote Sensing, 5934-5951.
[18] Makridakis, S. G., Wheelwright, S. C., & Hyndman, R. J. (1997). Forecasting Methods and Applications Third Edition. Hoboken: Wiley.
[19] Makridakis, S., Wheelwright, S., & Hyndman, R. (1997). Forecasting Methods and Applications (Third Edition ed.). Hoboken: Wiley.
[20] Mardika, I. M., Putra, I. B., & Wisnumurti, A. A. (2020). Pemberdayaan Pecalang Desa Adat Sumerta dalam Penanggulangan Covid-19. Postgraduated Community Service Journal, 1 (2), 37-42.
[21] Mellander, C., Lobo, J., Stolarick, K., & Matheson, Z. (2015). Night-Time Light Data: A Good Proxy Measure for Economic Activity? PLOS ONE 10(10): e0139779.
[22] Montgomery, D. C., Jennings, C. L., & Kulahci, M. (2015). Introduction to Time Series Analysis and Forecasting Second Edition. New Jersey: Wiley.
[23] Montgomery, D., Jennings, C., & Kulahci, M. (2015). Introduction to Time Series Analysis and Forecasting (Second Edition ed.). New Jersey: Wiley.
[24] Pankratz, A. (1983). Forecasting with Univariate Box-Jenkins Models: Concepts and Cases. Greencastle: John Wiley and Sons.
[25] Pesaresi, M., Corbane, C., Julea, A., Florczyk, A. J., Syrris, V., & Soille, P. (2016). Assessment of the Added-Value of Sentinel-2 for Detecting Built-up Areas. Remote Sensing, 299. Retrieved from https://www.mdpi.com/2072-4292/8/4/299
[26] Pesaresi, M., Ehrlich, D., Ferry, S., Florczyk, A. J., Freire, S., Halkia, M., . . . Syrris, V. (2016). Operating procedure for the production of the Global Human Settlement Layer from Landsat data of the epochs 1975, 1990, 2000, and 2014. Italy: European Commission.
[27] Pesaresi, M., Ehrlich, D., Ferry, S., Florczyk, A., Freire, S., Halkia, M., & Syrris, V. (2016). Operating procedure for the production of the Global Human Settlement Layer from Landsat data of the epochs 1975, 1990, 2000, and 2014. Italy: European Commission.
[28] Shmueli, G., & Lichtendahl Jr., K. (2016). Practical Time Series Forecasting with R: A Hands-on Guide. Axelrod Schnall.
[29] Shmueli, G., & Lichtendahl Jr., K. C. (2016). Practical Time Series Forecasting with R: A Hands-on Guide. Axelrod Schnall.
[30] WHO. (2020). Novel Coronavirus (2019-ncov) Situation Report - 1. Retrieved from https://apps.who.int/iris/bitstream/handle/10665/330760/nCoVsitrep21Jan2020-eng.pdf?sequence=3'isAllowed=y
[31] World Bank. (n.d.). 1. Time Series Charts. Retrieved from Open Night Light: https://worldbank.github.io/OpenNightLights/tutorials/mod4_1_time_series_charts.html
[32] Ye, J., Xiao, C., Esteves, R., & Rong, C. (2015). Time series similarity evaluation based on Spearman’s correlation coefficients and distance measures. Cloud Computing and Big Data: Second International Conference, CloudCom-Asia 2015, Huangshan, China, June 17-19, 2015, Revised Selected Papers 2 (pp. 319-331). Springer International Publishing.
[33] Zhao, N., Liu, Y., Hsu, F., Samson, E., Letu, H., Liang, D., & Cao, G. (2020). Time series analysis of VIIRS-DNB nighttime lights imagery for change detection in urban areas: A case study of devastation in Puerto Rico from hurricanes Irma and Maria. ScienceDirect.
Published
2025-04-25
How to Cite
Putro, D., Pramana, S., & Hendrawan, D. (2025). Socioeconomic impact of COVID-19 restrictions in Bali: A nighttime light analysis. Jurnal Ekonomi Indonesia, 14(1), 93-110. https://doi.org/10.52813/jei.v14i1.220
Section
Articles
