Abstract
Measuring the spatial differences in regional development was the main objective of this study. To meet this objective, spatial patterns & clusters of variables, viz. nightlight & population density, were identified at the LGA level. Secondly, regression analysis between the same variables was performed to find the spatial differences in the night light. VIIRS Day/Night Band (DNB) data was chosen as the dependent variable, and UN-Adjusted Population Density data was selected as an explanatory variable. Spatial patterns & clusters were identified using spatial statistics. Global Ordinary Least Squares (OLS) linear regression was chosen to model nightlight in terms of its relationships to population density. Geographically Weighted Regression (GWR) regression was used to model spatially varying relationships between the same variables. The results show nightlight (z >97, p <0000) & population density (z >108, p <0000) are highly clustered. The R2 obtained from OLS & GWR are 0.75 & 0.85, respectively. Moreover, model variables & diagnostics results confirm the validity of both models.
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Authors Affiliations
Zubairul Islam*
University of Abuja, Nigeria
* Correspondence address
Email: zubairul@gmail.com
References
Abrahams, A., Oram, C., & Lozano-Gracia, N. (2018). Deblurring DMSP nighttime lights: A new method using Gaussian filters and frequencies of illumination. Remote Sensing of Environment, 210, 242–258.
Adepoju, A. (2006). Population Dynamics in Sub-Saharan Africa: Challenges and Opportunities. In H. B. Tambo & M. Adepoju (Eds.), International Migration and Development in Sub-Saharan Africa (pp. 49-74). Center for Migration Studies.
Alahmadi, M., & Atkinson, P. M. (2019). Three-fold urban expansion in Saudi Arabia from 1992 to 2013 observed using calibrated DMSP-OLS night-time lights imagery. Remote Sensing, 11(19).
Anand, A., & Kim, D. H. (2021). Pandemic induced changes in economic activity around African protected areas captured through night-time light data. Remote Sensing, 13(2), 1–15.
Bertinelli, L., & Strobl, E. (2013). Quantifying the local economic growth impact of hurricane strikes: An analysis from outer space for the caribbean. Journal of Applied Meteorology and Climatology, 52(8), 1688–1697.
Bhandari, L., & Roychowdhury, K. (2011). Night Lights and Economic Activity in India: A study using DMSP-OLS night time images. Proceedings of the Asia-Pacific Advanced Network, 32(0), 218.
Bluhm, R., & Krause, M. (2022). Top lights: Bright cities and their contribution to economic development. Journal of Development Economics, 157, 102880.
Dieteren, C., & Bonfrer, I. (2021). Socioeconomic inequalities in lifestyle risk factors across low- and middle-income countries. BMC Public Health, 21(1). https://doi.org/10.1186/s12889-021-11014-1
Elvidge, C. D., Baugh, K. E., Anderson, S. J., Sutton, P. C., & Ghosh, T. (2012). The Night Light Development Index (NLDI): A spatially explicit measure of human development from satellite data. Social Geography, 7(1), 23–35.
Emovon, I., Samuel, O. D., Mgbemena, C. O., & Adeyeri, M. K. (2018). Electric Power generation crisis in Nigeria: A Review of causes and solutions. International Journal of Integrated Engineering, 10(1), 47–56.
Ene Blessing Ita. (2020). Human Development in Nigeria. International Journal of African and Asian Studies.
Eboh, E. (2014). Federalism and Nigeria’s Development: A Paradigm Shift. African Research Review, 8(2), 161-171.
Egwu, S. (2017). Political Leadership and Corruption in Nigeria Since 1960: A Socio-economic Analysis. African Journal of Political Science and International Relations, 11(8), 272-281.
Fan, J., Ma, T., Zhou, C., Zhou, Y., & Xu, T. (2014). Comparative Estimation of Urban Development in China’s Cities Using Socioeconomic and DMSP/OLS Night Light Data. Remote Sensing, 6(8), 7840–7856.
Gechbaia, B., Kharaishvili, E., Mushkudiani, Z., Goletiani, K., & Tsilosani, A. (2021). Challenges of sustainable and equal development of regions in Georgia. E3S Web of Conferences, 280, 11007.
Hodgson, S. (2018). Nigeria: Background to Unequal Development. In K. Kitchen, S. Hodgson, & S. Ford, (Eds.), Global Inequality: A Sociological Perspective (pp. 269-288). Routledge.
Ivan, K., Holobâcă, I. H., Benedek, J., & Török, I. (2020). Potential of night-time lights to measure regional inequality. Remote Sensing, 12(1), 1–15.
Krikigianni, E., Tsiakos, C., & Chalkias, C. (2019). Estimating the relationship between touristic activities and night light emissions. European Journal of Remote Sensing, 52(sup1), 233–246.
Lee, H. Y., Jang, K. M., & Kim, Y. (2020). Energy consumption prediction in vietnam with an artificial neural network-based urban growth model. Energies, 13(17).
Levin, N., Kyba, C. C. M., Zhang, Q., Sánchez de Miguel, A., Román, M. O., Li, X., Portnov, B. A., Molthan, A. L., Jechow, A., Miller, S. D., Wang, Z., Shrestha, R. M., & Elvidge, C. D. (2020). Remote sensing of night lights: A review and an outlook for the future. Remote Sensing of Environment, 237(September 2019).
Li, Y. (2021). Analysis of Regional Economic Development Differences Based on Intelligent Hybrid Algorithm. Complexity, 2021.
Ma, T. (2018). Quantitative responses of satellite-derived nighttime lighting signals to anthropogenic land-use and land-cover changes across China. Remote Sensing, 10(9).
Oladipo, S. E. (2006). Ethnic and Religious Conflicts: Challenges to Nigerian Federalism and National Integration. Nordic Journal of African Studies, 15(3), 378-401.
Omotola, J. S. (2011). Politics and Leadership in Nigeria’s Fourth Republic. African Spectrum, 46(2), 93-114.
Otchia, C., & Asongu, S. (2020). Industrial growth in sub-Saharan Africa: evidence from machine learning with insights from nightlight satellite images. Journal of Economic Studies.
Prakash, A., Shukla, A. K., Bhowmick, C., Carl, R., & Beyer, M. (2019). Night-time Luminosity: Does it Brighten Understanding of Economic Activity in India? Reserve Bank of India Occasional Papers, 40(1), 1–24.
Sahoo, S., Gupta, P. K., & Srivastav, S. K. (2020). Comparative analysis between VIIRS-DNB and DMSP-OLS night-time light data to estimate electric power consumption in Uttar Pradesh, India. International Journal of Remote Sensing, 41(7), 2565–2580.
Samuel, A., & TT, O. (2020). Power Generation In Nigeria: The Past, Present And The Future. Journal of Earth and Environmental Sciences Research, 2(2), 1–8.
Small, C., Elvidge, C. D., & Baugh, K. (2013). Mapping urban structure and spatial connectivity with VIIRS and OLS night light imagery. Joint Urban Remote Sensing Event 2013, JURSE 2013, 856, 230–233.
Suberu, R. T. (2001). Federalism and Ethnic Conflict in Nigeria. US Institute of Peace Press.
Wang, Y., Liu, Z., He, C., Xia, P., Liu, Z., & Liu, H. (2020). Quantifying urbanization levels on the Tibetan Plateau with high-resolution nighttime light data. Geography and Sustainability, 1(3), 233–244.
Weidmann, N. B., & Schutte, S. (2017). Using night light emissions for the prediction of local wealth. Journal of Peace Research, 54(2), 125–140.
Xiao, H., Ma, Z., Mi, Z., Kelsey, J., Zheng, J., Yin, W., & Yan, M. (2018). Spatio-temporal simulation of energy consumption in China’s provinces based on satellite night-time light data. Applied Energy, 231(June 2018), 1070–1078.
Zhao, F., Song, L., Peng, Z., Yang, J., Luan, G., Chu, C., Ding, J., Feng, S., Jing, Y., & Xie, Z. (2021). Night-time light remote sensing mapping: Construction and analysis of ethnic minority development index. Remote Sensing, 13(11), 1–26.
Zheng, Q., Weng, Q., Huang, L., Wang, K., Deng, J., Jiang, R., Ye, Z., & Gan, M. (2018). A new source of multi-spectral high spatial resolution night-time light imagery—JL1-3B. Remote Sensing of Environment, 215, 300–312.
Zheng, Q., Weng, Q., & Wang, K. (2019). Developing a new cross-sensor calibration model for DMSP-OLS and Suomi-NPP VIIRS night-light imageries. ISPRS Journal of Photogrammetry and Remote Sensing, 153(May), 36–47.
Zhong, Y., Lin, A., Zhou, Z., & Chen, F. (2018). Spatial pattern evolution and optimization of urban system in the Yangtze River economic belt, China, based on DMSP-OLS night light data. Sustainability (Switzerland), 10(10).
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