• Asian Journal of Business Environment
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• v.13 no.2
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• pp.9-20
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• 2023

Purpose: This study aims to map the spatial distribution of poverty using nighttime light satellite images as a proxy indicator of economic activities and infrastructure distribution in D.I Yogyakarta, Indonesia. Research design, data, and methodology: This study uses official poverty statistics (National Socio-economic Survey (SUSENAS) and Poverty Database 2015) to compare satellite imagery's ability to identify poor urban areas in D.I Yogyakarta. National Socioeconomic Survey (SUSENAS), as poverty statistics at the macro level, uses expenditure to determine the poor in a region. Poverty Database 2015 (BDT 2015), as poverty statistics at the micro-level, uses asset ownership to determine the poor population in an area. Pearson correlation is used to identify the correlation among variables and construct a Support Vector Regression (SVR) model to estimate the poverty level at a granular level of 1 km x 1 km. Results: It is found that macro poverty level and moderate annual nighttime light intensity have a Pearson correlation of 74 percent. It is more significant than micro poverty, with the Pearson correlation being 49 percent in 2015. The SVR prediction model can achieve the root mean squared error (RMSE) of up to 8.48 percent on SUSENAS 2020 poverty data.Conclusion: Nighttime light satellite imagery data has potential benefits as alternative data to support regional poverty mapping, especially in urban areas. Using satellite imagery data is better at predicting regional poverty based on expenditure than asset ownership at the micro-level. Light intensity at night can better describe the use of electricity consumption for economic activities at night, which is captured in spending on electricity financing compared to asset ownership.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.437-440
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• 2005

We examined the relationship between the 50m temperature estimated by remote sensing sea surface temperature (SST) and fishing ground (squid fishing ground) detected by nighttime visible channel defense meteorological satellite program (DMSP) I operational linescan system (OLS) images in the East/Japan Sea during 1993-2000. The results are as follows: The numbers of nighttime fishing boat were distributed the highest in October, and the lowest in April during this study. A nighttime fishing grounds have concentrated in the East Korea Warm Current region, coastal regions of Honshu Island, and Polar front region. Fishing grounds have distributed $11-18^{\circ}C$ of estimated 50m temperature from the satellite data. Relationship between estimated 50m temperature and the distributed fisheries boats showed that the north boundaries of fishing grounds have distributed the temperature of below $12^{\circ}C$ from 1996 to 2000 and that of $13-15^{\circ}C$ during 1993-1995 and 1997-1999. Stable fishing grounds appeared near the Korea/Tsushima Strait from January to March. The center of fishing grounds in spring (April-Jun) have moved to the northward than that in winter, and variations appeared largely in winter. In summer (July-September), center of fishing grounds have formed near the Uleung Island in the south east coast of Korea, and in autumn maximum fishing ground appeared in October, the fishing ground southward from November.

• Journal of the Economic Geographical Society of Korea
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• v.22 no.4
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• pp.458-471
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• 2019

DMSP-OLS nighttime satellite imagery could be used to derive the sum of lights (SOL) and built-up area, and the two indices have been widely employed to make the estimation of socio-economic variables and the dynamics of urban developments. Considering it, this research investigated the spatiotemporal patterns of economic growth and urbanized area in Jilin Province, China, using DMSP-OLS data for a time span between 1992 and 2012. This study found the SOLs of both the province and most cities to tend to grow during the period. While SOL-weighted centroids' means moved towards northwestern direction, urban-area centroids' means followed the trend of south-eastern migration. These directional patterns could be associated with the Northeast Revitalization Plan of Chinese governments. Nonetheless, a future study will need to consider SNPP VIIRS DNB imagery in order to overcome temporal limitation of DMSP-OLS data. In addition, it is also necessary to estimate socio-economic indices, e.g., growth regional domestic product, using a regression model developed with correlation relationship between economic statistics ad SOL.

• Proceedings of KOSOMES biannual meeting
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• 2004.05b
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• pp.93-94
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• 2004