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Spatial distribution of GDP based on integrated NPS-VIIRS nighttime light and MODIS EVI data: a case study of Turkey

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Abstract

Satellite-derived nighttime light data have been increasingly used as a proxy measure for investigating economic activity. However, there are few studies focusing on the spatialised mapping of the GDP at pixel level and further analysis of the economic differences in agricultural and non-agricultural sectors for the different regions using the VIIRS-NPP data. This paper aims to fill this gap in the literature through developing a pixel-level agricultural and non-agricultural GDP map for Turkey in 2015 by combining the VIIRS-NPP nighttime imagery, Terra MODIS-Enhanced Vegetation Index, and land use/cover data from CORINE. The inclusion of vegetation indices and land cover data would significantly improve the estimates of sectorial GDP for Turkey where agriculture is one of the dominating sectors in the Country. GDP density map offers a significant database for both researchers and policy makers in the analysis of regional economic dynamics that will assist in formulating sustainable regional growth strategies.

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Acknowledgements

The study presented here was funded by The Scientific and Technological Research Council of Turkey (TUBİTAK) linked to BIDEB-2232 Programme, Project No. 118C002.

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Conceptualisation, EU and RB; methodology, EU and RB; software, EU and RB; validation, EU., RB and AA; formal analysis, EU and RB; investigation, EU; resources, EU; data curation, EU and RB; writing—original draft preparation, EU and RB; writing—review and editing, EU; visualisation, EU and RB; supervision, AA; project administration, EU; funding acquisition, EU and AA.

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Correspondence to E. Ustaoglu.

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Appendix

Appendix

See Table 8.

Table 8 NTL indices for 81 provinces (NUTS3 regions) in the study area

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Ustaoglu, E., Bovkır, R. & Aydınoglu, A.C. Spatial distribution of GDP based on integrated NPS-VIIRS nighttime light and MODIS EVI data: a case study of Turkey. Environ Dev Sustain 23, 10309–10343 (2021). https://doi.org/10.1007/s10668-020-01058-5

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