Abstract
Frequent and rapid spatially explicit assessment of socioeconomic development is critical for achieving the Sustainable Development Goals (SDGs) at both national and global levels. Over the past decades, scientists have proposed many methods for estimating human activity on the Earth’s surface at various spatiotemporal scales using Defense Meteorological Satellite Program Operational Line System (DMSP-OLS) nighttime light (NTL) data. However, the DMSP-OLS NTL data and the associated processing methods have limited their reliability and applicability for systematic measuring and mapping of socioeconomic development. This study utilized Visible Infrared Imaging Radiometer Suite (VIIRS) NTL and the Isolation Forest machine learning algorithm for more intelligent data processing to capture human activities. We used machine learning and NTL data to map gross domestic product (GDP) at 1 km2. We then used these data products to derive inequality indexes (e.g., Gini coefficients) at nationally aggregate levels. This flexible approach processes the data in an unsupervised manner at various spatial scales. Our assessments show that this method produces accurate subnational GDP data products for mapping and monitoring human development uniformly across the globe.
Highlights
The United Nations has established a set of sustainable development goals to achieve a better future for people and the planet
Regional total gross domestic product (GDP) results of the nighttime light (NTL)-based GDP were aggregated using the zonal statistics tool in ArcGIS Pro based on the 1 km2 gridded NTL GDP product
We produced the cross-sectional fit comparing the NTL-based GDP against the actual GDP from OECD regions
Summary
The United Nations has established a set of sustainable development goals to achieve a better future for people and the planet. Building on the success of the Millennium Development Goals (MDGs), the 2030 Agenda for Sustainable Development aims to promote and stimulate a series of actions to transform our world. The 17 Sustainable Development Goals (SDGs) with 169 associated targets will unite and mobilize efforts from countries across the world to tackle and address urgent development issues like poverty, inequality, and climate change [1,2,3,4]. Significant progress has been made towards the achievement of these goals, some of the actions and policies have not been implemented effectively because of the complexity of the Earth system and human–environment interactions. Global climate change is progressing at a quick pace and many people are still living in poverty. It is important to understand the global distribution of wealth, characterize socioeconomic well-being, and predict environmental change at appropriate spatiotemporal resolutions to facilitate the implementation of policies and the achievement of SDGs [5]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
