Indirect Assessment of Watershed SDG7 Development Process Using Nighttime Light Data—An Example of the Aral Sea Watershed
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Title
Indirect Assessment of Watershed SDG7 Development Process Using Nighttime Light Data—An Example of the Aral Sea Watershed
Authors
Keywords
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Journal
Remote Sensing
Volume 14, Issue 23, Pages 6131
Publisher
MDPI AG
Online
2022-12-05
DOI
10.3390/rs14236131
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- (2021) Shuang Wang et al. Sustainable Cities and Society
- Assessing progress towards sustainable development over space and time
- (2020) Zhenci Xu et al. NATURE
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- (2020) Jaehyun Yoon Computational Economics
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- (2019) Salvador Bará et al. JOURNAL OF QUANTITATIVE SPECTROSCOPY & RADIATIVE TRANSFER
- Remote sensing of night lights: A review and an outlook for the future
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- DISO: A rethink of Taylor diagram
- (2018) Zengyun Hu et al. INTERNATIONAL JOURNAL OF CLIMATOLOGY
- National baselines for the Sustainable Development Goals assessed in the SDG Index and Dashboards
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- (2017) Andrew J. Tatem Scientific Data
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- (2014) Elena Lioubimtseva Environmental Earth Sciences
- Contrasting trends in light pollution across Europe based on satellite observed night time lights
- (2014) Jonathan Bennie et al. Scientific Reports
- Evaluating the Ability of NPP-VIIRS Nighttime Light Data to Estimate the Gross Domestic Product and the Electric Power Consumption of China at Multiple Scales: A Comparison with DMSP-OLS Data
- (2014) Kaifang Shi et al. Remote Sensing
- Potential of NPP-VIIRS Nighttime Light Imagery for Modeling the Regional Economy of China
- (2013) Xi Li et al. Remote Sensing
- Creating a Global Grid of Distributed Fossil Fuel CO2 Emissions from Nighttime Satellite Imagery
- (2010) Tilottama Ghosh et al. Energies
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- (2007) Sebastián Lozano et al. ECOLOGICAL ECONOMICS
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