TY - JOUR
T1 - Efficacy of the SDGSAT-1 glimmer imagery in measuring sustainable development goal indicators 7.1.1, 11.5.2, and target 7.3
AU - Liu, Shaoyang
AU - Wang, Congxiao
AU - Chen, Zuoqi
AU - Li, Wei
AU - Zhang, Lingxian
AU - Wu, Bin
AU - Huang, Yan
AU - Li, Yangguang
AU - Ni, Jingwen
AU - Wu, Jianping
AU - Yu, Bailang
N1 - Publisher Copyright:
© 2024 The Author(s)
PY - 2024/5/1
Y1 - 2024/5/1
N2 - The Sustainable Development Goals Satellite 1 (SDGSAT-1), equipped with the Glimmer Imager (GLI), provides high-resolution nighttime light (NTL) data across multiple spectral bands, potentially facilitating the monitoring of sustainable development goals (SDGs). This study developed a denoising algorithm for the multispectral SDGSAT-1 GLI and demonstrated that its data capacity allows for the measurement of the SDG indicators 7.1.1, 11.5.2, and the achievement of target 7.3. The results indicate that (1) The denoising algorithm can effectively remove strips and salt-and-pepper noise from SDGSAT-1 GLI images, with the residual noise significantly reduced and almost little information loss. (2) SDGSAT-1 GLI data can accurately identify electrified areas at a finer spatial scale for calculating Indicator 7.1.1, compared to the traditional NASA's Black Marble Product. The findings show that highly urbanized cities exhibit a greater proportion of their population with access to electricity than underdeveloped cities. (3) SDGSAT-1 proficiently estimates economic losses resulting from non-natural disasters for Indicator 11.5.2. Changes in SDGSAT-1 NTL intensity strongly correlate with pandemic-induced economic losses, with an R2 exceeding 0.8. (4) When measuring Target 7.3 achievement, the SDGSAT-1 GLI multispectral bands classify streetlight types into light-emitting diode and high-pressure sodium lamps with acceptable overall accuracy (89.9%). Sequentially, the classification shows that Shanghai achieved a 13.09% energy-saving benefit. Overall, by leveraging the high spatial resolution, multiple spectra, and appropriate satellite overpass times of SDGSAT-1 GLI, the estimated SDG indicators in this study outperform those based on Black Marble products, and SDGSAT-1 GLI data have the potential to serve as a direct data source or reference factor for estimating at least 11 SDG indicators.
AB - The Sustainable Development Goals Satellite 1 (SDGSAT-1), equipped with the Glimmer Imager (GLI), provides high-resolution nighttime light (NTL) data across multiple spectral bands, potentially facilitating the monitoring of sustainable development goals (SDGs). This study developed a denoising algorithm for the multispectral SDGSAT-1 GLI and demonstrated that its data capacity allows for the measurement of the SDG indicators 7.1.1, 11.5.2, and the achievement of target 7.3. The results indicate that (1) The denoising algorithm can effectively remove strips and salt-and-pepper noise from SDGSAT-1 GLI images, with the residual noise significantly reduced and almost little information loss. (2) SDGSAT-1 GLI data can accurately identify electrified areas at a finer spatial scale for calculating Indicator 7.1.1, compared to the traditional NASA's Black Marble Product. The findings show that highly urbanized cities exhibit a greater proportion of their population with access to electricity than underdeveloped cities. (3) SDGSAT-1 proficiently estimates economic losses resulting from non-natural disasters for Indicator 11.5.2. Changes in SDGSAT-1 NTL intensity strongly correlate with pandemic-induced economic losses, with an R2 exceeding 0.8. (4) When measuring Target 7.3 achievement, the SDGSAT-1 GLI multispectral bands classify streetlight types into light-emitting diode and high-pressure sodium lamps with acceptable overall accuracy (89.9%). Sequentially, the classification shows that Shanghai achieved a 13.09% energy-saving benefit. Overall, by leveraging the high spatial resolution, multiple spectra, and appropriate satellite overpass times of SDGSAT-1 GLI, the estimated SDG indicators in this study outperform those based on Black Marble products, and SDGSAT-1 GLI data have the potential to serve as a direct data source or reference factor for estimating at least 11 SDG indicators.
KW - Denoising algorithm
KW - Glimmer imager
KW - Nighttime light
KW - SDGSAT-1
KW - SDGs
UR - https://www.scopus.com/pages/publications/85186264656
U2 - 10.1016/j.rse.2024.114079
DO - 10.1016/j.rse.2024.114079
M3 - 文章
AN - SCOPUS:85186264656
SN - 0034-4257
VL - 305
JO - Remote Sensing of Environment
JF - Remote Sensing of Environment
M1 - 114079
ER -