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　nonnatural　disasters　for　Indicator　11.5.2.　Changes　in　SDGSAT-1　NTL　intensity　strongly　correlate　with　pandemicinduced　economic　losses,　with　an　R　2　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.