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Machine learning approaches for high-resolution urban land cover classification: a comparative study.

, , , , , and . COM.Geo, page 11:1-11:10. ACM, (2011)

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Probabilistic Change Detection Framework for Analyzing Settlement Dynamics Using Very High-resolution Satellite Imagery., and . ICCS, volume 9 of Procedia Computer Science, page 907-916. Elsevier, (2012)Temporally-Consistent Annual Land Cover from Landsat Time Series in the Southern Cone of South America., , , , , , , , , and . Remote. Sens., 14 (16): 4005 (2022)Reconstruction of Satellite Time Series With a Dynamic Smoother., , and . IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., (2022)Rapid damage assessment using high-resolution remote sensing imagery: Tools and techniques., , , , , , and . IGARSS, page 1445-1448. IEEE, (2011)Image Based Characterization of Formal and Informal Neighborhoods in an Urban Landscape., , , , , and . IEEE J Sel. Topics in Appl. Earth Observ. and Remote Sensing, 5 (4): 1164-1176 (2012)Machine learning approaches for high-resolution urban land cover classification: a comparative study., , , , , and . COM.Geo, page 11:1-11:10. ACM, (2011)Mapping slums using spatial features in Accra, Ghana., , , , , , and . JURSE, page 1-4. IEEE, (2015)Assessing the relationship between spatial features derived from high resolution satellite imagery and census variables in Accra, Ghana., , , and . IGARSS, page 2544-2547. IEEE, (2015)Contextural feature evaluation of multi-resolution imagery., , and . IGARSS, page 6782-6785. IEEE, (2016)