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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume XLIII-B2-2020
https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-521-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-521-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
12 Aug 2020
| 12 Aug 2020
DENSE MATCHING COMPARISON BETWEEN CLASSICAL AND DEEP LEARNING BASED ALGORITHMS FOR REMOTE SENSING DATA
Y. Xia
German Aerospace Center (DLR), Remote Sensing Technology Institute, 82234 Wessling, Germany
P. d’Angelo
German Aerospace Center (DLR), Remote Sensing Technology Institute, 82234 Wessling, Germany
J. Tian
German Aerospace Center (DLR), Remote Sensing Technology Institute, 82234 Wessling, Germany
P. Reinartz
German Aerospace Center (DLR), Remote Sensing Technology Institute, 82234 Wessling, Germany
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Short summary
Short summary
This study analyses the basal sliding and the hydrological drainage of Baltoro Glacier, Pakistan. The surface velocity was characterized by a spring speed-up, summer peak, and autumn speed-up. Snow melt has the largest impact on the spring speed-up, summer velocity peak, and the transition from inefficient to efficient drainage. Drainage from supraglacial lakes contributed to the fall speed-up. Increased summer temperatures will intensify the magnitude of meltwater and thus surface velocities.
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