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Observations of surface deformation within 1–2 km of a surface rupture contain invaluable information about the coseismic behavior of the shallow crust. We investigate the oblique strike‐slip 2016 M7 Kumamoto, Japan, earthquake, which ruptured the Futagawa‐Hinagu Fault. We solve for variable fault slip in an inversion of differential lidar topography, satellite optical image correlation, and Interferometric Synthetic Aperture Radar (InSAR)‐derived surface displacements. The near‐fault differential lidar pose several challenges. The model fault geometry must follow the surface trace at the sub‐kilometer scale. Integration of displacement datasets with different sensitivities to the 3D deformation field and varying spatial distribution permits additional complexity in the inferred slip but introduces ambiguity that requires careful selection of the regularization. We infer a Mw7.09−0.05+0.03 earthquake. The maximum slip of 6.9 m occurred at 4.5‐km depth, suggesting an on‐fault slip deficit in the upper several kilometers of the crust that likely reflects distributed and inelastic deformation within the shallow fault zone. Plain Language Summary: Coseismic slip inversions quantify fault slip over a fault surface and serve as critical input into research on rupture propagation, earthquake triggering, and seismic hazard. However, coseismic slip distributions are rarely constrained by observations of surface displacement immediately adjacent to the fault rupture. This limits the quality of slip models within the shallowest crust. We solve for the slip field of the 2016 M7 Kumamoto, Japan, earthquake throughout the seismogenic crust using near‐ and far‐field observations from differential lidar topography, satellite optical image correlation, and Interferometric Synthetic Aperture Radar surface displacements. The near‐field differential lidar topography is critical for measuring shallow fault slip. We infer a Mw7.09−0.05+0.03 earthquake and a maximum slip of 6.9 m at 4.5‐km depth. This represents a shallow fault slip deficit where slip is greater at depth than at the surface. The missing shallow along‐fault slip is accommodated as off‐fault and inelastic deformation, presumably along secondary faults and folds in the shallow crust. Future earthquakes are also likely to be measured with different surface displacement data types. Researchers will have a new opportunity to learn about the behavior of the shallow fault zone and will also be presented with technical challenges such as those discussed here. Key Points: We conduct an earthquake slip inversion using differential lidar topography, optical image correlation, and InSAR imageryWe show how each data set constrains the variable fault slipThe apparent shallow slip deficit may reflect shallow off‐fault deformation [ABSTRACT FROM AUTHOR]

Differencing multi-temporal topographic data (radar, lidar, or photogrammetrically derived point clouds or digital elevation models—DEMs) measures landscape change, with broad applications for scientific research, hazard management, industry, and urban planning. The United States Geological Survey's 3D Elevation Program (3DEP) is an ambitious effort to collect light detection and ranging (lidar) topography over the United States' lower 48 and Interferometric Synthetic Aperture Radar (IfSAR) in Alaska by 2023. The datasets collected through this program present an important opportunity to characterize topography and topographic change at regional and national scales. We present Indiana statewide topographic differencing results produced from the 2011–2013 and 2016–2020 lidar collections. We discuss the insights, challenges, and lessons learned from conducting large-scale differencing. Challenges include: (1) designing and implementing an automated differencing workflow over 94,000 km2 of high-resolution topography data, (2) ensuring sufficient computing resources, and (3) managing the analysis and visualization of the multiple terabytes of data. We highlight observations including infrastructure development, vegetation growth, and landscape change driven by agricultural practices, fluvial processes, and natural resource extraction. With 3DEP and the U.S. Interagency Elevation Inventory data, at least 37% of the Contiguous 48 U.S. states are already covered by repeat, openly available, high-resolution topography datasets, making topographic differencing possible. [ABSTRACT FROM AUTHOR]