Mountainous high-relief terrains stretching across several climatic zones are often subjected to natural extreme events such as debris flows and landsliding (e.g.,

The generation of Digital Elevation Models (DEMs) through stereogrammetry of optical satellite images has gained great popularity across various disciplines. For the analysis of these DEMs, it is important to understand the influence of the input data and different processing steps and parameters employed during stereo correlation. Here, we explore the effects that image texture, as well as the use of different matching algorithms (Block Matching (BM) and More Global Matching (MGM)), can have on optical DEMs derived from the flexible, open-source Ames Stereo Pipeline. Our analysis relies on a ∼2700 km2 clip of a SPOT6 tristereo scene covering the hyperarid, vegetation-free Pocitos Basin and adjacent mountain ranges in the northwestern Argentine Andes. A large, perfectly flat salt pan (paleolake bed) that covers the center of this basin is characterized by strong contrasts in image texture, providing a unique opportunity to quantitatively study the relationship between image texture and DEM quality unaffected by topography. Our findings suggest that higher image texture, measured by panchromatic variance, leads to lower DEM uncertainty. This improvement continues up to ∼103 panchromatic variance, above which further improvements in DEM quality are independent of local image texture but instead may have sensor or geometric origins. Based on this behavior, we propose that image texture may serve as an important proxy of DEM quality prior to stereo correlation and can help to set adequate processing parameters. With respect to matching algorithms, we observe that MGM improves matching in low-texture areas and overall generates a smoother surface that still preserves complex, narrow (i.e., ridge and valley) features. Based on this sharper representation of the landscape, we conclude that MGM should be preferred for geomorphic applications relying on stereo-derived DEMs. However, we note that the correlation kernel selected for stereo-matching must be carefully chosen depending on local image texture, whereby larger kernels generate more accurate matches (less artifacts) at the cost of smoothing results. Overall, our analysis suggests a path forward for the processing and fusion of overlapping satellite images with suitable view-angle differences to improve final DEMs.

<p>Mountainous high-relief terrains in climatically sensitive regions are often subjected to natural extreme events such as debris flows and landsliding. With people and infrastructure at risk, it is important to identify, measure, and comprehend the driving forces and mechanisms of slope movements in these environments at regional scale. Geomorphologic analyses and hazard assessments in these regions are, however, often limited by the availability of good-quality high-resolution digital elevation models (DEMs). Publically available data often have lower spatial resolution and are distorted in high-relief areas. In contrast, airplane-based lidar (light detection and ranging) data provide highly accurate information on 3D structure, yet, acquisition is costly and limits the size of the respective study area. Finding adequate, economical alternatives for creating high-resolution DEMs is therefore essential to study Earth-surface processes at regional scale, which may enable the detection of spatial variations, clusters and trends.</p><p>In areas with sparse vegetation, stereogrammetry has proven to be a viable tool for creating high-resolution DEMs. Here, we use SPOT-7 tri-stereo satellite imagery to create DEMs at 3 m spatial resolution for the Quebrada del Toro (QdT) in the Eastern Cordillera of NW Argentine Andes, an area with extreme gradients in topography, rainfall and erosion. Over 5000 GPS points collected during fieldwork ensure the spatial coherence of our DEMs.</p><p>Field observations in this high-elevation area show that the hillslopes of the deeply incised QdT gorge are characterized by debris flow deposits of various extent. Debris flows have a specific slope-drainage area relationship that curves in log-log space. Using high-resolution topographic data, we are able to provide further evidence for this phenomenon and characterize the distinct topographic signature of debris flows. We specifically focus on the transition zone between debris-flow and fluvial processes, which is variable in the different catchments. The transition is characterized by a pronounced kink revealed in slope-drainage plots, as well as an increase of slope scatter in the drainage area logbins. We propose that the presence and location of this kink reflects the nature of the dominating transport processes in the corresponding catchments. In light of these observations we discriminate between debris-flow and fluvially dominated catchments in the QdT and identify regions that primarily exhibit slope movement. Our new results reveal a cluster of fluvial catchments to the SE of our study area – an area that receives significantly more moisture than upstream regions. In contrast, debris flows are prominent in areas of sparse vegetation, where occasional extreme rainfall events are efficient in transporting large amounts of talus downhill. These observations are key to a better understanding of the relationships between the impact of extreme rainfalls at high elevation and the formation of large volumes of sediment in the arid highlands of the Andes.</p>

<p>The increase in freely available optical satellite data with 10-15 m spatial resolution offers new opportunities to monitor slow-moving landslides and study their past movements through image cross-correlation in difficult-to-access regions around the world. Here, we explore this potential using Landsat-8 and Sentinel-2 optical satellite imagery to detect and quantify slope movements in the northwestern Argentine Andes over the past eight years. Our study takes advantage of the large spatial and temporal availability of optical satellite imagery, but we also show the caveats associated with cross-correlation for slow-moving targets. The northwestern Argentine Andes, particularly the mountain ranges that border the Central Andean Plateau (Altiplano-Puna Plateau), are predisposed to slope movements because of their steep hillslopes, weakened lithologies, sparse vegetation cover, and frequent rainfall events. Previous studies based on radar interferometry have identified several landslides moving at ~1 m/yr throughout our study area. We use these areas of known offset to identify optimal processing routines, evaluate their accuracy, and define the limitations of monitoring the movement of slow-moving landslides with optical imagery. We present approaches to pre- and post-correlation filtering to reduce noise and increase signal strength and further validate our results with high spatial resolution imagery (1-3 m). In this way, we aim to better constrain the distribution of slow-moving landslides throughout our study area and understand the driving factors of past and present slope movements at the regional scale.</p>

<p>Resolving Earth’s surface at the meter scale is essential for an improved understanding of topographic signatures generated by debris-flow activity in high-relief mountainous terrains. Here, we explore the applicability and potential of digital elevation models (DEMs) derived from stereo-photogrammetry for debris-flow detection in the southern Central Andes of NW Argentina. Our analysis relies on a high-resolution (3 m) DEM created from SPOT-7 tri-stereo satellite data. We carefully validated DEM quality with ~5000 differential GPS points for an area of 245 km² in the Quebrada del Toro basin within the Eastern Cordillera.<span> </span></p><p>We build upon previous work that suggests that debris flows have a distinct signature in the drainage area and slope framework: debris-flow channels exhibit a nearly constant slope (no channel curvature), while channels dominated by fluvial transport processes show a negative power-law behavior in log-log space. Drainage-area approaches in geomorphic analysis are fast and efficient tools to distinguish signatures of debris-flow and fluvial transport processes, yet they might introduce an averaging bias because upstream areas are analyzed jointly.<span> </span></p><p>For a more precise localization and assessment of debris-flow activity, we evaluate topographic signatures of individual channels. We present a new approach that relies on connected components of similar slope that can be attributed to different transport regimes. Debris-flow activity reflects particularly steep segments of medium connected-component lengths in small drainage areas. The spatial occurrence and lengths of these segments are controlled by geologic and lithologic boundary conditions and we find that the highest debris-flow activity corresponds with steep slopes in areas documented Quaternary tectonic activity and the exposure of pervasively fractured bedrock. Comparing our results to topographic signatures of the corresponding catchments in log-log space, we show that individual channel approaches allow to better detect intra-catchment variability. These are imperative for understanding erosion and sediment-transport processes in the river channel. Since high-resolution data are needed to reliably resolve debris-flow channels, our meter-scale DEMs greatly improve the localization and prediction of debris-flow activity. Thus, for evaluations of recurring hazardous debris-flow activity in extensive, remote, and sparsely vegetated mountainous landscapes, stereo-photogrammetry presents a very suitable and cost-efficient alternative to airborne lidar data.<span> </span></p>