Refine
Year of publication
Document Type
- Article (107)
- Postprint (16)
- Other (2)
- Part of a Book (1)
- Conference Proceeding (1)
- Doctoral Thesis (1)
- Review (1)
Keywords
- Himalaya (9)
- erosion (7)
- cosmogenic nuclides (5)
- InSAR (4)
- TRMM (4)
- extreme rainfall (4)
- lidar (4)
- remote sensing (4)
- Indian summer monsoon (3)
- Precipitation (3)
Institute
- Institut für Geowissenschaften (117)
- Institut für Umweltwissenschaften und Geographie (6)
- Institut für Physik und Astronomie (4)
- Extern (2)
- Mathematisch-Naturwissenschaftliche Fakultät (2)
- Referat für Presse- und Öffentlichkeitsarbeit (2)
- Institut für Mathematik (1)
- Interdisziplinäres Zentrum für Musterdynamik und Angewandte Fernerkundung (1)
Mapping urban forest leaf area index with airborne lidar using penetration metrics and allometry
(2015)
In urban areas, leaf area index (LAI) is a key ecosystem structural attribute with implications for energy and water balance, gas exchange, and anthropogenic energy use. In this study, we estimated LAI spatially using airborne lidar in downtown Santa Barbara, California, USA. We implemented two different modeling approaches. First, we directly estimated effective LAI (LAIe) using scan angle- and clump-corrected lidar laser penetration metrics (LPM). Second, we adapted existing allometric equations to estimate crown structural metrics including tree height and crown base height using lidar. The latter approach allowed for LAI estimates at the individual tree-crown scale. The LPM method, at both high and decimated point densities, resulted in good linear agreement with estimates from ground-based hemispherical photography (r(2) = 0.82, y = 0.99x) using a model that assumed a spherical leaf angle distribution. Within individual tree crown segments, the lidar estimates of crown structure closely paralleled field measurements (e.g., r(2) = 0.87 for crown length). LAI estimates based on the lidar crown measurements corresponded well with estimates from field measurements (r(2) = 0.84, y = 0.97x + 0.10). Consistency of the LPM and allometric lidar methods was also strong at 71 validation plots (r(2) = 0.88) and at 450 additional sample locations across the entire study area (r(2) = 0.72). This level of correspondence exceeded that of the canopy hemispherical photography and allometric, ground-based estimates (r(2) = 0.53). The first-order alignment of these two disparate methods may indicate that the error bounds for mapping LAI in cities are small enough to pursue large scale, spatially explicit estimation. (C) 2015 Elsevier Inc All rights reserved.
Mapping Damage-Affected Areas after Natural Hazard Events Using Sentinel-1 Coherence Time Series
(2018)
The emergence of the Sentinel-1A and 1B satellites now offers freely available and widely accessible Synthetic Aperture Radar (SAR) data. Near-global coverage and rapid repeat time (6–12 days) gives Sentinel-1 data the potential to be widely used for monitoring the Earth’s surface. Subtle land-cover and land surface changes can affect the phase and amplitude of the C-band SAR signal, and thus the coherence between two images collected before and after such changes. Analysis of SAR coherence therefore serves as a rapidly deployable and powerful tool to track both seasonal changes and rapid surface disturbances following natural disasters. An advantage of using Sentinel-1 C-band radar data is the ability to easily construct time series of coherence for a region of interest at low cost. In this paper, we propose a new method for Potentially Affected Area (PAA) detection following a natural hazard event. Based on the coherence time series, the proposed method (1) determines the natural variability of coherence within each pixel in the region of interest, accounting for factors such as seasonality and the inherent noise of variable surfaces; and (2) compares pixel-by-pixel syn-event coherence to temporal coherence distributions to determine where statistically significant coherence loss has occurred. The user can determine to what degree the syn-event coherence value (e.g., 1st, 5th percentile of pre-event distribution) constitutes a PAA, and integrate pertinent regional data, such as population density, to rank and prioritise PAAs. We apply the method to two case studies, Sarpol-e, Iran following the 2017 Iran-Iraq earthquake, and a landslide-prone region of NW Argentina, to demonstrate how rapid identification and interpretation of potentially affected areas can be performed shortly following a natural hazard event.
Mapping Damage-Affected Areas after Natural Hazard Events Using Sentinel-1 Coherence Time Series
(2018)
The emergence of the Sentinel-1A and 1B satellites now offers freely available and widely accessible Synthetic Aperture Radar (SAR) data. Near-global coverage and rapid repeat time (6–12 days) gives Sentinel-1 data the potential to be widely used for monitoring the Earth’s surface. Subtle land-cover and land surface changes can affect the phase and amplitude of the C-band SAR signal, and thus the coherence between two images collected before and after such changes. Analysis of SAR coherence therefore serves as a rapidly deployable and powerful tool to track both seasonal changes and rapid surface disturbances following natural disasters. An advantage of using Sentinel-1 C-band radar data is the ability to easily construct time series of coherence for a region of interest at low cost. In this paper, we propose a new method for Potentially Affected Area (PAA) detection following a natural hazard event. Based on the coherence time series, the proposed method (1) determines the natural variability of coherence within each pixel in the region of interest, accounting for factors such as seasonality and the inherent noise of variable surfaces; and (2) compares pixel-by-pixel syn-event coherence to temporal coherence distributions to determine where statistically significant coherence loss has occurred. The user can determine to what degree the syn-event coherence value (e.g., 1st, 5th percentile of pre-event distribution) constitutes a PAA, and integrate pertinent regional data, such as population density, to rank and prioritise PAAs. We apply the method to two case studies, Sarpol-e, Iran following the 2017 Iran-Iraq earthquake, and a landslide-prone region of NW Argentina, to demonstrate how rapid identification and interpretation of potentially affected areas can be performed shortly following a natural hazard event.
We modeled the two most extreme highstands of Lake Naivasha during the last 175 k.y. to estimate potential precipitation/ evaporation changes in this basin. In a first step, the bathymetry of the paleolakes at f135 and 9 k.y. BP was reconstructed from sediment cores and surface outcrops. Second, we modeled the paleohydrologic budget during the highstands using a simplified coupled energy mass-balance model. Our results show that the hydrologic and hence the climate conditions at f135 and 9 k.y. BP were similar, but significantly different from today. The main difference is a f15% higher value in precipitation compared to the present. An adaptation and migration of vegetation in the cause of climate changes would result in a f30% increase in precipitation. The most likely cause for such a wetter climate at f135 and 9 k.y. BP is a more intense intertropical convergence and increased precipitation in East Africa.
A valley-filling ignimbrite re-exposed through subsequent river incision at the southern margin of the Andean (Puna) plateau preserves pristine geological evidence of pre-late Miocene palaeotopography in the north western Argentine Andes. Our new Ar-40/(39) Ar dating of the Las Papas Ignimbrites yields a plateau age of 9.24 +/- 0.03 Ma, indicating valley-relief and orographic-barrier conditions comparable to the present-day. A later infill of Plio-Pleistocene coarse conglomerates has been linked to wetter conditions, but resulted in no additional net incision of the Las Papas valley, considering that the base of the ignimbrite remains unexposed in the valley bottom. Our observations indicate that at least 550 m of local plateau margin relief (and likely > 2 km) existed by 9 Ma at the southern Puna margin, which likely aided the efficiency of the orographic barrier to rainfall along the eastern and south eastern flanks of the Puna and causes aridity in the plateau interior.
Late Quaternary intensified monsoon phases control landscape evolution in the northwest Himalaya
(2005)
The intensity of the Asian summer-monsoon circulation varies over decadal to millennial time scales and is reflected in changes in surface processes, terrestrial environments, and marine sediment records. However, the mechanisms of long-lived (2-5 k.y.) intensified monsoon phases, the related changes in precipitation distribution, and their effect on landscape evolution and sedimentation rates are not yet well understood. The and high-elevation sectors of the orogen correspond to a climatically sensitive zone that currently receives rain only during abnormal (i.e., strengthened) monsoon seasons. Analogous to present-day rainfall anomalies, enhanced precipitation during an intensified monsoon phase is expected to have penetrated far into these geomorphic threshold regions where hillslopes are close to the angle of failure. We associate landslide triggering during intensified monsoon phases with enhanced precipitation, discharge, and sediment flux leading to an increase in pore-water pressure, lateral scouring of rivers, and over- steepening of hillslopes, eventually resulting in failure of slopes and exceptionally large mass movements. Here we use lacustrine deposits related to spatially and temporally clustered large landslides (>0.5 km(3)) in the Sutlej Valley region of the northwest Himalaya to calculate sedimentation rates and to infer rainfall patterns during late Pleistocene (29-24 ka) and Holocene (10-4 ka) intensified monsoon phases. Compared to present-day sediment-flux measurements, a fivefold increase in sediment-transport rates recorded by sediments in landslide-dammed lakes characterized these episodes of high climatic variability. These changes thus emphasize the pronounced imprint of millennial-scale climate change on surface processes and landscape evolution
The India-Eurasia continental collision zone provides a spectacular example of active mountain building and climatic forcing. In order to quantify the critically important process of mass removal, I analyzed spatial and temporal precipitation patterns of the oscillating monsoon system and their geomorphic imprints. I processed passive microwave satellite data to derive high-resolution rainfall estimates for the last decade and identified an abnormal monsoon year in 2002. During this year, precipitation migrated far into the Sutlej Valley in the northwestern part of the Himalaya and reached regions behind orographic barriers that are normally arid. There, sediment flux, mean basin denudation rates, and channel-forming processes such as erosion by debris-flows increased significantly. Similarly, during the late Pleistocene and early Holocene, solar forcing increased the strength of the Indian summer monsoon for several millennia and presumably lead to analogous precipitation distribution as were observed during 2002. However, the persistent humid conditions in the steep, high-elevation parts of the Sutlej River resulted in deep-seated landsliding. Landslides were exceptionally large, mainly due to two processes that I infer for this time: At the onset of the intensified monsoon at 9.7 ka BP heavy rainfall and high river discharge removed material stored along the river, and lowered the baselevel. Second, enhanced discharge, sediment flux, and increased pore-water pressures along the hillslopes eventually lead to exceptionally large landslides that have not been observed in other periods. The excess sediments that were removed from the upstream parts of the Sutlej Valley were rapidly deposited in the low-gradient sectors of the lower Sutlej River. Timing of downcutting correlates with centennial-long weaker monsoon periods that were characterized by lower rainfall. I explain this relationship by taking sediment flux and rainfall dynamics into account: High sediment flux derived from the upstream parts of the Sutlej River during strong monsoon phases prevents fluvial incision due to oversaturation the fluvial sediment-transport capacity. In contrast, weaker monsoons result in a lower sediment flux that allows incision in the low-elevation parts of the Sutlej River.
Piggyback basins on the margins of growing orogens commonly serve as sensitive recorders of the onset of thrust deformation and changes in source areas. The Bieertuokuoyi piggyback basin, located in the hanging wall of the Pamir Frontal Thrust, provides an unambiguous record of the outward growth of the northeast Pamir margin in northwest China from the Miocene through the Quaternary. To reconstruct the deformation along the margin, we synthesized structural mapping, stratigraphy, magnetostratigraphy, and cosmogenic burial dating of basin fill and growth strata. The Bieertuokuoyi basin records the initiation of the Pamir Frontal Thrust and the Takegai Thrust similar to 5-6Ma, as well as clast provenance and paleocurrent changes resulting from the Pliocene-to-Recent uplift and exhumation of the Pamir to the south. Our results show that coeval deformation was accommodated on the major structures on the northeast Pamir margin throughout the Miocene to Recent. Furthermore, our data support a change in the regional kinematics around the Miocene-Pliocene boundary (similar to 5-6Ma). Rapid exhumation of NE Pamir extensional domes, coupled with cessation of the Kashgar-Yecheng Transfer System on the eastern margin of the Pamir, accelerated the outward propagation of the northeastern Pamir margin and the southward propagation of the Kashi-Atushi fold-and-thrust belt in the southern Tian Shan. This coeval deformation signifies the coupling of the Pamir and Tarim blocks and the transfer of shortening north to the Pamir frontal faults and across the quasi-rigid Tarim Basin to the southern Tian Shan Kashi-Atushi fold-and-thrust system.
Fluvial fill terraces preserve sedimentary archives of landscape responses to climate change, typically over millennial timescales. In the Humahuaca Basin of NW Argentina (Eastern Cordillera, southern Central Andes), our 29 new optically stimulated luminescence ages of late Pleistocene fill terrace sediments demonstrate that the timing of past river aggradation occurred over different intervals on the western and eastern sides of the valley, despite their similar bedrock lithology, mean slopes, and precipitation. In the west, aggradation coincided with periods of increasing precipitation, while in the east, aggradation coincided with decreasing precipitation or more variable conditions. Erosion rates and grain size dependencies in our cosmogenic Be-10 analyses of modern and fill terrace sediments reveal an increased importance of landsliding compared to today on the west side during aggradation, but of similar importance during aggradation on the east side. Differences in the timing of aggradation and the Be-10 data likely result from differences in valley geometry, which causes sediment to be temporarily stored in perched basins on the east side. It appears as if periods of increasing precipitation triggered landslides throughout the region, which induced aggradation in the west, but blockage of the narrow bedrock gorges downstream from the perched basins in the east. As such, basin geometry and fluvial connectivity appear to strongly influence the timing of sediment movement through the system. For larger basins that integrate subbasins with differing geometries or degrees of connectivity (like Humahuaca), sedimentary responses to climate forcing are likely attenuated.
Introducing PebbleCounts
(2019)
Grain-size distributions are a key geomorphic metric of gravel-bed rivers. Traditional measurement methods include manual counting or photo sieving, but these are achievable only at the 1–10 ㎡ scale. With the advent of drones and increasingly high-resolution cameras, we can now generate orthoimagery over hectares at millimeter to centimeter resolution. These scales, along with the complexity of high-mountain rivers, necessitate different approaches for photo sieving. As opposed to other image segmentation methods that use a watershed approach, our open-source algorithm, PebbleCounts, relies on k-means clustering in the spatial and spectral domain and rapid manual selection of well-delineated grains. This improves grain-size estimates for complex riverbed imagery, without post-processing. We also develop a fully automated method, PebbleCountsAuto, that relies on edge detection and filtering suspect grains, without the k-means clustering or manual selection steps. The algorithms are tested in controlled indoor conditions on three arrays of pebbles and then applied to 12 × 1 ㎡ orthomosaic clips of high-energy mountain rivers collected with a camera-on-mast setup (akin to a low-flying drone). A 20-pixel b-axis length lower truncation is necessary for attaining accurate grain-size distributions. For the k-means PebbleCounts approach, average percentile bias and precision are 0.03 and 0.09 ψ, respectively, for ∼1.16 mm pixel⁻¹ images, and 0.07 and 0.05 ψ for one 0.32 mm pixel⁻¹ image. The automatic approach has higher bias and precision of 0.13 and 0.15 ψ, respectively, for ∼1.16 mm pixel⁻¹ images, but similar values of −0.06 and 0.05 ψ for one 0.32 mm pixel⁻¹ image. For the automatic approach, only at best 70 % of the grains are correct identifications, and typically around 50 %. PebbleCounts operates most effectively at the 1 ㎡ patch scale, where it can be applied in ∼5–10 min on many patches to acquire accurate grain-size data over 10–100 ㎡ areas. These data can be used to validate PebbleCountsAuto, which may be applied at the scale of entire survey sites (102–104 ㎡ ). We synthesize results and recommend best practices for image collection, orthomosaic generation, and grain-size measurement using both algorithms.