/pdf/landslide-inventory-maps-new-tools-for-an-old-problem-wkxin2jqxg.pdf

Landslide inventory maps: New tools for an old problem

Wheaton, J. M., Brasington, J., Darby, S. E., Sear, D. A. (2010). Accounting for uncertainty in DEMs from repeat topographic surveys: improved sediment budgets. Earth Surface Processes and Landforms, 35, (2), 136-156.

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Accounting for uncertainty in DEMs from repeat topographic surveys: improved sediment budgets

The UK has passed legislation that introduces the world’s first long-term legally binding framework to tackle the dangers of climate change (The Climate Change Act 20084). The act requires Government to set carbon budgets, which are limits on greenhouse gas emissions in the UK for consecutive five year periods. 
Models analysed in IPCC AR4 have a range of 0-60% for an AMOC decrease over the next 100 years. The RAPID-WATCH 26˚N observations provide the only continuous measurements of the AMOC strength and vertical structure, and are thus a vital monitoring tool for this key climate variable'.
Analysis of the PSMSL data set, reviewed by scientific panels such as the IPCC, inform studies of impacts of climate change on both national and international levels (e.g. UK Marine Climate Change Impacts Partnership (MCCIP), UK Climate Impacts Programme (UKCIP), UK Foresight Flood and Coastal Defence Review, Charting Progress and Charting Progress 2, IPCC Working Group II).

Climate change impacts

Human populations and their use of land have transformed most of the terrestrial biosphere into anthropogenic biomes (anthromes), causing a variety of novel ecological patterns and processes to emerge. To assess whether human populations and their use of land have directly altered the terrestrial biosphere sufficiently to indicate that the Earth system has entered a new geological epoch, spatially explicit global estimates of human populations and their use of land were analysed across the Holocene for their potential to induce irreversible novel transformation of the terrestrial biosphere. Human alteration of the terrestrial biosphere has been significant for more than 8000 years. However, only in the past century has the majority of the terrestrial biosphere been transformed into intensively used anthromes with predominantly novel anthropogenic ecological processes. At present, even were human populations to decline substantially or use of land become far more efficient, the current global extent, duration, type and intensity of human transformation of ecosystems have already irreversibly altered the terrestrial biosphere at levels sufficient to leave an unambiguous geological record differing substantially from that of the Holocene or any prior epoch. It remains to be seen whether the anthropogenic biosphere will be sustained and continue to evolve.

Anthropogenic transformation of the terrestrial biosphere

Published by the American Geophysical Union as part of the Water Resources Monograph Series, Volume 18. Landslides are a constant in shaping our landscape. Whether by large episodic, or smaller chronic, mass movements, our mountains, hills, valleys, rivers, and streams bear evidence of change from landslides. Combined with anthropogenic factors, especially the development and settlement of unstable terrain, landslides (as natural processes) have become natural disasters. This book charts our understanding of landslide processes, prediction methods, and related land use issues. How and where do landslides initiate? What are the human and economic consequences? What hazard assessment and prediction methods are available, and how well do they work? How does land use, from timber harvesting and road building to urban and industrial development, affect landslide distribution in time and space? And what is the effect of land use and climate change on landslides? [Book Synopsis]

Landslides: Processes, Prediction, and Land Use

High-resolution topographic data have the potential to differentiate the main morphological features of a landscape. This paper analyses the capability of airborne LiDAR-derived data in the recognition of channel-bed morphology. For the purpose of this study, 0.5 m and 1 m resolution Digital Terrain Models (DTMs) were derived from the last pulse LiDAR data obtained by filtering the vegetation points. The analysis was carried out both at 1-D scale, i.e. along the longitudinal channel profile, and at 2-D scale, taking into account the whole extent of the channel bed. The 1-D approach analyzed the residuals of elevations orthogonal to the regression line drawn along the channel profile and the standard deviation of local slope. The 2-D analysis was based on two roughness indexes, consisting on the local variability of the elevation and slope of the channel bed. The study was conducted in a headwater catchment located in the Eastern Italian Alps. The results suggested a good capability of LiDAR data in the recognition of river morphology giving the potential to distinguish the riffle-pool and step-pool reaches.

The effectiveness of airborne LiDAR data in the recognition of channel-bed morphology

Hillslope scale soil moisture variability in a steep alpine terrain

In recent years, new remote-sensed technologies, such as airborne and terrestrial laser scanner, have improved the detail and the quality of topographic information, providing topographical high-resolution and high-quality data over larger areas better than other technologies. A new generation of high-resolution (≤3 m) digital terrain models (DTMs) is now available for different areas and is widely used by researchers, offering new opportunities for the scientific community. These data call for the development of a new generation of methodologies for an objective extraction of geomorphic features, such as channel heads, channel networks, bank geometry, debris-flow channel, debris-flow deposits, scree slope, landslide and erosion scars, etc. A high-resolution DTM is able to detect the divergence/convergence of areas related to unchannelized/channelized processes with better detail than a coarse DTM. In this work, we tested the performance of new methodologies for an objective extraction of geomorphic features related to shallow landsliding processes (landslide crowns), and bank erosion in a complex mountainous terrain. Giving a procedure that automatically recognizes these geomorphic features can offer a strategic tool to map natural hazard and to ease the planning and the assessment of alpine regions. The methodologies proposed are based on the detection of thresholds derived by the statistical analysis of variability of landform curvature. The study was conducted on an area located in the Eastern Italian Alps, where an accurate field survey on shallow landsliding, erosive channelized processes, and a high-quality set of both terrestrial and airborne laser scanner elevation data is available. The analysis was conducted using a high-resolution DTM and different smoothing factors for landform curvature calculation in order to test the most suitable scale of curvature calculation for the recognition of the selected features. The results revealed that (1) curvature calculation is strongly scale-dependent, and an appropriate scale for derivation of the local geometry has to be selected according to the scale of the features to be detected; (2) such approach is useful to automatically detect and highlight the location of shallow slope failures and bank erosion, and it can assist the interpreter/operator to correctly recognize and delineate such phenomena. These results highlight opportunities but also challenges in fully automated methodologies for geomorphic feature extraction and recognition.

Giancarlo Dalla Fontana

Papers

The effectiveness of airborne LiDAR data in the recognition of channel-bed morphology

Hillslope scale soil moisture variability in a steep alpine terrain

Geomorphic features extraction from high-resolution topography: landslide crowns and bank erosion

Hillslope-to-valley transition morphology: new opportunities from high resolution DTMs.

Analysis of topographic and climatic control on rainfall-triggered shallow landsliding using a quasi-dynamic wetness index