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Ex post landslide mapping for emergency response and ex ante landslide susceptibility modelling for hazard mitigation are two important application scenarios that require the development of accurate, yet cost-effective spatial landslide models. However, the manual labelling of instances for training machine learning models is time-consuming given the data requirements of flexible data-driven algorithms and the small percentage of area covered by landslides. Active learning aims to reduce labelling costs by selecting more informative instances. In this study, two common active-learning strategies, uncertainty sampling and query by committee, are combined with the support vector machine (SVM), a state-of-the-art machine-learning technique, in a landslide mapping case study in order to assess their possible benefits compared to simple random sampling of training locations. By selecting more “informative” instances, the SVMs with active learning based on uncertainty sampling outperformed both random sampling and query-by-committee strategies when considering mean AUROC (area under the receiver operating characteristic curve) as performance measure. Uncertainty sampling also produced more stable performances with a smaller AUROC standard deviation across repetitions. In conclusion, under limited data conditions, uncertainty sampling reduces the amount of expert time needed by selecting more informative instances for SVM training. We therefore recommend incorporating active learning with uncertainty sampling into interactive landslide modelling workflows, especially in emergency response settings, but also in landslide susceptibility modelling.
Zhihao Wang; Alexander Brenning. Active-Learning Approaches for Landslide Mapping Using Support Vector Machines. Remote Sensing 2021, 13, 2588 .
AMA StyleZhihao Wang, Alexander Brenning. Active-Learning Approaches for Landslide Mapping Using Support Vector Machines. Remote Sensing. 2021; 13 (13):2588.
Chicago/Turabian StyleZhihao Wang; Alexander Brenning. 2021. "Active-Learning Approaches for Landslide Mapping Using Support Vector Machines." Remote Sensing 13, no. 13: 2588.
The dynamics of forest recovery after windthrows (i.e., broken or uprooted trees by wind) are poorly understood in tropical forests. The Northwestern Amazon (NWA) is characterized by a higher occurrence of windthrows, greater rainfall, and higher annual tree mortality rates (~2%) than the Central Amazon (CA). We combined forest inventory data from three sites in the Iquitos region of Peru, with recovery periods spanning 2, 12, and 22 years following windthrow events. Study sites and sampling areas were selected by assessing the windthrow severity using remote sensing. At each site, we recorded all trees with a diameter at breast height (DBH) ≥ 10 cm along transects, capturing the range of windthrow severity from old-growth to highly disturbed (mortality > 60%) forest. Across all damage classes, tree density and basal area recovered to >90% of the old-growth values after 20 years. Aboveground biomass (AGB) in old-growth forest was 380 (±156) Mg ha−1. In extremely disturbed areas, AGB was still reduced to 163 (±68) Mg ha−1 after 2 years and 323 (± 139) Mg ha−1 after 12 years. This recovery rate is ~50% faster than that reported for Central Amazon forests. The faster recovery of forest structure in our study region may be a function of its higher productivity and adaptability to more frequent and severe windthrows. These varying rates of recovery highlight the importance of extreme wind and rainfall on shaping gradients of forest structure in the Amazon, and the different vulnerabilities of these forests to natural disturbances whose severity and frequency are being altered by climate change.
J. Urquiza Muñoz; Daniel Magnabosco Marra; Robinson Negrón-Juarez; Rodil Tello-Espinoza; Waldemar Alegría-Muñoz; Tedi Pacheco-Gómez; Sami Rifai; Jeffrey Chambers; Hillary Jenkins; Alexander Brenning; Susan Trumbore. Recovery of Forest Structure Following Large-Scale Windthrows in the Northwestern Amazon. Forests 2021, 12, 667 .
AMA StyleJ. Urquiza Muñoz, Daniel Magnabosco Marra, Robinson Negrón-Juarez, Rodil Tello-Espinoza, Waldemar Alegría-Muñoz, Tedi Pacheco-Gómez, Sami Rifai, Jeffrey Chambers, Hillary Jenkins, Alexander Brenning, Susan Trumbore. Recovery of Forest Structure Following Large-Scale Windthrows in the Northwestern Amazon. Forests. 2021; 12 (6):667.
Chicago/Turabian StyleJ. Urquiza Muñoz; Daniel Magnabosco Marra; Robinson Negrón-Juarez; Rodil Tello-Espinoza; Waldemar Alegría-Muñoz; Tedi Pacheco-Gómez; Sami Rifai; Jeffrey Chambers; Hillary Jenkins; Alexander Brenning; Susan Trumbore. 2021. "Recovery of Forest Structure Following Large-Scale Windthrows in the Northwestern Amazon." Forests 12, no. 6: 667.
Global greening trends have been widely reported based on long‐term remote‐sensing data of terrestrial ecosystems. Typically, a hypothesis test is performed for each grid cell; this leads to multiple hypothesis testing and false positive trend detection. We reanalyze global greening and account for this issue with a novel statistical method that allows robust inference on greening regions. Based on leaf area index (LAI) data, our methods reduce the detected greening from 35.2% to 15.3% of the terrestrial land surface; this reduction is most notable in non‐woody vegetation. Our results confirm several greening regions (China, India, Europe, Sahel, North America, Brazil, and Siberia), that are also supported by independent data products. We also report evidence for an increasing seasonal amplitude in LAI north of 35°N. Considering the widespread use of spatially replicated trend tests in global change research, we recommend adopting the proposed multiple testing procedure to control false positive outcomes.
José Cortés; Miguel D. Mahecha; Markus Reichstein; Ranga B. Myneni; Chi Chen; Alexander Brenning. Where Are Global Vegetation Greening and Browning Trends Significant? Geophysical Research Letters 2021, 48, 1 .
AMA StyleJosé Cortés, Miguel D. Mahecha, Markus Reichstein, Ranga B. Myneni, Chi Chen, Alexander Brenning. Where Are Global Vegetation Greening and Browning Trends Significant? Geophysical Research Letters. 2021; 48 (6):1.
Chicago/Turabian StyleJosé Cortés; Miguel D. Mahecha; Markus Reichstein; Ranga B. Myneni; Chi Chen; Alexander Brenning. 2021. "Where Are Global Vegetation Greening and Browning Trends Significant?" Geophysical Research Letters 48, no. 6: 1.
Raphael Knevels; Alexander Brenning; Simone Gingrich; Elisabeth Gruber; Theresia Lechner; Philip Leopold; Helene Petschko; Christoph Plutzar. Kulturlandschaft im Wandel: Ein indikatorenbasierter Rückblick bis in das 19. Jahrhundert. Fallstudie anhand der Gemeinden Waidhofen/Ybbs und Paldau. Mitteilungen der Österreichischen Geographischen Gesellschaft 2021, 1, 255 -285.
AMA StyleRaphael Knevels, Alexander Brenning, Simone Gingrich, Elisabeth Gruber, Theresia Lechner, Philip Leopold, Helene Petschko, Christoph Plutzar. Kulturlandschaft im Wandel: Ein indikatorenbasierter Rückblick bis in das 19. Jahrhundert. Fallstudie anhand der Gemeinden Waidhofen/Ybbs und Paldau. Mitteilungen der Österreichischen Geographischen Gesellschaft. 2021; 1 ():255-285.
Chicago/Turabian StyleRaphael Knevels; Alexander Brenning; Simone Gingrich; Elisabeth Gruber; Theresia Lechner; Philip Leopold; Helene Petschko; Christoph Plutzar. 2021. "Kulturlandschaft im Wandel: Ein indikatorenbasierter Rückblick bis in das 19. Jahrhundert. Fallstudie anhand der Gemeinden Waidhofen/Ybbs und Paldau." Mitteilungen der Österreichischen Geographischen Gesellschaft 1, no. : 255-285.
In June 2009 and September 2014, the Styrian Basin in Austria was affected by extreme events of heavy thunderstorms, triggering thousands of landslides. Since the relationship between intense rainfall, land cover/land use (LULC), and landslide occurrences is still not fully understood, our objective was to develop a model design that allows to assess landslide susceptibility specifically for past triggering events. We used generalized additive models (GAM) to link land surface, geology, meteorological, and LULC variables to observed slope failures. Accounting for the temporal variation in landslide triggering, we implemented an innovative spatio-temporal approach for landslide absence sampling. We assessed model performance using k-fold cross-validation in space and time to estimate the area under the receiver operating characteristic curve (AUROC). Furthermore, we analyzed the variable importance and its relationship to landslide occurrence. Our results showed that the models had on average acceptable to outstanding landslide discrimination capabilities (0.81–0.94 mAUROC in space and 0.72–0.95 mAUROC in time). Furthermore, meteorological and LULC variables were of great importance in explaining the landslide events (e.g., five-day rainfall 13.6–17.8% mean decrease in deviance explained), confirming their usefulness in landslide event analysis. Based on the present findings, future studies may assess the potential of this approach for developing future storylines of slope instability based on climate and LULC scenarios.
Raphael Knevels; Helene Petschko; Herwig Proske; Philip Leopold; Douglas Maraun; Alexander Brenning. Event-Based Landslide Modeling in the Styrian Basin, Austria: Accounting for Time-Varying Rainfall and Land Cover. Geosciences 2020, 10, 1 .
AMA StyleRaphael Knevels, Helene Petschko, Herwig Proske, Philip Leopold, Douglas Maraun, Alexander Brenning. Event-Based Landslide Modeling in the Styrian Basin, Austria: Accounting for Time-Varying Rainfall and Land Cover. Geosciences. 2020; 10 (6):1.
Chicago/Turabian StyleRaphael Knevels; Helene Petschko; Herwig Proske; Philip Leopold; Douglas Maraun; Alexander Brenning. 2020. "Event-Based Landslide Modeling in the Styrian Basin, Austria: Accounting for Time-Varying Rainfall and Land Cover." Geosciences 10, no. 6: 1.
With the increased availability of high-resolution digital terrain models (HRDTM) generated using airborne light detection and ranging (LiDAR), new opportunities for improved mapping of geohazards such as landslides arise. While the visual interpretation of LiDAR, HRDTM hillshades is a widely used approach, the automatic detection of landslides is promising to significantly speed up the compilation of inventories. Previous studies on automatic landslide detection often used a combination of optical imagery and geomorphometric data, and were implemented in commercial software. The objective of this study was to investigate the potential of open source software for automated landslide detection solely based on HRDTM-derived data in a study area in Burgenland, Austria. We implemented a geographic object-based image analysis (GEOBIA) consisting of (1) the calculation of land-surface variables, textural features and shape metrics, (2) the automated optimization of segmentation scale parameters, (3) region-growing segmentation of the landscape, (4) the supervised classification of landslide parts (scarp and body) using support vector machines (SVM), and (5) an assessment of the overall classification performance using a landslide inventory. We used the free and open source data-analysis environment R and its coupled geographic information system (GIS) software for the analysis; our code is included in the Supplementary Materials. The developed approach achieved a good performance (κ = 0.42) in the identification of landslides.
Raphael Knevels; Helene Petschko; Philip Leopold; Alexander Brenning. Geographic Object-Based Image Analysis for Automated Landslide Detection Using Open Source GIS Software. ISPRS International Journal of Geo-Information 2019, 8, 551 .
AMA StyleRaphael Knevels, Helene Petschko, Philip Leopold, Alexander Brenning. Geographic Object-Based Image Analysis for Automated Landslide Detection Using Open Source GIS Software. ISPRS International Journal of Geo-Information. 2019; 8 (12):551.
Chicago/Turabian StyleRaphael Knevels; Helene Petschko; Philip Leopold; Alexander Brenning. 2019. "Geographic Object-Based Image Analysis for Automated Landslide Detection Using Open Source GIS Software." ISPRS International Journal of Geo-Information 8, no. 12: 551.
Water resources are critical in semiarid Xinjiang, northwestern China, a mountainous region that heavily relies on meltwater, making it sensitive to climate change. A better understanding of climatic and hydrological changes is therefore highly required for water resources management. In this review, spatio-temporal climate change, climate extremes, snow and glacier fluctuations and variability in semiarid Xinjiang are summarized. In general terms, the available historical data demonstrate a rising mean temperature, likely increased precipitation (subject to greater uncertainty), declining snow cover and glacier extent, and increased streamflow in most rivers. Although the changes of projected future climate differ with different climate resembles, average temperature is expected to increase and seasonal precipitation will experience a slightly increase tendency. Additionally, climate extremes are predicted to become more frequent. Projected future streamflow is expected to increase although initial increase may be followed by a long-term decrease. Water demand is predicted to increase due to irrigation, population growth and economic development. We thereby conclude that water variability in semiarid Xinjiang is and will further be affected by future climate change and their hydrological impacts. However, climatic and hydrological changes differ in different basins, and the impacts of climate change on hydrological changes cannot be generalized. Historical and future climatic and hydrological changes have possible implications for vegetation and can intensify regional hydrological cycle and enhance pressure on seasonal water availability. Future research on climatic and hydrological changes in this region should reveal the mechanisms behind the change phenomenon, quantify the implications on water resources management and expand observational networks, in particular focus on snow and glacier melt processes, as meltwater is a crucial water source in this region. This research may provide suggestions for water resources management in semiarid Xinjiang and endorheic basins where totally depending on water from the surrounding mountains in central Asia or elsewhere.
Yan-Jun Shen; Ying Guo; Yucui Zhang; Hongwei Pei; Alexander Brenning. Review of historical and projected future climatic and hydrological changes in mountainous semiarid Xinjiang (northwestern China), central Asia. CATENA 2019, 187, 104343 .
AMA StyleYan-Jun Shen, Ying Guo, Yucui Zhang, Hongwei Pei, Alexander Brenning. Review of historical and projected future climatic and hydrological changes in mountainous semiarid Xinjiang (northwestern China), central Asia. CATENA. 2019; 187 ():104343.
Chicago/Turabian StyleYan-Jun Shen; Ying Guo; Yucui Zhang; Hongwei Pei; Alexander Brenning. 2019. "Review of historical and projected future climatic and hydrological changes in mountainous semiarid Xinjiang (northwestern China), central Asia." CATENA 187, no. : 104343.
Jason Goetz; Alexander Brenning. Quantifying Uncertainties in Snow Depth Mapping From Structure From Motion Photogrammetry in an Alpine Area. Water Resources Research 2019, 55, 7772 -7783.
AMA StyleJason Goetz, Alexander Brenning. Quantifying Uncertainties in Snow Depth Mapping From Structure From Motion Photogrammetry in an Alpine Area. Water Resources Research. 2019; 55 (9):7772-7783.
Chicago/Turabian StyleJason Goetz; Alexander Brenning. 2019. "Quantifying Uncertainties in Snow Depth Mapping From Structure From Motion Photogrammetry in an Alpine Area." Water Resources Research 55, no. 9: 7772-7783.
Antarctic marine ecosystems undergo enormous changes, presumably due to climate change and fishery. Unmanned aerial vehicles (UAVs) have an unprecedented potential for measuring these changes by mapping indicator species such as penguins even in remote areas. We used a battery-powered fixed-wing UAV to survey colonies along a 30-km stretch of the remote coast of southwest King George Island and northwest Nelson Island (South Shetland Islands, Antarctica) during the austral summer 2016/17. With multiple flights, we covered a total distance of 317 km. We determined the exact position of 14 chinstrap penguin colonies, including two small unknown colonies, with a total abundance of 35,604 adults. To model the number of occupied nests based on the number of adults counted in the UAV imagery we used data derived from terrestrial time-lapse imagery. The comparison with previous studies revealed a decline in the total abundance of occupied nests. However, we also found four chinstrap penguin colonies that have grown since the 1980s against the general trend on the South Shetland Islands. The results proved the suitability of the use of small and lightweight fixed-wing UAVs with electric engines for mapping penguin colonies in remote areas in the Antarctic.
Christian Pfeifer; Andres Barbosa; Osama Mustafa; Hans-Ulrich Peter; Marie-Charlott Rümmler; Alexander Brenning. Using Fixed-Wing UAV for Detecting and Mapping the Distribution and Abundance of Penguins on the South Shetlands Islands, Antarctica. Drones 2019, 3, 39 .
AMA StyleChristian Pfeifer, Andres Barbosa, Osama Mustafa, Hans-Ulrich Peter, Marie-Charlott Rümmler, Alexander Brenning. Using Fixed-Wing UAV for Detecting and Mapping the Distribution and Abundance of Penguins on the South Shetlands Islands, Antarctica. Drones. 2019; 3 (2):39.
Chicago/Turabian StyleChristian Pfeifer; Andres Barbosa; Osama Mustafa; Hans-Ulrich Peter; Marie-Charlott Rümmler; Alexander Brenning. 2019. "Using Fixed-Wing UAV for Detecting and Mapping the Distribution and Abundance of Penguins on the South Shetlands Islands, Antarctica." Drones 3, no. 2: 39.
In this study, we propose a methodology to estimate the spatial distribution of destabilizing rock glaciers, with a focus on the French Alps. We mapped geomorphological features that can be typically found in cases of rock glacier destabilization (e.g. crevasses and scarps) using orthoimages taken from 2000 to 2013. A destabilization rating was assigned by taking into account the evolution of these mapped destabilization geomorphological features and by observing the surface deformation patterns of the rock glacier, also using the available orthoimages. This destabilization rating then served as input to model the occurrence of rock glacier destabilization in relation to terrain attributes and to spatially predict the susceptibility to destabilization at a regional scale. Significant evidence of destabilization could be observed in 46 rock glaciers, i.e. 10 % of the total active rock glaciers in the region. Based on our susceptibility model of destabilization occurrence, it was found that this phenomenon is more likely to occur in elevations around the 0 ∘C isotherm (2700–2900 m a.s.l.), on north-facing slopes, steep terrain (25 to 30∘) and flat to slightly convex topographies. Model performance was good (AUROC = 0.76), and the susceptibility map also performed well at reproducing observable patterns of destabilization. About 3 km2 of creeping permafrost, or 10 % of the surface occupied by active rock glaciers, had a high susceptibility to destabilization. Considering we observed that only half of these areas of creep are currently showing destabilization evidence, we suspect there is a high potential for future rock glacier destabilization within the French Alps.
Marco Marcer; Charlie Serrano; Alexander Brenning; Xavier Bodin; Jason Goetz; Philippe Schoeneich. Evaluating the destabilization susceptibility of active rock glaciers in the French Alps. The Cryosphere 2019, 13, 141 -155.
AMA StyleMarco Marcer, Charlie Serrano, Alexander Brenning, Xavier Bodin, Jason Goetz, Philippe Schoeneich. Evaluating the destabilization susceptibility of active rock glaciers in the French Alps. The Cryosphere. 2019; 13 (1):141-155.
Chicago/Turabian StyleMarco Marcer; Charlie Serrano; Alexander Brenning; Xavier Bodin; Jason Goetz; Philippe Schoeneich. 2019. "Evaluating the destabilization susceptibility of active rock glaciers in the French Alps." The Cryosphere 13, no. 1: 141-155.
Diplodia sapinea and Diplodia scrobiculata are opportunistic pathogens of Pinus species. Several studies about taxonomy, impact and epidemiology of these fungi have been conducted in previous years, which have provided useful information and have raised new issues. These diseases produce a considerable impact on plantations resulting in significant economic losses. The main aims of this study are to increase the knowledge of the potential of genetic exchange and the relative aggressiveness of these organisms that can persist in healthy tissues of asymptomatic trees. A collection of 250 isolates among which are 149 strains collected from Pinus radiata plantations in Basque Country (Spain) and 101 strains from different countries was included in this work. Mating type ratios were analysed and compared using the structure of the MAT locus (MAT1‐1‐1 and MAT1‐2‐1). Inoculations of Pinus radiata seedlings were performed in a biosafety greenhouse (P2) to confirm pathogenicity of isolates and compare their aggressiveness. The frequency of occurrence of both idiomorphs of D. sapinea in Basque Country isolates was close to 1:1, however, for collection of isolates of this fungus from around the world, the ratio was 1:2. Furthermore, the spatial distribution of the two mating types in the Basque Country was random. Despite no detection of a sexual state, these results could suggest sexual reproduction behaviour. The pathogenicity of all strains in the collection was confirmed. Although aggressiveness (in terms of lesion lengths resulting from inoculation) varied greatly, no statistically significant effects of MAT type or pathogen species were detected.
Tania Manzanos; Glen R. Stanosz; Denise R. Smith; Jannes Muenchow; Patrick Schratz; Alexander Brenning; Ana Aragones; Eugenia Iturritxa. Mating type ratios and pathogenicity in Diplodia shoot blight fungi populations: Comparative analysis. Forest Pathology 2018, 49, e12475 .
AMA StyleTania Manzanos, Glen R. Stanosz, Denise R. Smith, Jannes Muenchow, Patrick Schratz, Alexander Brenning, Ana Aragones, Eugenia Iturritxa. Mating type ratios and pathogenicity in Diplodia shoot blight fungi populations: Comparative analysis. Forest Pathology. 2018; 49 (1):e12475.
Chicago/Turabian StyleTania Manzanos; Glen R. Stanosz; Denise R. Smith; Jannes Muenchow; Patrick Schratz; Alexander Brenning; Ana Aragones; Eugenia Iturritxa. 2018. "Mating type ratios and pathogenicity in Diplodia shoot blight fungi populations: Comparative analysis." Forest Pathology 49, no. 1: e12475.
Knowing the extent of degrading permafrost is a key issue in the context of emerging risks linked to climate change. In the present study we propose a methodology to estimate the spatial distribution of this phenomenon, focusing on the French Alps. At first, using recent orthoimages (2000 to 2013) covering the study region, we mapped the geomorphological features that can be typically found in cases of rock glacier destabilization (e.g. crevasses and scarps). This database was then used as support tool to rate rock glaciers destabilization. The destabilization rating was assigned also taking into account the surface deformation patterns of the rock glacier, observable by comparing the orthoimages. The destabilization rating served as database to model the occurrence of destabilization in relation to terrain attributes and to predict the susceptibility to destabilization at the regional scale. Potential destabilization could be observed in 58 rock glaciers, i.e. 12 of the total active rock glaciers in the region. Potentially destabilized rock glaciers were found to be more prone to strong acceleration than stable rock glaciers within the period 2000–2013. Modelling the occurrence of destabilization suggested that this phenomenon is more likely to occur in elevations around the 0 °C isotherm (2700–2900 m.s.l.), on north-exposed, steep (up to 30°) and flat to slightly convex topographies. Model performances were good (AUROC: 0.76) and the susceptibility map reproduced well the observable patterns. About 3 km2 of creeping permafrost, i.e. 10 % of the surface occupied by active rock glaciers, had a high susceptibility to destabilization. Only half of this surface is currently showing destabilization evidence, suggesting that a significant amount of rock glaciers are candidates for future destabilization.
Marco Marcer; Charlie Serrano; Alexander Brenning; Xavier Bodin; Jason Goetz; Philippe Schoeneich. Inferring the destabilization susceptibility of mountain permafrost in the French Alps using an inventory of destabilized rock glaciers. 2018, 2018, 1 -30.
AMA StyleMarco Marcer, Charlie Serrano, Alexander Brenning, Xavier Bodin, Jason Goetz, Philippe Schoeneich. Inferring the destabilization susceptibility of mountain permafrost in the French Alps using an inventory of destabilized rock glaciers. . 2018; 2018 ():1-30.
Chicago/Turabian StyleMarco Marcer; Charlie Serrano; Alexander Brenning; Xavier Bodin; Jason Goetz; Philippe Schoeneich. 2018. "Inferring the destabilization susceptibility of mountain permafrost in the French Alps using an inventory of destabilized rock glaciers." 2018, no. : 1-30.
The accuracy of digital elevation models (DEMs) derived from structure-from-motion (SFM) multi-view stereo (MVS) 3D reconstruction is commonly computed for a single realization of model elevations. This approach may be adequate to estimate an overall measure of systematic error; however, it cannot provide a good estimation of measurement precision. Knowing measurement precision is crucial for measuring elevation surface changes observed by DEM comparisons. In this paper, we illustrate an approach to characterize spatial variation in the precision for SFM-MVS derived DEMs. We use a snow-covered surface of an active rock glacier located in the southern French Alps as the case study. A spatially varying precision estimate is calculated from repeated close-range aerial surveys for a single acquisition period by calculating the standard deviation per grid cell between the DEMs created for each flight repetition. Regression analysis using a generalized additive model (GAM) is performed to model the estimated precision and provide insights regarding how sensor, survey design and field site conditions may spatially influence the measurement precision. Additionally, we define how DEM error can be described differently depending on the available validation data. In our study image height above ground level and distance to ground control points had the greatest explanatory power for spatial variation in DEM precision. Image overlap, mean reprojection error and saturation were also useful for explaining spatially varying measurement precision of the DEMs. Field site characteristics, such as slope angle and shading, had the least importance in our model of precision. From a practical point of view, regression-modeled relationships between precision and image and site characteristics can be utilized to design future surveys with similar sensing platforms and site conditions for improved DEM precision.
Jason Goetz; Alexander Brenning; Marco Marcer; Xavier Bodin. Modeling the precision of structure-from-motion multi-view stereo digital elevation models from repeated close-range aerial surveys. Remote Sensing of Environment 2018, 210, 208 -216.
AMA StyleJason Goetz, Alexander Brenning, Marco Marcer, Xavier Bodin. Modeling the precision of structure-from-motion multi-view stereo digital elevation models from repeated close-range aerial surveys. Remote Sensing of Environment. 2018; 210 ():208-216.
Chicago/Turabian StyleJason Goetz; Alexander Brenning; Marco Marcer; Xavier Bodin. 2018. "Modeling the precision of structure-from-motion multi-view stereo digital elevation models from repeated close-range aerial surveys." Remote Sensing of Environment 210, no. : 208-216.
Yanjun Shen; Manfred Fink; Sven Kralisch; Yaning Chen; Alexander Brenning. Trends and variability in streamflow and snowmelt runoff timing in the southern Tianshan Mountains. Journal of Hydrology 2018, 557, 173 -181.
AMA StyleYanjun Shen, Manfred Fink, Sven Kralisch, Yaning Chen, Alexander Brenning. Trends and variability in streamflow and snowmelt runoff timing in the southern Tianshan Mountains. Journal of Hydrology. 2018; 557 ():173-181.
Chicago/Turabian StyleYanjun Shen; Manfred Fink; Sven Kralisch; Yaning Chen; Alexander Brenning. 2018. "Trends and variability in streamflow and snowmelt runoff timing in the southern Tianshan Mountains." Journal of Hydrology 557, no. : 173-181.
Understanding the water balance, especially as it relates to the distribution of runoff components, is crucial for water resource management and coping with the impacts of climate change. However, hydrological processes are poorly known in mountainous regions due to data scarcity and the complex dynamics of snow and glaciers. This study aims to provide a quantitative comparison of gridded precipitation products in the Tianshan Mountains, located in Central Asia and in order to further understand the mountain hydrology and distribution of runoff components in the glacierized Kaidu Basin. We found that gridded precipitation products are affected by inconsistent biases based on a spatiotemporal comparison with the nearest weather stations and should be evaluated with caution before using them as boundary conditions in hydrological modeling. Although uncertainties remain in this data‐scarce basin, driven by field survey data and bias‐corrected gridded data sets (ERA‐Interim and APHRODITE), the water balance and distribution of runoff components can be plausibly quantified based on the distributed hydrological model (J2000). We further examined parameter sensitivity and uncertainty with respect to both simulated streamflow and different runoff components based on an ensemble of simulations. This study demonstrated the possibility of integrating gridded products in hydrological modeling. The methodology used can be important for model applications and design in other data‐scarce mountainous regions. The model‐based simulation quantified the water balance and how the water resources are partitioned throughout the year in Tianshan Mountain basins, although the uncertainties present in this study result in important limitations.
Yanjun Shen; Manfred Fink; Sven Kralisch; Alexander Brenning. Unraveling the Hydrology of the Glacierized Kaidu Basin by Integrating Multisource Data in the Tianshan Mountains, Northwestern China. Water Resources Research 2018, 54, 557 -580.
AMA StyleYanjun Shen, Manfred Fink, Sven Kralisch, Alexander Brenning. Unraveling the Hydrology of the Glacierized Kaidu Basin by Integrating Multisource Data in the Tianshan Mountains, Northwestern China. Water Resources Research. 2018; 54 (1):557-580.
Chicago/Turabian StyleYanjun Shen; Manfred Fink; Sven Kralisch; Alexander Brenning. 2018. "Unraveling the Hydrology of the Glacierized Kaidu Basin by Integrating Multisource Data in the Tianshan Mountains, Northwestern China." Water Resources Research 54, no. 1: 557-580.
In the present study we used the first rock glacier inventory for the entire French Alps to model spatial permafrost distribution in the region. Climatic and topographic data evaluated at the rock glacier locations were used as predictor variables in a Generalized Linear Model. Model performances are strong, suggesting that, in agreement with several previous studies, this methodology is able to model accurately rock glacier distribution. A methodology to estimate model uncertainties is proposed, revealing that the subjectivity in the interpretation of rock glacier activity and contours may substantially bias the model. The model highlights a North-South trend in the regional pattern of permafrost distribution which is attributed to the climatic influences of the Atlantic and Mediterranean climates. Further analysis suggest that lower amounts of precipitation in the early winter and a thinner snow cover, as typically found in the Mediterranean area, could contribute to the existence of permafrost at higher temperatures compared to the Northern Alps. A comparison with the Alpine Permafrost Index Map (APIM) shows no major differences with our model, highlighting the very good predictive power of the APIM despite its tendency to slightly overestimate permafrost extension with respect to our database. The use of rock glaciers as indicators of permafrost existence despite their time response to climate change is discussed and an interpretation key is proposed in order to ensure the proper use of the model for research as well as for operational purposes.
Marco Marcer; Xavier Bodin; Alexander Brenning; Philippe Schoeneich; Raphaële Charvet; Frédéric Gottardi. Permafrost Favorability Index: Spatial Modeling in the French Alps Using a Rock Glacier Inventory. Frontiers in Earth Science 2017, 5, 1 .
AMA StyleMarco Marcer, Xavier Bodin, Alexander Brenning, Philippe Schoeneich, Raphaële Charvet, Frédéric Gottardi. Permafrost Favorability Index: Spatial Modeling in the French Alps Using a Rock Glacier Inventory. Frontiers in Earth Science. 2017; 5 ():1.
Chicago/Turabian StyleMarco Marcer; Xavier Bodin; Alexander Brenning; Philippe Schoeneich; Raphaële Charvet; Frédéric Gottardi. 2017. "Permafrost Favorability Index: Spatial Modeling in the French Alps Using a Rock Glacier Inventory." Frontiers in Earth Science 5, no. : 1.
Mountain permafrost and rock glaciers in the dry Andes are of growing interest due to the increase in mining industry and infrastructure development in this remote area. Empirical models of mountain permafrost distribution based on rock glacier activity status and temperature data have been established as a tool for regional-scale assessments of its distribution; this kind of model approach has never been applied for a large portion of the Andes. In the present study, this methodology is applied to map permafrost favourability throughout the semi-arid Andes of central Chile (29–32° S), excluding areas of exposed bedrock. After spatially modelling of the mean annual air temperature distribution from scarce temperature records (116 station years) using a linear mixed-effects model, a generalized additive model was built to model the activity status of 3524 rock glaciers. A permafrost favourability index (PFI) was obtained by adjusting model predictions for conceptual differences between permafrost and rock glacier distribution. The results indicate that the model has an acceptable performance (median AUROC: 0.76). Conditions highly favourable to permafrost presence (PFI ≥ 0.75) are predicted for 1051 km2 of mountain terrain, or 2.7 % of the total area of the watersheds studied. Favourable conditions are expected to occur in 2636 km2, or 6.8 % of the area. Substantial portions of the Elqui and Huasco watersheds are considered to be favourable for permafrost presence (11.8 % each), while in the Limarí and Choapa watersheds permafrost is expected to be mostly limited to specific sub-watersheds. In the future, local ground-truth observations will be required to confirm permafrost presence in favourable areas and to monitor permafrost evolution under the influence of climate change.
Guillermo F. Azócar; Alexander Brenning; Xavier Bodin. Permafrost distribution modelling in the semi-arid Chilean Andes. The Cryosphere 2017, 11, 877 -890.
AMA StyleGuillermo F. Azócar, Alexander Brenning, Xavier Bodin. Permafrost distribution modelling in the semi-arid Chilean Andes. The Cryosphere. 2017; 11 (2):877-890.
Chicago/Turabian StyleGuillermo F. Azócar; Alexander Brenning; Xavier Bodin. 2017. "Permafrost distribution modelling in the semi-arid Chilean Andes." The Cryosphere 11, no. 2: 877-890.
Adequate estimates of near-surface temperature lapse rate (γlocal) are needed to represent air temperature in remote mountain regions with sparse instrumental records such as the mountains of Central Asia. To identify the spatial and temporal variation of γlocal in the Tianshan Mountains, long term (1961-2011) daily maximum, mean and minimum temperature (Tmax, Tmean and Tmin) data from 17 weather stations and one year of temperature logger data were analyzed considering three subregions: Northern Slopes, Kaidu Basin and Southern Slopes. Simple linear regression was performed to identify relationships between elevation and temperature, revealing spatial and seasonal variation in γlocal. γlocal are higher on the Southern slopes than the Northern slopes due to topography and regional climate conditions. Seasonally, γlocal are more pronounced higher in the summer than in the winter months. γlocal are generally higher for Tmax than Tmean and Tmin. The Kaidu Basin shows similar seasonal variability, but with the highest γlocal for Tmean and Tmin occurring in the spring. Formation of γlocal patterns is associated with the interactions of climate factors in different subregions. Overall, annual mean γlocal for Tmax, Tmean and Tmin in the study's subregions are lower than the standard atmospheric lapse rates (6.5 °C km-1), which would therefore be an inadequate choice for representing the near-surface temperature conditions in this area. Our findings highlight the importance of spatial and temporal variation of γlocal in hydro-meteorological research in the data-sparse Tianshan Mountains.
Yan-Jun Shen; Jason Goetz; Alexander Brenning. Spatial-temporal variation of near-surface temperature lapse rates over the Tianshan Mountains, central Asia. Journal of Geophysical Research: Atmospheres 2016, 121, 14,006 -14,017.
AMA StyleYan-Jun Shen, Jason Goetz, Alexander Brenning. Spatial-temporal variation of near-surface temperature lapse rates over the Tianshan Mountains, central Asia. Journal of Geophysical Research: Atmospheres. 2016; 121 (23):14,006-14,017.
Chicago/Turabian StyleYan-Jun Shen; Jason Goetz; Alexander Brenning. 2016. "Spatial-temporal variation of near-surface temperature lapse rates over the Tianshan Mountains, central Asia." Journal of Geophysical Research: Atmospheres 121, no. 23: 14,006-14,017.
Remote sensing-based woody biomass quantification in sparsely-vegetated areas is often limited when using only common broadband vegetation indices as input data for correlation with ground-based measured biomass information. Red edge indices and texture attributes are often suggested as a means to overcome this issue. However, clear recommendations on the suitability of specific proxies to provide accurate biomass information in semi-arid to arid environments are still lacking. This study contributes to the understanding of using multispectral high-resolution satellite data (RapidEye), specifically red edge and texture attributes, to estimate wood volume in semi-arid ecosystems characterized by scarce vegetation. LASSO (Least Absolute Shrinkage and Selection Operator) and random forest were used as predictive models relating in situ-measured aboveground standing wood volume to satellite data. Model performance was evaluated based on cross-validation bias, standard deviation and Root Mean Square Error (RMSE) at the logarithmic and non-logarithmic scales. Both models achieved rather limited performances in wood volume prediction. Nonetheless, model performance increased with red edge indices and texture attributes, which shows that they play an important role in semi-arid regions with sparse vegetation.
Paul Schumacher; Bunafsha Mislimshoeva; Alexander Brenning; Harald Zandler; Martin Brandt; Cyrus Samimi; Thomas Koellner. Do Red Edge and Texture Attributes from High-Resolution Satellite Data Improve Wood Volume Estimation in a Semi-Arid Mountainous Region? Remote Sensing 2016, 8, 540 .
AMA StylePaul Schumacher, Bunafsha Mislimshoeva, Alexander Brenning, Harald Zandler, Martin Brandt, Cyrus Samimi, Thomas Koellner. Do Red Edge and Texture Attributes from High-Resolution Satellite Data Improve Wood Volume Estimation in a Semi-Arid Mountainous Region? Remote Sensing. 2016; 8 (7):540.
Chicago/Turabian StylePaul Schumacher; Bunafsha Mislimshoeva; Alexander Brenning; Harald Zandler; Martin Brandt; Cyrus Samimi; Thomas Koellner. 2016. "Do Red Edge and Texture Attributes from High-Resolution Satellite Data Improve Wood Volume Estimation in a Semi-Arid Mountainous Region?" Remote Sensing 8, no. 7: 540.
Empirical models are frequently applied to produce landslide susceptibility maps for large areas. Subsequent quantitative validation results are routinely used as the primary criteria to infer the validity and applicability of the final maps or to select one of several models. This study hypothesizes that such direct deductions can be misleading. The main objective was to explore discrepancies between the predictive performance of a landslide susceptibility model and the geomorphic plausibility of subsequent landslide susceptibility maps while a particular emphasis was placed on the influence of incomplete landslide inventories on modelling and validation results. The study was conducted within the Flysch Zone of Lower Austria (1354 km2) which is known to be highly susceptible to landslides of the slide-type movement. Sixteen susceptibility models were generated by applying two statistical classifiers (logistic regression and generalized additive model) and two machine learning techniques (random forest and support vector machine) separately for two landslide inventories of differing completeness and two predictor sets. The results were validated quantitatively by estimating the area under the receiver operating characteristic curve (AUROC) with single holdout and spatial cross-validation technique. The heuristic evaluation of the geomorphic plausibility of the final results was supported by findings of an exploratory data analysis, an estimation of odds ratios and an evaluation of the spatial structure of the final maps. The results showed that maps generated by different inventories, classifiers and predictors appeared differently while holdout validation revealed similar high predictive performances. Spatial cross-validation proved useful to expose spatially varying inconsistencies of the modelling results while additionally providing evidence for slightly overfitted machine learning-based models. However, the highest predictive performances were obtained for maps that explicitly expressed geomorphically implausible relationships indicating that the predictive performance of a model might be misleading in the case a predictor systematically relates to a spatially consistent bias of the inventory. Furthermore, we observed that random forest-based maps displayed spatial artefacts. The most plausible susceptibility map of the study area showed smooth prediction surfaces while the underlying model revealed a high predictive capability and was generated with an accurate landslide inventory and predictors that did not directly describe a bias. However, none of the presented models was found to be completely unbiased. This study showed that high predictive performances cannot be equated with a high plausibility and applicability of subsequent landslide susceptibility maps. We suggest that greater emphasis should be placed on identifying confounding factors and biases in landslide inventories. A joint discussion between modelers and decision makers of the spatial pattern of the final susceptibility maps in the field might increase their acceptance and applicability.
Stefan Steger; Alexander Brenning; Rainer Bell; Helene Petschko; Thomas Glade. Exploring discrepancies between quantitative validation results and the geomorphic plausibility of statistical landslide susceptibility maps. Geomorphology 2016, 262, 8 -23.
AMA StyleStefan Steger, Alexander Brenning, Rainer Bell, Helene Petschko, Thomas Glade. Exploring discrepancies between quantitative validation results and the geomorphic plausibility of statistical landslide susceptibility maps. Geomorphology. 2016; 262 ():8-23.
Chicago/Turabian StyleStefan Steger; Alexander Brenning; Rainer Bell; Helene Petschko; Thomas Glade. 2016. "Exploring discrepancies between quantitative validation results and the geomorphic plausibility of statistical landslide susceptibility maps." Geomorphology 262, no. : 8-23.