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Stefan Schneiderbauer
Afromontane Research Unit (ARU), Department of Geography, QwaQwa Campus, University of the Free State, Phuthaditjhaba 9866, South Africa

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Journal article
Published: 30 July 2021 in Sustainability
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The Maloti-Drakensberg (MD) is the largest and highest-elevation mountain system in southern Africa. Covering 40,000 km2 and reaching 3500 m, the MD provides a range of ecosystem services (ES) to the entire southern African region—benefitting diverse users and extending well beyond the mountains. Rapid socioecological change threatens the provision of ES and presents multidimensional challenges to sustainable development. However, the continued land degradation and persisting socioeconomic problems indicate that development policy has not been effective in tackling these issues. In this paper, a multidisciplinary literature review forms the basis of a discussion which takes an ES framing to scrutinise the multidimensional social, political, economic and cultural issues in the study area. Three critical management systems are presented, and their associated ES are discussed, namely, water transfer, rangelands and conservation and tourism. In particular, the diversity of ES uses and values in the MD is considered. The results reveal the main drivers of continued unsustainable development and highlight important information gaps.

ACS Style

Jess Delves; V. Clark; Stefan Schneiderbauer; Nigel Barker; Jörg Szarzynski; Stefano Tondini; João Vidal; Andrea Membretti. Scrutinising Multidimensional Challenges in the Maloti-Drakensberg (Lesotho/South Africa). Sustainability 2021, 13, 8511 .

AMA Style

Jess Delves, V. Clark, Stefan Schneiderbauer, Nigel Barker, Jörg Szarzynski, Stefano Tondini, João Vidal, Andrea Membretti. Scrutinising Multidimensional Challenges in the Maloti-Drakensberg (Lesotho/South Africa). Sustainability. 2021; 13 (15):8511.

Chicago/Turabian Style

Jess Delves; V. Clark; Stefan Schneiderbauer; Nigel Barker; Jörg Szarzynski; Stefano Tondini; João Vidal; Andrea Membretti. 2021. "Scrutinising Multidimensional Challenges in the Maloti-Drakensberg (Lesotho/South Africa)." Sustainability 13, no. 15: 8511.

Journal article
Published: 10 May 2021 in ISPRS International Journal of Geo-Information
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Geo-social media data are widely used as a data source to model populations and processes in a variety of contexts. However, if the data do not adequately represent the population they are drawn from, analysis results will be biased. Unaddressed, these biases may lead to false interpretations and conclusions. In this paper, we propose a generic methodology for investigating the representativeness of geo-social media data for population groups of similar statistical predictive power based on reference data. The groups are designed to be spatially coherent regions with similar prediction errors. Based on these units, we investigate the influence of different socio-demographic covariates on the representativeness. We perform experiments based on over 1.6 billion tweets and 90 socio-demographic covariates. We demonstrate that Twitter data representativeness varies strongly over time and space. Our results show that densely populated areas tend to be underrepresented consistently in non-spatial models. Over time, some covariates like the number of people aged 20 years exhibit highly different effects on the prediction models, whereas others are much more stable. The spatial effects can most frequently be explained using spatial error models, indicating spatially related errors that indicate the necessity of additional covariates. Finally, we provide hints for interpreting the results of our approach for researchers using the concepts presented in this paper.

ACS Style

Andreas Petutschnig; Bernd Resch; Stefan Lang; Clemens Havas. Evaluating the Representativeness of Socio-Demographic Variables over Time for Geo-Social Media Data. ISPRS International Journal of Geo-Information 2021, 10, 323 .

AMA Style

Andreas Petutschnig, Bernd Resch, Stefan Lang, Clemens Havas. Evaluating the Representativeness of Socio-Demographic Variables over Time for Geo-Social Media Data. ISPRS International Journal of Geo-Information. 2021; 10 (5):323.

Chicago/Turabian Style

Andreas Petutschnig; Bernd Resch; Stefan Lang; Clemens Havas. 2021. "Evaluating the Representativeness of Socio-Demographic Variables over Time for Geo-Social Media Data." ISPRS International Journal of Geo-Information 10, no. 5: 323.

Preprint content
Published: 21 April 2021
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ACS Style

Stefano Terzi; Janez Sušnik; Stefan Schneiderbauer; Silvia Torresan; Andrea Critto. Supplementary material to "Stochastic System Dynamics Modelling for climate change water scarcity assessment on a reservoir in the Italian Alps". 2021, 1 .

AMA Style

Stefano Terzi, Janez Sušnik, Stefan Schneiderbauer, Silvia Torresan, Andrea Critto. Supplementary material to "Stochastic System Dynamics Modelling for climate change water scarcity assessment on a reservoir in the Italian Alps". . 2021; ():1.

Chicago/Turabian Style

Stefano Terzi; Janez Sušnik; Stefan Schneiderbauer; Silvia Torresan; Andrea Critto. 2021. "Supplementary material to "Stochastic System Dynamics Modelling for climate change water scarcity assessment on a reservoir in the Italian Alps"." , no. : 1.

Preprint content
Published: 21 April 2021
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Water management in mountain regions is facing multiple pressures due to climate change and anthropogenic activities. This is particularly relevant for mountain areas where water abundance in the past allowed for many anthropogenic activities, exposing them to future water scarcity. To better understand the processes involved in water scarcity impact, an innovative stochastic System Dynamics Modelling (SDM) explores water stored and turbined in the S.Giustina reservoir (Province of Trento, Italy). The integration of outputs from climate change simulations as well as from a hydrological model and statistical models into the SDM is a quick and effective tool to simulate past and future water availability and demand conditions. Short-term RCP4.5 simulations depict conditions of highest volume and outflow reductions starting in spring (−16.1 % and −44.7 % in May compared to the baseline). Long-term RCP8.5 simulations suggest conditions of volume and outflow reductions starting in summer and lasting until the end of the year. The number of events with stored water below the 30th and above the 80th quantiles suggest a general reduction both in terms of low and high volumes. These results call for the need to adapt to acute short-term water availability reductions in spring and summer while preparing for hydroelectric production reductions due to the chronic long-term trends affecting autumn and mid-winter. This study provides results and methodological insights for potential SDM upscaling across strategic mountain socio-economic sectors (e.g., hydropower, agriculture and tourism) to expand water scarcity assessments and prepare for future multi-risk conditions and impacts.

ACS Style

Stefano Terzi; Janez Sušnik; Stefan Schneiderbauer; Silvia Torresan; Andrea Critto. Stochastic System Dynamics Modelling for climate change water scarcity assessment on a reservoir in the Italian Alps. 2021, 2021, 1 -25.

AMA Style

Stefano Terzi, Janez Sušnik, Stefan Schneiderbauer, Silvia Torresan, Andrea Critto. Stochastic System Dynamics Modelling for climate change water scarcity assessment on a reservoir in the Italian Alps. . 2021; 2021 ():1-25.

Chicago/Turabian Style

Stefano Terzi; Janez Sušnik; Stefan Schneiderbauer; Silvia Torresan; Andrea Critto. 2021. "Stochastic System Dynamics Modelling for climate change water scarcity assessment on a reservoir in the Italian Alps." 2021, no. : 1-25.

Review article
Published: 07 April 2021 in Science of The Total Environment
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Mountains are highly sensitive to climate change. Their elevated areas provide essential ecosystem services both for the surrounding mountainous regions and particularly for adjacent lowlands. Impacts of a warmer climate affect these services and have negative consequences on the supply of water, on biodiversity and on protection from natural hazards. Mountain social-ecological systems are affected by these changes, which also influence communities' risk perception and responses to changing climate conditions. Therefore, to understand individual and societal responses to climate change in mountain areas, aspects and drivers of risk perception need to be scrutinised. This article presents the findings of a literature review of recent English language publications on risk perception in connection to climate change and related natural hazards in mountain regions worldwide. Studies were selected from recorded entries in JSTOR, Science Direct, Scopus and Web of Science covering the period 2000–2019 and analysed in two steps (structured exploratory analysis, n = 249 and in-depth analysis, n = 72) with respect to the studies' research question, methodology, geographical scope and risk perception drivers. The review reveals that socio-demographic factors, like gender, age and personal experiences, have a crucial impact on individual risk perception. Some of the less tangible but nevertheless decisive factors are important in mountain regions such as place attachment and socio-cultural practices. In conclusion, there is however little information in the literature which addresses the specific situation of risk perception in mountain areas and its influence on communities' responses to environmental changes. Further, we observed a strong gap concerning the integration of indigenous knowledge in risk perception research. Many studies overlook or oversimplify local knowledge and the cultural dimensions of risk perception. Based on these results, the paper identifies several gaps in research and knowledge which may influence the design of climate risk management strategies as well as on their successful implementation.

ACS Style

Stefan Schneiderbauer; Paola Fontanella Pisa; Jess L. Delves; Lydia Pedoth; Samuel Rufat; Marlene Erschbamer; Thomas Thaler; Fabio Carnelli; Sergio Granados-Chahin. Risk perception of climate change and natural hazards in global mountain regions: A critical review. Science of The Total Environment 2021, 784, 146957 .

AMA Style

Stefan Schneiderbauer, Paola Fontanella Pisa, Jess L. Delves, Lydia Pedoth, Samuel Rufat, Marlene Erschbamer, Thomas Thaler, Fabio Carnelli, Sergio Granados-Chahin. Risk perception of climate change and natural hazards in global mountain regions: A critical review. Science of The Total Environment. 2021; 784 ():146957.

Chicago/Turabian Style

Stefan Schneiderbauer; Paola Fontanella Pisa; Jess L. Delves; Lydia Pedoth; Samuel Rufat; Marlene Erschbamer; Thomas Thaler; Fabio Carnelli; Sergio Granados-Chahin. 2021. "Risk perception of climate change and natural hazards in global mountain regions: A critical review." Science of The Total Environment 784, no. : 146957.

Research article
Published: 19 February 2021 in Earth Surface Processes and Landforms
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The fronts of two rock glaciers located in South Tyrol (Italian Alps) failed on August 13, 2014, and initiated debris flows in their downslope channels. A multi‐method approach including climate, meteorological and ground temperature data analysis, aerial image correlation as well as geotechnical testing and modelling led to the reconstruction of the two events. An integrated investigation of static predisposing factors, slowly‐changing preparatory factors and potential triggering events shed light on the most likely reasons for such failures. Our results suggest that the occurrence of front destabilization at the two rock glaciers can only partly be explained by the occurrence of heavy rainfall events. Indeed, antecedent hydrological and thermal ground conditions were characterized by a saturated active layer favored by a snow‐rich winter and extensive precipitation in late spring and summer. Also, the rising trend of air temperature during spring and summer months since 1950s might explain the concurrent marked displacement of the two rock glaciers. Indeed, geotechnical investigations have provided strong indications that one of the investigated rock glacier fronts was at a marginally stable state prior to 2014. As rainfall events more intense than the one that occurred in August 2014 were previously recorded in the same area without resulting failures at the studied rock glaciers, we propose that both predisposing and preparatory destabilizing factors have played a key role in the 2014 rock glacier front failures.

ACS Style

Christian Kofler; Volkmar Mair; Stephan Gruber; Maria Cristina Todisco; Ian Nettleton; Stefan Steger; Marc Zebisch; Stefan Schneiderbauer; Francesco Comiti. When do rock glacier fronts fail? Insights from two case studies in South Tyrol (Italian Alps). Earth Surface Processes and Landforms 2021, 46, 1311 -1327.

AMA Style

Christian Kofler, Volkmar Mair, Stephan Gruber, Maria Cristina Todisco, Ian Nettleton, Stefan Steger, Marc Zebisch, Stefan Schneiderbauer, Francesco Comiti. When do rock glacier fronts fail? Insights from two case studies in South Tyrol (Italian Alps). Earth Surface Processes and Landforms. 2021; 46 (7):1311-1327.

Chicago/Turabian Style

Christian Kofler; Volkmar Mair; Stephan Gruber; Maria Cristina Todisco; Ian Nettleton; Stefan Steger; Marc Zebisch; Stefan Schneiderbauer; Francesco Comiti. 2021. "When do rock glacier fronts fail? Insights from two case studies in South Tyrol (Italian Alps)." Earth Surface Processes and Landforms 46, no. 7: 1311-1327.

Introduction
Published: 05 February 2021 in European Journal of Remote Sensing
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The transforming world evokes changes in social, environmental, and economic dimensions, pushed by the digitalisation of many, if not all, aspects of our lives. Satellite Earth observation, while being “digital” from early on, has experienced a boost by digitalisation in recent years, with new trend s of cloud processing, data cube infrastructure, computer vision, machine learning, at unprecedented speeds. This Special Issue on “Digital | Earth | Observation” is dedicated to the fruitful interplay between the Digital Earth concept and Earth observation, embedded in the great technological trends in this field, and demonstrates how this potential can be used in various application contexts.

ACS Style

Stefan Lang; Dirk Tiede; Barbara Riedler. Digital | Earth | observation. European Journal of Remote Sensing 2021, 54, 1 -5.

AMA Style

Stefan Lang, Dirk Tiede, Barbara Riedler. Digital | Earth | observation. European Journal of Remote Sensing. 2021; 54 (sup1):1-5.

Chicago/Turabian Style

Stefan Lang; Dirk Tiede; Barbara Riedler. 2021. "Digital | Earth | observation." European Journal of Remote Sensing 54, no. sup1: 1-5.

Digital earth observation
Published: 24 August 2020 in European Journal of Remote Sensing
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Radiative transfer models (RTM) provide universally applicable, highly accurate prospects for plant parameter retrieval. Due to the ill-posed nature of radiative transfer theory, however, the retrieval of plant parameters requires sophisticated strategies for model inversion. We argue that object-based image analysis (OBIA) works as an effective regularization measure to cope with this ill-posedness. Despite similar findings reported in the literature, OBIA and RTM are rarely used in a combined manner. Additionally, there is a clear lack of software solutions ready for operational usage. Therefore, we propose OBIA4RTM as an approach to combine OBIA and RTM using Python and PostgreSQL/PostGIS spatial databases in a fully Open Geospatial Consortium (OGC) compliant way. First results obtained in agricultural regions in southern Germany and Austria using Sentinel-2 data during the 2017 and 2018 growing season show root mean squared errors (RMSE) in the leaf area index (LAI) of 1.47 m²/m² in the case of silage maize and 1.31 m²/m² in the case of winter cereals. Issues of integrating space and time as well as defining appropriate validation strategies, however, require further research.

ACS Style

Lukas Graf; Levente Papp; Stefan Lang. OBIA4RTM – towards an operational open-source solution for coupling object-based image analysis with radiative transfer modelling. European Journal of Remote Sensing 2020, 54, 59 -70.

AMA Style

Lukas Graf, Levente Papp, Stefan Lang. OBIA4RTM – towards an operational open-source solution for coupling object-based image analysis with radiative transfer modelling. European Journal of Remote Sensing. 2020; 54 (sup1):59-70.

Chicago/Turabian Style

Lukas Graf; Levente Papp; Stefan Lang. 2020. "OBIA4RTM – towards an operational open-source solution for coupling object-based image analysis with radiative transfer modelling." European Journal of Remote Sensing 54, no. sup1: 59-70.

Journal article
Published: 07 August 2020 in Sustainability
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Climate change vulnerability assessments are an essential instrument to identify regions most vulnerable to adverse impacts of climate change and to determine appropriate adaptation measures. Vulnerability assessments directly support countries in developing adaptation plans and in identifying possible measures to reduce adverse consequences of changing climate conditions. Against this background, this paper describes a vulnerability assessment using an integrated and participatory approach that builds on standardized working steps of previously developed ‘Vulnerability Sourcebook’ guidelines. The backbone of this approach is impact chains as a conceptual model of cause–effect relationships as well as a structured selection of indicators according to the three main components of vulnerability, namely exposure, sensitivity and adaptive capacity. We illustrate our approach by reporting the results of a vulnerability assessment conducted in Burundi focusing on climate change impacts on water and soil resources. Our work covers two analysis scales: a national assessment with the aim to identify climate change ‘hotspot regions’ through vulnerability mapping; and a local assessment aiming at identifying local-specific drivers of vulnerability and appropriate adaptation measures. Referring to this vulnerability assessment in Burundi, we discuss the potentials and constraints of the approach. We stress the need to involve stakeholders in every step of the assessment and to communicate limitations and uncertainties of the applied methods, indicators and maps in order to increase the comprehension of the approach and the acceptance of the results by different stakeholders. The study proved the practical usability of the approach at the national level by the selection of three particularly vulnerable areas. The results at a local scale supported the identification of adaption measures through intensive engagement of local rural populations.

ACS Style

Stefan Schneiderbauer; Daniel Baunach; Lydia Pedoth; Kathrin Renner; Kerstin Fritzsche; Christina Bollin; Marco Pregnolato; Marc Zebisch; Stefan Liersch; María Rivas López; Salvator Ruzima. Spatial-Explicit Climate Change Vulnerability Assessments Based on Impact Chains. Findings from a Case Study in Burundi. Sustainability 2020, 12, 6354 .

AMA Style

Stefan Schneiderbauer, Daniel Baunach, Lydia Pedoth, Kathrin Renner, Kerstin Fritzsche, Christina Bollin, Marco Pregnolato, Marc Zebisch, Stefan Liersch, María Rivas López, Salvator Ruzima. Spatial-Explicit Climate Change Vulnerability Assessments Based on Impact Chains. Findings from a Case Study in Burundi. Sustainability. 2020; 12 (16):6354.

Chicago/Turabian Style

Stefan Schneiderbauer; Daniel Baunach; Lydia Pedoth; Kathrin Renner; Kerstin Fritzsche; Christina Bollin; Marco Pregnolato; Marc Zebisch; Stefan Liersch; María Rivas López; Salvator Ruzima. 2020. "Spatial-Explicit Climate Change Vulnerability Assessments Based on Impact Chains. Findings from a Case Study in Burundi." Sustainability 12, no. 16: 6354.

Digital earth observation
Published: 06 May 2020 in European Journal of Remote Sensing
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The availability and usage of optical very high spatial resolution (VHR) satellite images for efficient support of refugee/IDP (internally displaced people) camp planning and humanitarian aid are growing. In this research, an integrated approach was used for dwelling classification from VHR satellite images, which applied the preliminary results of a convolutional neural network (CNN) model as input data for an object-based image analysis (OBIA) knowledge-based semantic classification method. Unlike standard pixel-based classification methods that usually are applied for the CNN model, our integrated approach aggregates CNN results on separately delineated objects as the basic units of a rule-based classification, to include additional prior-knowledge and spatial concepts in the final instance segmentation. An object-based accuracy assessment methodology was used to assess the accuracy of the classified dwelling categories on a single object-level. Our findings reveal accuracies of more than 90% for each applied parameter of precision, recall and F1-score. We conclude that integrating the CNN models with the OBIA capabilities can be considered an efficient approach for dwelling extraction and classification, integrating not only sample derived knowledge but also prior-knowledge about refugee/IDP camp situations, like dwellings size constraints and additional context.

ACS Style

Omid Ghorbanzadeh; Dirk Tiede; Lorenz Wendt; Martin Sudmanns; Stefan Lang. Transferable instance segmentation of dwellings in a refugee camp - integrating CNN and OBIA. European Journal of Remote Sensing 2020, 54, 127 -140.

AMA Style

Omid Ghorbanzadeh, Dirk Tiede, Lorenz Wendt, Martin Sudmanns, Stefan Lang. Transferable instance segmentation of dwellings in a refugee camp - integrating CNN and OBIA. European Journal of Remote Sensing. 2020; 54 (sup1):127-140.

Chicago/Turabian Style

Omid Ghorbanzadeh; Dirk Tiede; Lorenz Wendt; Martin Sudmanns; Stefan Lang. 2020. "Transferable instance segmentation of dwellings in a refugee camp - integrating CNN and OBIA." European Journal of Remote Sensing 54, no. sup1: 127-140.

Preprint content
Published: 23 March 2020
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Landslides represent a major threat to humans and result in high costs for the society. Landslide inventory maps depict the areas of past slope instabilities and are a valuable information source for authorities, spatial planners and risk managers. However, existing inventories are rarely complete, especially in sparsely populated and/or areas difficult to access. Previous work based on change detection and using approaches that automatically map distinct landslide events exploiting remote sensing data has shown promising results. The aim of this study was to test the applicability of multi-temporal change indices derived from Sentinel-2 (S2) for landslide detection for two landslide-prone study sites in Italy and China: South Tyrol and Longnan, respectively.

The methodical approach was built upon a change vector analysis applied to annual cloud-free S2-composites at 10m spatial resolution to extract land-cover disturbances. Landslide areas in the time period 2015-2019 were analyzed on the basis of already known landslide location points, downslope-oriented moving windows and supervised classifications using the Receiver Operating Characteristic (ROC) curve.  Subsequently, time-series analysis was applied to the detected landslide-affected areas and to derive temporal breakpoints (i.e. the timing of the landslide occurrence). Finally, applying a multi-temporal revegetation analysis, we accounted for false positives originating from agricultural activities or artefacts on single images. Our findings highlight that out of the 67 already known landslide locations in South Tyrol, only 9 (13.4%) were detectable by means of S2 data. Major challenges resulted from similar spectral characteristics of landslides and other land cover disturbances (especially tree logging). However, larger landslides were detectable both spatially and temporally by means of the multi-temporal change detection approach. By applying a quantitative accuracy assessment for the independent test site in Longnan, China, we are currently assessing the transferability and suitability of the developed approach for efficient spatial-temporal landslide mapping over large areas.

ACS Style

Peter Mayrhofer; Stefan Steger; Ruth Sonnenschein; Giovanni Cuozzo; Clement Atzberger; Stefan Schneiderbauer; Marc Zebisch; Claudia Notarnicola. Forest change as a proxy for landslide occurrence - a Sentinel 2 based spatio-temporal landslide detection approach for two test sites. 2020, 1 .

AMA Style

Peter Mayrhofer, Stefan Steger, Ruth Sonnenschein, Giovanni Cuozzo, Clement Atzberger, Stefan Schneiderbauer, Marc Zebisch, Claudia Notarnicola. Forest change as a proxy for landslide occurrence - a Sentinel 2 based spatio-temporal landslide detection approach for two test sites. . 2020; ():1.

Chicago/Turabian Style

Peter Mayrhofer; Stefan Steger; Ruth Sonnenschein; Giovanni Cuozzo; Clement Atzberger; Stefan Schneiderbauer; Marc Zebisch; Claudia Notarnicola. 2020. "Forest change as a proxy for landslide occurrence - a Sentinel 2 based spatio-temporal landslide detection approach for two test sites." , no. : 1.

Review
Published: 23 March 2020
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Mountain regions are affected by various natural hazards, of which gravitational mass movements are some of the most important ones. Due to the accumulation of settlements and intense economic activities in exposed areas, mountain regions such as the Alps constitute a risk hot-spot. The threat posed by gravitational natural hazards to human activities affirms the strong need for risk management, particularly for prevention. Structural measures are increasingly applied in combination with land use planning and ecosystem-based solutions. In particular, ecosystem-based solutions not only prevent the initiation of the processes but also act as a protective barrier. These green measures have been gaining an increasing attention also due to their adaptability to respond to the challenges posed by global change. Systematic reviews on how ecosystems can be used for disaster risk reduction have been carried out; however, their focus is on urban and coastal environments or on specific natural hazards such as shallow landslides. Up to now, there is no systematic review which addresses the role of ecosystems in disaster risk reduction regarding multiple gravitational natural hazards in mountain areas.

This contribution provides such a systematic review aimed at filling this knowledge gap to give a direction for future research. The review is composed of two main parts: a quantitative bibliometric analysis followed by a qualitative review. The quantitative part, based on the Scopus peer-reviewed database, aimed to investigate the publication trend on the ecosystem-based solutions for gravitational natural hazard mitigation by comparing it with the general trend of published scientific documents. The bibliometric analysis also served as a basis to select most relevant articles on which to conduct the subsequent qualitative analysis. The content of the so selected publications was analysed qualitatively the following  predefined criteria: the natural hazards addressed, the features of the ecosystem (i.e. forest species composition, management activities, effectiveness in risk mitigation), the development of alternative scenarios to test different hypothesis, the degree of stakeholder involvement, and the monetary evaluation of the measures (i.e. comparing them to structural measures). Results show a sharp increase in the number of publications on the topic from 1980 to 2018 compared to the overall number of documents published on Scopus. Although the overall topic is gaining more attention in scientific literature, the in-depth qualitative analysis revealed that research still pays little attention to stakeholder involvement and an economic evaluation of measures. We conclude that filling this research gap might help to foster a wider adoption of ecosystem-based solutions for disaster risk reduction across mountain areas.

ACS Style

Silvia Cocuccioni; Francesca Poratelli; Cristian Accastello; Stefan Steger; Stefan Schneiderbauer; Filippo Brun. Ecosystem-based solutions for gravitational natural hazard mitigation: a review on the use of protection forests for disaster risk reduction in mountain areas. 2020, 1 .

AMA Style

Silvia Cocuccioni, Francesca Poratelli, Cristian Accastello, Stefan Steger, Stefan Schneiderbauer, Filippo Brun. Ecosystem-based solutions for gravitational natural hazard mitigation: a review on the use of protection forests for disaster risk reduction in mountain areas. . 2020; ():1.

Chicago/Turabian Style

Silvia Cocuccioni; Francesca Poratelli; Cristian Accastello; Stefan Steger; Stefan Schneiderbauer; Filippo Brun. 2020. "Ecosystem-based solutions for gravitational natural hazard mitigation: a review on the use of protection forests for disaster risk reduction in mountain areas." , no. : 1.

Preprint content
Published: 23 March 2020
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Most statistically-based landslide susceptibility maps are supposed to portray the relative likelihood of an area to be affected by future landslides. Literature indicates that vital modelling decisions, such as the selection of explanatory variables, are frequently based on quantitative criteria (e.g. predictive performance). The results obtained by apparently well-performing statistical models are also used to infer the causes of slope instability and to identify landslide “safe” terrain. It seems that comparably few studies pay particular attention to background information associated with the available landslide data. This research hypothesizes that inappropriate modelling decisions and wrong conclusions are likely to follow whenever the origin of the underlying landslide data is ignored. The aims were to (i) analyze the South Tyrolean landslide inventory in the context of its origin in order to (ii) highlight potential pitfalls of performance driven procedures and to (iii) develop a predictive model that takes landslide background information into account. The available landslide data (1928 slide-type movements) of the province of South Tyrol (~7400 km²) consists of positionally accurate points that depict the scarp location of events that induced interventions by e.g. the road service or the geological office. An initial exploratory statistical analysis revealed general relationships between landslide presence/absence data and frequently used explanatory variables. Subsequent modelling was based on a Generalized Additive Mixed Effects Model that allowed accounting for (non-linear) fixed effects and additional “nuisance” variables (random intercepts). The evaluation of the models (diverse variable combinations) focused on modelled relationships, variable importance, spatial and non-spatial predictive performance and the final prediction surfaces. The results highlighted that the best performing models did not reflect the “actual” landslide susceptibility situation. A critical interpretation led to the conclusion that the models simultaneously reflected both, effects likely related to slope instability (e.g. low likelihood of flat and very steep terrain) and effects rather associated with the provincial landslide intervention strategy (e.g. few interventions at high altitudes, increasing number of interventions with decreasing distance to infrastructure). Attempts to separate the nuisance related to “intervention effects” from the actual landslide effects using mixed effects modelling proved to be challenging, also due to omnipresent spatial interrelations among the explanatory variables and the fact that some variables concurrently represent effects related to landslide predisposition and effects associated with the intervention strategy (e.g. altitude). We developed a well-performing predictive landslide intervention index that is in line with the actual data origin and allows identifying areas where future interventions are more or less likely to take place. The efficiency of past interventions (e.g. stabilization of slopes) was demonstrated during recent storm events, because previously stabilized slopes were not affected by new landslides. This also showed that the correct interpretation of the final map requires a simultaneous visualization of both, the spatially predicted index (from low to high) and the available landslide inventory (low likelihood due to past interventions). The results confirm that wrong conclusions can be drawn from excellently performing statistical models whenever qualitative background information is disregarded.

ACS Style

Stefan Steger; Volkmar Mair; Christian Kofler; Stefan Schneiderbauer; Marc Zebisch. The necessity to consider the landslide data origin in statistically-based spatial predictive modelling – A landslide intervention index for South Tyrol (Italy). 2020, 1 .

AMA Style

Stefan Steger, Volkmar Mair, Christian Kofler, Stefan Schneiderbauer, Marc Zebisch. The necessity to consider the landslide data origin in statistically-based spatial predictive modelling – A landslide intervention index for South Tyrol (Italy). . 2020; ():1.

Chicago/Turabian Style

Stefan Steger; Volkmar Mair; Christian Kofler; Stefan Schneiderbauer; Marc Zebisch. 2020. "The necessity to consider the landslide data origin in statistically-based spatial predictive modelling – A landslide intervention index for South Tyrol (Italy)." , no. : 1.

Earth observation supporting sustainability
Published: 30 October 2019 in European Journal of Remote Sensing
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Humanitarian action has rapidly adopted Earth observation (EO) and geospatial technologies shaping them according to their needs. Protracted crises and large-scale population displacements require up-to-date information in many facets of humanitarian action support, from mission planning, resource deployment and monitoring, to nutrition and vaccination campaigns, camp plotting, damage assessment, etc. Even though nearly all assets of remote sensing apply in such demanding scenarios, it remains a challenge to fully implement and sustain a trustful and reliable information service. This paper discusses achievements and open issues in the use and uptake of EO technology, from a technical and organisational point of view, motivated by an information service for Médecins Sans Frontières (MSF) and its extension to other NGO’s information needs in the humanitarian sector. With a focus on EO-based population estimation based on (semi-)automated dwelling counting from very high-resolution optical satellite imagery as well as the exploitation of data integration (including radar sensors), the paper also covers potential service elements with respect to environmental and ground- or surface water monitoring. It investigates workflow elements in relation to information extraction and delivery by illustrating a broad range of application scenarios, and discusses first operational solutions of a customized service portfolio.

ACS Style

Stefan Lang; Petra Füreder; Barbara Riedler; Lorenz Wendt; Andreas Braun; Dirk Tiede; Elisabeth Schoepfer; Peter Zeil; Kristin Spröhnle; Kerstin Kulessa; Edith Rogenhofer; Magdalena Bäuerl; Alexander Öze; Gina Schwendemann; Volker Hochschild. Earth observation tools and services to increase the effectiveness of humanitarian assistance. European Journal of Remote Sensing 2019, 53, 67 -85.

AMA Style

Stefan Lang, Petra Füreder, Barbara Riedler, Lorenz Wendt, Andreas Braun, Dirk Tiede, Elisabeth Schoepfer, Peter Zeil, Kristin Spröhnle, Kerstin Kulessa, Edith Rogenhofer, Magdalena Bäuerl, Alexander Öze, Gina Schwendemann, Volker Hochschild. Earth observation tools and services to increase the effectiveness of humanitarian assistance. European Journal of Remote Sensing. 2019; 53 (sup2):67-85.

Chicago/Turabian Style

Stefan Lang; Petra Füreder; Barbara Riedler; Lorenz Wendt; Andreas Braun; Dirk Tiede; Elisabeth Schoepfer; Peter Zeil; Kristin Spröhnle; Kerstin Kulessa; Edith Rogenhofer; Magdalena Bäuerl; Alexander Öze; Gina Schwendemann; Volker Hochschild. 2019. "Earth observation tools and services to increase the effectiveness of humanitarian assistance." European Journal of Remote Sensing 53, no. sup2: 67-85.

Journal article
Published: 28 October 2019 in Geomorphology
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Ice presence in rock glaciers is a topic that is likely to gain importance in the future due to the expected decrease in water supply from glaciers and the increase of mass movements originating in periglacial areas. This makes it important to have at ones disposal inventories with complete information on the state of rock glaciers. This study presents a method to overcome incomplete information on the status of rock glaciers (i.e. intact vs. relict) recorded in regional scale inventories. The proposed data-driven modelling framework can be used to estimate the likelihood that rock glaciers contain frozen material. Potential predictor variables related to topography, environmental controls or the rock glacier appearance were derived from a digital terrain model (DTM), satellite data and gathered from existing data sets. An initial exploratory data analysis supported the heuristic selection of predictor variables. Three classification algorithms, namely logistic regression (GLM), support vector machine (SVM) and random forest (RF), were trained on the basis of the available information on the status of rock glaciers within the territory of South Tyrol (Eastern Italian Alps). The resulting classification rules led to assign a binary label – intact or relict – to 235 unclassified rock glaciers present in the inventory. All models were validated quantitatively on spatially-independent test samples (spatial cross validation) and achieved highly satisfactory performance scores. Hereby, the less flexible statistically-based classifier (GLM) performed slightly better than the more flexible machine learning algorithms (SVM and RF). Spatial permutation-based variable importance assessment revealed that elevation and vegetation cover (based on NDVI) were the most relevant predictors. For more than 80% of the unclassified rock glaciers, all of the three models agreed on the spatially predicted rock glacier status. Only for a minor portion (12.3%), one model differed from the remaining two.

ACS Style

Christian Kofler; Stefan Steger; Volkmar Mair; Marc Zebisch; Francesco Comiti; Stefan Schneiderbauer. An inventory-driven rock glacier status model (intact vs. relict) for South Tyrol, Eastern Italian Alps. Geomorphology 2019, 350, 106887 .

AMA Style

Christian Kofler, Stefan Steger, Volkmar Mair, Marc Zebisch, Francesco Comiti, Stefan Schneiderbauer. An inventory-driven rock glacier status model (intact vs. relict) for South Tyrol, Eastern Italian Alps. Geomorphology. 2019; 350 ():106887.

Chicago/Turabian Style

Christian Kofler; Stefan Steger; Volkmar Mair; Marc Zebisch; Francesco Comiti; Stefan Schneiderbauer. 2019. "An inventory-driven rock glacier status model (intact vs. relict) for South Tyrol, Eastern Italian Alps." Geomorphology 350, no. : 106887.

Review
Published: 24 October 2019 in ISPRS International Journal of Geo-Information
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The primary goal of collecting Earth observation (EO) imagery is to map, analyze, and contribute to an understanding of the status and dynamics of geographic phenomena. In geographic information science (GIScience), the term object-based image analysis (OBIA) was tentatively introduced in 2006. When it was re-formulated in 2008 as geographic object-based image analysis (GEOBIA), the primary focus was on integrating multiscale EO data with GIScience and computer vision (CV) solutions to cope with the increasing spatial and temporal resolution of EO imagery. Building on recent trends in the context of big EO data analytics as well as major achievements in CV, the objective of this article is to review the role of spatial concepts in the understanding of image objects as the primary analytical units in semantic EO image analysis, and to identify opportunities where GEOBIA may support multi-source remote sensing analysis in the era of big EO data analytics. We (re-)emphasize the spatial paradigm as a key requisite for an image understanding system capable to deal with and exploit the massive data streams we are currently facing; a system which encompasses a combined physical and statistical model-based inference engine, a well-structured CV system design based on a convergence of spatial and colour evidence, semantic content-based image retrieval capacities, and the full integration of spatio-temporal aspects of the studied geographical phenomena.

ACS Style

Stefan Lang; Geoffrey J. Hay; Andrea Baraldi; Dirk Tiede; Thomas Blaschke. Geobia Achievements and Spatial Opportunities in the Era of Big Earth Observation Data. ISPRS International Journal of Geo-Information 2019, 8, 474 .

AMA Style

Stefan Lang, Geoffrey J. Hay, Andrea Baraldi, Dirk Tiede, Thomas Blaschke. Geobia Achievements and Spatial Opportunities in the Era of Big Earth Observation Data. ISPRS International Journal of Geo-Information. 2019; 8 (11):474.

Chicago/Turabian Style

Stefan Lang; Geoffrey J. Hay; Andrea Baraldi; Dirk Tiede; Thomas Blaschke. 2019. "Geobia Achievements and Spatial Opportunities in the Era of Big Earth Observation Data." ISPRS International Journal of Geo-Information 8, no. 11: 474.

Journal article
Published: 17 July 2019 in Data
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There is an increasing amount of free and open Earth observation (EO) data, yet more information is not necessarily being generated from them at the same rate despite high information potential. The main challenge in the big EO analysis domain is producing information from EO data, because numerical, sensory data have no semantic meaning; they lack semantics. We are introducing the concept of a semantic EO data cube as an advancement of state-of-the-art EO data cubes. We define a semantic EO data cube as a spatio-temporal data cube containing EO data, where for each observation at least one nominal (i.e., categorical) interpretation is available and can be queried in the same instance. Here we clarify and share our definition of semantic EO data cubes, demonstrating how they enable different possibilities for data retrieval, semantic queries based on EO data content and semantically enabled analysis. Semantic EO data cubes are the foundation for EO data expert systems, where new information can be inferred automatically in a machine-based way using semantic queries that humans understand. We argue that semantic EO data cubes are better positioned to handle current and upcoming big EO data challenges than non-semantic EO data cubes, while facilitating an ever-diversifying user-base to produce their own information and harness the immense potential of big EO data.

ACS Style

Hannah Augustin; Martin Sudmanns; Dirk Tiede; Stefan Lang; Andrea Baraldi. Semantic Earth Observation Data Cubes. Data 2019, 4, 102 .

AMA Style

Hannah Augustin, Martin Sudmanns, Dirk Tiede, Stefan Lang, Andrea Baraldi. Semantic Earth Observation Data Cubes. Data. 2019; 4 (3):102.

Chicago/Turabian Style

Hannah Augustin; Martin Sudmanns; Dirk Tiede; Stefan Lang; Andrea Baraldi. 2019. "Semantic Earth Observation Data Cubes." Data 4, no. 3: 102.

Conference paper
Published: 16 April 2019 in Lecture Notes in Geoinformation and Cartography
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Technological advances require continuous efforts to keep existing curricula up-to-date and graduates employable in the Earth observation (EO) and geoinformation (GI) sectors. The increasing availability of space/geospatial data and the maturity of technology induce disruptive changes to workflows in the EO/GI sector that suggest the development of training programmes and academic courses for re-skilling of workforce and training new user groups. The target in the EO domain in this respect is to facilitate the ‘user uptake’ of the space infrastructure. User uptake requires knowledge of the workforce demand on the market as well as a skills strategy that takes potential emerging and disruptive changes in the sector into account. In the present contribution we build upon a study of demand for current workforce on the EO/GI market and occupational profiles that require priority when developing training programmes and curricula. Reflections on the findings of that study highlight the need to illustrate expected changes of workflows, i.e. the sequence of tasks executed by employees with a certain occupational profile, for an improved basis of discussion. Therefore, we present a methodology to first, acquire current occupational profiles and second, to illustrate sector developments by mapping the developments on tasks of the workflow. This methodology is demonstrated for the profile of remote sensing specialists. The illustration of changing tasks suggests scenarios for future workforce and questions and directions for the development of a sector skills strategy.

ACS Style

Barbara Hofer; Stefan Lang; Nicole Ferber. Future Occupational Profiles in Earth Observation and Geoinformation—Scenarios Resulting from Changing Workflows. Lecture Notes in Geoinformation and Cartography 2019, 349 -366.

AMA Style

Barbara Hofer, Stefan Lang, Nicole Ferber. Future Occupational Profiles in Earth Observation and Geoinformation—Scenarios Resulting from Changing Workflows. Lecture Notes in Geoinformation and Cartography. 2019; ():349-366.

Chicago/Turabian Style

Barbara Hofer; Stefan Lang; Nicole Ferber. 2019. "Future Occupational Profiles in Earth Observation and Geoinformation—Scenarios Resulting from Changing Workflows." Lecture Notes in Geoinformation and Cartography , no. : 349-366.

Review articles
Published: 14 March 2019 in International Journal of Digital Earth
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Turning Earth observation (EO) data consistently and systematically into valuable global information layers is an ongoing challenge for the EO community. Recently, the term ‘big Earth data’ emerged to describe massive EO datasets that confronts analysts and their traditional workflows with a range of challenges. We argue that the altered circumstances must be actively intercepted by an evolution of EO to revolutionise their application in various domains. The disruptive element is that analysts and end-users increasingly rely on Web-based workflows. In this contribution we study selected systems and portals, put them in the context of challenges and opportunities and highlight selected shortcomings and possible future developments that we consider relevant for the imminent uptake of big Earth data.

ACS Style

Martin Sudmanns; Dirk Tiede; Stefan Lang; Helena Bergstedt; Georg Trost; Hannah Augustin; Andrea Baraldi; Thomas Blaschke. Big Earth data: disruptive changes in Earth observation data management and analysis? International Journal of Digital Earth 2019, 13, 832 -850.

AMA Style

Martin Sudmanns, Dirk Tiede, Stefan Lang, Helena Bergstedt, Georg Trost, Hannah Augustin, Andrea Baraldi, Thomas Blaschke. Big Earth data: disruptive changes in Earth observation data management and analysis? International Journal of Digital Earth. 2019; 13 (7):832-850.

Chicago/Turabian Style

Martin Sudmanns; Dirk Tiede; Stefan Lang; Helena Bergstedt; Georg Trost; Hannah Augustin; Andrea Baraldi; Thomas Blaschke. 2019. "Big Earth data: disruptive changes in Earth observation data management and analysis?" International Journal of Digital Earth 13, no. 7: 832-850.

Journal article
Published: 05 February 2019 in International Journal of Digital Earth
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Sentinel-2 scenes are increasingly being used in operational Earth observation (EO) applications at regional, continental and global scales, in near-real time applications, and with multi-temporal approaches. On a broader scale, they are therefore one of the most important facilitators of the Digital Earth. However, the data quality and availability are not spatially and temporally homogeneous due to effects related to cloudiness, the position on the Earth or the acquisition plan. The spatio-temporal inhomogeneity of the underlying data may therefore affect any big remote sensing analysis and is important to consider. This study presents an assessment of the metadata for all accessible Sentinel-2 Level-1C scenes acquired in 2017, enabling the spatio-temporal coverage and availability to be quantified, including scene availability and cloudiness. Spatial exploratory analysis of the global, multi-temporal metadata also reveals that higher acquisition frequencies do not necessarily yield more cloud-free scenes and exposes metadata quality issues, e.g. systematically incorrect cloud cover estimation in high, non-vegetated altitudes. The continuously updated datasets and analysis results are accessible as a Web application called EO-Compass. It contributes to a better understanding and selection of Sentinel-2 scenes, and improves the planning and interpretation of remote sensing analyses.

ACS Style

Martin Sudmanns; Dirk Tiede; Hannah Augustin; Stefan Lang. Assessing global Sentinel-2 coverage dynamics and data availability for operational Earth observation (EO) applications using the EO-Compass. International Journal of Digital Earth 2019, 13, 768 -784.

AMA Style

Martin Sudmanns, Dirk Tiede, Hannah Augustin, Stefan Lang. Assessing global Sentinel-2 coverage dynamics and data availability for operational Earth observation (EO) applications using the EO-Compass. International Journal of Digital Earth. 2019; 13 (7):768-784.

Chicago/Turabian Style

Martin Sudmanns; Dirk Tiede; Hannah Augustin; Stefan Lang. 2019. "Assessing global Sentinel-2 coverage dynamics and data availability for operational Earth observation (EO) applications using the EO-Compass." International Journal of Digital Earth 13, no. 7: 768-784.