Date: 2 July 2019
Venue: Forbes room, Irvine Building
Title: Remote sensing of environmental change in mountain areas
The changes in temperature and precipitation patterns and human intervention of different types are changing the face of mountains at an unprecedented speed. Remote sensing provides us with periodic, unbiased information on a global scale with steadily improving quality.
On the Tibetan Plateau changes in glacier balance, oscillation of lake levels, floods and landslides are a consequence of such development. Relying on remote sensing, down-wasting of Tibetan glaciers could be estimated by satellite altimetry on a regional scale. An analysis of snow cover dynamics by optical medium resolution data from MODIS resulted in new knowledge about lake effect and biennial behaviour of snow cover in the drainage basin of sacred Nam Co lake one of the largest lakes in Tibet. Furthermore, a recurrent glacier lake outburst flood in Limi Valley was analyzed and better understood.
In the Ethiopian Highlands, slopes formed by rift development, volcanic activity, and fast river incision are heavily shaped by landsliding. Valuable information about their dynamics can be derived from aerial photographs from multiple aerial surveys which were initiated already in 1936 during the Italian occupation of the country. Investigation of two remarkable sites of landsliding in Ethiopia by various remote sensing techniques will be presented. The first site Debre Sina landslide is located in the vicinity of the trunk road connecting Addis Ababa with Eritrea and it is the largest recent landslide in Ethiopia. In Dessie, several large landslides are just next to its centre. Surprisingly, their timing and triggers remained unknown.
Jan Kropáček (https://home.czu.cz/jkropacek/uvod) is a geographer specialized on remote sensing with special focus on the mountain environment. He received his Ph.D. degree from the Faculty of Sciences of Charles University in Prague. After the accession of his country to the EU, he started to work at the Joint Research Centre of the European Commission in Ispra, Italy. His research was focused on mapping of biomass in tropical Africa and wetland detection in boreal forests of Eurasia. During his postdoc stays at the universities of Tubingen and Dresden in Germany, he took part in three projects studying cryosphere and hydrological cycle on the Tibetan Plateau. His further research interests are monitoring of slope instabilities in the Ethiopian Highlands and assessment of gully erosion in semi-arid regions. Since 2016 he continues his research and teaching at the Faculty of Environmental Sciences of the Czech University of Life Sciences Prague. During his free time, he travels and climbs on sandstone towers in Bohemian Paradise and elsewhere.
Date: 14 May 2019
Venue: Forbes room, Irvine Building
Title: Embracing variability: using remote sensing and spatial data to understand ecosystem function in seasonal ecosystems
Abstract: Highly seasonal environments are often characterized by a strong coupling between environmental variation and ecosystem responses, including organism adaptations, plant phenology and productivity, and biogeochemical cycling. This tight coupling can help us quantify and forecast changes in ecosystem function caused by changes in climatic and environmental factors, as long as we can understand and quantify the responses and uncertainties associated with seasonal variability. In his talk, Dr. Thiago Silva will show some examples of his previous and current work using direct and indirect remote sensing methods and spatial variables to capture, quantify and forecast the effects of environmental variation on vegetation dynamics, ecosystem function and biogeochemical cycling, from local to regional scales, focusing on Brazilian ecosystems.
Dr. Thiago Silva has recently joined University of Stiling after being an assistant professor for 5 years at São Paulo State University (UNESP, Brazil). He started his career as an ecosystem ecologist with a strong focus on remote sensing of Amazon floodplain wetlands. Since then, his research has expanded to encompass several aspects of global change biology, including plant community ecology, plant functional ecology and biogeography/macroecology. He is particularly interested in environmental regulation of community assembly and ecosystem function, and on developing quantitative approaches that explicitly incorporate the spatial and temporal dynamics of the biosphere at multiple scales. His research often combines in-situ ecological methods with modern remote sensing, GIS and data science, leading to collaborations with landscape, community and ecosystem ecologists, phylogeographers, and applied ecologists, as well as climatologists, hydrologists, geologists and computer scientists.
Date: 11 June 2019
Venue: Forbes room, Irvine Building
From static to dynamic: Aggregating the conceptualisation of movement data better captures real world and simulated animal-environment relationships.
Habitat selection analysis is a widely applied statistical framework used in spatial ecology. Many of the methods used to generate movement and couple it with the environment are strongly integrated within GIScience. The choice of movement conceptualisation and environmental space can potentially have long-lasting implications on the spatial statistics used to infer movement-environment relationships. This study explores how systematically altering the conceptualisation of movement, environmental space, and temporal resolution affects the results of habitat selection analyses using real-world case studies and a virtual ecologist approach. Model performance and coefficient estimates were explored between conceptualisations of movement, with substantial differences found for the more aggregated representations (e.g., segment and area). Key findings from the virtual ecologist approach identified that altering the temporal resolution identified inversions in the movement-environment relationship for vectors and moves, while systematically increasing resistance to linear features (e.g., roads) was not identified for individual aggregations. These results suggest that spatial statistics employed to investigate movement-environment relationships should advance beyond conceptualising movement as the (relatively) static conceptualisation of vectors and moves and replace these with (more) dynamic aggregations of longer-lasting movement processes such as segments and areal representations.
Bio: Paul Holloway is a lecturer in Geographic Information Science and Systems in the Department of Geography and a Principal Investigator in the Environmental Research Institute at University College Cork. His research and teaching interests include using GIScience and spatial analysis to address a suite of ecological, environmental, and geographic issues. His research addresses the long-standing issue of how to incorporate movement at different spatial and temporal extents into species distribution models, how the use of volunteered geographic information and machine learning can improve spatial predictions, and how movement data and geographic context are used to understand movement processes.