ALBERT

Description: In the past, environmental crises (like volcanic eruptions, or earthquakes) were seen as an opportunity by European scientists to 'drop in', make measurements, gather samples and return home to share their knowledge with other European scientists. This colonial history has left two legacies. First, while there are detailed reports of some of these past crises in European libraries, museums and archives, a lot of this information is only accessible to people who are able to visit in person. Second, the importance of local observers, and the value of their observations, has often been overlooked, or forgotten. We present details from both eruptive and non-eruptive crises on three volcanic islands of the Caribbean: St. Vincent, Montserrat and Dominica, from 1890 - 2000. This includes several major eruptions (1902, 1979; St Vincent; 1995- Montserrat), and earthquake activity associated with volcanic unrest (1934-1939, Montserrat; 1937 Dominica). We have uncovered information about the impacts of volcanic activity, and the responses of decision-makers. The uncertainty of volcanic unrest is particularly difficult to cope with, and decisions are delayed or not taken that could lead to disaster. Valuable observations and measurements made by observers are overlooked, we have been able to use these to reconstruct activity and will share their value in this presentation. Finally, networks are not just instrumental, they obstruct as well as circulate data and information. We will also share our new open-access digital repository for these documents and the lessons for crisis response today from the historical record.

Description: Glaciers are important contributors to water resources in many parts of the world, as well as constituting potential hazards. Monitoring of glaciers with remote sensing data is complicated by the presence of supraglacial debris which limits the effectiveness of semi-automated glacier delineation techniques. Furthermore, debris-covered glaciers are notoriously hard to survey in the field due to their complex, chaotic topography, and the presence of ephemeral ice cliffs and supraglacial lakes. As such, debris-covered glaciers are poorly represented in global inventories such as GLIMS and RGI, which consist of an assemblage of outlines from various dates. These inventories are subject to uncertainties due to mapping by multi-analysts using different methods. Despite recent efforts to map supraglacial debris cover at regional level, there remains an urgent need to develop a global, robust automated mapping approach based on open access data. Novel remote sensing data including high-resolution optical and radar data combined with emerging machine learning offer unique opportunities to advance current mapping methods. Here we evaluate current indices used in mapping supraglacial debris-cover and derive a best-practice workflow recommendation from particular combinations of these indices to derive glacier outlines for six representative subregions chosen globally: Khumbu and Manaslu regions (Nepal), Cordillera Blanca (Peru), Northern Patagonian Ice fields, Alaska Wrangell range, Hunza valley (Karakoram) and the Tien Shan. We present preliminary results of machine learning algorithms that combine the various remote sensing indices. The aim is to develop a robust, systematic method to map debris cover in a consistent manner at multi-temporal scales.