Evaluating the spatial transferability and temporal repeatability of remote-sensing-based lake water quality retrieval algorithms at the European scale: a meta-analysis approach

Many studies have shown the considerable potential for the application of remote-sensing-based methods for deriving estimates of lake water quality. However, the reliable application of these methods across time and space is complicated by the diversity of lake types, sensor configuration, and the multitude of different algorithms proposed. This study tested one operational and 46 empirical algorithms sourced from the peer-reviewed literature that have individually shown potential for estimating lake water quality properties in the form of chlorophyll-a (algal biomass) and Secchi disc depth (SDD) (water transparency) in independent studies. Nearly half (19) of the algorithms were unsuitable for use with the remote-sensing data available for this study. The remaining 28 were assessed using the Terra/Aqua satellite archive to identify the best performing algorithms in terms of accuracy and transferability within the period 2001–2004 in four test lakes, namely Vänern, Vättern, Geneva, and Balaton. These lakes represent the broad continuum of large European lake types, varying in terms of eco-region (latitude/longitude and altitude), morphology, mixing regime, and trophic status. All algorithms were tested for each lake separately and combined to assess the degree of their applicability in ecologically different sites. None of the algorithms assessed in this study exhibited promise when all four lakes were combined into a single data set and most algorithms performed poorly even for specific lake types. A chlorophyll-a retrieval algorithm originally developed for eutrophic lakes showed the most promising results (R2 = 0.59) in oligotrophic lakes. Two SDD retrieval algorithms, one originally developed for turbid lakes and the other for lakes with various characteristics, exhibited promising results in relatively less turbid lakes (R2 = 0.62 and 0.76, respectively). The results presented here highlight the complexity associated with remotely sensed lake water quality estimates and the high degree of uncertainty due to various limitations, including the lake water optical properties and the choice of methods.

Learning to 'understand backwards' in time: children's temporal cognition and the primary history curriculum

This study examines children’s temporal ways of knowing and it highlights the centrality of temporal cognition in the development of children’s historical understanding. It explores how young children conceptualise time and it examines the provision for temporal cognition at the levels of the intended, enacted and received history curriculum in the Irish primary school context. Positioning temporality as a prerequisite second-order concept, the study recognises the essential role of both first-order and additional second-order concepts in historical understanding. While the former can be defined as the basic, substantive content to be taught, the latter refers to a number of additional key concepts that are deemed fundamental to children's capacity to make meaningful sense of history. The study argues for due recognition to be given to temporality, in the belief that both sets of knowledge, the content and skills, are required to develop historical thinking (Lévesque, 2011). The study addresses a number of key research questions, using a mixed methods research design, comprising an analysis of history textbooks, a survey among final year student teachers about their teaching of history, and school-based interviews with primary school children: What opportunities are available for children to develop temporal ways of knowing? How do student teachers experience being apprenticed into the available culture for teaching history and understanding temporality at primary level? What insights do the cognitive-developmental and sociocultural perspectives on learning provide for understanding the dynamics of children’s temporal ways of knowing? The study argues that the skill of developing a deeper understanding of time is a key prerequisite in connecting with, and constructing, understandings and frameworks of the past. The study advances a view of temporality as complex, multi-faceted and developmental. The findings have a potential contribution to make in influencing policy and pedagogy in establishing an elaborated and well-defined curriculum framework for developing temporal cognition at both national and international levels.

Selection of a network of large lakes and reservoirs suitable for global environmental change analysis using Earth Observation

The GloboLakes project, a global observatory of lake responses to environmental change, aims to exploit current satellite missions and long remote-sensing archives to synoptically study multiple lake ecosystems, assess their current condition, reconstruct past trends to system trajectories, and assess lake sensitivity to multiple drivers of change. Here we describe the selection protocol for including lakes in the global observatory based upon remote-sensing techniques and an initial pool of the largest 3721 lakes and reservoirs in the world, as listed in the Global Lakes and Wetlands Database. An 18-year-long archive of satellite data was used to create spatial and temporal filters for the identification of waterbodies that are appropriate for remote-sensing methods. Further criteria were applied and tested to ensure the candidate sites span a wide range of ecological settings and characteristics; a total 960 lakes, lagoons, and reservoirs were selected. The methodology proposed here is applicable to new generation satellites, such as the European Space Agency Sentinel-series.