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The number and variety of technologies used for environmental surveillance is expanding rapidly, making constant data collection and near 'real time' analyses possible. 'Smart Earth' describes networked infrastructures comprised of devices and equipment and signals to the human dimensions inherent to developing, deploying and putting technology and large datasets to use. In this paper, we situate Smart Earth in terms of technological products and human practices and consider the relationship between Smart Earth and global environmental governance. Specifically, we review emerging literature and present a case study of an organization founded by environmental non-profit, SkyTruth, tech industry behemoth, Google and marine conservation NGO, Oceana. Called 'Global Fishing Watch' (GFW), this organization builds geospatial datasets, hosts an online mapping platform where anyone with internet access can surveil various types of ocean-going vessels and shares data and map products with scientists and practitioners. Two critical points emerge through the case. First, we show that GFW expands its surveillance capacity by pursuing 'data sharing' partnerships with sovereign states, many in the Global South. Second, the maps and datasets produced by GFW link vessels to a 'flag state' while the firms, subsidiaries and financiers that may own and/or operate these vessels remain obscure – and hence so too does the political economy of oceans fisheries. GFW maps and datasets offer new approaches to tracking fishing and are advancing fisheries science. At the same time, they rely on and are only legible through hegemonic geopolitical and political–economic orders deeply implicated in industrial (over)fishing. The norms and domains of global environmental governance are expanding, but Smart Earth 'solutions' risk leaving the structural drivers of environmental change unaddressed. [ABSTRACT FROM AUTHOR]

Algorithms – instructions for acting on data, executed by code – are increasingly being enrolled into climate policy governance via the prediction of policy outcomes, the evaluation of climate mitigation and adaptation strategies, and the design of practitioner actions. Yet the political implications of these technological changes in environmental governance are only just beginning to be theorised. In this paper, we examine one particular facet of this emerging politics: the relationship between thinking algorithmically and hegemonic power. Drawing from Laclau and Mouffe's theorisation of hegemony we argue that algorithmic forms of reasoning lend themselves towards producing hegemonising knowledge regimes, with important implications for a democratic politics of climate change. Recognising that algorithms stand for wider socio‐technical assemblages that structure and create knowledge, we call for greater attention to the reliance on algorithms within climate governance – less for the algorithms themselves than for their particular epistemic commitments that create algorithmic ways of thinking, with associated claims to power. Through a critical review of scholarship at the intersection of critical digital studies and environmental governance, we first identify three key epistemic commitments involved in thinking algorithmically: induction, abstraction, and optimisation. We then examine the correspondence between these key features of algorithmic thinking and the conditions that Laclau and Mouffe propose form the grounds for hegemony: objectivity, universality, and necessity. Better understanding what "thinking algorithmically" entails, and the forms of knowing and acting that it affords and excludes, is vital, we argue, to begin naming the political implications and transformative potential of new forms of climate governance. [ABSTRACT FROM AUTHOR]

• We conducted a Q-method survey of US stream restoration practitioners. • We designed and used the Q-TIP survey platform (https://qtip.geography.wisc.edu/). • Participants expressed four different views of stream restoration assessment. • These views vary on the feasibility of measuring outcomes. • Methodological rules of thumb limit Q, but we demonstrate unconventional approaches. We present results from a Q-method survey on a key question in water governance and reflect on Q-method as an approach that quantitatively distinguishes qualitative subject-positions. The survey was conducted with the Q-TIP platform, which we designed for the study and is now open to all researchers (https://qtip.geography.wisc.edu/). Our study asked how stream restoration should be evaluated in state regulatory programs. Streams are dynamic and multi-scalar geomorphological, chemical, biological, as well as socio-cultural systems and it is not obvious what good restoration means or how it should be assessed. Across the stream restoration community we found four different priorities, each of which differently characterizes the feasibility of assessing outcomes. These four perspectives were that metrics of success should: (a) be rigorous and site-focused; (b) be simple and easy to implement in the field; (c) capture complexity; (d) reflect innovations in watershed planning, ecosystem functions, and stakeholder inclusion. These subject-positions on assessment do not, however, map cleanly onto informant profession or background, and a single informant can hold more than one view. Despite relatively limited uptake in geography, Q offers the promise of a critical quantitative approach to researching subjectivity in a way that is compatible with poststructural understandings of identity. We use our case material to show that methodological rules of thumb limit Q's potential, but we demonstrate unconventional approaches. Drawing on the process and results of our survey of stream restoration practitioners, we argue that Q-method can help in the task of representing subjectivity while respecting its complexity. [ABSTRACT FROM AUTHOR]