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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]

• Environmental and climate crises are grist for tech solutions. • AI technologies require computational resources that are environmentally embedded. • Disasters become "shocks" that the AI industry capitalizes on. • Climate AI shapes material investment flows and landscapes. • Data-driven approaches to climate reproduce injustices faced by marginalized communities. Emerging narratives around artificial intelligence (AI) and machine learning place great faith in these technologies' ability to ameliorate threats posed by climate change. They promise the capacity to analyze vast amounts of more precise and real-time data, improving how decision-makers predict, respond, and adapt. Yet scholars in political ecology have long observed that technocentric approaches typically reduce complex human-environment relationships in ways that fail to account for social relations and power dynamics. This paper charts the emerging political economy of "climate AI" – the philanthropies, NGOs, private consultancies, and tech giants investing in data-driven climate initiatives. Mapping out two case studies, we show that environmental and climate crises are grist for tech solutions and find that many climate AI actors are interested in it for surveillance, greenwashing, and commodifying algorithms. We pay special attention to how neocolonial and racialized power structures manifest in climate AI and outline three ways for political ecologists and digital geographers to research its socio-materiality: how computational resources are environmentally embedded, how disasters become "shocks" that the AI industry capitalizes on, and how climate AI shapes material investment flows and landscapes. Highlighting how data-driven approaches to climate crises reproduce injustices already faced by marginalized communities, our analysis contributes to research on environmental data justice. [ABSTRACT FROM AUTHOR]

Conservationists, governments, and corporations see promise in digital technologies to provide holistic, rapid, and objective information to inform policy, shape investments, and monitor ecosystems. But it is increasingly clear that environmental data does more than simply offer a better view of the planet. This special issue makes a single overarching argument: that we cannot fully understand the current conjuncture in global environmental governance without understanding the platforms, devices, and institutions that comprise environmental data infrastructures. The papers draw together scholarship from political ecology and science and technology studies to demonstrate how data has become a significant site in which contemporary environmental politics are waged and socionatures are materialized. We address: (1) the contested practices of utilizing and maintaining data infrastructures; (2) the ways they are governed and the territorial statecraft they enable; (3) the socionatural materiality they arise within but also produce. The papers in this special issue show that, against its dominant representation, data is material, governed, practiced, and requires praxis. Political ecologists could adopt such an approach to make sense of the emerging ways in which data technologies shape environments and their politics. [ABSTRACT FROM AUTHOR]

Conservationists around the world advocate for "data-driven" environmental governance, expecting data infrastructures to make all relevant and actionable information readily available. But how exactly is data to be infrastructured and to what political effect? I show how putting together and maintaining environmental data for decision-making is not a straightforward technical task, but a practice shaped by and shaping politico-economic context. Drawing from the US state of Louisiana's coastal restoration planning process, I detail two ways ecosystem modelers manage fiscal and institutional "frictions" to "infrastructuring" data as a resource for decision-making. First, these experts work with the data they have. They leverage, tweak, and maintain existing datasets and tools, spending time and money to gather additional data only to the extent it fits existing goals. The assumption is that these goals will continue to be important, but building coastal data infrastructure around current research needs, plans, and austerity arguably limits what can be said in and done with the future. Second, modelers acquire the data they made to need. Coastal communities have protested the state's primary restoration tool: diversions of sediment from the Mississippi River. Planners reacted by relaxing institutional constraints and modelers brought together new data to highlight possible winners and losers from ecological restoration. Fishers and other coastal residents leveraged greater dissent in the planning process. Political ecologists show that technocentric environmental governance tends to foreclose dissent from hegemonic socioecological futures. I argue we can clarify the conditions in which this tends to happen by following how experts manage data frictions. As some conservationists and planners double down on driving with data in a "post-truth" world, I find that data's politicizing effects stem from what is asked of it, not whether it is "big" or "drives." [ABSTRACT FROM AUTHOR]

Geographers of technology illustrate software code's contexts, effects, and agencies as they shape urban space and everyday life, but the consequences of code for nature remain understudied. Political ecologists have critiqued remote sensing and Geographic Information Systems (GIS) based conservation projects, but have not engaged more broadly with the role of software in the contested production, circulation, and application of ecological knowledge. Yet, around the world, data analytics firms and conservation nonprofits argue for optimizing environmental management through faster and bigger data collection and new techniques of data manipulation and visualization. I present a case study from the US state of Oregon, illustrating how conservationists and environmental regulators employ computer programming to plan markets in which entrepreneurs restore stream and wetland ecosystem services to earn offset credits. In these markets, code-executed algorithms constituting spreadsheets, web maps, and GIS utilities generate, relate, and make sense of the data that define credit commodities. I argue that code tends toward three effects: producing a landscape defined by wetlands' modeled value, performing social relations associated with nature's neoliberalization and financialization, and legitimating these moves. Although emphasis on the performativity of code and other technological objects is warranted, the contexts in which these are authored, deployed, and evaluated should remain central to understanding environmental governance. This is to caution against seeing technology as reducing nature and society to state or capitalist rationalities and to hesitate to differentiate prima facie code's work on space and on nature. I call for bridging political ecology and geographies of technology in ways that can explain how code is generative of environmental knowledge, change, and conflict. [ABSTRACT FROM AUTHOR]