The chapter introduces the idea of using networks inspired by Systemic Functional Grammar to model the relationship between constructions that express a semantic field. The example used in the chapter is Causation. From the work described in chapter 3, 105 verb argument constructions are identified as expressing Causation. A preliminary division is made between causing an action, causing a state, and causing a change in thought or emotion. Finer distinctions within each are then identified, with these distinctions being explained and modelled in taxonomies or Meaning Networks. Finally, the features that contribute to those networks are identified and expressed as independent choice networks, referred to as Systemic Networks.

Chapter 9 examines the three factors that affect radar range measurement: spatial and temporal variations of the dry and wet components of the troposphere, phase advance of radar waves through the ionosphere, and the solid Earth tides. It also discusses practical corrections and mitigation approaches.

The Climate Vulnerable Forum (CVF) and the V20 group of finance ministers address climate change impacts on vulnerable countries. This chapter introduces the interconnectedness of climate justice, economic resilience, and sustainable development. It highlights personal stories, such as Victor Yalanda from Colombia and Jevanic Henry from Saint Lucia, who share their experiences of climate change’s impacts on their communities — covering both the economic loss and the emotional devastation caused to communities. We introduce the CVF’s Climate Vulnerability Monitor — a unique study of the impacts of climate change, including fresh modelling, covering biophysical, economics and health projections up to 2100. The global community via COP27 and COP28 have agreed on the urgency of both adaptation and mitigation strategies. Yet the speed of change is not sufficient. The fate of today’s most vulnerable will soon be the fate of the world.

Chapter 4 provides a comprehensive presentation of the commonly used range-Doppler algorithm for focusing complex backscatter data into a single-look complex (SLC) image.

The coda draws out the implications of modernist physiognomy for our contemporary moment. As we move from nineteenth-century physiognomy to modernist physiognomy, we encounter more minimalist descriptions of faces – facial sketches, outlines. We encounter faces reduced to a minimalist form. This form is taken up by contemporary facial recognition technologies. Across the scholarly literature on facial recognition technologies, there is a growing awareness of bias: technology is biased because training sets are biased. As Cathy O’Neil writes, “data embeds the dark past.” At the conclusion of this book, the coda frames its contribution to the call issued by Soshana Zuboff in Surveillance Capitalism: “If the digital future is to be our home, then it is we who must make it so.” This book will have aimed to give historicized substance to a fragment of this past: algorithmic data embeds the long history of the face, including elements of modernist physiognomy.

The chapter explains the process of building Meaning Networks and Systemic Networks, as described in chapter 6, for two semantic fields: Cognition and Communication. The identification of these fields is inspired by the Systemic Function Grammar processes: mental and verbal. The Cognition field is divided into Emotion (53 constructions), Perception (9 constructions) and Thought (92 constructions). Following an overview, the Communication field is divided into communication about a future action (Communication: Action) (21 constructions) and communication about information (Communication: Information) (82 constructions). For each semantic field, the constructions are described as they relate to one another. Their significant features are identified and expressed in Systemic Networks. The distinctions or choices between the constructions are modelled in taxonomies or Meaning Networks.

Soon after the project was announced in 2007, the Bengaluru Metro Rail Corporation Limited (BMRCL) began putting together plans to acquire land. Unsurprisingly, a number of middle-class and wealthy neighbourhoods refused to move in order to make way for the construction. Two working-class neighbourhoods, densely populated and centrally located, entered the arduous process of negotiating with the BMRCL. As they were in close proximity to the Central Majestic bus station and railway station, the two neighbourhoods – Basaveshwara Nagara and Jai Bhim Nagara – were also well connected to the other parts of the city.5 Unlike illegal settlements that are often evicted brutally, the two neighbourhoods were offered the chance of consultation and options once they had vacated their homes.