People as Sensors: Towards a Human–Machine Cooperation Approach in Monitoring Landslides in the Three Gorges Reservoir Region, China

Li, Zhenhua; Cheng, Guoxuan; Cheng, William C.; Mei, Hongbo

doi:10.1007/978-3-319-92564-6_3

Cited by 2 publications

(2 citation statements)

References 12 publications

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“…Ground‐breaking projects explored in the literature include the initiatives launched in the aftermath of the 2010 Haiti earthquake, which saw the Haitian government, UN as well as U.S. aid and relief agencies draw heavily on user generated data to coordinate relief efforts, target resource allocation, and support particularly vulnerable and exposed groups (ITU‐D, 2019; Yates & Paquette, 2010). The landslides monitoring project recently implemented in the Three Gorges Dam region in China, which combines “traditional” remote sensing techniques with the user‐generated data to monitor landslides (Li, Cheng, Cheng, & Mei, 2019), is another notable example.…”

Section: Seeds Of Digitalized Landd?mentioning

confidence: 99%

Clouded skies: How digital technologies could reshape “Loss and Damage” from climate change

Bettini

Gioli

Felli

2020

WIREs Climate Change

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As dangerous climate change becomes more and more likely, a consensus has been reached on the importance of addressing Loss and Damage (L&D) residual to mitigation (i.e., preventing climate change) and adaptation (i.e., adjusting in order to avert adverse impacts). In spite of sharp divisions in terms of how to understand and operationalize L&D, most approaches draw on classic environmental governance, with discrete analogic interventions implemented by States and international actors. L&D is mainly envisioned as an “international court of climate justice” that identifies the culprits (emitters), quantifies harm, and compensates victims. While digital technologies and algorithmic governance have colonized many germane policy fields and virtually all economic sectors, in the L&D field a substantive discussion on the use of information and communication technologies, algorithms, and user‐generated data has been conspicuously absent. By taking the prospect of a “digitalization” of L&D seriously, this advanced review identifies the seeds of emerging digitalized approaches to L&D through an overview of literature. We focus on examples in three key domains associated with L&D—insurance, disaster responses and risk management, and human displacement. These empirical cases are used to investigate the modes of governance that accompany the digital tools through which L&D could be implemented, and the profound changes in climate politics and justice that would accompany a digitalization/algorithmization of L&D. This article is categorized under: Social Status of Climate Change Knowledge > Climate Science and Decision Making

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Section: Seeds Of Digitalized Landd?mentioning

confidence: 99%

Clouded skies: How digital technologies could reshape “Loss and Damage” from climate change

Bettini

Gioli

Felli

2020

WIREs Climate Change

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“…Particularly, there are no detailed discussions on the effects induced by climate change and reservoir operations. From a long-term perspective, the application of available monitoring methods lacks community-based support, which benefits the hypothesis of the antecedent deformation of these landslides [33]. In this regard, reconstructing the whole evolution process of the landslide behaviors under complex geological conditions remains a significant challenge.…”

Section: Introductionmentioning

confidence: 99%

Characterizing the Development Pattern of a Colluvial Landslide Based on Long-Term Monitoring in the Three Gorges Reservoir

et al. 2021

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Since the impoundment of the Three Gorges Reservoir (TGR) in June 2003, the fluctuation of the reservoir water level coupled with rainfall has resulted in more than 2500 landslides in this region. Among these instability problems, most colluvial landslides exhibit slow-moving patterns and pose a significant threat to local people and channel navigation. Advanced monitoring techniques are therefore implemented to investigate landslide deformation and provide insights for the subsequent countermeasures. In this study, the development pattern of a large colluvial landslide, locally named the Ganjingzi landslide, is analyzed on the basis of long-term monitoring. To understand the kinematic characteristics of the landslide, an integrated analysis based on real-time and multi-source monitoring, including the global navigation satellite system (GNSS), crackmeters, inclinometers, and piezometers, was conducted. The results indicate that the Ganjingzi landslide exhibits a time-variable response to the reservoir water fluctuation and rainfall. According to the supplement of community-based monitoring, the evolution of the landslide consists of three stages, namely the stable stage before reservoir impoundment, the initial movement stage of retrogressive failure, and the shallow movement stage with stepwise acceleration. The latter two stages are sensitive to the drawdown of reservoir water level and rainfall infiltration, respectively. All of the monitoring approaches used in this study are significant for understanding the time-variable pattern of colluvial landslides and are essential for landslide mechanism analysis and early warning for risk mitigation.

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People as Sensors: Towards a Human–Machine Cooperation Approach in Monitoring Landslides in the Three Gorges Reservoir Region, China

Cited by 2 publications

References 12 publications

Clouded skies: How digital technologies could reshape “Loss and Damage” from climate change

Clouded skies: How digital technologies could reshape “Loss and Damage” from climate change

Characterizing the Development Pattern of a Colluvial Landslide Based on Long-Term Monitoring in the Three Gorges Reservoir

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