Selection and integration of earth observation-based data for an operational disease forecasting system

The current increase in the volume and quality of Earth Observation (EO) data being collected by satellites offers the potential to contribute to applications across a wide range of scientific domains. It is well established that there are correlations between characteristics that can be derived from EO satellite data, such as land surface temperature or land cover, and the incidence of some diseases. Thanks to the reliable frequent acquisition and rapid distribution of EO data it is now possible for this field to progress from using EO in retrospective analyses of historical disease case counts to using it in operational forecasting systems. However, bringing together EO-based and non-EO-based datasets, as is required for disease forecasting and many other fields, requires carefully designed data selection, formatting and integration processes. Similarly, it requires careful communication between collaborators to ensure that the priorities of that design process match the requirements of the application. Here we will present work from the D-MOSS (Dengue forecasting MOdel Satellite-based System) project. D-MOSS is a dengue fever early warning system for South and South East Asia that will allow public health authorities to identify areas at high risk of disease epidemics before an outbreak occurs in order to target resources to reduce spreading of epidemics and improve disease control. The D-MOSS system uses EO, meteorological and seasonal weather forecast data, combined with disease statistics and static layers such as land cover, as the inputs into a dengue fever model and a water availability model. Water availability directly impacts dengue epidemics due to the provision of mosquito breeding sites. The datasets are regularly updated with the latest data and run through the models to produce a new monthly forecast. For this we have designed a system to reliably feed standardised data to the models. The project has involved a close collaboration between remote sensing scientists, geospatial scientists, hydrologists and disease modelling experts. We will discuss our approach to the selection of data sources, data source quality assessment, and design of a processing and ingestion system to produce analysis-ready data for input to the disease and water availability models

Earthquakes and active faults in Central Asia

This thesis presents the results of research centred on three large Central Asian earthquakes from recent decades: the 1985 Wuqia (China), 1992 Suusamyr (Kyrgyzstan) and 2015 Pishan (China) earthquakes. For the Pishan earthquake I construct a fault slip model based on coseismic interferograms. It shows that the earthquake took place on a well-established fault that is visible in a seismic reflection profile. However, the coseismic and early postseismic deformations are misaligned with the longer-term topographic uplift pattern. Therefore, other mechanisms must be considered to explain the growth of topography. In a reinvestigation of the Wuqia earthquake, I combine data from several techniques to show that although surface ruptures were produced along a well-known fault, the existing models of that fault are not compatible with the earthquake’s focal mechanism or depth. Instead, most of the earthquake’s moment was released below a detachment. The detachment acts as a barrier to geomorphic expression of the basement fault, even though the observations require slip to have taken place both above and below the detachment within a month or less. In a study on the 1992 Suusamyr earthquake, I examine the significance of surface ruptures more closely. I use remote sensing and field observations to measure the extent and scarp height of the fresh ruptures, and to construct a paleoseismic record for the fault. The results reveal significant variability in the surface rupture pattern between successive earthquakes on the fault. Finally, I use those results to inform a broader study on the Suusamyr Basin. I map the tectonic structures across the entire basin and provide a slip rate estimate for the Suusamyr Fault. Overall this thesis extends the body of knowledge on continental reverse faulting earthquakes, and demonstrates the challenges and complexities of interpreting the fault structure and seismic hazard of an area based on surface observations.</p

Using remote sensing to collect data on the impact of flooding on the built environment in Kerala, India

Flooding displaces millions of people worldwide every year, causes billions of dollars’ worth of damage, and is only expected to worsen in coming decades. Measurements of floods’ socioeconomic impact are needed both to enable efficient targeting of relief resources for that event itself, and to act as verification data for the development and testing of impact-based forecast models. However, data about a flood event’s impacts can take months to collect in the aftermath of an event and are often not collected in a consistent fashion. Remote sensing data, while not equivalent to ground truth data, offers the capability to systematically collect data over large regions in a time-efficient way. Here we present research into methodologies for using remote sensing to collect data on the impact of flooding on the built environment, using the case study of the 2018 Kerala, India floods. According to figures published by the Kerala State Disaster Management Authority, the 2018 floods affected over 800,000 houses and damaged over 9,000 km of roads. Methods based on interferometric coherence decrease have proved successful in detecting structural damage in urban areas caused by natural disasters such as typhoons, tsunamis and landslides. In this situation, however, those methods perform less well because they struggle to detect flood impact in non-urban areas which did not have high pre-event coherence and at buildings that were damaged by inundation but did not sustain the type of structural or roof damage that causes coherence decrease. We therefore assess the alternative approach of combining flood and built environment datasets and we compare the results of doing so using existing or routinely-produced datasets versus using datasets processed especially for this application

Satellite data for dam safety monitoring

The use of datasets from satellites to aid the monitoring of dams has been possible for many years. Within the last five years there has been a rapid development in the type and accuracy of the data available, led by an influx of new satellites and improved access to these datasets. This paper gives an overview of the different types of satellite datasets and satellite infrastructure relevant to dam safety that are currently available, explains the complex processes of converting raw satellite data into useable information and summarises the advantages and disadvantages of each data type along with indications of the level of accuracy and cost. The information presented by the authors is based on experience gained undertaking a 3 year, £4 m, UK-government-funded research project to investigate and combine many types of space data to improve the monitoring of dams

DAMSAT - An operational system for tailings dam monitoring by bringing together remote sensing, meteorological and on-site observations

Tailings dams and storage facilities store toxic mine waste and effluent. Failure of a tailings storage facility can cause dramatic local ecosystem damage, water contamination and, if a tailings dam fails, loss of life due to inundation of the downstream area. The failure rate of tailings dams is known to be significantly greater than that of conventional water retention dams, but monitoring all tailings dams and storage facilities through frequent site visits could be an expensive and resource-demanding task. Monitoring tools based on remote sensing and internet of things (IoT) sensors have the potential to reduce the risk from tailings storage failures by enabling the organisations responsible to conduct some monitoring remotely, and hence direct their resources for detailed monitoring more efficiently. We present an overview of DAMSAT (Dam Monitoring from SATellites), an operational tool for monitoring tailings dams, tailings deposit areas and water dams. The tool consists of several different modules. Radar and optical satellite remote sensing data, and in situ internet of things (IoT) sensors are used to monitor surface movement and indicators of pollution at tailings storage sites. Meteorological forecasts are coupled to hydrological models in order to forecast changes in water level at the dams. DAMSAT presents the monitoring information together with risk information from hazard, consequence and evacuation models of possible dam failures in one integrated platform. The project is a partnership between UK and Peruvian organisations. This approach, alongside proactive user engagement activities and user requirements analysis, is designed to ensure that the system is developed with the needs of the user community in mind

Blind thrusting, surface folding and the development of geological structure in the Mw 6.3 2015 Pishan (China) Earthquake

The relationship between individual earthquakes and the longer-term growth of topography and of geological structures is not fully understood, but is key to our ability to make use of topographic and geological data sets in the contexts of seismic hazard and wider-scale tectonics. Here we investigate those relationships at an active fold-and-thrust belt in the southwest Tarim Basin, Central Asia. We use seismic waveforms and interferometric synthetic aperture radar (InSAR) to determine the fault parameters and slip distribution of the 2015 Mw6.3 Pishan earthquake—a blind, reverse-faulting event dipping toward the Tibetan Plateau. Our earthquake mechanism and location correspond closely to a fault mapped independently by seismic reflection, indicating that the earthquake was on a preexisting ramp fault over a depth range of ∼9–13 km. However, the geometry of folding in the overlying fluvial terraces cannot be fully explained by repeated coseismic slip in events such as the 2015 earthquake nor by the early postseismic motion shown in our interferograms; a key role in growth of the topography must be played by other mechanisms. The earthquake occurred at the Tarim-Tibet boundary, with the unusually low dip of 21°. We use our source models from Pishan and a 2012 event to argue that the Tarim Basin crust deforms only by brittle failure on faults whose effective coefficient of friction is ≤0.05 ± 0.025. In contrast, most of the Tibetan crust undergoes ductile deformation, with a viscosity of order 1020–1022 Pa s. This contrast in rheologies provides an explanation for the low dip of the earthquake fault plane

The damaging November 2022 Mw 5.6 earthquake in West Java, Indonesia

On 21 November 2022, a MW 5.6. earthquake hit Cianjur area in West Java, Indonesia. The small magnitude earthquake claimed 329 people’s lives, and about 114,414 people were taking shelter in refugee camps as of 1 December 2022 according to the National Disaster Mitigation Agency (BNPB) of Indonesia. We produced maps of coseismic deformation and surface disturbance (a.k.a. Damage Proxy Map, DPM) using Synthetic Aperture Radar (InSAR) data acquired by the ALOS-2 satellite about 11 hours after the earthquake. We combine and analyze ground observations, coseismic deformation and surface disturbance maps derived from ALOS-2 and Sentinel-1 SAR data, seismic waveforms of the mainshock and aftershocks, high-rate GNSS data, and tiltmeter data to characterize the source parameters of the earthquake and damage caused by the strong ground motion, landslides, and liquefaction, and study the potential impact of the event on the geohazards of the area

Magnitude of the 1920 Haiyuan Earthquake Reestimated Using Seismological and Geomorphological Methods

Reported magnitudes ranging between 7.8 and 8.7 highlight a confusion about the true size of the 1920 Haiyuan earthquake, the largest earthquake recorded in the northeast Tibetan Plateau. We compiled a global data set of previously unlooked‐at historical seismograms and performed modern computational analyses on the digitized seismic records. We found the epicenter to be near Haiyuan town and obtained a moment magnitude of MW=7.9±0.2. Following traditional approaches, we obtained mB=7.9±0.3 with data from 21 stations and MS(20)=8.1±0.2 with data from three stations. Geomorphologically, we mapped the surface rupture and horizontal offsets on high‐resolution Pleiades satellite and drone imagery that covered the entire western and middle sections of the 1920 Haiyuan earthquake rupture and compiled offsets reported on the eastern section from field measurements in the 1980s. Careful discrimination between single‐event and cumulative offsets suggests average horizontal slips of 3.0±1.0 m on the western section, 4.5±1.5 m on the middle section, and 3.5±0.5 m on the eastern section, indicating a total moment magnitude of MW=7.8±0.1. Thus, the seismological and geomorphological results agree within the uncertainties, a weighted average giving a moment magnitude of MW=7.9±0.2 for the 1920 Haiyuan earthquake. It is likely that earthquake magnitudes based on the historical M were systematically overestimated