‘Looting marks’ in space-borne SAR imagery: measuring rates of archaeological looting in Apamea (Syria) with TerraSAR-X Staring Spotlight

In archaeological remote sensing, space-borne Synthetic Aperture Radar (SAR) has not been used so far to monitor ‘looting’ (i.e. illegal excavations in heritage sites) mainly because of the spatial resolution of SAR images, typically not comparable to the ground dimensions of looting features. This paper explores the potential of the new TerraSAR-X beam mode Staring Spotlight (ST) to investigate looting within a workflow of radar backscattering change detection. A bespoke time series of five single polarisation, ascending mode, ST scenes with an unprecedented azimuth resolution of 0.24 m was acquired over the archaeological site of Apamea in western Syria, from October 2014 to June 2015 with a regular sampling of one image every two months. Formerly included in the Tentative List of UNESCO, the site has been heavily looted from at least early 2012 to May 2014, as confirmed by Google Earth Very High Resolution (VHR) optical imagery. Building upon the theory of SAR imaging, we develop a novel conceptual model of ‘looting marks’, identify marks due to occurrence of new looting and discriminate them from alteration (e.g. filling) of pre-existing looting holes. ‘Looting marks’ appear as distinctive patterns of shadow and layover which are visible in the ground-range reprojected ST image and generated by the morphology of the holes. The recognition of looting marks within ratio maps of radar backscatter (σ0) between consecutive ST scenes allows quantification of the magnitude, spatial distribution and rates of looting activities. In agreement with the estimates based on Google Earth imagery, the ST acquired in October 2014 shows that ~ 45% of the site was looted. In the following eight months new looting happened locally, with holes mainly dug along the margins of the already looted areas. Texture values of ~ 0.31 clearly distinguish these holes from the unaltered, bare ground nearby. Hot spots of change are identified based on the temporal variability of σ0, and colour composites indicate where repeated looting and alteration of existing holes occurred. Most looting marks are observed north of the two main Roman decumani. Looting intensified almost steadily from December 2014, with over 1500 new marks in February–April 2015. The estimated rates of looting increased from 214 looting marks/month in October–December 2014 to over 780 marks/month in April–June 2015, and numerically express the dynamic nature of the phenomenon to which Apamea is still exposed. The method of identifying looting marks in VHR radar images therefore proves a reliable opportunity for archaeologists and image analysts to measure remotely the scale of looting and monitor its temporal evolution

Aspects of Nucleon Compton Scattering

We consider the spin-averaged nucleon forward Compton scattering amplitude in heavy baryon chiral perturbation theory including all terms to order ${\cal O} (q^4)$. The chiral prediction for the spin-averaged forward Compton scattering amplitude is in good agreement with the data for photon energies $\omega \le 110$ MeV. We also evaluate the nucleon electric and magnetic Compton polarizabilities to this order and discuss the uncertainties of the various counter terms entering the chiral expansion of these quantities.Comment: 17 pp, TeX, 7 figures available from the authors, preprint CRN-93/5

UNDERSTANDING THE SCALAR MESON qqˉq\bar q NONET

It is shown that one can fit the available data on the a0(980), f0(980), f0(1300) and K*0(1430) mesons as a distorted 0++ qq bar nonet using very few (5-6) parameters and an improved version of the unitarized quark model. This includes all light two-pseudoscalar thresholds, constraints from Adler zeroes, flavour symmetric couplings, unitarity and physically acceptable analyticity. The parameters include a bare uu bar or dd bar mass, an over-all coupling constant, a cutoff and a strange quark mass of 100 MeV, which is in accord with expectations from the quark model. It is found that in particular for the a0(980) and f0(980) the KK bar component in the wave function is large, i.e., for a large fraction of the time the qq bar state is transformed into a virtual KK bar pair. This KK bar component, together with a similar component of eta' pi for the a0(980) , and eta eta, eta eta' and eta' eta' components for the f0(980), causes the substantial shift to a lower mass than what is naively expected from the qq bar component alone. Mass, width and mixing parameters, including sheet and pole positions, of the four resonances are given, with a detailed pedagogical discussion of their meaning.Comment: 35 pages in plain latex (ZPC in press), 10 figures obtainable from the author ([email protected]) with regular mail or as a large PS fil

Use of SMS texts for facilitating access to online alcohol interventions: a feasibility study

A41 Use of SMS texts for facilitating access to online alcohol interventions: a feasibility study In: Addiction Science & Clinical Practice 2017, 12(Suppl 1): A4

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

The effect of leaf-on and leaf-off forest canopy conditions on LiDAR derived estimations of forest structural diversity

Forest structural diversity metrics describing diversity in tree size and crown shape within forest stands can be used as indicators of biodiversity. These diversity metrics can be generated using airborne laser scanning (LiDAR) data to provide a rapid and cost effective alternative to ground-based inspection. Measures of tree height derived from LiDAR can be significantly affected by the canopy conditions at the time of data collection, in particular whether the canopy is under leaf-on or leaf-off conditions, but there have been no studies of the effects on structural diversity metrics. The aim of this research is to assess whether leaf-on/leaf-off changes in canopy conditions during LiDAR data collection affect the accuracy of calculated forest structural diversity metrics. We undertook a quantitative analysis of LiDAR ground detection and return height, and return height diversity from two airborne laser scanning surveys collected under leaf-on and leaf-off conditions to assess initial dataset differences. LiDAR data were then regressed against field-derived tree size diversity measurements using diversity metrics from each LiDAR dataset in isolation and, where appropriate, a mixture of the two. Models utilising leaf-off LiDAR diversity variables described DBH diversity, crown length diversity and crown width diversity more successfully than leaf-on (leaf-on models resulted in R² values of 0.66, 0.38 and 0.16, respectively, and leaf-off models 0.67, 0.37 and 0.23, respectively). When LiDAR datasets were combined into one model to describe tree height diversity and DBH diversity the models described 75% and 69% of the variance (R² of 0.75 for tree height diversity and 0.69 for DBH diversity). The results suggest that tree height diversity models derived from airborne LiDAR, collected (and where appropriate combined) under any seasonal conditions, can be used to differentiate between simple single and diverse multiple storey forest structure with confidence

Remote sensing for monitoring tropical dryland forests: A review of current research, knowledge gaps and future directions for Southern Africa

Climate change, manifest via rising temperatures, extreme drought, and associated anthropogenic activities, has a negative impact on the health and development of tropical dryland forests. Southern Africa encompasses significant areas of dryland forests that are important to local communities but are facing rapid deforestation and are highly vulnerable to biome degradation from land uses and extreme climate events. Appropriate integration of remote sensing technologies helps to assess and monitor forest ecosystems and provide spatially explicit, operational, and long-term data to assist the sustainable use of tropical environment landscapes. The period from 2010 onwards has seen the rapid development of remote sensing research on tropical forests, which has led to a significant increase in the number of scientific publications. This review aims to analyse and synthesise the evidence published in peer review studies with a focus on optical and radar remote sensing of dryland forests in Southern Africa from 1997-2020. For this study, 137 citation indexed research publications have been analysed with respect to publication timing, study location, spatial and temporal scale of applied remote sensing data, satellite sensors or platforms employed, research topics considered, and overall outcomes of the studies. This enabled us to provide a comprehensive overview of past achievements, current efforts, major research topics studies, EO product gaps/challenges, and to propose ways in which challenges may be overcome. It is hoped that this review will motivate discussion and encourage uptake of new remote sensing tools (e.g., Google Earth Engine (GEE)), data (e.g., the Sentinel satellites), improved vegetation parameters (e.g., red-edge related indices, vegetation optical depth (VOD)) and methodologies (e.g., data fusion or deep learning, etc.), where these have potential applications in monitoring dryland forests

Improving above ground biomass estimates of Southern Africa dryland forests by combining Sentinel-1 SAR and Sentinel-2 multispectral imagery

Having the ability to make accurate assessments of above ground biomass (AGB) at high spatial resolution is invaluable for the management of dryland forest resources in areas at risk from deforestation, forest degradation pressure and climate change impacts. This study reports on the use of satellite-based synthetic-aperture radar (SAR) and multispectral imagery for estimating AGB by correlating satellite observations with ground truth data collected on forest plots from dryland forests in the Chobe National Park, Botswana. We undertook nineteen quantitative experiments with Sentinel-1 (S1), and Sentinel-2 (S2) and tested simple and multivariate regression including parametric (linear) and non-parametric (random forests) algorithms, to explore the optimal approaches for AGB estimation. The largest AGB value of 145 Mg/ha was found in northern Chobe while a large part of the study area (85%) is characterized by low AGB values (80 Mg/ha AGB, whereas the inclusion of SAR backscatter and optical red edge bands (B5) significantly reduces saturation effects in areas of high biomass. GNDVI and red edge (B5) derived vegetation indices have more potential for estimating AGB in dryland forests than NDVI. Our results demonstrate that dryland AGB can be estimated with a reasonable level of precision from open access Earth observation data using multivariate random forest regression

Integrating remote sensing and demography for more efficient and effective assessment of changing mountain forest distribution

Species range shifts have been well studied in light of rising global temperatures and the role climate plays in restricting species distribution. In mountain regions, global trends show upward elevational shifts of altitudinal treelines. However, there is significant variation in response between geographic locations driven by climatic and habitat heterogeneity and biotic interactions. Accurate estimation of treeline shifts requires fine-scale patterns of forest structure to be discriminated across mountain ranges. Satellite remote sensing allows detailed information on forest structure to be extrapolated across mountain ranges, however, variation in methodology combined with a lack of information on accuracy and repeatability has led to high uncertainty in the utility of remotely sensed data in studies of mountain treelines. We unite three themes; suitability of remote sensing products, ecological relevance of classifications and effectiveness of the training and validation process in relation to the study of mountain treeline ecotones. We identify needs for further research comparing the utility of different remotely sensed data sets, better characterisation of treeline structure and incorporation of accuracy assessment. Collectively, the improvements we describe will significantly improve the utility of remote sensing by facilitating a more consistent approach to defining geographic variation in treeline structure, improving our ability to link processes from stand to regional scale and the accuracy of range shift assessments. Ultimately, this advance will enable better monitoring of mountain treeline shifts and estimation of the associated to biodiversity and ecosystem function