SSL4EO-L: Datasets and Foundation Models for Landsat Imagery

The Landsat program is the longest-running Earth observation program in history, with 50+ years of data acquisition by 8 satellites. The multispectral imagery captured by sensors onboard these satellites is critical for a wide range of scientific fields. Despite the increasing popularity of deep learning and remote sensing, the majority of researchers still use decision trees and random forests for Landsat image analysis due to the prevalence of small labeled datasets and lack of foundation models. In this paper, we introduce SSL4EO-L, the first ever dataset designed for Self-Supervised Learning for Earth Observation for the Landsat family of satellites (including 3 sensors and 2 product levels) and the largest Landsat dataset in history (5M image patches). Additionally, we modernize and re-release the L7 Irish and L8 Biome cloud detection datasets, and introduce the first ML benchmark datasets for Landsats 4-5 TM and Landsat 7 ETM+ SR. Finally, we pre-train the first foundation models for Landsat imagery using SSL4EO-L and evaluate their performance on multiple semantic segmentation tasks. All datasets and model weights are available via the TorchGeo (https://github.com/microsoft/torchgeo) library, making reproducibility and experimentation easy, and enabling scientific advancements in the burgeoning field of remote sensing for a multitude of downstream applications

Planning a 'slum free' Trivandrum: housing upgrade and the rescaling of urban governance in India

This paper examines how India’s national urban development agenda is reshaping relationships between national, State and city-level governments. JNNURM, the flagship programme that heralded a new era of urban investment in India, contained a range of key governance aspirations: linking the analysis of urban poverty to city-level planning, developing holistic housing solutions for the urban poor, and above all empowering Urban Local Bodies to re-balance relationships between State and city-level governments in favour of the latter. Here, we trace JNNURM’s implementation in Kerala’s capital city, Trivandrum (Thiruvananthapuram), where the city’s decentralised urban governance structure and use of ‘pro-poor’ institutions to implement housing upgrade programmes could have made it an exemplar of success. In practice, Trivandrum’s ‘city visioning’ exercises and the housing projects it has undertaken have fallen short of JNNURM’s lofty goals. The contradictions between empowering cities and retaining centralised control embedded within this national programme, and the unintended city-level consequences of striving for JNNURM funding success, have reshaped urban governance in ways not envisaged within policy. As a result, JNNURM has been important in rescaling governance relationships through three interlinked dynamics of problem framing, technologies of governance and the scalar strategy of driving reform ‘from above’ that together have ensured the national state’s continued influence over the practices of urban governance in India

Groundwater dynamics in subterranean estuaries of coastal unconfined aquifers: Controls on submarine groundwater discharge and chemical inputs to the ocean

Sustainable coastal resource management requires sound understanding of interactions between coastal unconfined aquifers and the ocean as these interactions influence the flux of chemicals to the coastal ocean and the availability of fresh groundwater resources. The importance of submarine groundwater discharge in delivering chemical fluxes to the coastal ocean and the critical role of the subterranean estuary (STE) in regulating these fluxes is well recognized. STEs are complex and dynamic systems exposed to various physical, hydrological, geological, and chemical conditions that act on disparate spatial and temporal scales. This paper provides a review of the effect of factors that influence flow and salt transport in STEs, evaluates current understanding on the interactions between these influences, and synthesizes understanding of drivers of nutrient, carbon, greenhouse gas, metal and organic contaminant fluxes to the ocean. Based on this review, key research needs are identified. While the effects of density and tides are well understood, episodic and longer-period forces as well as the interactions between multiple influences remain poorly understood. Many studies continue to focus on idealized nearshore aquifer systems and future work needs to consider real world complexities such as geological heterogeneities, and non-uniform and evolving alongshore and cross-shore morphology. There is also a significant need for multidisciplinary research to unravel the interactions between physical and biogeochemical processes in the STE, as most existing studies treat these processes in isolation. Better understanding of this complex and dynamic system can improve sustainable management of coastal water resources under the influence of anthropogenic pressures and climate change

Dynamics of Broad-Emission Line Region in NGC 5548: Hydromagnetic Wind Model versus Observations

We analyze the results of long-term observations of broad-line region (BLR) in the Sy1 galaxy NGC 5548 and provide a critical comparison with the predictions of a hydromagnetically-driven outflow model of Emmering, Blandford and Shlosman. This model was used to generate a time series of CIV line profiles that have responded to a time varying continuum. The model includes cloud emission anisotropy, cloud obscuration, a CLOUDY-generated emissivity function and a narrow-line component used to generate the line profiles, and is driven with continuum input based on the monitoring campaigns of NGC 5548. The line strengths, profiles and lags are compared with the observations. It reproduces the basic features of CIV line variability in this AGN without varying the model parameters. The best fit model provides the effective size, the dominant geometry, the emissivity distribution and the 3D velocity field of the CIV BLR and constrains the mass of the central BH. The inner part of the wind appears to be responsible for the anisotropically emitted CIV line, while its outer part remains dusty and molecular, thus having similar spectral characteristics to a molecular torus, although its dynamics is fundamentally different. In addition, our model predicts a differential response across the CIV line profile, producing a red-side-first response in the mid-wings followed by the blue mid-wing and by the line core. Based on the comparison of data and model cross-correlation functions and 1D and 2D transfer functions, we find that the rotating outflow model is compatible with observations of the BLR in NGC 5548.Comment: 50 pages, TeX, 14 figures. Also available as compressed postscript at ftp://gradj.pa.uky.edu/shlosman/ngc5548 . Accepted for publication in Ap

Mapping species distributions: A comparison of skilled naturalist and lay citizen science recording

To assess the ability of traditional biological recording schemes and lay citizen science approaches to gather data on species distributions and changes therein, we examined bumblebee records from the UK’s national repository (National Biodiversity Network) and from BeeWatch. The two recording approaches revealed similar relative abundances of bumblebee species but different geographical distributions. For the widespread common carder (Bombus pascuorum), traditional recording scheme data were patchy, both spatially and temporally, reflecting active record centre rather than species distribution. Lay citizen science records displayed more extensive geographic coverage, reflecting human population density, thus offering better opportunities to account for recording effort. For the rapidly spreading tree bumblebee (Bombus hypnorum), both recording approaches revealed similar distributions due to a dedicated mapping project which overcame the patchy nature of naturalist records. We recommend, where possible, complementing skilled naturalist recording with lay citizen science programmes to obtain a nation-wide capability, and stress the need for timely uploading of data to the national repository

Eight grand challenges in socio-environmental systems modeling

Modeling is essential to characterize and explore complex societal and environmental issues in systematic and collaborative ways. Socio-environmental systems (SES) modeling integrates knowledge and perspectives into conceptual and computational tools that explicitly recognize how human decisions affect the environment. Depending on the modeling purpose, many SES modelers also realize that involvement of stakeholders and experts is fundamental to support social learning and decision-making processes for achieving improved environmental and social outcomes. The contribution of this paper lies in identifying and formulating grand challenges that need to be overcome to accelerate the development and adaptation of SES modeling. Eight challenges are delineated: bridging epistemologies across disciplines; multi-dimensional uncertainty assessment and management; scales and scaling issues; combining qualitative and quantitative methods and data; furthering the adoption and impacts of SES modeling on policy; capturing structural changes; representing human dimensions in SES; and leveraging new data types and sources. These challenges limit our ability to effectively use SES modeling to provide the knowledge and information essential for supporting decision making. Whereas some of these challenges are not unique to SES modeling and may be pervasive in other scientific fields, they still act as barriers as well as research opportunities for the SES modeling community. For each challenge, we outline basic steps that can be taken to surmount the underpinning barriers. Thus, the paper identifies priority research areas in SES modeling, chiefly related to progressing modeling products, processes and practices

Garden and landscape-scale correlates of moths of differing conservation status: significant effects of urbanization and habitat diversity

Moths are abundant and ubiquitous in vegetated terrestrial environments and are pollinators, important herbivores of wild plants, and food for birds, bats and rodents. In recent years, many once abundant and widespread species have shown sharp declines that have been cited by some as indicative of a widespread insect biodiversity crisis. Likely causes of these declines include agricultural intensification, light pollution, climate change, and urbanization; however, the real underlying cause(s) is still open to conjecture. We used data collected from the citizen science Garden Moth Scheme (GMS) to explore the spatial association between the abundance of 195 widespread British species of moth, and garden habitat and landscape features, to see if spatial habitat and landscape associations varied for species of differing conservation status. We found that associations with habitat and landscape composition were species-specific, but that there were consistent trends in species richness and total moth abundance. Gardens with more diverse and extensive microhabitats were associated with higher species richness and moth abundance; gardens near to the coast were associated with higher richness and moth abundance; and gardens in more urbanized locations were associated with lower species richness and moth abundance. The same trends were also found for species classified as increasing, declining and vulnerable under IUCN (World Conservation Union) criteria

Exploiting Large Neuroimaging Datasets to Create Connectome-Constrained Approaches for more Robust, Efficient, and Adaptable Artificial Intelligence

Despite the progress in deep learning networks, efficient learning at the edge (enabling adaptable, low-complexity machine learning solutions) remains a critical need for defense and commercial applications. We envision a pipeline to utilize large neuroimaging datasets, including maps of the brain which capture neuron and synapse connectivity, to improve machine learning approaches. We have pursued different approaches within this pipeline structure. First, as a demonstration of data-driven discovery, the team has developed a technique for discovery of repeated subcircuits, or motifs. These were incorporated into a neural architecture search approach to evolve network architectures. Second, we have conducted analysis of the heading direction circuit in the fruit fly, which performs fusion of visual and angular velocity features, to explore augmenting existing computational models with new insight. Our team discovered a novel pattern of connectivity, implemented a new model, and demonstrated sensor fusion on a robotic platform. Third, the team analyzed circuitry for memory formation in the fruit fly connectome, enabling the design of a novel generative replay approach. Finally, the team has begun analysis of connectivity in mammalian cortex to explore potential improvements to transformer networks. These constraints increased network robustness on the most challenging examples in the CIFAR-10-C computer vision robustness benchmark task, while reducing learnable attention parameters by over an order of magnitude. Taken together, these results demonstrate multiple potential approaches to utilize insight from neural systems for developing robust and efficient machine learning techniques.Comment: 11 pages, 4 figure

Infection with the hepatitis C virus causes viral genotype-specific differences in cholesterol metabolism and hepatic steatosis

Lipids play essential roles in the hepatitis C virus (HCV) life cycle and patients with chronic HCV infection display disordered lipid metabolism which resolves following successful anti-viral therapy. It has been proposed that HCV genotype 3 (HCV-G3) infection is an independent risk factor for hepatocellular carcinoma and evidence suggests lipogenic proteins are involved in hepatocarcinogenesis. We aimed to characterise variation in host lipid metabolism between participants chronically infected with HCV genotype 1 (HCV-G1) and HCV-G3 to identify likely genotype-specific differences in lipid metabolism. We combined several lipidomic approaches: analysis was performed between participants infected with HCV-G1 and HCV-G3, both in the fasting and non-fasting states, and after sustained virological response (SVR) to treatment. Sera were obtained from 112 fasting patients (25% with cirrhosis). Serum lipids were measured using standard enzymatic methods. Lathosterol and desmosterol were measured by gas-chromatography mass spectrometry (MS). For further metabolic insight on lipid metabolism, ultra-performance liquid chromatography MS was performed on all samples. A subgroup of 13 participants had whole body fat distribution determined using in vivo magnetic resonance imaging and spectroscopy. A second cohort of (non-fasting) sera were obtained from HCV Research UK for comparative analyses: 150 treatment naïve patients and 100 non-viraemic patients post-SVR. HCV-G3 patients had significantly decreased serum apoB, non-HDL cholesterol concentrations, and more hepatic steatosis than those with HCV-G1. HCV-G3 patients also had significantly decreased serum levels of lathosterol, without significant reductions in desmosterol. Lipidomic analysis showed lipid species associated with reverse cholesterol transport pathway in HCV-G3. We demonstrated that compared to HCV-G1, HCV-G3 infection is characterised by low LDL cholesterol levels, with preferential suppression of cholesterol synthesis via lathosterol, associated with increasing hepatic steatosis. The genotype-specific lipid disturbances may shed light on genotypic variations in liver disease progression and promotion of hepatocellular cancer in HCV-G3

Establishing a core outcome set for peritoneal dialysis : report of the SONG-PD (standardized outcomes in nephrology-peritoneal dialysis) consensus workshop

Outcomes reported in randomized controlled trials in peritoneal dialysis (PD) are diverse, are measured inconsistently, and may not be important to patients, families, and clinicians. The Standardized Outcomes in Nephrology-Peritoneal Dialysis (SONG-PD) initiative aims to establish a core outcome set for trials in PD based on the shared priorities of all stakeholders. We convened an international SONG-PD stakeholder consensus workshop in May 2018 in Vancouver, Canada. Nineteen patients/caregivers and 51 health professionals attended. Participants discussed core outcome domains and implementation in trials in PD. Four themes relating to the formation of core outcome domains were identified: life participation as a main goal of PD, impact of fatigue, empowerment for preparation and planning, and separation of contributing factors from core factors. Considerations for implementation were identified: standardizing patient-reported outcomes, requiring a validated and feasible measure, simplicity of binary outcomes, responsiveness to interventions, and using positive terminology. All stakeholders supported inclusion of PD-related infection, cardiovascular disease, mortality, technique survival, and life participation as the core outcome domains for PD