Publications

    Vi Hart, Divya Siddarth, Bethan Cantrell, Lila Tretikov, Peter Eckersley, John Langford, Scott Leibrand, Sham Kakade, Steve Latta, Dana Lewis, Stefano Tessaro, and Glen Weyl. 5/9/2020. Outpacing the Virus: Digital Response to Containing the Spread of COVID-19 while Mitigating Privacy Risks. Edmond J. Safra Center for Ethics: Rapid Response Initiative. Publisher's VersionAbstract
    There is a growing consensus that we must use a combined strategy of medical and technological tools to provide us with response at a scale that can outpace the speed and proliferation of the SARS-CoV-2 virus. A process of identifying exposed individuals who have come into contact with diagnosed individuals, called “contact tracing,” has been shown to effectively enable suppression of new cases of SARS-CoV-2 (COVID-19). Important concerns around protecting patient’s confidentiality and civil liberties, and lack of familiarity with available privacy-protecting technologies, have both led to suboptimal privacy implementations and hindered adoption. This paper reviews the trade-offs of these methods, their techniques, the necessary rate of adoption, and critical security and privacy controls and concerns for an information system that can accelerate medical response. Proactive use of intentionally designed technology can support voluntary participation from the public toward the goals of smart testing, effective resource allocation, and relaxing some of physical distancing measures, but only when it guarantees and assures an individual’s complete control over disclosure, and use of data in the way that protects individual rights.
    Justin Chan, Dean Foster, Shyam Gollakota, Eric Horvitz, Joseph Jaeger, Sham Kakade, Tadayoshi Kohno, John Langford, Jonathan Larson, Puneet Sharma, Sudheesh Singanamalla, and Jacob Sunshine. 5/7/2020. “PACT: Privacy Sensitive Protocols and Mechanisms for Mobile Contact Tracing.” IEEE Bulletin on Data Engineering, Pp. 15-35. Publisher's VersionAbstract
    The global health threat from COVID-19 has been controlled in a number of instances by large-scale testing and contact tracing efforts. We created this document to suggest three functionalities on how we might best harness computing technologies to supporting the goals of public health organizations in minimizing morbidity and mortality associated with the spread of COVID-19, while protecting the civil liberties of individuals. In particular, this work advocates for a third-party free approach to assisted mobile contact tracing, because such an approach mitigates the security and privacy risks of requiring a trusted third party. We also explicitly consider the inferential risks involved in any contract tracing system, where any alert to a user could itself give rise to de-anonymizing information. More generally, we hope to participate in bringing together colleagues in industry, academia, and civil society to discuss and converge on ideas around a critical issue rising with attempts to mitigate the COVID-19 pandemic.
    Alex Zwanenburg, Martin Vallières, Mahmoud A Abdalah, Hugo JWL Aerts, Vincent Andrearczyk, Aditya Apte, Saeed Ashrafinia, Spyridon Bakas, Roelof J Beukinga, Ronald Boellaard, Marta Bogowicz, Luca Boldrini, Irène Buvat, Gary JR Cook, Christos Davatzikos, Adrien Depeursinge, Marie-Charlotte Desseroit, Nicola Dinapoli, Cuong Viet Dinh, Sebastian Echegaray, Issam El Naqa, Andriy Y Fedorov, Roberto Gatta, Robert J Gillies, Vicky Goh, Michael Götz, Matthias Guckenberger, Sung Min Ha, Mathieu Hatt, Fabian Isensee, Philippe Lambin, Stefan Leger, Ralph TH Leijenaar, Jacopo Lenkowicz, Fiona Lippert, Are Losnegård, Klaus H Maier-Hein, Olivier Morin, Henning Müller, Sandy Napel, Christophe Nioche, Fanny Orlhac, Sarthak Pati, Elisabeth AG Pfaehler, Arman Rahmim, Arvind UK Rao, Jonas Scherer, Muhammad Musib Siddique, Nanna M Sijtsema, Jairo Socarras Fernandez, Emiliano Spezi, Roel JHM Steenbakkers, Stephanie Tanadini-Lang, Daniela Thorwarth, Esther GC Troost, Taman Upadhaya, Vincenzo Valentini, Lisanne V van Dijk, Joost van Griethuysen, Floris HP van Velden, Philip Whybra, Christian Richter, and Steffen Löck. 5/2020. “The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping.” Radiology, 295, 2, Pp. 328-38.Abstract
    Background Radiomic features may quantify characteristics present in medical imaging. However, the lack of standardized definitions and validated reference values have hampered clinical use. Purpose To standardize a set of 174 radiomic features. Materials and Methods Radiomic features were assessed in three phases. In phase I, 487 features were derived from the basic set of 174 features. Twenty-five research teams with unique radiomics software implementations computed feature values directly from a digital phantom, without any additional image processing. In phase II, 15 teams computed values for 1347 derived features using a CT image of a patient with lung cancer and predefined image processing configurations. In both phases, consensus among the teams on the validity of tentative reference values was measured through the frequency of the modal value and classified as follows: less than three matches, weak; three to five matches, moderate; six to nine matches, strong; 10 or more matches, very strong. In the final phase (phase III), a public data set of multimodality images (CT, fluorine 18 fluorodeoxyglucose PET, and T1-weighted MRI) from 51 patients with soft-tissue sarcoma was used to prospectively assess reproducibility of standardized features. Results Consensus on reference values was initially weak for 232 of 302 features (76.8%) at phase I and 703 of 1075 features (65.4%) at phase II. At the final iteration, weak consensus remained for only two of 487 features (0.4%) at phase I and 19 of 1347 features (1.4%) at phase II. Strong or better consensus was achieved for 463 of 487 features (95.1%) at phase I and 1220 of 1347 features (90.6%) at phase II. Overall, 169 of 174 features were standardized in the first two phases. In the final validation phase (phase III), most of the 169 standardized features could be excellently reproduced (166 with CT; 164 with PET; and 164 with MRI). Conclusion A set of 169 radiomics features was standardized, which enabled verification and calibration of different radiomics software. © RSNA, 2020 See also the editorial by Kuhl and Truhn in this issue.
    Andrew Cropper and Rolf Morel. 5/2020. “Learning programs by learning from failures”. PDFAbstract
    We introduce learning programs by learning from failures. In this approach, an inductive logic programming (ILP) system (the learner) decomposes the learning problem into three separate stages: generate, test, and constrain. In the generate stage, the learner generates a hypothesis (a logic program) that satisfies a set of hypothesis constraints (constraints on the syntactic form of hypotheses). In the test stage, the learner tests the hypothesis against training examples. A hypothesis fails when it does not entail all the positive examples or entails a negative example. If a hypothesis fails, then, in the constrain stage, the learner learns constraints from the failed hypothesis to prune the hypothesis space, i.e. to constrain subsequent hypothesis generation. For instance, if a hypothesis is too general (entails a negative example), the constraints prune generalisations of the hypothesis. If a hypothesis is too specific (does not entail all the positive examples), the constraints prune specialisations of the hypothesis. This loop repeats until (1) the learner finds a hypothesis that entails all the positive and none of the negative examples, or (2) there are no more hypotheses to test. We implement our idea in Popper, an ILP system which combines answer set programming and Prolog. Popper supports infinite domains, reasoning about lists and numbers, learning optimal (textually minimal) programs, and learning recursive programs. Our experimental results on three diverse domains (number theory problems, robot strategies, and list transformations) show that (1) constraints drastically improve learning performance, and (2) Popper can substantially outperform state-of-the-art ILP systems, both in terms of predictive accuracies and learning times.
    Andrey Fedorov, Reinhard Beichel, Jayashree Kalpathy-Cramer, David Clunie, Michael Onken, Jörg Riesmeier, Christian Herz, Christian Bauer, Andrew Beers, Jean-Christophe Fillion-Robin, Andras Lasso, Csaba Pinter, Steve Pieper, Marco Nolden, Klaus Maier-Hein, Markus D Herrmann, Joel Saltz, Fred Prior, Fiona Fennessy, John Buatti, and Ron Kikinis. 5/2020. “Quantitative Imaging Informatics for Cancer Research.” JCO Clin Cancer Inform, 4, Pp. 444-53.Abstract
    PURPOSE: We summarize Quantitative Imaging Informatics for Cancer Research (QIICR; U24 CA180918), one of the first projects funded by the National Cancer Institute (NCI) Informatics Technology for Cancer Research program. METHODS: QIICR was motivated by the 3 use cases from the NCI Quantitative Imaging Network. 3D Slicer was selected as the platform for implementation of open-source quantitative imaging (QI) tools. Digital Imaging and Communications in Medicine (DICOM) was chosen for standardization of QI analysis outputs. Support of improved integration with community repositories focused on The Cancer Imaging Archive (TCIA). Priorities included improved capabilities of the standard, toolkits and tools, reference datasets, collaborations, and training and outreach. RESULTS: Fourteen new tools to support head and neck cancer, glioblastoma, and prostate cancer QI research were introduced and downloaded over 100,000 times. DICOM was amended, with over 40 correction proposals addressing QI needs. Reference implementations of the standard in a popular toolkit and standalone tools were introduced. Eight datasets exemplifying the application of the standard and tools were contributed. An open demonstration/connectathon was organized, attracting the participation of academic groups and commercial vendors. Integration of tools with TCIA was improved by implementing programmatic communication interface and by refining best practices for QI analysis results curation. CONCLUSION: Tools, capabilities of the DICOM standard, and datasets we introduced found adoption and utility within the cancer imaging community. A collaborative approach is critical to addressing challenges in imaging informatics at the national and international levels. Numerous challenges remain in establishing and maintaining the infrastructure of analysis tools and standardized datasets for the imaging community. Ideas and technology developed by the QIICR project are contributing to the NCI Imaging Data Commons currently being developed.
    Aloni Cohen and Kobbi Nissim. 5/2020. “Towards formalizing the GDPR’s notion of singling out.” Proceedings of the National Academy of Sciences. Publisher's VersionAbstract
    There is a significant conceptual gap between legal and mathematical thinking around data privacy. The effect is uncertainty as to which technical offerings meet legal standards. This uncertainty is exacerbated by a litany of successful privacy attacks demonstrating that traditional statistical disclosure limitation techniques often fall short of the privacy envisioned by regulators. We define “predicate singling out,” a type of privacy attack intended to capture the concept of singling out appearing in the General Data Protection Regulation (GDPR). An adversary predicate singles out a dataset x using the output of a data-release mechanism M(x) if it finds a predicate p matching exactly one row in x with probability much better than a statistical baseline. A data-release mechanism that precludes such attacks is “secure against predicate singling out” (PSO secure). We argue that PSO security is a mathematical concept with legal consequences. Any data-release mechanism that purports to “render anonymous” personal data under the GDPR must prevent singling out and, hence, must be PSO secure. We analyze the properties of PSO security, showing that it fails to compose. Namely, a combination of more than logarithmically many exact counts, each individually PSO secure, facilitates predicate singling out. Finally, we ask whether differential privacy and k-anonymity are PSO secure. Leveraging a connection to statistical generalization, we show that differential privacy implies PSO security. However, and in contrast with current legal guidance, k-anonymity does not: There exists a simple predicate singling out attack under mild assumptions on the k-anonymizer and the data distribution.
    Collin F. Payne, Sumaya Mall, Lindsay Kobayashi, Kathy Kahn, and Lisa Berkman. 4/24/2020. “Life-Course Trauma and Later Life Mental, Physical, and Cognitive Health in a Postapartheid South African Population: Findings From the HAALSI study.” Journal of Aging and Health, Pp. 0898264320913450. Publisher's VersionAbstract
    Objective: To investigate the relationships between exposure to life-course traumatic events (TEs) and later life mental, physical, and cognitive health outcomes in the older population of a rural South African community. Method: Data were from baseline interviews with 2,473 adults aged ≥40 years in the population-representative Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community in South Africa (HAALSI) study, conducted in 2015. We assessed exposure to 16 TEs, and used logistic regression models to estimate associations with depression, post-traumatic stress disorder (PTSD), activities of daily living disability, and cognitive impairment. Results: Participants reported an average of 5 (SD = 2.4) TEs over their lifetimes. Exposure was ubiquitous across sociodemographic and socioeconomic groups. Trauma exposure was associated with higher odds of depression, PTSD, and disability, but not with cognitive health. Discussion: Results suggest that TEs experienced in earlier life continue to reverberate today in terms of mental health and physical disability outcomes in an older population in rural South Africa.
    Lily Xu*, Shahrzad Gholami *, Sara Mc Carthy, Bistra Dilkina, Andrew Plumptre, Milind Tambe, Rohit Singh, Mustapha Nsubuga, Joshua Mabonga, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Tom Okello, and Eric Enyel. 4/20/2020. “Stay Ahead of Poachers: Illegal Wildlife Poaching Prediction and Patrol Planning Under Uncertainty with Field Test Evaluations.” In IEEE International Conference on Data Engineering (ICDE-20).Abstract
    Illegal wildlife poaching threatens ecosystems and drives endangered species toward extinction. However, efforts for wildlife protection are constrained by the limited resources of law enforcement agencies. To help combat poaching, the Protection Assistant for Wildlife Security (PAWS) is a machine learning pipeline that has been developed as a data-driven approach to identify areas at high risk of poaching throughout protected areas and compute optimal patrol routes. In this paper, we take an end-to-end approach to the data-to-deployment pipeline for anti-poaching. In doing so, we address challenges including extreme class imbalance (up to 1:200), bias, and uncertainty in wildlife poaching data to enhance PAWS, and we apply our methodology to three national parks with diverse characteristics. (i) We use Gaussian processes to quantify predictive uncertainty, which we exploit to improve robustness of our prescribed patrols and increase detection of snares by an average of 30%. We evaluate our approach on real-world historical poaching data from Murchison Falls and Queen Elizabeth National Parks in Uganda and, for the first time, Srepok Wildlife Sanctuary in Cambodia. (ii) We present the results of large-scale field tests conducted in Murchison Falls and Srepok Wildlife Sanctuary which confirm that the predictive power of PAWS extends promisingly to multiple parks. This paper is part of an effort to expand PAWS to 800 parks around the world through integration with SMART conservation software. 
    Donald E. Frederick and Tyler J. VanderWeele. 4/17/2020. “Longitudinal meta-analysis of job crafting shows positive association with work engagement.” Cogent Psychology, 7, 1, Pp. 1746733. Publisher's VersionAbstract
    Work engagement is a state in which workers show high levels of vigor, dedication, and absorption to and in their work and have been associated with several positive life outcomes. Job crafting describes a set of pro-active behaviors in which individuals alter their work behaviors and environments. It is thought increased job crafting may be associated with increased work engagement. In order to estimate the effect of job crafting on work engagement and control for reverse causation, we performed a random-effects meta-analysis focused on repeated data designs (e.g., longitudinal, daily diary, RCT). We found a considerable positive association between job crafting and later work engagement (standardized effect size of d = 0.37, 95%CI = [0.16, 0.58]). We conclude the paper with a general discussion of the state of job crafting research, limitations, and a call for large randomized controlled trial interventions
    Ece Amber Özçelik, Julia Rohr, Kristy Hackett, Iqbal Shah, and David Canning. 4/14/2020. “Applying Inverse Probability Weighting to Measure Contraceptive Prevalence Using Data from a Community-Based Reproductive Health Intervention in Pakistan.” Kristy Hackett, 46, Pp. 21-33. Publisher's VersionAbstract

    CONTEXT: Many community-based reproductive health programs use their program data to monitor progress toward goals. However, using such data to assess programmatic impact on outcomes such as contraceptive use poses methodological challenges. Inverse probability weighting (IPW) may help overcome these issues.

    METHODS: Data on 33,162 women collected in 2013–2015 as part of a large-scale community-based reproductive health initiative were used to produce population-level estimates of the contraceptive prevalence rate (CPR) and modern contraceptive prevalence rate (mCPR) among married women aged 15–49 in Pakistan's Korangi District. To account for the nonrandom inclusion of women in the sample, estimates of contraceptive prevalence during the study's four seven-month intervention periods were made using IPW; these estimates were compared with estimates made using complete case analysis (CCA) and the last observation carried forward (LOCF) method—two approaches for which modeling assumptions are less flexible.

    RESULTS: In accordance with intervention protocols, the likelihood that women were visited by intervention personnel and thus included in the sample differed according to their past and current contraceptive use. Estimates made using IPW suggest that the CPR increased from 51% to 64%, and the mCPR increased from 34% to 53%, during the study. For both outcomes, IPW estimates were higher than CCA estimates, were generally similar to LOCF estimates and yielded the widest confidence intervals.

    CONCLUSION: IPW offers a powerful methodology for overcoming estimation challenges when using program data that are not representative of the population in settings where cost impedes collection of outcome data for an appropriate control group.

    130 -, O’Connor BB, Grevesse T, Zimmerman JF, Ardoña HAM, Jimenez JA, Bitounis D, Demokritou P, and Parker KK. 4/14/2020. “Human brain microvascular endothelial cell pairs model tissue-level blood–brain barrier function.” Integrative Biology, 2, 3, Pp. 64-79. Publisher's VersionAbstract
    The blood-brain barrier plays a critical role in delivering oxygen and nutrients to the brain while preventing the transport of neurotoxins. Predicting the ability of potential therapeutics and neurotoxicants to modulate brain barrier function remains a challenge due to limited spatial resolution and geometric constraints offered by existing in vitro models. Using soft lithography to control the shape of microvascular tissues, we predicted blood-brain barrier permeability states based on structural changes in human brain endothelial cells. We quantified morphological differences in nuclear, junction, and cytoskeletal proteins that influence, or indicate, barrier permeability. We established a correlation between brain endothelial cell pair structure and permeability by treating cell pairs and tissues with known cytoskeleton-modulating agents, including a Rho activator, a Rho inhibitor, and a cyclic adenosine monophosphate analog. Using this approach, we found that high-permeability cell pairs showed nuclear elongation, loss of junction proteins, and increased actin stress fiber formation, which were indicative of increased contractility. We measured traction forces generated by high- and low-permeability pairs, finding that higher stress at the intercellular junction contributes to barrier leakiness. We further tested the applicability of this platform to predict modulations in brain endothelial permeability by exposing cell pairs to engineered nanomaterials, including gold, silver-silica, and cerium oxide nanoparticles, thereby uncovering new insights into the mechanism of nanoparticle-mediated barrier disruption. Overall, we confirm the utility of this platform to assess the multiscale impact of pharmacological agents or environmental toxicants on blood-brain barrier integrity.
    Aditya Mate, Jackson A. Killian, Bryan Wilder, Marie Charpignon, Ananya Awasthi, Milind Tambe, and Maimuna S. Majumder. 4/13/2020. “Evaluating COVID-19 Lockdown Policies For India: A Preliminary Modeling Assessment for Individual States.” SSRN. Publisher's VersionAbstract
    Background: On March 24, India ordered a 3-week nationwide lockdown in an effort to control the spread of COVID-19. While the lockdown has been effective, our model suggests that completely ending the lockdown after three weeks could have considerable adverse public health ramifications. We extend our individual-level model for COVID-19 transmission [1] to study the disease dynamics in India at the state level for Maharashtra and Uttar Pradesh to estimate the effect of further lockdown policies in each region. Specifically, we test policies which alternate between total lockdown and simple physical distancing to find "middle ground" policies that can provide social and economic relief as well as salutary population-level health effects.

    Methods: We use an agent-based SEIR model that uses population-specific age distribution, household structure, contact patterns, and comorbidity rates to perform tailored simulations for each region. The model is first calibrated to each region using publicly available COVID-19 death data, then implemented to simulate a range of policies. We also compute the basic reproduction number R0 and case documentation rate for both regions.

    Results: After the initial lockdown, our simulations demonstrate that even policies that enforce strict physical distancing while returning to normal activity could lead to widespread outbreaks in both states. However, "middle ground" policies that alternate weekly between total lockdown and physical distancing may lead to much lower rates of infection while simultaneously permitting some return to normalcy.
    A. Shekhar, J. Chen, J. C. Paetzold, F. Dietrich, X. Zhao, S. Bhattacharjee, V. Ruisinger, and S. C. Wofsy. 4/10/2020. “Anthropogenic CO(2)emissions assessment of Nile Delta using XCO(2)and SIF data from OCO-2 satellite.” Environmental Research Letters, 15, 9. Publisher's VersionAbstract
    We estimate CO2 emissions from the Nile Delta region of Egypt, using over five years of column-averaged CO2 dry air mole fraction (XCO2) data from the NASA's OCO-2 satellite. The Nile Delta has significant anthropogenic emissions of CO2 from urban areas and irrigated farming. It is surrounded by the Sahara desert and the Mediterranean Sea, minimizing the confounding influence of CO2 sources in surrounding areas. We compiled the observed spatial and temporal variations of XCO2 in the Nile Delta region (XCO2,del), and found that values for XCO2,del were on average 1.1 ppm higher than XCO2,des (mean XCO2 in desert area). We modelled the expected enhancements of XCO2 over the Nile Delta based on two global CO2 emission inventories, EDGAR and ODIAC. Modelled XCO2 enhancements were much lower, indicating underestimation of CO2 emissions in the Nile Delta region by mean factors of 4.5 and 3.4 for EDGAR and ODIAC, respectively. Furthermore, we captured a seasonal pattern of XCO2 enhancement (ΔXCO2), with significantly lower ΔXCO2 during the summer agriculture season in comparison to other seasons. Additionally, we used solar-induced fluorescence (SIF) measurement from OCO-2 to understand how the CO2 emissions are related to agricultural activities. Finally, we estimated an average emission of CO2 from the Nile Delta from 2014–2019 of 470 Mt CO2/year, about 1% of global anthropogenic emissions, which is significantly more than estimated hitherto.
    Michael Neuder, Daniel J. Moroz, Rithvik Rao, and David C. Parkes. 4/8/2020. “Selfish Behavior in the Tezos Proof-of-Stake Protocol.” Cryptoeconomic Systems (CES) Conference 4/8/2020. Publisher's VersionAbstract
    Proof-of-Stake consensus protocols give rise to complex mod- eling challenges. We analyze the Babylon update (October 2019) to the Proof-of-Stake protocol on the Tezos blockchain, and demonstrate that, under certain conditions, rational partic- ipants are incentivized to behave dishonestly. In doing so, we provide a theoretical analysis of the feasibility and profitabil- ity of a block stealing attack that we call selfish endorsing, a concrete instance of an attack previously only theoretically considered. We propose and analyze a simple change to the Tezos protocol which significantly reduces the (already small) profitability of this dishonest behavior, and introduce a new de- lay and reward scheme that is provably secure against length-1 and length-2 selfish endorsing attacks. Our framework pro- vides a template for analyzing other Proof-of-Stake protocols for the possibility of selfish behavior.
    Anurag Anshu. 4/6/2020. “Improved local spectral gap thresholds for lattices of finite dimension.” Physical Review B, 101, 16. Publisher's VersionAbstract
    Knabe's theorem lower bounds the spectral gap of a one-dimensional frustration-free local Hamiltonian in terms of the local spectral gaps of finite regions. It also provides a local spectral gap threshold for Hamiltonians that are gapless in the thermodynamic limit, showing that the local spectral gap must scale inverse linearly with the length of the region for such systems. Recent works have further improved upon this threshold, tightening it in the one-dimensional case and extending it to higher dimensions. Here, we show a local spectral gap threshold for frustration-free Hamiltonians on a finite-dimensional lattice that is optimal up to a constant factor that depends on the dimension of the lattice. Our proof is based on the detectability lemma framework and uses the notion of a coarse-grained Hamiltonian (introduced in [Anshu et al., Phys. Rev. B 93, 205142]) as a link connecting the (global) spectral gap and the local spectral gap.
    Joshua B. Fisher, Brian Lee, Adam J. Purdy, Gregory H. Halverson, Matthew B. Dohlen, Kerry Cawse-Nicholson, Audrey Wang, Ray G. Anderson, Bruno Aragon, M. Altaf Arain, Dennis D. Baldocchi, John M. Baker, Hélène Barral, Carl J. Bernacchi, Christian Bernhofer, Sébastien C. Biraud, Gil Bohrer, Nathaniel Brunsell, Bernard Cappelaere, Saulo Castro-Contreras, Junghwa Chun, Bryan J. Conrad, Edoardo Cremonese, Jérôme Demarty, Ankur R. Desai, Anne De Ligne, Lenka Foltýnová, Michael L. Goulden, Timothy J. Griffis, Thomas Grünwald, Mark S. Johnson, Minseok Kang, Dave Kelbe, Natalia Kowalska, Jong-Hwan Lim, Ibrahim Maïnassara, Matthew F. McCabe, Justine E.C. Missik, Binayak P. Mohanty, Caitlin E. Moore, Laura Morillas, Ross Morrison, J. William Munger, Gabriela Posse, Andrew D. Richardson, Eric S. Russell, Youngryel Ryu, Arturo Sanchez-Azofeifa, Marius Schmidt, Efrat Schwartz, Iain Sharp, Ladislav Šigut, Yao Tang, Glynn Hulley, Martha Anderson, Christopher Hain, Andrew French, Eric Wood, and Simon Hook. 4/6/2020. “ECOSTRESS: NASA's Next Generation Mission to Measure Evapotranspiration From the International Space Station.” Water Resources Research, 56, 4, Pp. e2019WR026058. Publisher's VersionAbstract
    The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) was launched to the International Space Station on 29 June 2018 by the National Aeronautics and Space Administration (NASA). The primary science focus of ECOSTRESS is centered on evapotranspiration (ET), which is produced as Level-3 (L3) latent heat flux (LE) data products. These data are generated from the Level-2 land surface temperature and emissivity product (L2_LSTE), in conjunction with ancillary surface and atmospheric data. Here, we provide the first validation (Stage 1, preliminary) of the global ECOSTRESS clear-sky ET product (L3_ET_PT-JPL, Version 6.0) against LE measurements at 82 eddy covariance sites around the world. Overall, the ECOSTRESS ET product performs well against the site measurements (clear-sky instantaneous/time of overpass: r2 = 0.88; overall bias = 8%; normalized root-mean-square error, RMSE = 6%). ET uncertainty was generally consistent across climate zones, biome types, and times of day (ECOSTRESS samples the diurnal cycle), though temperate sites are overrepresented. The 70-m-high spatial resolution of ECOSTRESS improved correlations by 85%, and RMSE by 62%, relative to 1-km pixels. This paper serves as a reference for the ECOSTRESS L3 ET accuracy and Stage 1 validation status for subsequent science that follows using these data.

Pages