Commuter Mobility Patterns in Social Media: Correlating Twitter and LODES Data

The Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics (LODES) are an important city planning resource in the USA. However, curating these statistics is resource-intensive, and their accuracy deteriorates when changes in population and urban structures lead to shifts in commuter patterns. Our study area is the San Francisco Bay area, and it has seen rapid population growth over the past years, which makes frequent updates to LODES or the availability of an appropriate substitute desirable. In this paper, we derive mobility flows from a set of over 40 million georeferenced tweets of the study area and compare them with LODES data. These tweets are publicly available and offer fine spatial and temporal resolution. Based on an exploratory analysis of the Twitter data, we pose research questions addressing different aspects of the integration of LODES and Twitter data. Furthermore, we develop methods for their comparative analysis on different spatial scales: at the county, census tract, census block, and individual street segment level. We thereby show that Twitter data can be used to approximate LODES on the county level and on the street segment level, but it also contains information about non-commuting-related regular travel. Leveraging Twitter’s high temporal resolution, we also show how factors like rush hour times and weekends impact mobility. We discuss the merits and shortcomings of the different methods for use in urban planning and close with directions for future research avenues.

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Multimodal in vivo recording using transparent graphene microelectrodes illuminates spatiotemporal seizure dynamics at the microscale

Communications Biology ◽

10.1038/s42003-021-01670-9 ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Nicolette Driscoll ◽

Richard E. Rosch ◽

Brendan B. Murphy ◽

Arian Ashourvan ◽

Ramya Vishnubhotla ◽

...

Keyword(s):

Temporal Resolution ◽

Spatial Scales ◽

Epileptic Seizures ◽

Therapeutic Interventions ◽

State Transitions ◽

Integrated Analysis ◽

High Temporal Resolution ◽

Seizure Onset ◽

Acute Seizures

AbstractNeurological disorders such as epilepsy arise from disrupted brain networks. Our capacity to treat these disorders is limited by our inability to map these networks at sufficient temporal and spatial scales to target interventions. Current best techniques either sample broad areas at low temporal resolution (e.g. calcium imaging) or record from discrete regions at high temporal resolution (e.g. electrophysiology). This limitation hampers our ability to understand and intervene in aberrations of network dynamics. Here we present a technique to map the onset and spatiotemporal spread of acute epileptic seizures in vivo by simultaneously recording high bandwidth microelectrocorticography and calcium fluorescence using transparent graphene microelectrode arrays. We integrate dynamic data features from both modalities using non-negative matrix factorization to identify sequential spatiotemporal patterns of seizure onset and evolution, revealing how the temporal progression of ictal electrophysiology is linked to the spatial evolution of the recruited seizure core. This integrated analysis of multimodal data reveals otherwise hidden state transitions in the spatial and temporal progression of acute seizures. The techniques demonstrated here may enable future targeted therapeutic interventions and novel spatially embedded models of local circuit dynamics during seizure onset and evolution.

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DSCOVR/EPIC-derived global hourly and daily downward shortwave and photosynthetically active radiation data at 0.1° × 0.1° resolution

Earth System Science Data ◽

10.5194/essd-12-2209-2020 ◽

2020 ◽

Vol 12 (3) ◽

pp. 2209-2221

Author(s):

Dalei Hao ◽

Ghassem R. Asrar ◽

Yelu Zeng ◽

Qing Zhu ◽

Jianguang Wen ◽

...

Keyword(s):

Temporal Resolution ◽

Photosynthetically Active Radiation ◽

Spatial Scales ◽

Radiant Energy ◽

Surface Radiation ◽

Radiation Budget ◽

High Temporal Resolution ◽

Active Radiation ◽

Global Coverage ◽

Mean Square Errors

Abstract. Downward shortwave radiation (SW) and photosynthetically active radiation (PAR) play crucial roles in Earth system dynamics. Spaceborne remote sensing techniques provide a unique means for mapping accurate spatiotemporally continuous SW–PAR, globally. However, any individual polar-orbiting or geostationary satellite cannot satisfy the desired high temporal resolution (sub-daily) and global coverage simultaneously, while integrating and fusing multisource data from complementary satellites/sensors is challenging because of co-registration, intercalibration, near real-time data delivery and the effects of discrepancies in orbital geometry. The Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR), launched in February 2015, offers an unprecedented possibility to bridge the gap between high temporal resolution and global coverage and characterize the diurnal cycles of SW–PAR globally. In this study, we adopted a suite of well-validated data-driven machine-learning models to generate the first global land products of SW–PAR, from June 2015 to June 2019, based on DSCOVR/EPIC data. The derived products have high temporal resolution (hourly) and medium spatial resolution (0.1∘×0.1∘), and they include estimates of the direct and diffuse components of SW–PAR. We used independently widely distributed ground station data from the Baseline Surface Radiation Network (BSRN), the Surface Radiation Budget Network (SURFRAD), NOAA's Global Monitoring Division and the U.S. Department of Energy's Atmospheric System Research (ASR) program to evaluate the performance of our products, and we further analyzed and compared the spatiotemporal characteristics of the derived products with the benchmarking Clouds and the Earth's Radiant Energy System Synoptic (CERES) data. We found both the hourly and daily products to be consistent with ground-based observations (e.g., hourly and daily total SWs have low biases of −3.96 and −0.71 W m−2 and root-mean-square errors (RMSEs) of 103.50 and 35.40 W m−2, respectively). The developed products capture the complex spatiotemporal patterns well and accurately track substantial diurnal, monthly, and seasonal variations in SW–PAR when compared to CERES data. They provide a reliable and valuable alternative for solar photovoltaic applications worldwide and can be used to improve our understanding of the diurnal and seasonal variabilities of the terrestrial water, carbon and energy fluxes at various spatial scales. The products are freely available at https://doi.org/10.25584/1595069 (Hao et al., 2020).

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Comparison of Landsat and Land-Based Phenology Camera Normalized Difference Vegetation Index (NDVI) for Dominant Plant Communities in the Great Basin

Sensors ◽

10.3390/s19051139 ◽

2019 ◽

Vol 19 (5) ◽

pp. 1139 ◽

Cited By ~ 4

Author(s):

Keirith Snyder ◽

Justin Huntington ◽

Bryce Wehan ◽

Charles Morton ◽

Tamzen Stringham

Keyword(s):

Great Basin ◽

Plant Communities ◽

Spatial Resolution ◽

Temporal Resolution ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Spatial Scales ◽

Plant Phenology ◽

High Temporal Resolution ◽

Spatial Coverage

Phenology of plants is important for ecological interactions. The timing and development of green leaves, plant maturity, and senescence affects biophysical interactions of plants with the environment. In this study we explored the agreement between land-based camera and satellite-based phenology metrics to quantify plant phenology and phenophases dates in five plant community types characteristic of the semi-arid cold desert region of the Great Basin. Three years of data were analyzed. We calculated the Normalized Difference Vegetation Index (NDVI) for both land-based cameras (i.e., phenocams) and Landsat imagery. NDVI from camera images was calculated by taking a standard RGB (red, green, and blue) image and then a near infrared (NIR) plus RGB image. Phenocam NDVI was calculated by extracting the red digital number (DN) and the NIR DN from images taken a few seconds apart. Landsat has a spatial resolution of 30 m2, while phenocam spatial resolution can be analyzed at the single pixel level at the scale of cm2 or area averaged regions can be analyzed with scales up to 1 km2. For this study, phenocam regions of interest were used that approximated the scale of at least one Landsat pixel. In the tall-statured pinyon and juniper woodland sites, there was a lack of agreement in NDVI between phenocam and Landsat NDVI, even after using National Agricultural Imagery Program (NAIP) imagery to account for fractional coverage of pinyon and juniper versus interspace in the phenocam data. Landsat NDVI appeared to be dominated by the signal from the interspace and was insensitive to subtle changes in the pinyon and juniper tree canopy. However, for short-statured sagebrush shrub and meadow communities, there was good agreement between the phenocam and Landsat NDVI as reflected in high Pearson’s correlation coefficients (r > 0.75). Due to greater temporal resolution of the phenocams with images taken daily, versus the 16-day return interval of Landsat, phenocam data provided more utility in determining important phenophase dates: start of season, peak of season, and end of season. More specific species-level information can be obtained with the high temporal resolution of phenocams, but only for a limited number of sites, while Landsat can provide the multi-decadal history and spatial coverage that is unmatched by other platforms. The agreement between Landsat and phenocam NDVI for short-statured plant communities of the Great Basin, shows promise for monitoring landscape and regional-level plant phenology across large areas and time periods, with phenocams providing a more comprehensive understanding of plant phenology at finer spatial scales, and Landsat extending the historical record of observations.

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Inverting for volcanic SO2 flux at high temporal resolution using spaceborne plume imagery and chemistry-transport modelling: the 2010 Eyjafjallajökull eruption case study

Atmospheric Chemistry and Physics ◽

10.5194/acp-13-8569-2013 ◽

2013 ◽

Vol 13 (17) ◽

pp. 8569-8584 ◽

Cited By ~ 33

Author(s):

M. Boichu ◽

L. Menut ◽

D. Khvorostyanov ◽

L. Clarisse ◽

C. Clerbaux ◽

...

Keyword(s):

Temporal Resolution ◽

Spatial Scales ◽

Source Parameters ◽

Volcanic Plume ◽

High Temporal Resolution ◽

Transport Modelling ◽

Important Indicator ◽

So2 Flux ◽

Volcanic Source

Abstract. Depending on the magnitude of their eruptions, volcanoes impact the atmosphere at various temporal and spatial scales. The volcanic source remains a major unknown to rigorously assess these impacts. At the scale of an eruption, the limited knowledge of source parameters, including time variations of erupted mass flux and emission profile, currently represents the greatest issue that limits the reliability of volcanic cloud forecasts. Today, a growing number of satellite and remote sensing observations of distant plumes are becoming available, bringing indirect information on these source terms. Here, we develop an inverse modelling approach combining satellite observations of the volcanic plume with an Eulerian regional chemistry-transport model (CHIMERE) to characterise the volcanic SO2 emissions during an eruptive crisis. The May 2010 eruption of Eyjafjallajökull is a perfect case study to apply this method as the volcano emitted substantial amounts of SO2 during more than a month. We take advantage of the SO2 column amounts provided by a vast set of IASI (Infrared Atmospheric Sounding Interferometer) satellite images to reconstruct retrospectively the time series of the mid-tropospheric SO2 flux emitted by the volcano with a temporal resolution of ~2 h, spanning the period from 1 to 12 May 2010. We show that no a priori knowledge on the SO2 flux is required for this reconstruction. The initialisation of chemistry-transport modelling with this reconstructed source allows for reliable simulation of the evolution of the long-lived tropospheric SO2 cloud over thousands of kilometres. Heterogeneities within the plume, which mainly result from the temporal variability of the emissions, are correctly tracked over a timescale of a week. The robustness of our approach is also demonstrated by the broad similarities between the SO2 flux history determined by this study and the ash discharge behaviour estimated by other means during the phases of high explosive activity at Eyjafjallajökull in May 2010. Finally, we show how a sequential IASI data assimilation allows for a substantial improvement in the forecasts of the location and concentration of the plume compared to an approach assuming constant flux at the source. As the SO2 flux is an important indicator of the volcanic activity, this approach is also of interest to monitor poorly instrumented volcanoes from space.

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Inverting for volcanic SO<sub>2</sub> flux at high temporal resolution using spaceborne plume imagery and chemistry-transport modelling: the 2010 Eyjafjallajökull eruption case-study

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-13-6553-2013 ◽

2013 ◽

Vol 13 (3) ◽

pp. 6553-6588 ◽

Cited By ~ 3

Author(s):

M. Boichu ◽

L. Menut ◽

D. Khvorostyanov ◽

L. Clarisse ◽

C. Clerbaux ◽

...

Keyword(s):

Temporal Resolution ◽

Spatial Scales ◽

Source Parameters ◽

Volcanic Plume ◽

High Temporal Resolution ◽

Transport Modelling ◽

Important Indicator ◽

So2 Flux ◽

Volcanic Source

Abstract. Depending on the magnitude of their eruptions, volcanoes impact the atmosphere at various temporal and spatial scales. The volcanic source remains a major unknown to rigorously assess these impacts. At the scale of an eruption, the limited knowledge of source parameters, including time-variations of erupted mass flux and emission profile, currently represents the greatest issue that limits the reliability of volcanic cloud forecasts. Today, a growing number of satellite and remote sensing observations of distant plumes are becoming available, bringing indirect information on these source terms. Here, we develop an inverse modeling approach combining satellite observations of the volcanic plume with an Eulerian regional chemistry-transport model (CHIMERE) to better characterise the volcanic SO2 emissions during an eruptive crisis. The May 2010 eruption of Eyjafjallajökull is a perfect case-study to apply this method as the volcano emitted substantial amounts of SO2 during more than a month. We take advantage of the SO2 column amounts provided by a vast set of IASI (Infrared Atmospheric Sounding Interferometer) satellite images to reconstruct retrospectively the time-series of the mid-tropospheric SO2 flux emitted by the volcano with a temporal resolution of ~2 h, spanning the period from 1 to 12 May 2010. The initialisation of chemistry-transport modelling with this reconstructed source allows for a reliable simulation of the evolution of the long-lived tropospheric SO2 cloud over thousands of kilometres. Heterogeneities within the plume, which mainly result from the temporal variability of the emissions, are correctly tracked over a time scale of a week. The robustness of our approach is also demonstrated by the broad similarities between the SO2 flux history determined by this study and the ash discharge behaviour estimated by other means during the phases of high explosive activity at Eyjafjallajökull in May 2010. Finally, we show how a sequential IASI data assimilation allows for a substantial improvement in the forecasts of the location and concentration of the plume compared to an approach assuming constant flux at the source. As the SO2 flux is an important indicator of the volcanic activity, this approach is also of interest to monitor poorly instrumented volcanoes from space.

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DSCOVR/EPIC-derived global hourly/daily downward shortwave and photosynthetically active radiation data at 0.1° × 0.1° resolution

10.5194/essd-2020-19 ◽

2020 ◽

Author(s):

Dalei Hao ◽

Ghassem R. Asrar ◽

Yelu Zeng ◽

Qing Zhu ◽

Jianguang Wen ◽

...

Keyword(s):

Temporal Resolution ◽

Photosynthetically Active Radiation ◽

Spatial Scales ◽

Surface Radiation ◽

Radiation Budget ◽

High Temporal Resolution ◽

Active Radiation ◽

Global Coverage ◽

Spatio Temporal ◽

Mean Square Errors

Abstract. Downward shortwave radiation (SW) and photosynthetically active radiation (PAR) play crucial roles in Earth system dynamics. Spaceborne remote sensing techniques provide a unique means for mapping accurate spatio-temporally-continuous SW/PAR, globally. However, any individual polar-orbiting or geostationary satellite cannot satisfy the desired high temporal resolution (sub-daily) and global coverage simultaneously, while integrating and fusing multi-source data from complementary satellites/sensors is challenging because of co-registration, inter-calibration, near real-time data delivery and the effects of discrepancies in orbital geometry. The Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR), launched in February 2015, offers an unprecedented possibility to bridge the gap between high temporal resolution and global coverage, and characterize the diurnal cycles of SW/PAR globally. In this study, we adopted a suite of well-validated data-driven machine-learning models to generate the first global land products of SW/PAR, from June 2015 to June 2019, based on DSCOVR/EPIC data. The derived products have high temporal resolution (hourly) and medium spatial resolution (0.1° × 0.1°), and include estimates of the direct and diffuse components of SW/PAR. We used independently widely-distributed ground station data from the Baseline Surface Radiation Network (BSRN), the Surface Radiation Budget Network (SURFRAD), NOAA's Global Monitoring Division and the U.S. Department of Energy’s Atmospheric System Research (ASR) program to evaluate the performance of our products, and further analyzed and compared the spatio-temporal characteristics of the derived products with the benchmarking Clouds and the Earth's Radiant Energy System Synoptic (CERES) data. We found both the hourly and daily products to be consistent with ground-based observations (e.g., hourly and daily total SWs have low biases of −3.96 and −0.71 W/m2 and root mean square errors (RMSEs) of 103.50 and 35.40 W/m2, respectively). The developed products capture the complex spatio-temporal patterns well and accurately track substantial diurnal, monthly, and seasonal variations of SW/PAR when compared to CERES data. They provide a reliable and valuable alternative for solar photovoltaic applications worldwide and can be used to improve our understanding of the diurnal and seasonal variabilities of the terrestrial water, carbon and energy fluxes at various spatial scales. The products are freely available at https://doi.org/10.25584/1595069 (Hao et al., 2020).

Download Full-text

Multimodal in vivo recording using transparent graphene microelectrodes illuminates spatiotemporal seizure dynamics at the microscale

10.1101/2020.06.04.134189 ◽

2020 ◽

Author(s):

Nicolette Driscoll ◽

Richard Rosch ◽

Brendan B. Murphy ◽

Arian Ashourvan ◽

Ramya Vishnubhotla ◽

...

Keyword(s):

Temporal Resolution ◽

Spatial Scales ◽

Epileptic Seizures ◽

Therapeutic Interventions ◽

State Transitions ◽

Integrated Analysis ◽

High Temporal Resolution ◽

Seizure Onset ◽

Acute Seizures

Neurological disorders such as epilepsy arise from disrupted brain networks. Our capacity to treat these disorders is limited by our inability to map these networks at sufficient temporal and spatial scales to target interventions. Current best techniques either sample broad areas at low temporal resolution (e.g. calcium imaging) or record from discrete regions at high temporal resolution (e.g. electrophysiology). This limitation hampers our ability to understand and intervene in aberrations of network dynamics. Here we present a technique to map the onset and spatiotemporal spread of acute epileptic seizures in vivo by simultaneously recording high bandwidth microelectrocorticography and calcium fluorescence using transparent graphene microelectrode arrays. We integrate dynamic data features from both modalities using non-negative matrix factorization to identify sequential spatiotemporal patterns of seizure onset and evolution, revealing how the temporal progression of ictal electrophysiology is linked to the spatial evolution of the recruited seizure core. This integrated analysis of multimodal data reveals otherwise hidden state transitions in the spatial and temporal progression of acute seizures. The techniques demonstrated here may enable future targeted therapeutic interventions and novel spatially embedded models of local circuit dynamics during seizure onset and evolution.

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Exploring the Electrophysiological Correlates of Encoding Retractions of Misinformation

10.31234/osf.io/e2zaq ◽

2018 ◽

Author(s):

Christopher Brydges ◽

Andrew Gordon ◽

Ullrich K. H. Ecker

Keyword(s):

Temporal Resolution ◽

Event Related Potential ◽

Future Research ◽

High Temporal Resolution ◽

Memory Encoding ◽

Bayesian Analyses ◽

Neural Processes ◽

Behavioural Research ◽

Corrective Information ◽

With Memory

A plethora of behavioural research has suggested that the successful encoding of retracting information is required to minimise the lingering effects of misinformation. However, neuroscientific research in this area is much scarcer. Participants (n = 34) completed a typical continued-influence misinformation paradigm whilst electroencephalographic data were recorded. Two event-related potential (ERP) components associated with memory encoding and updating (a left-frontal positivity and the parietal P3b) were examined when participants processed misinformation retractions in comparison to when no misinformation was presented. Neither frequentist nor Bayesian analyses found differences between ERP amplitudes elicited by retractions and non-retractions. It is plausible that misinformation removal and the integration of corrective information are not temporally reliable across trials, resulting in suppressed amplitude in the ERP. Nonetheless, the high temporal resolution of ERPs may still be able to provide an informative perspective on the neural processes of misinformation processing in future research.

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Electrochemical measurement of acetylcholine in the dorsolateral prefrontal cortex: A technical report

10.1101/120691 ◽

2017 ◽

Cited By ~ 1

Author(s):

Devavrat Vartak ◽

Chris van der Togt ◽

Bram van Vugt ◽

Pieter R. Roelfsema

Keyword(s):

Prefrontal Cortex ◽

Temporal Resolution ◽

Dorsolateral Prefrontal Cortex ◽

High Sensitivity ◽

Electrochemical Measurement ◽

Model Systems ◽

Future Research ◽

High Temporal Resolution ◽

Dorsolateral Prefrontal

AbstractEver since the discovery of acetylcholine in 1913, its role as neuromodulator has been extensively studied in a variety of model systems. These previous studies revealed that acetylcholine is of critical importance for several cognitive functions including attention, learning and memory. In spite of these previous findings, it has proven difficult to determine the amount of acetylcholine that is released during cognitive tasks with sub-second temporal resolution. One method that might be used to measure acetylcholine release is the use of an enzyme-coupled amperometric sensor, which has been suggested to measure acetylcholine with high sensitivity, selectivity and relatively high temporal resolution (< 1 second). In the present study, we have tried to adapt the technique developed in the rodent model system by Parikh and colleagues1,2 for use in non-human primates. We aimed to measure in-vivo levels of acetylcholine in the macaque dorsolateral prefrontal cortex while the monkey performed an attention demanding curve-tracing task3,4. We report that our attempts to measure acetylcholine using amperometry in an awake behaving macaque monkey proved difficult and tedious and that our results are inconsistent and prone to noise. In the discussion, we will outline the challenges that will need to be addressed to use this technique in non-human primates and hope that our observations inspire solutions to help future research on the role of this important neurotransmitter.

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