A Quantitative Validation of Multi-Modal Image Fusion and Segmentation for Object Detection and Tracking

In previous works, we have shown the efficacy of using Deep Belief Networks, paired with clustering, to identify distinct classes of objects within remotely sensed data via cluster analysis and qualitative analysis of the output data in comparison with reference data. In this paper, we quantitatively validate the methodology against datasets currently being generated and used within the remote sensing community, as well as show the capabilities and benefits of the data fusion methodologies used. The experiments run take the output of our unsupervised fusion and segmentation methodology and map them to various labeled datasets at different levels of global coverage and granularity in order to test our models’ capabilities to represent structure at finer and broader scales, using many different kinds of instrumentation, that can be fused when applicable. In all cases tested, our models show a strong ability to segment the objects within input scenes, use multiple datasets fused together where appropriate to improve results, and, at times, outperform the pre-existing datasets. The success here will allow this methodology to be used within use concrete cases and become the basis for future dynamic object tracking across datasets from various remote sensing instruments

Airborne methane remote measurements reveal heavy-tail flux distribution in Four Corners region

Methane (CH_4) impacts climate as the second strongest anthropogenic greenhouse gas and air quality by influencing tropospheric ozone levels. Space-based observations have identified the Four Corners region in the Southwest United States as an area of large CH_4 enhancements. We conducted an airborne campaign in Four Corners during April 2015 with the next-generation Airborne Visible/Infrared Imaging Spectrometer (near-infrared) and Hyperspectral Thermal Emission Spectrometer (thermal infrared) imaging spectrometers to better understand the source of methane by measuring methane plumes at 1- to 3-m spatial resolution. Our analysis detected more than 250 individual methane plumes from fossil fuel harvesting, processing, and distributing infrastructures, spanning an emission range from the detection limit ∼2 kg/h to 5 kg/h through ∼5,000 kg/h. Observed sources include gas processing facilities, storage tanks, pipeline leaks, and well pads, as well as a coal mine venting shaft. Overall, plume enhancements and inferred fluxes follow a lognormal distribution, with the top 10% emitters contributing 49 to 66% to the inferred total point source flux of 0.23 Tg/y to 0.39 Tg/y. With the observed confirmation of a lognormal emission distribution, this airborne observing strategy and its ability to locate previously unknown point sources in real time provides an efficient and effective method to identify and mitigate major emissions contributors over a wide geographic area. With improved instrumentation, this capability scales to spaceborne applications [Thompson DR, et al. (2016) Geophys Res Lett 43(12):6571–6578]. Further illustration of this potential is demonstrated with two detected, confirmed, and repaired pipeline leaks during the campaign

SN2002es-like Supernovae from Different Viewing Angles

In this article, we compare optical light curves of two SN2002es-like Type Ia supernovae (SNe), iPTF14atg and iPTF14dpk, from the intermediate Palomar Transient Factory. Although the two light curves resemble each other around and after maximum, they show distinct early-phase rise behavior in the r-band. On the one hand, iPTF14atg revealed a slow and steady rise that lasted for 22 days with a mean rise rate of 0.2–0.3 mag day^(-1), before it reached the R-band peak (−18.05 mag). On the other hand, iPTF14dpk rose rapidly to −17 mag within a day of discovery with a rise rate > 1.8 mag day^(-1) , and then rose slowly to its peak (−18.19 mag) with a rise rate similar to iPTF14atg. The apparent total rise time of iPTF14dpk is therefore only 16 days. We show that emission from iPTF14atg before −17 days with respect to its maximum can be entirely attributed to radiation produced by collision between the SN and its companion star. Such emission is absent from iPTF14dpk probably because of an unfavored viewing angle, provided that SN2002es-like events arise from the same progenitor channel. We further show that an SN2002es-like SN may experience a dark phase after the explosion but before its radioactively powered light curve becomes visible. This dark phase may be lit by radiation from supernova–companion interaction

Absence of Fast-moving Iron in an Intermediate Type Ia Supernova between Normal and Super-Chandrasekhar

In this paper, we report observations of a peculiar SN Ia iPTF13asv (a.k.a., SN2013cv) from the onset of the explosion to months after its peak. The early-phase spectra of iPTF13asv show an absence of iron absorption, indicating that synthesized iron elements are confined to low-velocity regions of the ejecta, which, in turn, implies a stratified ejecta structure along the line of sight. Our analysis of iPTF13asv's light curves and spectra shows that it is an intermediate case between normal and super-Chandrasekhar events. On the one hand, its light curve shape (B-band Δm_(15) = 1.03 ± 0.01) and overall spectral features resemble those of normal SNe Ia. On the other hand, its large peak optical and UV luminosity (M_B = -19.84 mag, M_(uvm2) = -15.5 mag) and its low but almost constant Si II velocities of about 10,000 km s^(−1) are similar to those in super-Chandrasekhar events, and its persistent carbon signatures in the spectra are weaker than those seen commonly in super-Chandrasekhar events. We estimate a ^(56)Ni mass of 0.81 ± ^(+0.10)_(-0.18) M⊙ and a total ejecta mass of 1.59^(+0.45)_(-0.12)M⊙. The large ejecta mass of iPTF13asv and its stratified ejecta structure together seemingly favor a double-degenerate origin

California’s methane super-emitters

Methane is a powerful greenhouse gas and is targeted for emissions mitigation by the US state of California and other jurisdictions worldwide. Unique opportunities for mitigation are presented by point-source emitters—surface features or infrastructure components that are typically less than 10 metres in diameter and emit plumes of highly concentrated methane. However, data on point-source emissions are sparse and typically lack sufficient spatial and temporal resolution to guide their mitigation and to accurately assess their magnitude4. Here we survey more than 272,000 infrastructure elements in California using an airborne imaging spectrometer that can rapidly map methane plumes. We conduct five campaigns over several months from 2016 to 2018, spanning the oil and gas, manure-management and waste-management sectors, resulting in the detection, geolocation and quantification of emissions from 564 strong methane point sources. Our remote sensing approach enables the rapid and repeated assessment of large areas at high spatial resolution for a poorly characterized population of methane emitters that often appear intermittently and stochastically. We estimate net methane point-source emissions in California to be 0.618 teragrams per year (95 per cent confidence interval 0.523–0.725), equivalent to 34–46 per cent of the state’s methane inventory for 2016. Methane ‘super-emitter’ activity occurs in every sector surveyed, with 10 per cent of point sources contributing roughly 60 per cent of point-source emissions—consistent with a study of the US Four Corners region that had a different sectoral mix. The largest methane emitters in California are a subset of landfills, which exhibit persistent anomalous activity. Methane point-source emissions in California are dominated by landfills (41 per cent), followed by dairies (26 per cent) and the oil and gas sector (26 per cent). Our data have enabled the identification of the 0.2 per cent of California’s infrastructure that is responsible for these emissions. Sharing these data with collaborating infrastructure operators has led to the mitigation of anomalous methane-emission activity

Methane emissions from underground gas storage in California

Accurate and timely detection, quantification, and attribution of methane emissions from Underground Gas Storage (UGS) facilities is essential for improving confidence in greenhouse gas inventories, enabling emission mitigation by facility operators, and supporting efforts to assess facility integrity and safety. We conducted multiple airborne surveys of the 12 active UGS facilities in California between January 2016 and November 2017 using advanced remote sensing and in situ observations of near-surface atmospheric methane (CH₄). These measurements where combined with wind data to derive spatially and temporally resolved methane emission estimates for California UGS facilities and key components with spatial resolutions as small as 1–3 m and revisit intervals ranging from minutes to months. The study spanned normal operations, malfunctions, and maintenance activity from multiple facilities including the active phase of the Aliso Canyon blowout incident in 2016 and subsequent return to injection operations in summer 2017. We estimate that the net annual methane emissions from the UGS sector in California averaged between 11.0 ± 3.8 GgCH₄ yr⁻¹ (remote sensing) and 12.3 ± 3.8 GgCH₄ yr⁻¹ (in situ). Net annual methane emissions for the 7 facilities that reported emissions in 2016 were estimated between 9.0 ± 3.2 GgCH₄ yr⁻¹ (remote sensing) and 9.5 ± 3.2 GgCH₄ yr⁻¹ (in situ), in both cases around 5 times higher than reported. The majority of methane emissions from UGS facilities in this study are likely dominated by anomalous activity: higher than expected compressor loss and leaking bypass isolation valves. Significant variability was observed at different time-scales: daily compressor duty-cycles and infrequent but large emissions from compressor station blow-downs. This observed variability made comparison of remote sensing and in situ observations challenging given measurements were derived largely at different times, however, improved agreement occurred when comparing simultaneous measurements. Temporal variability in emissions remains one of the most challenging aspects of UGS emissions quantification, underscoring the need for more systematic and persistent methane monitoring

Strong Ultraviolet Pulse From a Newborn Type Ia Supernova

Type Ia supernovae are destructive explosions of carbon oxygen white dwarfs. Although they are used empirically to measure cosmological distances, the nature of their progenitors remains mysterious, One of the leading progenitor models, called the single degenerate channel, hypothesizes that a white dwarf accretes matter from a companion star and the resulting increase in its central pressure and temperature ignites thermonuclear explosion. Here we report observations of strong but declining ultraviolet emission from a Type Ia supernova within four days of its explosion. This emission is consistent with theoretical expectations of collision between material ejected by the supernova and a companion star, and therefore provides evidence that some Type Ia supernovae arise from the single degenerate channel.Comment: Accepted for publication on the 21 May 2015 issue of Natur

Airborne methane remote measurements reveal heavy-tail flux distribution in Four Corners region

Methane (CH_4) impacts climate as the second strongest anthropogenic greenhouse gas and air quality by influencing tropospheric ozone levels. Space-based observations have identified the Four Corners region in the Southwest United States as an area of large CH_4 enhancements. We conducted an airborne campaign in Four Corners during April 2015 with the next-generation Airborne Visible/Infrared Imaging Spectrometer (near-infrared) and Hyperspectral Thermal Emission Spectrometer (thermal infrared) imaging spectrometers to better understand the source of methane by measuring methane plumes at 1- to 3-m spatial resolution. Our analysis detected more than 250 individual methane plumes from fossil fuel harvesting, processing, and distributing infrastructures, spanning an emission range from the detection limit ∼2 kg/h to 5 kg/h through ∼5,000 kg/h. Observed sources include gas processing facilities, storage tanks, pipeline leaks, and well pads, as well as a coal mine venting shaft. Overall, plume enhancements and inferred fluxes follow a lognormal distribution, with the top 10% emitters contributing 49 to 66% to the inferred total point source flux of 0.23 Tg/y to 0.39 Tg/y. With the observed confirmation of a lognormal emission distribution, this airborne observing strategy and its ability to locate previously unknown point sources in real time provides an efficient and effective method to identify and mitigate major emissions contributors over a wide geographic area. With improved instrumentation, this capability scales to spaceborne applications [Thompson DR, et al. (2016) Geophys Res Lett 43(12):6571–6578]. Further illustration of this potential is demonstrated with two detected, confirmed, and repaired pipeline leaks during the campaign