remote sensing

Article Methane Mapping with Future Satellite Imaging Spectrometers

Alana K. Ayasse 1,*, Philip E. Dennison 2 , Markus Foote 4 , Andrew K. Thorpe 3, Sarang Joshi 4, Robert O. Green 3, Riley M. Duren 3,5, David R. Thompson 3 and Dar A. Roberts 1 1 Department of Geography, University of California Santa Barbara, Santa Barbara, CA 93106, USA; [email protected] 2 Department of Geography, University of Utah, Salt Lake City, UT 84112, USA; [email protected] 3 Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA; Andrew.K.Thorpe@jpl.nasa.gov (A.K.T.); [email protected] (R.O.G.); [email protected] (R.M.D.); [email protected] (D.R.T.) 4 Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT 84112, USA; [email protected] (M.F.); [email protected] (S.J.) 5 Office for Research, Innovation and Impact, University of Arizona, Tucson, AZ 85721, USA * Correspondence: [email protected]



Received: 14 November 2019; Accepted: 13 December 2019; Published: 17 December 2019


Abstract: This study evaluates a new generation of satellite imaging spectrometers to measure point source methane emissions from anthropogenic sources. We used the Airborne Visible and Infrared Imaging Spectrometer Next Generation(AVIRIS-NG) images with known methane plumes to create two simulated satellite products. One simulation had a 30 m spatial resolution with ~200 Signal-to-Noise Ratio (SNR) in the Shortwave Infrared (SWIR) and the other had a 60 m spatial resolution with ~400 SNR in the SWIR; both products had a 7.5 nm spectral spacing. We applied a linear matched filter with a sparsity prior and an albedo correction to detect and quantify the methane emission in the original AVIRIS-NG images and in both satellite simulations. We also calculated an emission flux for all images. We found that all methane plumes were detectable in all satellite simulations. The flux calculations for the simulated satellite images correlated well with the calculated flux for the original AVIRIS-NG images. We also found that coarsening spatial resolution had the largest impact on the sensitivity of the results. These results suggest that methane detection and quantification of point sources will be possible with the next generation of satellite imaging spectrometers.

Keywords: methane; imaging spectrometer; hyperspectral; gas plumes; satellite; EMIT; AVIRIS-NG; matched filter; remote sensing

1. Introduction Methane is a prominent greenhouse gas and is responsible for about 20% of all atmospheric radiative forcing [1,2]. As our planet continues to warm due to radiative forcing caused by greenhouse gases, understanding, monitoring, and reducing these emissions will become increasingly important. However, there remains a high level of uncertainty regarding the magnitude of methane sources and sinks globally [2,3]. Anthropogenic sources, which make up 50–65% of all methane emissions, mostly come from the energy, waste, and agriculture sectors [2,4]. These are generally point sources, or emissions emanating from a single easily identifiable source like a gas storage tank or a landfill [5,6]. Although these sectors can also contain diffuse sources, or emissions coming from a larger area, a few point sources can dominate the emissions budget. Identifying emission sources and quantifying their rates can improve regional greenhouse gas budgets and mitigation strategies [6,7].

Remote Sens. 2019, 11, 3054; doi:10.3390/rs11243054 www.mdpi.com/journal/remotesensing Remote Sens. 2019, 11, 3054 2 of 19

This study investigates the potential to use a future generation of Earth observing satellites to map methane emissions. Past and present satellite missions measure atmospheric methane, but lack the fine spatial resolution needed to measure individual point sources. These sensors, such as the Atmospheric Infrared Sounder (AIRS), SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY), TROPOspheric Monitoring Instrument (TROPOMI), and the Greenhouse gas Observing Satellite (GOSAT), can accurately characterize the global and regional distributions of methane, but only at spatial resolutions between 7 and 60 km [8–12]. More recently, GHGsat demonstrated the ability to map methane plumes at a resolution as fine as 50 m [13,14]. Future satellites may be able to detect methane at even finer spatial resolutions. In the coming decade, there is strong interest in a new generation of Earth observing satellites equipped with Visible and Shortwave Infrared (VSWIR) imaging spectrometers [15]. VSWIR imaging spectrometers typically measure between 380 and about 2500 nm with between 5 to 10 nm spectral spacing [6,16–19]. These imaging spectrometers are sensitive to gas absorption features, which allows for the detection and quantitative mapping of methane, carbon dioxide, and water vapor [16,20–22]. In 2019, the Italian space agency launched the Hyperspectral Precursor and Application Mission (PRISMA), a medium resolution imaging spectrometer [23,24]. In 2020, the German space agency plans to launch the Environmental Mapping and Analysis Program (EnMAP) [25] and the Japanese government plans to launch the Hyperspectral Imager Suite (HISUI) [26], both of which are spaceborne imaging spectrometers.The National Aeronautics and Space Administration (NASA) plans to launch the Earth Surface Mineral Dust Source Investigation (EMIT) to the International Space Station (ISS) in 2021. NASA’s Surface Biology and Geology investigation is likely to include an imaging spectrometer that could launch as early as 2025 [27]. None of these sensors are being designed for gas mapping, but if these instruments can be used for methane mapping, the global monitoring of greenhouse gases will drastically improve. Recent work with a current satellite VSWIR imaging spectrometer and airborne imaging spectrometer data have provided a testbed for evaluating point source methane detection and measurements with these types of instruments [16,18,20,22,28]. The Hyperion imaging spectrometer on board the EO-1 satellite successfully detected the accidental methane release at Aliso Canyon [28], despite the age of the sensor and low signal-to-noise ratio (SNR). The Airborne Visible and Infrared Imaging Spectrometer Next Generation instrument (AVIRIS-NG), detected, geolocated, and quantified over 500 methane point sources throughout California from the oil and gas, manure management, and waste management sectors [7]. Across each sector, a small number of point sources contributed the majority of observed methane emissions, demonstrating the importance of observing point sources. While none of the proposed future imaging spectrometers are explicitly designed to map greenhouse gases, given their design and the prior successful work using similar airborne sensors to map methane, the upcoming generation of spaceborne imaging spectrometers has great potential for global mapping of near-surface methane emissions. This study examines the possibility of using these future sensors to monitor emissions from three of the largest anthropogenic methane sectors: oil/gas, waste management, and agriculture.

2. Methods In order to test the capability of future sensors for methane mapping, we resampled AVIRIS-NG data to create a simulated satellite product (Figure1) and then tested methane retrievals using this new product. We based our simulated satellite data on the sensor design for the upcoming EMIT mission [29]. The EMIT sensor design favors radiometric sensitivity over spatial resolution, leading to a 60 m spatial sampling that is slightly coarser than the 30 m spatial sampling slated for many orbital VSWIR sensors. Therefore, we simulated two sensor designs. The first was characteristic of a hypothetical future NASA mission after EMIT as well as those already operating or planned for launch by other space agencies. It has a 30 m spatial resolution with lower SNR. The second was a direct analogue of the EMIT instrument, with a 60 m spatial resolution and a higher SNR. Both simulations Remote Sens. 2019, 11, x FOR PEER REVIEW 3 of 19 direct analogue of the EMIT instrument, with a 60 m spatial resolution and a higher SNR. Both simulations are important for understanding the methane mapping potential for NASA’s future generation of sensors. The following section describes the original AVIRIS-NG data used, the process to resample it to a simulated satellite product, and the methane retrieval algorithm.

2.1. Imagery AVIRIS-NG is an airborne imaging spectrometer that measures radiance in the visible through shortwave-infrared (SWIR). It measures in the spectral range from about 380 to 2500 nm with a 5 nm spectral sampling [31–33]. AVIRIS-NG has a 34° field of view and a one milliradian instantaneous field-of-view that results in spatial resolutions ranging between approximately 1 and 8 meters, depending on the height of the aircraft. The AVIRIS-NG data used in this study were collected in 2016 and 2017 throughout California as part of the California Methane Survey and an image from a 2018 controlled release experiment [34]. We selected images of plumes from a landfill, a dairy, a dairy digester, a wastewater treatment facility, and oil/gas infrastructure. In this study, eight examples of plumes (Table 1), one or more from each source, were resampled to satellite specifications using the methods described below.

Table 1. The Airborne Visible and Infrared Imaging Spectrometers Next Generation (AVIRIS-NG) flight lines used in this study. The methane source type, time, date, and spatial resolution of each flight line.

Date of Time of Flight Spatial Line Name Source Type Flight (UTC) Resolution ang20161104t183025 Gas Storage Facility 11/4/2016 18:30:25 1.6 m ang20160915t185210 Gas Distribution Line 9/15/2016 18:52:10 1.7 m ang20170618t194516 Landfill 6/18/2017 19:45:16 3.3 m ang20170918t201542 Well 9/18/2017 20:15:42 3.3 m Remoteang20170618t193955 Sens. 2019, 11, 3054 Wastewater Treatment 6/18/2017 19:39:55 3.3 m 3 of 19 ang20170616t210522 Dairy Manure Lagoon 6/16/2017 21:05:22 3.0 m ang20170616t212046 Dairy Digester 6/16/2017 21:20:46 3.0 m are important for understanding the methane mapping potential for NASA’s future generation of ang20180917t201723 Controlled Release 9/17/2018 20:17:23 2.3 m sensors. The following section describes the original AVIRIS-NG data used, the process to resample it 2.2.to a Simulated simulated Satellite satellite Images product, and the methane retrieval algorithm.

Figure 1. Figure 1. FlowFlow chart chart of of the the steps steps for for creating creating the simulated satellite data. 2.1. Imagery 2.2.1. Aircraft to Top-of-Atmosphere AVIRIS-NG is an airborne imaging spectrometer that measures radiance in the visible through shortwave-infraredTo simulate the (SWIR). additional It measures atmosphere in the between spectral the range original from aircraft about 380 height to 2500 and nm the with top aof 5 nmthe atmosphere (TOA), we used MODerate resolution atmospheric TRANsmission 6 (MODTRAN6) to spectral sampling [30–32]. AVIRIS-NG has a 34◦ field of view and a one milliradian instantaneous simulatefield-of-view one-way that transmittance results in spatial between resolutions the two ranging heights between[35]. Each approximately transmittance 1simulation and 8 meters, was generateddepending with on thethe heightaircraft of height, the aircraft. latitude, The longitud AVIRIS-NGe, day, data and usedtime inof thisday studyof the wereoriginal collected AVIRIS- in NG2016 flight. and 2017 In addition, throughout we assumed California a background as part of the carbon California dioxide, Methane methane, Survey and and water an vapor image profile. from a Pixel2018 controlledradiance values release from experiment each image [33]. were We selected multiplied images by each of plumes simulated from atransmittance landfill, a dairy, spectrum. a dairy Fordigester, more adetails wastewater on the MODTRAN6 treatment facility, inputs and and oil an/gas example infrastructure. of a radiance In this spectrum study, eight adjusted examples to TOA, of pleaseplumes see (Table Appendix1), one A. or more from each source, were resampled to satellite specifications using the methods described below. 2.2.2. Spectral Resampling Table 1. The Airborne Visible and Infrared Imaging Spectrometers Next Generation (AVIRIS-NG) flight lines used in this study. The methane source type, time, date, and spatial resolution of each flight line.

Time of Flight Line Name Source Type Date of Flight Spatial Resolution (UTC) ang20161104t183025 Gas Storage Facility 11/4/2016 18:30:25 1.6 m ang20160915t185210 Gas Distribution Line 9/15/2016 18:52:10 1.7 m ang20170618t194516 Landfill 6/18/2017 19:45:16 3.3 m ang20170918t201542 Well 9/18/2017 20:15:42 3.3 m ang20170618t193955 Wastewater Treatment 6/18/2017 19:39:55 3.3 m ang20170616t210522 Dairy Manure Lagoon 6/16/2017 21:05:22 3.0 m ang20170616t212046 Dairy Digester 6/16/2017 21:20:46 3.0 m ang20180917t201723 Controlled Release 9/17/2018 20:17:23 2.3 m

2.2. Simulated Satellite Images

2.2.1. Aircraft to Top-of-Atmosphere To simulate the additional atmosphere between the original aircraft height and the top of the atmosphere (TOA), we used MODerate resolution atmospheric TRANsmission 6 (MODTRAN6) to simulate one-way transmittance between the two heights [34]. Each transmittance simulation was generated with the aircraft height, latitude, longitude, day, and time of day of the original AVIRIS-NG flight. In addition, we assumed a background carbon dioxide, methane, and water vapor profile. Pixel radiance values from each image were multiplied by each simulated transmittance spectrum. For more details on the MODTRAN6 inputs and an example of a radiance spectrum adjusted to TOA, please see AppendixA. Remote Sens. 2019, 11, 3054 4 of 19

2.2.2. Spectral Resampling The exact band centers and full width half maximum (FWHM) for EMIT are still to be determined. However, EMIT will most likely have a 7.4 nm spectral sampling with an 8.2 to 8.8 nm FWHM. We resampled spectra from AVIRIS-NG radiance images using a Gaussian convolution with band centers and FWHM based on these specifications. In total, the resampled spectra had 288 bands between 376.4 and 2500 nm.

2.2.3. Resample Spatial Resolution Each image was resampled to 30 m and 60 m spatial resolutions using Gaussian resampling. The stated spatial resolution represents the full-width half maximum of the Gaussian function, with the x-y coordinates for each AVIRIS-NG pixel center used to calculate each pixel’s weighting for resampling. The original unorthorectified AVIRIS-NG images were used for resampling, but pixel coordinate information allowed the creation of orthorectified 30 m and 60 m output images.

2.2.4. Sensor Noise The SNR from AVIRIS-NG is higher than the proposed SNR for the EMIT sensor and in addition, after spatial and spectrally resampling the data, some of the noise from the original AVIRIS-NG data is reduced through averaging. Therefore, adding sensor noise back into the data is critical for accurately modeling satellite data. To properly model the SNR of the satellite sensors, a noise component aimed at mimicking expected sensor noise was added to the radiance. Modeled sensor noise comes from two main components: photon noise (PN) and constant noise (CN). PN increases as the number of photons hitting a detector increases, and scales with the square root of radiance. CN is mainly associated with electronics and quantization in the signal chain. A primary contributor is “read noise”, caused by the analog-to-digital conversion as the instrument digitally records the signal, and this parameter can be modeled as constant across wavelengths and pixels. To calculate PN, we first converted the spectral radiance to the total number of photons and then multiplied it by the etendue (G), which is calculated based on the area of the emitting source (in this case, the Sun) times the solid angle, band FWHM, integration time (τ), and the system transmittance factor (T): r  λ  PN = L G FWHM τ T (1) λ × hc × × × × where PN is the photon noise; Lλ is the radiance at each wavelength in each pixel; λ is the wavelength; and hc is Planck’s constant times the speed of light. The AVIRIS-NG CN is 100 photons, therefore the same value was used for this simulation. The total noise was calculated as follows: q TN = (PN2 + CN2) (2) where TN is the total noise. The total noise was then converted back to radiance units by substituting TN for PN in Equation (1) and inverting. TN converted to radiance was then multiplied by a random number from a Gaussian distribution with a mean of 0 and standard deviation of 1, then added to the original radiance for each wavelength for each pixel. PN increases with increasing radiance; for low radiance values, CN dominates the total noise and for higher radiance values, PN dominates. For the 60 m image, we multiplied PN by the square root of 2. The SNR was calculated by dividing the signal by the noise. In this case, the signal was the number of photons and the noise is the total noise. The resulting average SNR for the 30 m simulated satellite images in the SWIR (2100 nm–2500 nm) was 214 and the average SNR for the 60 m simulated satellite images in the SWIR was 484. Figure2 shows the full spectrum SNR for the two simulations. RemoteRemote Sens.Sens.2019 2019, ,11 11,, 3054 x FOR PEER REVIEW 55 ofof 1919

Figure 2. Signal-to-Noise Ratio (SNR) for the 30 m simulated satellite data (blue) and for the 60 m simulatedFigure 2. satelliteSignal-to-Noise data (red). Ratio (SNR) for the 30 m simulated satellite data (blue) and for the 60 m simulated satellite data (red). 2.3. Matched Filter Methane Retrieval 2.3. MatchedThe methane Filter enhancementMethane Retrieval above the background for each pixel was estimated using an iterative matchedThe filtermethane technique enhancement tuned withabove a the methane background unit absorption for each pixel spectrum was estimated [19,35–37 using]. This an iterative iterative methodmatched included filter technique additional tuned optimization with a methane factors unit that absorption correct for spectrum spatially [19,36–38]. varying surface This iterative albedo. Inmethod addition, included a `1 sparsity additional prior optimi was includedzation factors to reflect that the correct expectation for spatially that methanevarying enhancementsurface albedo. is In a rareaddition, occurrence a ℓ1 sparsity within anprior image. was This included sparse to approach reflect the is similarexpectation to methods that methane employed enhancement in compressed is a sensingrare occurrence techniques within for thean image. reduction This of sparse acquisition approach time is or similar improved to methods resolution employed in fields in ascompressed varied as medicalsensing imaging,techniques radio for the astronomy, reduction and of electronacquisition microscopy time or improved [38–42]. The resolution iterative in technique fields as varied required as formedical solving imaging, this sparse radio optimization astronomy, problem and electron additionally microscopy produces [39–43]. the The explicit iterative removal technique of any methanerequired absorptionfor solving signal this sparse from the optimization background problem covariance additionally matrix; failure produces to remove the thisexplicit signal removal is detrimental of any tomethane matched absorption filter techniques signal from [36,37 the,43 ,44background]. covariance matrix; failure to remove this signal is detrimentalThis iterative to matched matched filter filter techniques with sparsity [37,38,44,45]. and albedo correction was applied to the AVIRIS-NG imagesThis and iterative simulated matched 30 m filter and with 60 m sparsity images. and For albedo all scenes, correction the sparsewas applied matched to the filter AVIRIS-NG was run forimages 30 iterations, and simulated which 30 includes m and 60 an m additionalimages. For 50% all scenes, margin the over sparse the matched 20 iterations filter that was producedrun for 30 initialiterations, observable which convergenceincludes an additional of the optimization 50% marg energy.in over The the number20 iterations of iterations that produced was based initial on observationsobservable convergence of convergence of from the aoptimization test dataset. Theenergy. methane The unitnumber absorption of iterations spectrum was for eachbased scene on wasobservations computed of from convergence the change from in radiance a test dataset. corresponding The methane to a change unit absorption in methane spectrum concentration for each in MODTRAN6scene was computed with each from scene’s the sensor change height in andradiance solar zenithcorresponding angle. The to albedoa change correction in methane factor wasconcentration estimated in by MODTRAN6 the ratio of a pixel’swith each radiance scene’s to sens theor mean height radiance and solar in the zenith scene. angle. For theThe original albedo AVIRIS-NGcorrection factor data, thewas matched estimated filter by wasthe ratio applied of a to pixe groupsl’s radiance of five adjacent to the mean columns, radiance corresponding in the scene. to adjacentFor the original detectors AVIRIS-NG of the AVIRIS-NG data, the instrument.matched filter This was grouping applied to improved groups of the five covariance adjacent columns, estimate usedcorresponding by the matched to adjacent filter to detectors describe theof the background AVIRIS-NG by suppressinginstrument. artifactsThis grouping from non-uniformity improved the amongcovariance detector estimate elements used [ 19by]. the For matched the simulated filter to satellite describe images, the background column artifacts by suppressing were averaged artifacts out byfrom spatial non-uniformity resampling, andamong therefore detector the matchedelements filter[19]. wasFor appliedthe simulated to the entire satellite image. images, column artifactsThe were resulting averaged methane out by enhancement spatial resampling, image and is measured therefore the in ppm-m,matched wherefilter was ppm applied represents to the concentrationentire image. and m represents the path length over which absorption occurs. Due to this algorithm’s sparsityThe prior, resulting many methane pixels are enhancement reported to haveimage no is methanemeasured enhancement in ppm-m, abovewhere theppm background. represents Thisconcentration allows for and interpreting m represents the enhancement the path length values over as which a detection absorption result occurs. (presence Due/absence to this ofalgorithm’s methane forsparsity a positive prior,/zero many enhancement pixels are value). reported We to also have consider no methane the resulting enhancement images as above a quantitative the background. retrieval directlyThis allows from for the per-pixelinterpreting methane the enhancement concentration. valu Fores moreas a informationdetection result on the (presence/absence retrieval algorithm of pleasemethane see Footefor a et.positive/zero al., In Review enhancement [45]. value). We also consider the resulting images as a quantitative retrieval directly from the per-pixel methane concentration. For more information on the 2.4. Integrated Mass Enhancement retrieval algorithm please see Foote et. al., In Review [46]. The integrated mass enhancement (IME) is the sum of all the methane enhancement above the background2.4. Integrated concentration Mass Enhancement present in each plume. To calculate the IME, we first need to identify the pixelsThe associated integrated with mass the plumeenhancement and filter (IME) out is spurious the sum signals. of all the We methane applied aenhancement 200 ppm-m thresholdabove the background concentration present in each plume. To calculate the IME, we first need to identify the

Remote Sens. 2019, 11, 3054 6 of 19 to filter out any potential spurious signals. The 200 ppm-m threshold was determined by reviewing the mean and standard deviation for the matched filter outputs. A 200 ppm-m value represents a round average of one standard deviation below the average mean of the enhanced pixels. To further filter out spurious signals, we calculated the number of pixels in contiguous clusters, any clusters below a certain threshold were filtered out. For the original AVIRIS-NG images, any clusters below 350 contiguous pixels were filtered out. For the 30 m satellite simulation, clusters below four pixels were filtered out and for the 60 m satellite simulation, clusters below two pixels were filtered out. Different thresholds were used for some cases based on empirical adjustments and are documented in AppendixA. We then calculated an integrated mass enhancement (IME) or the sum of the methane present in each plume [6] as follows:

Xn IME = k α(i)S(i) (3) i=0 where α is the methane value in ppm-m for the n pixels in the plume over the pixel area S and the constant k is used to convert to methane mass units [6].

2.5. Flux Estimate A simple flux estimate can be calculated using the IME, the length of the plume, and the wind speed. The methods for calculating the IME are listed above. To calculate the length of the plume, we identified the two pixels in the plume with the furthest distance and calculated the Euclidean distance between the two pixels. HRRRv3 10 m wind fields in forecast mode were used to estimate wind speeds for the location and time of each AVIRIS-NG scene [46,47]. Using the 3 km grid product, an average wind speed and standard deviation was calculated using a total of 27 HRRRv3 grid cells, a 3 3 box × centered on the source for three time-steps (plume detection time 1 hour). The equation for the flux is ± as follows: IME Flux = s (4) l where IME is the amount of methane in kg (calculated above); l is the plume length in meters; s is the wind speed meter/hour; and the resulting flux in the units of kg/hour. The uncertainties for the flux estimates result from uncertainties in the wind speeds.

3. Results and Discussion

3.1. Methane Plumes by Sector One advantage of using a satellite system to detect methane plumes is the ability to observe a large diversity of methane emitting sectors. Plumes from different sectors have different shapes, sizes, and underlying land cover that can influence how well a plume is detected. Here, we look at plumes from the three largest anthropogenic methane emitting sectors to understand how well a satellite system would perform in each sector. The following sections present the matched filter methane retrieval results for the AVIRIS-NG, 30 m, and 60 m satellite simulations.

3.1.1. Petroleum and Natural Gas The natural gas and petroleum industry represents about 30%–35% of all anthropogenic methane emissions globally [2,4,48]. Methane emissions from this sector can be challenging to characterize, given the significant variability in source type, plume shape and size, and intermittence. Here, we present three examples from different sources. The first is a gas storage facility that has two emission sources, the second is a well with a methane plume, and the third is a leak from a natural gas distribution line in a neighborhood [7]. All plumes were detectable from the 30 m and 60 m simulated satellite images. RemoteRemote Sens. Sens.2019 2019, 11, 11, 3054, x FOR PEER REVIEW 77 of of 19 19 Remote Sens. 2019, 11, x FOR PEER REVIEW 7 of 19 Figure 3 depicts the results of two plumes at the Honor Ranch gas storage facility. The source for theFigure top 3plume3 depicts depicts is an thethe emergency resultsresults ofof twoshutdowntwo plumesplumes stack atat thethe an Honor dHonor for the Ranch Ranch bottom gasgas plume, storage storage it facility.isfacility. a compressor TheThe sourcesource unit. forIn the topAVIRIS-NG plume is image,an emergency these two shutdown plumes stack were andistinct, andd for thewhich bottom bottom allows plume, plume, the plumesit it is is a a compressor compressor to be attributed unit. unit. Into the their AVIRIS-NGAVIRIS-NG exact sources. image,image, In these thesethe 30 two two m plumes image,plumes weresome were distinct, ofdistinct, the detail which which of allows allowsthe plume the the plumes plumesis lost, to tobut be be attributed two attributed distinct to theirtoplumes their exact exactare sources. still sources. visible. In theIn At 30the 60 m 30m, image, mthe image, methane some some of enhancement the of detail the detail of the is visible,of plume the plume isbut lost, the is but distinction lost, two but distinct two between distinct plumes the areplumestwo still plumes are visible. still disappears. visible. At 60 m, At At the60 the m, methane 30the m methane and enhancement 60 menhancement resolution, is visible, weis visible, could but the easilybut distinction the attribute distinction between the betweenplume the to two the the plumestwofacility, plumes disappears. but disappears.not to Atthe the exact At 30 the mlocations 30 and m 60 and mwithin resolution,60 m theresolution, facility we could aswe we easilycould could attributeeasily with attribute the the original plume the toplume AVIRIS-NG the facility, to the butfacility,image. not to but the not exact to the locations exact locations within the within facility the as facility we could as withwe could the original with the AVIRIS-NG original AVIRIS-NG image. image.

FigureFigure 3. 3.Matched Matched filterfilter methanemethane retrievalretrieval forfor aa plumeplume fromfrom aa 44 November,November, 20162016 AVIRIS-NGAVIRIS-NG image.image. TheFigureThe plumeplume 3. Matched isis fromfrom filter thethe Honor Honormethane RanchRanch retrieval gasgas storage storagefor a plum facility,facility,e fromwhere where a 4 November,there thereare are two two2016 plumes, plumes, AVIRIS-NG oneone from fromimage. anan emergencyTheemergency plume is shutdownshutdown from the stackHonorstack andand Ranch thethe othergasother storage fromfrom afa a compressorcility, compressor where unit. thereunit. (are(AA)) ResultstwoResults plumes, fromfrom one thethe from originaloriginal an AVIRIS-NGemergencyAVIRIS-NG shutdown image. image. (B(B )stack) Results Results and from from the the otherthe 30 30 mfrom m simulated simulate a compressord satellite satellite unit. image image (A with) withResults ~200 ~200 from SNR.SNR. the (C(C) )original Results Results fromAVIRIS-NGfrom the the 60 60 m image.m simulated simulated (B) Results satellite satellite from image im agethe with 30with m about aboutsimulate ~400 ~400d SNR. satelliteSNR. The The leftimage left side side with of theof ~200 the scale scaleSNR. bar bar ( areC) are unitsResults units in partsfromin parts perthe million60per m million simulated per meter per satellitemeter (ppm-m) (ppm-m) im aboveage with above the about background. the ~400 background. SNR. The The right The left side rightside of theof side the scale of scale the bar bar arescale are methane bar units are unitsinmethane parts in gper/ munits2 million. in g/m per2. meter (ppm-m) above the background. The right side of the scale bar are methane units in g/m2. FigureFigure4 4shows shows the the matched matched filter filter results results from from a a methane methane plume plume from from a a well. well. Given Given the the sheer sheer quantityquantityFigure andand 4 highshowshigh densitydensity the matched ofof wellswells filter throughoutthroughout results from thethe United aUnited methane States,States, plume aa satellitesatellite from a system systemwell. Given wouldwould the bebe sheer wellwell suitedquantitysuited toto and identifyidentify high those thosedensity thatthat of are arewells emitting emitting throughout methane. methan thee. ThisUnitedThis particularparticular States, a example examplesatellite issystemis fromfrom awoulda hydrocarbonhydrocarbon be well extractionsuitedextraction to identify site site within within those the the that Aliso Aliso are Canyon Canyon emitting gas gas methan storage storagee. facility. facility.This particular The The details details example of of the the plume isplume from are are a hydrocarbon most most distinct distinct inextractionin thethe originaloriginal site within AVIRIS-NGAVIRIS-NG the Aliso image. image. Canyon InIn the thegas 30 30storage mm andand facility. 6060 mm satelliteThesatellite details images,images, of the the theplume plumeplume are ismostis stillstill distinct clearlyclearly detectable,indetectable, the original but but becomesAVIRIS-NG becomes increasingly increasingly image. In less lessthe detailed. detailed.30 m and 60 m satellite images, the plume is still clearly detectable, but becomes increasingly less detailed.

Figure 4. Matched filter methane retrieval results from a plume from a 18 September, 2017 AVIRIS-NG image. The plume is from an oil producing well in Aliso Canyon. (A) Results from the original AVIRIS-NGFigure 4. Matched image. filter (B) Results methane from retrieval the 30 results m simulated from a satellite plume from image a with18 September, ~200 SNR. 2017 (C) AVIRIS- Results fromFigureNG image. the 4. 60Matched mThe simulated plume filter ismethane satellite from an image retrieval oil producing with results about well from ~400 in a SNR. Alisoplume The Canyon. from leftside a 18(A of )September, Results the scale from bar 2017 arethe AVIRIS- unitsoriginal in partsNGAVIRIS-NG image. per million The image. plume per meter(B )is Results from (ppm-m) an from oil above producing the 30 the m background. simulate well in Alisod satellite The Canyon. right image side (A ofwith) Results the ~200 scale from SNR. bar arethe (C methane)original Results unitsAVIRIS-NGfromin the g/ m602 image..m simulated (B) Results satellite from im agethe 30with m aboutsimulate ~400d satelliteSNR. The image left side with of ~200 the scaleSNR. bar (C) areResults units fromin parts the 60per m million simulated per satellitemeter (ppm-m) image with above about the ~400 background. SNR. The The left rightside of side the of scale the barscale are bar units are Oneinmethane parts concern per units million inin g/m the per2 natural. meter (ppm-m) gas and above petroleum the background. sector are The leaks right and side other of the fugitive scale bar emissions. are Not onlymethane do theseunits in emissions g/m2. contribute to the overall greenhouse gas budget, but they also represent lost revenueOne concern and in in su theffi cientlynatural large gas and amounts petroleum can pose sector a publicare leaks safety and hazard.other fugitive The ability emissions. to detect Not onlyOne do these concern emissions in the natural contribute gas andto the petroleum overall greenhouse sector are leaks gas budget, and other but fugitive they also emissions. represent Not lost only do these emissions contribute to the overall greenhouse gas budget, but they also represent lost

Remote Sens. 2019, 11, 3054 8 of 19 Remote Sens. 2019, 11, x FOR PEER REVIEW 8 of 19 leaksrevenue over and large in sufficiently areas could large help amounts improve can the pose mitigation a public of safety greenhouse hazard. gas The emissions ability to and detect hazards. leaks Figureover large5 is anareas example could ofhelp an improve underground the mitigation natural gas of distributiongreenhouse linegas emissions leak that was and detected hazards. in Figure 2016 in5 is the an Chinoexample Hills of neighborhood,an underground CA. natural This particulargas distribution leak was line detected leak that using was detected the real timein 2016 methane in the mappingChino Hills capability neighborhood, of AVIRIS-NG CA. andThis theparticular results were leak shared was detected with the localusing gas the company real time who methane quickly confirmedmapping capability and repaired of AVIRIS-NG the leak [19 and]. The the plume results is were clearly shared visible with in thethe AVIRIS-NGlocal gas company image and who a distinctquickly methaneconfirmed enhancement and repaired is the visible leak in [19]. the The 30 m plume and 60 is m clearly simulated visible images. in the AVIRIS-NG image and a distinct methane enhancement is visible in the 30 m and 60 m simulated images.

Figure 5. Matched filter methane retrieval results for a plume from a 15 September, 2016 AVIRIS-NG Figure 5. Matched filter methane retrieval results for a plume from a 15 September, 2016 AVIRIS-NG image. The plume is from a low pressure natural gas distribution line leak in the Chino Hills image. The plume is from a low pressure natural gas distribution line leak in the Chino Hills neighborhood. (A) Results from the original AVIRIS-NG image. (B) Results from the 30 m simulated neighborhood. (A) Results from the original AVIRIS-NG image. (B) Results from the 30 m simulated satellite image with ~200 SNR. (C) Results from the 60 m simulated satellite image with about ~400 SNR. Thesatellite left sideimage of with the scale ~200 bar SNR. are ( unitsC) Results in parts from per the million 60 m persimulate meterd (ppm-m)satellite image above with the background. about ~400 TheSNR. right The side left ofside the of scale the bar scale are bar methane are units units in in parts g/m2. per million per meter (ppm-m) above the background. The right side of the scale bar are methane units in g/m2. Current and past satellite sensors, like SCIAMACY and TROPOMI, are able to detect regional methaneCurrent enhancements and past satellite over areas sensors, with heavylike SCIAMACY oil and gas and production, TROPOMI, like theare methaneable to detect anomaly regional over themethane Four enhancements Corners areas over in the areas Western with heavy United oil Sates and gas [49], production, but cannot like identify the methane the exact anomaly location over of individualthe Four Corners point sources. areas in Currently,the Western the United only way Sates to locate[50], but a specific cannot sourceidentify is throughthe exact a location ground orof airborneindividual campaign, point sources. which Currently, can be costly, the only time way consuming, to locate and a specific have a source limited isgeographic through a ground extent [or6]. Therefore,airborne campaign, a higher spatialwhich resolutioncan be costly, satellite time sensorconsum thating, could and have identify a limited point sourcesgeographic would extent help [6]. us understandTherefore, a thehigher dynamics spatial ofresolution oil and natural satellite gas sensor methane that could emissions. identify Other point studies sources have would looked help into us theunderstand possibility the of dynamics using spaceborne of oil and sensors natural to gas do finemethane scale emissions. methane plume Other detection. studies haveVaron looked et al. into[13] performedthe possibility a sensitivity of using spaceborne study indicating sensors that to individualdo fine scale plumes methane could plume be mapped detection. with Varon a su etffi cientlyal. [13] sensitiveperformed constellation a sensitivity ofstudy point indicating source monitoring that individual satellites, plumes similar could tobe themapped planned with GHGSat a sufficiently fleet. Insensitive addition, constellation Cusworth of et point al. showed source thatmonitoring plumes satellites, from oil/gas similar facilities to the could planned be detected GHGSat with fleet. the In upcomingaddition, Cusworth EnMAP missionet al. showed [50]. The that future plumes generation from oil/gas of imaging facilities spectrometers could be detected will help with us the to improveupcoming our EnMAP understanding mission of[51]. methane The future emissions generation from the of oilim andaging natural spectrometers gas sectors. will help us to improve our understanding of methane emissions from the oil and natural gas sectors. 3.1.2. Landfill/Wastewater Treatment 3.1.2. Landfill/Wastewater Treatment The waste sector, which includes landfills and wastewater treatment, is thought to make up about 16%The of global waste anthropogenic sector, which methaneincludes emissions,landfills and with wa thestewater majority treatment, coming is from thought landfills to make [2,4, 47up]. Globally,about 16% landfills of global take anthropogenic on many diff erentmethane forms, emissi andons, factors with like the the majority composition coming of thefrom waste, landfills the temperature,[2,4,48]. Globally, the age, landfills and management take on many system differen can allt forms, influence and the factors amount like of methanethe composition emitted fromof the a landfillwaste, the [51 –temperature,53]. Of those the landfills age, and exhibiting management plumes system during can the all California influence Methane the amount Survey, of methane plumes appearedemitted from persistent a landfill across [52–54]. multiple Of those years, landfills therefore exhibiting making themplumes an during excellent the target California for spaceborne Methane studiesSurvey, [plumes7]. Satellite appeared monitoring persistent of these across sites multiple can help years, understand therefore emissions making fromthem this an excellent under sampled target sector,for spaceborne assess gas studies capture [7]. systems, Satellite and monitoring generally of provide these sites a better can help understanding understand of emissions landfill emissions. from this underFigure sampled6 shows sector, the assess matched gas filter capture results systems, from theand Newby generally Island provide landfill a better in San understanding Jose, CA. In this of image,landfill a emissions. very large plume is present, originating from multiple places in the landfill. Note the scale on (C) SatelliteFigure 606 shows m is higher the matched than the filter other results figures, from which the is Newby due to theIsland large landfill size of in the San plume. Jose, CA. The plumeIn this remainsimage, a visiblevery large in all plume simulated is present, satellite originating images. Large from plumesmultiple have places been in the detected landfill. with Note AVIRIS-NG the scale on (C) Satellite 60 m is higher than the other figures, which is due to the large size of the plume. The plume remains visible in all simulated satellite images. Large plumes have been detected with

Remote Sens. 2019, 11, 3054 9 of 19

Remote Sens. 2019, 11, x FOR PEER REVIEW 9 of 19 from other landfills in California and a large landfill in India, indicating that this type of methane AVIRIS-NG from other landfills in California and a large landfill in India, indicating that this type of source can be studied from space. methane source can be studied from space.

Figure 6. Matched filter methane retrieval results for a plume from a 18 June, 2017 AVIRIS-NG image. TheFigure plume 6. Matched is from filter Newby methane Island retrieval Land fill results in San for Jose, a plume CA. (A from) Results a 18 June, from 2017 the original AVIRIS-NG AVIRIS-NG image. image.The plume (B) Theis from matched Newby filter Island results Land from fill the in 30 San m simulatedJose, CA. ( satelliteA) Results image from with the ~200 original SNR. AVIRIS-NG (C) Results fromimage. the (B 60) The m simulated matched satellitefilter results image from with the about 30 ~400m simulated SNR. The satellite left side image of the scalewith bar~200 are SNR. units (C in) partsResults per from million the per60 m meter simulated (ppm-m) sate abovellite image the background. with about ~400 The rightSNR. side The ofleft the side scale of the bar scale are methane bar are units inin gparts/m2. per million per meter (ppm-m) above the background. The right side of the scale bar 2 are methane units in g/m2. Adjacent to the landfill is a wastewater treatment facility. Figure7 shows a small plume that is evidentlyAdjacent emanating to the landfill from one is ofa wastewater the tanks. The treatment plume isfacility. clearly Figure visible 7 in shows the AVIRIS-NG a small plume image, that but is lessevidently so in theemanating 30 m and from 60 mone images. of the tanks. Given The this plum result,e is the clearly detection visible of in a the methane AVIRIS-NG plume image, from thisbut particularless so in the source 30 m will and be 60 di ffimcult images. for the Given satellite this instrumentsresult, the detection modeled of here. a methane plume from this particular source will be difficult for the satellite instruments modeled here.

Figure 7. Matched filter methane retrieval results for a plume from a 18 Jun, 2017 AVIRIS-NG image. TheFigure plume 7. Matched a wastewater filter methane treatment retrieval plant south results of for the aNewby plume from Island a Landfill.18 Jun, 2017 (A) AVIRIS-NG The matched image. filter resultsThe plume from a thewastewater original AVIRIS-NGtreatment plant image. south (B) of Results the Newby from the Island 30 m Landfill. simulated (A) satellite The matched image filter with ~200results SNR. from (C the) Results original from AVIRIS-NG the 60 m simulated image. (B satellite) Results image from with the 30 about m simulated ~400 SNR. satellite The left image side of with the scale~200 SNR. bar are (C units) Results in parts from per the million 60 m simulated per meter (ppm-m)satellite im aboveage with the background. about ~400 SNR. The rightThe left side side of the of scalethe scale bar arebar methaneare units unitsin parts in g per/m2 .million per meter (ppm-m) above the background. The right side 2 of the scale bar are methane units in g/m2. 3.1.3. Dairies 3.1.3.Enteric Dairies fermentation and manure management make up about 28% of global anthropogenic methaneEnteric emissions fermentation [2,4,48 ].and This manure is a significant management anthropogenic make up methane about 28% source, of global but the anthropogenic most difficult tomethane map using emissions this method. [2,4,49]. Enteric This is fermentationa significant anthropogenic is an area source methane and does source, not produce but the methanemost difficult from ato single map using easily this identifiable method. point.Enteric This fermentation makes mapping is an area methane source from and cattledoes not with produce imaging methane spectroscopy from morea single diffi cult.easily However,identifiable there point. is an This exception makes for mapping some methods methane of manure from cattle management. with imaging Many manurespectroscopy lagoons more from difficult. large dairies However, and some there digesters is an exception in California for producesome methods small yet of detectable manure management. Many manure lagoons from large dairies and some digesters in California produce small yet detectable plumes. Figure 8 shows the matched filter results of a plume from a typical dairy

Remote Sens. 2019, 11, 3054 10 of 19 Remote Sens. 2019, 11, x FOR PEER REVIEW 10 of 19 Remote Sens. 2019, 11, x FOR PEER REVIEW 10 of 19 plumes.manure lagoon. Figure8 Itshows is clearly the matchedvisible in filter the AVIRIS-NG results of a plume images from and aremains typical dairydetectable manure in the lagoon. 30 m Itand is manure lagoon. It is clearly visible in the AVIRIS-NG images and remains detectable in the 30 m and clearly60 m images. visible in the AVIRIS-NG images and remains detectable in the 30 m and 60 m images. 60 m images.

Figure 8. Matched filter methane retrieval results for a plume from a 16 June, 2017 AVIRIS-NG image. Figure 8. Matched filter methane retrieval results for a plume from a 16 June, 2017 AVIRIS-NG image. TheFigure plume 8. Matched is from afilter typical methane manure retrieval lagoon results on a California for a plume dairy. from (A) a The 16 June, matched 2017 filter AVIRIS-NG results from image. the The plume is from a typical manure lagoon on a California dairy. (A) The matched filter results from originalThe plume AVIRIS-NG is from a image.typical (manureB) The matched lagoon on filter a California results from dairy. the 30(A) m The simulated matched satellite filter results image from with the original AVIRIS-NG image. (B) The matched filter results from the 30 m simulated satellite image ~200the original SNR. (C AVIRIS-NG) The matched image. filter (B results) The matched from the filter 60 m results simulated from satellite the 30 imagem simulated with about satellite ~400 image SNR. with ~200 SNR. (C) The matched filter results from the 60 m simulated satellite image with about ~400 Thewith left ~200 side SNR. of the(C) scaleThe matched bar areunits filter inresults parts from permillion the 60 m per simulated meter (ppm-m) satellite aboveimage thewith background. about ~400 SNR. The left side of the scale bar are units in parts2 per million per meter (ppm-m) above the TheSNR. right The side left ofside the of scale the bar scale are bar methane are units units in in gparts/m . per million per meter (ppm-m) above the background. The right side of the scale bar are methane units in g/m2. background. The right side of the scale bar are methane units in g/m2. An anaerobic digester is an enclosed area where the breakdown of organic material (manure) is promotedAn anaerobic and the biogasdigester is thenis an capturedenclosed andarea used where as anthe energy breakdown source. of Manyorganic studies material have (manure) measured is An anaerobic digester is an enclosed area where the breakdown of organic material (manure) is thepromoted potential and biogas the biogas produced is then from captured digesters inand order used to as estimate an energy gas production source. Many [54, 55studies]. However, have promoted and the biogas is then captured and used as an energy source. Many studies have fewmeasured studies the have potential looked biogas at the gasproduced lost due from to leaks. digest Iners addition, in order emissionsto estimate from gas manureproduction can be[55,56]. well measured the potential biogas produced from digesters in order to estimate gas production [55,56]. constrainedHowever, few with studies isotopic have measurements, looked at the butgas thislost doesdue notto leaks. allow In for addition, the distinction emissions between from anmanure open However, few studies have looked at the gas lost due to leaks. In addition, emissions from manure manurecan be well lagoon constrained and a digester with [ 56is].otopic Regular measurements, satellite measurements but this do ofes large not dairy allow production for the distinction areas like can be well constrained with isotopic measurements, but this does not allow for the distinction California’sbetween an Sanopen Joaquin manure Valley lagoon would and improvea digester understanding [57]. Regular satellite of the dynamics measurements of methane of large emission dairy between an open manure lagoon and a digester [57]. Regular satellite measurements of large dairy fromproduction manure areas management. like California’s Figure San9 shows Joaquin the Va matchedlley would filter improve results of understanding three plumes in of the the upper dynamics left production areas like California’s San Joaquin Valley would improve understanding of the dynamics cornerof methane coming emission off a digester from manure in California. management. In the 30 Figure m and 9 60shows m simulated the matched images, filter the results plume ofis three still of methane emission from manure management. Figure 9 shows the matched filter results of three visible,plumes butin the has upper blended left into corner one coming larger plume off a digester instead ofin threeCalifornia. smaller In ones.the 30 m and 60 m simulated plumes in the upper left corner coming off a digester in California. In the 30 m and 60 m simulated images, the plume is still visible, but has blended into one larger plume instead of three smaller ones. images, the plume is still visible, but has blended into one larger plume instead of three smaller ones.

Figure 9. Matched filter methane retrieval results of a plume from a 16 June, 2017 AVIRIS-NG image. Figure 9. Matched filter methane retrieval results of a plume from a 16 June, 2017 AVIRIS-NG image. TheFigure plume 9. Matched is from filter a covered methane lagoon retrieval digester results in California.of a plume from (A) The a 16 matched June, 2017 filter AVIRIS-NG results from image. the The plume is from a covered lagoon digester in California. (A) The matched filter results from the originalThe plume AVIRIS-NG is from a image. covered (B )lagoon The matched digester filter in California. results from (A the) The 30 m matched simulated filter satellite results image from with the original AVIRIS-NG image. (B) The matched filter results from the 30 m simulated satellite image ~200original SNR. AVIRIS-NG (C) The matched image. filter (B) The results matched from the filter 60 mresults simulated from satellitethe 30 m image simulated with about satellite ~400 image SNR. with ~200 SNR. (C) The matched filter results from the 60 m simulated satellite image with about ~400 Thewith left ~200 side SNR. of the(C) scaleThe matched bar areunits filter inresults parts from permillion the 60 m per simulated meter (ppm-m) satellite aboveimage thewith background. about ~400 SNR. The left side of the scale bar are units in parts2 per million per meter (ppm-m) above the TheSNR. right The side left ofside the of scale the bar scale are bar methane are units units in in gparts/m . per million per meter (ppm-m) above the background. The right side of the scale bar are methane units in g/m2. 2 3.1.4.background. Controlled The Release right side of the scale bar are methane units in g/m . 3.1.4. Controlled Release 3.1.4.In Controlled September Release 2018, a controlled release experiment was performed to test the accuracy of the AVIRIS-NGIn September methane 2018, retrievals. a controlled Natural release gas was experiment released by was a pipeline performed operator to test at the a known accuracy flux of while the In September 2018, a controlled release experiment was performed to test the accuracy of the AVIRIS-NG flewmethane over. retrievals. We analyzed Natural one scene gas was from released this experiment by a pipeline to verify operator that our at methodsa known wereflux AVIRIS-NG methane retrievals. Natural gas was released by a pipeline operator at a known flux producingwhile AVIRIS-NG reasonable flew results over. We (Figure analyzed 10). The one flux scene during from thisthis flightexperiment was 103.71 to verify kg/h that and our the methods retrieval while AVIRIS-NG flew over. We analyzed one scene from this experiment to verify that our methods were producing reasonable results (Figure 10). The flux during this flight was 103.71 kg/h and the were producing reasonable results (Figure 10). The flux during this flight was 103.71 kg/h and the retrieval from AVIRIS-NG with our methods was 117.59 ± 15.53 kg/h. The agreement between the retrieval from AVIRIS-NG with our methods was 117.59 ± 15.53 kg/h. The agreement between the

Remote Sens. 2019, 11, 3054 11 of 19 fromRemote AVIRIS-NG Sens. 2019, 11, with x FOR our PEER methods REVIEW was 117.59 15.53 kg/h. The agreement between the AVIRIS-NG11 of 19 ± flux and actual flux was good, however, the agreement for the 30 m and 60 m images was not as close AVIRIS-NG flux and actual flux was good, however, the agreement for the 30 m and 60 m images (Table2). This was a smaller plume and the entire plume spanned one or two pixels in the 60 m satellite was not as close (Table 2). This was a smaller plume and the entire plume spanned one or two pixels simulation, therefore calculating an accurate flux was more difficult. Regardless, the plumes were in the 60 m satellite simulation, therefore calculating an accurate flux was more difficult. Regardless, visible in both the 30 m and 60 m, which indicates that plumes with a flux as small as ~100 kg/h will be the plumes were visible in both the 30 m and 60 m, which indicates that plumes with a flux as small visible with the next generation of satellite imaging spectrometers. as ~100 kg/h will be visible with the next generation of satellite imaging spectrometers.

Figure 10. Matched filter methane retrieval results from a controlled release experiment on 17 September, 2018. (A) The matched filter results from the original AVIRIS-NG image. (B) The matched filter results fromFigure the 10. 30 mMatched simulated filter satellite methane image retrieval with ~200results SNR. from (C )a The controlled matched release filter results experiment from theon 6017 mSeptember, simulated 2018. satellite (A) imageThe matched with about filter ~400 results SNR. from The the left original side of AVIRIS-NG the scale bar image. are units (B) The in parts matched per millionfilter results per meter from (ppm-m) the 30 m above simula theted background. satellite image The with right ~200 side ofSNR. the scale(C) The bar matched are methane filter units results in gfrom/m2. the 60 m simulated satellite image with about ~400 SNR. The left side of the scale bar are units in parts per million per meter (ppm-m) above the background. The right side of the scale bar are methane units Tablein g/m 2.2. The flux and uncertainty due to wind for the selected plumes. Flux (kg/h) 3.2. Flux Source AVIRIS-NG 30 m 60 m TheGas fluxes Storage for Facility the AVIRIS-NG, 1209.97 30 m, 131.11and 60 m images 1497.54 were162.26 calculated 1674.46 using the181.43 methods ± ± ± presented above.Well Calculating the flux 553.03 allows92.76 the scientific 578.53 community108.46 to quantitatively 547.73 91.87 assess the ± ± ± volumeGas of Distributionmethane emitted Line per source 156.20 and48.17 sector. We tested 224.63 an69.28 image from 225.62a controlled69.58 release ± ± ± Landfill 1231.67 332.78 1613.23 435.87 1663.51 449.45 experiment (presented above) to empirically± validate our flux± estimates. We calculated± a flux Wastewater Treatment 198.00 40.38 159.42 32.51 179.11 36.53 estimation of 117.59 ± 15.53 kg/h for the AVIRIS-NG± image of the± controlled release experiment.± The Dairy Manure Lagoon 397.89 434.38 584.28 637.86 480.28 524.33 ± ± ± reported fluxDairy at Digesterthe time of the image 552.65 was 103.7147.75 kg/h. These 578.53 results49.98 are close 580.00enough 20.11that we feel ± ± ± confidentControlled that the ReleaseAVIRIS-NG images 117.59 provide15.53 a good estimation 167.20 22.09 of the magnitude 65.42 of the8.64 flux. We can therefore compare the results from the± satellite simulations to± the original AVIRIS-NG± image to 3.2.understand Flux how well a satellite system would perform. In general, the flux estimates from the satellite simulations are consistent with the flux estimations from the AVIRIS-NG image. Table 2 provides the resultsThe of fluxes the flux for theestimates AVIRIS-NG, for the 30 AVIRIS-NG, m, and 60 m the images 30 m, were and calculated 60 m images. using Figure the methods 11 shows presented the flux above.results Calculatingfrom the 30 them and flux 60 allows m image the scientificplotted against community the flux to quantitativelyresults from the assess AVIRIS-NG the volume image. of methaneThe relationship emitted between per source the and satellite sector. simula We testedtions and an imagethe AVIRIS-NG from a controlled image was release strong experiment (R2 = 0.98), (presentedalthough the above) linear to regression empirically line validate did not ourmatch flux the estimates. 1:1 line, the We error calculated bars crossed a flux or estimation came close ofto 117.59 15.53 kg/h for the AVIRIS-NG image of the controlled release experiment. The reported flux the 1:1± line. The satellite simulations tended to overestimate the flux for both simulations. In addition, atthe the overestimation time of the image appears was to 103.71 become kg/ h.larger These as resultsthe size are of close the methane enough thatplume we increases, feel confident however, that thewhen AVIRIS-NG the error is images normalized provide by the a good size of estimation the plume, of this the relationship magnitude breaks of the flux.down. We One can explanation therefore comparefor the overestimation the results from is the that satellite the coarser simulations spatial to re thesolution original inflates AVIRIS-NG the spat imageial extent to understand of the plume, how wellwhich a satelliteincreases system the IME would and plume perform. length. In general, However, the the flux IME estimates tends to from increase the satellitemore than simulations the plume arelength, consistent causing with the theflux flux to also estimations increase.from In a simi the AVIRIS-NGlar study, Cusworth image. Tableet al. 2found provides that thethe resultssatellite ofsimulation the flux estimatesunderestimated for the the AVIRIS-NG, AVIRIS-NG the retrieval, 30 m, andbut they 60 m used images. a differen Figuret retrieval 11 shows algorithm, the flux a resultsdifferent from plume the 30mask, m and and 60 did m not image simulate plotted a 60 against m instrument the flux [51]. results More from work the will AVIRIS-NG be needed image. to be 2 Thedone relationship to understand between precisely the satellite how increasing simulations spat andial resolution the AVIRIS-NG changes image the wasIME strong and therefore (R = 0.98), the althoughflux. the linear regression line did not match the 1:1 line, the error bars crossed or came close to the 1:1 line. The satellite simulations tended to overestimate the flux for both simulations. In addition, Table 2. The flux and uncertainty due to wind for the selected plumes.

Flux (kg/h) Source AVIRIS-NG 30 m 60 m

Remote Sens. 2019, 11, 3054 12 of 19 Remote Sens. 2019, 11, x FOR PEER REVIEW 12 of 19 the overestimationGas Storage appears Facility to become 1209.97 larger ± 131.11 as the size 1497.54 of the ± methane 162.26 plume 1674.46 increases, ± 181.43 however, when the error isWell normalized by the size 553.03 of the ± 92.76 plume, this 578.53 relationship ± 108.46 breaks down.547.73 ± One 91.87 explanation for the overestimationGas Distribution is thatLine the coarser 156.20 spatial ± 48.17 resolution 224.63 inflates ± 69.28 the spatial 225.62 extent ± 69.58 of the plume, which increasesLandfill the IME and plume 1231.67 length. ± However, 332.78 the 1613.23 IME tends ± 435.87 to increase 1663.51 more ± than449.45 the plume length, causingWastewater the fluxTreatment to also increase. 198.00In ± a 40.38similar study, 159.42 Cusworth ± 32.51 et al. found179.11 that± 36.53 the satellite simulationDairy underestimated Manure Lagoon the AVIRIS-NG 397.89 ± retrieval,434.38 but 584.28 they used± 637.86 a di fferent 480.28 retrieval ± 524.33 algorithm, a different plumeDairy mask, Digester and did not simulate 552.65 ± a 47.75 60 m instrument 578.53 [±50 49.98]. More work 580.00 will ± be 20.11 needed to be done to understandControlled precisely Release how increasing 117.59 ± spatial15.53 resolution 167.20 changes ± 22.09 the IME 65.42 and therefore± 8.64 the flux.

Figure 11. (A) The 30 m flux plotted against the original AVIRIS-NG. The error bars represent Figureuncertainty 11. (A in) theThe wind 30 m speed flux estimate,plotted against which inthe turn origin leadsal AVIRIS-NG. to uncertainty The in theerror flux bars estimate. represent The uncertaintyR2 = 0.98, the in slopethe wind= 1.3, speed and theestimate, y-intercept which= in 21.turn (B leads) The to 60 uncertainty m flux is plotted in the against flux estimate. the original The − RAVIRIS-NG.2 = 0.98, the Theslope errors = 1.3, bars and represent the y-intercept error due = − to21. wind (B) The speed. 60 m The flux R2 is= 0.98,plotted the against slope = the1.4, original and the AVIRIS-NG.y-intercept = The109. errors For bars both repres figures,ent the error red due dashed to wind line isspeed. the one-to-one The R2 = 0.98, line the and slope the blue = 1.4, line and is the the − y-interceptbest fit linear = − regression.109. For both figures, the red dashed line is the one-to-one line and the blue line is the best fit linear regression. 3.3. Spatial Resolution and Signal-to Noise Ratio 3.3. SpatialIn this Resolution analysis, theand spatial Signal-to resolution Noise Ratio and SNR are the two variables that distinguish the 30 m and 60 mIn satellite this analysis, simulations. the spatial Sensor resolution design often and requiresSNR are compromisesthe two variables between that didistinguishfferent performance the 30 m andmeasures. 60 m satellite For example, simulations. designers Sensor may sacrificedesign often SNR forrequires finer spatialcompromises resolution between andvice different versa. performanceWe looked at measures. which of For these example, factors designers had the largest may sa impactcrifice onSNR methane for finer gas spatial mapping. resolution We usedand vice the versa.Honor We Ranch looked gas at storage which facilityof these as factors an example had th ande largest tested impact how ouron methane retrieval gas changed mapping. with We diff usederent thenoise Honor levels; Ranch no added gas noise,storage ~400 facility SNR, as and an ~200 example SNR. Weandfound tested that how visually, our retrieval the plume changed became with less differentdistinct fromnoise the levels; background no added and noise, the presence~400 SNR, of and spurious ~200 SNR. signals We increased, found that which visually, in turn the slightlyplume becameincreased less the distinct flux estimate from the (Figure background 12). We and also the tested presence the imageof spurious with thesignals same increased, SNR at the which native in turnresolution slightly (1.6 increased m), 30m, the and flux 60 es m.timate We found(Figure that 12). the We plume also tested became the lessimage detailed with the with same coarsening SNR at thespatial native resolution, resolution indicating (1.6 m), that 30 spatialm, and resolution, 60 m. We ratherfound than that SNR, the plume had a larger became influence less detailed on detecting with coarseningplumes. In addition,spatial resolution, we performed indicating an Analysis that ofspatial Variance resolution, (ANOVA) rather with athan Tukey SNR, post had hoc usinga larger the flux and standard deviation, and found that the only image that was significantly different (p 0.05) influence on detecting plumes. In addition, we performed an Analysis of Variance (ANOVA) with≤ a Tukeyfrom the post original hoc using AVIRIS-NG the flux was and the standard 60 m image. deviation, More and plumes found as that well the as aonly larger image range that in SNRwas significantlyand pixel size different will be needed(p ≤ 0.05) to accuratelyfrom the original quantify AVIRIS-NG how noise versuswas the spatial 60 m image. resolution More eff ectsplumes plume as wellretrieval. as a larger However, range these in SNR results and indicate pixel size that will changing be needed the spatial to accurately resolution quantify has a largerhow noise impact versus than spatialchanging resolution the noise. effects plume retrieval. However, these results indicate that changing the spatial resolution has a larger impact than changing the noise.

Remote Sens. 2019, 11, x 3054 FOR PEER REVIEW 1313 of of 19 19

Figure 12. (A) The y-axis is the flux in kg/h and each bar on the x-axis represents an image. The spatial Figureresolution 12. ( isA held) The constanty-axis is (30the m)flux but in thekg/h SNR andvaries each bar from on nothe additional x-axis represents noise, ~400 an image. SNR in The the spatial SWIR, resolutionand ~200 SNR is held in theconstant SWIR. (30 (B )m) The but y-axis the SNR is the vari fluxes (kgfrom/h) no and additional the bars onnoise, the x-axis~400 SNR represent in the imagesSWIR, andwhere ~200 the SNR SNR in is the constant SWIR.(200 (B) The SNR) y-axis but theis the spatial flux resolution(kg/h) and isth thee bars native on the 1.6 x-axis m, 30 m,represent and 60 images m. The where60 m image the SNR is the is onlyconstant image (200 that SNR) is significantly but the spatia diffl erentresolution from is the the AVIRIS-NG, native 1.6 m, p = 300.019. m, and The 60 light m. Thegray 60 bar m inimage both is charts the only is the image original that AVIRIS-NG is significantly for referencedifferent fr andom thethe error AVIRIS-NG, bars represent p = 0.019. the The flux lighterror gray due tobar wind in both speed charts uncertainty. is the original AVIRIS-NG for reference and the error bars represent the flux error due to wind speed uncertainty. 3.4. Limitations 3.4. LimitationsThe satellite simulations indicate that point source methane mapping will be possible with the futureThe satellite generation simulations of satellite indicate imaging that point spectrometers. source methane However, mapping there will are be possible some limitations with the futurewith the generation simulations of satellite presented imaging here. Whilespectrometer the specificationss. However, for there the are simulation some limitations represent with the bestthe simulationsavailable knowledge presented about here. theWhile design the specifications of a future spectrometer for the simulation (EMIT), represent there remains the best a possibility available knowledgethat specifications about willthe changedesign beforeof a future launch. spectrom Other satelliteeter (EMIT), designs there might rema includeins a di possibilityfferent spectral, that specificationsspatial, or SNR will characteristics change before not modeledlaunch. Other here, however satellite thesedesigns are might unlikely include to be drastically different spectral, different. spatial,In addition, or SNR this studycharacteristics did not accountnot modeled for other here factors, however associated these withare unlikely satellite sensorsto be drastically including different.potential orbits,In addition, cloud cover,this study sun angles,did not and account surface for brightness. other factors In particular,associated surfacewith satellite brightness sensors has includingproven to potential have a large orbits, influence cloud oncover, methane sun angles, retrievals and [ 50surface,57]. Whilebrightness. there isIn inherentparticular, variability surface brightnessin surface brightnesshas proven into thehave AVIRIS-NG a large influence scenes, on we methane were not retrievals able to [51,58]. control While this variable. there is inherent Finally, variabilitywhile the flightlines in surface from brightness this study in the represent AVIRIS-NG a range scenes, of emissions we were over not variableable to control surface this terrain, variable. more Finally,challenging while examples the flightlines containing from lower this fluxesstudy wererepresent not tested. a range of emissions over variable surface terrain,Other more limitations challenging in examples the study containing include the lower methods fluxes we were used not to tested. create a plume mask and the fluxOther estimate. limitations The plume in the mask study is include intended the to methods isolate thewe plumeused to andcreate filter a plume out spurious mask and signals the flux or estimate.false positives. The plume Spurious mask signals is intended were present to isolate in boththe plume the airborne and filter data out and spurious the satellite signals simulations or false positives.(Figures3– 10Spurious). For this signals study, were we attempted present toin beboth as consistentthe airborne as possible data and and the therefore satellite generally simulations used (Figuresconsistent 3–10). thresholds For this to isolatestudy, thewe plume.attempted It should to be beas noted,consistent however, as possible that more and tailored therefore thresholding generally usedcould consistent produce better thresholds results to in is futureolate the studies. plume. The It thresholdingshould be no andted, segmentation however, that can more have tailored a large thresholdingimpact on the could results, produce more workbetter is results needed in to future determine studies. the The best thresholding practices for and how segmentation to approach this.can haveAdditional a large work impact is required on the results, to assess more the impactwork is that needed these to spurious determine signals the maybest havepractices on our for IME how and to approachflux estimates. this. Additional This study work also used is required a simple to methodassess the to estimateimpact that the these flux ofspurious the plumes. signals More may robust have onflux our calculations IME and couldflux estimates. lead to more This accurate study also results. used a simple method to estimate the flux of the plumes. More robust flux calculations could lead to more accurate results.

5. Conclusions We tested the potential to use future Earth observing satellites such as EMIT or SBG to map and measure methane plumes from the three main anthropogenic emission sectors. These particular

Remote Sens. 2019, 11, 3054 14 of 19

4. Conclusions We tested the potential to use future Earth observing satellites such as EMIT or SBG to map and measure methane plumes from the three main anthropogenic emission sectors. These particular future satellites will measure in the SWIR with 7–10 nm spectral sampling, the spatial resolution will range from 30 m to 60 m pixels, and will have a SNR in the SWIR between 200 and 400. To test the potential of using these instruments for high resolution methane mapping, we simulated two proposed satellite designs from the AVIRIS-NG data. The first was a 30 m pixel resolution with a ~200 SNR in the SWIR, the second was a 60 m pixel resolution with ~400 SNR in the SWIR. We then ran a matched filter methane retrieval algorithm on the simulated satellite images and compared it to the original AVIRIS-NG. We found that for almost all plumes, the methane enhancement remained visible at the coarser spatial resolutions. This indicated that most point source emissions from the largest anthropogenic sources should be detectable, at minimum, in a 30 m resolution image. We found that when we quantified the flux of the plume in the simulated images, it correlated well with the flux calculated from the AVIRIS-NG results. In addition, for the controlled release experiment, the flux calculated from the AVIRIS-NG data was similar to the known flux. Within the limits of our study, we also found that the spatial resolution had a larger impact on the results than the SNR. We conclude that a satellite system will be able to map and quantify the biggest of the point source emitters and should be able to detect plumes as small as ~100 kg/h, although accurate quantification of flux may be more difficult. These plumes may only be a small fraction of the total number of plumes, but likely represent up to 40% of emitted methane. While the future generation of satellite imaging spectrometers were not designed for high resolution gas mapping, this work indicates that they will be able to map methane plumes and quantify emission rates. However, imaging spectrometer concepts have been developed that would utilize finer spectral resolution to improve gas sensitivities [50,58]. Eventually, these sensors will become integrated into larger greenhouse gas monitoring schemes and will help scientists better understand global methane emissions.

Author Contributions: A.K.A. created the model, performed the analysis, and was the main author. P.E.D., D.A.R., and A.K.T. helped conceive the experimental design and methodological approach. M.F., P.E.D., and S.J. developed and assisted with the methane retrieval algorithm. A.K.T. and R.M.D. provided the AVIRIS-NG data and contributed supporting material. R.O.G. and D.R.T. provided information on the design for the satellite simulations. Funding: This research was funded by the National Aeronautics and Space Administration (NASA), grant number 80NSSC17K0575. Acknowledgments: A portion of this research was supported by the Chevron Energy Technology Company and performed at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration (NASA). US Government support is acknowledged. Data for this research was provided by the California Methane Survey funded by NASA, the California Air Resources Board, the California Energy Commission, and NASA’s Carbon Monitoring System. Conflicts of Interest: The authors declare no conflicts of interest.

Appendix A

Table A1. MODerate resolution atmospheric TRANsmission (MODTRAN) inputs for simulating the atmosphere from the aircraft to the top-of-atmosphere (TOA).

Attribute Values Wavelengths 350–2500 nm Carbon dioxide 405 ppm Water Vapor 1245.3 atm-cm Visibility 30 km Methane 1.7 ppm Remote Sens. 2019, 11, x FOR PEER REVIEW 15 of 19

Remote Sens. 2019, 11, x FOR PEER REVIEW 15 of 19

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Figure A1. Example a radiance spectrum for the original AVIRIS-NG (red) and example of the same spectrum adjusted for TOA (blue). Figure A1. Example a radiance spectrum for the original AVIRIS-NG (red) and example of the same Figure A1. Example a radiance spectrum for the original AVIRIS-NG (red) and example of the same spectrum adjusted for TOA (blue). spectrum adjusted for TOA (blue).

Figure A2. Figure A2. Example of a radiance spectrum at 5 nm samplingsampling (blue) and the same example at 7.5 nm sampling (red). Note the decreased detail in the gas absorption bands. sampling (red). Note the decreased detail in the gas absorption bands. Figure A2.Table Example A2. ofIntegrated a radiance Mass spectrum Enhancements at 5 nm sampling (IME) and(blue) lengths and the for same all plumes. example at 7.5 nm sampling (red).Table Note A2. theIntegrated decreased Mass deta Enhancementsil in the gas absorption (IME)and bands. lengths for all plumes. IME (kg) Length (m) Source IME (kg) Length (m) Table A2. IntegratedAVIRIS-NG Mass Enhancements 30 m (IME)and 60 m lengths AVIRIS-NG for all plumes. 30 m 60 m Source AVIRIS-NG 30 m 60 m AVIRIS-NG 30 m 60 m GasGas Storage FacilityFacility 70.23 70.23 116.51IME 116.51 (kg) 128.23 128.23 671.50 671.50 Length 900.00 900.00 (m) 885.89 885.89 Well *** 13.30 28.60 14.63 314.87 550.73 349.86 WellSource *** AVIRIS-NG 13.30 28.60 30 m 14.6360 m AVIRIS-NG 314.87 30 550.73 m 60 349.86 m GasGas Distribution Storage Facility Line 6.99 70.23 11.54 116.51 128.23 14.51 671.50 224.79 258.07900.00 885.89 323.11 Gas DistributionLandfill * Line 325.73 6.99 442.21 11.54 14.51 469.16 224.792123.18 2200.66 258.07 2264.16 323.11 Well *** 13.30 28.60 14.63 314.87 550.73 349.86 WastewaterLandfill Treatment * † 5.54 325.73 442.21 2.02 469.16 3.22 2123.18 208.97 94.872200.66 134.162264.16 Gas Distribution Line 6.99 11.54 14.51 224.79 258.07 323.11 WastewaterDairy Manure Treatment Lagoon ** † 12.515.54 9.782.02 3.22 10.05 208.97 360.80 192.0994.87 240.00134.16 Landfill * 325.73 442.21 469.16 2123.18 2200.66 2264.16 DairyDairy Manure Digester Lagoon ** 23.96 12.51 28.60 9.78 10.05 24.40 360.80 483.04 550.73 192.09 468.62 240.00 WastewaterControlled ReleaseTreatment † 1.625.54 1.592.02 3.22 0.58 208.97 97.71 67.0894.87 134.16 62.92 Dairy Digester 23.96 28.60 24.40 483.04 550.73 468.62 Dairy* 600 pixel Manure threshold Lagoon for the ** AVIRIS-NG 12.51 image, eight 9.78 pixels for 10.05 the 30 m, and 360.80 four for the 60 192.09 m; ** 2000 240.00 pixel Controlled Release 1.62 1.59 0.58 97.71 67.08 62.92 thresholdDairy for Digester the AVIRIS-NG image, 15 23.96 pixels for the 30 28.60 m, and four 24.40 for the 60 m; 483.04 *** 25 pixel threshold 550.73 for the 468.62 30 m image and four pixels for the 60 m; A 300 ppm-m threshold was used for the 30 m and 60 m images. Controlled* 600 pixel threshold Release for the AVIRIS-NG† 1.62 image, 1.59 eigh t pixels 0.58 for the 30 97.71 m, and four 67.08 for the 60 m. 62.92 * 600 pixel threshold for the AVIRIS-NG image, eight pixels for the 30 m, and four for the 60 m.

Remote Sens. 2019, 11, 3054 16 of 19

Table A3. Mean wind speed and standard deviation for each plume from the High-Resolution Rapid Refresh (HRRR) reanalysis product.

Source Mean Wind Speed (m/s) Standard Deviation Wind Speed (m/s) Gas Storage Facility 1.395 0.430 Pump Jack 3.213 0.348 Pipeline Leak 3.187 3.479 Landfill 3.094 0.267 Wastewater Treatment 2.075 0.423 Dairy Manure Lagoon 2.230 0.602 Dairy Digester 3.637 0.610 Controlled Release 1.959 0.258

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