The Radiance Enhancement (RE) method was introduced for efficient detection of clouds from the space. Recently, we have also reported that due to high reflectance of combustion-originated smokes, this approach can also be generalized for detection of the forest fires by retrieving and analyzing datasets collected from a space orbiting micro-spectrometer operating in the near infrared spectral range. In our previous publication, we have performed a comparison of observed and synthetic radiance spectra by developing a method for computation of surface reflectance consisting of different canopies by weighted sum based on their areal coverage. However, this approach should be justified by a method based on corresponding proportions of the upwelling radiance. The results of computations we performed in this study reveal a good match between areal coverage of canopies and the corresponding proportions of the upwelling radiance due to effect of the instrument slit function.
KeywordsRadiance EnhancementUpwelling RadianceLine-by-Line ComputationRadiative Transfer Model
Buchwitz, M., Rozanov, V.V. and Burrows, J.P. (2000) A Near-Infrared Optimized DOAS Method for the Fast Global Retrieval of Atmospheric CH4, CO, CO2, H2O, and N2O Total Column Amounts from SCIAMACHY Envisat-1 Nadir Radiances. Journal of Geophysical Research, 105, 15231-15245. https://doi.org/10.1029/2000JD900191
Buchwitz, M., de Beek, R., Burrows, J.P., Bovensmann, H., Warneke, T., Notholt, J., Meirink, J.F., Goede, A.P.H., Bergamaschi, P., Körner, S., Heimann M. and Schulz, A. (2005) Atmospheric Methane and Carbon Dioxide from SCIAMACHY Satellite Data: Initial Comparison with Chemistry and Transport Models. Atmospheric Chemistry and Physics, 5, 941-962. https://doi.org/10.5194/acp-5-941-2005
Buchwitz, M., de Beek, R., Noel, S., Burrows, J.P., Bovensmann, H., Bremer, H., Bergamaschi, P., Körner S. and Heimann, M. (2005) Carbon Monoxide, Methane and Carbon Dioxide Columns Retrieved from SCIAMACHY by WFM-DOAS: Year 2003 Initial Data Set. Atmospheric Chemistry and Physics, 5, 3313-3329. https://doi.org/10.5194/acp-5-3313-2005
Bösch, H., Toon, G.C., Sen, B., Washenfelder, R.A., Wennberg, P.O., Buchwitz, M., de Beek, R., Burrows, J.P., Crisp, D., Christi, M., Connor, B.J., Natraj, V. and Yung, Y.L. (2006) Space-Based Near-Infrared CO2 Measurements: Testing the Orbiting Carbon Observatory Retrieval Algorithm and Validation Concept Using SCIAMACHY Observations over Park Falls, Wisconsin. Journal of Geophysical Research, 111, D23302. https://doi.org/10.1029/2006JD007080
Jagpal, R.K., Quine, B.M., Chesser, H., Abrarov S. and Lee, R. (2010) Calibration and In-Orbit Performance of the Argus 1000 Spectrometer—The Canadian Pollution Monitor. Journal of Applied Remote Sensing, 4, Article ID: 049501. https://doi.org/10.1117/1.3302405
Jagpal, R.K. (2011) Calibration and Validation of Argus 1000 Spectrometer—A Canadian Pollution Monitor. PhD Thesis, York University, Toronto. https://doi.org/10.1117/1.3302405
Christopher S.A. and Gupta, P. (2010) Satellite Remote Sensing of Particulate Matter Air Quality: The Cloud-Cover Problem. Journal of the Air & Waste Management Association, 40, 5880-5892. https://doi.org/10.3155/1047-3289.60.5.596
Jagpal, R.K., Siddiqui, R., Abrarov, S.M. and Quine, B.M. (2019) Carbon Dioxide Retrieval of Argus 1000 Space Data by Using GENSPECT Line-by-Line Radiative Transfer Model. Environment and Natural Resources Research, 9, 77-85. https://doi.org/10.5539/enrr.v9n3p77
Siddiqui, R., Jagpal, J., Salem, N.A. and Quine, B.M. (2015) Classification of Cloud Scenes by Argus Spectral Data. International Journal of Space Science and Engineering, 3, 295-311. https://doi.org/10.1504/IJSPACESE.2015.075911
Siddiqui, R., Jagpal, R.K. and Quine, B.M. (2017) Short Wave Upwelling Radiative Flux (SWupRF) within Near Infrared (NIR) Wavelength Bands of O2, H2O, CO2 and CH4 by Argus 1000 Along with GENSPECT Line-Byline Radiative Transfer Model. Canadian Journal of Remote Sensing, 43, 330-344. https://doi.org/10.1080/07038992.2017.1346467
Siddiqui, R. (2017) Efficient Detection of Cloud Scenes by a Space-Orbiting Argus 1000 Micro-Spectrometer. PhD Thesis, York University, Toronto.
Siddiqui, R., Jagpal, R.K. and Abrarov, S.M. and Quine, B.M. (2020) Radiance Enhancement and Shortwave Upwelling Radiative Flux Methods for Efficient Detection of Cloud Scenes. International Journal of Space Science and Engineering, 6, 1-27. https://doi.org/10.1504/IJSPACESE.2020.109745
Siddiqui, R. and Jagpal, R.K., Abrarov, S.M. and Quine, B.M. (2020) A New Approach to Detect Combustion-Originated Aerosols by Using a Cloud Method. AGU Fall Meeting 2020, 1-17 December 2020.
Siddiqui, R., Jagpal, R.K., Abrarov, S.M. and Quine, B.M. (2021) Efficient Application of the Radiance Enhancement Method for Detection of the Forest Fires due to Combustion-Originated Reflectance. Journal of Environmental Protection, 12, 717-733. https://doi.org/10.4236/jep.2021.1210043
Quine, B.M. and Drummond, J.R. (2002) GENSPECT: A Line-by-Line Code with Selectable Interpolation Error Tolerance. Journal of Quantitative Spectroscopy & Radiative Transfer, 74, 147-165. https://doi.org/10.1016/S0022-4073(01)00193-5
Rankin, D., Kekez, D.D., Zee, R.E., Pranajaya, F.M., Foisy D.G. and Beattie, A.M. (2005) The CanX-2 Nanosatellite: Expanding the Science Abilities of Nanosatellites. Acta Astronautica, 57, 167-174. https://doi.org/10.1016/j.actaastro.2005.03.032
Toot, R., Frelich, L.E., Butler, E.E. and Peter, B. (2020) Reich Climate-Biome Envelope Shifts Create Enormous Challenges and Novel Opportunities for Conservation. Forests, 11, 1015. https://doi.org/10.3390/f11091015
Anderson, R.C. (2006) Evolution and Origin of the Central Grassland of North America: Climate, Fire, and Mammalian Grazers. The Journal of the Torrey Botanical Society, 133, 626-647. https://doi.org/10.3159/1095-5674(2006)133[626:EAOOTC]2.0.CO;2
Roberts, Y.L., Pilewskie, P., Kindel, B.C., Feldman, D.R. and Collins, W.D. (2013) Quantitative Comparison of the Variability in Observed and Simulated Shortwave Reflectance. Atmospheric Chemistry and Physics, 13, 3133-3147. https://doi.org/10.5194/acp-13-3133-2013
Li, S., Suna, D., Goldberg, M.D., Sjoberg, B., Santek, D., Hoffman, J.P., DeWeese, M., Restrepo, P., Lindsey, S. and Holloway, E. (2018) Automatic near Realtime Flood Detection Using Suomi-NPP/VIIRS Data. Remote Sensing of Environment, 204, 672-689. https://doi.org/10.1016/j.rse.2017.09.032
MODIS Land. https://modis-land.gsfc.nasa.gov
Baldridge, A.M., Hook, S.J., Grove, C.I. and Rivera, R. (2009) The ASTER Spectral Library Version 2.0. Remote Sensing of Environment, 113, 711-715. https://doi.org/10.1016/j.rse.2008.11.007
Dick, M., Porter, T.J., Pisaric, M.F.J., Wertheimer, è., de Montigny, P., Perreault, J.T. and Robillard, K.-L. (2014) A Multi-Century Eastern White Pine Tree-Ring Chronology Developed from Salvaged River Logs and Its Utility for Dating Heritage Structures in Canada’s National Capital Region. Dendrochronologia, 32, 120-126. https://doi.org/10.1016/j.dendro.2014.02.001
Apadula, F., Cassardo, C., Ferrarese, S., Heltai, D. and Lanza, A. (2019) Thirty Years of Atmospheric CO2 Observations at the Plateau Rosa Station, Italy. Atmosphere, 10, 418. https://doi.org/10.3390/atmos10070418
Karnauskas, K.B., Miller, S.L. and Schapiro, A.C. (2020) Fossil Fuel Combustion Is Driving Indoor CO2 toward Levels Harmful to Human Cognition. Geo-Health, 4, e2019GH000237. https://doi.org/10.1029/2019GH000237
Davidson, C.J., Foster, K.R. and Tanna, R.N. (2020) Forest Health Effects Due to Atmospheric Deposition: Findings from Long-Term Forest Health Monitoring in the Athabasca Oil Sands Region. Science of the Total Environment, 699, Article ID: 134277. https://doi.org/10.1016/j.scitotenv.2019.134277
Tymstra, C., Stocks, B.J., Cai, X. and Flannigan, M.D. (2020) Wildfire Management in Canada: Review, Challenges and Opportunities. Progress in Disaster Science, 5, Article ID: 100045. https://doi.org/10.1016/j.pdisas.2019.100045
Axelson, J.N., Alfaro, R.I. and Hawkes, B.C. (2009) Influence of Fire and Mountain Pine Beetle on the Dynamics of Lodgepole Pine Stands in British Columbia, Canada. Forest Ecology and Management, 257, 1874-1882. https://doi.org/10.1016/j.foreco.2009.01.047
Benali, A., Russo, A., Sà, A.C.L., Pinto, R.M.S., Price, O., Koutsias, N. and Pereira, J.M.C. (2016) Determining Fire Dates and Locating Ignition Points with Satellite Data. Remote Sensing, 8, 326. https://doi.org/10.3390/rs8040326
Google Earth. https://www.google.com/earth
Hill, C., Gordon, I.E., Kochanov, R.V., Barrett, L., Wilzewski, J.S. and Rothman, L.S. (2016) HITRANonline: An Online Interface and the Flexible Representation of Spectroscopic Data in the HITRAN Database. Journal of Quantitative Spectroscopy & Radiative Transfer, 177, 4-14. https://doi.org/10.1016/j.jqsrt.2015.12.012
Abrarov, S.M., Quine, B.M., Siddiqui, R. and Jagpal, R.K. (2019) A Single-Domain Implementation of the Voigt/Complex Error Function by Vectorized Interpolation. Earth Science Research, 8, 52-63. https://doi.org/10.5539/esr.v8n2p52
Abrarov, S.M. and Quine, B.M. (2011) Efficient Algorithmic Implementation of the Voigt/Complex Error Function Based on Exponential Series Approximation. Applied Mathematics and Computation, 218, 1894-1902. https://doi.org/10.1016/j.amc.2011.06.072
Abrarov, S.M., Quine, B.M. and Jagpal, R.K. (2018) A Sampling-Based Approximation of the Complex Error Function and Its Implementation without Poles. Applied Numerical Mathematics, 129, 181-191. https://doi.org/10.1016/j.apnum.2018.03.009
Abrarov, S.M. and Quine, B.M. (2018) A Rational Approximation of the Dawson’s Integral for Efficient Computation of the Complex Error Function. Applied Mathematics and Computation, 321, 526-543. https://doi.org/10.1016/j.amc.2017.10.032
Fomin, B.A. (1995) Effective Interpolation Technique for Line-by-Line Calculations of Radiation Absorption in Gases. Journal of Quantitative Spectroscopy & Radiative Transfer, 53, 663-669. https://doi.org/10.1016/0022-4073(95)00029-K
Sparks, L. (1997) Efficient Line-by-Line Calculation of Absorption Coefficients to High Numerical Accuracy. Journal of Quantitative Spectroscopy & Radiative Transfer, 57, 631-650. https://doi.org/10.1016/S0022-4073(96)00154-9
Beirle, S., Lampel, J., Lerot, C., Sihler, H. and Wagner, T. (2017) Parameterizing the Instrumental Spectral Response Function and Its Changes by a Super-Gaussian and Its Derivatives. Atmospheric Measurement Techniques, 10, 581-598. https://doi.org/10.5194/amt-10-581-2017
Galan, L.D. and Winefordner, J.D. (1968) Slit Function Effects in Atomic Spectroscopy. Spectrochemica Acta B, 23, 277-289. https://doi.org/10.1016/0584-8547(68)80007-2
Röseler, A. (1966) Measurements of the Instrument Function and of the Spectral Slit width of a Prism Spectrometer. Infrared Physics, 6, 111-122. https://doi.org/10.1016/0020-0891(66)90005-4
Edwards, D.P. (1992) GENLN2: A General Line-by-Line Atmospheric Transmittance and Radiance Model, Version 3.0 Description and Users Guide. NCAR/TN-367-STR, National Center for Atmospheric Research, Boulder.
Liou, K.N. (2002) An Introduction to Atmospheric Radiation. 2nd Edition, Academic Press, Cambridge.
Edwards, D.P. (1987) GENLN2: The New Oxford Line-by-Line Atmospheric Transmission/Radiance Model. Dept. of Atmospheric, Oceanic and Planetary Physics, Memorandum 87.2, University of Oxford, Oxford.
Edwards, D.P. (1988) Atmospheric Transmittance and Radiance Calculations Using Line-by-Line Computer Models. Proceedings, Modeling of the Atmosphere, 1988 Technical Symposium on Optics, Electro-Optics, and Sensors, Orlando, Volume 928, 94-116. https://doi.org/10.1117/12.975622
Nordebo, S. (2021) Uniform Error Bounds for Fast Calculation of Approximate Voigt Profiles. Journal of Quantitative Spectroscopy & Radiative Transfer, 270, Article ID: 107715. https://doi.org/10.1016/j.jqsrt.2021.107715
Jallad, A.-H., Marpu, P., Aziz, Z.A., Marar, A.A. and Awad, M. (2019) MeznSat—A 3U Cubesat for Monitoring Greenhouse Gases Using Short Wave Infrared Spectrometry: Mission Concept and Analysis. Aerospace, 6, 118. https://doi.org/10.3390/aerospace6110118