Abril-Salcedo, D. S., Melo-Velandia, L. F., ParraAmado, D. 2020. Nonlinear relationship between the weather phenomenon El niño and Colombian food prices. Australian Journal of Agricultural and Resource Economics, 64(4), 1059-1086. https://doi.org/10.1111/1467-8489.12394
Akagi, S. K., Yokelson, R. J., Wiedinmyer, C., Alvarado, M. J., Reid, J. S., Karl, T., … Wennberg, P. O. 2011. Emission factors for open and domestic biomass burning for use in atmospheric models. Atmospheric Chemistry and Physics, 11(9), 4039-4072. https://doi.org/10.5194/acp-11-4039-2011
Anaya, J. A., Chuvieco, E. 2010. Accuracy assessment of burned area products in the Orinoco basin. American Society for Photogrammetry and Remote Sensing Annual Conference 2010: Opportunities for Emerging Geospatial Technologies, 1(1), 8-17
[+]
Abril-Salcedo, D. S., Melo-Velandia, L. F., ParraAmado, D. 2020. Nonlinear relationship between the weather phenomenon El niño and Colombian food prices. Australian Journal of Agricultural and Resource Economics, 64(4), 1059-1086. https://doi.org/10.1111/1467-8489.12394
Akagi, S. K., Yokelson, R. J., Wiedinmyer, C., Alvarado, M. J., Reid, J. S., Karl, T., … Wennberg, P. O. 2011. Emission factors for open and domestic biomass burning for use in atmospheric models. Atmospheric Chemistry and Physics, 11(9), 4039-4072. https://doi.org/10.5194/acp-11-4039-2011
Anaya, J. A., Chuvieco, E. 2010. Accuracy assessment of burned area products in the Orinoco basin. American Society for Photogrammetry and Remote Sensing Annual Conference 2010: Opportunities for Emerging Geospatial Technologies, 1(1), 8-17
Anaya, J. A., Chuvieco, E., Palacios-Orueta, A. 2009. Aboveground biomass assessment in Colombia: A remote sensing approach. Forest Ecology and Management, 257(4), 1237-1246. https://doi.org/10.1016/j.foreco.2008.11.016
Anaya, J. A., Colditz, R. R., Valencia, G. 2015. Land Cover Mapping of a Tropical Region by Integrating Multi-Year Data into an Annual Time Series. Remote Sensing, 7(12), 16274-16292. https://doi.org/10.3390/rs71215833
Anderson, B. E., Grant, W. B., Gregory, G. L., Browell, E. V., Collins, J. E., Sachse, G. W., … Blake, N. J. 1996. Aerosols from biomass burning over the tropical South Atlantic region: Distributions and impacts. Journal of Geophysical Research: Atmospheres, 101(D19), 24117-24137. https://doi.org/10.1029/96JD00717
Andreae, M. 1991. Biomass burning: its history, use, and distribution and its impact on environmental quality and global climate. In J. Levine (Ed.), MIT Press (pp. 3-21). Cambridge.
Avitabile, V, Herold, M., Heuvelink, G. B. M., Lewis, S. L., Phillips, O. L., Asner, G. P., … Willcock, S. 2015. An integrated pan-tropical biomass map using multiple reference datasets. Global Change Biology, n/a-n/a. https://doi.org/10.1111/gcb.13139
Avitabile, Valerio, Camia, A. 2018. An assessment of forest biomass maps in Europe using harmonized national statistics and inventory plots. Forest Ecology and Management, 409(November 2017), 489-498. https://doi.org/10.1016/j.foreco.2017.11.047
Baccini, a., Goetz, S. J., Walker, W. S., Laporte, N. T., Sun, M., Sulla-Menashe, D., … Houghton, R. a. 2012. Estimated carbon dioxide emissions from tropical deforestation improved by carbondensity maps. Nature Clim. Change, 2(3), 182-185. https://doi.org/10.1038/nclimate1354
Bastarrika, A., Alvarado, M., Artano, K., Martinez, M. P., Mesanza, A., Torre, L., … Chuvieco, E. 2014. BAMS: A Tool for Supervised Burned Area Mapping Using Landsat Data. Remote Sensing, 6, 12360-12380. https://doi.org/10.3390/rs61212360
Bauduin, S., Clarisse, L., Theunissen, M., George, M., Hurtmans, D., Clerbaux, C., Coheur, P. F. 2017. IASI's sensitivity to near-surface carbon monoxide (CO): Theoretical analyses and retrievals on test cases. Journal of Quantitative Spectroscopy and Radiative Transfer, 189, 428-440. https://doi.org/10.1016/j.jqsrt.2016.12.022
BBC. 2019. Amazon fires increase by 84% in one year - space agency - BBC News. BBC. Retrieved from https://www.bbc.com/news/world-latinamerica-49415973
Boschetti, L., Roy, D. P., Giglio, L., Huang, H., Zubkova, M., Humber, M. L. 2019. Global validation of the collection 6 MODIS burned area product. Remote Sensing of Environment, 235(October), 111490. https://doi.org/10.1016/j.rse.2019.111490
Brown, K. 2017. NASA Pinpoints Cause of Earth's Recent Record Carbon Dioxide Spike. National Aeronotics and Space Administration (NASA). Retrieved from http://www.nasa.gov/press-release/ nasa-pinpoints-cause-of-earth-s-recent-recordcarbon-dioxide-spike
Buis, A. 2019. The Atmosphere: Getting a Handle on Carbon Dioxide - Climate Change: Vital Signs of the Planet. Retrieved December 6, 2020, from https://climate.nasa.gov/news/2915/the-atmospheregetting-a-handle-on-carbon-dioxide/
Chave, J., Davies, S. J., Phillips, O. L., Lewis, S. L., Sist, P., Schepaschenko, D., … Saatchi, S. 2019. Ground Data are Essential for Biomass Remote Sensing Missions. Surveys in Geophysics, 40(4), 863-880. https://doi.org/10.1007/s10712-019-09528-w
Chuvieco, E., Mouillot, F., van der Werf, G. R., San Miguel, J., Tanasse, M., Koutsias, N., … Giglio, L. 2019. Historical background and current developments for mapping burned area from satellite Earth observation. Remote Sensing of Environment, 225(November 2018), 45-64. https://doi.org/10.1016/j.rse.2019.02.013
Chuvieco, E., Opazo, S., Sione, W., Del Valle, H., Anaya, J., Di Bella, C., … Libonati, R. 2008. Global burned-land estimation in Latin America using MODIS composite data. Ecological Applications, 18(1), 64-79. https://doi.org/10.1890/06-2148.1
Clerbaux, C., Hadji-Lazaro, J., Turquety, S., George, M., Boynard, A., Pommier, M., … Van Damme, M. 2015. Tracking pollutants from space: Eight years of IASI satellite observation. Comptes Rendus - Geoscience, 347(3), 134-144. https://doi.org/10.1016/j.crte.2015.06.001
Crutzen, P. J., Andreae, M. O. 1990. Biomass Burning in the Tropics: Impact on Atmospheric Chemistry and Biogeochemical Cycles. Science, 250(4988), 1669-1678. https://doi.org/10.1126/science.250.4988.1669
Dammers, E., Palm, M., Van Damme, M., Vigouroux, C., Smale, D., Conway, S., … Erisman, J. W. 2016. An evaluation of IASI-NH3 with ground-based Fourier transform infrared spectroscopy measurements. Atmospheric Chemistry and Physics, 16(16), 10351-10368. https://doi.org/10.5194/acp-16-10351-2016
Edwards, D. P., Emmons, L. K., Hauglustaine, D. a., Chu, D. a., Gille, J. C., Kaufman, Y. J., … Drummond, J. R. 2004. Observations of carbon monoxide and aerosols from the Terra satellite: Northern Hemisphere variability. Journal of Geophysical Research D: Atmospheres, 109(24), 1-17. https://doi.org/10.1029/2004JD004727
EPA. 2019a. Basic Information of Air Emissions Factors and Quantification.
EPA. 2019b. Basic Information of Air EmissionsFactors and Quantification, 2017-2019. Retrieved from https://www.epa.gov/air-emissions-factorsand-quantification/basic-information-air-emissionsfactors-and-quantification
Evangeliou, N., Balkanski, Y., Eckhardt, S., Cozic, A., Van Damme, M., Coheur, P. F., … Hauglustaine, Di. 2021. 10-Year Satellite-Constrained Fluxes of Ammonia Improve Performance of Chemistry Transport Models. Atmospheric Chemistry and Physics, 21(6), 4431-4451. https://doi.org/10.5194/acp-21-4431-2021
Freitas, S. R., Longo, K. M., Alonso, M. F., Pirre, M., Marecal, V., Grell, G., … Sánchez Gácita, M. 2011. PREP-CHEM-SRC - 1.0: a preprocessor of trace gas and aerosol emission fields for regional and global atmospheric chemistry models. Geoscientific Model Development, 4(2), 419-433. https://doi.org/10.5194/gmd-4-419-2011
Fry, M. M., Naik, V., West, J. J., Schwarzkopf, M. D., Fiore, A. M., Collins, W. J., … Zeng, G. 2012. The influence of ozone precursor emissions from four world regions on tropospheric composition and radiative climate forcing. Journal of Geophysical Research Atmospheres, 117(7), 1-16. https://doi.org/10.1029/2011JD017134
Galloway, J. N., Aber, J. D., Erisman, J. W., Seitzinger, S. P., Howarth, R. W., Cowling, E. B., Cosby, B. J. 2003. The Nitrogen Cascade. BioScience, 53(4), 341. https://doi.org/10.1641/0006-3568(2003)053[0341:TNC]2.0.CO;2
Ghasemi, A., Zahediasl, S. 2012. Normality tests for statistical analysis: A guide for non-statisticians. International Journal of Endocrinology and Metabolism, 10(2), 486-489. https://doi.org/10.5812/ijem.3505
Giglio, L., Csiszar, I., Justice, C. O. 2006. Global distribution and seasonality of active fires as observed with the Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. Journal of Geophysical Research, 111(July 1996), 1-12. https://doi.org/10.1029/2005JG000142
Giglio, L., Randerson, J. T., Van Der Werf, G. R. 2013. Analysis of daily, monthly, and annual burned area using the fourth-generation global fire emissions database (GFED4). Journal of Geophysical Research: Biogeosciences, 118(1), 317-328. https://doi.org/10.1002/jgrg.20042
Gray, E. 2019. Satellite Data Record Shows Climate Change's Impact on Fires. Retrieved December 6, 2020, from https://climate.nasa.gov/news/2912/satellite-data-record-shows-climate-changesimpact-on-fires/
Hampel, F. R., Ronchetti, E. M., Rousseeuw, P. J., Stahel, W. A. 1986. Robust Statistics: The Approach Based on Influence Functions. (J. W. & Sons, Ed.). New York.
Huber, P. J., Ronchetti, E. M. 2009. Robust Statistics. (Wiley, Ed.) (2nd ed.). https://doi.org/10.1002/9780470434697
IPCC. 2018. IPCC Special Report on the impacts of global warming of 1.5°C. Ipcc - Sr15. Retrieved from http://www.ipcc.ch/report/sr15/
Jaffe, L. S. 1968. Ambient carbon monoxide and its fate in the atmosphere. Journal of the Air Pollution Control Association, 18(8), 534-540. https://doi.org/10.1080/00022470.1968.10469168
Janssens-Maenhout, G., Dentener, F., Aardenne, J. Van, Monni, S., Pagliari, V., Orlandini, L., … Keating, T. 2012. EDGAR-HTAP: a harmonized gridded air pollution emission dataset based on national inventories. … Office, Ispra (Italy). https://doi.org/10.2788/14102
Janssens-Maenhout, G., Petrescu, A. M. R., Muntean, M., Blujdea, V. 2011. Verifying Greenhouse Gas Emissions: Methods to Support International Climate Agreements. Greenhouse Gas Measurement and Management, 1(2), 132-133. https://doi.org/10.1080/20430779.2011.579358
Jones, M. W., Smith, A., Betts, R., Canadell, J. G., Prentice, I. C., Le Quéré, C. 2020. Climate change increases the risk of wildfires. Rapid Response Review, (March 2013), 2013-2015. Retrieved from https://sciencebrief.org/briefs/wildfires
Kaiser, J. W., Heil, a., Andreae, M. O., Benedetti, a., Chubarova, N., Jones, L., … Van Der Werf, G. R. 2012. Biomass burning emissions estimated with a global fire assimilation system based on observed fire radiative power. Biogeosciences, 9(1), 527-554. https://doi.org/10.5194/bg-9-527-2012
Koenker, R. 1994. Confidence Intervals for Regression Quantiles. In P. Mandl & M. Hušková (Eds.), Asymptotic Statistics (pp. 349-359). https://doi.org/10.1007/978-3-642-57984-4_29
Koenker, R. W. 2005. Quantile Regression. (Cambridge University Press, Ed.). https://doi.org/10.1017/CBO9780511754098
Kumar, S. S., Hult, J., Picotte, J., Peterson, B. 2020. Potential underestimation of satellite fire radiative power retrievals over gas flares and wildland fires. Remote Sensing, 12(2), 10-14. https://doi.org/10.3390/rs12020238
Lamarque, J. F., Bond, T. C., Eyring, V., Granier, C., Heil, a., Klimont, Z., … Van Vuuren, D. P. 2010. Historical (1850-2000) gridded anthropogenic and biomass burning emissions of reactive gases and aerosols: Methodology and application. Atmospheric Chemistry and Physics, 10(15), 7017-7039. https://doi.org/10.5194/acp-10-7017-2010
Langmann, B., Duncan, B., Textor, C., Trentmann, J., van der Werf, G. R. 2009. Vegetation fire emissions and their impact on air pollution and climate. Atmospheric Environment, 43(1), 107-116. https://doi.org/10.1016/j.atmosenv.2008.09.047
Lees, K. J., Quaife, T., Artz, R. R. E., Khomik, M., Clark, J. M. 2018. Potential for using remote sensing to estimate carbon fluxes across northern peatlands - A review. Science of the Total Environment, 615, 857-874. https://doi.org/10.1016/j.scitotenv.2017.09.103
Levine, J. S., Cofer III, W. R., Pinto, J. P. 2001. Chapter 14. Biomass Burning. In Atmospheric methane: source, sinks, and role in Global Change (Vol. 113, pp. 299-313). NATO ASI series. Retrieved from http://earthobservatory.nasa.gov/Features/BiomassBurning/ https://doi.org/10.1007/978-3-642-84605-2_14
Libonati, R., DaCamara, C., Setzer, A. W., Morelli, F., Melchiori, A. E., Cândido, P. de A., Jesús, S. C. de. 2015. Validating MODIS burned area products over Cerrado region. In XVII Simpósio Brasileiro de Sensoriamento Remoto - SBSR (pp. 6381-6388).
Limpert, E., Stahel, W. A. 2011. Problems with using the normal distribution - and ways to improve quality and efficiency of data analysis. PLoS ONE, 6(7). https://doi.org/10.1371/journal.pone.0021403
Liu, Y. Y., van Dijk, A. I. J. M., de Jeu, R. a M., Canadell, J. G., McCabe, M. F., Evans, J. P., Wang, G. 2015. Recent reversal in loss of global terrestrial biomass. Nature Climate Change, 5(May), 1-5. https://doi.org/10.1038/nclimate2581
Löndahl, J., Swietlicki, E., Lindgren, E., Loft, S. 2010. Aerosol exposure versus aerosol cooling of climate: What is the optimal emission reduction strategy for human health? Atmospheric Chemistry and Physics, 10(19), 9441-9449. https://doi.org/10.5194/acp-10-9441-2010
Longo, K. M., Freitas, S. R., Andreae, M. O., Setzer, a., Prins, E., Artaxo, P. 2010. The Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS) - Part 2: Model sensitivity to the biomass burning inventories. Atmospheric Chemistry and Physics, 10(13), 5785-5795. https://doi.org/10.5194/acp-10-5785-2010
Malhi, Y., Rowland, L., Aragão, L. E. O. C., Fisher, R. A. 2018. New insights into the variability of the tropical land carbon cycle from the El Niño of 2015/2016. Philosophical Transactions of the Royal Society B: Biological Sciences, 373(1760). https://doi.org/10.1098/rstb.2017.0298
Masek, J.., Vermote, E. F., Saleous, N. E., Wolfe, R., Hall, F. G., Huemmrich, K. F., … Lim, T. 2006. A Landsat Surface Reflectance Dataset for North America, 1990-2000. IEEE Geoscience and Remote Sensing Letters, 3(1), 68-72. https://doi.org/10.1109/LGRS.2005.857030
Masek, J.., Vermote, E. F., Saleous, N., Wolfe, R., Hall, F. G., Huemmrich, F., … Lim, T. K. 2013. LEDAPS Calibration, Reflectance, Atmospheric Correction Preprocessing Code. Oak Ridge National Laboratory Distributed Active Archive Center. Tennessee, U.S.A. https://doi.org/10.3334/ORNLDAAC/1146
Mavroidis, I., Chaloulakou, a. 2011. Long-term trends of primary and secondary NO2 production in the Athens area. Variation of the NO2/NOx ratio. Atmospheric Environment, 45(38), 6872-6879. https://doi.org/10.1016/j.atmosenv.2010.11.006
Mieville, a., Granier, C., Liousse, C., Guillaume, B., Mouillot, F., Lamarque, J.-F., … Pétron, G. 2010. Emissions of gases and particles from biomass burning during the 20th century using satellite data and an historical reconstruction. Atmospheric Environment, 44(11), 1469-1477. https://doi.org/10.1016/j.atmosenv.2010.01.011
Monks, P. S., Granier, C., Fuzzi, S., Stohl, A., Williams, M. L., Akimoto, H., … von Glasow, R. 2009. Atmospheric composition change - global and regional air quality. Atmospheric Environment, 43(33), 5268-5350. https://doi.org/10.1016/j.atmosenv.2009.08.021
Moreira, D. S., Freitas, S. R., Bonatti, J. P., Mercado, L. M., Rosário, N. M. É., Longo, K. M., …Gatti, L. V. 2013. Coupling between the JULES land-surface scheme and the CCATT-BRAMS atmospheric chemistry model (JULES-CCATTBRAMS1.0): applications to numerical weather forecasting and the CO2 budget in South America. Geoscientific Model Development, 6(4), 1243-1259. https://doi.org/10.5194/gmd-6-1243-2013
Mouillot, F., Schultz, M. G., Yue, C., Cadule, P., Tansey, K., Ciais, P., Chuvieco, E. 2014. Ten years of global burned area products from spaceborne remote sensing-A review: Analysis of user needs and recommendations for future developments. International Journal of Applied Earth Observation and Geoinformation, 26(1), 64-79. https://doi.org/10.1016/j.jag.2013.05.014
Opazo, S., Chuvieco, E. 2013. Análisis geográfico de áreas quemadas en Sudamérica. Geofocus, 13(2), 1-24. https://doi.org/10.1104/pp.104.051110.3582
Padilla, M., Olofsson, P., Stehman, S. V, Tansey, K., Chuvieco, E. 2017. Stratification and sample allocation for reference burned area data. Remote Sensing of Environment, 203, 240-255. https://doi.org/10.1016/j.rse.2017.06.041
Padilla, M., Stehman, S. V., Chuvieco, E. 2014. Validation of the 2008 MODIS-MCD45 global burned area product using stratified random sampling. Remote Sensing of Environment, 144, 187-196. https://doi.org/10.1016/j.rse.2014.01.008
Padilla, M., Stehman, S. V., Ramo, R., Corti, D., Hantson, S., Oliva, P., … Chuvieco, E. 2015. Comparing the accuracies of remote sensing global burned area products using stratified random sampling and estimation. Remote Sensing of Environment, 160(April), 114-121. https://doi.org/10.1016/j.rse.2015.01.005
Palmer, P. I., Feng, L., Baker, D., Chevallier, F., Bösch, H., Somkuti, P. 2019. Net carbon emissions from African biosphere dominate pan-tropical atmospheric CO2 signal. Nature Communications, 10(1), 1-9. https://doi.org/10.1038/s41467-019-11097-w
Palomino, S., Anaya, J. A. 2012. Evaluation of the Causes of Error in the Mcd45 Burned-Area Product for the Savannas of Northern South America. DynaColombia, 79(176), 35-44.
Pierre-Louis, K. 2019. The Amazon, Siberia, Indonesia: A World of Fire. The New York Times. Retrieved from https://www.nytimes.com/2019/08/28/climate/fire-amazon-africa-siberia-worldwide.html
Portnoy, S., Koenker, R. 1997. The Gaussian hare and the Laplacian tortoise: computability of squarederror versus absolute-error estimators, 279-300. https://doi.org/10.1214/ss/1030037960
Prosperi, P., Bloise, M., Tubiello, F. N., Conchedda, G., Rossi, S., Boschetti, L., … Bernoux, M. 2020. New estimates of greenhouse gas emissions from biomass burning and peat fires using MODIS Collection 6 burned areas. Climatic Change, 161(3), 415-432. https://doi.org/10.1007/s10584-020-02654-0
Rodriguez-Montellano, A., Libonati, R., Melchiori, E. 2015. Sensibilidad en la detección de áreas quemadas en tres ecosistemas vegetales de Bolivia, utilizando tres productos regionales. In XVII Simpósio Brasileiro de Sensoriamento Remoto - SBSR (Vol. 1, pp. 1663-1670).
Rodríguez-Veiga, P., Wheeler, J., Louis, V., Tansey, K., Balzter, H. 2017. Quantifying Forest Biomass Carbon Stocks From Space. Current Forestry Reports, 3, 1-18. https://doi.org/10.1007/s40725-017-0052-5
Rousseeuw, P. J., Huber, M. 1997. Recent developments in PROGRESS. In L1-Statistical Procedures and Related Topics. Dodge, IMS Lecture Notes, 31, 201-214. https://doi.org/10.1214/lnms/1215454138
Rousseeuw, P. J., Leroy, A. M. 2005. Robust Regression and Outlier Detection. (John Wiley & Sons, Ed.). Wiley. Retrieved from https://books.google.com.co/books?id=woaH_73s-MwC
Saatchi, S. S., Harris, N. L., Brown, S., Lefsky, M., Mitchard, E. T. A., Salas, W., … Morel, A. 2011. Benchmark map of forest carbon stocks in tropical regions across three continents. Proceedings of the National Academy of Sciences of the United States of America, 108(24), 9899-904. https://doi.org/10.1073/pnas.1019576108
Santoro, M., Beaudoin, A., Beer, C., Cartus, O., Fransson, J. E. S., Hall, R. J., … Wegmüller, U. 2015. Forest growing stock volume of the northern hemisphere: Spatially explicit estimates for 2010 derived from Envisat ASAR. Remote Sensing of Environment, 168, 316-334. https://doi.org/10.1016/j.rse.2015.07.005
Seiler, W., Crutzen, P. J. 1980. Estimates of gross and net fluxes of carbon between the biosphere and the atmosphere from biomass burning. Climatic Change, 2(3), 207-247. https://doi.org/10.1007/BF00137988
Shi, Y., Matsunaga, T., Saito, M., Yamaguchi, Y., Chen, X. 2015. Comparison of global inventories of CO2 emissions from biomass burning during 2002-2011 derived from multiple satellite products. Environmental Pollution, 206, 479-487. https://doi.org/10.1016/j.envpol.2015.08.009
Shi, Y., Matsunaga, T., Yamaguchi, Y. 2015. HighResolution Mapping of Biomass Burning Emissions in Three Tropical Regions. Environmental Science and Technology, 49(18), 10806-10814. https://doi.org/10.1021/acs.est.5b01598
Simões Amaral, S., Andrade de Carvalho, J., Martins Costa, M., Pinheiro, C. 2016. Particulate Matter Emission Factors for Biomass Combustion. Atmosphere, 7(11), 141. https://doi.org/10.3390/atmos7110141
Solaun, K., Sopelana, A., Arraibi, E., Pérez, M. 2014. Series CO2: Black Carbon y sus efectos en el clima. Factor CO2, 52. Retrieved from https://www.factorco2.com/comun/docs/131-Series%20CO2_Black%20Carbon_Factor%20CO2_20140613.pdf
Stahl, S. 2014. Evolution of the Normal Distribution. In Mathematics magazine (pp. 96-113). Retrieved from https://www.maa.org/sites/default/files/pdf/upload_library/22/Allendoerfer/stahl96.pdf https://doi.org/10.1080/0025570X.2006.11953386
Tie, X., Chandra, S., Ziemke, J. R., Granier, C., Brasseur, G. P. 2007. Satellite measurements of tropospheric column O3 and NO 2 in eastern and southeastern asia: Comparison with a global model (MOZART-2). Journal of Atmospheric Chemistry, 56(2), 105-125. https://doi.org/10.1007/s10874-006-9045-7
Urbanski, S. P., Hao, W. M., Nordgren, B. 2011. The wildland fire emission inventory: Western United States emission estimates and an evaluation of uncertainty. Atmospheric Chemistry and Physics, 11(24), 12973-13000. https://doi.org/10.5194/acp-11-12973-2011
Valencia, G. M., Anaya, J. A., Caro-Lopera, F. J. 2016. Implementación y evaluación del modelo Landsat Ecosystem Disturbance Adaptive Processing System ( LEDAPS ): estudio de caso en los Andes colombianos. Revista de Teledetección, 46(46), 83-101. https://doi.org/10.4995/raet.2016.3582
Valencia, G. M., Anaya, J. A., Ramo, R., Velásquez, É. A., Francisco, J. 2020a. About ValidationComparison of Burned Area Products. Remote Sensing, 12(2018), 1-39. https://doi.org/10.3390/rs12233972
van der Werf, G. R., Randerson, J. T., Giglio, L., Leeuwen, T. T. Van, Chen, Y., Collatz, G. J., … Kasibhatla, P. S. 2017. Global fire emissions estimates during 1997 - 2016. Earth System Science Data, 9, 697-720. https://doi.org/10.5194/essd-9-697-2017
Vasconcelos, S. S. De, Fearnside, P. M., Graça, P. M. L. D. A., Nogueira, E. M., Oliveira, L. C. De, Figueiredo, E. O. 2013. Forest fires in southwestern Brazilian Amazonia: Estimates of area and potential carbon emissions. Forest Ecology and Management, 291, 199-208. https://doi.org/10.1016/j.foreco.2012.11.044
Voiland, A. 2015. Fourteen years of carbon monoxide from MOPITT - Climate Change: Vital Signs of the Planet. Retrieved December 6, 2020, from https://climate.nasa.gov/news/2291/fourteen-years-ofcarbon-monoxide-from-mopitt/
von Bobrutzki, K., Braban, C., Famulari, D., Jones, S., Blackall, T., Smith, T. E. L., … Nemitz, E. 2010. Field inter-comparison of eleven atmospheric ammonia measurement techniques, 91-112. https://doi.org/10.5194/amtd-2-1783-2009
Whitburn, S., Van Damme, M., Kaiser, J. W. W., Van Der Werf, G. R. R., Turquety, S., Hurtmans, D., … Coheur, P.-F. F. 2014. Ammonia emissions in tropical biomass burning regions: Comparison between satellite-derived emissions and bottom-up fire inventories. Atmospheric Environment, 121, 42-54. https://doi.org/10.1016/j.atmosenv.2015.03.015
Whitburn, Simon, Van Damme, M., Clarisse, L., Hurtmans, D., Clerbaux, C., Coheur, P. F. 2017. IASIderived NH3 enhancement ratios relative to CO for the tropical biomass burning regions. Atmospheric Chemistry and Physics, 17(19), 12239-12252. https://doi.org/10.5194/acp-17-12239-2017
Wiedinmyer, C., Akagi, S. K., Yokelson, R. J., Emmons, L. K., Al-Saadi, J. A., Orlando, J. J., Soja, A. J. 2011. The Fire INventory from NCAR (FINN) - a high resolution global model to estimate the emissions from open burning. Geoscientific Model Development Discussions, 3(4), 2439-2476. https://doi.org/10.5194/gmdd-3-2439-2010
Williams, A. P., Abatzoglou, J. T., Gershunov, A., Guzman-Morales, J., Bishop, D. A., Balch, J. K., Lettenmaier, D. P. 2019. Observed Impacts of Anthropogenic Climate Change on Wildfire in California. Earth's Future, 7(8), 892-910. https://doi.org/10.1029/2019EF001210
Yang, J., Gong, P., Fu, R., Zhang, M., Chen, J., Liang, S., … Dickinson, R. 2013. The role of satellite remote sensing in climate change studies. Nature Climate Change, 3(10), 875-883. https://doi.org/10.1038/nclimate1908
YuSheng, S., Matsunaga, T., Yamaguchi, Y. 2015. High-resolution mapping of biomass burning emissions in three tropical regions. Environmental Science & Technology, 49(18), 10806-10814. https://doi.org/10.1021/acs.est.5b01598
Zuluaga, O., Patiño, J. E., Valencia, G. M. 2021. Modelos implementados en el análisis de series de tiempo de temperatura superficial e índices de vegetación: una propuesta taxonómica en el contexto de cambio climático global. Revista de Geografía Norte Grande, 78, 323-344. https://doi.org/10.4067/S0718-34022021000100323
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