About validation-comparison of burned area products

This paper proposes a validation-comparison method for burned area (BA) products. The technique considers: (1) bootstrapping of scenes for validation-comparison and (2) permutation tests for validation. The research focuses on the tropical regions of Northern Hemisphere South America and Northern He...

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Fecha de publicación:: 2020

Institución:: Universidad de Medellín

Repositorio:: Repositorio UDEM

Idioma:: eng

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network_acronym_str	REPOUDEM2
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repository_id_str
dc.title.none.fl_str_mv	About validation-comparison of burned area products
title	About validation-comparison of burned area products
spellingShingle	About validation-comparison of burned area products Bootstrap Fire-CCI MCD45 MCD64 Permutation test Random matrix theory Riemannian distance Robust statistics Validation and comparison of BA products Random variables Burned biomass Comparison methods Northern Hemispheres Permutation tests Procrustes distance Random matrix theory Research focus Tropical regions Fires
title_short	About validation-comparison of burned area products
title_full	About validation-comparison of burned area products
title_fullStr	About validation-comparison of burned area products
title_full_unstemmed	About validation-comparison of burned area products
title_sort	About validation-comparison of burned area products
dc.subject.spa.fl_str_mv	Bootstrap Fire-CCI MCD45 MCD64 Permutation test Random matrix theory Riemannian distance Robust statistics Validation and comparison of BA products
topic	Bootstrap Fire-CCI MCD45 MCD64 Permutation test Random matrix theory Riemannian distance Robust statistics Validation and comparison of BA products Random variables Burned biomass Comparison methods Northern Hemispheres Permutation tests Procrustes distance Random matrix theory Research focus Tropical regions Fires
dc.subject.keyword.eng.fl_str_mv	Random variables Burned biomass Comparison methods Northern Hemispheres Permutation tests Procrustes distance Random matrix theory Research focus Tropical regions Fires
description	This paper proposes a validation-comparison method for burned area (BA) products. The technique considers: (1) bootstrapping of scenes for validation-comparison and (2) permutation tests for validation. The research focuses on the tropical regions of Northern Hemisphere South America and Northern Hemisphere Africa and studies the accuracy of the BA products: MCD45, MCD64C5.1, MCD64C6, Fire CCI C4.1, and Fire CCI C5.0. The first and second parts consider methods based on random matrix theory for zone differentiation and multiple ancillary variables such as BA, the number of burned fragments, ecosystem type, land cover, and burned biomass. The first method studies the zone effect using bootstrapping of Riemannian, full Procrustes, and partial Procrustes distances. The second method explores the validation by using distance permutation tests under uncertainty. The results refer to Fire CCI 5.0 with the best BA description, followed by MCD64C6, MCD64C5.1, MCD45, and Fire CCI 4.1. It was also found that biomass, total BA, and the number of fragments affect the BA product accuracy. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
publishDate	2020
dc.date.accessioned.none.fl_str_mv	2021-02-05T14:57:52Z
dc.date.available.none.fl_str_mv	2021-02-05T14:57:52Z
dc.date.none.fl_str_mv	2020
dc.type.eng.fl_str_mv	Article
dc.type.coarversion.fl_str_mv	http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.coar.fl_str_mv	http://purl.org/coar/resource_type/c_6501 http://purl.org/coar/resource_type/c_2df8fbb1
dc.type.driver.none.fl_str_mv	info:eu-repo/semantics/article
dc.identifier.issn.none.fl_str_mv	20724292
dc.identifier.uri.none.fl_str_mv	http://hdl.handle.net/11407/5913
dc.identifier.doi.none.fl_str_mv	10.3390/rs12233972
identifier_str_mv	20724292 10.3390/rs12233972
url	http://hdl.handle.net/11407/5913
dc.language.iso.none.fl_str_mv	eng
language	eng
dc.relation.isversionof.none.fl_str_mv	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097313286&doi=10.3390%2frs12233972&partnerID=40&md5=7818b3c2a39f4e9d5e8526801e8617da
dc.relation.citationvolume.none.fl_str_mv	12
dc.relation.citationissue.none.fl_str_mv	23
dc.relation.citationstartpage.none.fl_str_mv	1
dc.relation.citationendpage.none.fl_str_mv	23
dc.relation.references.none.fl_str_mv	Van Der Werf, G.R., Randerson, J.T., Giglio, L., Collatz, G.J., Mu, M., Kasibhatla, P., Morton, D.C., Van Leeuwen, T.T., Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997–2009) (2010) Atmos. Chem. Phys. Discuss, 10, pp. 11707-11735. , [CrossRef] Padilla-Parellada, M., Stehman, S., Ramo, R., Corti, D., Hantson, S., Oliva, P., Alonso-Canas, I., Mota, B.W., Comparing the accuracies of remote sensing global burned area products using stratified random sampling and estimation (2015) Remote. Sens. Environ, 160, pp. 114-121. , [CrossRef] Giglio, L., Randerson, J.T., Van Der Werf, G.R., Analysis of daily, monthly, and annual burned area using the fourth-generation global fire emissions database (GFED4) (2013) J. Geophys. Res. Biogeosci, 118, pp. 317-328. , [CrossRef] Giglio, L., Boschetti, L., Roy, D.P., Humber, M.L., Justice, C., The Collection 6 MODIS burned area mapping algorithm and product (2018) Remote Sens. Environ, 217, pp. 72-85. , [CrossRef] [PubMed] Anaya-Acevedo, J.A., Colditz, R.R., Valencia, G.M., Land Cover Mapping of a Tropical Region by Integrating Multi-Year Data into an Annual Time Series (2015) Remote Sens, 7, pp. 16274-16292. , [CrossRef] Randerson, J.T., Chen, Y., Van Der Werf, G.R., Rogers, B.M., Morton, D.C., Global burned area and biomass burning emissions from small fires (2012) J. Geophys. Res. Space Phys, 117. , [CrossRef] Juárez-Orozco, S.M., Siebe, C., Fernández, D.F.Y., Causes and Effects of Forest Fires in Tropical Rainforests: A Bibliometric Approach (2017) Trop. Conserv. Sci, 10. , [CrossRef] Giglio, L., Randerson, J.T., Van Der Werf, G.R., Kasibhatla, P., Collatz, G.J., Morton, D.C., DeFries, R.S., Assessing variability and long-term trends in burned area by merging multiple satellite fire products (2010) Biogeosciences, 7, pp. 1171-1186. , [CrossRef] Chuvieco, E., Lizundia-Loiola, J., Pettinari, M.L., Ramo, R., Padilla, M., Tansey, K., Mouillot, F., Heil, A., Generation and analysis of a new global burned area product based on MODIS 250 m reflectance bands and thermal anomalies (2018) Earth Syst. Sci. Data, 10, pp. 2015-2031. , [CrossRef] Avitabile, V., Herold, M., Heuvelink, G.B.M., Lewis, S.L., Phillips, O.L., Asner, G.P., Armston, J.D., Bayol, N., An integrated pan-tropical biomass map using multiple reference datasets (2016) Glob. Chang. Boil, 22, pp. 1406-1420. , [CrossRef] Hu, T., Su, Y., Xue, B., Liu, J., Zhao, X., Fang, J., Guo, Q., Mapping Global Forest Aboveground Biomass with Spaceborne LiDAR, Optical Imagery, and Forest Inventory Data (2016) Remote Sens, 8, p. 565. , [CrossRef] Rodríguez-Veiga, P., Wheeler, J., Louis, V., Tansey, K., Balzter, H., Quantifying Forest Biomass Carbon Stocks From Space (2017) Curr. Rep, 3, pp. 1-18. , [CrossRef] Van Der Werf, G.R., Randerson, J.T., Giglio, L., Van Leeuwen, T.T., Chen, Y., Rogers, B.M., Marle, M., James, G., Global fire emissions estimates during 1997–2016 (2017) Earth Syst. Sci. Data, 9, pp. 697-720. , [CrossRef] Van Marle, M., Kloster, S., Magi, B.I., Marlon, J., Daniau, A.-L., Field, R.D., Arneth, A., Kehrwald, N.M., Historic global biomass burning emissions for CMIP6 (BB4CMIP) based on merging satellite observations with proxies and fire models (1750–2015) (2017) Geosci. Model. Dev, 10, pp. 3329-3357. , [CrossRef] Padilla, M., Stehman, S.V., Chuvieco, E., Validation of the 2008 MODIS-MCD45 global burned area product using stratified random sampling (2014) Remote Sens. Environ, 144, pp. 187-196. , [CrossRef] Boschetti, L., Stehman, S.V., Roy, D.P., A stratified random sampling design in space and time for regional to global scale burned area product validation (2016) Remote Sens. Environ, 186, pp. 465-478. , [CrossRef] Armenteras, D., Gibbes, C., Anaya-Acevedo, J.A., Dávalos, L.M., Integrating remotely sensed fires for predicting deforestation for REDD+ (2017) Ecol. Appl, 27, pp. 1294-1304. , [CrossRef] Andela, N., Van Der Werf, G.R., Kaiser, J.W., Van Leeuwen, T.T., Wooster, M.J., Lehmann, C., Biomass burning fuel consumption dynamics in the tropics and subtropics assessed from satellite (2016) Biogeosciences, 13, pp. 3717-3734. , [CrossRef] Santana, L.D., Ribeiro, J.H.C., Berg, E.V.D., Carvalho, F.A., Impact on soil and tree community of a threatened subtropical phytophysiognomy after a forest fire (2020) Folia Geobot. Et Phytotaxon, , [CrossRef] Chu, T., Guo, X., Remote Sensing Techniques in Monitoring Post-Fire Effects and Patterns of Forest Recovery in Boreal Forest Regions: A Review (2013) Remote Sens, 6, pp. 470-520. , [CrossRef] Palomino, S., Anaya, J.A., Evaluation of the Causes of Error in the Mcd45 Burned-Area Product for the Savannas of Northern South America (2012) Dyna Colomb, 79, pp. 35-44 Roy, D., Boschetti, L., Justice, C.O., Ju, J., The collection 5 MODIS burned area product—Global evaluation by comparison with the MODIS active fire product (2008) Remote Sens. Environ, 112, pp. 3690-3707. , [CrossRef] Congalton, R.G., Green, K., (2009) Assessing the Accuracy of Remotely Sensed Data: Principles and Practices, , 2nd ed. Lewis Publishers: Sound Parkway-Boca Raton, FL, USA Boschetti, L., Roy, D.P., Justice, C.O., (2010) CEOS International Global Burned Area Satellite Product Validation Protocol, Part I—Production and Standardization of Validation Reference Data, , https://lpvs.gsfc.nasa.gov/PDF/BurnedAreaValidationProtocol.pdf, (accessed on 7 March 2019) Schepers, L., Haest, B., Veraverbeke, S., Spanhove, T., Borre, J.V., Goossens, R., Burned Area Detection and Burn Severity Assessment of a Heathland Fire in Belgium Using Airborne Imaging Spectroscopy (APEX) (2014) Remote Sens, 6, pp. 1803-1826. , [CrossRef] Nogueira, J., Ruffault, J., Chuvieco, E., Mouillot, F., Can We Go Beyond Burned Area in the Assessment of Global Remote Sensing Products with Fire Patch Metrics? (2016) Remote Sens, 9, p. 7. , [CrossRef] Singh, G., (2008) A Multi-Sensor Approach For. Burned Area Extraction Due to Crop. Residue Burning Using Multi-Temporal Satellite Data, , http://www.iirs.gov.in/iirs/sites/default/files/StudentThesis/gurdeep.pdf, Degre of Master of Science in Geo-information Science and Earth Observation, ITC Netherlands and IIRS India. (accessed on 21 May 2019) Long, T., Zhang, Z., He, G., Jiao, W., Tang, C., Wu, B., Zhang, X., Yin, R., 30 m Resolution Global Annual Burned Area Mapping Based on Landsat Images and Google Earth Engine (2019) Remote Sens, 11, p. 489. , [CrossRef] Roy, D.P., Frost, P.G.H., Justice, C.O., Landmann, T., Le Roux, J.L., Gumbo, K., Makungwa, S., Mhwandagara, K., The Southern Africa Fire Network (SAFNet) regional burned-area product-validation protocol (2005) Int. J. Remote Sens, 26, pp. 4265-4292. , [CrossRef] Roy, D., Boschetti, L., Southern Africa Validation of the MODIS, L3JRC, and GlobCarbon Burned-Area Products (2009) IEEE Trans. Geosci. Remote Sens, 47, pp. 1032-1044. , [CrossRef] De Santis, A., Chuvieco, E., Vaughan, P.J., Short-term assessment of burn severity using the inversion of PROSPECT and GeoSail models (2009) Remote Sens. Environ, 113, pp. 126-136. , [CrossRef] Negri, J.A., (2016) Evaluation and Validation of Multiple Predictive Models Applied to Post-Wildfire Debris-Flow Hazards, , https://mountainscholar.org/handle/11124/170086?show=full, Degree of Master of Science (Geological Engineering), Colorado School of Mines. (accessed on 8 August 2020) Ghasemi, A., Zahediasl, S., Normality Tests for Statistical Analysis: A Guide for Non-Statisticians (2012) Int. J. Endocrinol. Metab, 10, pp. 486-489. , [CrossRef] Limpert, E., Stahel, W.A., Problems with Using the Normal Distribution—And Ways to Improve Quality and Efficiency of Data Analysis (2011) PLoS ONE, 6, p. e21403. , [CrossRef] Stahl, S., Evolution of the Normal Distribution (2014) Mathematics Magazine, pp. 96-113. , Taylor & Francis: Beloit, WI, USA Faraway, J.J., (2005) Linear Models with R Texts in Statistical Science Series, , Chapman & Hall/CRC: Boca Raton, FL, USA Roteta, E., Bastarrika, A., Padilla, M., Storm, T., Chuvieco, E., Development of a Sentinel-2 burned area algorithm: Generation of a small fire database for sub-Saharan Africa (2019) Remote Sens. Environ, 222, pp. 1-17. , [CrossRef] Roy, D.P., Huang, H., Boschetti, L., Giglio, L., Yan, L., Zhang, H.K., Li, Z., Landsat-8 and Sentinel-2 burned area mapping—A combined sensor multi-temporal change detection approach (2019) Remote Sens. Environ, 231, p. 111254. , [CrossRef] Boschetti, L., Roy, D.P., Giglio, L., Huang, H., Zubkova, M., Humber, M.L., Global validation of the collection 6 MODIS burned area product (2019) Remote Sens. Environ, 235, p. 111490. , [CrossRef] [PubMed] Valencia, G.M., Anaya-Acevedo, J.A., Caro-Lopera, F.J., Implementación y evaluación del modelo Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS): Estudio de caso en los Andes colombianos (2016) Rev. Teledetección, 46, p. 83. , [CrossRef] Cook, J.R., Stefanski, L.A., Simulation-Extrapolation Estimation in Parametric Simulation-Extrapolation Estimation in Parametric Measurement Error Models (1994) J. Am. Stat. Assoc, 89, pp. 1314-1328. , [CrossRef] Giglio, L., Csiszar, I., Justice, C.O., Global distribution and seasonality of active fires as observed with the Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) sensors (2006) J. Geophys. Res. Space Phys, 111, pp. 1-12. , [CrossRef] Alvarado, S.T., Fornazari, T., Costola, A., Morellato, L.P.C., Silva, T., Drivers of fire occurrence in a mountainous Brazilian cerrado savanna: Tracking long-term fire regimes using remote sensing (2017) Ecol. Indic, 78, pp. 270-281. , [CrossRef] Alvarado, S.T., Silva, T., Archibald, S.A., Management impacts on fire occurrence: A comparison of fire regimes of African and South American tropical savannas in different protected areas (2018) J. Environ. Manag, 218, pp. 79-87. , [CrossRef] Dong, X., Fu, J.S., Huang, K., Lin, N.-H., Wang, S.-H., Yang, C.-E., Analysis of the Co-existence of Long-range Transport Biomass Burning and Dust in the Subtropical West Pacific Region (2018) Sci. Rep, 8, p. 8962. , [CrossRef] Hurteau, M.D., Liang, S., Westerling, A.L., Wiedinmyer, C., Vegetation-fire feedback reduces projected area burned under climate change (2019) Sci. Rep, 9, p. 2838. , [CrossRef] Kettridge, N., Lukenbach, M., Hokanson, K., Hopkinson, C., Devito, K., Petrone, R., Mendoza, C., Waddington, J.M., Extreme wildfire exposes remnant peat carbon stocks to increased post-fire drying (2018) Proceedings of the 20th EGU General Assembly Conference Abstracts EGU2018, 20, p. 8399. , Vienna, Austria, 4–13 April Mouillot, F., Schultz, M.G., Yue, C., Cadule, P., Tansey, K., Ciais, P., Chuvieco, E., Ten years of global burned area products from spaceborne remote sensing—A review: Analysis of user needs and recommendations for future developments (2014) Int. J. Appl. Earth Obs. Geoinf, 26, pp. 64-79. , [CrossRef] Giglio, L., Van Der Werf, G.R., Randerson, J.T., Collatz, G.J., Kasibhatla, P., Global estimation of burned area using MODIS active fire observations (2005) Atmos. Chem. Phys. Discuss, 5, pp. 11091-11141. , [CrossRef] Bastarrika, A., Alvarado, M., Artano, K., Martínez, M.P., Mesanza-Moraza, A., Torre-Tojal, L., Ramo, R., Chuvieco, E., BAMS: A Tool for Supervised Burned Area Mapping Using Landsat Data (2014) Remote Sens, 6, pp. 12360-12380. , [CrossRef] Masek, J.G., Vermote, E.F., Saleous, N.E., Wolfe, R., Hall, F.G., Huemmrich, K.F., Gao, F., Lim, T.K., A Landsat Surface Reflectance Dataset for North America, 1990–2000 (2006) IEEE Geosci. Remote Sens. Lett, 3, pp. 68-72. , [CrossRef] Claverie, M., Vermote, E., Franch, B., Masek, J.G., Evaluation of the Landsat-5 TM and Landsat-7 ETM+ surface reflectance products (2015) Remote Sens. Environ, 169, pp. 390-403. , [CrossRef] Chuvieco, E., Yue, C., Heil, A., Mouillot, F., Alonso-Canas, I., Padilla, M., Pereira, J.M.C., Tansey, K., A new global burned area product for climate assessment of fire impacts (2016) Glob. Ecol. Biogeogr, 25, pp. 619-629. , [CrossRef] Olson, D.M., Dinerstein, E., Wikramanayake, E.D., Burgess, N.D., Powell, G.V., Underwood, E.C., D’amico, J.A., Morrison, J.C., Terrestrial Ecoregions of the World: A New Map of Life on Earth (2001) Bioscience, 51, pp. 933-938. , [CrossRef] (2017) Land Cover CCI Product User Guide Version 2, , http://maps.elie.ucl.ac.be/CCI/viewer/download/ESACCI-LC-Ph2-PUGv2_2.0.pdf, ESA. Tech. Rep. (accessed on 8 August 2020) Dryden, I.L., Mardia, K.V., (2016) Statistical Shape Analysis, with Applications in R, , Wiley: Chichester, West Sussex, UK Quintero, J.H., Mariño, A., Šiller, L., Restrepo-Parra, E., Caro-Lopera, F., Rocking curves of gold nitride species prepared by arc pulsed—Physical assisted plasma vapor deposition (2017) Surf. Coat. Technol, 309, pp. 249-257. , [CrossRef] Arias, E., Caro-Lopera, F.J., Florez, E., Pérez-Torres, J.F., Two Novel Approaches Based on the Thompson Theory and Shape Analysis for Determination of Equilibrium Structures of Nanoclusters: Cu8, Ag8 and Ag18 as study cases (2019) J. Phys. Conf. Ser, 1247, p. 012008. , [CrossRef] Villarreal-Rios, A.L., Calle, A.H.B., Caro-Lopera, F.J., Ortiz-Méndez, U., García-Méndez, M., Pérez-Ramírez, F.O., Ultrathin tunable conducting oxide films for near-IR applications: An introduction to spectroscopy shape theory (2019) SN Appl. Sci, 1, p. 1553. , [CrossRef] Boschetti, L., Roy, D.P., Justice, C., Humber, M.L., MODIS–Landsat fusion for large area 30m burned area mapping (2015) Remote Sens. Environ, 161, pp. 27-42. , [CrossRef]
dc.rights.coar.fl_str_mv	http://purl.org/coar/access_right/c_16ec
rights_invalid_str_mv	http://purl.org/coar/access_right/c_16ec
dc.publisher.none.fl_str_mv	MDPI AG
dc.publisher.program.spa.fl_str_mv	Tronco común Ingenierías Ingeniería Ambiental
dc.publisher.faculty.spa.fl_str_mv	Facultad de Ciencias Básicas Facultad de Ingenierías
publisher.none.fl_str_mv	MDPI AG
dc.source.none.fl_str_mv	Remote Sensing
institution	Universidad de Medellín
repository.name.fl_str_mv	Repositorio Institucional Universidad de Medellin
repository.mail.fl_str_mv	repositorio@udem.edu.co
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spelling	20202021-02-05T14:57:52Z2021-02-05T14:57:52Z20724292http://hdl.handle.net/11407/591310.3390/rs12233972This paper proposes a validation-comparison method for burned area (BA) products. The technique considers: (1) bootstrapping of scenes for validation-comparison and (2) permutation tests for validation. The research focuses on the tropical regions of Northern Hemisphere South America and Northern Hemisphere Africa and studies the accuracy of the BA products: MCD45, MCD64C5.1, MCD64C6, Fire CCI C4.1, and Fire CCI C5.0. The first and second parts consider methods based on random matrix theory for zone differentiation and multiple ancillary variables such as BA, the number of burned fragments, ecosystem type, land cover, and burned biomass. The first method studies the zone effect using bootstrapping of Riemannian, full Procrustes, and partial Procrustes distances. The second method explores the validation by using distance permutation tests under uncertainty. The results refer to Fire CCI 5.0 with the best BA description, followed by MCD64C6, MCD64C5.1, MCD45, and Fire CCI 4.1. It was also found that biomass, total BA, and the number of fragments affect the BA product accuracy. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.engMDPI AGTronco común IngenieríasIngeniería AmbientalFacultad de Ciencias BásicasFacultad de Ingenieríashttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85097313286&doi=10.3390%2frs12233972&partnerID=40&md5=7818b3c2a39f4e9d5e8526801e8617da1223123Van Der Werf, G.R., Randerson, J.T., Giglio, L., Collatz, G.J., Mu, M., Kasibhatla, P., Morton, D.C., Van Leeuwen, T.T., Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997–2009) (2010) Atmos. Chem. Phys. Discuss, 10, pp. 11707-11735. , [CrossRef]Padilla-Parellada, M., Stehman, S., Ramo, R., Corti, D., Hantson, S., Oliva, P., Alonso-Canas, I., Mota, B.W., Comparing the accuracies of remote sensing global burned area products using stratified random sampling and estimation (2015) Remote. Sens. Environ, 160, pp. 114-121. , [CrossRef]Giglio, L., Randerson, J.T., Van Der Werf, G.R., Analysis of daily, monthly, and annual burned area using the fourth-generation global fire emissions database (GFED4) (2013) J. Geophys. Res. Biogeosci, 118, pp. 317-328. , [CrossRef]Giglio, L., Boschetti, L., Roy, D.P., Humber, M.L., Justice, C., The Collection 6 MODIS burned area mapping algorithm and product (2018) Remote Sens. Environ, 217, pp. 72-85. , [CrossRef] [PubMed]Anaya-Acevedo, J.A., Colditz, R.R., Valencia, G.M., Land Cover Mapping of a Tropical Region by Integrating Multi-Year Data into an Annual Time Series (2015) Remote Sens, 7, pp. 16274-16292. , [CrossRef]Randerson, J.T., Chen, Y., Van Der Werf, G.R., Rogers, B.M., Morton, D.C., Global burned area and biomass burning emissions from small fires (2012) J. Geophys. Res. Space Phys, 117. , [CrossRef]Juárez-Orozco, S.M., Siebe, C., Fernández, D.F.Y., Causes and Effects of Forest Fires in Tropical Rainforests: A Bibliometric Approach (2017) Trop. Conserv. Sci, 10. , [CrossRef]Giglio, L., Randerson, J.T., Van Der Werf, G.R., Kasibhatla, P., Collatz, G.J., Morton, D.C., DeFries, R.S., Assessing variability and long-term trends in burned area by merging multiple satellite fire products (2010) Biogeosciences, 7, pp. 1171-1186. , [CrossRef]Chuvieco, E., Lizundia-Loiola, J., Pettinari, M.L., Ramo, R., Padilla, M., Tansey, K., Mouillot, F., Heil, A., Generation and analysis of a new global burned area product based on MODIS 250 m reflectance bands and thermal anomalies (2018) Earth Syst. Sci. Data, 10, pp. 2015-2031. , [CrossRef]Avitabile, V., Herold, M., Heuvelink, G.B.M., Lewis, S.L., Phillips, O.L., Asner, G.P., Armston, J.D., Bayol, N., An integrated pan-tropical biomass map using multiple reference datasets (2016) Glob. Chang. Boil, 22, pp. 1406-1420. , [CrossRef]Hu, T., Su, Y., Xue, B., Liu, J., Zhao, X., Fang, J., Guo, Q., Mapping Global Forest Aboveground Biomass with Spaceborne LiDAR, Optical Imagery, and Forest Inventory Data (2016) Remote Sens, 8, p. 565. , [CrossRef]Rodríguez-Veiga, P., Wheeler, J., Louis, V., Tansey, K., Balzter, H., Quantifying Forest Biomass Carbon Stocks From Space (2017) Curr. Rep, 3, pp. 1-18. , [CrossRef]Van Der Werf, G.R., Randerson, J.T., Giglio, L., Van Leeuwen, T.T., Chen, Y., Rogers, B.M., Marle, M., James, G., Global fire emissions estimates during 1997–2016 (2017) Earth Syst. Sci. Data, 9, pp. 697-720. , [CrossRef]Van Marle, M., Kloster, S., Magi, B.I., Marlon, J., Daniau, A.-L., Field, R.D., Arneth, A., Kehrwald, N.M., Historic global biomass burning emissions for CMIP6 (BB4CMIP) based on merging satellite observations with proxies and fire models (1750–2015) (2017) Geosci. Model. Dev, 10, pp. 3329-3357. , [CrossRef]Padilla, M., Stehman, S.V., Chuvieco, E., Validation of the 2008 MODIS-MCD45 global burned area product using stratified random sampling (2014) Remote Sens. Environ, 144, pp. 187-196. , [CrossRef]Boschetti, L., Stehman, S.V., Roy, D.P., A stratified random sampling design in space and time for regional to global scale burned area product validation (2016) Remote Sens. Environ, 186, pp. 465-478. , [CrossRef]Armenteras, D., Gibbes, C., Anaya-Acevedo, J.A., Dávalos, L.M., Integrating remotely sensed fires for predicting deforestation for REDD+ (2017) Ecol. Appl, 27, pp. 1294-1304. , [CrossRef]Andela, N., Van Der Werf, G.R., Kaiser, J.W., Van Leeuwen, T.T., Wooster, M.J., Lehmann, C., Biomass burning fuel consumption dynamics in the tropics and subtropics assessed from satellite (2016) Biogeosciences, 13, pp. 3717-3734. , [CrossRef]Santana, L.D., Ribeiro, J.H.C., Berg, E.V.D., Carvalho, F.A., Impact on soil and tree community of a threatened subtropical phytophysiognomy after a forest fire (2020) Folia Geobot. 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Environ, 161, pp. 27-42. , [CrossRef]Remote SensingBootstrapFire-CCIMCD45MCD64Permutation testRandom matrix theoryRiemannian distanceRobust statisticsValidation and comparison of BA productsRandom variablesBurned biomassComparison methodsNorthern HemispheresPermutation testsProcrustes distanceRandom matrix theoryResearch focusTropical regionsFiresAbout validation-comparison of burned area productsArticleinfo:eu-repo/semantics/articlehttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Valencia, G.M., Facultad de Ingenierías, Universidad de San Buenaventura, Medellín, 050010, Colombia, Facultad de Ingenierías, Universidad de Medellín, Medellín, 050026, ColombiaAnaya, J.A., Facultad de Ingenierías, Universidad de Medellín, Medellín, 050026, ColombiaVelásquez, É.A., Facultad de Ciencias Básicas, Universidad de Medellín, Medellín, 050026, ColombiaRamo, R., Departamento de Geología, Geografía y Medio Ambiente, Universidad de Alcalá, Colegios 2, Alcalá de Henares, 28801, SpainCaro-Lopera, F.J., Facultad de Ciencias Básicas, Universidad de Medellín, Medellín, 050026, Colombiahttp://purl.org/coar/access_right/c_16ecValencia G.M.Anaya J.A.Velásquez É.A.Ramo R.Caro-Lopera F.J.11407/5913oai:repository.udem.edu.co:11407/59132021-02-05 09:57:52.617Repositorio Institucional Universidad de Medellinrepositorio@udem.edu.co

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