367
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Validating MCD64A1 and FireCCI51 burned area mapping in the Qinghai-Tibetan Plateau

, , ORCID Icon, , &
Article: 2285345 | Received 01 May 2023, Accepted 15 Nov 2023, Published online: 01 Dec 2023

References

  • Alonso-Canas I, Chuvieco E. 2015. Global burned area mapping from ENVISAT-MERIS and MODIS active fire data. Remote Sens Environ. 163:140–152. doi: 10.1016/j.rse.2015.03.011.
  • Bastarrika A, Chuvieco E, Martín MP. 2011. Automatic burned land mapping from MODIS time series images: assessment in Mediterranean Ecosystems. IEEE Trans Geosci Remote Sens. 49(9):3401–3413. doi: 10.1109/TGRS.2011.2128327.
  • Boschetti L, Flasse SP, Brivio PA. 2004. Analysis of the conflict between omission and commission in low spatial resolution dichotomic thematic products: the pareto boundary. Remote Sens Environ. 91(3-4):280–292. doi: 10.1016/j.rse.2004.02.015.
  • Boschetti L, Roy DP, Giglio L, Huang H, Zubkova M, Humber ML. 2019. Global validation of the collection 6 MODIS burned area product. Remote Sens Environ. 235:111490. doi: 10.1016/j.rse.2019.111490.
  • Boschetti L, Stehman SV, Roy DP. 2016. A stratified random sampling design in space and time for regional to global scale burned area product validation. Remote Sens Environ. 186:465–478. doi: 10.1016/j.rse.2016.09.016.
  • Campagnolo ML, Libonati R, Rodrigues JA, Pereira JMC. 2021. A comprehensive characterization of MODIS daily burned area mapping accuracy across fire sizes in tropical Savannas. Remote Sens Environ. 252:112115. doi: 10.1016/j.rse.2020.112115.
  • Carmona-Moreno C, Belward A, Malingreau JP, Hartley A, Garcia-Alegre M, Antonovskiy M, Buchshtaber V, Pivovarov V. 2005. Characterizing interannual variations in global fire calendar using data from earth observing satellites. Glob Change Biol. 11(9):1537–1555. doi: 10.1111/j.1365-2486.2005.01003.x.
  • Chuvieco E, Lizundia-Loiola J, Pettinari ML, Ramo R, Padilla M, Tansey K, Mouillot F, Laurent P, Storm T, Heil A, et al. 2018. Generation and analysis of a new global burned area product based on MODIS 250 m reflectance bands and thermal anomalies. Earth Syst Sci Data. 10(4):2015–2031. doi: 10.5194/essd-10-2015-2018.
  • Chuvieco E, Mouillot F, van der Werf GR, Miguel JS, Tanase M, Koutsias N, García M, Yebra M, Padilla M, Gitas M, et al. 2019. Historical background and current developments for mapping burned area from satellite earth observation. Remote Sens Environ. 225:45–64. doi: 10.1016/j.rse.2019.02.013.
  • De Araújo FM, Ferreira LG. 2015. Satellite-based automated burned area detection: a performance assessment of the MODIS MCD45A1 in the Brazilian Savanna. Int J Appl Earth Obs Geoinf. 36(7):94–102. doi: 10.1016/j.jag.2014.10.009.
  • Eva H, Lambin EF. 1998. Remote sensing of biomass burning in tropical regions. Remote Sens Environ. 64(3):292–315. doi: 10.1016/S0034-4257(98)00006-6.
  • Fornacca D, Ren GP, Xiao W. 2017. Performance of three MODIS fire products (MCD45A1, MCD64A1, MCD14ML), and ESA fire_CCI in a mountainous area of Northwest Yunnan, China, characterized by frequent small fires. Remote Sens. 9(11):1131. doi: 10.3390/rs9111131.
  • Giglio L. 2018. Collection 6 MODIS Burned area product user’s guide version 1.2. Available from https://archive.ceda.ac.uk/.
  • Giglio L, Loboda T, Roy DP, Quayle B, Justice CO. 2009. An active-fire based burned area mapping algorithm for the MODIS sensor. Remote Sens Environ. 113(2):408–420. doi: 10.1016/j.rse.2008.10.006.
  • Giglio L, Randerson JT, van der Werf GR. 2013. Analysis of daily, monthly, and annual burned area using the fourth-generation global fire emissions database (GFED4). JGR Biogeosci. 118(1):317–328. doi: 10.1002/jgrg.20042.
  • Giglio L, Schroeder W, Justice CO. 2016. The collection 6 MODIS active fire detection algorithm and fire products. Remote Sens Environ. 178:31–41. doi: 10.1016/j.rse.2016.02.054.
  • Giglio L, Boschetti L, Roy DP, Humber ML, Justice CO. 2018. The collection 6 MODIS burned area mapping algorithm and product. Remote Sens Environ. 217:72–85. doi: 10.1016/j.rse.2018.08.005.
  • Hall JV, Argueta F, Giglio L. 2021. Validation of MCD64A1 and FireCCI51 cropland burned area mapping in Ukraine. Int J Appl Earth Obs Geoinf. 102:102443. doi: 10.1016/j.jag.2021.102443.
  • Hawbaker TJ, Vanderhoof MK, Schmidt GL, Beal YJ, Picotte JJ, Takacs JD, Falgout JT, Dwyer JL. 2020. The Landsat burned area algorithm and products for the conterminous United States. Remote Sens Environ. 244(117):111801. doi: 10.1016/j.rse.2020.111801.
  • Humber ML, Boschetti L, Giglio L, Justice CO. 2019. Spatial and temporal inter comparison of four global burned area products. Int J Digit Earth. 12(4):460–484. doi: 10.1080/17538947.2018.1433727.
  • Katagis T, Gitas IZ. 2022. Assessing the accuracy of MODIS MCD64A1 C6 and FireCCI51 burned area products in mediterranean ecosystems. Remote Sens. 14(3):602. doi: 10.3390/rs14030602.
  • Li J, Song Y, Huang X, Li M. 2015. Comparison of forest burned areas in mainland China derived from MCD45A1 and data recorded in yearbooks from 2001 to 2011. Int J Wildland Fire. 24(1):103–113. doi: 10.1071/WF14031.
  • Li X, Yao Z, Xiao J, Wang H. 2016. 2010. Analysis of the spatial-temporal variation characteristics of precipitation over the Tibetan Plateau from 1961 through. J Glaciol Geocryol. 38(5):1233–1240.
  • Liu J, Gao J, Wang W. 2013. Variations of vegetation coverage and its relations to global climate changes on the Tibetan Plateau during 1981–2005. J MT Sci. 2:234–242.
  • Lizundia-Loiola J, Otón G, Ramo R, Chuvieco E. 2020. A spatio-temporal active-fire clustering approach for global burned area mapping at 250 m from MODIS data. Remote Sens Environ. 236:111493. doi: 10.1016/j.rse.2019.111493.
  • Lizundia-Loiola J, Pettinari ML, Chuvieco E. 2019. ESA CCI, and ECV fire disturbance, D3.3.3 product user guide-MODIS, version 1.4. Available from https://www.esa-fire-cci.org/documents.
  • Long T, Zhang Z, He G, Jiao W, Tang C, Wu B, Zhang X, Wang G, Yin R. 2019. 30 m resolution global annual burned area mapping based on landsat images and Google earth engine. Remote Sens. 11(5):489. doi: 10.3390/rs11050489.
  • Moreira AG. 2000. Effects of fire protection on savanna structure in Central Brazil. J Biogeogr. 27(4):1021–1029. doi: 10.1046/j.1365-2699.2000.00422.x.
  • Mouillot F, Schultz MG, 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. Int J Appl Earth Obs. 26(1):64–79. doi: 10.1016/j.jag.2013.05.014.
  • Myers N, Mittermeier RA, Mittermeier CG, da Fonseca GAB, Kent J. 2000. Biodiversity hotspots for conservation priorities. Nature. 403(6772):853–858. doi: 10.1038/35002501.
  • Núñez-Casillas L, Lázaro JRG, Moreno-Ruiz JA, Arbelo M. 2013. A comparative analysis of burned area datasets in Canadian Boreal Forest in 2000. ScientificWorldJournal. 2013:289013–289056. doi: 10.1155/2013/289056.
  • Padilla M, Stehman SV, Ramo R, Corti D, Hantson S, Oliva P, Alonso-Canas I, Bradley AV, Tansey K, Mota B, et al. 2015. Comparing the accuracies of remote sensing global burned area products using stratified random sampling and estimation. Remote Sens Environ. 160:114–121. doi: 10.1016/j.rse.2015.01.005.
  • Plummer S, Arino O, Simon M, Steffen W. 2006. Establishing a earth observation product service for the terrestrial carbon community: the globcarbon initiative. Mitig Adapt Strat Glob Change. 11(1):97–111. doi: 10.1007/s11027-006-1012-8.
  • Pu D, Zhang Z, Long T, Niu X, He G, Wang G, Sun J, Tang C, Wei M. 2020. GABAM2010 accuracy assessment using stratified random sampling. J Remote Sens. 24(5):550–558. doi: 10.11834/jrs.20209171.
  • Qi W, Zhang B, Pang Y, Zhao F, Zhang S. 2013. TRMM-data-based spatial and seasonal patterns of precipitation in the Qinghai-Tibet Plateau. Sci Geol Sin. 33(8):999–1005.
  • Qi W, Liu S, Zhou L. 2020. Regional differentiation of population in Tibetan Plateau: insight from the “Hu Line”. Acta Geogr Sin. 75(2):255–267.
  • Qiu J. 2008. China: the third pole. Nature. 454(7203):393–396. doi: 10.1038/454393a.
  • Rodrigues JA, Libonati R, Pereira AA, Nogueira JMP, Santos FLM, Peres LF, Santa Rosa A, Schroeder W, Pereira JMC, Giglio L, et al. 2019. How well do global burned area products represent fire patterns in the Brazilian Savannas biome? An accuracy assessment of the MCD64 collections. Int J Appl Earth Obs. 78:318–331. doi: 10.1016/j.jag.2019.02.010.
  • Roteta E, Bastarrika A, Padilla M, Storm T, Chuvieco E. 2019. Development of a Sentinel-2 burned area algorithm: generation of a small fire database for sub-Saharan Africa. Remote Sens Environ. 222:1–17. doi: 10.1016/j.rse.2018.12.011.
  • Roy DP, Boschetti L. 2009. Southern Africa validation of the MODIS, L3JRC, and GlobCarbon burned-area products. IEEE Trans Geosci Remote Sensing. 47(4):1032–1044. doi: 10.1109/TGRS.2008.2009000.
  • Roy DP, Jin Y, Lewis PE, Justice CO. 2005. Prototyping a global algorithm for systematic fire-affected area mapping using MODIS time series data. Remote Sens Environ. 97(2):137–162. doi: 10.1016/j.rse.2005.04.007.
  • Roy DP, Huang H, Boschetti L, Giglio L, Yan L, Zhang H, Li Z. 2019. Landsat-8 and Sentinel-2 burned area mapping - a combined sensor multi-temporal change detection approach. Remote Sens Environ. 231:111254. doi: 10.1016/j.rse.2019.111254.
  • Sun H, Zheng D, Yao TD, Zhang YL. 2012. Protection and construction of the national ecological security shelter zone on Tibetan Plateau. Acta Geogr Sin. 67(1):3–12.
  • Tansey K, Grégoire JM, Defourny P, Leigh R, Pekel JF, van Bogaert E, Bartholomé E. 2008. A new, global, multi-annual (2000–2007) burnt area product at 1 km resolution. Geophys Res Lett. 35(1):L01401.
  • Tansey K, Grégoire JM, Stroppiana D, Sousa A, Silva J, Pereira JMC, Boschetti L, Maggi M, Brivio PA, Fraser R, et al. 2004. Vegetation burning in the year 2000: global burned area estimates from SPOT VEGETATION data. J Geophys Res. 109(D14):D14S03. doi: 10.1029/2003JD003598.
  • Tian X, Zhao F, Shu L, Wang M. 2014. Changes in forest fire danger for south-Western China in the 21st century. Int J Wildland Fire. 23(2):185–195. doi: 10.1071/WF13014.
  • Tsela P, Helden PV, Frost P, Wessels K, Archibald S. 2010. Validation of the MODIS burned-area products across different biomes in south Africa. Int Geosci Remote Sens Symp (IGARSS). :3652–3655.
  • Tsela P, Wessels K, Botai J, Archibald S, Swanepoel D, Steenkamp K, Frost P. 2014. Validation of the two standard MODIS satellite burned-area products and an empirically derived merged product in South Africa. Remote Sens. 6(2):1275–1293. doi: 10.3390/rs6021275.
  • Vetrita Y, Cochrane MA, Suwarsono, PM, Priyatna M, Sukowati KAD, Khomarudin MR. 2021. Evaluating accuracy of four MODIS-derived burned area products for tropical peatland and non-peatland fires.Environ. Res. Lett. 16(3):035015. doi: 10.1088/1748-9326/abd3d1.
  • Vilar L, Camia A, San-Miguel-Ayanz J. 2015. A comparison of remote sensing products and forest fire statistics for improving fire information in Mediterranean Europe. Eur J Remote Sens. 48(1):345–364. doi: 10.5721/EuJRS20154820.
  • Yu B, Lv C. 2011. Assessment of ecological vulnerability on the Tibetan Plateau. Geogr Res. 30(12):2289–2295.
  • Zhang Y, Liu L, Wang Z, Bai W, Ding M, Wang X, Yan J, Xu E, Wu X, Zhang B, et al. 2019. Spatial and temporal characteristics of land use and cover changes in the Tibetan Plateau. Chin Sci Bull. 64(27):2865–2875. doi: 10.1360/TB-2019-0046.
  • Zhang Y, Li B, Zheng D. 2002. A discussion on the boundary and area of the Tibetan Plateau in China. Geogr Res. 21(1):1–8.