@article{veraverbekeMappingDailyProgression2014,
  title = {Mapping the Daily Progression of Large Wildland Fires Using {{MODIS}} Active Fire Data},
  author = {Veraverbeke, Sander and Sedano, Fernando and Hook, Simon J. and Randerson, James T. and Jin, Yufang and Rogers, Brendan M.},
  year = {2014},
  volume = {23},
  pages = {655+},
  issn = {1049-8001},
  doi = {10.1071/wf13015},
  abstract = {High temporal resolution information on burnt area is needed to improve fire behaviour and emissions models. We used the Moderate Resolution Imaging Spectroradiometer (MODIS) thermal anomaly and active fire product (MO(Y)D14) as input to a kriging interpolation to derive continuous maps of the timing of burnt area for 16 large wildland fires. For each fire, parameters for the kriging model were defined using variogram analysis. The optimal number of observations used to estimate a pixel's time of burning varied between four and six among the fires studied. The median standard error from kriging ranged between 0.80 and 3.56 days and the median standard error from geolocation uncertainty was between 0.34 and 2.72 days. For nine fires in the south-western US, the accuracy of the kriging model was assessed using high spatial resolution daily fire perimeter data available from the US Forest Service. For these nine fires, we also assessed the temporal reporting accuracy of the MODIS burnt area products (MCD45A1 and MCD64A1). Averaged over the nine fires, the kriging method correctly mapped 73\,\% of the pixels within the accuracy of a single day, compared with 33\,\% for MCD45A1 and 53\,\% for MCD64A1. Systematic application of this algorithm to wildland fires in the future may lead to new information about vegetation, climate and topographic controls on fire behaviour.},
  journal = {International Journal of Wildland Fire},
  keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-13314064,mapping,modelling,modis,regression,wildfires},
  lccn = {INRMM-MiD:c-13314064},
  number = {5}
}

{"_id":"8WwRpaoBNdc7zZBAf","bibbaseid":"veraverbeke-sedano-hook-randerson-jin-rogers-mappingthedailyprogressionoflargewildlandfiresusingmodisactivefiredata-2014","downloads":0,"creationDate":"2016-06-22T10:19:55.439Z","title":"Mapping the Daily Progression of Large Wildland Fires Using MODIS Active Fire Data","author_short":["Veraverbeke, S.","Sedano, F.","Hook, S. J.","Randerson, J. T.","Jin, Y.","Rogers, B. M."],"year":2014,"bibtype":"article","biburl":"https://sharefast.me/php/download.php?id=zOUKvA&token=29","bibdata":{"bibtype":"article","type":"article","title":"Mapping the Daily Progression of Large Wildland Fires Using MODIS Active Fire Data","author":[{"propositions":[],"lastnames":["Veraverbeke"],"firstnames":["Sander"],"suffixes":[]},{"propositions":[],"lastnames":["Sedano"],"firstnames":["Fernando"],"suffixes":[]},{"propositions":[],"lastnames":["Hook"],"firstnames":["Simon","J."],"suffixes":[]},{"propositions":[],"lastnames":["Randerson"],"firstnames":["James","T."],"suffixes":[]},{"propositions":[],"lastnames":["Jin"],"firstnames":["Yufang"],"suffixes":[]},{"propositions":[],"lastnames":["Rogers"],"firstnames":["Brendan","M."],"suffixes":[]}],"year":"2014","volume":"23","pages":"655+","issn":"1049-8001","doi":"10.1071/wf13015","abstract":"High temporal resolution information on burnt area is needed to improve fire behaviour and emissions models. We used the Moderate Resolution Imaging Spectroradiometer (MODIS) thermal anomaly and active fire product (MO(Y)D14) as input to a kriging interpolation to derive continuous maps of the timing of burnt area for 16 large wildland fires. For each fire, parameters for the kriging model were defined using variogram analysis. The optimal number of observations used to estimate a pixel's time of burning varied between four and six among the fires studied. The median standard error from kriging ranged between 0.80 and 3.56 days and the median standard error from geolocation uncertainty was between 0.34 and 2.72 days. For nine fires in the south-western US, the accuracy of the kriging model was assessed using high spatial resolution daily fire perimeter data available from the US Forest Service. For these nine fires, we also assessed the temporal reporting accuracy of the MODIS burnt area products (MCD45A1 and MCD64A1). Averaged over the nine fires, the kriging method correctly mapped 73\\,% of the pixels within the accuracy of a single day, compared with 33\\,% for MCD45A1 and 53\\,% for MCD64A1. Systematic application of this algorithm to wildland fires in the future may lead to new information about vegetation, climate and topographic controls on fire behaviour.","journal":"International Journal of Wildland Fire","keywords":"*imported-from-citeulike-INRMM,~INRMM-MiD:c-13314064,mapping,modelling,modis,regression,wildfires","lccn":"INRMM-MiD:c-13314064","number":"5","bibtex":"@article{veraverbekeMappingDailyProgression2014,\n title = {Mapping the Daily Progression of Large Wildland Fires Using {{MODIS}} Active Fire Data},\n author = {Veraverbeke, Sander and Sedano, Fernando and Hook, Simon J. and Randerson, James T. and Jin, Yufang and Rogers, Brendan M.},\n year = {2014},\n volume = {23},\n pages = {655+},\n issn = {1049-8001},\n doi = {10.1071/wf13015},\n abstract = {High temporal resolution information on burnt area is needed to improve fire behaviour and emissions models. We used the Moderate Resolution Imaging Spectroradiometer (MODIS) thermal anomaly and active fire product (MO(Y)D14) as input to a kriging interpolation to derive continuous maps of the timing of burnt area for 16 large wildland fires. For each fire, parameters for the kriging model were defined using variogram analysis. The optimal number of observations used to estimate a pixel's time of burning varied between four and six among the fires studied. The median standard error from kriging ranged between 0.80 and 3.56 days and the median standard error from geolocation uncertainty was between 0.34 and 2.72 days. For nine fires in the south-western US, the accuracy of the kriging model was assessed using high spatial resolution daily fire perimeter data available from the US Forest Service. For these nine fires, we also assessed the temporal reporting accuracy of the MODIS burnt area products (MCD45A1 and MCD64A1). Averaged over the nine fires, the kriging method correctly mapped 73\\,\\% of the pixels within the accuracy of a single day, compared with 33\\,\\% for MCD45A1 and 53\\,\\% for MCD64A1. Systematic application of this algorithm to wildland fires in the future may lead to new information about vegetation, climate and topographic controls on fire behaviour.},\n journal = {International Journal of Wildland Fire},\n keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-13314064,mapping,modelling,modis,regression,wildfires},\n lccn = {INRMM-MiD:c-13314064},\n number = {5}\n}\n\n","author_short":["Veraverbeke, S.","Sedano, F.","Hook, S. J.","Randerson, J. T.","Jin, Y.","Rogers, B. M."],"key":"veraverbekeMappingDailyProgression2014","id":"veraverbekeMappingDailyProgression2014","bibbaseid":"veraverbeke-sedano-hook-randerson-jin-rogers-mappingthedailyprogressionoflargewildlandfiresusingmodisactivefiredata-2014","role":"author","urls":{},"keyword":["*imported-from-citeulike-INRMM","~INRMM-MiD:c-13314064","mapping","modelling","modis","regression","wildfires"],"downloads":0},"search_terms":["mapping","daily","progression","large","wildland","fires","using","modis","active","fire","data","veraverbeke","sedano","hook","randerson","jin","rogers"],"keywords":["mapping","modelling","modis","regression","wildfires","*imported-from-citeulike-inrmm","~inrmm-mid:c-13314064"],"authorIDs":[],"dataSources":["5S2zj2hKW8TWTkuMq"]}