A. G. Flores-Rodríguez, J. G. Flores-Garnica, D. González-Eguiarte, Agustín Gallegos-Rodríguez, Patricia Zarazúa-Villaseñor, Salvador Mena-Munguía
{"title":"森林火灾生态系统中松树自然再生的预测模型","authors":"A. G. Flores-Rodríguez, J. G. Flores-Garnica, D. González-Eguiarte, Agustín Gallegos-Rodríguez, Patricia Zarazúa-Villaseñor, Salvador Mena-Munguía","doi":"10.32870/ecucba.vi17.215","DOIUrl":null,"url":null,"abstract":"In ecosystems the effects of forest fires are variable depending on the severity of the fire. Consequently, the recovery that thevegetation will have in these areas is different. However, the evaluation in the field of the ecosystems' response to this impactimplies a significant expenditure of resources, either due to the extent of the fire or the inaccessibility of the terrain. Due to this,alternative strategies are sought for the evaluation and determination of priority areas for the implementation of management, suchas the use of spectral indices derived from remote sensors. In this work, the correlation presented by different variables takendirectly in the field and obtained by applying spectral indices to satellite images was evaluated to determine predictive models of thenatural regeneration of pine after the occurrence of a forest fire. Being the variables of tree canopy diameter, improved vegetationindex and slope those that were included in the predictive models, presenting a higher value of Rin the model in which bothenvironmental variables and those taken from satellite images are taken together. Finally, the resulting model with the improvedvegetation index was applied to a forest fire one year later and two years after the occurrence of the fire, obtaining as a result adecrease in regeneration individuals two years after the fire, however, it is notorious the tendency to find more regeneration in fireaffected areas compared to non-burned areas","PeriodicalId":447849,"journal":{"name":"e-CUCBA","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Modelos predictivos de la regeneración natural de pino en ecosistemas con incendios forestales\",\"authors\":\"A. G. Flores-Rodríguez, J. G. Flores-Garnica, D. González-Eguiarte, Agustín Gallegos-Rodríguez, Patricia Zarazúa-Villaseñor, Salvador Mena-Munguía\",\"doi\":\"10.32870/ecucba.vi17.215\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In ecosystems the effects of forest fires are variable depending on the severity of the fire. Consequently, the recovery that thevegetation will have in these areas is different. However, the evaluation in the field of the ecosystems' response to this impactimplies a significant expenditure of resources, either due to the extent of the fire or the inaccessibility of the terrain. Due to this,alternative strategies are sought for the evaluation and determination of priority areas for the implementation of management, suchas the use of spectral indices derived from remote sensors. In this work, the correlation presented by different variables takendirectly in the field and obtained by applying spectral indices to satellite images was evaluated to determine predictive models of thenatural regeneration of pine after the occurrence of a forest fire. Being the variables of tree canopy diameter, improved vegetationindex and slope those that were included in the predictive models, presenting a higher value of Rin the model in which bothenvironmental variables and those taken from satellite images are taken together. Finally, the resulting model with the improvedvegetation index was applied to a forest fire one year later and two years after the occurrence of the fire, obtaining as a result adecrease in regeneration individuals two years after the fire, however, it is notorious the tendency to find more regeneration in fireaffected areas compared to non-burned areas\",\"PeriodicalId\":447849,\"journal\":{\"name\":\"e-CUCBA\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"e-CUCBA\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.32870/ecucba.vi17.215\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"e-CUCBA","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.32870/ecucba.vi17.215","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Modelos predictivos de la regeneración natural de pino en ecosistemas con incendios forestales
In ecosystems the effects of forest fires are variable depending on the severity of the fire. Consequently, the recovery that thevegetation will have in these areas is different. However, the evaluation in the field of the ecosystems' response to this impactimplies a significant expenditure of resources, either due to the extent of the fire or the inaccessibility of the terrain. Due to this,alternative strategies are sought for the evaluation and determination of priority areas for the implementation of management, suchas the use of spectral indices derived from remote sensors. In this work, the correlation presented by different variables takendirectly in the field and obtained by applying spectral indices to satellite images was evaluated to determine predictive models of thenatural regeneration of pine after the occurrence of a forest fire. Being the variables of tree canopy diameter, improved vegetationindex and slope those that were included in the predictive models, presenting a higher value of Rin the model in which bothenvironmental variables and those taken from satellite images are taken together. Finally, the resulting model with the improvedvegetation index was applied to a forest fire one year later and two years after the occurrence of the fire, obtaining as a result adecrease in regeneration individuals two years after the fire, however, it is notorious the tendency to find more regeneration in fireaffected areas compared to non-burned areas