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Phenology Patterns and Postfire Vegetation Regeneration in the Chiquitania Region of Bolivia Using Sentinel-2
The natural regeneration of ecosystems impacted by fires is a high priority in Bolivia, and represents one of the country’s greatest environmental challenges. With the abundance of spatial data and access to improved technologies, it is critical to provide an effective method of analysis to evaluate...
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Published in: | Fire (Basel, Switzerland) Switzerland), 2022-06, Vol.5 (3), p.70 |
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creator | Maillard, Oswaldo Flores-Valencia, Marcio Michme, Gilka Coronado, Roger Bachfischer, Mercedes Azurduy, Huascar Vides-Almonacid, Roberto Flores, Reinaldo Angulo, Sixto Mielich, Nicolas |
description | The natural regeneration of ecosystems impacted by fires is a high priority in Bolivia, and represents one of the country’s greatest environmental challenges. With the abundance of spatial data and access to improved technologies, it is critical to provide an effective method of analysis to evaluate changes in land use in the face of the global need to understand the dynamics of vegetation in regeneration processes. In this context, we evaluated the dynamics of natural regeneration through phenological patterns by measuring the maximal and minimal spectral thresholds at four fire-impacted sites in Chiquitania in 2019 and 2020, and compared them with unburned areas using harmonic fitted values of the Normalized Difference Vegetation Index (NDVI) and the Normalized Burn Ratio (NBR). We used two-way ANOVA test to evaluate the significant differences in the values of the profiles of NDVI and NBR indices. We quantified severity at the four study sites using the dNBR obtained from the difference between pre- and postfire NBR. Additionally, we selected 66 sampling sites to apply the Composite Burn Index (CBI) methodology. Our results indicate that NBR is the most reliable index for interannual comparisons and determining changes in the phenological pattern, which allow for the detection of postfire regeneration. Fire severity levels based on dNBR and CBI indices are reliable methodologies that allow for determining the severity and dynamics of changes in postfire regeneration levels in forested and nonforested areas. |
doi_str_mv | 10.3390/fire5030070 |
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With the abundance of spatial data and access to improved technologies, it is critical to provide an effective method of analysis to evaluate changes in land use in the face of the global need to understand the dynamics of vegetation in regeneration processes. In this context, we evaluated the dynamics of natural regeneration through phenological patterns by measuring the maximal and minimal spectral thresholds at four fire-impacted sites in Chiquitania in 2019 and 2020, and compared them with unburned areas using harmonic fitted values of the Normalized Difference Vegetation Index (NDVI) and the Normalized Burn Ratio (NBR). We used two-way ANOVA test to evaluate the significant differences in the values of the profiles of NDVI and NBR indices. We quantified severity at the four study sites using the dNBR obtained from the difference between pre- and postfire NBR. Additionally, we selected 66 sampling sites to apply the Composite Burn Index (CBI) methodology. Our results indicate that NBR is the most reliable index for interannual comparisons and determining changes in the phenological pattern, which allow for the detection of postfire regeneration. Fire severity levels based on dNBR and CBI indices are reliable methodologies that allow for determining the severity and dynamics of changes in postfire regeneration levels in forested and nonforested areas.</description><identifier>ISSN: 2571-6255</identifier><identifier>EISSN: 2571-6255</identifier><identifier>DOI: 10.3390/fire5030070</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Abayoy ; Accuracy ; Agricultural production ; Bolivia ; Chiquitano Forest ; Classification ; Cultural heritage ; Ecosystems ; Environmental aspects ; Evaluation ; Forest & brush fires ; Geospatial data ; Google Earth Engine ; Human influences ; Land use ; natural regeneration ; NBR ; Normalized difference vegetative index ; Regeneration ; Regeneration (Botany) ; Remote sensing ; Spatial data ; Time series ; Trends ; Variance analysis ; Vegetation ; Vegetation dynamics ; Vegetation index ; Wildfires</subject><ispartof>Fire (Basel, Switzerland), 2022-06, Vol.5 (3), p.70</ispartof><rights>COPYRIGHT 2022 MDPI AG</rights><rights>2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). 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Flores-Valencia, Marcio ; Michme, Gilka ; Coronado, Roger ; Bachfischer, Mercedes ; Azurduy, Huascar ; Vides-Almonacid, Roberto ; Flores, Reinaldo ; Angulo, Sixto ; Mielich, Nicolas</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c403t-e8d8ba2029a02aeb823e79eb982e8d4d40e75eafbc730e514a6ae98ba41603263</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Abayoy</topic><topic>Accuracy</topic><topic>Agricultural production</topic><topic>Bolivia</topic><topic>Chiquitano Forest</topic><topic>Classification</topic><topic>Cultural heritage</topic><topic>Ecosystems</topic><topic>Environmental aspects</topic><topic>Evaluation</topic><topic>Forest & brush fires</topic><topic>Geospatial data</topic><topic>Google Earth Engine</topic><topic>Human influences</topic><topic>Land use</topic><topic>natural regeneration</topic><topic>NBR</topic><topic>Normalized difference vegetative index</topic><topic>Regeneration</topic><topic>Regeneration (Botany)</topic><topic>Remote sensing</topic><topic>Spatial data</topic><topic>Time series</topic><topic>Trends</topic><topic>Variance analysis</topic><topic>Vegetation</topic><topic>Vegetation dynamics</topic><topic>Vegetation index</topic><topic>Wildfires</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Maillard, Oswaldo</creatorcontrib><creatorcontrib>Flores-Valencia, Marcio</creatorcontrib><creatorcontrib>Michme, Gilka</creatorcontrib><creatorcontrib>Coronado, Roger</creatorcontrib><creatorcontrib>Bachfischer, Mercedes</creatorcontrib><creatorcontrib>Azurduy, Huascar</creatorcontrib><creatorcontrib>Vides-Almonacid, Roberto</creatorcontrib><creatorcontrib>Flores, Reinaldo</creatorcontrib><creatorcontrib>Angulo, Sixto</creatorcontrib><creatorcontrib>Mielich, Nicolas</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Agricultural Science Collection</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>SciTech Premium Collection</collection><collection>Agriculture Science Database</collection><collection>Publicly Available Content Database (Proquest) (PQ_SDU_P3)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Fire (Basel, Switzerland)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Maillard, Oswaldo</au><au>Flores-Valencia, Marcio</au><au>Michme, Gilka</au><au>Coronado, Roger</au><au>Bachfischer, Mercedes</au><au>Azurduy, Huascar</au><au>Vides-Almonacid, Roberto</au><au>Flores, Reinaldo</au><au>Angulo, Sixto</au><au>Mielich, Nicolas</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Phenology Patterns and Postfire Vegetation Regeneration in the Chiquitania Region of Bolivia Using Sentinel-2</atitle><jtitle>Fire (Basel, Switzerland)</jtitle><date>2022-06-01</date><risdate>2022</risdate><volume>5</volume><issue>3</issue><spage>70</spage><pages>70-</pages><issn>2571-6255</issn><eissn>2571-6255</eissn><abstract>The natural regeneration of ecosystems impacted by fires is a high priority in Bolivia, and represents one of the country’s greatest environmental challenges. With the abundance of spatial data and access to improved technologies, it is critical to provide an effective method of analysis to evaluate changes in land use in the face of the global need to understand the dynamics of vegetation in regeneration processes. In this context, we evaluated the dynamics of natural regeneration through phenological patterns by measuring the maximal and minimal spectral thresholds at four fire-impacted sites in Chiquitania in 2019 and 2020, and compared them with unburned areas using harmonic fitted values of the Normalized Difference Vegetation Index (NDVI) and the Normalized Burn Ratio (NBR). We used two-way ANOVA test to evaluate the significant differences in the values of the profiles of NDVI and NBR indices. We quantified severity at the four study sites using the dNBR obtained from the difference between pre- and postfire NBR. Additionally, we selected 66 sampling sites to apply the Composite Burn Index (CBI) methodology. Our results indicate that NBR is the most reliable index for interannual comparisons and determining changes in the phenological pattern, which allow for the detection of postfire regeneration. Fire severity levels based on dNBR and CBI indices are reliable methodologies that allow for determining the severity and dynamics of changes in postfire regeneration levels in forested and nonforested areas.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/fire5030070</doi><orcidid>https://orcid.org/0000-0002-8833-2004</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Abayoy Accuracy Agricultural production Bolivia Chiquitano Forest Classification Cultural heritage Ecosystems Environmental aspects Evaluation Forest & brush fires Geospatial data Google Earth Engine Human influences Land use natural regeneration NBR Normalized difference vegetative index Regeneration Regeneration (Botany) Remote sensing Spatial data Time series Trends Variance analysis Vegetation Vegetation dynamics Vegetation index Wildfires |
title | Phenology Patterns and Postfire Vegetation Regeneration in the Chiquitania Region of Bolivia Using Sentinel-2 |
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