{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T17:22:12Z","timestamp":1778088132041,"version":"3.51.4"},"reference-count":76,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2021,1,5]],"date-time":"2021-01-05T00:00:00Z","timestamp":1609804800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100010896","name":"International Cooperation and Exchange Programme","doi-asserted-by":"publisher","award":["41961144019"],"award-info":[{"award-number":["41961144019"]}],"id":[{"id":"10.13039\/501100010896","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100010211","name":"Education Department of Jilin Province","doi-asserted-by":"publisher","award":["JJKH20190285KJ"],"award-info":[{"award-number":["JJKH20190285KJ"]}],"id":[{"id":"10.13039\/501100010211","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sustainability"],"abstract":"<jats:p>An important component in improving the quality of forests is to study the interference intensity of forest fires, in order to describe the intensity of the forest fire and the vegetation recovery, and to improve the monitoring ability of the dynamic change of the forest. Using a forest fire event in Bilahe, Inner Monglia in 2017 as a case study, this study extracted the burned area based on the BAIS2 index of Sentinel-2 data for 2016\u20132018. The leaf area index (LAI) and fractional vegetation cover (FVC), which are more suitable for monitoring vegetation dynamic changes of a burned area, were calculated by comparing the biophysical and spectral indices. The results showed that patterns of change of LAI and FVC of various land cover types were similar post-fire. The LAI and FVC of forest and grassland were high during the pre-fire and post-fire years. During the fire year, from the fire month (May) through the next 4 months (September), the order of areas of different fire severity in terms of values of LAI and FVC was: low &gt; moderate &gt; high severity. During the post fire year, LAI and FVC increased rapidly in areas of different fire severity, and the ranking of areas of different fire severity in terms of values LAI and FVC was consistent with the trend observed during the pre-fire year. The results of this study can improve the understanding of the mechanisms involved in post-fire vegetation change. By using quantitative inversion, the health trajectory of the ecosystem can be rapidly determined, and therefore this method can play an irreplaceable role in the realization of sustainable development in the study area. Therefore, it is of great scientific significance to quantitatively retrieve vegetation variables by remote sensing.<\/jats:p>","DOI":"10.3390\/su13010432","type":"journal-article","created":{"date-parts":[[2021,1,5]],"date-time":"2021-01-05T21:18:57Z","timestamp":1609881537000},"page":"432","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["Short-Term Effects of Fire Severity on Vegetation Based on Sentinel-2 Satellite Data"],"prefix":"10.3390","volume":"13","author":[{"given":"Aru","family":"Han","sequence":"first","affiliation":[{"name":"School of Environment, Northeast Normal University, Changchun 130024, China"},{"name":"Laboratory for Vegetation Ecology, Ministry of Education, Changchun 130024, China"},{"name":"State Environmental Protection Key Laboratory of Wetland Ecology and Vegetation Restoration, Changchun 130024, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Song","family":"Qing","sequence":"additional","affiliation":[{"name":"College of Geographical Science, Inner Mongolia Normal University, Hohhot 010022, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yongbin","family":"Bao","sequence":"additional","affiliation":[{"name":"School of Environment, Northeast Normal University, Changchun 130024, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Li","family":"Na","sequence":"additional","affiliation":[{"name":"School of Environment, Northeast Normal University, Changchun 130024, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuhai","family":"Bao","sequence":"additional","affiliation":[{"name":"College of Geographical Science, Inner Mongolia Normal University, Hohhot 010022, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xingpeng","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Environment, Northeast Normal University, Changchun 130024, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6077-8429","authenticated-orcid":false,"given":"Jiquan","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Environment, Northeast Normal University, Changchun 130024, China"},{"name":"Laboratory for Vegetation Ecology, Ministry of Education, Changchun 130024, China"},{"name":"State Environmental Protection Key Laboratory of Wetland Ecology and Vegetation Restoration, Changchun 130024, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chunyi","family":"Wang","sequence":"additional","affiliation":[{"name":"Chinese Academy of Meteorological Sciences, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,1,5]]},"reference":[{"key":"ref_1","unstructured":"Hu, H.Q. (2005). Forest Ecology and Management, China Forestry Publishing House."},{"key":"ref_2","first-page":"305","article-title":"Validation of MODIS Active Fire Detection Products Derived from Two Algorithms","volume":"9","author":"Morisette","year":"2005","journal-title":"Earth Int."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"408","DOI":"10.1590\/0102-33062015abb0009","article-title":"Post-fire dynamics of the woody vegetation of a savanna forest (Cerrad\u00e3o) in the Cerrado-Amazon transition zone","volume":"3","author":"Reis","year":"2015","journal-title":"Acta Bot. Bras."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"557","DOI":"10.1071\/WF05096","article-title":"Influence of topography and forest structure on patterns of mixed severity fire in ponderosa pine forests of the South Dakota Black Hills, USA","volume":"15","author":"Lentile","year":"2006","journal-title":"Int. J. Wildland Fire"},{"key":"ref_5","unstructured":"Key, C., and Benson, N. (2006). Landscape Assessment: Ground Measure of Severity, the Composite Burn Index and Remote Sensing of Severity, the Normalized Burn Ratio, FIREMON: Fire Effects Monitoring and Inventory System, Gen. Tech. Rep. RMRS-GTR-164-CD."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1071\/WF07049","article-title":"Fire intensity, fire severity and burn severity: A brief review and suggested usage","volume":"18","author":"Keeley","year":"2009","journal-title":"Int. J. Wildland Fire"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"397","DOI":"10.1016\/j.rse.2003.12.015","article-title":"Comparison of AVIRIS and Landsat ETM+ detection capabilities for burn severity","volume":"92","author":"Root","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1109\/LGRS.2005.858485","article-title":"Remote sensing of fire severity assessing the performance of the normalized burn ratio","volume":"3","author":"Roy","year":"2006","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"3139","DOI":"10.1080\/0143116032000160435","article-title":"Estimation of interannual variation in productivity of global vegetation using NDVI data","volume":"25","author":"Chen","year":"2004","journal-title":"Int. J. Remote Sens."},{"key":"ref_10","first-page":"198","article-title":"Retrieval Sub-pixel Fire Area with MODIS and ASTER Data","volume":"22","author":"Cui","year":"2008","journal-title":"J. Arid Land Resour. Environ."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Szpakowski, D.M., and Jensen, J.L.R. (2019). A Review of the Applications of Remote Sensing in Fire Ecology. Remote Sens., 11.","DOI":"10.3390\/rs11222638"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"645","DOI":"10.1016\/j.rse.2008.11.009","article-title":"Calibration and validation of the relative differenced normalized burn ratio (RdNBR) to three measures of fire severity in the Sierra Nevada and Klamath Mountains, California, USA","volume":"113","author":"Miller","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1016\/j.rse.2006.12.006","article-title":"Quantifying burn severity in a heterogeneous landscape with a relative version of the delta Normalized Burn Ratio (dNBR)","volume":"109","author":"Miller","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_14","first-page":"28","article-title":"Advances in the assessment of forest fire severity and its spatial heterogeneity (in Chinese)","volume":"21","author":"Chang","year":"2012","journal-title":"J. Natur. Disasters"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"500","DOI":"10.1071\/WF08107","article-title":"Evaluating the potential of Landsat TM\/ETM+ imagery for assessing fire severity in Alaskan black spruce forests","volume":"17","author":"Hoy","year":"2008","journal-title":"Int. J. Wildland Fire"},{"key":"ref_16","unstructured":"Lei, C.L. (2012). Estimating Burned Severity with Multiple Methods in Da Hinggan Mountains. [Ph.D. Thesis, Northeast Forestry University]. (In Chinese)."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1080\/10106049109354290","article-title":"Taylor & francis online: Mapping burns and natural reforestation using Thematic Mapper data","volume":"6","author":"Caselles","year":"1991","journal-title":"Geocarto Int."},{"key":"ref_18","first-page":"84","article-title":"An adaptability analysis of remote sensing indices in evaluating fire severity","volume":"28","author":"Tan","year":"2016","journal-title":"Remote Sens. Land Resour."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"463","DOI":"10.1071\/WF08034","article-title":"Assessing the differenced Normalized Burn Ratio\u2019s ability to map burn severity in the boreal forest and tundra ecosystems of Alaska\u2019s national parks","volume":"17","author":"Allen","year":"2008","journal-title":"Int. J. Wildland Fire"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1909","DOI":"10.1016\/j.envsoft.2010.06.003","article-title":"Forest fires mapping and monitoring of current and past forest fire activity from Meteosat Second Generation Data","volume":"25","author":"Carvalheiro","year":"2010","journal-title":"Environ. Modeling Softw."},{"key":"ref_21","first-page":"120","article-title":"Modeling of multi-strata forest fire severity using Landsat TM data","volume":"13","author":"Meng","year":"2011","journal-title":"Int. J. Appl. Earth. Obs. Geoinf."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Chuvieco, E., Riano, D., Danson, F.M., and Martin, P. (2006). Use of a radiative transfer model to simulate the postfire spectral response to burn severity. J. Geophys. Res.-Biogeo., 111.","DOI":"10.1029\/2005JG000143"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Filipponi, F. (2018). BAIS2: Burned Area Index for Sentinel-2. Proceedings, 2.","DOI":"10.3390\/ecrs-2-05177"},{"key":"ref_24","first-page":"170","article-title":"Sentinel-2A red-edge spectral indices suitability for discriminating fire severity","volume":"50","author":"Quintano","year":"2016","journal-title":"Int. J. Appl. Earth. Obs. Geoinf."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"527","DOI":"10.1071\/WF08038","article-title":"Seasonal and topographic effects on estimating fire severity from Landsat TM\/ETM+ data","volume":"17","author":"Verbyla","year":"2008","journal-title":"Int. J. Wildland Fire"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1016\/j.rse.2006.03.019","article-title":"Assessment of fire severity and species diversity in the southern Appalachians using Landsat TM and ETM+ imagery","volume":"108","author":"Wimberly","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Caselles, V., L\u00f3pez Garc\u00eda, M.J., Meli\u00e1, J., and P\u00e9rez Cueva, A.J. (1991). Analysis of the heat-island effect of the city of Valencia, Spain, through air temperature transects and NOAA satellite data. Theor. Appl. Climatol., 43.","DOI":"10.1007\/BF00867455"},{"key":"ref_28","unstructured":"Zhu, X. (2013). Study on Forest Fire Damage Monitoring Method Based on HJ-1 Satellite Data. [Master\u2019s Thesis, Chinese Academy of Forestry]. (In Chinese)."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1007\/s10310-004-0106-y","article-title":"Evaluating Vegetation Recovery Following Large\u2014Scale Forest Fires in Borneo and North-eastern China Using Multi-Temporal NOAA\/AVHRR Images","volume":"10","author":"Idris","year":"2005","journal-title":"J. For. Res."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"383","DOI":"10.1016\/S0034-4257(97)00048-5","article-title":"Modeling rates of ecosystem recovery after fires by using Landsat TM data","volume":"61","author":"Viedma","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Morresi, D., Vitali, A., Urbinati, C., and Garbarino, M. (2019). Forest Spectral Recovery and Regeneration Dynamics in Stand-Replacing Wildfires of Central Apennines Derived from Landsat Time Series. Remote Sens., 11.","DOI":"10.3390\/rs11030308"},{"key":"ref_32","first-page":"441","article-title":"Fisher\u2013Shannon information plane analysis of SPOT\/Vegetation Normalized Difference Vegetation Index (NDVI) time series to characterize vegetation recovery after fire disturbance","volume":"26","author":"Lanorte","year":"2014","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Pena, M.A., and Ulloa, J. (2017, January 15\u201316). Mapping the post-fire vegetation recovery by NDVI time series. Proceedings of the 2017 First IEEE International Symposium of Geoscience and Remote Sensing (GRSS-CHILE), Valdivia, Chile.","DOI":"10.1109\/GRSS-CHILE.2017.7996002"},{"key":"ref_34","first-page":"45","article-title":"Dynamics of Primary Productivity and Soil Organic Matter of Typical Steppe in the XiLin River Basin of Inner Mongolia and Their Response to Climate Change","volume":"38","author":"Xiao","year":"1996","journal-title":"Acta Bot. Sin."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Filipponi, F., and Manfron, G. (2019). Observing Post-Fire Vegetation Regeneration Dynamics Exploiting High-Resolution Sentinel-2 Data. Proceedings, 18.","DOI":"10.3390\/ECRS-3-06200"},{"key":"ref_36","first-page":"97","article-title":"Evaluation of forest fire on Madeira Island using Sentinel-2A MSI imagery","volume":"58","author":"Navarroa","year":"2017","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/j.isprsjprs.2017.04.016","article-title":"Examining the strength of the newly-launched Sentinel 2 MSI sensor in detecting and discriminating subtle differences between C3 and C4 grass species","volume":"129","author":"Shoko","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Harald, V.D., and Freek, V.D.M. (2016). Sentinel-2A MSI and Landsat 8 OLI Provide Data Continuity for Geological Remote Sensing. Remote Sens., 8.","DOI":"10.3390\/rs8110883"},{"key":"ref_39","unstructured":"Gu, F. (2018). Dynamic Monitoring of Vegetation Participants in Typical Oasis Based on Sentinel-2 Data. [Master\u2019s Thesis, Xinjiang University]. (In Chinese)."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/j.rse.2011.10.032","article-title":"Generating global leaf area index from Landsat: Algorithm formulation and demonstration","volume":"122","author":"Ganguly","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1016\/S0034-4257(01)00300-5","article-title":"Derivation and validation of Canada-wide coarse-resolution leaf area index maps using high-resolution satellite imagery and ground measurements","volume":"80","author":"Chen","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Djamai, N., Zhong, D., Fernandes, R., and Zhou, F. (2019). Evaluation of vegetation biophysical variables time series derived from synthetic Sentinel-2 images. Remote Sens., 11.","DOI":"10.3390\/rs11131547"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"416","DOI":"10.1016\/j.rse.2019.03.020","article-title":"Validation of the Sentinel Simplified Level 2 Product Prototype Processor (SL2P) for mapping cropland biophysical variables using Sentinel-2\/MSI and Landsat-8\/OLI data","volume":"225","author":"Djamai","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"422","DOI":"10.1016\/j.rse.2006.11.022","article-title":"Burn severity estimation from remotely sensed data: Performance of simulation versus empirical models","volume":"108","author":"Chuvieco","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"370","DOI":"10.1016\/j.scib.2019.03.002","article-title":"Stable classification with limited sample: Transferring a 30-m resolution sample set collected in 2015 to mapping 10-m resolution global land cover in 2017","volume":"64","author":"Peng","year":"2019","journal-title":"Sci. Bull."},{"key":"ref_46","unstructured":"Zhang, L. (2013). The Present Situation and Distribution of Forest Resource of the Bilahe Bureau in Inner Mongolia. Inn. Mong. For. Invest. Design., 57\u201359. (In Chinese)."},{"key":"ref_47","first-page":"403","article-title":"Performance evaluation of object based greenhouse detection from Sentinel-2 MSI and landsat 8 OLI data: A case study from Almer\u00eda (Spain)","volume":"52","author":"Novelli","year":"2016","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_48","unstructured":"M\u00fcller-Wilm, U. (2016). Sen2Cor Configuration and User Manual, European Space Agency."},{"key":"ref_49","first-page":"013","article-title":"Remote Sensing Assessment of Forest Fire Damage Degree in Bilahe Forest Farm, Inner Mongolia","volume":"1","author":"Liu","year":"2018","journal-title":"For. Resour. Manag."},{"key":"ref_50","first-page":"1","article-title":"A method of establishing groups of equal amplitude in plant sociology based on similarity of species and its application to analyses of the vegetation on Danish commons","volume":"5","year":"1948","journal-title":"Biol. Skr. K. Danskc Vidensk. Selsk."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"297","DOI":"10.2307\/1932409","article-title":"Measures of the amount of ecologic association between species","volume":"26","author":"Dice","year":"1945","journal-title":"Ecology"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1093\/treephys\/7.1-2-3-4.33","article-title":"Exploring the relationship between reflectance red edge and chlorophyll content in slash pine","volume":"7","author":"Curran","year":"1990","journal-title":"Tree Physiol."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1111\/geb.12133","article-title":"Global dependence of field-observed leaf area index in woody species on climate: A systematic review","volume":"23","author":"Iio","year":"2014","journal-title":"Glob. Ecol. Biogeogr."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1016\/0034-4257(90)90097-6","article-title":"Use of narrow-band spectra to estimate the fraction of absorbed photosynthetically active radiation","volume":"32","author":"Hall","year":"1990","journal-title":"Remote Sens. Environ."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1016\/S0034-4257(01)00289-9","article-title":"Novel algorithms for remote estimation of vegetation fraction","volume":"80","author":"Gitelson","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Tang, L., He, M., and Li, X. (2020). Verification of Fractional Vegetation Coverage and NDVI of Desert Vegetation via UAVRS Technology. Remote Sens., 12.","DOI":"10.3390\/rs12111742"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1626\/jcs.51.134","article-title":"Distribution of chlorophyll content in leaf blade of rice plant","volume":"51","author":"Kariya","year":"1982","journal-title":"Jpn. J. Crop Sci."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1016\/j.fishres.2012.10.004","article-title":"A reliable game fish weight estimation model for atlantic tarpon (megalops atlanticus)","volume":"139","author":"Ault","year":"2013","journal-title":"Fish. Res."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"429","DOI":"10.1016\/j.patrec.2003.11.005","article-title":"An improved face recognition technique based on modular PCA approach","volume":"25","author":"Gottumukkal","year":"2004","journal-title":"Pattern Recognit. Lett."},{"key":"ref_60","unstructured":"Key, C.H., and Benson, N.C. (1999). The Normalized Burn Ratio (NBR): A Landsat TM Radiometric Measure of Burn Severity."},{"key":"ref_61","unstructured":"Key, C.H., and Benson, N.C. (2002). Measuring and Remote Sensing of Burn Severity."},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Iizuka, K., Kato, T., Silsigia, S., Soufiningrum, A.Y., and Kozan, O. (2019). Estimating and Examining the Sensitivity of Different Vegetation Indices to Fractions of Vegetation Cover at Different Scaling Grids for Early Stage Acacia Plantation Forests Using a Fixed-Wing UAS. Remote Sens., 11.","DOI":"10.3390\/rs11151816"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"15082","DOI":"10.3390\/rs71115082","article-title":"Estimation of CO2 Sequestration by the Forests in Japan by Discriminating Precise Tree Age Category using Remote Sensing Techniques","volume":"7","author":"Iizuka","year":"2015","journal-title":"Remote Sens."},{"key":"ref_64","first-page":"S1","article-title":"Gravity index fomula of eco-environment quality evalution based on normalized index values","volume":"32","author":"Zhang","year":"2014","journal-title":"Environ. Eng."},{"key":"ref_65","first-page":"29","article-title":"Soil physical properties","volume":"Volume 4","author":"Neary","year":"1999","journal-title":"Wildland Fire in Ecosystems: Effects of Fire on Soil and Water"},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1016\/j.rse.2006.08.006","article-title":"Characterization of post-fire surface cover, soils, and burn severity at the Cerro Grande Fire, New Mexico, using hyper-spectral and multispectral remote sensing","volume":"106","author":"Kokaly","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"467","DOI":"10.1016\/j.rse.2006.11.027","article-title":"Postfire soil burn severity mapping with hyperspectral image unmixing","volume":"108","author":"Robichaud","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/j.ecolmodel.2009.03.011","article-title":"Post-fire vegetation regrowth detection in the Deiva Marina region (Liguria-Italy) using Landsat TM and ETM+ data","volume":"221","author":"Vila","year":"2010","journal-title":"Ecol. Model."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/j.ecolind.2015.11.026","article-title":"Remote sensing approach to detect post-fire vegetation regrowth in Siberian boreal larch forest","volume":"62","author":"Chu","year":"2016","journal-title":"Ecol. Indic."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"2017","DOI":"10.3390\/s8032017","article-title":"Monitoring the Effects of Forest Restoration Treatments on Post-Fire Vegetation Recovery with MODIS Multitemporal Data","volume":"8","year":"2008","journal-title":"Sensors"},{"key":"ref_71","unstructured":"Ch\u00e1vez, R.O. (2014). Assessing Water Stress of Desert Vegetation Using Remote Sensing: The Case of the Tamarugo Forest in the Atacama Desert (Northern Chile). [Ph.D. Thesis, Wageningen University]."},{"key":"ref_72","first-page":"44","article-title":"Effects of Forest Fire on Understory Vegetation Diversity and Biomass of Larix gmelini Forest","volume":"44","author":"Shi","year":"2016","journal-title":"J. Northeast For. U."},{"key":"ref_73","first-page":"272","article-title":"Study on vegetation regeneration of burned land in Xiaoxing\u2019an Mountains","volume":"2","author":"Shang","year":"2012","journal-title":"Guide Sci. Tech."},{"key":"ref_74","first-page":"125","article-title":"Review on the Recovery after the Catastrophic Forest Fire in Daxing\u2019anling Mountains","volume":"2","author":"Zhao","year":"2013","journal-title":"For. Resour. Manag."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.foreco.2003.11.006","article-title":"Prescribed burning and productivity in southern pine forests: A review","volume":"191","author":"Carter","year":"2004","journal-title":"For. Ecol. Manag."},{"key":"ref_76","doi-asserted-by":"crossref","unstructured":"Abbate, A., Longoni, L., Ivanov, V.I., and Papini, M. (2019). Wildfire Impacts on Slope Stability Triggering in Mountain Areas. Geosciences, 9.","DOI":"10.3390\/geosciences9100417"}],"container-title":["Sustainability"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2071-1050\/13\/1\/432\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:07:15Z","timestamp":1760159235000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2071-1050\/13\/1\/432"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,1,5]]},"references-count":76,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2021,1]]}},"alternative-id":["su13010432"],"URL":"https:\/\/doi.org\/10.3390\/su13010432","relation":{},"ISSN":["2071-1050"],"issn-type":[{"value":"2071-1050","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,1,5]]}}}