Gerard, F.,
Plummer, S.,
Wadsworth, R.,
Sanfeliu, A.F.,
Iliffe, L.,
Balzter, H.,
Wyatt, B.,
Forest fire scar detection in the boreal forest with multitemporal
spot-vegetation data,
GeoRS(41), No. 11, November 2003, pp. 2575-2585.
IEEE Abstract.
0311
BibRef
Brewer, C.K.[C. Kenneth],
Winne, J.C.[J. Chris],
Redmond, R.L.[Roland L.],
Opitz, D.W.[David W.],
Mangrich, M.V.[Mark V.],
Classifying and Mapping Wildfire Severity: A Comparison of Methods,
PhEngRS(71), No. 11, November 2005, pp. 1311-1320.
WWW Link.
0602
A comparison of six remote sensing methods for classifying and mapping
wildfire severity on forests and rangelands: artificial networks,
principal component analysis, and normalized temporal image
differencing.
BibRef
Henry, M.C.[Mary C.],
Comparison of Single- and Multi-date Landsat Data for Mapping Wildfire
Scars in Ocala National Forest, Florida,
PhEngRS(74), No. 7, July 2008, pp. 881-892.
WWW Link.
0804
Datasets classified using a traditional maximum likelihood
classification method and a non-parametric classification and
regression tree technique.
BibRef
Mitri, G.H.,
Gitas, I.Z.,
Mapping Postfire Vegetation Recovery Using EO-1 Hyperion Imagery,
GeoRS(48), No. 3, March 2010, pp. 1613-1618.
IEEE DOI
1003
BibRef
Lhermitte, S.,
Verbesselt, J.,
Verstraeten, W.W.,
Veraverbeke, S.,
Coppin, P.,
Assessing intra-annual vegetation regrowth after fire using the pixel
based regeneration index,
PandRS(66), No. 1, January 2011, pp. 17-27.
Elsevier DOI
1101
Forest fire; Monitoring; Temporal; Spatial; Vegetation
BibRef
Tanase, M.A.,
Perez-Cabello, F.,
de la Riva, J.,
Santoro, M.,
TerraSAR-X Data for Burn Severity Evaluation in Mediterranean Forests
on Sloped Terrain,
GeoRS(48), No. 2, February 2010, pp. 917-929.
IEEE DOI
1002
BibRef
Zhang, X.Y.[Xiao-Yang],
Kondragunta, S.,
Quayle, B.,
Estimation of Biomass Burned Areas Using Multiple-Satellite-Observed
Active Fires,
GeoRS(49), No. 11, November 2011, pp. 4469-4482.
IEEE DOI
1112
BibRef
Magnussen, S.,
Wulder, M.,
Post-Fire Canopy Height Recovery in Canada's Boreal Forests Using
Airborne Laser Scanner (ALS),
RS(4), No. 6, June 2012, pp. 1600-1616.
DOI Link
1208
BibRef
Polychronaki, A.,
Gitas, I.,
Burned Area Mapping in Greece Using SPOT-4 HRVIR Images and
Object-Based Image Analysis,
RS(4), No. 2, February 2012, pp. 424-438.
DOI Link
1203
BibRef
Bastarrika, A.,
Chuvieco, E.,
Martin, M.P.,
Automatic Burned Land Mapping From MODIS Time Series Images:
Assessment in Mediterranean Ecosystems,
GeoRS(49), No. 9, September 2011, pp. 3401-3413.
IEEE DOI
1109
BibRef
Libonati, R.,
da Camara, C.C.,
Pereira, J.M.C.,
Peres, L.F.,
Retrieving Middle-Infrared Reflectance Using Physical and Empirical
Approaches: Implications for Burned Area Monitoring,
GeoRS(50), No. 1, January 2012, pp. 281-294.
IEEE DOI
1201
BibRef
Veraverbeke, S.,
Gitas, I.,
Katagis, T.,
Polychronaki, A.,
Somers, B.,
Goossens, R.,
Assessing post-fire vegetation recovery using red-near infrared
vegetation indices: Accounting for background and vegetation
variability,
PandRS(68), No. 1, March 2012, pp. 28-39.
Elsevier DOI
1204
BibRef
And:
Erratum:
PandRS(68), No. 1, March 2012, pp. 191.
Elsevier DOI
1204
Forestry; Vegetation; Forest fire; Landsat; Spectral
BibRef
Leon, J.,
van Leeuwen, W.,
Casady, G.,
Using MODIS-NDVI for the Modeling of Post-Wildfire Vegetation Response
as a Function of Environmental Conditions and Pre-Fire Restoration
Treatments,
RS(4), No. 3, March 2012, pp. 598-621;.
DOI Link
1204
BibRef
Sedano, F.,
Kempeneers, P.,
Strobl, P.,
McInerney, D.O.,
San Miguel-Ayanz, J.,
Increasing Spatial Detail of Burned Scar Maps Using IRS-AWiFS Data for
Mediterranean Europe,
RS(4), No. 3, March 2012, pp. 726-744;.
DOI Link
1204
BibRef
Kempeneers, P.,
Sedano, F.,
Strobl, P.,
McInerney, D.O.,
San Miguel-Ayanz, J.,
Increasing Robustness of Postclassification Change Detection Using Time
Series of Land Cover Maps,
GeoRS(50), No. 9, September 2012, pp. 3327-3339.
IEEE DOI
1209
BibRef
Stroppiana, D.,
Bordogna, G.,
Carrara, P.,
Boschetti, M.,
Boschetti, L.,
Brivio, P.A.,
A method for extracting burned areas from Landsat TM/ETM+ images by
soft aggregation of multiple Spectral Indices and a region growing
algorithm,
PandRS(69), No. 1, April 2012, pp. 88-102.
Elsevier DOI
1202
Fuzzy set theory; Fire perimeters; Multi-criteria approach;
Mediterranean environment
BibRef
Moreira de Araújo, F.,
Ferreira, L.,
Arantes, A.,
Distribution Patterns of Burned Areas in the Brazilian Biomes: An
Analysis Based on Satellite Data for the 2002-2010 Period,
RS(4), No. 7, July 2012, pp. 1929-1946.
DOI Link
1208
BibRef
Chu, T.[Thuan],
Guo, X.[Xulin],
Remote Sensing Techniques in Monitoring Post-Fire Effects and
Patterns of Forest Recovery in Boreal Forest Regions: A Review,
RS(6), No. 1, 2013, pp. 470-520.
DOI Link
1402
BibRef
Yi, K.P.[Kun-Peng],
Tani, H.[Hiroshi],
Zhang, J.Q.[Ji-Quan],
Guo, M.[Meng],
Wang, X.F.[Xiu-Feng],
Zhong, G.S.[Guo-Sheng],
Long-Term Satellite Detection of Post-Fire Vegetation Trends in
Boreal Forests of China,
RS(5), No. 12, 2013, pp. 6938-6957.
DOI Link
1402
BibRef
Pleniou, M.[Magdalini],
Koutsias, N.[Nikos],
Sensitivity of spectral reflectance values to different burn and
vegetation ratios: A multi-scale approach applied in a fire affected
area,
PandRS(79), No. 1, May 2013, pp. 199-210.
Elsevier DOI
1305
Spectral properties; Sub-pixel; Burned surfaces; LANDSAT; ASTER;
IKONOS
BibRef
Huang, S.L.[Sheng-Li],
Jin, S.[Suming],
Dahal, D.[Devendra],
Chen, X.X.[Xue-Xia],
Young, C.[Claudia],
Liu, H.P.[He-Ping],
Liu, S.G.[Shu-Guang],
Reconstructing satellite images to quantify spatially explicit land
surface change caused by fires and succession: A demonstration in the
Yukon River Basin of interior Alaska,
PandRS(79), No. 1, May 2013, pp. 94-105.
Elsevier DOI
1305
Alaska; Fire; Land surface; Landsat; Image reconstruction; NDVI
BibRef
Polychronaki, A.[Anastasia],
Gitas, I.Z.[Ioannis Z.],
Veraverbeke, S.[Sander],
Debien, A.[Annekatrien],
Evaluation of ALOS PALSAR Imagery for Burned Area Mapping in Greece
Using Object-Based Classification,
RS(5), No. 11, 2013, pp. 5680-5701.
DOI Link
1312
BibRef
Moreno Ruiz, J.A.[José Andrés],
García Lázaro, J.R.[José Rafael],
del Águila Cano, I.[Isabel],
Hernández Leal, P.[Pedro],
Burned Area Mapping in the North American Boreal Forest Using
Terra-MODIS LTDR (2001-2011): A Comparison with the MCD45A1, MCD64A1
and BA GEOLAND-2 Products,
RS(6), No. 1, 2014, pp. 815-840.
DOI Link
1402
BibRef
Tsela, P.[Philemon],
Wessels, K.[Konrad],
Botai, J.[Joel],
Archibald, S.[Sally],
Swanepoel, D.[Derick],
Steenkamp, K.[Karen],
Frost, P.[Philip],
Validation of the Two Standard MODIS Satellite Burned-Area Products
and an Empirically-Derived Merged Product in South Africa,
RS(6), No. 2, 2014, pp. 1275-1293.
DOI Link
1403
BibRef
Schepers, L.[Lennert],
Haest, B.[Birgen],
Veraverbeke, S.[Sander],
Spanhove, T.[Toon],
Vanden Borre, J.[Jeroen],
Goossens, R.[Rudi],
Burned Area Detection and Burn Severity Assessment of a Heathland
Fire in Belgium Using Airborne Imaging Spectroscopy (APEX),
RS(6), No. 3, 2014, pp. 1803-1826.
DOI Link
1404
BibRef
Parks, S.A.[Sean A.],
Dillon, G.K.[Gregory K.],
Miller, C.[Carol],
A New Metric for Quantifying Burn Severity:
The Relativized Burn Ratio,
RS(6), No. 3, 2014, pp. 1827-1844.
DOI Link
1404
BibRef
And:
Correction:
RS(6), No. 12, 2014, pp. 12509-12510.
DOI Link
1412
BibRef
Padilla, M.[Marc],
Stehman, S.V.[Stephen V.],
Litago, J.[Javier],
Chuvieco, E.[Emilio],
Assessing the Temporal Stability of the Accuracy of a Time Series of
Burned Area Products,
RS(6), No. 3, 2014, pp. 2050-2068.
DOI Link
1404
BibRef
Kalogirou, V.,
Ferrazzoli, P.,
Della Vecchia, A.,
Foumelis, M.,
On the SAR Backscatter of Burned Forests: A Model-Based Study in
C-Band, Over Burned Pine Canopies,
GeoRS(52), No. 10, October 2014, pp. 6205-6215.
IEEE DOI
1407
Backscatter
BibRef
da Silva Cardozo, F.[Francielle],
Pereira, G.[Gabriel],
Shimabukuro, Y.E.[Yosio Edemir],
Moraes, E.C.[Elisabete Caria],
Analysis and Assessment of the Spatial and Temporal Distribution of
Burned Areas in the Amazon Forest,
RS(6), No. 9, 2014, pp. 8002-8025.
DOI Link
1410
BibRef
Dragozi, E.[Eleni],
Gitas, I.Z.[Ioannis Z.],
Stavrakoudis, D.G.[Dimitris G.],
Theocharis, J.B.[John B.],
Burned Area Mapping Using Support Vector Machines and the FuzCoC
Feature Selection Method on VHR IKONOS Imagery,
RS(6), No. 12, 2014, pp. 12005-12036.
DOI Link
1412
BibRef
Nioti, F.[Foula],
Xystrakis, F.[Fotios],
Koutsias, N.[Nikos],
Dimopoulos, P.[Panayotis],
A Remote Sensing and GIS Approach to Study the Long-Term Vegetation
Recovery of a Fire-Affected Pine Forest in Southern Greece,
RS(7), No. 6, 2015, pp. 7712.
DOI Link
1507
BibRef
Dragozi, E.[Eleni],
Gitas, I.Z.[Ioannis Z.],
Bajocco, S.[Sofia],
Stavrakoudis, D.G.[Dimitris G.],
Exploring the Relationship between Burn Severity Field Data and Very
High Resolution GeoEye Images: The Case of the 2011 Evros Wildfire in
Greece,
RS(8), No. 7, 2016, pp. 566.
DOI Link
1608
BibRef
Bishop, B.D.[Brian D.],
Dietterick, B.C.[Brian C.],
White, R.A.[Russell A.],
Mastin, T.B.[Tom B.],
Classification of Plot-Level Fire-Caused Tree Mortality in a Redwood
Forest Using Digital Orthophotography and LiDAR,
RS(6), No. 3, 2014, pp. 1954-1972.
DOI Link
1404
BibRef
Bastarrika, A.[Aitor],
Alvarado, M.[Maite],
Artano, K.[Karmele],
Martinez, M.P.[Maria Pilar],
Mesanza, A.[Amaia],
Torre, L.[Leyre],
Ramo, R.[Rubén],
Chuvieco, E.[Emilio],
BAMS: A Tool for Supervised Burned Area Mapping Using Landsat Data,
RS(6), No. 12, 2014, pp. 12360-12380.
DOI Link
1412
BibRef
Bernhard, E.M.[Eva-Maria],
Twele, A.[André],
Martinis, S.[Sandro],
The Effect of Vegetation Type and Density on X-Band SAR Backscatter
after Forest Fires,
PFG(2014), No. 4, 2014, pp. 275-285.
DOI Link
1410
BibRef
Chen, G.[Gang],
Metz, M.R.[Margaret R.],
Rizzo, D.M.[David M.],
Dillon, W.W.[Whalen W.],
Meentemeyer, R.K.[Ross K.],
Object-based assessment of burn severity in diseased forests using
high-spatial and high-spectral resolution MASTER airborne imagery,
PandRS(102), No. 1, 2015, pp. 38-47.
Elsevier DOI
1503
GEOBIA
BibRef
Stroppiana, D.[Daniela],
Azar, R.[Ramin],
Calò, F.[Fabiana],
Pepe, A.[Antonio],
Imperatore, P.[Pasquale],
Boschetti, M.[Mirco],
Silva, J.M.N.[João M. N.],
Brivio, P.A.[Pietro A.],
Lanari, R.[Riccardo],
Integration of Optical and SAR Data for Burned Area Mapping in
Mediterranean Regions,
RS(7), No. 2, 2015, pp. 1320-1345.
DOI Link
1503
BibRef
de Carvalho Júnior, O.A.[Osmar Abílio],
Guimarães, R.F.[Renato Fontes],
Silva, C.R.[Cristiano Rosa],
Gomes, R.A.T.[Roberto Arnaldo Trancoso],
Standardized Time-Series and Interannual Phenological Deviation:
New Techniques for Burned-Area Detection Using Long-Term MODIS-NBR Dataset,
RS(7), No. 6, 2015, pp. 6950.
DOI Link
1507
See also New Approach to Change Vector Analysis Using Distance and Similarity Measures, A.
BibRef
Libonati, R.[Renata],
DaCamara, C.C.[Carlos C.],
Setzer, A.W.[Alberto W.],
Morelli, F.[Fabiano],
Melchiori, A.E.[Arturo E.],
An Algorithm for Burned Area Detection in the Brazilian Cerrado Using
4µm MODIS Imagery,
RS(7), No. 11, 2015, pp. 15782.
DOI Link
1512
BibRef
Sánchez, J.M.[Juan M.],
Bisquert, M.[Mar],
Rubio, E.[Eva],
Caselles, V.[Vicente],
Impact of Land Cover Change Induced by a Fire Event on the Surface
Energy Fluxes Derived from Remote Sensing,
RS(7), No. 11, 2015, pp. 14899.
DOI Link
1512
BibRef
Huang, H.Y.[Hai-Yan],
Roy, D.P.[David P.],
Boschetti, L.[Luigi],
Zhang, H.K.[Hankui K.],
Yan, L.[Lin],
Kumar, S.S.[Sanath Sathyachandran],
Gomez-Dans, J.[Jose],
Li, J.[Jian],
Separability Analysis of Sentinel-2A Multi-Spectral Instrument (MSI)
Data for Burned Area Discrimination,
RS(8), No. 10, 2016, pp. 873.
DOI Link
1609
BibRef
Verhegghen, A.[Astrid],
Eva, H.[Hugh],
Ceccherini, G.[Guido],
Achard, F.[Frederic],
Gond, V.[Valery],
Gourlet-Fleury, S.[Sylvie],
Cerutti, P.O.[Paolo Omar],
The Potential of Sentinel Satellites for Burnt Area Mapping and
Monitoring in the Congo Basin Forests,
RS(8), No. 12, 2016, pp. 986.
DOI Link
1612
BibRef
Soulard, C.E.[Christopher E.],
Albano, C.M.[Christine M.],
Villarreal, M.L.[Miguel L.],
Walker, J.J.[Jessica J.],
Continuous 1985-2012 Landsat Monitoring to Assess Fire Effects on
Meadows in Yosemite National Park, California,
RS(8), No. 5, 2016, pp. 371.
DOI Link
1606
BibRef
Sparks, A.M.[Aaron M.],
Kolden, C.A.[Crystal A.],
Talhelm, A.F.[Alan F.],
Smith, A.M.S.[Alistair M.S.],
Apostol, K.G.[Kent G.],
Johnson, D.M.[Daniel M.],
Boschetti, L.[Luigi],
Spectral Indices Accurately Quantify Changes in Seedling Physiology
Following Fire: Towards Mechanistic Assessments of Post-Fire Carbon
Cycling,
RS(8), No. 7, 2016, pp. 572.
DOI Link
1608
BibRef
Llovería, R.M.[Raquel Montorio],
Pérez-Cabello, F.[Fernando],
García-Martín, A.[Alberto],
Assessing post-fire ground cover in Mediterranean shrublands with
field spectrometry and digital photography,
PandRS(119), No. 1, 2016, pp. 187-197.
Elsevier DOI
1610
Fire severity
BibRef
Sato, L.Y.[Luciane Yumie],
Gomes, V.C.F.[Vitor Conrado Faria],
Shimabukuro, Y.E.[Yosio Edemir],
Keller, M.[Michael],
Arai, E.[Egidio],
dos-Santos, M.N.[Maiza Nara],
Brown, I.F.[Irving Foster],
Oliveira e Cruz de Aragão, L.E.[Luiz Eduardo],
Post-Fire Changes in Forest Biomass Retrieved by Airborne LiDAR in
Amazonia,
RS(8), No. 10, 2016, pp. 839.
DOI Link
1609
BibRef
Zhao, F.R.[Feng R.],
Meng, R.[Ran],
Huang, C.Q.[Cheng-Quan],
Zhao, M.S.[Mao-Sheng],
Zhao, F.A.[Feng A.],
Gong, P.[Peng],
Yu, L.[Le],
Zhu, Z.L.[Zhi-Liang],
Long-Term Post-Disturbance Forest Recovery in the Greater Yellowstone
Ecosystem Analyzed Using Landsat Time Series Stack,
RS(8), No. 11, 2016, pp. 898.
DOI Link
1612
BibRef
Nogueira, J.M.P.[Joana M. P.],
Ruffault, J.[Julien],
Chuvieco, E.[Emilio],
Mouillot, F.[Florent],
Can We Go Beyond Burned Area in the Assessment of Global Remote
Sensing Products with Fire Patch Metrics?,
RS(9), No. 1, 2017, pp. xx-yy.
DOI Link
1702
BibRef
Fraser, R.H.[Robert H.],
van der Sluijs, J.[Jurjen],
Hall, R.J.[Ronald J.],
Calibrating Satellite-Based Indices of Burn Severity from UAV-Derived
Metrics of a Burned Boreal Forest in NWT, Canada,
RS(9), No. 3, 2017, pp. xx-yy.
DOI Link
1704
BibRef
Ayhan, B.[Bulent],
Kwan, C.[Chiman],
On the use of radiance domain for burn scar detection under varying
atmospheric illumination conditions and viewing geometry,
SIViP(11), No. 4, May 2017, pp. 605-612.
WWW Link.
1704
BibRef
Hess, K.A.[Katherine A.],
Cullen, C.[Cheila],
Cobian-Iñiguez, J.[Jeanette],
Ramthun, J.S.[Jacob S.],
Lenske, V.[Victor],
Magness, D.R.[Dawn R.],
Bolten, J.D.[John D.],
Foster, A.C.[Adrianna C.],
Spruce, J.[Joseph],
Satellite-Based Assessment of Grassland Conversion and Related Fire
Disturbance in the Kenai Peninsula, Alaska,
RS(11), No. 3, 2019, pp. xx-yy.
DOI Link
1902
BibRef
Morresi, D.[Donato],
Vitali, A.[Alessandro],
Urbinati, C.[Carlo],
Garbarino, M.[Matteo],
Forest Spectral Recovery and Regeneration Dynamics in Stand-Replacing
Wildfires of Central Apennines Derived from Landsat Time Series,
RS(11), No. 3, 2019, pp. xx-yy.
DOI Link
1902
BibRef
Campanharo, W.A.[Wesley A.],
Lopes, A.P.[Aline P.],
Anderson, L.O.[Liana O.],
da Silva, T.F.M.R.[Thiago F. M. R.],
Aragão, L.E.O.C.[Luiz E. O. C.],
Translating Fire Impacts in Southwestern Amazonia into Economic Costs,
RS(11), No. 7, 2019, pp. xx-yy.
DOI Link
1904
BibRef
Zhou, L.[Lei],
Wang, Y.H.[Yu-Hang],
Chi, Y.G.[Yong-Gang],
Wang, S.Q.[Shao-Qiang],
Wang, Q.[Quan],
Contrasting Post-Fire Dynamics between Africa and South America based
on MODIS Observations,
RS(11), No. 9, 2019, pp. xx-yy.
DOI Link
1905
BibRef
Saha, M.V.[Michael V.],
d'Odorico, P.[Paolo],
Scanlon, T.M.[Todd M.],
Kalahari Wildfires Drive Continental Post-Fire Brightening in
Sub-Saharan Africa,
RS(11), No. 9, 2019, pp. xx-yy.
DOI Link
1905
BibRef
Ayhan, B.[Bulent],
Kwan, C.[Chiman],
Tree, Shrub, and Grass Classification Using Only RGB Images,
RS(12), No. 8, 2020, pp. xx-yy.
DOI Link
2004
BibRef
Shan, T.C.[Tian-Chan],
Wang, C.L.[Chang-Lin],
Chen, F.[Fang],
Wu, Q.C.[Qin-Chun],
Li, B.[Bin],
Yu, B.[Bo],
Shirazi, Z.[Zeeshan],
Lin, Z.Y.[Zheng-Yang],
Wu, W.[Wei],
A Burned Area Mapping Algorithm for Chinese FengYun-3 MERSI Satellite
Data,
RS(9), No. 7, 2017, pp. xx-yy.
DOI Link
1708
BibRef
Engelbrecht, J.[Jeanine],
Theron, A.[Andre],
Vhengani, L.[Lufuno],
Kemp, J.[Jaco],
A Simple Normalized Difference Approach to Burnt Area Mapping Using
Multi-Polarisation C-Band SAR,
RS(9), No. 8, 2017, pp. xx-yy.
DOI Link
1708
BibRef
Pereira, A.A.[Allan A.],
Pereira, J.M.C.[José M. C.],
Libonati, R.[Renata],
Oom, D.[Duarte],
Setzer, A.W.[Alberto W.],
Morelli, F.[Fabiano],
Machado-Silva, F.[Fausto],
de Carvalho, L.M.T.[Luis Marcelo Tavares],
Burned Area Mapping in the Brazilian Savanna Using a One-Class
Support Vector Machine Trained by Active Fires,
RS(9), No. 11, 2017, pp. xx-yy.
DOI Link
1712
BibRef
Pereira, A.A.[Allan A.],
Libonati, R.[Renata],
Rodrigues, J.A.[Julia A.],
Nogueira, J.[Joana],
Santos, F.L.M.[Filippe L. M.],
Oom, D.[Duarte],
Sanches, W.[Waislan],
Alvarado, S.T.[Swanni T.],
Pereira, J.M.C.[José M. C.],
Multi-Sensor, Active Fire-Supervised, One-Class Burned Area Mapping
in the Brazilian Savanna,
RS(13), No. 19, 2021, pp. xx-yy.
DOI Link
2110
BibRef
Ramo, R.[Rubén],
Chuvieco, E.[Emilio],
Developing a Random Forest Algorithm for MODIS Global Burned Area
Classification,
RS(9), No. 11, 2017, pp. xx-yy.
DOI Link
1712
BibRef
Wang, J.J.[Jun-Jie],
Wang, C.Z.[Cui-Zhen],
Zang, S.Y.[Shu-Ying],
Assessing Re-Composition of Xing'an Larch in Boreal Forests after the
1987 Fire, Northeast China,
RS(9), No. 5, 2017, pp. xx-yy.
DOI Link
1706
BibRef
Mithal, V.[Varun],
Nayak, G.[Guruprasad],
Khandelwal, A.[Ankush],
Kumar, V.[Vipin],
Nemani, R.[Ramakrishna],
Oza, N.C.[Nikunj C.],
Mapping Burned Areas in Tropical Forests Using a Novel Machine
Learning Framework,
RS(10), No. 1, 2018, pp. xx-yy.
DOI Link
1802
BibRef
Axel, A.C.[Anne C.],
Burned Area Mapping of an Escaped Fire into Tropical Dry Forest in
Western Madagascar Using Multi-Season Landsat OLI Data,
RS(10), No. 3, 2018, pp. xx-yy.
DOI Link
1804
BibRef
Tane, Z.[Zachary],
Roberts, D.[Dar],
Veraverbeke, S.[Sander],
Casas, Á.[Ángeles],
Ramirez, C.[Carlos],
Ustin, S.[Susan],
Evaluating Endmember and Band Selection Techniques for Multiple
Endmember Spectral Mixture Analysis using Post-Fire Imaging
Spectroscopy,
RS(10), No. 3, 2018, pp. xx-yy.
DOI Link
1804
BibRef
Hislop, S.[Samuel],
Jones, S.[Simon],
Soto-Berelov, M.[Mariela],
Skidmore, A.[Andrew],
Haywood, A.[Andrew],
Nguyen, T.H.[Trung H.],
Using Landsat Spectral Indices in Time-Series to Assess Wildfire
Disturbance and Recovery,
RS(10), No. 3, 2018, pp. xx-yy.
DOI Link
1804
See also Comparison of Imputation Approaches for Estimating Forest Biomass Using Landsat Time-Series and Inventory Data, A.
BibRef
Melchiorre, A.[Andrea],
Boschetti, L.[Luigi],
Global Analysis of Burned Area Persistence Time with MODIS Data,
RS(10), No. 5, 2018, pp. xx-yy.
DOI Link
1806
BibRef
Boonprong, S.[Sornkitja],
Cao, C.X.[Chun-Xiang],
Chen, W.[Wei],
Bao, S.N.[Shan-Ning],
Random Forest Variable Importance Spectral Indices Scheme for Burnt
Forest Recovery Monitoring: Multilevel RF-VIMP,
RS(10), No. 6, 2018, pp. xx-yy.
DOI Link
1806
BibRef
García-Lázaro, J.R.[José R.],
Moreno-Ruiz, J.A.[José A.],
Riaño, D.[David],
Arbelo, M.[Manuel],
Estimation of Burned Area in the Northeastern Siberian Boreal Forest
from a Long-Term Data Record (LTDR) 1982-2015 Time Series,
RS(10), No. 6, 2018, pp. xx-yy.
DOI Link
1806
BibRef
Cabral, A.I.R.[Ana I.R.],
Silva, S.[Sara],
Silva, P.C.[Pedro C.],
Vanneschi, L.[Leonardo],
Vasconcelos, M.J.[Maria J.],
Burned area estimations derived from Landsat ETM+ and OLI data:
Comparing Genetic Programming with Maximum Likelihood and
Classification and Regression Trees,
PandRS(142), 2018, pp. 94-105.
Elsevier DOI
1807
Burned area mapping, Genetic Programming, Savana woodlands,
Classification and Regression Trees, Maximum Likelihood, Landsat ETM+/OLI
BibRef
Li, X.D.[Xue-Dong],
Zhang, H.Y.[Hong-Yan],
Yang, G.B.[Guang-Bin],
Ding, Y.L.[Yan-Ling],
Zhao, J.J.[Jian-Jun],
Post-Fire Vegetation Succession and Surface Energy Fluxes Derived
from Remote Sensing,
RS(10), No. 7, 2018, pp. xx-yy.
DOI Link
1808
BibRef
Fornacca, D.[Davide],
Ren, G.[Guopeng],
Xiao, W.[Wen],
Evaluating the Best Spectral Indices for the Detection of Burn Scars
at Several Post-Fire Dates in a Mountainous Region of Northwest
Yunnan, China,
RS(10), No. 8, 2018, pp. xx-yy.
DOI Link
1809
BibRef
Maffei, C.[Carmine],
Alfieri, S.M.[Silvia Maria],
Menenti, M.[Massimo],
Relating Spatiotemporal Patterns of Forest Fires Burned Area and
Duration to Diurnal Land Surface Temperature Anomalies,
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link
1812
BibRef
Santana, N.C.[Níckolas Castro],
de Carvalho Júnior, O.A.[Osmar Abílio],
Gomes, R.A.T.[Roberto Arnaldo Trancoso],
Guimarães, R.F.[Renato Fontes],
Burned-Area Detection in Amazonian Environments Using Standardized
Time Series Per Pixel in MODIS Data,
RS(10), No. 12, 2018, pp. xx-yy.
DOI Link
1901
BibRef
Plank, S.[Simon],
Martinis, S.[Sandro],
A Fully Automatic Burnt Area Mapping Processor Based on AVHRR
Imagery: A TIMELINE Thematic Processor,
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link
1804
See also Fully Automatic Instantaneous Fire Hotspot Detection Processor Based on AVHRR Imagery: A TIMELINE Thematic Processor, A.
BibRef
Fava, F.[Francesco],
Colombo, R.[Roberto],
Remote Sensing-Based Assessment of the 2005-2011 Bamboo Reproductive
Event in the Arakan Mountain Range and Its Relation with Wildfires,
RS(9), No. 1, 2017, pp. xx-yy.
DOI Link
1702
BibRef
Fernández-García, V.[Víctor],
Quintano, C.[Carmen],
Taboada, A.[Angela],
Marcos, E.[Elena],
Calvo, L.[Leonor],
Fernández-Manso, A.[Alfonso],
Remote Sensing Applied to the Study of Fire Regime Attributes and
Their Influence on Post-Fire Greenness Recovery in Pine Ecosystems,
RS(10), No. 5, 2018, pp. xx-yy.
DOI Link
1806
BibRef
Ryu, J.H.[Jae-Hyun],
Han, K.S.[Kyung-Soo],
Hong, S.[Sungwook],
Park, N.W.[No-Wook],
Lee, Y.W.[Yang-Won],
Cho, J.[Jaeil],
Satellite-Based Evaluation of the Post-Fire Recovery Process from the
Worst Forest Fire Case in South Korea,
RS(10), No. 6, 2018, pp. xx-yy.
DOI Link
1806
BibRef
Michael, Y.[Yaron],
Lensky, I.M.[Itamar M.],
Brenner, S.[Steve],
Tchetchik, A.[Anat],
Tessler, N.[Naama],
Helman, D.[David],
Economic Assessment of Fire Damage to Urban Forest in the
Wildland-Urban Interface Using Planet Satellites Constellation Images,
RS(10), No. 9, 2018, pp. xx-yy.
DOI Link
1810
BibRef
Vasilakos, C.[Christos],
Tsekouras, G.E.[George E.],
Palaiologou, P.[Palaiologos],
Kalabokidis, K.[Kostas],
Neural-Network Time-Series Analysis of MODIS EVI for Post-Fire
Vegetation Regrowth,
IJGI(7), No. 11, 2018, pp. xx-yy.
DOI Link
1812
BibRef
Henry, M.C.[Mary C.],
Maingi, J.K.[John K.],
McCarty, J.[Jessica],
Fire on the Water Towers: Mapping Burn Scars on Mount Kenya Using
Satellite Data to Reconstruct Recent Fire History,
RS(11), No. 2, 2019, pp. xx-yy.
DOI Link
1902
BibRef
Ba, R.[Rui],
Song, W.G.[Wei-Guo],
Li, X.L.[Xiao-Lian],
Xie, Z.X.[Zi-Xi],
Lo, S.M.[Siu-Ming],
Integration of Multiple Spectral Indices and a Neural Network for
Burned Area Mapping Based on MODIS Data,
RS(11), No. 3, 2019, pp. xx-yy.
DOI Link
1902
BibRef
Fang, L.[Lei],
Crocker, E.V.[Ellen V.],
Yang, J.[Jian],
Yan, Y.[Yan],
Yang, Y.Z.[Yuan-Zheng],
Liu, Z.H.[Zhi-Hua],
Competition and Burn Severity Determine Post-Fire Sapling Recovery in
a Nationally Protected Boreal Forest of China: An Analysis from Very
High-Resolution Satellite Imagery,
RS(11), No. 6, 2019, pp. xx-yy.
DOI Link
1903
BibRef
Filipponi, F.[Federico],
Exploitation of Sentinel-2 Time Series to Map Burned Areas at the
National Level: A Case Study on the 2017 Italy Wildfires,
RS(11), No. 6, 2019, pp. xx-yy.
DOI Link
1903
BibRef
Long, T.F.[Teng-Fei],
Zhang, Z.M.[Zhao-Ming],
He, G.J.[Guo-Jin],
Jiao, W.L.[Wei-Li],
Tang, C.[Chao],
Wu, B.F.[Bing-Fang],
Zhang, X.O.[Xia-Omei],
Wang, G.Z.[Gui-Zhou],
Yin, R.[Ranyu],
30 m Resolution Global Annual Burned Area Mapping Based on Landsat
Images and Google Earth Engine,
RS(11), No. 5, 2019, pp. xx-yy.
DOI Link
1903
BibRef
Fernandez-Manso, A.[Alfonso],
Quintano, C.[Carmen],
Roberts, D.A.[Dar A.],
Burn severity analysis in Mediterranean forests using maximum entropy
model trained with EO-1 Hyperion and LiDAR data,
PandRS(155), 2019, pp. 102-118.
Elsevier DOI
1908
Burn severity, EO-1 Hyperion, LiDAR, MaxEnt
BibRef
Quintano, C.[Carmen],
Fernández-Manso, A.[Alfonso],
Calvo, L.[Leonor],
Roberts, D.A.[Dar A.],
Vegetation and Soil Fire Damage Analysis Based on Species
Distribution Modeling Trained with Multispectral Satellite Data,
RS(11), No. 15, 2019, pp. xx-yy.
DOI Link
1908
BibRef
Otón, G.[Gonzalo],
Ramo, R.[Rubén],
Lizundia-Loiola, J.[Joshua],
Chuvieco, E.[Emilio],
Global Detection of Long-Term (1982-2017) Burned Area with AVHRR-LTDR
Data,
RS(11), No. 18, 2019, pp. xx-yy.
DOI Link
1909
BibRef
And:
Correction:
RS(12), No. 14, 2020, pp. xx-yy.
DOI Link
2007
BibRef
Quintano, C.[Carmen],
Fernandez-Manso, A.[Alfonso],
Marcos, E.[Elena],
Calvo, L.[Leonor],
Burn Severity and Post-Fire Land Surface Albedo Relationship in
Mediterranean Forest Ecosystems,
RS(11), No. 19, 2019, pp. xx-yy.
DOI Link
1910
BibRef
Wozniak, E.[Edyta],
Aleksansdrowicz, S.[Sebastian],
Self-Adjusting Thresholding for Burnt Area Detection Based on Optical
Images,
RS(11), No. 22, 2019, pp. xx-yy.
DOI Link
1911
BibRef
Wang, P.[Peng],
Zhang, L.[Lei],
Zhang, G.[Gong],
Jin, B.Z.[Ben-Zhou],
Leung, H.[Henry],
Multispectral Image Super-Resolution Burned-Area Mapping Based on
Space-Temperature Information,
RS(11), No. 22, 2019, pp. xx-yy.
DOI Link
1911
BibRef
Wang, L.G.[Li-Guo],
Hao, S.Y.[Si-Yuan],
Wang, Q.M.[Qun-Ming],
Wang, Y.[Ying],
Semi-supervised classification for hyperspectral imagery based on
spatial-spectral Label Propagation,
PandRS(97), No. 1, 2014, pp. 123-137.
Elsevier DOI
1410
Hyperspectral imagery
BibRef
Wang, P.[Peng],
Wang, L.G.[Li-Guo],
Leung, H.[Henry],
Zhang, G.[Gong],
Super-Resolution Mapping Based on Spatial-Spectral Correlation for
Spectral Imagery,
GeoRS(59), No. 3, March 2021, pp. 2256-2268.
IEEE DOI
2103
Correlation, Imaging, Euclidean distance, Optimization,
Resource management, Probability density function,
super-resolution mapping (SRM)
BibRef
Belenguer-Plomer, M.A.[Miguel A.],
Chuvieco, E.[Emilio],
Tanase, M.A.[Mihai A.],
Temporal Decorrelation of C-Band Backscatter Coefficient in
Mediterranean Burned Areas,
RS(11), No. 22, 2019, pp. xx-yy.
DOI Link
1911
BibRef
Maffei, C.[Carmine],
Menenti, M.[Massimo],
Predicting forest fires burned area and rate of spread from pre-fire
multispectral satellite measurements,
PandRS(158), 2019, pp. 263-278.
Elsevier DOI
1912
MODIS, Perpendicular Moisture Index (PMI),
Fire Weather Index (FWI), Live fuel moisture content (LFMC),
Probability of extreme events
BibRef
Walker, J.J.[Jessica J.],
Soulard, C.E.[Christopher E.],
Phenology Patterns Indicate Recovery Trajectories of Ponderosa Pine
Forests After High-Severity Fires,
RS(11), No. 23, 2019, pp. xx-yy.
DOI Link
1912
BibRef
Zhang, P.[Puzhao],
Nascetti, A.[Andrea],
Ban, Y.F.[Yi-Fang],
Gong, M.[Maoguo],
An implicit radar convolutional burn index for burnt area mapping
with Sentinel-1 C-band SAR data,
PandRS(158), 2019, pp. 50-62.
Elsevier DOI
1912
Sentinel-1 SAR, Burnt area mapping, InSAR coherence,
Change detection, Fully Convolutional Networks (FCN),
Radar Convolutional Burn Index (RCBI)
BibRef
Kibler, C.L.[Christopher L.],
Parkinson, A.M.L.[Anne-Marie L.],
Peterson, S.H.[Seth H.],
Roberts, D.A.[Dar A.],
d'Antonio, C.M.[Carla M.],
Meerdink, S.K.[Susan K.],
Sweeney, S.H.[Stuart H.],
Monitoring Post-Fire Recovery of Chaparral and Conifer Species Using
Field Surveys and Landsat Time Series,
RS(11), No. 24, 2019, pp. xx-yy.
DOI Link
1912
BibRef
Chen, Y.P.[Ya-Ping],
Lara, M.J.[Mark Jason],
Hu, F.S.[Feng Sheng],
A robust visible near-infrared index for fire severity mapping in
Arctic tundra ecosystems,
PandRS(159), 2020, pp. 101-113.
Elsevier DOI
1912
Burn severity, Disturbance,
Global Environmental Monitoring Index, Multispectral index, Wildfire
BibRef
Chen, D.[Dong],
Loboda, T.V.[Tatiana V.],
Hall, J.V.[Joanne V.],
A systematic evaluation of influence of image selection process on
remote sensing-based burn severity indices in North American boreal
forest and tundra ecosystems,
PandRS(159), 2020, pp. 63-77.
Elsevier DOI
1912
Boreal forest, Tundra, ABoVE, Alaska, Canada, Remote sensing,
Disturbance, Wildfire, Burn severity, dNBR, Landsat
BibRef
Wang, J.M.[Jian-Min],
Zhang, X.Y.[Xiao-Yang],
Investigation of wildfire impacts on land surface phenology from
MODIS time series in the western US forests,
PandRS(159), 2020, pp. 281-295.
Elsevier DOI
1912
Land surface phenology, Forest, Wildfire, Timing, Greenness,
MODIS, Western US
BibRef
Adrianto, H.A.[Hari A.],
Spracklen, D.V.[Dominick V.],
Arnold, S.R.[Stephen R.],
Sitanggang, I.S.[Imas S.],
Syaufina, L.[Lailan],
Forest and Land Fires Are Mainly Associated with Deforestation in
Riau Province, Indonesia,
RS(12), No. 1, 2019, pp. xx-yy.
DOI Link
2001
BibRef
Lizundia-Loiola, J.[Joshua],
Pettinari, M.L.[M. Lucrecia],
Chuvieco, E.[Emilio],
Temporal Anomalies in Burned Area Trends: Satellite Estimations of
the Amazonian 2019 Fire Crisis,
RS(12), No. 1, 2020, pp. xx-yy.
DOI Link
2001
BibRef
Tanase, M.A.[Mihai A.],
Belenguer-Plomer, M.A.[Miguel A.],
Roteta, E.[Ekhi],
Bastarrika, A.[Aitor],
Wheeler, J.[James],
Fernández-Carrillo, Á.[Ángel],
Tansey, K.[Kevin],
Wiedemann, W.[Werner],
Navratil, P.[Peter],
Lohberger, S.[Sandra],
Siegert, F.[Florian],
Chuvieco, E.[Emilio],
Burned Area Detection and Mapping: Intercomparison of Sentinel-1 and
Sentinel-2 Based Algorithms over Tropical Africa,
RS(12), No. 2, 2020, pp. xx-yy.
DOI Link
2001
BibRef
Liu, M.[Meng],
Popescu, S.[Sorin],
Malambo, L.[Lonesome],
Feasibility of Burned Area Mapping Based on ICESAT-2 Photon Counting
Data,
RS(12), No. 1, 2019, pp. xx-yy.
DOI Link
2001
BibRef
Malambo, L.[Lonesome],
Heatwole, C.D.[Conrad D.],
Automated training sample definition for seasonal burned area mapping,
PandRS(160), 2020, pp. 107-123.
Elsevier DOI
2001
Fire, Burned area, Automatic training, Abrupt change, Clustering,
Fuzzy c-means, Landsat, Random Forest, Zambia, Southern Africa
BibRef
Pinto, M.M.[Miguel M.],
Libonati, R.[Renata],
Trigo, R.M.[Ricardo M.],
Trigo, I.F.[Isabel F.],
DaCamara, C.C.[Carlos C.],
A deep learning approach for mapping and dating burned areas using
temporal sequences of satellite images,
PandRS(160), 2020, pp. 260-274.
Elsevier DOI
2001
Burned areas, Wildfires, VIIRS, Segmentation, Deep learning
BibRef
Franco, M.G.[María Guadalupe],
Mundo, I.A.[Ignacio A.],
Veblen, T.T.[Thomas T.],
Field-Validated Burn-Severity Mapping in North Patagonian Forests,
RS(12), No. 2, 2020, pp. xx-yy.
DOI Link
2001
BibRef
Philipp, M.B.[Marius B.],
Levick, S.R.[Shaun R.],
Exploring the Potential of C-Band SAR in Contributing to Burn
Severity Mapping in Tropical Savanna,
RS(12), No. 1, 2019, pp. xx-yy.
DOI Link
2001
BibRef
Saulino, L.[Luigi],
Rita, A.[Angelo],
Migliozzi, A.[Antonello],
Maffei, C.[Carmine],
Allevato, E.[Emilia],
Garonna, A.P.[Antonio Pietro],
Saracino, A.[Antonio],
Detecting Burn Severity across Mediterranean Forest Types by Coupling
Medium-Spatial Resolution Satellite Imagery and Field Data,
RS(12), No. 4, 2020, pp. xx-yy.
DOI Link
2003
BibRef
Zheng, Z.[Zhong],
Wang, J.F.[Jin-Fei],
Shan, B.[Bo],
He, Y.J.[Yong-Jun],
Liao, C.H.[Chun-Hua],
Gao, Y.H.[Yang-Hua],
Yang, S.Q.[Shi-Qi],
A New Model for Transfer Learning-Based Mapping of Burn Severity,
RS(12), No. 4, 2020, pp. xx-yy.
DOI Link
2003
BibRef
Pulvirenti, L.[Luca],
Squicciarino, G.[Giuseppe],
Fiori, E.[Elisabetta],
Fiorucci, P.[Paolo],
Ferraris, L.[Luca],
Negro, D.[Dario],
Gollini, A.[Andrea],
Severino, M.[Massimiliano],
Puca, S.[Silvia],
An Automatic Processing Chain for Near Real-Time Mapping of Burned
Forest Areas Using Sentinel-2 Data,
RS(12), No. 4, 2020, pp. xx-yy.
DOI Link
2003
BibRef
Syifa, M.[Mutiara],
Panahi, M.[Mahdi],
Lee, C.W.[Chang-Wook],
Mapping of Post-Wildfire Burned Area Using a Hybrid Algorithm and
Satellite Data: The Case of the Camp Fire Wildfire in California, USA,
RS(12), No. 4, 2020, pp. xx-yy.
DOI Link
2003
BibRef
Humber, M.L.,
Boschetti, L.,
Giglio, L.,
Assessing the Shape Accuracy of Coarse Resolution Burned Area
Identifications,
GeoRS(58), No. 3, March 2020, pp. 1516-1526.
IEEE DOI
2003
Accuracy assessment, MODIS Burned Area, North America, wildfire
BibRef
Fernández-Manso, A.[Alfonso],
Quintano, C.[Carmen],
Roberts, D.A.[Dar A.],
Can Landsat-Derived Variables Related to Energy Balance Improve
Understanding of Burn Severity From Current Operational Techniques?,
RS(12), No. 5, 2020, pp. xx-yy.
DOI Link
2003
BibRef
Fernández-Manso, A.[Alfonso],
Quintano, C.[Carmen],
A Synergetic Approach to Burned Area Mapping Using Maximum Entropy
Modeling Trained with Hyperspectral Data and VIIRS Hotspots,
RS(12), No. 5, 2020, pp. xx-yy.
DOI Link
2003
BibRef
Pereira-Pires, J.E.[João E.],
Aubard, V.[Valentine],
Ribeiro, R.A.[Rita A.],
Fonseca, J.M.[José M.],
Silva, J.M.N.[João M. N.],
Mora, A.[André],
Semi-Automatic Methodology for Fire Break Maintenance Operations
Detection with Sentinel-2 Imagery and Artificial Neural Network,
RS(12), No. 6, 2020, pp. xx-yy.
DOI Link
2003
BibRef
Pádua, L.[Luís],
Guimarães, N.[Nathalie],
Adão, T.[Telmo],
Sousa, A.[António],
Peres, E.[Emanuel],
Sousa, J.J.[Joaquim J.],
Effectiveness of Sentinel-2 in Multi-Temporal Post-Fire Monitoring
When Compared with UAV Imagery,
IJGI(9), No. 4, 2020, pp. xx-yy.
DOI Link
2005
BibRef
Viana-Soto, A.[Alba],
Aguado, I.[Inmaculada],
Salas, J.[Javier],
García, M.[Mariano],
Identifying Post-Fire Recovery Trajectories and Driving Factors Using
Landsat Time Series in Fire-Prone Mediterranean Pine Forests,
RS(12), No. 9, 2020, pp. xx-yy.
DOI Link
2005
BibRef
Adagbasa, E.G.[Efosa G.],
Adelabu, S.A.[Samuel A.],
Okello, T.W.[Tom W.],
Development of post-fire vegetation response-ability model in
grassland mountainous ecosystem using GIS and remote sensing,
PandRS(164), 2020, pp. 173-183.
Elsevier DOI
2005
Remote sensing, GIS, Post-fire recovery, Adaptive strategy,
Fire severity, Environmental variables
BibRef
Fernández-Guisuraga, J.M.[José Manuel],
Calvo, L.[Leonor],
Suárez-Seoane, S.[Susana],
Comparison of pixel unmixing models in the evaluation of post-fire
forest resilience based on temporal series of satellite imagery at
moderate and very high spatial resolution,
PandRS(164), 2020, pp. 217-228.
Elsevier DOI
2005
Dimidiate pixel model, Fire regime,
Fractional vegetation cover, Landsat, MESMA, WorldView-2
BibRef
McCaffrey, D.[David],
Hopkinson, C.[Chris],
Repeat Oblique Photography Shows Terrain and Fire-Exposure Controls
on Century-Scale Canopy Cover Change in the Alpine Treeline Ecotone,
RS(12), No. 10, 2020, pp. xx-yy.
DOI Link
2006
BibRef
Smiraglia, D.[Daniela],
Filipponi, F.[Federico],
Mandrone, S.[Stefania],
Tornato, A.[Antonella],
Taramelli, A.[Andrea],
Agreement Index for Burned Area Mapping: Integration of Multiple
Spectral Indices Using Sentinel-2 Satellite Images,
RS(12), No. 11, 2020, pp. xx-yy.
DOI Link
2006
BibRef
Kganyago, M.[Mahlatse],
Shikwambana, L.[Lerato],
Assessment of the Characteristics of Recent Major Wildfires in the
USA, Australia and Brazil in 2018-2019 Using Multi-Source Satellite
Products,
RS(12), No. 11, 2020, pp. xx-yy.
DOI Link
2006
BibRef
Scholtz, R.[Rheinhardt],
Prentice, J.[Jayson],
Tang, Y.[Yao],
Twidwell, D.[Dirac],
Improving on MODIS MCD64A1 Burned Area Estimates in Grassland
Systems: A Case Study in Kansas Flint Hills Tall Grass Prairie,
RS(12), No. 13, 2020, pp. xx-yy.
DOI Link
2007
BibRef
Nolde, M.[Michael],
Plank, S.[Simon],
Riedlinger, T.[Torsten],
An Adaptive and Extensible System for Satellite-Based, Large Scale
Burnt Area Monitoring in Near-Real Time,
RS(12), No. 13, 2020, pp. xx-yy.
DOI Link
2007
BibRef
Huang, Z.B.[Zhi-Bin],
Cao, C.X.[Chun-Xiang],
Chen, W.[Wei],
Xu, M.[Min],
Dang, Y.F.[Yong-Feng],
Singh, R.P.[Ramesh P.],
Bashir, B.[Barjeece],
Xie, B.[Bo],
Lin, X.J.[Xiao-Juan],
Remote Sensing Monitoring of Vegetation Dynamic Changes after Fire in
the Greater Hinggan Mountain Area: The Algorithm and Application for
Eliminating Phenological Impacts,
RS(12), No. 1, 2020, pp. xx-yy.
DOI Link
2001
BibRef
Steiner, J.L.[Jean L.],
Wetter, J.[Jeffrey],
Robertson, S.[Shelby],
Teet, S.[Stephen],
Wang, J.[Jie],
Wu, X.C.[Xiao-Cui],
Zhou, Y.T.[Yu-Ting],
Brown, D.[David],
Xiao, X.M.[Xiang-Ming],
Grassland Wildfires in the Southern Great Plains: Monitoring
Ecological Impacts and Recovery,
RS(12), No. 4, 2020, pp. xx-yy.
DOI Link
2003
BibRef
Potter, C.[Christopher],
Recovery Rates of Wetland Vegetation Greenness in Severely Burned
Ecosystems of Alaska Derived from Satellite Image Analysis,
RS(10), No. 9, 2018, pp. xx-yy.
DOI Link
1810
BibRef
Khodaee, M.[Mahsa],
Hwang, T.H.[Tae-Hee],
Kim, J.[JiHyun],
Norman, S.P.[Steven P.],
Robeson, S.M.[Scott M.],
Song, C.H.[Cong-He],
Monitoring Forest Infestation and Fire Disturbance in the Southern
Appalachian Using a Time Series Analysis of Landsat Imagery,
RS(12), No. 15, 2020, pp. xx-yy.
DOI Link
2008
BibRef
Knopp, L.[Lisa],
Wieland, M.[Marc],
Rättich, M.[Michaela],
Martinis, S.[Sandro],
A Deep Learning Approach for Burned Area Segmentation with Sentinel-2
Data,
RS(12), No. 15, 2020, pp. xx-yy.
DOI Link
2008
BibRef
de Bem, P.P.[Pablo Pozzobon],
de Carvalho Júnior, O.A.[Osmar Abílio],
de Carvalho, O.L.F.[Osmar Luiz Ferreira],
Gomes, R.A.T.[Roberto Arnaldo Trancoso],
Guimarães, R.F.[Renato Fontes],
Performance Analysis of Deep Convolutional Autoencoders with
Different Patch Sizes for Change Detection from Burnt Areas,
RS(12), No. 16, 2020, pp. xx-yy.
DOI Link
2008
BibRef
Salvoldi, M.[Manuel],
Siaki, G.[Gil],
Sprintsin, M.[Michael],
Karnieli, A.[Arnon],
Burned Area Mapping Using Multi-Temporal Sentinel-2 Data by Applying
the Relative Differenced Aerosol-Free Vegetation Index (RdAFRI),
RS(12), No. 17, 2020, pp. xx-yy.
DOI Link
2009
BibRef
Talucci, A.C.[Anna C.],
Forbath, E.[Elena],
Kropp, H.[Heather],
Alexander, H.D.[Heather D.],
DeMarco, J.[Jennie],
Paulson, A.K.[Alison K.],
Zimov, N.S.[Nikita S.],
Zimov, S.[Sergei],
Loranty, M.M.[Michael M.],
Evaluating Post-Fire Vegetation Recovery in Cajander Larch Forests in
Northeastern Siberia Using UAV Derived Vegetation Indices,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link
2009
BibRef
Hanberry, B.B.[Brice B.],
Classifying Large Wildfires in the United States by Land Cover,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link
2009
BibRef
Viedma, O.[Olga],
Almeida, D.R.A.[Danilo R. A.],
Moreno, J.M.[Jose Manuel],
Postfire Tree Structure from High-Resolution LiDAR and RBR Sentinel
2A Fire Severity Metrics in a Pinus halepensis-Dominated Burned Stand,
RS(12), No. 21, 2020, pp. xx-yy.
DOI Link
2011
BibRef
Shimabukuro, Y.E.[Yosio Edemir],
Dutra, A.C.[Andeise Cerqueira],
Arai, E.[Egidio],
Duarte, V.[Valdete],
Cassol, H.L.G.[Henrique Luís Godinho],
Pereira, G.[Gabriel],
da Silva Cardozo, F.[Francielle],
Mapping Burned Areas of Mato Grosso State Brazilian Amazon Using
Multisensor Datasets,
RS(12), No. 22, 2020, pp. xx-yy.
DOI Link
2011
BibRef
Santana, N.C.[Níckolas Castro],
de Carvalho Júnior, O.A.[Osmar Abílio],
Gomes, R.A.T.[Roberto Arnaldo Trancoso],
Guimarães, R.F.[Renato Fontes],
Comparison of Post-fire Patterns in Brazilian Savanna and Tropical
Forest from Remote Sensing Time Series,
IJGI(9), No. 11, 2020, pp. xx-yy.
DOI Link
2012
BibRef
Valencia, G.M.[Germán M.],
Anaya, J.A.[Jesús A.],
Velásquez, É.A.[Éver A.],
Ramo, R.[Rubén],
Caro-Lopera, F.J.[Francisco J.],
About Validation-Comparison of Burned Area Products,
RS(12), No. 23, 2020, pp. xx-yy.
DOI Link
2012
BibRef
Pessôa, A.C.M.[Ana Carolina M.],
Anderson, L.O.[Liana O.],
Carvalho, N.S.[Nathália S.],
Campanharo, W.A.[Wesley A.],
Junior, C.H.L.S.[Celso H. L. Silva],
Rosan, T.M.[Thais M.],
Reis, J.B.C.[João B. C.],
Pereira, F.R.S.[Francisca R. S.],
Assis, M.[Mauro],
Jacon, A.D.[Aline D.],
Ometto, J.P.[Jean P.],
Shimabukuro, Y.E.[Yosio E.],
Silva, C.V.J.[Camila V. J.],
Pontes-Lopes, A.[Aline],
Morello, T.F.[Thiago F.],
Aragão, L.E.O.C.[Luiz E. O. C.],
Intercomparison of Burned Area Products and Its Implication for
Carbon Emission Estimations in the Amazon,
RS(12), No. 23, 2020, pp. xx-yy.
DOI Link
2012
BibRef
Bonney, M.T.[Mitchell T.],
He, Y.H.[Yu-Hong],
Myint, S.W.[Soe W.],
Contextualizing the 2019-2020 Kangaroo Island Bushfires: Quantifying
Landscape-Level Influences on Past Severity and Recovery with Landsat
and Google Earth Engine,
RS(12), No. 23, 2020, pp. xx-yy.
DOI Link
2012
BibRef
Danneyrolles, V.[Victor],
Valeria, O.[Osvaldo],
Djerboua, I.[Ibrahim],
Gauthier, S.[Sylvie],
Bergeron, Y.[Yves],
How Initial Forest Cover, Site Characteristics and Fire Severity
Drive the Dynamics of the Southern Boreal Forest,
RS(12), No. 23, 2020, pp. xx-yy.
DOI Link
2012
BibRef
Hamilton, D.[Dale],
Levandovsky, E.[Enoch],
Hamilton, N.[Nicholas],
Mapping Burn Extent of Large Wildland Fires from Satellite Imagery
Using Machine Learning Trained from Localized Hyperspatial Imagery,
RS(12), No. 24, 2020, pp. xx-yy.
DOI Link
2012
BibRef
Hamilton, D.[Dale],
Brothers, K.[Kamden],
McCall, C.[Cole],
Gautier, B.[Bryn],
Shea, T.[Tyler],
Mapping Forest Burn Extent from Hyperspatial Imagery Using Machine
Learning,
RS(13), No. 19, 2021, pp. xx-yy.
DOI Link
2110
BibRef
Seydi, S.T.[Seyd Teymoor],
Akhoondzadeh, M.[Mehdi],
Amani, M.[Meisam],
Mahdavi, S.[Sahel],
Wildfire Damage Assessment over Australia Using Sentinel-2 Imagery
and MODIS Land Cover Product within the Google Earth Engine Cloud
Platform,
RS(13), No. 2, 2021, pp. xx-yy.
DOI Link
2101
BibRef
Hamilton, D.A.[Dale A.],
Brothers, K.L.[Kamden L.],
Jones, S.D.[Samuel D.],
Colwell, J.[Jason],
Winters, J.[Jacob],
Wildland Fire Tree Mortality Mapping from Hyperspatial Imagery Using
Machine Learning,
RS(13), No. 2, 2021, pp. xx-yy.
DOI Link
2101
BibRef
Xu, Y.F.[Yong-Fang],
Lin, Z.H.[Zhao-Hui],
Wu, C.[Chenglai],
Spatiotemporal Variation of the Burned Area and Its Relationship with
Climatic Factors in Central Kazakhstan,
RS(13), No. 2, 2021, pp. xx-yy.
DOI Link
2101
BibRef
Roteta, E.[Ekhi],
Bastarrika, A.[Aitor],
Franquesa, M.[Magí],
Chuvieco, E.[Emilio],
Landsat and Sentinel-2 Based Burned Area Mapping Tools in Google
Earth Engine,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link
2103
BibRef
Qiu, J.[Jie],
Wang, H.[Heng],
Shen, W.J.[Wen-Juan],
Zhang, Y.[Yali],
Su, H.[Huiyi],
Li, M.[Mingshi],
Quantifying Forest Fire and Post-Fire Vegetation Recovery in the
Daxin'anling Area of Northeastern China Using Landsat Time-Series
Data and Machine Learning,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link
2103
BibRef
Marcos, B.[Bruno],
Gonçalves, J.[João],
Alcaraz-Segura, D.[Domingo],
Cunha, M.[Mário],
Honrado, J.P.[João P.],
A Framework for Multi-Dimensional Assessment of Wildfire Disturbance
Severity from Remotely Sensed Ecosystem Functioning Attributes,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link
2103
BibRef
Wang, X.X.[Xiao-Xiao],
Di, Z.H.[Zhen-Hua],
Li, M.[Mei],
Yao, Y.J.[Yun-Jun],
Satellite-Derived Variation in Burned Area in China from 2001 to 2018
and Its Response to Climatic Factors,
RS(13), No. 7, 2021, pp. xx-yy.
DOI Link
2104
BibRef
Hu, X.[Xikun],
Ban, Y.F.[Yi-Fang],
Nascetti, A.[Andrea],
Uni-Temporal Multispectral Imagery for Burned Area Mapping with Deep
Learning,
RS(13), No. 8, 2021, pp. xx-yy.
DOI Link
2104
BibRef
Pinto, M.M.[Miguel M.],
Trigo, R.M.[Ricardo M.],
Trigo, I.F.[Isabel F.],
DaCamara, C.C.[Carlos C.],
A Practical Method for High-Resolution Burned Area Monitoring Using
Sentinel-2 and VIIRS,
RS(13), No. 9, 2021, pp. xx-yy.
DOI Link
2105
BibRef
Smith, C.W.[Christopher W.],
Panda, S.K.[Santosh K.],
Bhatt, U.S.[Uma S.],
Meyer, F.J.[Franz J.],
Badola, A.[Anushree],
Hrobak, J.L.[Jennifer L.],
Assessing Wildfire Burn Severity and Its Relationship with
Environmental Factors: A Case Study in Interior Alaska Boreal Forest,
RS(13), No. 10, 2021, pp. xx-yy.
DOI Link
2105
BibRef
Pelletier, F.[Flavie],
Eskelson, B.N.I.[Bianca N.I.],
Monleon, V.J.[Vicente J.],
Tseng, Y.C.[Yi-Chin],
Using Landsat Imagery to Assess Burn Severity of National Forest
Inventory Plots,
RS(13), No. 10, 2021, pp. xx-yy.
DOI Link
2105
BibRef
Fernández-Guisuraga, J.M.[José Manuel],
Suárez-Seoane, S.[Susana],
Calvo, L.[Leonor],
Radiative transfer modeling to measure fire impact and forest
engineering resilience at short-term,
PandRS(176), 2021, pp. 30-41.
Elsevier DOI
2106
Burn severity, Deimos-2, Forest fire,
Fractional vegetation cover, PROSAIL-D,
Resilience
BibRef
Sali, M.[Matteo],
Piaser, E.[Erika],
Boschetti, M.[Mirco],
Brivio, P.A.[Pietro Alessandro],
Sona, G.[Giovanna],
Bordogna, G.[Gloria],
Stroppiana, D.[Daniela],
A Burned Area Mapping Algorithm for Sentinel-2 Data Based on
Approximate Reasoning and Region Growing,
RS(13), No. 11, 2021, pp. xx-yy.
DOI Link
2106
BibRef
Zhang, H.X.[Hui-Xian],
Hagan, D.F.T.[Daniel Fiifi Tawia],
Dalagnol, R.[Ricardo],
Liu, Y.[Yi],
Forest Canopy Changes in the Southern Amazon during the 2019 Fire
Season Based on Passive Microwave and Optical Satellite Observations,
RS(13), No. 12, 2021, pp. xx-yy.
DOI Link
2106
BibRef
Sun, Q.[Qiaoqi],
Burrell, A.[Arden],
Barrett, K.[Kirsten],
Kukavskaya, E.[Elena],
Buryak, L.[Ludmila],
Kaduk, J.[Jörg],
Baxter, R.[Robert],
Climate Variability May Delay Post-Fire Recovery of Boreal Forest in
Southern Siberia, Russia,
RS(13), No. 12, 2021, pp. xx-yy.
DOI Link
2106
BibRef
Delcourt, C.J.F.[Clement J. F.],
Combee, A.[Alisha],
Izbicki, B.[Brian],
Mack, M.C.[Michelle C.],
Maximov, T.[Trofim],
Petrov, R.[Roman],
Rogers, B.M.[Brendan M.],
Scholten, R.C.[Rebecca C.],
Shestakova, T.A.[Tatiana A.],
van Wees, D.[Dave],
Veraverbeke, S.[Sander],
Evaluating the Differenced Normalized Burn Ratio for Assessing Fire
Severity Using Sentinel-2 Imagery in Northeast Siberian Larch Forests,
RS(13), No. 12, 2021, pp. xx-yy.
DOI Link
2106
BibRef
van Gerrevink, M.J.[Max J.],
Veraverbeke, S.[Sander],
Evaluating the Hyperspectral Sensitivity of the Differenced
Normalized Burn Ratio for Assessing Fire Severity,
RS(13), No. 22, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Liu, J.X.[Jin-Xiu],
Maeda, E.E.[Eduardo Eiji],
Wang, D.[Du],
Heiskanen, J.[Janne],
Sensitivity of Spectral Indices on Burned Area Detection using
Landsat Time Series in Savannas of Southern Burkina Faso,
RS(13), No. 13, 2021, pp. xx-yy.
DOI Link
2107
BibRef
Xulu, S.[Sifiso],
Mbatha, N.[Nkanyiso],
Peerbhay, K.[Kabir],
Burned Area Mapping over the Southern Cape Forestry Region, South
Africa Using Sentinel Data within GEE Cloud Platform,
IJGI(10), No. 8, 2021, pp. xx-yy.
DOI Link
2108
BibRef
Stroppiana, D.[Daniela],
Bordogna, G.[Gloria],
Sali, M.[Matteo],
Boschetti, M.[Mirco],
Sona, G.[Giovanna],
Brivio, P.A.[Pietro Alessandro],
A Fully Automatic, Interpretable and Adaptive Machine Learning
Approach to Map Burned Area from Remote Sensing,
IJGI(10), No. 8, 2021, pp. xx-yy.
DOI Link
2108
BibRef
Reilly, S.[Sean],
Clark, M.L.[Matthew L.],
Bentley, L.P.[Lisa Patrick],
Matley, C.[Corbin],
Piazza, E.[Elise],
Menor, I.O.[Imma Oliveras],
The Potential of Multispectral Imagery and 3D Point Clouds from
Unoccupied Aerial Systems (UAS) for Monitoring Forest Structure and
the Impacts of Wildfire in Mediterranean-Climate Forests,
RS(13), No. 19, 2021, pp. xx-yy.
DOI Link
2110
BibRef
Chen, D.[Dong],
Shevade, V.[Varada],
Baer, A.E.[Allison E.],
Loboda, T.V.[Tatiana V.],
Missing Burns in the High Northern Latitudes: The Case for Regionally
Focused Burned Area Products,
RS(13), No. 20, 2021, pp. xx-yy.
DOI Link
2110
BibRef
Gallagher, M.R.[Michael R.],
Maxwell, A.E.[Aaron E.],
Guillén, L.A.[Luis Andrés],
Everland, A.[Alexis],
Loudermilk, E.L.[E. Louise],
Skowronski, N.S.[Nicholas S.],
Estimation of Plot-Level Burn Severity Using Terrestrial Laser
Scanning,
RS(13), No. 20, 2021, pp. xx-yy.
DOI Link
2110
BibRef
Lizundia-Loiola, J.[Joshua],
Franquesa, M.[Magí],
Boettcher, M.[Martin],
Kirches, G.[Grit],
Pettinari, M.L.[M. Lucrecia],
Chuvieco, E.[Emilio],
Implementation of the Burned Area Component of the Copernicus Climate
Change Service: From MODIS to OLCI Data,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Roteta, E.[Ekhi],
Bastarrika, A.[Aitor],
Ibisate, A.[Askoa],
Chuvieco, E.[Emilio],
A Preliminary Global Automatic Burned-Area Algorithm at Medium
Resolution in Google Earth Engine,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Paugam, R.[Ronan],
Wooster, M.J.[Martin J.],
Mell, W.E.[William E.],
Rochoux, M.C.[Mélanie C.],
Filippi, J.B.[Jean-Baptiste],
Rücker, G.[Gernot],
Frauenberger, O.[Olaf],
Lorenz, E.[Eckehard],
Schroeder, W.[Wilfrid],
Main, B.[Bruce],
Govender, N.[Navashni],
Orthorectification of Helicopter-Borne High Resolution Experimental
Burn Observation from Infra Red Handheld Imagers,
RS(13), No. 23, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Oliveira, E.R.[Eduardo R.],
Disperati, L.[Leonardo],
Alves, F.L.[Fátima L.],
A New Method (MINDED-BA) for Automatic Detection of Burned Areas
Using Remote Sensing,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Tselka, I.[Ioanna],
Krassakis, P.[Pavlos],
Rentzelos, A.[Alkiviadis],
Koukouzas, N.[Nikolaos],
Parcharidis, I.[Issaak],
Assessing Post-Fire Effects on Soil Loss Combining Burn Severity and
Advanced Erosion Modeling in Malesina, Central Greece,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Seydi, S.T.[Seyd Teymoor],
Hasanlou, M.[Mahdi],
Chanussot, J.[Jocelyn],
DSMNN-Net: A Deep Siamese Morphological Neural Network Model for
Burned Area Mapping Using Multispectral Sentinel-2 and Hyperspectral
PRISMA Images,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Liu, J.X.[Jin-Xiu],
Wang, D.[Du],
Maeda, E.E.[Eduardo Eiji],
Pellikka, P.K.E.[Petri K. E.],
Heiskanen, J.[Janne],
Mapping Cropland Burned Area in Northeastern China by Integrating
Landsat Time Series and Multi-Harmonic Model,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Yin, C.M.[Chang-Ming],
Xing, M.[Minfeng],
Yebra, M.[Marta],
Liu, X.Z.[Xiang-Zhuo],
Relationships between Burn Severity and Environmental Drivers in the
Temperate Coniferous Forest of Northern China,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Nolde, M.[Michael],
Plank, S.[Simon],
Riedlinger, T.[Torsten],
Utilization of Hyperspectral Remote Sensing Imagery for Improving
Burnt Area Mapping Accuracy,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link
2112
BibRef
da Silva Junior, C.A.[Carlos Antonio],
Lima, M.[Mendelson],
Teodoro, P.E.[Paulo Eduardo],
de Oliveira-Júnior, J.F.[José Francisco],
Rossi, F.S.[Fernando Saragosa],
Funatsu, B.M.[Beatriz Miky],
Butturi, W.[Weslei],
Lourençoni, T.[Thaís],
Kraeski, A.[Aline],
Pelissari, T.D.[Tatiane Deoti],
Moratelli, F.A.[Francielli Aloisio],
Arvor, D.[Damien],
dos Santos Luz, I.M.[Iago Manuelson],
Teodoro, L.P.R.[Larissa Pereira Ribeiro],
Dubreuil, V.[Vincent],
Teixeira, V.M.[Vinicius Modolo],
Fires Drive Long-Term Environmental Degradation in the Amazon Basin,
RS(14), No. 2, 2022, pp. xx-yy.
DOI Link
2201
BibRef
Florath, J.[Janine],
Keller, S.[Sina],
Supervised Machine Learning Approaches on Multispectral Remote
Sensing Data for a Combined Detection of Fire and Burned Area,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link
2202
BibRef
Katagis, T.[Thomas],
Gitas, I.Z.[Ioannis Z.],
Assessing the Accuracy of MODIS MCD64A1 C6 and FireCCI51 Burned Area
Products in Mediterranean Ecosystems,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link
2202
BibRef
Nascente, J.C.[Jéssika Cristina],
Ferreira, M.E.[Manuel Eduardo],
Nunes, G.M.[Gustavo Manzon],
Integrated Fire Management as a Renewing Agent of Native Vegetation
and Inhibitor of Invasive Plants in Vereda Habitats: Diagnosis by
Remotely Piloted Aircraft Systems,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link
2202
BibRef
Yan, J.[Jining],
He, H.[Haixu],
Wang, L.[Lizhe],
Zhang, H.[Hao],
Liang, D.[Dong],
Zhang, J.Q.[Jun-Qiang],
Inter-Comparison of Four Models for Detecting Forest Fire Disturbance
from MOD13A2 Time Series,
RS(14), No. 6, 2022, pp. xx-yy.
DOI Link
2204
BibRef
Guz, J.[Jaclyn],
Sangermano, F.[Florencia],
Kulakowski, D.[Dominik],
The Influence of Burn Severity on Post-Fire Spectral Recovery of
Three Fires in the Southern Rocky Mountains,
RS(14), No. 6, 2022, pp. xx-yy.
DOI Link
2204
BibRef
White, L.A.[Laura A.],
Gibson, R.K.[Rebecca K.],
Comparing Fire Extent and Severity Mapping between Sentinel 2 and
Landsat 8 Satellite Sensors,
RS(14), No. 7, 2022, pp. xx-yy.
DOI Link
2205
BibRef
Pontes-Lopes, A.[Aline],
Dalagnol, R.[Ricardo],
Dutra, A.C.[Andeise Cerqueira],
de Jesus Silva, C.V.[Camila Valéria],
de Alencastro Graça, P.M.L.[Paulo Maurício Lima],
de Oliveira e Cruz de Aragão, L.E.[Luiz Eduardo],
Quantifying Post-Fire Changes in the Aboveground Biomass of an
Amazonian Forest Based on Field and Remote Sensing Data,
RS(14), No. 7, 2022, pp. xx-yy.
DOI Link
2205
BibRef
Alcaras, E.[Emanuele],
Costantino, D.[Domenica],
Guastaferro, F.[Francesca],
Parente, C.[Claudio],
Pepe, M.[Massimiliano],
Normalized Burn Ratio Plus (NBR+): A New Index for Sentinel-2 Imagery,
RS(14), No. 7, 2022, pp. xx-yy.
DOI Link
2205
BibRef
Sun, L.[Li],
Yang, L.[Lei],
Xia, X.G.[Xian-Gao],
Wang, D.D.[Dong-Dong],
Zhang, T.N.[Tie-Ning],
Climatological Aspects of Active Fires in Northeastern China and
Their Relationship to Land Cover,
RS(14), No. 10, 2022, pp. xx-yy.
DOI Link
2206
BibRef
Alencar, A.A.C.[Ane A. C.],
Arruda, V.L.S.[Vera L. S.],
da Silva, W.V.[Wallace Vieira],
Conciani, D.E.[Dhemerson E.],
Costa, D.P.[Diego Pereira],
Crusco, N.[Natalia],
Duverger, S.G.[Soltan Galano],
Ferreira, N.C.[Nilson Clementino],
Franca-Rocha, W.[Washington],
Hasenack, H.[Heinrich],
Martenexen, L.F.M.[Luiz Felipe Morais],
Piontekowski, V.J.[Valderli J.],
Ribeiro, N.V.[Noely Vicente],
Rosa, E.R.[Eduardo Reis],
Rosa, M.R.[Marcos Reis],
dos Santos, S.M.B.[Sarah Moura B.],
Shimbo, J.Z.[Julia Z.],
Vélez-Martin, E.[Eduardo],
Long-Term Landsat-Based Monthly Burned Area Dataset for the Brazilian
Biomes Using Deep Learning,
RS(14), No. 11, 2022, pp. xx-yy.
DOI Link
2206
BibRef
Chen, X.[Xu],
Chen, W.[Wei],
Xu, M.[Min],
Remote-Sensing Monitoring of Postfire Vegetation Dynamics in the
Greater Hinggan Mountain Range Based on Long Time-Series Data:
Analysis of the Effects of Six Topographic and Climatic Factors,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Skakun, R.[Rob],
Castilla, G.[Guillermo],
Metsaranta, J.[Juha],
Whitman, E.[Ellen],
Rodrigue, S.[Sebastien],
Little, J.[John],
Groenewegen, K.[Kathleen],
Coyle, M.[Matthew],
Extending the National Burned Area Composite Time Series of Wildfires
in Canada,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Silva-Cardoza, A.I.[Adrián Israel],
Vega-Nieva, D.J.[Daniel José],
Briseño-Reyes, J.[Jaime],
Briones-Herrera, C.I.[Carlos Ivan],
López-Serrano, P.M.[Pablito Marcelo],
Corral-Rivas, J.J.[José Javier],
Parks, S.A.[Sean A.],
Holsinger, L.M.[Lisa M.],
Evaluating a New Relative Phenological Correction and the Effect of
Sentinel-Based Earth Engine Compositing Approaches to Map Fire
Severity and Burned Area,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Chhabra, A.[Aakash],
Rüdiger, C.[Christoph],
Yebra, M.[Marta],
Jagdhuber, T.[Thomas],
Hilton, J.[James],
RADAR-Vegetation Structural Perpendicular Index (R-VSPI) for the
Quantification of Wildfire Impact and Post-Fire Vegetation Recovery,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Xu, H.Z.[Hai-Zhou],
Zhang, G.[Gui],
Zhou, Z.M.[Zhao-Ming],
Zhou, X.B.[Xia-Bing],
Zhang, J.[Jia],
Zhou, C.[Cui],
Development of a Novel Burned-Area Subpixel Mapping (BASM) Workflow
for Fire Scar Detection at Subpixel Level,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Stroppiana, D.[Daniela],
Sali, M.[Matteo],
Busetto, L.[Lorenzo],
Boschetti, M.[Mirco],
Ranghetti, L.[Luigi],
Franquesa, M.[Magí],
Pettinari, M.L.[M. Lucrecia],
Chuvieco, E.[Emilio],
Sentinel-2 sampling design and reference fire perimeters to assess
accuracy of Burned Area products over Sub-Saharan Africa for the year
2019,
PandRS(191), 2022, pp. 223-234.
Elsevier DOI
2208
Accuracy assessment, Regional and continental products,
Sampling approach, Reference dataset, Validation methodology, Burned area
BibRef
Gersh, M.[Max],
Gleason, K.E.[Kelly E.],
Surunis, A.[Anton],
Forest Fire Effects on Landscape Snow Albedo Recovery and Decay,
RS(14), No. 16, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Franquesa, M.[Magí],
Rodriguez-Montellano, A.M.[Armando M.],
Chuvieco, E.[Emilio],
Aguado, I.[Inmaculada],
Reference Data Accuracy Impacts Burned Area Product Validation: The
Role of the Expert Analyst,
RS(14), No. 17, 2022, pp. xx-yy.
DOI Link
2209
BibRef
Kurbanov, E.[Eldar],
Vorobev, O.[Oleg],
Lezhnin, S.[Sergey],
Sha, J.M.[Jin-Ming],
Wang, J.L.[Jin-Liang],
Li, X.M.[Xiao-Mei],
Cole, J.[Janine],
Dergunov, D.[Denis],
Wang, Y.[Yibo],
Remote Sensing of Forest Burnt Area, Burn Severity, and Post-Fire
Recovery: A Review,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link
2210
BibRef
Lasaponara, R.[Rosa],
Abate, N.[Nicodemo],
Fattore, C.[Carmen],
Aromando, A.[Angelo],
Cardettini, G.[Gianfranco],
di Fonzo, M.[Marco],
On the Use of Sentinel-2 NDVI Time Series and Google Earth Engine to
Detect Land-Use/Land-Cover Changes in Fire-Affected Areas,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link
2210
BibRef
Tomshin, O.[Oleg],
Solovyev, V.[Vladimir],
Features of the Extreme Fire Season of 2021 in Yakutia (Eastern
Siberia) and Heavy Air Pollution Caused by Biomass Burning,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link
2210
BibRef
Howe, A.A.[Alexander A.],
Parks, S.A.[Sean A.],
Harvey, B.J.[Brian J.],
Saberi, S.J.[Saba J.],
Lutz, J.A.[James A.],
Yocom, L.L.[Larissa L.],
Comparing Sentinel-2 and Landsat 8 for Burn Severity Mapping in
Western North America,
RS(14), No. 20, 2022, pp. xx-yy.
DOI Link
2211
BibRef
Koutsias, N.[Nikos],
Karamitsou, A.[Anastasia],
Nioti, F.[Foula],
Coutelieris, F.[Frank],
Assessment of Fire Regimes and Post-Fire Evolution of Burned Areas
with the Dynamic Time Warping Method on Time Series of Satellite
Images: Setting the Methodological Framework in the Peloponnese,
Greece,
RS(14), No. 20, 2022, pp. xx-yy.
DOI Link
2211
BibRef
Fernández-Guisuraga, J.M.[José Manuel],
Suárez-Seoane, S.[Susana],
Quintano, C.[Carmen],
Fernández-Manso, A.[Alfonso],
Calvo, L.[Leonor],
Comparison of Physical-Based Models to Measure Forest Resilience to
Fire as a Function of Burn Severity,
RS(14), No. 20, 2022, pp. xx-yy.
DOI Link
2211
BibRef
Negri, R.G.[Rogério G.],
Luz, A.E.O.[Andréa E. O.],
Frery, A.C.[Alejandro C.],
Casaca, W.[Wallace],
Mapping Burned Areas with Multitemporal-Multispectral Data and
Probabilistic Unsupervised Learning,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link
2212
BibRef
Fernández-Alonso, J.M.[José María],
Llorens, R.[Rafael],
Sobrino, J.A.[José Antonio],
Ruiz-González, A.D.[Ana Daría],
Alvarez-González, J.G.[Juan Gabriel],
Vega, J.A.[José Antonio],
Fernández, C.[Cristina],
Exploring the Potential of Lidar and Sentinel-2 Data to Model the
Post-Fire Structural Characteristics of Gorse Shrublands in NW Spain,
RS(14), No. 23, 2022, pp. xx-yy.
DOI Link
2212
BibRef
Avetisyan, D.[Daniela],
Velizarova, E.[Emiliya],
Filchev, L.[Lachezar],
Post-Fire Forest Vegetation State Monitoring through Satellite Remote
Sensing and In Situ Data,
RS(14), No. 24, 2022, pp. xx-yy.
DOI Link
2212
BibRef
Gholamrezaie, H.[Houri],
Hasanlou, M.[Mahdi],
Amani, M.[Meisam],
Mirmazloumi, S.M.[S. Mohammad],
Automatic Mapping of Burned Areas Using Landsat 8 Time-Series Images
in Google Earth Engine: A Case Study from Iran,
RS(14), No. 24, 2022, pp. xx-yy.
DOI Link
2212
BibRef
Amroussia, M.[Mouna],
Viedma, O.[Olga],
Achour, H.[Hammadi],
Abbes, C.[Chaabane],
Predicting Spatially Explicit Composite Burn Index (CBI) from
Different Spectral Indices Derived from Sentinel 2A: A Case of Study
in Tunisia,
RS(15), No. 2, 2023, pp. xx-yy.
DOI Link
2301
BibRef
Ye, J.[Junhong],
Wang, N.[Nan],
Sun, M.[Min],
Liu, Q.Q.[Qin-Qin],
Ding, N.[Ning],
Li, M.[Mingshi],
A New Method for the Rapid Determination of Fire Disturbance Events
Using GEE and the VCT Algorithm:
A Case Study in Southwestern and Northeastern China,
RS(15), No. 2, 2023, pp. xx-yy.
DOI Link
2301
BibRef
East, A.[Alyson],
Hansen, A.[Andrew],
Armenteras, D.[Dolors],
Jantz, P.[Patrick],
Roberts, D.W.[David W.],
Measuring Understory Fire Effects from Space: Canopy Change in
Response to Tropical Understory Fire and What This Means for
Applications of GEDI to Tropical Forest Fire,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link
2302
BibRef
Pirotti, F.[Francesco],
Adedipe, O.[Opeyemi],
Leblon, B.[Brigitte],
Sentinel-1 Response to Canopy Moisture in Mediterranean Forests
before and after Fire Events,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link
2302
BibRef
Oliveira, E.R.[Eduardo R.],
Disperati, L.[Leonardo],
Alves, F.L.[Fátima L.],
MINDED-FBA: An Automatic Remote Sensing Tool for the Estimation of
Flooded and Burned Areas,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link
2302
BibRef
Sudiana, D.[Dodi],
Lestari, A.I.[Anugrah Indah],
Riyanto, I.[Indra],
Rizkinia, M.[Mia],
Arief, R.[Rahmat],
Prabuwono, A.S.[Anton Satria],
Sumantyo, J.T.S.[Josaphat Tetuko Sri],
A Hybrid Convolutional Neural Network and Random Forest for Burned
Area Identification with Optical and Synthetic Aperture Radar (SAR)
Data,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link
2302
BibRef
Chan, A.H.Y.[Aland H. Y.],
Guizar-Coutiño, A.[Alejandro],
Kalamandeen, M.[Michelle],
Coomes, D.A.[David A.],
Reconstructing 34 Years of Fire History in the Wet, Subtropical
Vegetation of Hong Kong Using Landsat,
RS(15), No. 6, 2023, pp. 1489.
DOI Link
2304
BibRef
Valles, H.E.P.[Harold E. Pineda],
Nunes, G.M.[Gustavo Manzon],
Berlinck, C.N.[Christian Niel],
Gonçalves, L.G.[Luiz Gustavo],
Pires-de Mello-Ribeiro, G.H.[Gabriel Henrique],
Use of Remotely Piloted Aircraft System Multispectral Data to
Evaluate the Effects of Prescribed Burnings on Three Macrohabitats of
Pantanal, Brazil,
RS(15), No. 11, 2023, pp. 2934.
DOI Link
2306
BibRef
Lin, S.[Simei],
Zhang, H.Q.[Hui-Qing],
Liu, S.B.[Shang-Bo],
Gao, G.[Ge],
Li, L.[Linyuan],
Huang, H.G.[Hua-Guo],
Characterizing Post-Fire Forest Structure Recovery in the Great
Xing'an Mountain Using GEDI and Time Series Landsat Data,
RS(15), No. 12, 2023, pp. xx-yy.
DOI Link
2307
BibRef
Wang, X.Q.[Xiao-Qiong],
Yan, J.[Jun],
Tian, Q.J.[Qing-Jiu],
Li, X.[Xianyi],
Tian, J.[Jia],
Zhu, C.C.[Cui-Cui],
Li, Q.J.[Qian-Jing],
Estimation of Forest Fire Burned Area by Distinguishing
Non-Photosynthetic and Photosynthetic Vegetation Using Triangular
Space Method,
RS(15), No. 12, 2023, pp. xx-yy.
DOI Link
2307
BibRef
Fernández-García, V.[Víctor],
Alonso-González, E.[Esteban],
Global Patterns and Dynamics of Burned Area and Burn Severity,
RS(15), No. 13, 2023, pp. 3401.
DOI Link
2307
BibRef
Wang, X.Y.[Xue-Yan],
Di, Z.H.[Zhen-Hua],
Liu, J.G.[Jian-Guo],
Evaluating the Abilities of Satellite-Derived Burned Area Products to
Detect Forest Burning in China,
RS(15), No. 13, 2023, pp. 3260.
DOI Link
2307
BibRef
Ribeiro, T.F.R.[Tiago F.R.],
Silva, F.[Fernando],
Moreira, J.[José],
de-C.-Costa, R.L.[Rogério Luís],
Burned area semantic segmentation: A novel dataset and evaluation
using convolutional networks,
PandRS(202), 2023, pp. 565-580.
Elsevier DOI
2308
Forest fires, Burned area segmentation, UAV, Deep learning, Benchmark
BibRef
Jaime, X.A.[Xavier A.],
Angerer, J.P.[Jay P.],
Yang, C.H.[Cheng-Hai],
Walker, J.[John],
Mata, J.[Jose],
Tolleson, D.R.[Doug R.],
Wu, X.B.[X. Ben],
Exploring Effective Detection and Spatial Pattern of Prickly Pear
Cactus (Opuntia Genus) from Airborne Imagery before and after
Prescribed Fires in the Edwards Plateau,
RS(15), No. 16, 2023, pp. 4033.
DOI Link
2309
BibRef
Zhang, P.[Puzhao],
Ban, Y.[Yifang],
Nascetti, A.[Andrea],
Total-variation regularized U-Net for wildfire burned area mapping
based on Sentinel-1 C-Band SAR backscattering data,
PandRS(203), 2023, pp. 301-313.
Elsevier DOI
2310
Wildfire, Burned area, SAR, Deep learning, Segmentation, U-Net,
Total variation, Sentinel-1
BibRef
Letsios, V.[Vasilis],
Faraslis, I.[Ioannis],
Stathakis, D.[Demetris],
Multi-Temporal PSI Analysis and Burn Severity Combination to
Determine Ground-Burned Hazard Zones,
RS(15), No. 18, 2023, pp. 4598.
DOI Link
2310
BibRef
Hamilton, D.[Dale],
Gibson, W.[William],
Harris, D.[Daniel],
McGath, C.[Camden],
Evaluation of Multi-Spectral Band Efficacy for Mapping Wildland Fire
Burn Severity from PlanetScope Imagery,
RS(15), No. 21, 2023, pp. 5196.
DOI Link
2311
BibRef
Abid, N.[Nosheen],
Malik, M.I.[Muhammad Imran],
Shahzad, M.[Muhammad],
Shafait, F.[Faisal],
Ali, H.[Haider],
Ghaffar, M.M.[Muhammad Mohsin],
Weis, C.[Christian],
Wehn, N.[Norbert],
Liwicki, M.[Marcus],
Burnt Forest Estimation from Sentinel-2 Imagery of Australia using
Unsupervised Deep Learning,
DICTA21(01-08)
IEEE DOI
2201
Deep learning, Training, Adaptation models,
Biological system modeling, Fires, Forestry,
Aerial Imagery
BibRef
Ongeri, D.,
Kenduiywo, B.K.,
Burnt Area Detection Using Medium Resolution Sentinel 2 and Landsat 8
Satellites,
ISPRS20(B5:131-137).
DOI Link
2012
BibRef
Bomber, M.,
Portelli, R.,
Multi-scale Analysis of Jack Pine Saplings After Fire Across Burn
Severities,
ISPRS20(B3:671-675).
DOI Link
2012
BibRef
Geserbaatar, N.E.,
Nasanbat, E.,
Lkhamjav, O.,
The Impact of Forest Fire on Forest Cover Types In Mongolia,
ISPRS20(B3:693-698).
DOI Link
2012
BibRef
Novo, A.,
González-Jorge, H.,
Martínez-Sánchez, J.,
Lorenzo, H.,
Remote Sensing Approach to Evaluate Post-fire Vegetation Structure,
ISPRS20(B3:1031-1038).
DOI Link
2012
BibRef
Gong, A.,
Li, J.,
Yang, Y.,
Chen, Y.,
Zeng, T.,
Wu, J.,
Li, J.,
Chen, Y.,
Tang, H.,
Yue, J.,
Analysis of Response and Recovery of Vegetation to Forest Fire,
ISPRS20(B3:1207-1212).
DOI Link
2012
BibRef
Barrile, V.,
Bilotta, G.,
Fotia, A.,
Bernardo, E.,
Integrated GIS System for Post-fire Hazard Assessments With Remote
Sensing,
Gi4DM20(13-20).
DOI Link
2012
BibRef
Darmawan, S.[Soni],
Sari, D.K.[Dewi Kania],
Wikantika, K.[Ketut],
Tridawati, A.[Anggun],
Hernawati, R.[Rika],
Sedu, M.K.[Maria Kurniawati],
Identification before-after Forest Fire and Prediction of Mangrove
Forest Based on Markov-Cellular Automata in Part of Sembilang
National Park, Banyuasin, South Sumatra, Indonesia,
RS(12), No. 22, 2020, pp. xx-yy.
DOI Link
2011
BibRef
Chung, M.,
Jung, M.,
Kim, Y.,
Wildfire Damage Assessment Using Multi-temporal Sentinel-2 Data,
Gi4DM19(97-102).
DOI Link
1912
BibRef
Attaf, D.,
Djerriri, K.,
Mansour, D.,
Hamdadou, D.,
Mapping of Burned Area Using Presence and Background Learning Framework
On The Google Earth Engine Platform,
Gi4DM19(37-41).
DOI Link
1912
BibRef
Valipour Shokouhi, B.,
Eslami, M.,
Fuzzy Logic Based Burned Severity Classification and Mapping With
Landsat-8 Data,
PIA19(259-265).
DOI Link
1912
BibRef
Pádua, L.,
Adão, T.,
Guimarães, N.,
Sousa, A.,
Peres, E.,
Sousa, J.J.,
Post-fire Forestry Recovery Monitoring Using High-resolution
Multispectral Imagery From Unmanned Aerial Vehicles,
Gi4DM19(301-305).
DOI Link
1912
BibRef
Savorskiy, V.,
Bartalev, S.,
Kashnitskiy, A.,
Mazurov, A.,
Panova, O.,
Stytsenko, F.,
Geoinformation Tools Providing Estimations Of Vegetation Areal Damages
Caused By Wild Fire Disasters,
Gi4DM18(437-444).
DOI Link
1805
BibRef
Akca, D.,
Stylianidis, E.,
Poli, D.,
Gruen, A.,
Altan, O.,
Hofer, M.,
Smagas, K.,
Sanchez Martin, V.,
Walli, A.,
Jimeno, E.,
Garcia, A.,
3-dimensional Pre- And Post-fire Comparison Of Forest Areas,
Gi4DM18(9-16).
DOI Link
1805
BibRef
Çolak, E.,
Sunar, A.F.,
Remote Sensing and GIS Integration for Monitoring the Areas Affected by
Forest Fires: A Case Study in Izmir, Turkey,
Gi4DM18(165-170).
DOI Link
1805
BibRef
Brook, A.,
Polinova, M.,
Kopel, D.,
Malkinson, D.,
Wittenberg, L.,
Roberts, D.,
Shtober-Zisu, N.,
Remote Sensing Techniques To Assess Post-fire Effects at the Hillslope
and Sub-Basin Scales Via Multi-scale Model,
Hannover17(135-141).
DOI Link
1805
BibRef
Mazher, A.[Abeer],
Li, P.J.[Pei-Jun],
Zhang, J.[Jun],
Mapping burned areas from Landsat TM imags: A comparative study,
CVRS12(285-290).
IEEE DOI
1302
BibRef
Chuvieco, E.,
Sandow, C.,
Guenther, K.P.,
González-alonso, F.,
Pereira, J.M.,
Pérez, O.,
Bradley, A.V.,
Schultz, M.,
Mouillot, F.,
Ciais, P.,
Global Burned Area Mapping From European Satellites: The Esa Fire_cci
Project,
ISPRS12(XXXIX-B8:13-16).
DOI Link
1209
BibRef
Mckinley, R.,
Clark, J.,
Lecker, J.,
Burn Severity Mapping In Australia 2009,
ISPRS12(XXXIX-B8:51-54).
DOI Link
1209
BibRef
Pirotti, F.,
Guarnieri, A.,
Vettore, A.,
Waveform Analysis For The Extraction Of Post-fire Vegetation
Characteristics,
ISPRS12(XXXIX-B7:523-527).
DOI Link
1209
BibRef
Schnase, J.L.,
Carroll, M.L.,
Weber, K.T.,
Brown, M.E.,
Gill, R.L.,
Wooten, M.,
May, J.,
Serr, K.,
Smith, E.,
Goldsby, R.,
Newtoff, K.,
Bradford, K.,
Doyle, C.,
Volker, E.,
Weber, S.,
RECOVER: An Automated, Cloud-Based Decision Support System for
Post-Fire Rehabilitation Planning,
LandImaging14(363-370).
DOI Link
1411
BibRef
Chen, J.C.,
Chen, C.T.,
Jump, A.S.,
Forest Disturbance Leads To The Rapid Spread Of The Invasive Leucaena
Leucocephala In Taiwan,
ISPRS12(XXXIX-B2:35-40).
DOI Link
1209
BibRef
Kusimi, J.M.,
Appati, J.W.,
Bushfires In The Krachi District: The Socio-economic And Environmental
Implications,
ISPRS12(XXXIX-B8:39-44).
DOI Link
1209
BibRef
Michaletz, S.T.[Sean T.],
Johnson, E.A.[Edward A.],
Modeling post-fire tree mortality: sapwood area reduction in stems,
CGC10(331).
PDF File.
1006
BibRef
Mallinis, G.[Georgios],
Pleniou, M.,
Koutsiasb, N.,
Object-Based vs. Pixel-Based Mapping of Fire Scars Using Multi-Scale
Satellite Data,
GEOBIA10(xx-yy).
PDF File.
1007
BibRef
Chapter on Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR continues in
Forest Change Evaluation, Change Detection, Temporal Analysis .