22.5.11.6 Forest Fire Evaluation, Wildfire Analysis, Fire Detection, Fire Damage Assessment

Chapter Contents (Back)
Forest. Forest Fires. Fire Detection. See also Burned Area Detection. Mostly for non-fire changes: See also Forest Change Evaluation, Change Detection, Temporal Analysis. See also Surveillance Systems, Applied to Fire and Flame Detection.

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

Shephard, M.W., Kennelly, E.J.,
Effect of band-to-band coregistration on fire property retrievals,
GeoRS(41), No. 11, November 2003, pp. 2648-2661.
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

Mims, S.R., Kahn, R.A., Moroney, C.M., Gaitley, B.J., Nelson, D.L., Garay, M.J.,
MISR Stereo Heights of Grassland Fire Smoke Plumes in Australia,
GeoRS(48), No. 1, January 2010, pp. 25-35.
IEEE DOI 1001
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

Harris, S., Veraverbeke, S., Hook, S.,
Evaluating Spectral Indices for Assessing Fire Severity in Chaparral Ecosystems (Southern California) Using MODIS/ASTER (MASTER) Airborne Simulator Data,
RS(3), No. 11, November 2011, pp. 2403-2419.
DOI Link 1203
BibRef

Sifakis, N., Iossifidis, C., Kontoes, C.C., Keramitsoglou, I.,
Wildfire Detection and Tracking over Greece Using MSG-SEVIRI Satellite Data,
RS(3), No. 3, March 2011, pp. 524-538.
DOI Link 1203
BibRef

Listopad, C., Drake, J., Masters, R., Weishampel, J.,
Portable and Airborne Small Footprint LiDAR: Forest Canopy Structure Estimation of Fire Managed Plots,
RS(3), No. 7, July 2011, pp. 1284-1307.
DOI Link 1203
BibRef

Gunay, O., Toreyin, B.U., Kose, K., Cetin, A.E.,
Entropy-Functional-Based Online Adaptive Decision Fusion Framework With Application to Wildfire Detection in Video,
IP(21), No. 5, May 2012, pp. 2853-2865.
IEEE DOI 1204
BibRef

Lewis, S., Robichaud, P., Hudak, A., Austin, B., Liebermann, R.,
Utility of Remotely Sensed Imagery for Assessing the Impact of Salvage Logging after Forest Fires,
RS(4), No. 7, July 2012, pp. 2112-2132.
DOI Link 1208
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

Orozco, C.V.[Carmen Vega], Tonini, M.[Marj], Conedera, M.[Marco], Kanveski, M.[Mikhail],
Cluster recognition in spatial-temporal sequences: The case of forest fires,
GeoInfo(16), No. 4, October 2012, pp. 653-673.
WWW Link. 1210
BibRef

Bernhard, E.M.[Eva-Maria], Twele, A.[André], Gähler, M.[Monika],
Rapid Mapping of Forest Fires in the European Mediterranean Region: A Change Detection Approach Using X-Band SAR-Data,
PFG(2011), No. 4, 2011, pp. 261-270.
WWW Link. 1211
BibRef

Maier, S.W.[Stefan W.], Russell-Smith, J.[Jeremy], Edwards, A.C.[Andrew C.], Yates, C.[Cameron],
Sensitivity of the MODIS fire detection algorithm (MOD14) in the savanna region of the Northern Territory, Australia,
PandRS(76), No. 1, February 2013, pp. 11-16.
Elsevier DOI 1301
Forest fire; Thermal; Performance; Hazards; Monitoring; Detection BibRef

Honkavaara, E., Litkey, P., Nurminen, K.,
Automatic Storm Damage Detection in Forests Using High-Altitude Photogrammetric Imagery,
RS(5), No. 3, March 2013, pp. 1405-1424.
DOI Link 1304
BibRef

Litkey, P., Nurminen, K., Honkavaara, E.,
Automatic Detection of Storm Damages Using High-Altitude Photogrammetric Imaging,
Hannover13(195-200).
DOI Link 1308
BibRef

Jakovevic, T.[Toni], Stipanicev, D.[Darko], Krstinic, D.[Damir],
Visual spatial-context based wildfire smoke sensor,
MVA(24), No. 4, May 2013, pp. 707-719.
WWW Link. 1304
BibRef

Vastaranta, M., Kantola, T., Lyytikäinen-Saarenmaa, P., Holopainen, M., Kankare, V., Wulder, M., Hyyppä, J., Hyyppä, H.,
Area-Based Mapping of Defoliation of Scots Pine Stands Using Airborne Scanning LiDAR,
RS(5), No. 3, March 2013, pp. 1220-1234.
DOI Link 1304
BibRef

Ortiz, S., Breidenbach, J., Kändler, G.,
Early Detection of Bark Beetle Green Attack Using TerraSAR-X and RapidEye Data,
RS(5), No. 4, April 2013, pp. 1912-1931.
DOI Link 1305
BibRef

Huang, S.L.[Sheng-Li], Jin, S.[Suming], Dahal, D.[Devendra], Chen, X.[Xuexia], 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

Paugam, R., Wooster, M.J., Roberts, G.,
Use of Handheld Thermal Imager Data for Airborne Mapping of Fire Radiative Power and Energy and Flame Front Rate of Spread,
GeoRS(51), No. 6, 2013, pp. 3385-3399.
IEEE DOI 1307
flames; infrared imaging; georeferencing algorithm BibRef

Labati, R.D.[R. Donida], Genovese, A., Piuri, V., Scotti, F.,
Wildfire Smoke Detection Using Computational Intelligence Techniques Enhanced With Synthetic Smoke Plume Generation,
SMCS(43), No. 4, 2013, pp. 1003-1012.
IEEE DOI 1307
lattice Boltzmann; neural networks; wildfire BibRef

Ko, B.C.[Byoung-Chul], Park, J.O.[Jun-Oh], Nam, J.Y.[Jae-Yeal],
Spatiotemporal bag-of-features for early wildfire smoke detection,
IVC(31), No. 10, 2013, pp. 786-795.
Elsevier DOI 1310
Wildfire smoke detection BibRef

Park, J.[Jun_Oh], Ko, B.[Byoung_Chul], Nam, J.Y.[Jae-Yeal], Kwak, S.[Soo_Yeong],
Wildfire smoke detection using spatiotemporal bag-of-features of smoke,
WACV13(200-205).
IEEE DOI 1303
BibRef

Pennypacker, C.R.[Carlton R.], Jakubowski, M.K.[Marek K.], Kelly, M.[Maggi], Lampton, M.[Michael], Schmidt, C.[Christopher], Stephens, S.[Scott], Tripp, R.[Robert],
FUEGO: Fire Urgency Estimator in Geosynchronous Orbit: A Proposed Early-Warning Fire Detection System,
RS(5), No. 10, 2013, pp. 5173-5192.
DOI Link 1311
BibRef

Bisquert, M.[Mar], Sánchez, J.M.[Juan Manuel], Caselles, V.[Vicente],
Modeling Fire Danger in Galicia and Asturias (Spain) from MODIS Images,
RS(6), No. 1, 2014, pp. 540-554.
DOI Link 1402
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

Fisher, D., Muller, J.P., Yershov, V.N.,
Automated Stereo Retrieval of Smoke Plume Injection Heights and Retrieval of Smoke Plume Masks From AATSR and Their Assessment With CALIPSO and MISR,
GeoRS(52), No. 2, February 2014, pp. 1249-1258.
IEEE DOI 1402
geophysical techniques BibRef

Pennypacker, C.[Carlton],
FUEGO: a satellite system for rapid location of wildfires,
SPIE(Newsroom), February 14, 2014
DOI Link 1402
Combining imaging, computation, software modeling, and satellite hosting systems with firefighting methods may enable cost-effective detection and monitoring of wildland fires in their first few minutes. BibRef

Huo, H.Y.[Hong-Yuan], Jiang, X.G.[Xiao-Guang], Song, X.F.[Xian-Feng], Li, Z.L.[Zhao-Liang], Ni, Z.[Zhuoya], Gao, C.[Caixia],
Detection of Coal Fire Dynamics and Propagation Direction from Multi-Temporal Nighttime Landsat SWIR and TIR Data: A Case Study on the Rujigou Coalfield, Northwest (NW) China,
RS(6), No. 2, 2014, pp. 1234-1259.
DOI Link 1403
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

Freeborn, P.H.[Patrick H.], Wooster, M.J.[Martin J.], Roberts, G.[Gareth], Xu, W.D.[Wei-Dong],
Evaluating the SEVIRI Fire Thermal Anomaly Detection Algorithm across the Central African Republic Using the MODIS Active Fire Product,
RS(6), No. 3, 2014, pp. 1890-1917.
DOI Link 1404
BibRef

Le, G.E.[George E.], Breysse, P.N.[Patrick N.], McDermott, A.[Aidan], Eftim, S.E.[Sorina E.], Geyh, A.[Alison], Berman, J.D.[Jesse D.], Curriero, F.C.[Frank C.],
Canadian Forest Fires and the Effects of Long-Range Transboundary Air Pollution on Hospitalizations among the Elderly,
IJGI(3), No. 2, 2014, pp. 713-731.
DOI Link 1407
BibRef

Freeborn, P.H.[Patrick H.], Cochrane, M.A.[Mark A.], Wooster, M.J.[Martin J.],
A Decade Long, Multi-Scale Map Comparison of Fire Regime Parameters Derived from Three Publically Available Satellite-Based Fire Products: A Case Study in the Central African Republic,
RS(6), No. 5, 2014, pp. 4061-4089.
DOI Link 1407
BibRef

Montealegre, A.L.[Antonio Luis], Lamelas, M.T.[María Teresa], Tanase, M.A.[Mihai A.], de la Riva, J.[Juan],
Forest Fire Severity Assessment Using ALS Data in a Mediterranean Environment,
RS(6), No. 5, 2014, pp. 4240-4265.
DOI Link 1407
BibRef

Ling, B.[Bohua], Goodin, D.G.[Douglas G.], Mohler, R.L.[Rhett L.], Laws, A.N.[Angela N.], Joern, A.[Anthony],
Estimating Canopy Nitrogen Content in a Heterogeneous Grassland with Varying Fire and Grazing Treatments: Konza Prairie, Kansas, USA,
RS(6), No. 5, 2014, pp. 4430-4453.
DOI Link 1407
BibRef

Katagis, T.[Thomas], Gitas, I.Z.[Ioannis Z.], Mitri, G.H.[George H.],
An Object-Based Approach for Fire History Reconstruction by Using Three Generations of Landsat Sensors,
RS(6), No. 6, 2014, pp. 5480-5496.
DOI Link 1407
BibRef

Vlassova, L.[Lidia], Pérez-Cabello, F.[Fernando], Mimbrero, M.R.[Marcos Rodrigues], Llovería, R.M.[Raquel Montorio], García-Martín, A.[Alberto],
Analysis of the Relationship between Land Surface Temperature and Wildfire Severity in a Series of Landsat Images,
RS(6), No. 7, 2014, pp. 6136-6162.
DOI Link 1408
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

Daldegan, G.A.[Gabriel Antunes], de Carvalho, O.A.[Osmar Abílio], Guimarães, R.F.[Renato Fontes], Gomes, R.A.T.[Roberto Arnaldo Trancoso], de Figueiredo Ribeiro, F.[Fernanda], McManus, C.[Concepta],
Spatial Patterns of Fire Recurrence Using Remote Sensing and GIS in the Brazilian Savanna: Serra do Tombador Nature Reserve, Brazil,
RS(6), No. 10, 2014, pp. 9873-9894.
DOI Link 1411
BibRef

Safronov, A.N.[Alexander N.], Fokeeva, E.V.[Ekaterina V.], Rakitin, V.S.[Vadim S.], Grechko, E.I.[Eugene I.], Shumsky, R.A.[Roman A.],
Severe Wildfires Near Moscow, Russia in 2010: Modeling of Carbon Monoxide Pollution and Comparisons with Observations,
RS(7), No. 1, 2014, pp. 395-429.
DOI Link 1502
BibRef

Gross, B.[Barry], Wu, Y.H.[Yong-Hua], Moshary, F.[Fred], Delgado, R.[Ruben], Hoff, R.[Ray], Su, J.[Jia], Lee, R.[Robert], McCormick, P.[Pat],
Using lidar networks to explore aloft plume properties,
SPIE(Newsroom), December 30, 2014
DOI Link 1504
A coordinated lidar network in the northeastern United States explored the optical properties of transported plumes from fires and dust and diagnosed chemical transport model concentration biases. BibRef

Chowdhury, E.H.[Ehsan H.], Hassan, Q.K.[Quazi K.],
Development of a New Daily-Scale Forest Fire Danger Forecasting System Using Remote Sensing Data,
RS(7), No. 3, 2015, pp. 2431-2448.
DOI Link 1504
BibRef

Chowdhury, E.H.[Ehsan H.], Hassan, Q.K.[Quazi K.],
Operational perspective of remote sensing-based forest fire danger forecasting systems,
PandRS(104), No. 1, 2015, pp. 224-236.
Elsevier DOI 1505
Fire occurrence BibRef

Abdollahi, M.[Masoud], Islam, T.[Tanvir], Gupta, A.[Anil], Hassan, Q.K.[Quazi K.],
An Advanced Forest Fire Danger Forecasting System: Integration of Remote Sensing and Historical Sources of Ignition Data,
RS(10), No. 6, 2018, pp. xx-yy.
DOI Link 1806
BibRef

Li, X.L.[Xiao-Lian], Song, W.G.[Wei-Guo], Lian, L.P.[Li-Ping], Wei, X.G.[Xiao-Ge],
Forest Fire Smoke Detection Using Back-Propagation Neural Network Based on MODIS Data,
RS(7), No. 4, 2015, pp. 4473-4498.
DOI Link 1505
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

Borrelli, P.[Pasquale], Armenteras, D.[Dolors], Panagos, P.[Panos], Modugno, S.[Sirio], Schütt, B.[Brigitta],
The Implications of Fire Management in the Andean Paramo: A Preliminary Assessment Using Satellite Remote Sensing,
RS(7), No. 9, 2015, pp. 11061.
DOI Link 1511
BibRef

Toulouse, T., Rossi, L., Akhloufi, M., Celik, T., Maldague, X.,
Benchmarking of wildland fire colour segmentation algorithms,
IET-IPR(9), No. 12, 2015, pp. 1064-1072.
DOI Link 1512
fires BibRef

Li, P.[Peng], Feng, Z.M.[Zhi-Ming],
Extent and Area of Swidden in Montane Mainland Southeast Asia: Estimation by Multi-Step Thresholds with Landsat-8 OLI Data,
RS(8), No. 1, 2016, pp. 44.
DOI Link 1602
slash and burn analysis. BibRef

Bui, D.T.[Dieu Tien], Le, K.T.T.[Kim-Thoa Thi], Nguyen, V.C.[Van Cam], Le, H.D.[Hoang Duc], Revhaug, I.[Inge],
Tropical Forest Fire Susceptibility Mapping at the Cat Ba National Park Area, Hai Phong City, Vietnam, Using GIS-Based Kernel Logistic Regression,
RS(8), No. 4, 2016, pp. 347.
DOI Link 1604
BibRef

Benali, A.[Akli], Russo, A.[Ana], Sá, A.C.L.[Ana C. L.], Pinto, R.M.S.[Renata M. S.], Price, O.[Owen], Koutsias, N.[Nikos], Pereira, J.M.C.[José M. C.],
Determining Fire Dates and Locating Ignition Points With Satellite Data,
RS(8), No. 4, 2016, pp. 326.
DOI Link 1604
BibRef

Lin, L.[Lei], Meng, Y.[Yu], Yue, A.Z.[An-Zhi], Yuan, Y.[Yuan], Liu, X.Y.[Xiao-Yi], Chen, J.B.[Jing-Bo], Zhang, M.M.[Meng-Meng], Chen, J.S.[Jian-Sheng],
A Spatio-Temporal Model for Forest Fire Detection Using HJ-IRS Satellite Data,
RS(8), No. 5, 2016, pp. 403.
DOI Link 1606
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

Polivka, T.N., Wang, J., Ellison, L.T., Hyer, E.J., Ichoku, C.M.,
Improving Nocturnal Fire Detection With the VIIRS Day: Night Band,
GeoRS(54), No. 9, September 2016, pp. 5503-5519.
IEEE DOI 1609
remote sensing BibRef

Oom, D.[Duarte], Silva, P.C.[Pedro C.], Bistinas, I.[Ioannis], Pereira, J.M.C.[José M. C.],
Highlighting Biome-Specific Sensitivity of Fire Size Distributions to Time-Gap Parameter Using a New Algorithm for Fire Event Individuation,
RS(8), No. 8, 2016, pp. 663.
DOI Link 1609
BibRef

de Grandi, E.C.[Elsa Carla], Mitchard, E.[Edward], Hoekman, D.[Dirk],
Wavelet Based Analysis of TanDEM-X and LiDAR DEMs across a Tropical Vegetation Heterogeneity Gradient Driven by Fire Disturbance in Indonesia,
RS(8), No. 8, 2016, pp. 641.
DOI Link 1609
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

Xie, H.[Huan], Du, L.[Li], Liu, S.[Sicong], Chen, L.[Lei], Gao, S.[Sa], Liu, S.[Shuang], Pan, H.Y.[Hai-Yan], Tong, X.H.[Xiao-Hua],
Dynamic Monitoring of Agricultural Fires in China from 2010 to 2014 Using MODIS and GlobeLand30 Data,
IJGI(5), No. 10, 2016, pp. 172.
DOI Link 1610
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

Tian, G., Ren, Y., Zhou, M.,
Dual-Objective Scheduling of Rescue Vehicles to Distinguish Forest Fires via Differential Evolution and Particle Swarm Optimization Combined Algorithm,
ITS(17), No. 11, November 2016, pp. 3009-3021.
IEEE DOI 1609
Engines BibRef

Zhao, F.R.[Feng R.], Meng, R.[Ran], Huang, C.Q.[Cheng-Quan], Zhao, M.[Maosheng], Zhao, F.A.[Feng A.], Gong, P.[Peng], Yu, L.[Le], Zhu, Z.[Zhiliang],
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

Wickramasinghe, C.H.[Chathura H.], Jones, S.[Simon], Reinke, K.[Karin], Wallace, L.[Luke],
Development of a Multi-Spatial Resolution Approach to the Surveillance of Active Fire Lines Using Himawari-8,
RS(8), No. 11, 2016, pp. 932.
DOI Link 1612
BibRef

Plank, S.[Simon], Fuchs, E.M.[Eva-Maria], Frey, C.[Corinne],
A Fully Automatic Instantaneous Fire Hotspot Detection Processor Based on AVHRR Imagery: A TIMELINE Thematic Processor,
RS(9), No. 1, 2017, pp. xx-yy.
DOI Link 1702
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
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

García, M.[Mariano], Saatchi, S.[Sassan], Casas, A.[Angeles], Koltunov, A.[Alexander], Ustin, S.L.[Susan L.], Ramirez, C.[Carlos], Balzter, H.[Heiko],
Extrapolating Forest Canopy Fuel Properties in the California Rim Fire by Combining Airborne LiDAR and Landsat OLI Data,
RS(9), No. 4, 2017, pp. xx-yy.
DOI Link 1705
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

Fukuhara, T., Kouyama, T., Kato, S., Nakamura, R., Takahashi, Y., Akiyama, H.,
Detection of Small Wildfire by Thermal Infrared Camera With the Uncooled Microbolometer Array for 50-kg Class Satellite,
GeoRS(55), No. 8, August 2017, pp. 4314-4324.
IEEE DOI 1708
Brightness temperature, Cameras, Instruments, Low earth orbit satellites, Satellite broadcasting, Spatial resolution, Infrared imaging, remote sensing, satellite, applications BibRef

Lin, Z., Chen, F., Li, B., Yu, B., Shirazi, Z., Wu, Q., Wu, W.,
FengYun-3C VIRR Active Fire Monitoring: Algorithm Description and Initial Assessment Using MODIS and Landsat Data,
GeoRS(55), No. 11, November 2017, pp. 6420-6430.
IEEE DOI 1711
Algorithm design and analysis, Earth, Heuristic algorithms, MODIS, Active fire monitoring. BibRef

Fornacca, D.[Davide], Ren, G.[Guopeng], Xiao, W.[Wen],
Performance of Three MODIS Fire Products (MCD45A1, MCD64A1, MCD14ML), and ESA Fire_CCI in a Mountainous Area of Northwest Yunnan, China, Characterized by Frequent Small Fires,
RS(9), No. 11, 2017, pp. xx-yy.
DOI Link 1712
BibRef

Zhang, X.X.[Xiao-Xiang], Yao, J.[Jing], Sila-Nowicka, K.[Katarzyna],
Exploring Spatiotemporal Dynamics of Urban Fires: A Case of Nanjing, China,
IJGI(7), No. 1, 2018, pp. xx-yy.
DOI Link 1801
BibRef
Earlier: A2, A1, Only:
Spatial-temporal Dynamics Of Urban Fire Incidents: A Case Study Of Nanjing, China,
ISPRS16(B2: 63-69).
DOI Link 1610
BibRef

Cho, K.[Kangjoon], Kim, Y.[Yonghyun], Kim, Y.[Yongil],
Disaggregation of Landsat-8 Thermal Data Using Guided SWIR Imagery on the Scene of a Wildfire,
RS(10), No. 1, 2018, pp. xx-yy.
DOI Link 1802
BibRef

Myoung, B.[Boksoon], Kim, S.H.[Seung Hee], Nghiem, S.V.[Son V.], Jia, S.[Shenyue], Whitney, K.[Kristen], Kafatos, M.C.[Menas C.],
Estimating Live Fuel Moisture from MODIS Satellite Data for Wildfire Danger Assessment in Southern California USA,
RS(10), No. 1, 2018, pp. xx-yy.
DOI Link 1802
BibRef

Jia, S.[Shenyue], Kim, S.H.[Seung Hee], Nghiem, S.V.[Son V.], Kafatos, M.[Menas],
Estimating Live Fuel Moisture Using SMAP L-Band Radiometer Soil Moisture for Southern California, USA,
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Remote Sensing Applied to the Study of Fire Regime Attributes and Their Influence on Post-Fire Greenness Recovery in Pine Ecosystems,
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Mean Composite Fire Severity Metrics Computed with Google Earth Engine Offer Improved Accuracy and Expanded Mapping Potential,
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How Well Does the 'Small Fire Boost' Methodology Used within the GFED4.1s Fire Emissions Database Represent the Timing, Location and Magnitude of Agricultural Burning?,
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Remote Sensing Approach to Detect Burn Severity Risk Zones in Palo Verde National Park, Costa Rica,
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FRP: Fire Radiative Power. Active fire monitoring. BibRef

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IEEE DOI 1907
Table lookup, Cameras, Sensors, MODIS, Solar radiation, Fires, Bispectral method, fire radiative power (FRP), TET-1 BibRef

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Giving Ecological Meaning to Satellite-Derived Fire Severity Metrics across North American Forests,
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Methods to Detect Edge Effected Reductions in Fire Frequency in Simulated Forest Landscapes,
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Ahmed, M.R.[M. Razu], Hassan, Q.K.[Quazi K.], Abdollahi, M.[Masoud], Gupta, A.[Anil],
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Rihan, W.[Wu], Zhao, J.J.[Jian-Jun], Zhang, H.Y.[Hong-Yan], Guo, X.Y.[Xiao-Yi], Ying, H.[Hong], Deng, G.R.[Guo-Rong], Li, H.[Hui],
Wildfires on the Mongolian Plateau: Identifying Drivers and Spatial Distributions to Predict Wildfire Probability,
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Karna, Y.K.[Yogendra K.], Penman, T.D.[Trent D.], Aponte, C.[Cristina], Bennett, L.T.[Lauren T.],
Assessing Legacy Effects of Wildfires on the Crown Structure of Fire-Tolerant Eucalypt Trees Using Airborne LiDAR Data,
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Lin, Z., Chen, F., Li, B., Yu, B., Jia, H., Zhang, M., Liang, D.,
A Contextual and Multitemporal Active-Fire Detection Algorithm Based on FengYun-2G S-VISSR Data,
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IEEE DOI 1911
Satellite broadcasting, Spatial resolution, MODIS, Geostationary satellites, Detection algorithms, geostationary satellite data BibRef

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A Review of the Applications of Remote Sensing in Fire Ecology,
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Shah, S.B., Grübler, T., Krempel, L., Ernst, S., Mauracher, F., Contractor, S.,
Real-time Wildfire Detection From Space - a Trade-off Between Sensor Quality, Physical Limitations and Payload Size,
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Hesam, S., Valizadeh Kamran, K.,
Intelligent Management Occurrence and Spread of Front Fire in Gis By Using Cellular Automata. Case Study: Golestan Forest,
SMPR19(475-481).
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Jahdi, R., Salis, M., Arabi, M., Arca, B.,
Fire Modelling to Assess Spatial Patterns of Wildfire Exposure In Ardabil, Nw Iran,
SMPR19(577-581).
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Stefanidou, A.[Alexandra], Gitas, I.Z.[Ioannis Z.], Stavrakoudis, D.[Dimitris], Eftychidis, G.[Georgios],
Midterm Fire Danger Prediction Using Satellite Imagery and Auxiliary Thematic Layers,
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Ying, L.X.[Ling-Xiao], Shen, Z.[Zehao], Yang, M.Z.[Ming-Zheng], Piao, S.L.[Shi-Long],
Wildfire Detection Probability of MODIS Fire Products under the Constraint of Environmental Factors: A Study Based on Confirmed Ground Wildfire Records,
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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,
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Govil, K.[Kinshuk], Welch, M.L.[Morgan L.], Ball, J.T.[J. Timothy], Pennypacker, C.R.[Carlton R.],
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Kumar, S.S.[Sanath Sathyachandran], Hult, J.[John], Picotte, J.[Joshua], Peterson, B.[Birgit],
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Valero, M.M.[Mario M.], Verstockt, S.[Steven], Mata, C.[Christian], Jimenez, D.[Dan], Queen, L.[Lloyd], Rios, O.[Oriol], Pastor, E.[Elsa], Planas, E.[Eulàlia],
Image Similarity Metrics Suitable for Infrared Video Stabilization during Active Wildfire Monitoring: A Comparative Analysis,
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Li, X., Chen, Z., Wu, Q.M.J., Liu, C.,
3D Parallel Fully Convolutional Networks for Real-Time Video Wildfire Smoke Detection,
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IEEE DOI 2002
convolutional neural nets, feature extraction, geophysical image processing, image classification, natural scene BibRef

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Varotsos, C.A.[Costas A.], Krapivin, V.F.[Vladimir F.], Mkrtchyan, F.A.[Ferdenant A.],
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Pham, H.X., La, H.M., Feil-Seifer, D., Deans, M.C.,
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IEEE DOI 2004
Mathematical model, Unmanned aerial vehicles, Robot sensing systems, Decentralized control, Task analysis, Color, networked robots BibRef

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Farahmand, A.[Alireza], Stavros, E.N.[E. Natasha], Reager, J.T.[John T.], Behrangi, A.[Ali],
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Zhang, X.X.[Xiao-Xiang], Yao, J.[Jing], Sila-Nowicka, K.[Katarzyna], Jin, Y.[Yuhao],
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Pan, H.Y.[Hong-Yi], Badawi, D.[Diaa], Zhang, X.[Xi], Cetin, A.E.[Ahmet Enis],
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Udahemuka, G.[Gustave], van Wyk, B.J.[Barend J.], Hamam, Y.[Yskandar],
Characterization of Background Temperature Dynamics of a Multitemporal Satellite Scene through Data Assimilation for Wildfire Detection,
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Razavi-Termeh, S.V.[Seyed Vahid], Sadeghi-Niaraki, A.[Abolghasem], Choi, S.M.[Soo-Mi],
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Li, F.[Fangjun], Zhang, X.Y.[Xiao-Yang], Kondragunta, S.[Shobha],
Biomass Burning in Africa: An Investigation of Fire Radiative Power Missed by MODIS Using the 375 m VIIRS Active Fire Product,
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Donovan, V.M.[Victoria M.], Wonkka, C.L.[Carissa L.], Wedin, D.A.[David A.], Twidwell, D.[Dirac],
Land-Use Type as a Driver of Large Wildfire Occurrence in the U.S. Great Plains,
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García, M.[Mariano], Riaño, D.[David], Yebra, M.[Marta], Salas, J.[Javier], Cardil, A.[Adrián], Monedero, S.[Santiago], Ramirez, J.[Joaquín], Martín, M.P.[M. Pilar], Vilar, L.[Lara], Gajardo, J.[John], Ustin, S.[Susan],
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Wei, X.[Xikun], Wang, G.[Guojie], Chen, T.[Tiexi], Hagan, D.F.T.[Daniel Fiifi Tawia], Ullah, W.[Waheed],
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Li, Z.P.[Zheng-Peng], Shi, H.[Hua], Vogelmann, J.E.[James E.], Hawbaker, T.J.[Todd J.], Peterson, B.[Birgit],
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Guldåker, N.[Nicklas],
Geovisualization and Geographical Analysis for Fire Prevention,
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Graff, C.A., Coffield, S.R., Chen, Y., Foufoula-Georgiou, E., Randerson, J.T., Smyth, P.,
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IEEE DOI 2006
Predictive models, Weather forecasting, MODIS, Atmospheric modeling, Forecasting, Satellites, vapor pressure deficit (VPD) BibRef


de Paula, L.G.[Lucas Goncalves], Hyttel, K.[Kristian], Geipel, K.R.[Kenneth Richard], de Domingo Gil, J.E.[Jacobo Eduardo], Novac, I.[Iuliu], Chrysostomou, D.[Dimitrios],
Estimation of Wildfire Size and Location Using a Monocular Camera on a Semi-autonomous Quadcopter,
CVS19(133-142).
Springer DOI 1912
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Biswal, S.S., Gorai, A.K.,
Detection and Delineation of Subsurface Coal Mine Fire From Spaceborne Thermal Infrared Data in Jharia Coalfield, Dhanbad, India,
Gi4DM19(65-69).
DOI Link 1912
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Špulák, P.,
Aerial Firefighting of Forest Fires: Spatial Data Support,
Gi4DM19(409-413).
DOI Link 1912
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Adão, T., Pinho, T.M., Pádua, L., Santos, N., Sousa, A., Sousa, J.J., Peres, E.,
Using Virtual Scenarios to Produce Machine Learnable Environments For Wildfire Detection and Segmentation,
Gi4DM19(9-15).
DOI Link 1912
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Chung, M., Jung, M., Kim, Y.,
Wildfire Damage Assessment Using Multi-temporal Sentinel-2 Data,
Gi4DM19(97-102).
DOI Link 1912
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Akay, A.E., Karas, I.R., Kahraman, I.,
Determining the Locations of Potential Firefighting Teams By Using GIS Techniques,
GeoDisast18(83-88).
DOI Link 1901
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Nasanbat, E., Lkhamjav, O., Balkhai, A., Tsevee-Oirov, C., Purev, A., Dorjsuren, M.,
A Spatial Distributionmap Of The Wildfire Risk In Mongolia Using Decision Support System,
Gi4DM18(357-362).
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Chapter on Remote Sensing, Cartography, Aerial Images, Buildings, Roads, Terrain, ATR continues in
Burned Area Detection .


Last update:Jul 10, 2020 at 16:03:35