23.4.13.8.1 Smoke from Forest Fires, Smoke from Wildfires

Chapter Contents (Back)
Smoke Detection. Forest Fires. Smoke. More surveillance:
See also Surveillance Systems for Smoke Detection, Aerial Image Smoke Detection.
See also Forest Fire Evaluation, Wildfire Analysis, Brushfire Analysis, Fire Detection.

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

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

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

Bugaric, M.[Marin], Jakovcevic, T.[Toni], Stipanicev, D.[Darko],
Adaptive estimation of visual smoke detection parameters based on spatial data and fire risk index,
CVIU(118), No. 1, 2014, pp. 184-196.
Elsevier DOI 1312
Smoke detection 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

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

Martin, M.V.[Maria Val], Kahn, R.A.[Ralph A.], Tosca, M.G.[Mika G.],
A Global Analysis of Wildfire Smoke Injection Heights Derived from Space-Based Multi-Angle Imaging,
RS(10), No. 10, 2018, pp. xx-yy.
DOI Link 1811
BibRef

Várnai, T.[Tamás], Gatebe, C.[Charles], Gautam, R.[Ritesh], Poudyal, R.[Rajesh], Su, W.Y.[Wen-Ying],
Developing an Aircraft-Based Angular Distribution Model of Solar Reflection from Wildfire Smoke to Aid Satellite-Based Radiative Flux Estimation,
RS(11), No. 13, 2019, pp. xx-yy.
DOI Link 1907
BibRef

Ba, R.[Rui], Chen, C.[Chen], Yuan, J.[Jing], Song, W.G.[Wei-Guo], Lo, S.[Siuming],
SmokeNet: Satellite Smoke Scene Detection Using Convolutional Neural Network with Spatial and Channel-Wise Attention,
RS(11), No. 14, 2019, pp. xx-yy.
DOI Link 1908
BibRef

Li, X., Chen, Z., Wu, Q.M.J., Liu, C.,
3D Parallel Fully Convolutional Networks for Real-Time Video Wildfire Smoke Detection,
CirSysVideo(30), No. 1, January 2020, pp. 89-103.
IEEE DOI 2002
convolutional neural nets, feature extraction, geophysical image processing, image classification, natural scene BibRef

Zhu, G.D.[Guo-Dong], Chen, Z.X.[Zhen-Xue], Liu, C.Y.[Cheng-Yun], Rong, X.W.[Xue-Wen], He, W.K.[Wei-Kai],
3D video semantic segmentation for wildfire smoke,
MVA(31), No. 6, August 2020, pp. Article50.
Springer DOI 2008
BibRef

Lu, X.M.[Xiao-Man], Zhang, X.Y.[Xiao-Yang], Li, F.J.[Fang-Jun], Cochrane, M.A.[Mark A.], Ciren, P.[Pubu],
Detection of Fire Smoke Plumes Based on Aerosol Scattering Using VIIRS Data over Global Fire-Prone Regions,
RS(13), No. 2, 2021, pp. xx-yy.
DOI Link 2101
BibRef

Mo, Y.H.[Yu-Hao], Yang, X.[Xin], Tang, H.[Hong], Li, Z.G.[Zhi-Gang],
Smoke Detection from Himawari-8 Satellite Data over Kalimantan Island Using Multilayer Perceptrons,
RS(13), No. 18, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Wang, Z.W.[Ze-Wei], Yang, P.F.[Peng-Fei], Liang, H.T.[Hao-Tian], Zheng, C.[Change], Yin, J.Y.[Ji-Yan], Tian, Y.[Ye], Cui, W.B.[Wen-Bin],
Semantic Segmentation and Analysis on Sensitive Parameters of Forest Fire Smoke Using Smoke-Unet and Landsat-8 Imagery,
RS(14), No. 1, 2022, pp. xx-yy.
DOI Link 2201
BibRef

Zheng, X.[Xin], Chen, F.[Feng], Lou, L.M.[Li-Ming], Cheng, P.[Pengle], Huang, Y.[Ying],
Real-Time Detection of Full-Scale Forest Fire Smoke Based on Deep Convolution Neural Network,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Dewangan, A.[Anshuman], Pande, Y.[Yash], Braun, H.W.[Hans-Werner], Vernon, F.[Frank], Perez, I.[Ismael], Altintas, I.[Ilkay], Cottrell, G.W.[Garrison W.], Nguyen, M.H.[Mai H.],
FIgLib & SmokeyNet: Dataset and Deep Learning Model for Real-Time Wildland Fire Smoke Detection,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Nakata, M.[Makiko], Sano, I.[Itaru], Mukai, S.[Sonoyo], Kokhanovsky, A.[Alexander],
Characterization of Wildfire Smoke over Complex Terrain Using Satellite Observations, Ground-Based Observations, and Meteorological Models,
RS(14), No. 10, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Konovalov, I.B.[Igor B.], Golovushkin, N.A.[Nikolai A.], Beekmann, M.[Matthias], Turquety, S.[Solène],
Using Multi-Platform Satellite Observations to Study the Atmospheric Evolution of Brown Carbon in Siberian Biomass Burning Plumes,
RS(14), No. 11, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Lemmouchi, F.[Farouk], Cuesta, J.[Juan], Eremenko, M.[Maxim], Derognat, C.[Claude], Siour, G.[Guillaume], Dufour, G.[Gaëlle], Sellitto, P.[Pasquale], Turquety, S.[Solène], Tran, D.[Dung], Liu, X.[Xiong], Zoogman, P.[Peter], Lutz, R.[Ronny], Loyola, D.[Diego],
Three-Dimensional Distribution of Biomass Burning Aerosols from Australian Wildfires Observed by TROPOMI Satellite Observations,
RS(14), No. 11, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Chen, J.[Jie], Zheng, W.[Wei], Wu, S.[Shuang], Liu, C.[Cheng], Yan, H.[Hua],
Fire Monitoring Algorithm and Its Application on the Geo-Kompsat-2A Geostationary Meteorological Satellite,
RS(14), No. 11, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Martins, L.[Leonardo], Guede-Fernández, F.[Federico], de Almeida, R.V.[Rui Valente], Gamboa, H.[Hugo], Vieira, P.[Pedro],
Real-Time Integration of Segmentation Techniques for Reduction of False Positive Rates in Fire Plume Detection Systems during Forest Fires,
RS(14), No. 11, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Engel, C.B.[Chermelle B.], Jones, S.D.[Simon D.], Reinke, K.J.[Karin J.],
Fire Radiative Power (FRP) Values for Biogeographical Region and Individual Geostationary HHMMSS Threshold (BRIGHT) Hotspots Derived from the Advanced Himawari Imager (AHI),
RS(14), No. 11, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Deng, Z.[Zhen], Hu, S.H.[Shu-Hao], Yin, S.B.[Shi-Bai], Wang, Y.[Yibin], Basu, A.[Anup], Cheng, I.[Irene],
Multi-step implicit Adams predictor-corrector network for fire detection,
IET-IPR(16), No. 9, 2022, pp. 2338-2350.
DOI Link 2206
BibRef

Zhao, L.[Liang], Liu, J.[Jixue], Peters, S.[Stefan], Li, J.Y.[Jiu-Yong], Oliver, S.[Simon], Mueller, N.[Norman],
Investigating the Impact of Using IR Bands on Early Fire Smoke Detection from Landsat Imagery with a Lightweight CNN Model,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link 2208
BibRef

López-Cayuela, M.Á.[María-Ángeles], Herrera, M.E.[Milagros E.], Córdoba-Jabonero, C.[Carmen], Pérez-Ramírez, D.[Daniel], Carvajal-Pérez, C.V.[Clara Violeta], Dubovik, O.[Oleg], Guerrero-Rascado, J.L.[Juan Luis],
Retrieval of Aged Biomass-Burning Aerosol Properties by Using GRASP Code in Synergy with Polarized Micro-Pulse Lidar and Sun/Sky Photometer,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Lv, Z.H.[Zheng-Han], Shi, Y.S.[Yu-Sheng], Guo, D.F.[Dian-Fan], Zhu, Y.[Yue], Man, H.R.[Hao-Ran], Zhang, Y.[Yang], Zang, S.Y.[Shu-Ying],
High-Resolution Daily Emission Inventory of Biomass Burning in the Amur-Heilong River Basin Based on MODIS Fire Radiative Energy Data,
RS(14), No. 16, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Yazdi, A.[Amirhessam], Qin, H.Y.[He-Yang], Jordan, C.B.[Connor B.], Yang, L.[Lei], Yan, F.[Feng],
Nemo: An Open-Source Transformer-Supercharged Benchmark for Fine-Grained Wildfire Smoke Detection,
RS(14), No. 16, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Adam, M.[Mariana], Fragkos, K.[Konstantinos], Solomos, S.[Stavros], Belegante, L.[Livio], Andrei, S.[Simona], Talianu, C.[Camelia], Marmureanu, L.[Luminita], Antonescu, B.[Bogdan], Ene, D.[Dragos], Nicolae, V.[Victor], Amiridis, V.[Vassilis],
Methodology for Lidar Monitoring of Biomass Burning Smoke in Connection with the Land Cover,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210
BibRef

de Rosa, B.[Benedetto], Amato, F.[Francesco], Amodeo, A.[Aldo], d'Amico, G.[Giuseppe], Dema, C.[Claudio], Falconieri, A.[Alfredo], Giunta, A.[Aldo], Gumà-Claramunt, P.[Pilar], Kampouri, A.[Anna], Solomos, S.[Stavros], Mytilinaios, M.[Michail], Papagiannopoulos, N.[Nikolaos], Summa, D.[Donato], Veselovskii, I.[Igor], Mona, L.[Lucia],
Characterization of Extremely Fresh Biomass Burning Aerosol by Means of Lidar Observations,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210
BibRef

Attiya, A.A.[Ali A.], Jones, B.G.[Brian G.],
Impact of Smoke Plumes Transport on Air Quality in Sydney during Extensive Bushfires (2019) in New South Wales, Australia Using Remote Sensing and Ground Data,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Bar, S.[Somnath], Parida, B.R.[Bikash Ranjan], Pandey, A.C.[Arvind Chandra], Kumar, N.[Navneet],
Pixel-Based Long-Term (2001-2020) Estimations of Forest Fire Emissions over the Himalaya,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Li, J.[Jian], Liu, H.[Hua], Du, J.[Jia], Cao, B.[Bin], Zhang, Y.W.[Yi-Wei], Yu, W.L.[Wei-Lin], Zhang, W.J.[Wei-Jian], Zheng, Z.[Zhi], Wang, Y.[Yan], Sun, Y.[Yue], Chen, Y.[Yuanhui],
Detection of Smoke from Straw Burning Using Sentinel-2 Satellite Data and an Improved YOLOv5s Algorithm,
RS(15), No. 10, 2023, pp. xx-yy.
DOI Link 2306
BibRef

Bhamra, J.K.[Jaspreet Kaur], Ramaprasad, S.A.[Shreyas Anantha], Baldota, S.[Siddhant], Luna, S.[Shane], Zen, E.[Eugene], Ramachandra, R.[Ravi], Kim, H.[Harrison], Schmidt, C.[Chris], Arends, C.[Chris], Block, J.[Jessica], Perez, I.[Ismael], Crawl, D.[Daniel], Altintas, I.[Ilkay], Cottrell, G.W.[Garrison W.], Nguyen, M.H.[Mai H.],
Multimodal Wildland Fire Smoke Detection,
RS(15), No. 11, 2023, pp. 2790.
DOI Link 2306
BibRef

Chen, G.[Gong], Cheng, R.[Renxi], Lin, X.[Xufeng], Jiao, W.[Wanguo], Bai, D.[Di], Lin, H.F.[Hai-Feng],
LMDFS: A Lightweight Model for Detecting Forest Fire Smoke in UAV Images Based on YOLOv7,
RS(15), No. 15, 2023, pp. xx-yy.
DOI Link 2308
BibRef

Tao, H.[Huanjie], Duan, Q.[Qianyue], Lu, M.H.[Ming-Hao], Hu, Z.[Zhenwu],
Learning discriminative feature representation with pixel-level supervision for forest smoke recognition,
PR(143), 2023, pp. 109761.
Elsevier DOI 2310
Deep neural network, Component separation, Forest smoke recognition, Supervision information BibRef

Mukai, S.[Sonoyo], Hioki, S.[Souichiro], Nakata, M.[Makiko],
Biomass Burning Plume from Simultaneous Observations of Polarization and Radiance at Different Viewing Directions with SGLI,
RS(15), No. 22, 2023, pp. 5405.
DOI Link 2311
BibRef

Yang, H.Y.[Huan-Yu], Wang, J.[Jun], Wang, J.[Jiacun],
Efficient Detection of Forest Fire Smoke in UAV Aerial Imagery Based on an Improved Yolov5 Model and Transfer Learning,
RS(15), No. 23, 2023, pp. 5527.
DOI Link 2312
BibRef


Gupta, T.[Taanya], Liu, H.Y.[Heng-Yue], Bhanu, B.[Bir],
Early Wildfire Smoke Detection in Videos,
ICPR21(8523-8530)
IEEE DOI 2105
Training, Fires, Vegetation, Object segmentation, Forestry, Unmanned aerial vehicles, Pattern recognition BibRef

Chapter on Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR continues in
Forest Fire Prediction, Fire Hazard, Mitigation, Risk, Susceptibility .


Last update:Jan 30, 2024 at 20:33:16