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.H.[Yuan-Hui],
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.F.[Xu-Feng],
Jiao, W.G.[Wan-Guo],
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.J.[Huan-Jie],
Duan, Q.Y.[Qian-Yue],
Lu, M.H.[Ming-Hao],
Hu, Z.W.[Zhen-Wu],
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
Damiano, R.[Riccardo],
Amoruso, S.[Salvatore],
Sannino, A.[Alessia],
Boselli, A.[Antonella],
Lidar Optical and Microphysical Characterization of Tropospheric and
Stratospheric Fire Smoke Layers Due to Canadian Wildfires Passing
over Naples (Italy),
RS(16), No. 3, 2024, pp. 538.
DOI Link
2402
BibRef
Sowden, M.[Miles],
Hanigan, I.C.[Ivan C.],
Robbins, D.J.V.[Daniel Jamie Victor],
Cope, M.[Martin],
Silver, J.D.[Jeremy D.],
Noonan, J.[Julie],
Characterizing Smoke Haze Events in Australia Using a Hybrid Approach
of Satellite-Based Aerosol Optical Depth and Chemical Transport
Modeling,
RS(16), No. 7, 2024, pp. 1266.
DOI Link
2404
BibRef
Mulena, G.C.[Gabriela Celeste],
Asmi, E.M.[Eija Maria],
Ruiz, J.J.[Juan José],
Pallotta, J.V.[Juan Vicente],
Jin, Y.[Yoshitaka],
Biomass Burning Aerosol Observations and Transport over Northern and
Central Argentina: A Case Study,
RS(16), No. 10, 2024, pp. 1780.
DOI Link
2405
BibRef
Yang, M.[Ming],
Qian, S.[Songrong],
Wu, X.Q.[Xiao-Qin],
Real-time fire and smoke detection with transfer learning based on
cloud-edge collaborative architecture,
IET-IPR(18), No. 12, 2024, pp. 3716-3728.
DOI Link
2411
cloud computing, edge detection, fires, image enhancement,
image recognition, smoke
BibRef
Liu, Y.[Yang],
Chen, F.[Faying],
Zhang, C.C.[Chang-Chun],
Wang, Y.[Yuan],
Zhang, J.[Junguo],
Early Wildfire Smoke Detection Method Based on EDA,
RS(16), No. 24, 2024, pp. 4684.
DOI Link
2501
BibRef
Chapter on Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR continues in
Forest Fire Prediction, Fire Hazard, Mitigation, Risk, Susceptibility .