Articles | Volume 15, issue 5
https://doi.org/10.5194/essd-15-1911-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-15-1911-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
09 May 2023
Data description paper |
| 09 May 2023
| 09 May 2023
An adapted hourly Himawari-8 fire product for China: principle, methodology and verification
Jie Chen
Key Laboratory of Radiometric Calibration and Validation for
Environmental Satellites, National Satellite Meteorological Center (National
Center for Space Weather), China Meteorological Administration and
Innovation Center for FengYun Meteorological Satellite (FYSIC), Beijing
100081, China
Qiancheng Lv
College of Global Change and Earth System Science, Beijing Normal
University, Beijing 100091, China
Shuang Wu
Heilongjiang Eco-Meteorology Center, Harbin, Heilongjiang 150030,
China
Yelu Zeng
College of Land Science and Technology, China Agricultural University,
Beijing 100083, China
Manchun Li
School of Geography and Ocean Science, Nanjing University, Nanjing
210023, China
Ziyue Chen
CORRESPONDING AUTHOR
College of Global Change and Earth System Science, Beijing Normal
University, Beijing 100091, China
Enze Zhou
Electric Power Research Institute, Guangdong Power Grid, Guangzhou,
Guangdong 510000, China
Wei Zheng
Key Laboratory of Radiometric Calibration and Validation for
Environmental Satellites, National Satellite Meteorological Center (National
Center for Space Weather), China Meteorological Administration and
Innovation Center for FengYun Meteorological Satellite (FYSIC), Beijing
100081, China
Cheng Liu
College of Global Change and Earth System Science, Beijing Normal
University, Beijing 100091, China
Xiao Chen
College of Global Change and Earth System Science, Beijing Normal
University, Beijing 100091, China
Jing Yang
College of Global Change and Earth System Science, Beijing Normal
University, Beijing 100091, China
Bingbo Gao
CORRESPONDING AUTHOR
College of Land Science and Technology, China Agricultural University,
Beijing 100083, China
Related authors
Yang Liu, Jie Chen, Yusheng Shi, Wei Zheng, Tianchan Shan, and Gang Wang
Earth Syst. Sci. Data, 16, 3495–3515, https://doi.org/10.5194/essd-16-3495-2024, https://doi.org/10.5194/essd-16-3495-2024, 2024
Short summary
Short summary
Open biomass burning has a significant impact on regional and global air quality. To enhance the quantification of global emissions from open biomass burning, we have developed the Global Emissions Inventory from Open Biomass Burning (GEIOBB) dataset, which provides a global daily-scale database at 1 km resolution of multiple pollutant emissions. This database aids global-scale environmental analysis of biomass burning.
Jie Chen, Qi Yao, Ziyue Chen, Manchun Li, Zhaozhan Hao, Cheng Liu, Wei Zheng, Miaoqing Xu, Xiao Chen, Jing Yang, Qiancheng Lv, and Bingbo Gao
Earth Syst. Sci. Data, 14, 3489–3508, https://doi.org/10.5194/essd-14-3489-2022, https://doi.org/10.5194/essd-14-3489-2022, 2022
Short summary
Short summary
The potential degradation of mainstream global fire products leads to large uncertainty in the effective monitoring of wildfires and their influence. To fill this gap, we produced a Fengyun-3D (FY-3D) global active fire product with a similar spatial and temporal resolution to MODIS fire products, aiming to serve as continuity and a replacement for MODIS fire products. The FY-3D fire product is an ideal tool for global fire monitoring and can be preferably employed for fire monitoring in China.
Yang Liu, Jie Chen, Yusheng Shi, Wei Zheng, Tianchan Shan, and Gang Wang
Earth Syst. Sci. Data, 16, 3495–3515, https://doi.org/10.5194/essd-16-3495-2024, https://doi.org/10.5194/essd-16-3495-2024, 2024
Short summary
Short summary
Open biomass burning has a significant impact on regional and global air quality. To enhance the quantification of global emissions from open biomass burning, we have developed the Global Emissions Inventory from Open Biomass Burning (GEIOBB) dataset, which provides a global daily-scale database at 1 km resolution of multiple pollutant emissions. This database aids global-scale environmental analysis of biomass burning.
Miaoqing Xu, Jing Yang, Manchun Li, Xiao Chen, Qiancheng Lv, Qi Yao, Bingbo Gao, and Ziyue Chen
Atmos. Chem. Phys., 23, 14065–14076, https://doi.org/10.5194/acp-23-14065-2023, https://doi.org/10.5194/acp-23-14065-2023, 2023
Short summary
Short summary
Although the temporal-scale effects on PM2.5–meteorology associations have been discussed, no quantitative evidence has proved this before. Based on rare 3 h meteorology data, we revealed that the dominant meteorological factor for PM2.5 concentrations across China extracted at the 3 h and 24 h scales presented large variations. This research suggests that data sources of different temporal scales should be comprehensively considered for better attribution and prevention of airborne pollution.
Jie Chen, Qi Yao, Ziyue Chen, Manchun Li, Zhaozhan Hao, Cheng Liu, Wei Zheng, Miaoqing Xu, Xiao Chen, Jing Yang, Qiancheng Lv, and Bingbo Gao
Earth Syst. Sci. Data, 14, 3489–3508, https://doi.org/10.5194/essd-14-3489-2022, https://doi.org/10.5194/essd-14-3489-2022, 2022
Short summary
Short summary
The potential degradation of mainstream global fire products leads to large uncertainty in the effective monitoring of wildfires and their influence. To fill this gap, we produced a Fengyun-3D (FY-3D) global active fire product with a similar spatial and temporal resolution to MODIS fire products, aiming to serve as continuity and a replacement for MODIS fire products. The FY-3D fire product is an ideal tool for global fire monitoring and can be preferably employed for fire monitoring in China.
Ruiyuan Li, Miaoqing Xu, Manchun Li, Ziyue Chen, Na Zhao, Bingbo Gao, and Qi Yao
Atmos. Chem. Phys., 21, 15631–15646, https://doi.org/10.5194/acp-21-15631-2021, https://doi.org/10.5194/acp-21-15631-2021, 2021
Short summary
Short summary
We employed ground observations of ozone and satellite products of HCHO and NO2 to investigate spatiotemporal variations of ozone formation regimes across China. Two different models were employed for determining the crucial thresholds that separate three ozone formation regimes, including NOx-limited, VOC-limited, and transitional regimes. The close output from two different models provides a reliable reference for better understanding ozone formation regimes.
Ziyue Chen, Danlu Chen, Mei-Po Kwan, Bin Chen, Bingbo Gao, Yan Zhuang, Ruiyuan Li, and Bing Xu
Atmos. Chem. Phys., 19, 13519–13533, https://doi.org/10.5194/acp-19-13519-2019, https://doi.org/10.5194/acp-19-13519-2019, 2019
Short summary
Short summary
We employed Kolmogorov–Zurbenko filtering and WRF-CMAQ to quantify the relative contribution of meteorological variations and emission reduction to PM2.5 reduction in Beijing from 2013 to 2017, which is crucial to evaluate the Five-year Clean Air Action Plan. Both models suggested that despite favourable meteorological conditions, the control of anthropogenic emissions accounted for around 80 % of PM2.5 reduction in Beijing. Therefore, such a long-term clean air plan should be continued.
Ziyue Chen, Danlu Chen, Wei Wen, Yan Zhuang, Mei-Po Kwan, Bin Chen, Bo Zhao, Lin Yang, Bingbo Gao, Ruiyuan Li, and Bing Xu
Atmos. Chem. Phys., 19, 6879–6891, https://doi.org/10.5194/acp-19-6879-2019, https://doi.org/10.5194/acp-19-6879-2019, 2019
Short summary
Short summary
This research is the first attempt to comprehensively evaluate the recent
2+26strategy for air quality improvement in Beijing. We additionally considered two corresponding pollution episodes with different emission-reduction strategies to comprehensively understand the effects of
2+26strategy. The findings suggested that red alerts be employed in heavy pollution episodes to intentionally reduce vehicle exhaust, which has become the dominant source for high PM2.5 concentrations in Beijing.
Ziyue Chen, Xiaoming Xie, Jun Cai, Danlu Chen, Bingbo Gao, Bin He, Nianliang Cheng, and Bing Xu
Atmos. Chem. Phys., 18, 5343–5358, https://doi.org/10.5194/acp-18-5343-2018, https://doi.org/10.5194/acp-18-5343-2018, 2018
Short summary
Short summary
With an advanced causality analysis method CCM, we quantified the influence of individual meteorological factors on PM2.5 concentrations and revealed notable spatial and temporal variations of meteorological influences on PM2.5 concentrations across China. Temperature, humidity and wind exert the strongest influences on PM2.5 concentrations in most cities across China. Given the notable spatial variations, meteorological means for reducing PM2.5 concentrations should be designed accordingly.
Related subject area
Domain: ESSD – Land | Subject: Energy and Emissions
Meteorological, snow and soil data, CO2, water and energy fluxes from a low-Arctic valley of Northern Quebec
Systematically tracking the hourly progression of large wildfires using GOES satellite observations
GloCAB: global cropland burned area from mid-2002 to 2020
Greenhouse gas emissions and their trends over the last 3 decades across Africa
A coarse pixel-scale ground “truth” dataset based on global in situ site measurements to support validation and bias correction of satellite surface albedo products
Multi-decadal trends and variability in burned area from the fifth version of the Global Fire Emissions Database (GFED5)
Developing a spatially explicit global oil and gas infrastructure database for characterizing methane emission sources at high resolution
A GeoNEX-based high-spatiotemporal-resolution product of land surface downward shortwave radiation and photosynthetically active radiation
Mapping photovoltaic power plants in China using Landsat, random forest, and Google Earth Engine
Florent Domine, Denis Sarrazin, Daniel F. Nadeau, Georg Lackner, and Maria Belke-Brea
Earth Syst. Sci. Data, 16, 1523–1541, https://doi.org/10.5194/essd-16-1523-2024, https://doi.org/10.5194/essd-16-1523-2024, 2024
Short summary
Short summary
The forest–tundra ecotone is the transition region between the boreal forest and Arctic tundra. It spans over 13 000 km across the Arctic and is evolving rapidly because of climate change. We provide extensive data sets of two sites 850 m apart, one in tundra and one in forest in this ecotone for use in various models. Data include meteorological and flux data and unique snow and soil physics data.
Tianjia Liu, James T. Randerson, Yang Chen, Douglas C. Morton, Elizabeth B. Wiggins, Padhraic Smyth, Efi Foufoula-Georgiou, Roy Nadler, and Omer Nevo
Earth Syst. Sci. Data, 16, 1395–1424, https://doi.org/10.5194/essd-16-1395-2024, https://doi.org/10.5194/essd-16-1395-2024, 2024
Short summary
Short summary
To improve our understanding of extreme wildfire behavior, we use geostationary satellite data to develop the GOFER algorithm and track the hourly fire progression of large wildfires. GOFER fills a key temporal gap present in other fire tracking products that rely on low-Earth-orbit imagery and reveals considerable variability in fire spread rates on diurnal timescales. We create a product of hourly fire perimeters, active-fire lines, and fire spread rates for 28 fires in California.
Joanne V. Hall, Fernanda Argueta, Maria Zubkova, Yang Chen, James T. Randerson, and Louis Giglio
Earth Syst. Sci. Data, 16, 867–885, https://doi.org/10.5194/essd-16-867-2024, https://doi.org/10.5194/essd-16-867-2024, 2024
Short summary
Short summary
Crop-residue burning is a widespread practice often occurring close to population centers. Its recurrent nature requires accurate mapping of the area burned – a key input into air quality models. Unlike larger fires, crop fires require a specific burned area (BA) methodology, which to date has been ignored in global BA datasets. Our global cropland-focused BA product found a significant increase in global cropland BA (81 Mha annual average) compared to the widely used MCD64A1 (32 Mha).
Mounia Mostefaoui, Philippe Ciais, Matthew J. McGrath, Philippe Peylin, Prabir K. Patra, and Yolandi Ernst
Earth Syst. Sci. Data, 16, 245–275, https://doi.org/10.5194/essd-16-245-2024, https://doi.org/10.5194/essd-16-245-2024, 2024
Short summary
Short summary
Our aim is to assess African anthropogenic greenhouse gas emissions and removals by using different data products, including inventories and process-based models, and to compare their relative merits with inversion data coming from satellites. We show a good match among the various estimates in terms of overall trends at a regional level and on a decadal basis, but large differences exist even among similar data types, which is a limit to the possibility of verification of country-reported data.
Fei Pan, Xiaodan Wu, Qicheng Zeng, Rongqi Tang, Jingping Wang, Xingwen Lin, Dongqin You, Jianguang Wen, and Qing Xiao
Earth Syst. Sci. Data, 16, 161–176, https://doi.org/10.5194/essd-16-161-2024, https://doi.org/10.5194/essd-16-161-2024, 2024
Short summary
Short summary
To effectively tackle the challenges posed by spatial-scale differences and spatial heterogeneity, this paper presents a distinctive coarse pixel-scale ground “truth" dataset by upscaling sparsely distributed in situ measurements. This dataset is a valuable resource for validating and correcting global surface albedo products, enhancing reference data accuracy by 6.04 %. Remarkably, it substantially enhances 17.09 % in regions with strong spatial heterogeneity.
Yang Chen, Joanne Hall, Dave van Wees, Niels Andela, Stijn Hantson, Louis Giglio, Guido R. van der Werf, Douglas C. Morton, and James T. Randerson
Earth Syst. Sci. Data, 15, 5227–5259, https://doi.org/10.5194/essd-15-5227-2023, https://doi.org/10.5194/essd-15-5227-2023, 2023
Short summary
Short summary
Using multiple sets of remotely sensed data, we created a dataset of monthly global burned area from 1997 to 2020. The estimated annual global burned area is 774 million hectares, significantly higher than previous estimates. Burned area declined by 1.21% per year due to extensive fire loss in savanna, grassland, and cropland ecosystems. This study enhances our understanding of the impact of fire on the carbon cycle and climate system, and may improve the predictions of future fire changes.
Mark Omara, Ritesh Gautam, Madeleine A. O'Brien, Anthony Himmelberger, Alex Franco, Kelsey Meisenhelder, Grace Hauser, David R. Lyon, Apisada Chulakadabba, Christopher Chan Miller, Jonathan Franklin, Steven C. Wofsy, and Steven P. Hamburg
Earth Syst. Sci. Data, 15, 3761–3790, https://doi.org/10.5194/essd-15-3761-2023, https://doi.org/10.5194/essd-15-3761-2023, 2023
Short summary
Short summary
We acquire, integrate, and analyze ~ 6 million geospatial oil and gas infrastructure data records based on information available in the public domain and develop an open-access global database including all the major oil and gas facility types that are important sources of methane emissions. This work helps fulfill a crucial geospatial data need, in support of the assessment, attribution, and mitigation of global oil and gas methane emissions at high resolution.
Ruohan Li, Dongdong Wang, Weile Wang, and Ramakrishna Nemani
Earth Syst. Sci. Data, 15, 1419–1436, https://doi.org/10.5194/essd-15-1419-2023, https://doi.org/10.5194/essd-15-1419-2023, 2023
Short summary
Short summary
There has been an increasing need for high-spatiotemporal-resolution surface downward shortwave radiation (DSR) and photosynthetically active radiation (PAR) data for ecological, hydrological, carbon, and solar photovoltaic research. This study produced a new 1 km hourly product of land surface DSR and PAR from the enhanced GeoNEX new-generation geostationary data. Our validation indicated that the GeoNEX DSR and PAR product has a higher accuracy than other existing products.
Xunhe Zhang, Ming Xu, Shujian Wang, Yongkai Huang, and Zunyi Xie
Earth Syst. Sci. Data, 14, 3743–3755, https://doi.org/10.5194/essd-14-3743-2022, https://doi.org/10.5194/essd-14-3743-2022, 2022
Short summary
Short summary
Photovoltaic (PV) power plants have been increasingly built across the world to mitigate climate change. A map of the PV power plants is important for policy management and environmental assessment. We established a map of PV power plants in China by 2020, covering a total area of 2917 km2. Based on the derived map, we found that most PV power plants were situated on cropland. In addition, the installation of PV power plants has generally decreased the vegetation cover.
Cited articles
Abram, N. J., Henley, B. J., Sen Gupta, A., Lippmann, T. J., Clarke, H., Dowdy,
A. J., Sharples, J. J., Nolan, R. H., Zhang, T., and Wooster, M. J.: Connections
of climate change and variability to large and extreme forest fires in
southeast Australia, Commun. Earth Environ., 2, 1–17,
https://doi.org/10.1038/s43247-020-00065-8, 2021.
Andela, N., Morton, D. C., Giglio, L., Chen, Y., van der Werf, G. R.,
Kasibhatla, P. S., DeFries, R. S., Collatz, G. J., Hantson, S., Kloster, S.,
Bachelet, D., Forrest, M., Lasslop, G., Li, F., Mangeon, S., Melton, J. R.,
Yue, C., and Randerson, J. T.: A human-driven decline in global burned area,
Science, 356, 1356–1362, https://doi.org/10.1126/science.aal4108, 2017.
Andersen, A. N., Cook, G. D., Corbett, L. K., Douglas, M. M., Eager, R. W.,
Russell-Smith, J., Setterfield, S. A., Williams, R. J., and Woinarski, J. C.: Fire
frequency and biodiversity conservation in Australian tropical savannas:
implications from the Kapalga fire experiment, Austral Ecol., 30, 155–167,
https://doi.org/10.1111/j.1442-9993.2005.01441.x, 2005.
Angassa, A. and Oba, G.: Herder perceptions on impacts of range enclosures,
crop farming, fire ban and bush encroachment on the rangelands of Borana,
Southern Ethiopia, Human Ecol., 36, 201–215,
https://doi.org/10.1007/s10745-007-9156-z, 2008.
Arino, O., Casadio, S., and Serpe, D.: Global night-time fire season timing
and fire count trends using the ATSR instrument series, Remote Sens., 116,
226–238, https://doi.org/10.1016/j.rse.2011.05.025, 2012.
Balch, J. K., Bradley, B. A., D'Antonio, C. M., and Gómez-Dans, J.:
Introduced annual grass increases regional fire activity across the arid
western USA (1980–2009), Glob. Chang. Biol., 19, 173–183,
https://doi.org/10.1111/gcb.12046, 2013.
Bessho, K., Date, K., Hayashi, M., Ikeda, A., Imai, T., Inoue, H., Kumagai,
Y., Miyakawa, T., Murata, H., and Ohno, T.: An introduction to
Himawari-8/9 – Japan's new-generation geostationary meteorological
satellites, J. Meteorol. Soc. Japan, Ser. II, 94, 151–183,
https://doi.org/10.2151/jmsj.2016-009, 2016.
Cascio, W. E.: Wildland fire smoke and human health, Sci. Total Environ.,
624, 586–595, https://doi.org/10.1016/j.scitotenv.2017.12.086, 2018.
Chen, J., Lv, Q., Wu, S., Zeng, Y., Li, M., Chen, Z., Zhou, E., Zheng, W.,
Chen, X., Yang, J., and Gao, B.: NSMC-Himawari-8 fire product for China,
figshare [data set], https://doi.org/10.6084/m9.figshare.21550248, 2022a.
Chen, J., Yao, Q., Chen, Z., Li, M., Hao, Z., Liu, C., Zheng, W., Xu, M., Chen, X., Yang, J., Lv, Q., and Gao, B.: The Fengyun-3D (FY-3D) global active fire product: principle, methodology and validation, Earth Syst. Sci. Data, 14, 3489–3508, https://doi.org/10.5194/essd-14-3489-2022, 2022b.
Chen, J., Zheng, W., Wu, S., Liu, C., and Yan, H.: Fire Monitoring Algorithm
and Its Application on the Geo-Kompsat-2A Geostationary Meteorological
Satellite, Remote Sens., 14, 2655, https://doi.org/10.3390/rs14112655,
2022c.
Csiszar, I. A., Morisette, J. T., and Giglio, L.: Validation of active fire
detection from moderate-resolution satellite sensors: the MODIS example in
northern Eurasia, IEEE T. Geosci. Remote, 44, 1757–1764,
https://doi.org/10.1109/TGRS.2006.875941, 2006.
Cui, X., Alam, M. A., Perry, G. L., Paterson, A. M., Wyse, S. V., and
Curran, T. J.: Green firebreaks as a management tool for wildfires: Lessons
from China, J. Environ. Manage., 233, 329–336,
https://doi.org/10.1016/j.jenvman.2018.12.043, 2019.
Driscoll, D. A., Lindenmayer, D. B., Bennett, A. F., Bode, M., Bradstock, R. A.,
Cary, G. J., Clarke, M. F., Dexter, N., Fensham, R., and Friend, G.: Fire
management for biodiversity conservation: key research questions and our
capacity to answer them, Biol. Conserv., 143, 1928–1939,
https://doi.org/10.1016/j.biocon.2010.05.026, 2010.
Earl, N. and Simmonds, I.: Spatial and temporal variability and trends in
2001–2016 global fire activity, J. Geophys. Res.-Atmos., 123, 2524–2536,
https://doi.org/10.1002/2017JD027749, 2018.
ESA: A Global Plant Functional Types (PFT) dataset (v2.0.8) 2019–2020, ESA [data set], http://maps.elie.ucl.ac.be/CCI/viewer/download.php, last access: 5 May 2023.
Freeborn, P. H., Wooster, M. J., and Roberts, G.: Addressing the
spatiotemporal sampling design of MODIS to provide estimates of the fire
radiative energy emitted from Africa, Remote Sens. Environ., 115, 475–489,
https://doi.org/10.1016/j.rse.2010.09.017, 2011.
Fuller, D. O. and Fulk, M.: Comparison of noaa-avhrr and DMSP-OLS for
operational fire monitoring in kalimantan, Indonesia. Int. J. Remote Sens.,
21, 181–187, https://doi.org/10.1080/014311600211073, 2000.
Giglio, L., Csiszar, I., Justice, C. O.: Global distribution and seasonality
of active fires as observed with the Terra and Aqua Moderate Resolution
Imaging Spectroradiometer (MODIS) sensors, J. Geophys. Res.-Biogeo., 111,
G02016, https://doi.org/10.1029/2005JG000142, 2006.
Giglio, L., Boschetti, L., Roy, D. P., Humber, M. L., and Justice, C. O.:
The Collection 6 MODIS burned area mapping algorithm and product, Remote
Sens. Environ., 217, 72–85, https://doi.org/10.1016/j.rse.2018.08.005, 2018.
Hall, J. V., Zhang, R., Schroeder, W., Huang, C., and Giglio, L.: Validation
of GOES-16 ABI and MSG SEVIRI active fire products. Int. J. Appl. Earth
Obs. Geoinf., 83, 101928, https://doi.org/10.1016/j.jag.2019.101928, 2019.
Herold, M. and Roberts, D.: Spectral characteristics of asphalt road aging and
deterioration: implications for remote-sensing applications, Appl.
Optics, 44, 4327–4334, https://doi.org/10.1364/AO.44.004327, 2005.
Huang, X., Li, M., Li, J., and Song, Y.: A high-resolution emission
inventory of crop burning in fields in China based on MODIS Thermal
Anomalies/Fire products, Atmos. Environ., 50, 9–15,
https://doi.org/10.1016/j.atmosenv.2012.01.017, 2012.
Huff, A. K., Kondragunta, S., Zhang, H., and Hoff, R. M.: Monitoring the
impacts of wildfires on forest ecosystems and public health in the exo-urban
environment using high-resolution satellite aerosol products from the
visible infrared imaging radiometer suite (VIIRS), Environ. Health
Insights., 9s2, EHI.S19590, https://doi.org/10.4137/ehi.s19590, 2015.
Ichoku, C., Kahn, R., and Chin, M.: Satellite contributions to the
quantitative characterization of biomass burning for climate modeling,
Atmos. Res., 111, 1–28, https://doi.org/10.1016/j.atmosres.2012.03.007,
2012.
Jang, E., Kang, Y., Im, J., Lee, D. W., Yoon, J., and Kim, S. K.: Detection
and monitoring of forest fires using Himawari-8 geostationary satellite data
in South Korea, Remote Sens., 11, 271,
https://doi.org/10.3390/rs11030271, 2019.
Johnston, F. H., Henderson, S. B., Chen, Y., Randerson, J. T., Marlier, M.,
DeFries, R. S., Kinney, P., Bowman, D. M., and Brauer, M.: Estimated global
mortality attributable to smoke from landscape fires, Environ. Health
Perspect., 120, 695–701, https://doi.org/10.1289/ehp.1104422, 2012.
Justice, C., Giglio, L., Korontzi, S., Owens, J., Morisette, J., Roy, D.,
Descloitres, J., Alleaume, S., Petitcolin, F., and Kaufman, Y.: The MODIS
fire products, Remote Sens. Environ., 83, 244–262,
https://doi.org/10.1016/S0034-4257(02)00076-7, 2002.
Kuenzer, C. and Dech, S.: Theoretical background of thermal infrared remote
sensing, in: Thermal infrared remote sensing, Springer, Dordrecht, 1–26,
https://doi.org/10.1007/978-94-007-6639-6_1, 2013.
Li, F., Zhang, X., Roy, D. P., and Kondragunta, S.: Estimation of
biomass-burning emissions by fusing the fire radiative power retrievals from
polar-orbiting and geostationary satellites across the conterminous United
States, Atmos. Environ., 211, 274–287,
https://doi.org/10.1016/j.atmosenv.2019.05.017, 2019.
Li, J., Bo, Y., and Xie, S.: Estimating emissions from crop residue open
burning in China based on statistics and MODIS fire products, J. Environ.
Sci.-China, 44, 158–170, https://doi.org/10.1016/j.jes.2015.08.024, 2016.
Liu, J. C., Pereira, G., Uhl, S. A., Bravo, M. A., and Bell, M. L.: A
systematic review of the physical health impacts from non-occupational
exposure to wildfire smoke, Environ. Res., 136, 120–132,
https://doi.org/10.1016/j.envres.2014.10.015, 2015.
Liu, T., Marlier, M. E., DeFries, R. S., Westervelt, D. M., Xia, K. R., Fiore,
A. M., Mickley, L. J., Cusworth, D. H., and Milly, G.: Seasonal impact of
regional outdoor biomass burning on air pollution in three Indian cities:
Delhi, Bengaluru, and Pune, Atmos. Environ., 172, 83–92,
https://doi.org/10.1016/j.atmosenv.2017.10.024, 2018.
Liu, X., He, B., Quan, X., Yebra, M., Qiu, S., Yin, C., Liao, Z., and Zhang,
H.: Near real-time extracting wildfire spread rate from Himawari-8 satellite
data, Remote Sens., 10, 1654, https://doi.org/10.3390/rs10101654, 2018.
Liu, Z., Yang, J., Chang, Y., Weisberg, P. J., and He, H. S.: Spatial
patterns and drivers of fire occurrence and its future trend under climate
change in a boreal forest of Northeast China, Glob. Chang. Biol., 18,
2041–2056, https://doi.org/10.1111/j.1365-2486.2012.02649.x, 2012.
Marlier, M. E., DeFries, R. S., Kim, P. S., Koplitz, S. N., Jacob, D. J.,
Mickley, L. J., and Myers, S. S.: Fire emissions and regional air quality
impacts from fires in oil palm, timber, and logging concessions in
Indonesia, Environ. Res. Lett., 10, 085005,
https://doi.org/10.1088/1748-9326/10/8/085005, 2015.
Na, L., Zhang, J., Bao, Y., Bao, Y., Na, R., Tong, S., and Si, A.:
Himawari-8 satellite based dynamic monitoring of grassland fire in
China-Mongolia border regions, Sensors, 18, 276,
https://doi.org/10.3390/s18010276, 2018.
Niu, R. and Zhai, P.: Study on forest fire danger over Northern China during
the recent 50 years, Clim. Change, 111, 723–736,
https://doi.org/10.1007/s10584-011-0198-2, 2012.
NOAA: NOAA-20 Visible Infrared Imaging Radiometer Suite (VIIRS) 2019–2021, NOAA [data set], https://ncc.nesdis.noaa.gov/NOAA-20/NOAA20VIIRS.php, last access: 5 May 2023.
Panjaitan, R. B., Sumartono, S., Sarwono, S., and Saleh, C.: The role of
central government and local government and the moderating effect of good
governance on forest fire policy in Indonesia, Benchmarking: An
International Journal, 26, 147–159,
https://doi.org/10.1108/BIJ-12-2017-0336, 2019.
Quinn, T. J. and Martin, J. E.: A radiometric determination of the
Stefan-Boltzmann constant and thermodynamic temperatures between −40 ∘C and +100 ∘C, Philos. T. Roy. Soc. Lond. A, 316, 85–189,
https://doi.org/10.1098/rsta.1985.0058, 1985.
Reid, C. E., Brauer, M., Johnston, F. H., Jerrett, M., Balmes, J. R., and
Elliott, C. T.: Critical review of health impacts of wildfire smoke
exposure, Environ. Health Perspect., 124, 1334–1343,
https://doi.org/10.1289/ehp.1409277, 2016.
Röder, A., Hill, J., Duguy, B., Alloza, J. A., and Vallejo, R.: Using
long time series of Landsat data to monitor fire events and post-fire
dynamics and identify driving factors. A case study in the Ayora region
(eastern Spain), Remote Sens. Environ., 112, 259–273,
https://doi.org/10.1016/j.rse.2007.05.001, 2008.
Schmit, T. J., Griffith, P., Gunshor, M. M., Daniels, J. M., Goodman, S. J., and
Lebair, W. J.: A closer look at the ABI on the GOES-R series, B. Am.
Meteorol. Soc., 98, 681–698, https://doi.org/10.1175/bams-d-15-00230.1,
2017.
Schroeder, W., Csiszar, I., and Morisette, J.: Quantifying the impact of
cloud obscuration on remote sensing of active fires in the Brazilian Amazon,
Remote Sens. Environ., 112, 456–470,
https://doi.org/10.1016/j.rse.2007.05.004, 2008.
Schroeder, W., Oliva, P., Giglio, L., and Csiszar, I. A.: The New VIIRS 375
m active fire detection data product: Algorithm description and initial
assessment, Remote Sens. Environ., 143, 85–96,
https://doi.org/10.1016/j.rse.2013.12.008, 2014.
Sharma, A., Wang, J., and Lennartson, E. M.: Intercomparison of MODIS and VIIRS
fire products in Khanty-Mansiysk Russia: Implications for characterizing gas
flaring from space, Atmosphere, 8, 95,
https://doi.org/10.3390/atmos8060095, 2017.
Song, R., Wang, T., Han, J., Xu, B., Ma, D., Zhang, M., Li, S., Zhuang, B.,
Li, M., and Xie, M.: Spatial and temporal variation of air pollutant
emissions from forest fires in China, Atmos. Environ., 281, 119156,
https://doi.org/10.1016/j.atmosenv.2022.119156, 2022.
Tiedemann, A. R., Klemmedson, J. O., and Bull, E. L.: Solution of forest health
problems with prescribed fire: are forest productivity and wildlife at risk,
For. Ecol. Manag., 127, 1–18, https://doi.org/10.1016/S0378-1127(99)00114-0,
2000.
Wang, J., Bhattacharjee, P. S., Tallapragada, V., Lu, C.-H., Kondragunta, S., da Silva, A., Zhang, X., Chen, S.-P., Wei, S.-W., Darmenov, A. S., McQueen, J., Lee, P., Koner, P., and Harris, A.: The implementation of NEMS GFS Aerosol Component (NGAC) Version 2.0 for global multispecies forecasting at NOAA/NCEP – Part 1: Model descriptions, Geosci. Model Dev., 11, 2315–2332, https://doi.org/10.5194/gmd-11-2315-2018, 2018.
Wang, X., Min, M., Wang, F., Guo, J., Li, B., and Tang, S.: Intercomparisons
of cloud mask products among Fengyun-4A, Himawari-8, and MODIS, IEEE
T. Geosci. Remote, 57, 8827–8839,
https://doi.org/10.1109/TGRS.2019.2923247, 2019.
Wickramasinghe, C. H., Jones, S., Reinke, K., and Wallace, L.: Development
of a multi-spatial resolution approach to the surveillance of active fire
lines using Himawari-8, Remote Sens., 8, 932, https://doi.org/10.3390/rs8110932, 2016.
Wu, Z., He, H. S., Yang, J., Liu, Z., and Liang, Y.: Relative effects of
climatic and local factors on fire occurrence in boreal forest landscapes of
northeastern China, Sci. Total Environ., 493, 472–480,
https://doi.org/10.1016/j.scitotenv.2014.06.011, 2014.
Xu, G. and Zhong, X.: Real-time wildfire detection and tracking in
Australia using geostationary satellite: Himawari-8, Remote Sens. Lett.,
8, 1052–1061, https://doi.org/10.1080/2150704X.2017.1350303, 2017.
Xu, W., Wooster, M. J., Kaneko, T., He, J., Zhang, T., and Fisher, D.: Major
advances in geostationary fire radiative power (FRP) retrieval over Asia and
Australia stemming from use of Himarawi-8 AHI, Remote Sens. Environ., 193,
138–149, https://doi.org/10.1016/j.rse.2017.02.024, 2017.
Yang, Z., Zhang, P., Gu, S., Hu, X., Tang, S., Yang, L., Xu, N., Zhen, Z.,
Wang, L., and Wu, Q.: Capability of Fengyun-3D satellite in earth system
observation, J. Meteorol. Res., 33, 1113–1130,
https://doi.org/10.1007/s13351-019-9063-4, 2019.
Yang, Z.-Y., Ishii, S., Yokoyama, T., Dao, T.D., Sun, M.-G., Pankin, P.S.,
Timofeev, I.V., Nagao, T., and Chen, K.-P.: Narrowband wavelength selective
thermal emitters by confined tamm plasmon polaritons, Acs Photonics, 4,
2212–2219, https://doi.org/10.1021/acsphotonics.7b00408, 2017.
Ying, L., Han, J., Du, Y., and Shen, Z.: Forest fire characteristics in
China: Spatial patterns and determinants with thresholds, For. Ecol. Manag.,
424, 345–354, https://doi.org/10.1016/j.foreco.2018.05.020, 2018.
Yuan, J., Wang, D., and Li, R.: Remote sensing image segmentation by
combining spectral and texture features, IEEE T. Geosci. Remote,
52, 16–24, https://doi.org/10.1109/TGRS.2012.2234755, 2014.
Zackrisson, O.: Influence of forest fires on the North Swedish boreal
forest, Oikos, 29, 22–32, https://doi.org/10.2307/3543289, 2013, 1977.
Zhang, X. and Kondragunta, S.: Temporal and spatial variability in biomass
burned areas across the USA derived from the GOES fire product, Remote Sens.
Environ., 112, 2886–2897, https://doi.org/10.1016/j.rse.2008.02.006,
2008.
Short summary
The Himawari-8 fire product is the mainstream fire product with the highest temporal resolution, yet it presents large uncertainties and is not suitable for reliable real-time fire monitoring in China. To address this issue, we proposed an adaptive hourly NSMC (National Satellite Meteorological Center) Himawari-8 fire product for China; the overall accuracy increased from 54 % (original Himawari product) to 80 %. This product can largely enhance real-time fire monitoring and relevant research.
The Himawari-8 fire product is the mainstream fire product with the highest temporal resolution,...
Altmetrics
Final-revised paper
Preprint