The first polar-orbiting meteorological satellite FY-1A was launched in 1988. Since then, China has developed 4 series of FY meteorological satellites and successfully launched 19 such satellites, including 9 polar-orbiting and 10 geostationary (Table 1). At present, totally eight FY meteorological satellites operate in orbit, including three FY-2, three FY-3, and two FY-4, which have formed an observation network with both polar-orbiting and geostationary meteorological satellites. FY-2 is the first-generation geostationary meteorological satellite; FY-2H, FY-2G, and FY-2F are operating at 79°, 99.5°, and 112°E above the equator, respectively. FY-4 is the second-generation geostationary meteorological satellite; FY-4A has advanced earth observation capabilities and provides better temporal resolution than the FY-2 series. FY-3 is the second-generation polar-orbiting meteorological satellite. Compared with the first-generation polar-orbiting satellite, FY-3 series has more than 10 instruments and provides higher resolution data with more spectral coverage from the ultraviolet, visible, infrared, to microwave bands (Xian et al., 2021).
Satellite Launch time Type Design life Status FY-1A 1988-09-07 Experiment 2 yr 39 days FY-1B 1990-09-03 Experiment 2 yr 158 days FY-1C 1999-05-10 Operation 2 yr 6.5 yr FY-1D 2002-05-15 Operation 2 yr 10 yr FY-3A 2008-05-27 Experiment 3 yr 10 yr FY-3B 2010-11-05 Experiment 3 yr 10 yr FY-3C 2013-09-23 Operation 5 yr In orbit service FY-3D 2017-11-15 Operation 5 yr In orbit service FY-3E 2021-07-15 Operation 8 yr In orbit test FY-2A 1997-06-10 Experiment 2 yr 10 months FY-2B 2000-06-25 Experiment 2 yr 8 months FY-2C 2004-10-19 Operation 3 yr 8.5 yr FY-2D 2006-12-08 Operation 3 yr 10 yr FY-2E 2008-12-23 Operation 3 yr 10 yr FY-2F 2012-01-13 Operation 4 yr In orbit service FY-2G 2014-12-31 Operation 4 yr In orbit service FY-2H 2018-06-05 Operation 4 yr In orbit service FY-4A 2016-12-11 Experiment 7 yr In orbit service FY-4B 2021-06-03 Operation 7 yr In orbit test
Table 1. Information on the Fengyun (FY) series of meteorological satellites (the names of those satellites currently in orbit are italicized)
The capability of earth system monitoring was greatly enhanced after the second-generation polar-orbiting FY-3 satellites and the geostationary FY-4 satellites were launched. Meanwhile, the quality of the products generated from FY-3 and FY-4 is comparable to that of the Moderate Resolution Imaging Spectroradiometer (MO-DIS) products. At present, more than 100 products are derived from FY polar-orbiting and geostationary meteorological satellite data and released to the public (Table 2). The FY meteorological satellites have contributed to earth science and sustainability studies through an open data policy and stable product quality. FY satellite data have been utilized extensively in weather forecasting, climate prediction, climate change study; monitoring of environmental disaster, agriculture, and ecological environment, “Belt and Road” service, and so on.
Product type Polar-orbiting satellite Geostationary satellite Cloud and
Albedo, cloud mask, cloud amount, cloud phase, cloud type, cloud top temperature, cloud top height, cloud optical depth, cloud effective radius, outgoing longwave radiation, surface upward longwave radiation Cloud optical depth, cloud phase, cloud top height, cloud top pressure, cloud top temperature, cloud type, downward longwave radiation, surface outgoing longwave radiation, surface reflected shortwave radiation, top of atmosphere reflectance, surface solar irradiance Atmosphere Aerosol optical depth, fog detection, precipitation, perceptible water, dust storm index, atmospheric total cloud liquid water, microwave rainfall rate, rain detection, vertical temperature profile, vertical humidity profile, total ozone, vertical ozone profile, ultraviolet aerosol index, atmospheric density profile Aerosol optical depth, atmospheric correction image, atmospheric motion wind vector, convective initiation, fog detection, dust detection, total column precipitable water, vertical moisture profile, vertical temperature profile, lightning detection, liquid water profile, rainfall rate, tropopause folding, lightning density, lightning frequency Land and
Fire detection, land cover, albedo, normalized difference vegetation index, land surface temperature, leaf area index, evapotranspiration, fraction of photosynthetically active radiation, net primary productivity, soil moisture, drought index Fire/hot spot, land surface temperature, land surface emissivity, dust storm index, fog detection, dust detection, rainfall rate, evapotranspiration, aerosol optical depth over land surface Cryosphere Sea ice, snow cover, snow depth, snow water equivalent Ocean Sea surface temperature, sea surface wind speed, ocean color, water-leaving radiance Sea surface temperature, aerosol optical depth over ocean Space weather Energetic electrons, surface potential, radiation dose rate, solar X-ray image, solar extreme ultraviolet image, geomagnetic field, Global Navigation Satellite System Radio Occultation Sounder (GNOS) electron density profile, critical frequency of F2 layer (foF2), ionospheric total electron content (TEC), peak height of F2 layer, electron differential directional flux, proton differential directional flux, airglow Energetic electrons, energetic proton
Table 2. List of the remote sensing products from FY meteorological satellites
Since the beginning of the twentieth century, China has been using the FY satellite data to monitor the ecological environment. With the observation ability of FY meteorological satellites being improved significantly, application of the FY satellite data to ecological environment monitoring has undergone comprehensive and ra-pid development. A number of scientific algorithms for deriving the key parameters of ecological environment using the FY satellite data have been developed, and an integrated earth-observation system has been established, which is able to monitor the ecological environment in real time. The long time series datasets of ecological environment parameters based on the FY satellite observations have been developed and employed to evaluate the ecological environment change, the suitable place for human settlement, and the management and control of ecological conservation redline. Ecological environment monitoring systems at both national and provincial levels have been established, and the monitoring area has been extended to cover the whole globe, including the Belt and Road Initiative region. Prediction of ecological environment change based on the FY satellite data is also under development.
Support of ecological civilization construction by meteorological service is one of the two main responsibilities of meteorological departments in China, who have unique advantages in accessing satellite remote sensing data resources, accumulating remote sensing monitoring data for meteorological elements, and providing observations of meteorological elements sensitive to ecological environment change. Besides, considerable work has been carried out on exploitation and utilization of climate resources, monitoring and early warning of meteorological disasters affecting the ecology, as well as protection, restoration, and utilization of the ecosystem. In order to meet the new requirements of ecological civilization construction in China, operational meteorological service in support of ecological civilization and ecologi-cal monitoring and assessment has been widely developed through applications of FY meteorological satellite data, in the form of ecological meteorological service, such as prevention of air pollution, management and control of ecological redline, facilitating of the Belt and Road Initiative, and evaluation of natural oxygen distribution in China. The ecological meteorological service has applied the wisdom of meteorological science and technology to the ecological civilization construction.
Air pollution is the most serious problem for many countries in the world. Although the emission of air pollutants in China has been declining rapidly in recent years, the total amount is still high (Zhou, 2017). In ear-lier years, satellite remote sensing was used by meteorological departments of China to monitor the greenhouse gases, trace gases, and aerosols in the atmospheric environment, and relevant results were obtained (Wang et al., 2010; Yan et al., 2016; Tang et al., 2018). In recent years, remote sensing monitoring of PM2.5 concentrations near ground has become an effective method for regional atmospheric environment monitoring. This is a new technology developed rapidly and also a hot topic for environmental remote sensing research in the world. The PM2.5 concentrations near ground are usually estimated through the AOD retrieved from satellite remote sensing. Based on the AOD products from FY and other satellites combined with meteorological factors such as boundary layer height, relative humidity, temperature, and wind speed, as well as the factors such as population density and land-use type, the spatiotemporal changes of PM2.5 concentrations can be comprehensively analyzed. On this basis, the remote sensing-based estimate model of PM2.5 concentrations is constructed (Jia et al., 2013; Tao et al., 2013; Ma, 2015; Chen et al., 2019). FY-3, the second-generation polar-orbiting meteorological satellites of China, has greatly enhanced our capability in monitoring the atmospheric environment quality in China, providing a new remote sensing data source for the large-scale monitoring of aerosols and particulates in the atmosphere. Some studies (e.g., Chen et al., 2018) have proved the ability of the FY-3B/MERSI satellite data in monitoring the aerosols and PM2.5 concentrations near ground.
Meteorological service for the atmospheric environment has become a daily operation in Chinese meteorological departments, among which the satellite remote sensing technology provides strong technical support to the monitoring and control of air pollution. Based on the dynamic monitoring of the spatiotemporal distributions of national and regional AOD retrieved by FY satellite data, it is found that the AOD in China presents a declining trend in recent years (CMA, 2018). The retrieved AOD can be further used to monitor the spatial distribution and change process of atmospheric pollutants such as PM2.5 and PM10. Moreover, combined with meteorological observations and weather forecasts, the operational forecasting services for air quality and heavy pollution weather such as smog are carried out. Through FY satellites, the all-weather, continuous, and dynamic remote sensing monitoring of heavy pollution weather such as smog, sand, and dust has been realized (Xu, 2015; Qiu et al., 2018), and the monitoring of air pollution sources due to forest fire and straw burning has been basically realized in operation. In the future, the meteorological satellite observations, ground observations, and refined weather forecasts will be collectively utilized to improve the forecasting accuracy of heavy pollution weather such as smog. Analysis of the heavy pollution weather processes will be carried out to scientifically evaluate the contribution of meteorological conditions in the transition of air quality.
Demarcation and control of the ecological conservation redline (ECR) play a key role in the maintenance of national and regional ecological security and the sustainable development of China. ECR is a boundary imposed to prevent construction or other human activities within a specified area aimed at ecological protection of the area. ECR commits over one-fourth of China’s territory to varying degrees of protection for biodiversity, disaster mitigation and providing critical ecosystem services. This is an important measure to promote the ecological civilization construction and also an important innovation of the Chinese ecological environment protection policy (Yang et al., 2014). In China, ECR has a wide distribution with diverse topographic and geomorphic features as well as complex and changeable natural conditions. The demarcation, monitoring, and evaluation of ECR are based on the remote sensing data, including satellite remote sensing observations, aerial remote sensing observations, and ground observations (Wang et al., 2017; Han and Tang, 2018).
Real-time monitoring of the types and distributions of the ecosystem such as the mountain, lake, forest, farmland, and grassland within the region of ECR, and the closely related meteorological elements, has been carried out through mainly using the FY satellite data and other remote sensing data. Based on multisource data from FY meteorological satellites, GF series satellites, and meteorological observations, the NSMC has established remote sensing based ecological indices such as vegetation index, vegetation coverage, land-use type, NPP, and the biodiversity index, considering the physical meaning and mathematical model of ecological service function. Through principal component analysis of the weight coefficient of each index, the indices for ecological functions of wind-breaking and sand-fixing, biodiversity maintenance, soil and water conservation, and water resource conservation, as well as the index of rocky desertification sensitivity, have been proposed and investigated, respectively (Zhou et al., 2021). On this basis, an comprehensive evaluation model for eco-environmental conditions has been constructed, realizing the quantitative evaluation of ecological environment (Figs. 2, 3).
Figure 2. Distribution of the national eco-environmental condition in 2019; the higher (lower) the index (denoted by color shading, with color bar on the lower left of the figure), the better (worse) the ecological environment condition.
In view of the ecological function areas and ecologi-cal fragile areas within the range of ECR, the satellite remote sensing monitoring and meteorological service based on local demands are actively implemented in provincial meteorological departments, where special features and highlights are identified. For ecological fragile areas of rocky desertification in Guangxi Region of China, the ecological–meteorological integrated observation network is constructed and improved, and the collaborative monitoring as well as climatic assessment of rocky desertification based on satellite and surface meteorological observations is performed (Chen et al., 2021). In provinces in Northeast China such as Liaoning, for different types of wetlands such as lake, river, swamp, and artificial paddy fields, the observations from the polar-orbiting satellites including FY-3 are taken as the main data sources to establish the indicators for monitoring typical wetlands and an indicator model for evaluating the overall ecosystem environment in Northeast China (Yu et al., 2020). On this basis, dynamic monitoring and quantitative evaluation of wetlands in Northeast China by remote sensing are carried out, which provides scientific support to the protection, restoration, and reconstruction of wetlands as well as the improvement of the ecological environment in Northeast China. Nevertheless, the application of satellite remote sensing technology and meteorological service in the management and control of ECR still needs to be enhanced. From the aspects of ecosystem pattern, quality, and function, it is necessary to combine additional data sources and parame-ters such as environmental observations and ecosystem condition parameters, so as to provide basis to better management and decision-making associated with the practice of ECR.
The FY-3 polar-orbiting meteorological satellite series has a global observation ability and can provide informative, highly accurate, real-time, and dynamic monitoring. It is expected that more objective and accurate data can be obtained for monitoring and assessment of the ecological environment in the Belt and Road Initiative region. Multiscale and multisource satellite data are used to monitor the ecological environment of this region, such as the macro pattern of terrestrial ecosystem, condition of major vegetation ecosystem, terrestrial solar energy resources, terrestrial water budget, regional ecological constraints of main economic corridors, as well as the ecological environment associated with development of important node cities (Liu Y. H. et al., 2018). Through the land cover data retrieved by satellite remote sensing, combined with the social–economic data from the countries along the route, spatiotemporal dynamic variations of land cover along this route and related driving mechanism are analyzed (Fan and Li, 2019; Ge et al., 2019). Characteristics of regional climate, topography, soil, hydrology, vegetation cover, and terrestrial ecosystem are evaluated by an integrated application of remote sensing monitoring and statistical analysis (Wu et al., 2018).
The FY meteorological satellite series in China, together with the NOAA series in the United States and the polar-orbiting meteorological satellite (MetOp) series in Europe, has become an important space infrastructure used to construct earth’s operational observation system. The FY satellites have been incorporated into the global operational meteorological satellite network by the World Meteorological Organization (WMO), becoming an important member of the global integrated observation system (Xian et al., 2021). In addition, FY meteorological satellite is a duty satellite of the International Charter Space and Major Disasters to support disaster response worldwide. The losses caused by disasters in related countries and regions along the Belt and Road Initiative are more than twice the global average, among which the largest part of losses are caused by meteorological disasters. Timely and efficient observation of extreme weather, climate, and environmental events in the global or regional range along the Belt and Road Initiative can be realized by using FY meteorological satellites. The countries using FY satellite data have increased to 117, including 83 countries along the Belt and Road Initiative (Table 3). In order to make the FY meteorological satellites better serve the related countries and regions along the Belt and Road Initiative in disaster prevention and mitigation, the CMA has adjusted the layout of meteorological satellites to realize the full coverage of geostationary satellites of FY series over the whole territory of China, related countries and regions along the Belt and Road Initiative, the Indian Ocean, and most African countries. In addition, in 2018, CMA established an emergency support mechanism for international users of FY meteorological satellites in disaster prevention and mitigation (FY-ESM). When natural disasters happen in the countries along the Belt and Road Initiative, intensified observations can be provided based on the needs for monitoring of the disasters. By 2020, there have been 29 registered countries for the emergency support mechanism. Since January 2018, the support service of disaster prevention and mitigation for international users of FY meteorological satellites has been activated nearly 20 times due to meteorological disasters, including typhoon, heavy rainfall, sandstorm, flood, wildfire, volcanic eruption, and severe drought (Fig. 4). In order to satisfy the need for ecological environment monitoring of the Belt and Road Initiative by remote sensing, it is necessary to focus on the key elements, regions, and types of ecological environment in future. The application of FY meteorological satellite remote sensing to ecological environment monitoring should be expanded. The monitoring, early warning, and research on the ecological environment and disasters prevention related to climate and vegetation, as well as the severe flood, wildfire, and snow within the region of the Belt and Road Initiative should be enhanced, so as to achieve dynamic monitoring of the ecological environment elements in these regions.
Service Country Use of data service network Global users; 117 countries in total Direct-receiving of FY-2 data Mongolia, North Korea, Nepal, Thailand, French Reunion, Australia, Mozambique,
Kyrgyzstan, Oman (9 countries)
Direct-receiving of FY-3 data Zimbabwe, Namibia, Iran (3 countries) Use of FY-3 satellite software package The United States, Germany, Russia, the United Kingdom, Australia, Indonesia, South Korea, Brazil, Thailand, Norway, Oman, Finland, Canada, Malaysia, Bolivia, Poland, the Netherlands, Mongolia, Greece, United Arab Emirates, Belarus, Japan, Niger, Sweden, Vietnam, France, Ukraine, Spain, the Philippines (29 countries, 55 users) Use of CMACast (a system that uses satellite
Digital Video Broadcast technology to transmit meteorological data)
Bangladesh, Indonesia, the Maldives, Nepal, Mongolia, Malaysia, Pakistan, Thailand, the Philippines, Uzbekistan, Tajikistan, Kyrgyzstan, Laos, Sri Lanka, North Korea, Vietnam, Myanmar, Iran, Kazakhstan (19 countries) Use of emergency support mechanism of FY satellites (FY-ESM) Laos, Myanmar, Iran, the Maldives, Thailand, the Philippines, Algeria, Malaysia, Uzbekistan, Tunisia, Mongolia, Nepal, New Zealand, Oman, Mozambique, Kyrgyzstan, Lesotho, Nigeria, Ethiopia, Guinea, Benin, Mauritius, Ghana, Portugal, Malawi, Armenia, Sri Lanka, the Solomon Islands, Vanuatu (29 countries)
Table 3. Countries served by FY meteorological satellites by April 2021
Clean water, fresh air, secured food, and high-quality ecological products have become the expectation of people for a better life. More high-quality ecological products are needed to meet people’s ever-growing demands for a beautiful ecological environment. The gene-ral office of the State Council of China proposed that the integrated development of tourism with transportation, environmental protection, land, ocean, meteorology, and other industries be promoted, and the ecotourism area, natural oxygen zones, and meteorological parks be developed. It is necessary for meteorological departments of China to give a full play to their own advantages and actively use the satellite remote sensing technology to provide technical support to the establishment of natural oxygen zones (areas with high negative oxygen ion level, good air quality, superior climate and environment, and complete tourism facilities that are suitable for tourism, leisure, and health) and to the improvement of ecologi-cal environment for human settlement.
To meet the needs of users, NSMC has developed new index products for evaluating the natural oxygen zones of China in addition to existing satellite remote sensing monitoring products. The new products are produced mainly based on the FY satellite data (Fig. 5), providing assistance to the establishment and evaluation of natural oxygen zones according to the relevant standards of China (CMSA, 2017). With the national ecological remote sensing products, satellite remote sensing-based indicators of 5 kinds covering 12 terms are studied and computed. They include the evaluation indices for the quantity of oxygen release (based on the NPP and the quantity of forest oxygen release), climate comfort level for human settlement (based on the satellite retrieved LST, relative humidity, intensity of urban heat island, and temperature–humidity index), atmospheric environment (based on the satellite retrieved air quality index, air quality index in periods suitable for tourism, proportion of the days with air quality at good and moderate levels, and proportion of the time range with air quality at good and moderate levels), percentage of forest cover, and regional water quality. In the evaluation of natural oxygen zones of China during 2017–2019, the above 5 kinds of indicators covering 12 terms provided support to a scientific, objective, and quantitative evaluation of the ecological environment of natural oxygen zones in China.
The urban heat island effect has become one of the most serious problems in urban ecological protection, bringing about negative effects to the sustainable development of the city, the life quality of urban residents, and the improvement of human settlement. Based on FY and other sources of satellite data, real-time and dynamic monitoring of the intensity of urban heat island is conducted in meteorological departments of China, and the relationship between urban heat island and climate change is also analyzed (Liu Q. H. et al., 2018). In August 2019, the CMA launched the monitoring and evaluation services for national urban heat island using FY satellites, which is the first running operation in the integrated application system of national satellite remote sensing. The meteorological departments have been carrying out monitoring of the urban LST, and monitoring and evaluating of urban heat island intensity (Fig. 6). On this basis, an operational layout covering the country, province, city (prefecture), and county can be formed, to provide scientific basis for the improvement of ecologi-cal environment for human settlement, urban planning and construction, fine management, and so on. For a long time, satellite remote sensing mainly provides decision-making services for the government, but few for the public. To change this situation, Jiangsu Provincial Meteorological Bureau uses FY satellites and other satellites and ground observation data, constructs quantitative estimation model based on remote sensing technology and machine learning algorithm, and releases six public service products including the ecological heat, greenness, dryness, humidity, atmospheric turbidity, and water surface coverage, for use by the public. A platform for product making and releasing is developed, which realizes the operational running of public service for ecological remote sensing. The six remote sensing-based ecological products and derivative public service products make the ecological remote sensing a part of human life, and effectively expand the breadth and depth of meteorologi-cal support service for ecological civilization construction, thus attracting widespread attention in China.
|Satellite||Launch time||Type||Design life||Status|
|FY-1A||1988-09-07||Experiment||2 yr||39 days|
|FY-1B||1990-09-03||Experiment||2 yr||158 days|
|FY-1C||1999-05-10||Operation||2 yr||6.5 yr|
|FY-1D||2002-05-15||Operation||2 yr||10 yr|
|FY-3A||2008-05-27||Experiment||3 yr||10 yr|
|FY-3B||2010-11-05||Experiment||3 yr||10 yr|
|FY-3C||2013-09-23||Operation||5 yr||In orbit service|
|FY-3D||2017-11-15||Operation||5 yr||In orbit service|
|FY-3E||2021-07-15||Operation||8 yr||In orbit test|
|FY-2A||1997-06-10||Experiment||2 yr||10 months|
|FY-2B||2000-06-25||Experiment||2 yr||8 months|
|FY-2C||2004-10-19||Operation||3 yr||8.5 yr|
|FY-2D||2006-12-08||Operation||3 yr||10 yr|
|FY-2E||2008-12-23||Operation||3 yr||10 yr|
|FY-2F||2012-01-13||Operation||4 yr||In orbit service|
|FY-2G||2014-12-31||Operation||4 yr||In orbit service|
|FY-2H||2018-06-05||Operation||4 yr||In orbit service|
|FY-4A||2016-12-11||Experiment||7 yr||In orbit service|
|FY-4B||2021-06-03||Operation||7 yr||In orbit test|