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From 1 January 2010 to 24 August 2023, 566 orbital stages and 511 spacecraft with a radar cross section >1 m2 have re-entered without control the Earth's atmosphere. The total returned mass was 1650 metric tons, corresponding to a mean of 115 metric tons per year. 77% of the mass belonged to orbital stages, 23% to spacecraft. The uncontrolled re-entries of orbital stages are currently dominated by China, accounting for more than half of the decaying mass, while for spacecraft 2/3 of the mass belongs to American satellites. 60% of the re-entries occurred within 2 years of the launch. The ground casualty expectancy due to orbital stages was always predominant over that from spacecraft, by an average factor of nearly three. From 2010 to 2018, the total casualty probability remained substantially stable, with a mean annual value just over 1%. Since 2019, instead, the annual casualty probability of both spacecraft and orbital stages progressively increased, reaching a total value of around 3% in 2022 and 2023 (extrapolated). Even assuming a stable launch activity, in the coming years, when many of the recently launched spacecraft will start to re-enter, the casualty expectancy of orbital stages will remain basically the same, while that of spacecraft might progressively increase by a factor of 20. This would lead to an annual casualty probability of about 20%, even more in case of a further growth in launch activity, very likely based on current forecasts. The quick implementation of widespread and effective mitigation measures, like controlled de-orbiting and design for demise, is therefore necessary, to prevent the situation from deteriorating too much. • The statistics and ground casualty risk of uncontrolled re-entries of large spacecraft and orbital stages were revisited. • The uncontrolled re-entries of orbital stages are currently dominated by China, accounting for more than half of the decaying mass, while for spacecraft 2/3 of the mass belongs to American satellites. • Since 2019, the annual casualty probability of both spacecraft and orbital stages progressively increased, reaching a total value of around 3% in 2022. • 70% of the casualty expectancy is associated with the uncontrolled re-entries of orbital stages, 30% with the re-entries of satellites. • It is necessary to take effective mitigation measures as soon as possible, for instance requiring the generalized adoption of controlled de-orbiting for large orbital stages and satellites. [ABSTRACT FROM AUTHOR]

The existing maintainable spacecraft costs a lot to realize the maintainability, and the technical development path is not clear, so it is difficult to popularize and apply. Based on the analysis of the technical characteristics of foreign maintainable spacecraft, this paper puts forward a general design method for maintainable spacecraft from three aspects: maintainable architecture, replaceable functional module architecture and plug-and-play interface architecture. Combined with the proposed method, a modular maintainable satellite with variable main structure configuration is designed, and the key technologies involved are described. The designed serviceable satellite takes the open mechanical system with variable configuration, distributed heterogeneous network system and refillable propulsion system as the core architecture, and the two-level functional modules and three-level interfaces as the repairable carrier. It realizes the maintainability at low cost, reduces the capability requirements for maintenance operators, and the system function and performance can evolve dynamically with the technology development. The proposed method and typical design case could provide reference for the development of maintainable spacecraft and corresponding technologies in China. [ABSTRACT FROM AUTHOR]

Abstract: The laser-driven flyer system with a single pulses from a Q-switched Nd: glass laser, of 15ns duration and up to 20J energy, launched the aluminum films of 7μm thickness up to 8.3km/s velocity in Beijing Institute of Spacecrafts Environment Engineering (BISEE) are briefly introduced. Some experimental aspects in our efforts on the space debris hypervelocity impacts on the outer surfaces functional of material, such as the thermal control material, window glass, OSR etc., are reviewed. Though still developing, the laser-driven flyer technique has been demonstrated promise in simulating micro M/OD hypervelocity impacting effects. [Copyright &y& Elsevier]

Passivating spacecraft and upper stages at the end of their operational life is a must: numerous in orbit break-ups have been encountered by all space operators due to a lack of proper passivation leading to an explosion triggered by mixture of hypergolic propellants, pressure build-up, or hyper-velocity collision with a small object.The following paper recalls first the high level guidelines that have to be adopted at international level to achieve proper space debris mitigation, recalls the definition of passivation, then describes the most frequent solutions currently adopted. Several examples, mainly from India and China, are quoted, extracted generally from IADC presentations; they are presented in italics, unmodified. The paper then reviews briefly the main problems encountered during the process of designing the passivation system and operating it. [ABSTRACT FROM AUTHOR]

Satellite-based methods are proposed for the estimation of clear day average hourly illuminance from satellite data under local climate conditions. First, aerosol optical depth (AOD) data collected using a ground-based sun photometer were used to calibrate the satellite remote sensing AOD data. Next, we screened for the factors affecting the illuminance of clear sky and detected three important factors, namely the sine of the solar altitude angle, aerosol optical thickness, and atmospheric precise water content. Finally, based on the AOD data of satellite remote sensing, combined with the local illumination data and meteorological data, a clear sky average hourly illumination model in Chongqing was established via the regression method. There was good agreement between the calculated and the measured values of clear day average hourly illuminance, with a root mean square difference and mean bias difference of 22% and -0.05%, respectively. The model was used to map clear day annual, quarterly, and monthly average hourly illuminance. The maps show the clear day annual, seasonal, and monthly variations of average hourly illuminance in Chongqing., Competing Interests: The authors have declared that no competing interests exist.

Satellite observations offer a great approach to investigate the features of major marine parameters, including sea surface chlorophyll (CHL), sea surface temperature (SST), sea surface height (SSH), and factors derived from these parameters (e.g., fronts). This study shows a step-by-step procedure to use satellite observations to describe major parameters and their relationships in seasonal and anomalous fields. This method is illustrated using satellite datasets from 2002-2017 that were used to describe the surface features of the South China Sea (SCS). Due to cloud coverage, monthly averaged data were used in this study. The empirical orthogonal function (EOF) was applied to describe the spatial distribution and temporal variabilities of different factors. The monsoon wind dominates the variability in the basin. Thus, wind from the reanalysis dataset was used to investigate its driving force on different parameters. The seasonal variability in CHL was prominent and significantly correlated with other factors in a majority of the SCS. In winter, a strong northeast monsoon induces a deep mixed layer and high level of chlorophyll throughout the basin. Significant correlation coefficients were found among factors at the seasonal cycle. In summer, high CHL levels were mostly found in the western SCS. Instead of a seasonal dependence, the region was highly dynamic, and factors correlated significantly in anomalous fields such that unusually high CHL levels were associated with abnormally strong winds and intense frontal activities. The study presents a step-by-step procedure to use satellite observations to describe major parameters and their relationships in seasonal and anomalous fields. The method can be applied to other global oceans and will be helpful for understanding marine dynamics.

Human exposure to PM 2.5 , represented by population-weighted mean PM 2.5 concentration (c ρ ), declines under three conditions: (1) mean PM 2.5 concentration declines, (2) PM 2.5 concentration within urban areas goes through more of a decrease than within rural areas, or (3) city planning relocates people into cleaner areas. Decomposing these effects on human exposure is essential to guide future environmental policies. The lack of ground PM 2.5 observations limits the assessment of human exposure to PM 2.5 over China. This study proposed a novel diagnostic framework using satellite observations to decompose the variation in c ρ resulting from change in the mean PM 2.5 concentration, spatial difference in PM 2.5 change, and demographic change. In this framework, we decomposed c ρ into mean PM 2.5 concentration (c 0 ) and pollution-population-coincidence induced PM 2.5 exposure (PPCE). We then used this framework to decompose the variation in c ρ over China within three recent Five-Year Plans (FYPs) (2001-2015). The results showed that the decline in c 0 reduced c ρ in most provinces within the eleventh and twelfth FYPs. The spatial difference in PM 2.5 change reduced the PPCE and c ρ in most provinces within the tenth and twelfth FYPs, with the most substantial reduction rate of -3.64 μg m -3 ·yr -1 in Tianjin within the twelfth FYP. Rural-to-urban migration resulting from rapid urbanization, however, increased the PPCE and c ρ (by as much as 0.22 μg m -3 ·yr -1 ) in all provinces except Taiwan within all three FYPs. The demographic change reduced c ρ in Taiwan because of the migration of population into less polluted areas. To better reduce human exposure, it is recommended that control efforts further target populous residential areas and urbanization planning relocates people into less polluted areas. Our decomposition framework paves a new way to decompose the human exposure to other air pollutants in China and other regions., (Copyright © 2020 Elsevier Inc. All rights reserved.)

In the developing countries such as China, most well-developed areas have suffered severe haze pollution, which was associated with increased premature morbidity and mortality and attracted widespread public concerns. Since ground-based PM 2.5 monitoring has limited temporal and spatial coverage, satellite aerosol remote sensing data has been increasingly applied to map large-scale PM 2.5 characteristics through advanced spatial statistical models. Although most existing research has taken advantage of the polar orbiting satellite instruments, a major limitation of the polar orbiting platform is its limited sampling frequency (e.g., 1-2 times/day), which is insufficient for capturing the PM 2.5 variability during short but intense heavy haze episodes. As the first attempt, we quantitatively investigated the feasibility of using the aerosol optical depth (AOD) data retrieved by the Geostationary Ocean Color Imager (GOCI) to estimate hourly PM 2.5 concentrations during winter haze episodes in the Yangtze River Delta (YRD). We developed a three-stage spatial statistical model, using GOCI AOD and fine mode fraction, as well as corresponding monitoring PM 2.5 concentrations, meteorological and land use data on a 6-km modeling grid with complete coverage in time and space. The 10-fold cross-validation R 2 was 0.72 with a regression slope of 1.01 between observed and predicted hourly PM 2.5 concentrations. After gap filling, the R 2 value for the three-stage model was 0.68. We further analyzed two representative large regional episodes, i.e., a "multi-process diffusion episode" during December 21-26, 2015 and a "Chinese New Year episode" during February 7-8, 2016. We concluded that AOD retrieved by geostationary satellites could serve as a new valuable data source for analyzing the heavy air pollution episodes., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Understanding migration ecology of Eurasian wigeons ( Mareca penelope ) is crucial for effective population management, mitigating conflicts with human, and habitat conservation. The objectives of the present study were 1) to determine their migration patterns of Eurasian wigeons in the East Asian flyway, and 2) to identify the key breeding and stopover sites. From 2007 to 2016, a total of the 64 wigeons, which wintered in Japan, were equipped with satellite transmitters. Most Eurasian wigeons migrated to breeding sites in Russia either (a) via a continental route through China, (b) via the Kamchatka Peninsula, or (c) via Sakhalin Island. In spring, many of the Eurasian wigeons (60.98%) migrated via the continental route. In autumn, most Eurasian wigeons (57.14%) migrated through Kamchatka. These differences may be attributable to the influence of Okhotsk Sea air mass on migration decisions due to loop migration. Similarly to the migration of Mallards, Eurasian wigeons employed a "long-stay and short-travel" migration strategy. Eurasian wigeons mainly nested between latitude between 43° to 75°N. From the present findings and the published literature, Eurasian wigeons that winter in Japan are considered to migrate to Russia, China, and the United States during the breeding season, although the main breeding area is in northeastern Russia. A total of 296 important sites to Eurasian wigeons were mapped, and 118 location names with geographic coordinates, and the top five most frequently used sites were identified in each season.

In recent years, ozone pollution has become more and more serious in China. Several epidemiological studies have demonstrated the correlation between short-term ozone exposure and several health risks including all-cause mortality, cardiovascular mortality, and respiratory mortality. In this study, the daily ozone exposure levels with 10 km × 10 km resolution were estimated based on satellite data derived from Ozone Monitoring Instrument (OMI) and the monitoring data. The health impacts for potential decrease in the daily ozone concentration and the corresponding economic benefits in 2016 were estimated by applying the environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE) model. By reducing the daily maximum 8-h average concentration of ozone to 100 μg/m 3 , the estimated avoided all-cause mortalities were 120 × 10 3 (95% confidence interval (CI): 67 × 10 3 , 160 × 10 3 ) cases and the correspondingly economic benefits ranged from 36 to 64 billion CNY using amended human capital (AHC) and willingness to pay (WTP) method in 2016. If the daily maximum 8-h average concentration of ozone were rolled back to 70 μg/m 3 , the estimated avoided all-cause mortalities were 160 × 10 3 (95% CI: 98 × 10 3 , 230 × 10 3 ) cases and economic benefits ranged from 54 to 95 billion CNY based on AHC and WTP methods., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

China launched the Tiangong-2 space laboratory in 2016 and will eventually build a basic space station by the early 2020s. These spaceflight missions require astronauts to stay on the space station for more than 6 months, and they inevitably carry microbes into the space environment. It is known that the space environment affects microbial behavior, including growth rate, biofilm formation, virulence, drug resistance, and metabolism. However, the mechanisms of these alternations have not been fully elucidated. Therefore, it is beneficial to monitor microorganisms for preventing infections among astronauts in a space environment. Salmonella enteritidis is a Gram-negative bacterial pathogen that commonly causes acute gastroenteritis in humans. In this study, to better understand the effects of the space environment on S. enteritidis, a S. enteritidis strain was taken into space by the Shenzhou-11 spacecraft from 17 October 2016 to 18 November 2016, and a ground simulation with similar temperature conditions was simultaneously performed as a control. It was found that the flight strain displayed an increased growth rate, enhanced amikacin resistance, and some metabolism alterations compared with the ground strain. Enrichment analysis of proteome revealed that the increased growth rate might be associated with differentially expressed proteins involved in transmembrane transport and energy production and conversion assembly. A combined transcriptome and proteome analysis showed that the amikacin resistance was due to the downregulation of the oppA gene and oligopeptide transporter protein OppA. In conclusion, this study is the first systematic analysis of the phenotypic, genomic, transcriptomic, and proteomic variations in S. enteritidis during spaceflight and will provide beneficial insights for future studies on space microbiology., (© 2019 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.)

A time series of satellite data on Chlorophyll-a concentration (Chl-a) that used ocean color was studied to determine mechanisms of phytoplankton variation in recent decade in the Yellow Sea, China during 2003-2015. The variability patterns on seasonal and inter-annual oscillation periods were confirmed using the Empirical Orthogonal Function (EOF), and Morlet wavelet transform analyses, respectively. The first EOF mode for Chl-a was dominated by obvious spring and fall blooms in a spatial pattern that was related to the strong mixing of the water masses from the Yellow Sea Cold Warm Mass (YSCWM) and the Yellow Sea Warm Current (YSWC) in winter. The second EOF mode for Chl-a showed an opposite spatial pattern between the northern and southern regions. The temporal coefficient showed differences in the timing of blooms. On an inter-annual scale, Chl-a indicated variation at periods of 2-4 years during 2003-2015. Chl-a showed a significantly negative correlation with the sea surface temperature (r = -0.21, p<0.01), with time lags of 4 months (Chl-a ahead). Chl-a was coupled with El Niño Southern Oscillation (ENSO) events, with a positive correlation (r = 0.46, p<0.01) at a lag of 3-5 months (ENSO ahead). The present study demonstrated that the variation in phytoplankton biomass was controlled primarily by water mass seasonally, and it was influenced by ENSO events on an inter-annual scale., Competing Interests: The authors have declared that no competing interests exist.

After successfully launching two space laboratories, namely, Tiangong-1 and Tiangong-2, China has announced her next plan of constructing the Chinese Space Station (CSS) in 2022. The CSS will provide not only platforms for Chinese scientists to carry out experimental studies in outer space but also opportunities for open international cooperation. In this article, we review the development of China's manned space exploration missions and the preliminary plan for CSS. Additionally, China has initiated space radiation research decades ago with both ground-based simulation research platform and space vehicles and has made noticeable progresses in several aspects. These include studies on human health risk assessment using mammalian cell cultures and animals as models. Furthermore, there have been numerous studies on assessing the space environment in plant breeding., (Copyright © 2019 The Committee on Space Research (COSPAR). Published by Elsevier Ltd. All rights reserved.)

China has prepared for construction of a space station by the early 2020s. The mission will require astronauts to stay on the space station for at least 180 days. Microbes isolated from the International Space Station (ISS) have shown profound resistance to clinical antibiotics and environmental stresses. Previous studies have demonstrated that the space environment could affect microbial survival, growth, virulence, biofilms, metabolism, as well as their antibiotic-resistant phenotypes. Furthermore, several studies have reported that astronauts experience a decline in their immunity during long-duration spaceflights. Monitoring microbiomes in the ISS or the spacecraft will be beneficial for the prevention of infection among the astronauts during spaceflight. The development of a manned space program worldwide not only provides an opportunity to investigate the impact of this extreme environment on opportunistic pathogenic microbes, but also offers a unique platform to detect mutations in pathogenic bacteria. Various microorganisms have been carried on a spacecraft for academic purposes. Acinetobacter baumannii is a common multidrug-resistant bacterium often prevalent in hospitals. Variations in the ability to cope with environmental hazards increase the chances of microbial survival. Our study aimed to compare phenotypic variations and analyze genomic and transcriptomic variations in A. baumannii among three different groups: SS1 (33 days on the Shenzhou 11 spacecraft), GS1 (ground control), and Aba (reference strain). Consequently, the biofilm formation ability of the SS1 strain decreased after 33 days of spaceflight. Furthermore, high-throughput sequencing revealed that some differentially expressed genes were downregulated in the SS1 strain compared with those in the GS1 strain. In conclusion, this present study provides insights into the environmental adaptation of A. baumannii and might be useful for understanding changes in the opportunistic pathogenic microbes on our spacecraft and on China's future ISS., (© 2018 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.)

In this study, we propose to assess climate impact on forest cover (represented by EVI) at multiple scales in areas undergoing substantial land cover change, using Landsat imagery with human-induced land cover change effect excluded. Taking the Qingliu River catchment located in a subtropical humid monsoon area in China as a case study, the results indicate that EVI increases significantly (p < 0.01) during 1989-2014 with a magnitude of 0.026/decade. Spatial distribution of EVI is distinct in summer and growing season. Temperature and precipitation show high partial correlations with EVI, with better partial correlation found between EVI and temperature. Their partial correlations with EVI on monthly scale are higher than those on annual scale. Besides, precipitation and pan evaporation show accumulative lag effects (4 months) on forest EVI, while temperature has no lag effect. Finally, an empirical formula is established to quantify the relationship among EVI and its main driving factors (temperature and precipitation) by considering the precipitation threshold (200 mm). The findings should provide scientific supports for local forest management and ecosystem services, and should also support the hydrological effect assessment of vegetation cover change under climate change for the study area., (Copyright © 2019. Published by Elsevier B.V.)

Ecosystems in arid and semi-arid regions are vulnerable to climatic and anthropogenic disturbances. However, our understanding of vegetation stability (including resistance and resilience, which are the abilities of ecosystems to resist perturbations and return to pre-disturbance structure or function, respectively) in response to environmental changes in dryland ecosystems remains insufficient, particularly in the absence of large-scale observations of water availability. Here we introduced GRACE monthly total water storage anomaly (TWSA) data into an autoregressive model with remote sensed EVI, air temperature and precipitation to investigate the short-term vegetation stability and its influencing factors in Central Asia (CA) during 2003-2015. The results showed that the grid-level vegetation resilience in CA increased logarithmically as mean annual precipitation (R 2  = 0.33, P < 0.05) but decreased linearly with increasing mean annual temperature (R 2  = 0.41, P < 0.05). Vegetation resilience was not correlated with TWSA, due to the decoupling of TWSA with precipitation both spatially and temporally in the majority of CA. At the biome level, vegetation resilience also increased as a logarithmical function of aridity index (R 2  = 0.80, P < 0.05). Vegetation resistance to TWSA showed minor difference across biomes, while vegetation resistance to precipitation functioned as a parabolic curve along the aridity gradient (R 2  = 0.59, P < 0.05). Our results suggest that accounting for the effects of total water column instead of precipitation only is critical in understanding vegetation-water relationships in drylands. The steep decrease in vegetation resilience in areas with high temperature and low water availability implies a high risk of collapse for these water-limited ecosystems if there are severe droughts. Furthermore, reduction in total water storage, induced by, e.g., large-scale extraction of surface runoff or shallow-layer groundwater for irrigation, can result in negative influences to natural biomes in dryland regions., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Teleoperation rendezvous and docking (RVD) can be used as a supporting technology for unmanned spacecrafts, or as a technology to dock the chaser with a noncooperative target. Teleoperation RVD has attracted little attention in the scientific community in the past according to a literature survey, while it is of application significance to China's space station project. This paper outlines the concept design of a novel teleoperation RVD system as well as the controller. Experiments to verify the feasibility of the novel concept design focus on the communication bandwidth, the impact of time delay within the control loop, and a predictive display approach to reduce the impact of time delay. The results show that the chaser is controllable even though the time delay is as large as 6 s during ground-based teleoperating closed-loop control, i.e., the newly designed system is feasible. In addition, the control approach based on predictive display demonstrates an increase in effectiveness within teleoperation RVD. Experimental results indicate that the success rate of this approach increases by 14% compared to the traditional approach that uses only visual feedbacks. [ABSTRACT FROM AUTHOR]

The limitations of satellite data acquisition mean that there is a lack of satellite data with high spatial and temporal resolutions for environmental process monitoring. In this study, we address this problem by applying the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) and the Spatial and Temporal Data Fusion Approach (STDFA) to combine Huanjing satellite charge coupled device (HJ CCD), Gaofen satellite no. 1 wide field of view camera (GF-1 WFV) and Moderate Resolution Imaging Spectroradiometer (MODIS) data to generate daily high spatial resolution synthetic data for land surface process monitoring. Actual HJ CCD and GF-1 WFV data were used to evaluate the precision of the synthetic images using the correlation analysis method. Our method was tested and validated for two study areas in Xinjiang Province, China. The results show that both the ESTARFM and STDFA can be applied to combine HJ CCD and MODIS reflectance data, and GF-1 WFV and MODIS reflectance data, to generate synthetic HJ CCD data and synthetic GF-1 WFV data that closely match actual data with correlation coefficients (r) greater than 0.8989 and 0.8643, respectively. Synthetic red- and near infrared (NIR)-band data generated by ESTARFM are more suitable for the calculation of Normalized Different Vegetation Index (NDVI) than the data generated by STDFA.

Satellite-based precipitation data have contributed greatly to quantitatively forecasting precipitation, and provides a potential alternative source for precipitation data allowing researchers to better understand patterns of precipitation over ungauged basins. However, the absence of calibration satellite data creates considerable uncertainties for The Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42 product over high latitude areas beyond the TRMM satellites latitude band (38°NS). This study attempts to statistically assess TMPA V7 data over the region beyond 40°NS using data obtained from numerous weather stations in 1998-2012. Comparative analysis at three timescales (daily, monthly and annual scale) indicates that adoption of a monthly adjustment significantly improved correlation at a larger timescale increasing from 0.63 to 0.95; TMPA data always exhibits a slight overestimation that is most serious at a daily scale (the absolute bias is 103.54%). Moreover, the performance of TMPA data varies across all seasons. Generally, TMPA data performs best in summer, but worst in winter, which is likely to be associated with the effects of snow/ice-covered surfaces and shortcomings of precipitation retrieval algorithms. Temporal and spatial analysis of accuracy indices suggest that the performance of TMPA data has gradually improved and has benefited from upgrades; the data are more reliable in humid areas than in arid regions. Special attention should be paid to its application in arid areas and in winter with poor scores of accuracy indices. Also, it is clear that the calibration can significantly improve precipitation estimates, the overestimation by TMPA in TRMM-covered area is about a third as much as that in no-TRMM area for monthly and annual precipitation. The systematic evaluation of TMPA over mid-high latitudes provides a broader understanding of satellite-based precipitation estimates, and these data are important for the rational application of TMPA methods in climatic and hydrological research.

The reliable detection and attribution of changes in vegetation growth is a prerequisite for the development of strategies for the sustainable management of ecosystems. This is an extraordinary challenge. To our knowledge, this study is the first to comprehensively detect and attribute a greening trend in China over the last three decades. We use three different satellite-derived Leaf Area Index (LAI) datasets for detection as well as five different process-based ecosystem models for attribution. Rising atmospheric CO2 concentration and nitrogen deposition are identified as the most likely causes of the greening trend in China, explaining 85% and 41% of the average growing-season LAI trend (LAIGS) estimated by satellite datasets (average trend of 0.0070 yr(-1), ranging from 0.0035 yr(-1) to 0.0127 yr(-1)), respectively. The contribution of nitrogen deposition is more clearly seen in southern China than in the north of the country. Models disagree about the contribution of climate change alone to the trend in LAIGS at the country scale (one model shows a significant increasing trend, whereas two others show significant decreasing trends). However, the models generally agree on the negative impacts of climate change in north China and Inner Mongolia and the positive impact in the Qinghai-Xizang plateau. Provincial forest area change tends to be significantly correlated with the trend of LAIGS (P < 0.05), and marginally significantly (P = 0.07) correlated with the residual of LAIGS trend, calculated as the trend observed by satellite minus that estimated by models through considering the effects of climate change, rising CO2 concentration and nitrogen deposition, across different provinces. This result highlights the important role of China's afforestation program in explaining the spatial patterns of trend in vegetation growth., (© 2014 John Wiley & Sons Ltd.)

Inhalable particulate matter (PM10) is a primary air pollutant closely related to public health, and an especially serious problem in urban areas. The urban heat island (UHI) effect has made the urban PM10 pollution situation more complex and severe. In this study, we established a health risk assessment system utilizing an epidemiological method taking the thermal environment effects into consideration. We utilized a remote sensing method to retrieve the PM10 concentration, UHI, Normalized Difference Vegetation Index (NDVI), and Normalized Difference Water Index (NDWI). With the correlation between difference vegetation index (DVI) and PM10 concentration, we utilized the established model between PM10 and thermal environmental indicators to evaluate the PM10 health risks based on the epidemiological study. Additionally, with the regulation of UHI, NDVI and NDWI, we aimed at regulating the PM10 health risks and thermal environment simultaneously. This study attempted to accomplish concurrent thermal environment regulation and elimination of PM10 health risks through control of UHI intensity. The results indicate that urban Beijing has a higher PM10 health risk than rural areas; PM10 health risk based on the thermal environment is 1.145, which is similar to the health risk calculated (1.144) from the PM10 concentration inversion; according to the regulation results, regulation of UHI and NDVI is effective and helpful for mitigation of PM10 health risk in functional zones.

Human activities contribute highly to water eutrophication. In this study, the relationship between human activities and water eutrophication in Dianchi Lake in China was characterized using a combination of satellite imaging, sedimentary physicochemical and meteorological data analyses. The heavy eutrophic status and algal bloom in Dianchi Lake were first observed by satellite in 1977 and 1989, respectively. The C/N ratio, an indicator of organic sources in sediments, also showed that the planktonic organic source in the sediment significantly increased beginning in 1989. The land use cover in the Dianchi basin showed that both farm lands and forests, but particularly farmlands, were reduced during the period from 1974 to 2009. The urbanized land area increased from 1974 to 2009, particularly after 2000. The effects of human activities on water eutrophication were expressed by land use cover, population, gross domestic product (GDP; separated into primary, secondary and tertiary industries) and wastewater discharge. For land use cover, farm and urbanized lands were the main sources of water nutrients; forest contributed slightly to these nutrients. For GDP, primary (correlation coefficient=0.94, P<0.001) and tertiary (correlation coefficient=0.95, P<0.001) industries were highly correlated with total nitrogen. Secondary (correlation coefficient=0.95, P<0.001) and tertiary (correlation coefficient=0.96, P<0.001) industries were highly correlated with total phosphorus. The algal bloom area was significantly correlated with wastewater discharge (correlation coefficient=0.78, P<0.005) (except industrial wastewater), which was primarily led by the non-agricultural population, from 2000 to 2009. This study suggests that the protection of water environments requires a comprehensive protection policy in addition to a unilateral protection policy., (Copyright © 2014 Elsevier B.V. All rights reserved.)

The regression tree method is used to upscale evapotranspiration (ET) measurements at eddy-covariance (EC) towers to the grassland ecosystems over the Dryland East Asia (DEA). The regression tree model was driven by satellite and meteorology datasets, and explained 82% and 76% of the variations of ET observations in the calibration and validation datasets, respectively. The annual ET estimates ranged from 222.6 to 269.1 mm yr(-1) over the DEA region with an average of 245.8 mm yr(-1) from 1982 through 2009. Ecosystem ET showed decreased trends over 61% of the DEA region during this period, especially in most regions of Mongolia and eastern Inner Mongolia due to decreased precipitation. The increased ET occurred primarily in the western and southern DEA region. Over the entire study area, water balance (the difference between precipitation and ecosystem ET) decreased substantially during the summer and growing season. Precipitation reduction was an important cause for the severe water deficits. The drying trend occurring in the grassland ecosystems of the DEA region can exert profound impacts on a variety of terrestrial ecosystem processes and functions.

On June 4 and 17, 2011, separate oil spill accidents occurred at two oil platforms in the Bohai Sea, China. The oil spills were subsequently observed on different types of satellite images including SAR (Synthetic Aperture Radar), Chinese HJ-1-B CCD and NASA MODIS. To illustrate the fate of the oil spills, we performed two numerical simulations to simulate the trajectories of the oil spills with the GNOME (General NOAA Operational Modeling Environment) model. For the first time, we drive the GNOME with currents obtained from an operational ocean model (NCOM, Navy Coastal Ocean Model) and surface winds from operational scatterometer measurements (ASCAT, the Advanced Scatterometer). Both data sets are freely and openly available. The initial oil spill location inputs to the model are based on the detected oil spill locations from the SAR images acquired on June 11 and 14. Three oil slicks are tracked simultaneously and our results show good agreement between model simulations and subsequent satellite observations in the semi-enclosed shallow sea. Moreover, GNOME simulation shows that the number of 'splots', which denotes the extent of spilled oil, is a vital factor for GNOME running stability when the number is less than 500. Therefore, oil spill area information obtained from satellite sensors, especially SAR, is an important factor for setting up the initial model conditions., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

Satellite measurements have distinct advantages over conventional ground measurements because they can collect the information repeatedly and automatically. Since 1970 globally and 1985 in China, the availability of remote sensing (RS) techniques has steadily grown and they are becoming increasingly important to improve our understanding of human health. This paper gives the first detailed overview on the developments of RS applications for disease control in China. The problems, challenges and future directions are also discussed with an aim of guiding prospective studies.

Satellite-retrieved data on aerosol optical depth (AOD) and Ångström exponent (AE) using a moderate resolution imaging spectrometer (MODIS) were used to analyze large-scale distributions of atmospheric aerosols in East Asia. AOD was relatively high in March (0.44 ± 0.25) and low in September (0.24 ± 0.21) in the East Asian region in 2009. Sandstorms originating from the deserts and dry areas in northern China and Mongolia were transported on a massive scale during the springtime, thus contributing to the high AOD in East Asia. However, whereas PM10 with diameters ≤10 μm was the highest in February at Anmyon, Cheongwon, and Ulleung, located leeward about halfway through the Korean Peninsula, AOD rose to its highest in May. The growth of hygroscopic aerosols attendant on increases in relative humidity prior to the Asian monsoon season contributed to a high AOD level in May. AE typically appears at high levels (1.30 ± 0.37) in August due to anthropogenic aerosols originating from the industrial areas in eastern China, while AOD stays low in summer due to the removal process caused by rainfall. The linear correlation coefficients of the MODIS AOD and ground-based mass concentrations of PM10 at Anmyon, Cheongwon, and Ulleung were measured at 0.4~0.6. Four cases (6 days) of mineral dustfall from sandstorms and six cases (12 days) of anthropogenically polluted particles were observed in the central area of the Korean Peninsula in 2009. PM10 mass concentrations increased at both Anmyon and Cheongwon in the cases of mineral dustfall and anthropogenically polluted particles. Cases of dustfall from sandstorms and anthropogenic polluted particles, with increasing PM10 mass concentrations, showed higher AOD values in the Yellow Sea region.

The dynamics of vegetation coverage and associated driving forces are one of the key issues in global environmental change. In the study, taking Lijiang County as a case, the Normalized Difference Vegetation Index was used to quantify vegetation coverage change in mountain areas of Northwestern Yunnan, China, with the application of remote sensing data and GIS technologies. And associated driving forces of vegetation coverage change were also analyzed, with a focus on land use change and elevation. The results showed that there was high vegetation coverage with a significant increase in the whole county during 1986-2002. However, due to economic development and the implementation of environmental protection polices, vegetation coverage change in the county showed distinct spatial diversity, which mainly behaved as the increasing in the northwest of the county with low human activities, and the decreasing in the south with high economic development. The results also showed that as a restrictive factor, elevation was of great signification on the spatial distribution of vegetation coverage in a broad scale; while in the county level, it was land use that determined the vegetation coverage, since the change of vegetation coverage grades in the study area was mainly associated with the change of land use types.

Cyanobacterial blooms are often a result of eutrophication. Recently, however, their expansion has also been found to be associated with changes in climate. To elucidate the effects of climatic variables on the expansion of cyanobacterial blooms in Taihu, China, we analyzed the relationships between climatic variables and bloom events which were retrieved by satellite images. We then assessed the contribution of each climate variable to the phenology of blooms using multiple regression models. Our study demonstrates that retrieving ecological information from satellite images is meritorious for large-scale and long-term ecological research in freshwater ecosystems. Our results show that the phenological changes of blooms at an inter-annual scale are strongly linked to climate in Taihu during the past 23 yr. Cyanobacterial blooms occur earlier and last longer with the increase of temperature, sunshine hours, and global radiation and the decrease of wind speed. Furthermore, the duration increases when the daily averages of maximum, mean, and minimum temperature each exceed 20.3 °C, 16.7 °C, and 13.7 °C, respectively. Among these factors, sunshine hours and wind speed are the primary contributors to the onset of the blooms, explaining 84.6% of their variability over the past 23 yr. These factors are also good predictors of the variability in the duration of annual blooms and determined 58.9% of the variability in this parameter. Our results indicate that when nutrients are in sufficiently high quantities to sustain the formation of cyanobacterial blooms, climatic variables become crucial in predicting cyanobacterial bloom events. Climate changes should be considered when we evaluate how much the amount of nutrients should be reduced in Taihu for lake management., (Copyright © 2011 Elsevier Ltd. All rights reserved.)

Impervious surface area (ISA) is considered as an indicator of environment change and is regarded as an important input parameter for hydrological cycle simulation, water management and area pollution assessment. The Pearl River Delta (PRD), the 3rd most important economic district of China, is chosen in this paper to extract the ISA information based on Landsat images of 1998, 2003 and 2008 by using a linear spectral un-mixing method and to monitor impervious surface change by analyzing the multi-temporal Landsat-derived fractional impervious surface. Results of this study were as follows: (1) the area of ISA in the PRD increased 79.09% from 1998 to 2003 and 26.88% from 2003 to 2008 separately; (2) the spatial distribution of ISA was described according to the 1998/2003 percentage respectively. Most of middle and high percentage ISA was located in northwestern and southeastern of the whole delta, and middle percentage ISA was mainly located in the city interior, high percentage ISA was mainly located in the suburban around the city accordingly; (3) the expanding direction and trend of high percentage ISA was discussed in order to understand the change of urban in this delta; High percentage ISA moved from inner city to edge of urban area during 1998-2003 and moved to the suburban area that far from the urban area mixed with jumpily and gradually during 2003-2008. According to the discussion of high percentage ISA spatial expanded direction, it could be found out that high percentage ISA moved outward from the centre line of Pearl River of the whole delta while a high ISA percentage in both shores of the Pearl River Estuary moved toward the Pearl River; (4) combining the change of ISA with social conditions, the driving relationship was analyzed in detail. It was evident that ISA percentage change had a deep relationship with the economic development of this region in the past ten years. Contemporaneous major sport events (16th Asia Games of Guangzhou, 26th Summer Universidad of Shenzhen) and the government policies also promoted the development of the ISA. Meanwhile, topographical features like the National Nature Reserve of China restricted and affected the expansion of the ISA. Above all, this paper attempted to extract ISA in a major region of the PRD; the temporal and spatial analyses to PRD ISA demonstrated the drastic changes in developed areas of China. These results were important and valuable for land use management, ecological protection and policy establishment.

Enhancing water use efficiency (WUE) is the key approach to maintain sustainable water resource supply. Due to the complexity of the water cycle, accurate estimation of WUE at the regional scale is a challenging task. Here we presented a framework of relative water use efficiency (RWUE). According to the linkage between RWUE and land use types, assessment of WUE at a regional scale could be performed operationally. This approach was evaluated in a study area, Tuhai-Majia Basin, North China. Based on remote sensing-derived evapotranspiration (ET) and land use data, regional WUE were assessed accordingly. The mean RWUE of agriculture, ecosystem and total basin in 2005 was 60.12, 30.07 and 62.5%, respectively. Spatial analysis showed that the agricultural WUE played the dominant role in water-saving of the study area; water management of unused land (RWUE of 2005 was 5.46%), especially wetland protection and other unused land development, will contribute significantly to ecological RWUE improvement. Temporal analysis indicated that there was considerable inter-annual variability in RWUE time series profiles. The agricultural interlude period might be important for enhancing WUE in the Tuhai-Majia Basin. In general, the results indicated that the RWUE-based method was an efficient and simple method to evaluate WUE at regional scale.

Spatiotemporal shifts in the extent and distribution of alpine wetland ecosystems in China's Qinghai-Tibet plateau were investigated for the period 1967-2004. Using aerial photographs for 1967, and satellite remote sensing data for 1986, 2000, and 2004/5, the main components and distribution of alpine wetland ecosystems in the headwaters regions of the Yangtze and Yellow Rivers, as well as those of the nearby Zoige region, were analyzed. Widespread degradation of the Qinghai-Tibet plateau's alpine wetlands occurred between 1967 and 2004, with over 10% of their area being lost. The greatest such degradation occurred in the headwaters region of Yangtze River, where wetland areas shrank by 29%, and the area of dried-up lakes rose by 17.5%. In the Yellow River's headwaters region as well as the Zoige region, wetland ecosystems clearly underwent accelerated fragmentation and isolation in their spatial distribution. The wetlands' degradation was closely correlated to the rise in air temperature, which from 1982-2004 was over 2-fold faster that from 1965-1982.

Changing the landscape has serious environmental impacts affecting the ecosystem services, particularly in the tropics. In this paper, we report changes in ecosystem services in relation to land use and land cover over an 18-year period (1988--2006) in the Menglun Township, Xishuangbanna, Southwest China. We used Landsat TM/ETM and Quickbird data sets to estimate changes in ten land use and land cover categories, and generalized value coefficients to estimate changes in the ecosystem services provided by each land category. The results showed that over the 18-year period, the land use and land cover in the study area experienced significant changes. Rubber plantations increased from 12.10% of total land cover to 45.63%, while forested area and swidden field decreased from 48.73 and 13.14 to 27.57 and 0.46%, respectively. During this period, the estimated value of ecosystem services dropped by US $11.427 million (approximately 27.73%). Further analysis showed that there were significant changes in ecological functions such as nutrient cycling, erosion control, climate regulation and water treatment as well as recreation; the obvious increase in the ecological function is provision of raw material (natural rubber). Our findings conclude that an abrupt shift in land use from ecologically important tropical forests and traditionally managed swidden fields to large-scale rubber plantations result in a great loss of ecosystem services in this area. Further, the study suggests that provision of alternative economic opportunities would help in maintaining ecosystem services and for an appropriate compensation mechanisms need to be established based on rigorous valuation.

Land use/land cover (LULC) has a profound impact on economy, society and environment, especially in rapid developing areas. Rapid and prompt monitoring and predicting of LULC's change are crucial and significant. Currently, integration of Geographical Information System (GIS) and Remote Sensing (RS) methods is one of the most important methods for detecting LULC's change, which includes image processing (such as geometrical-rectifying, supervised-classification, etc.), change detection (post-classification), GIS-based spatial analysis, Markov chain and a Cellular Automata (CA) models, etc. The core corridor of Pearl River Delta was selected for studying LULC's change in this paper by using the above methods for the reason that the area contributed 78.31% (1998)-81.4% (2003) of Gross Domestic Product (GDP) to the whole Pearl River Delta (PRD). The temporal and spatial LULC's changes from 1998 to 2003 were detected by RS data. At the same time, urban expansion levels in the next 5 and 10 years were predicted temporally and spatially by using Markov chain and a simple Cellular Automata model respectively. Finally, urban expansion and farmland loss were discussed against the background of China's urban expansion and cropland loss during 1990-2000. The result showed: (1) the rate of urban expansion was up to 8.91% during 1998-2003 from 169,078.32 to 184,146.48 ha; (2) the rate of farmland loss was 5.94% from 312,069.06 to 293,539.95 ha; (3) a lot of farmland converted to urban or development area, and more forest and grass field converted to farmland accordingly; (4) the spatial predicting result of urban expansion showed that urban area was enlarged ulteriorly compared with the previous results, and the directions of expansion is along the existing urban area and transportation lines.

In this paper, a method of assessing water quality from satellite data is introduced. The composite pollution index (CPI) was calculated from measured chemical oxygen demand (COD) and nutrient concentration. The relationships between CPI and 240 band combinations of SeaWiFS water-leaving radiance were analyzed and the optimal band combination for estimating CPI was chosen from the 240 band combinations. An algorithm for retrieval of CPI was developed using the optimal band combination, (L(443)xL(510))/(L(412)+L(490)). The CPI was estimated from atmospherically corrected SeaWiFS data by employing the algorithm. Furthermore, the CPI value range for each water quality level was determined based on data obtained from 850 samples taken in the Pearl River Estuary. The remotely sensed CPIs were then transferred to water quality levels and appropriate maps were derived. The remotely sensed water quality level maps displayed a similar distribution of levels based on in situ investigation issued by the State Ocean Administration, China. This study demonstrates that remote sensing can play an important role in water quality assessment.

Political and health sector reforms, along with demographic, environmental and socio-economic transformations in the face of global warming, could cause the re-emergence of schistosomiasis in areas where transmission has been successfully interrupted and its emergence in previously non-endemic areas in China. In the present study, we used geographic information systems and remote sensing techniques to predict potential habitats of Oncomelania hupensis, the intermediate host snail of Schistosoma japonicum. Focussing on the Hongze, Baima and Gaoyou lakes in Jiangsu province in eastern China, we developed a model using the normalized difference vegetation index, a tasseled-cap transformed wetness index, and flooding areas to predict snail habitats at a small scale. Data were extracted from two Landsat images, one taken during a typical dry year and the other obtained three years later during a flooding event. An area of approximately 163.6 km2 was predicted as potential O. hupensis habitats around the three lakes, which accounts for 4.3% of the estimated snail habitats in China. In turn, these predicted snail habitats are risk areas for transmission of schistosomiasis, and hence illustrate the scale of the possible impact of climate change and other ecological transformations. The generated risk map can be used by health policy makers to guide mitigation policies targetting the possible spread of O. hupensis, and with the aim of containing the transmission of S. japonicum.

Application of growing degree day-water budget analysis and satellite climatology to vector-borne parasites will be reviewed to demonstrate the value of using the unique thermal-hydrological preferences and limits of tolerance of individual parasite-vector systems to define the environmental niche of disease agents in the landscape by modern geospatial analysis methods. Applications of geospatial modeling will be illustrated by examples on fascioliasis, malaria, leprosy and leishmaniasis.

Urban growth represents specific response to economic, demographic and environmental conditions. Rapid urbanization and industrializations have resulted in sharp land cover changes. The present investigation was carried out from Shaoxing City to quantify satellite-derived estimates of urban growth using a three-epoch time series Landsat TM data for the years 1984, 1997 and ETM 2000. The methodology used was based on post classification comparison. The use of GIS allowed spatial analysis of the data derived from remotely sensed images. Results showed that the built-up area surrounding Shaoxing City has expanded at an annual average of 7 km2. Analysis of the classified map showed that the physical growth of urban area is upsetting the other land cover classes such as farming, water resources, etc. The study conclusion mainly emphasized the need for sustainable urban capacity.

The article used two NOAA-14 Advanced Very High Resolution Radiometer (AVHRR) datasets to assess flood damage in the middle and lower reaches of China's Changjiang River (Yangtze River) in 1998. As the AVHRR is an optical sensor, it cannot penetrate the clouds that frequently cover the land during the flood season, and this technology is greatly limited in flood monitoring. However the widely used normalized difference vegetation index (NDVI) can be used to monitor flooding, since water has a much lower NDVI value than other surface features. Though many factors other than flooding (e.g. atmospheric conditions, different sun-target-satellite angles, and cloud) can change NDVI values, inundated areas can be distinguished from other types of ground cover by changes in the NDVI value before and after the flood after eliminating the effects of other factors on NDVI. AVHRR data from 26 May and 22 August, 1998 were selected to represent the ground conditions before and after flooding. After accurate geometric correction by collecting GCPs, and atmospheric and angular corrections by using the 6S code, NDVI values for both days and their differences were calculated for cloud-free pixels. The difference in the NDVI values between these two times, together with the NDVI values and a land-use map, were used to identify inundated areas and to assess the area lost to the flood. The results show a total of 358,867 ha, with 207,556 ha of cultivated fields (paddy and non-irrigated field) inundated during the flood of 1998 in the middle and lower reaches of the Changjiang River Catchment; comparing with the reported total of 321,000 and 197,000 ha, respectively. The discrimination accuracy of this method was tested by comparing the results from two nearly simultaneous sets of remote-sensing data (NOAA's AVHRR data from 10 September, 1998, and JERS-1 synthetic aperture radar (SAR) data from 11 September, 1998, with a lag of about 18.5 hr) over a representative flooded region in the study area. The results showed that 67.26% of the total area identified as inundated using the NOAA data was also identified as inundated using the SAR data.

Mathematical models of disease transmission processes can serve as platforms for integration of diverse data, including site-specific information, for the purpose of designing strategies for minimizing transmission. A model describing the transmission of schistosomiasis is adapted to incorporate field data typically developed in disease control efforts in the mountainous regions of Sichuan Province in China, with the object of exploring the feasibility of model-based control strategies. The model is studied using computer simulation methods. Mechanistically based models of this sort typically have a large number of parameters that pose challenges in reducing parametric uncertainty to levels that will produce predictions sufficiently precise to discriminate among competing control options. We describe here an approach to parameter estimation that uses a recently developed statistical procedure called Bayesian melding to sequentially reduce parametric uncertainty as field data are accumulated over several seasons. Preliminary results of applying the approach to a historical data set in southwestern Sichuan are promising. Moreover, technologic advances using the global positioning system, remote sensing, and geographic information systems promise cost-effective improvements in the nature and quality of field data. This, in turn, suggests that the utility of the modeling approach will increase over time.

To assess the impact of the 1998 flood on snail distribution in the lower Yangtze River Basin, two study areas were selected, one in the Poyang Lake region, and the other along the Yangtze River in Jiangsu province. Using image analysis software, geocoded Landsat TM data were used to create TNDVI maps based on the formula TNDVI=Sqrt[(band4-band3/band4+band3)+0.5]. The images taken in the flood season were classified to produce a map depicting water and land. The images taken during springtime were processed and classified based on TNDVI. Composite images were created based on the time difference analysis, combining the flood season maps and spring vegetation maps to produce a map in which potential snail habitats were identified. When compared with ground survey data collected in the spring of 2000, the correspondence rate between potential snail habitats identified by image analysis of 1998-1999 Landsat TM data and ground survey data was over 90% in both regions. Results indicate that ecology based Landsat TM image analysis provides a new way to predict snail distribution under specific environmental conditions associated with the extent of the annual flood season.

This study focuses on relationships between the phenological growing season of plant communities and the seasonal metrics of Normalized Difference Vegetation Index (NDVI) at sample stations and pixels overlying them, and explores the procedure for determining the growing season of terrestrial vegetation at the regional scale, using threshold NDVI values obtained by surface-satellite analysis at individual stations/pixels. The cumulative frequency of phenophases has been calculated for each plant community and each year in order to determine the growing season at the three sample stations from 1982 to 1993. The precise thresholds were arbitrarily set as the dates on which the phenological cumulative frequency reached 5% and 10% (for the beginning) and 90% and 95% (for the end). The beginning and end dates of the growing season were then applied each year as time thresholds, to determine the corresponding 10-day peak greenness values from NDVI curves for 8-km2 pixels overlying the phenological stations. According to a trend analysis, a lengthening of the growing seasons and an increase of the integrated growing season NDVI have been detected in the central part of the research region. The correlation between the beginning dates of the growing season and the corresponding threshold NDVI values is very low, which indicates that the satellite-sensor-derived greenness is independent of the beginning time of the growing season of local plant communities. Other than in spring, the correlation between the end dates of the growing season and the corresponding threshold NDVI values is highly significant. The negative correlation shows that the earlier the growing season terminates, the larger the corresponding threshold NDVI value, and vice versa. In order to estimate the beginning and end dates of the growing season using the threshold NDVI values at sites without phenological data from 1982 to 1993, we calculated the spatial correlation coefficients between NDVI time-series at each sample station and other contiguous sites year by year. The results provide the spatial extrapolation area of the growing season for each sample station. Thus, we can use the threshold NDVI value obtained at one sample station/pixel for a year to determine the growing season at the extrapolation sites with a similar vegetation type for the same year.

The objectives of this study are to explore the relationships between plant phenology and satellite-sensor-derived measures of greenness, and to advance a new procedure for determining the growing season of land vegetation at the regional scale. Three phenological stations were selected as sample sites to represent different climatic zones and vegetation types in northern China. The mixed data set consists of occurrence dates of all observed phenophases for 50-70 kinds of trees and shrubs from 1983 to 1988. Using these data, we calculated the cumulative frequency of phenophases in every 5-day period (pentad) throughout each year, and also drew the cumulative frequency distribution curve for all station-years, in order to reveal the typical seasonal characteristics of these plant communities. The growing season was set as the time interval between 5% and 95% of the phenological cumulative frequency. Average lengths of the growing season varied between 188 days in the northern, to 259 days in the southern part of the research region. The beginning and end dates of the surface growing season were then applied each year as time thresholds, to determine the corresponding 10-day peak greenness values from normalized difference vegetation index curves for 8-km2 pixels overlying the phenological stations. Our results show that, at the beginning of the growing season, the largest average greenness value occurs in the southern part, then in the northern, and finally the middle part of the research region. In contrast, at the end of the growing season, the largest average greenness value is measured in the northern part, next in the middle and lastly the southern part of the research region. In future studies, these derived NDVI thresholds can be applied to determine the growing season of similar plant communities at other sites, which lack surface phenological data.