Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites

Beijing, China

Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites

Beijing, China
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Hou P.,Satellite Environment Center | Hou P.,Beijing Normal University | Chen Y.,Beijing Normal University | Qiao W.,Satellite Environment Center | And 3 more authors.
Theoretical and Applied Climatology | Year: 2013

Near-surface air temperature (NSAT) directly reflects the thermal conditions above the ground and has been considered as a relevant indicator of resident health in urban regions. The rapid retrieval of NSAT data is necessary to assess urban environments. In this paper, a method of NSAT retrieval is developed that employs Landsat Thematic Mapper images using an Energy Balance Bowen Ratio model. This model is established based on the energy balance over land and the Bowen ratio. The degree of retrieval error obtained when using this model is determined on the basis of a comparison with the observed values obtained from weather stations; the mean error is approximately 2. 21 °C. Moreover, the spatial relationship between NSAT and urban wetlands is analyzed using Geographical Information System technology. The results show that wetlands have an obvious influence on atmospheric temperature and that this influence decreases as the distance from the wetland increases. When that distance is less than 300 m, its influence on the NSAT is significant. © 2012 Springer-Verlag.


Hou P.,Satellite Environment Center | Hou P.,Beijing Normal University | Jiang W.,Beijing Normal University | Cao G.,Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites | Li J.,Beijing Normal University
International Journal of Remote Sensing | Year: 2012

Human activity is one of the most important aerosol sources. Because the underlaying surface feature records most human activities, it is important to recognize the correlation between aerosol distribution and the underlaying surface. In this research, the dark object algorithm and a second-generation operational algorithm of Moderate-Resolution Imaging Spectroradiometer (MODIS) aerosol retrieval are used to estimate aerosol optical depth from Enhanced Thematic Mapper Plus (ETM+) images acquired by the Landsat 7 satellite system in urban regions, and the correlations between aerosol distribution and urban underlaying surface features (including landform, land cover and urbanization level) is analysed. Results show that (1) it is feasible to apply a second-generation algorithm to retrieve aerosol optical depth with ETM+ images. When a validation is performed with the ground observation meteorological range converted into aerosol optical depth with the correlation model acquired by a Moderate-Resolution Atmospheric Transmission (MODTRAN) simulation, the retrieval error is about 0.0094. For higher spatial resolution of an ETM+ image, it is better to study the aerosol distribution features in the urban regions. Additionally, (2) there are obvious variations in spatial distribution of aerosol over the different features of the underlaying surface. For the landform, aerosol optical depth is mountain < hill > plain; for the land cover, aerosol optical depth is dense vegetation < sparse vegetation < water < bare soil > residential area; for the different urbanization-level regions, there is bigger and bigger aerosol optical depth with increasing of the urbanization level. On the whole, as human activities increase, so too does the aerosol optical depth. © 2012 Taylor and Francis Group, LLC.


Zhang X.,Nanjing University of Information Science and Technology | Guo Y.,Nanjing University of Information Science and Technology | Yang C.,Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites
Journal of Computational Information Systems | Year: 2013

In order to study the effect of clouds on meteorological satellite communications under cloudy conditions, the shadowing effect and multipath effect of the clouds on meteorological satellite signal are as a static composite channel effect, the probability density function and bit error rate function of the static composite channel are given. Meteorological satellite composite channel simulation model is established, the fading of the reception signal in the composite channel is divided into three cases of mild fading, moderate fading and severe fading. The results of computer experiments indicate that the probability density curves and bit error rate curves function of the received signal in the simulation model are quite consistent with the theory model, and demonstrate it is an accurate and efficient method. © 2013 by Binary Information Press.


Chen L.,Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites | Chen L.,National Satellite Meteorology Center | Hu X.,Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites | Hu X.,National Satellite Meteorology Center | And 4 more authors.
Remote Sensing | Year: 2013

Based on simulated reflectance, deep convective clouds (DCC) can be used as an invariant target to monitor the radiometric response degradation of the FY-3A/MERSI (Medium Resolution Spectral Imager) reflective solar bands (RSBs). The long-term response of the MERSI RSBs can easily be predicted using a quadratic fit of the monthly DCC mean reflectance, except for bands 6 and 7, which suffer from instrument anomalies. DCC-based degradations show that the blue bands (λ < 500 nm) and water-vapor bands have degraded significantly, whereas for near-infrared bands, the total degradations in four years are within 3% (excluding bands 3 and 20). For most bands, the degradation rates are greatest during the first year in orbit and decrease over time. The FY-3A/MERSI degradation results derived from DCC are consistent within 2.5%, except for bands, 11, 18 and 19, when compared with Aqua/MODIS(Moderate Resolution Imaging Sepetroradiometer) inter-calibration, multi-site invariant earth target calibration and the CRCS(Chinese Radiometric Calibration Site) Dunhuang desert vicarious calibration methods. Overall, the 2σ/mean degradation uncertainty for most MERSI bands was within 3%, validating the temporal stability of the DCC monthly mean reflectances. The DCC method has reduced the degradation uncertainties for MERSI water vapor bands over other methods. This is asignificant advantage of the DCC calibration method. The saturation of some MERSI bands may hinder the effectiveness of the DCC calibration approach. © 2013 by the authors.


Cui T.,State Oceanic Administration | Zhang J.,State Oceanic Administration | Groom S.,Plymouth Marine Laboratory | Sun L.,Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites | And 3 more authors.
Remote Sensing of Environment | Year: 2010

An extensive in situ data set in the Bohai Sea of China was collected to assess radiometric properties and concentrations of ocean constituents derived from Medium Resolution Imaging Spectrometer (MERIS). The data collected include spectral normalized water-leaving radiance Lwn(λ) and concentrations of suspended particulate matter (SPM) and chlorophyll a (Chl-a). A strict spatio-temporal match-up method was adopted in view of the complexity and variability of the turbid coastal area, resulting in 13, 48 and 18 match-ups for MERIS Lwn(λ), SPM and Chl-a estimates, respectively. For MERIS Lwn(λ), the match-ups showed mean absolute percentage differences (APD) of 17%-20% in the 412, 443, 620 and 665nm bands, whereas Lwn(λ) at bands from 490 and 560nm had better APD of 15-16%. The band ratio of Lwn(490) to Lwn(560) of the satellite data was in good agreement with in situ observations with an APD of 4%. MERIS SPM and Chl-a products overestimated the in situ values, with the APD of approximately 50% and 60%, respectively. When match-up criteria were relaxed, the assessment results degraded systematically. Hence, in turbid coastal areas where temporal variability and spatial heterogeneity of bio-optical properties may be pronounced as the result of terrestrial influences and local dynamics, the strict spatio-temporal match-up is recommended. © 2010 Elsevier Inc.


Hou P.,Satellite Environment Application Center | Wang Q.,Satellite Environment Application Center | Cao G.,Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites | Wang C.,Satellite Environment Application Center | And 2 more authors.
Journal of Geographical Sciences | Year: 2012

Terrestrial ecosystem and climate system are closely related to each other. Faced with the unavoidable global climate change, it is important to investigate terrestrial ecosystem responding to climate change. In inland river basin of arid and semi-arid regions in China, sensitivity difference of vegetation responding to climate change from 1998 to 2007 was analyzed in this paper. (1) Differences in the global spatio-temporal distribution of vegetation and climate are obvious. The vegetation change shows a slight degradation in this whole region. Degradation is more obvious in densely vegetated areas. Temperature shows a general downward trend with a linear trend coefficient of -1.1467. Conversely, precipitation shows an increasing trend with a linear trend coefficient of 0. 3896. (2) About the central tendency response, there are similar features in spatial distribution of both NDVI responding to precipitation (NDVI-P) and NDVI responding to AI (NDVI-AI), which are contrary to that of NDVI responding to air temperature (NDVI-T). Typical sensitivity region of NDVI-P and NDVI-AI mainly covers the northern temperate arid steppe and the northern temperate desert steppe. NDVI-T typical sensitivity region mainly covers the northern temperate desert steppe. (3) Regarding the fluctuation amplitude response, NDVI-T is dominated by the lower sensitivity, typical regions of the warm temperate shrubby, selui-shrubby, bare extreme dry desert, and northern temperate meadow steppe in the east and temperate semi-shrubby, dwarf arboreous desert in the north are high response. (4) Fluctuation amplitude responses between NDVI-P and NDVI-AI present a similar spatial distribution. The typical sensitivity region mainly covers the northern temperate desert steppe. There are various linear change trend responses of NDVI-T, NDVI-P and NDVI-AI. As to the NDVI-T and NDVI-AI, which are influenced by the boundary effect of semi-arid and semi-humid climate zones, there is less correlation of their linear change tendency along the border. There is stronger correlation in other regions, especially in the NDVI-T in the northern temperate desert steppe and NDVI-AI in the warm temperate shrubby, selui-shrubby, bare, extreme and dry desert. © 2012 Science China Press and Springer-Verlag Berlin Heidelberg.


Fang Y.,Beijing Climate Center | Zhang Y.,Nanjing University | Huang A.,Nanjing University | Li B.,Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites
Advances in Atmospheric Sciences | Year: 2013

The performance of a regional air-sea coupled model, comprising the Regional Integrated Environment Model System (RIEMS) and the Princeton Ocean Model (POM), in simulating the seasonal and intraseasonal variations of East Asian summer monsoon (EASM) rainfall was investigated. Through comparisons of the model results among the coupled model, the uncoupled RIEMS, and observations, the impact of air-sea coupling on simulating the EASM was also evaluated. Results showed that the regional air-sea coupled climate model performed better in simulating the spatial pattern of the precipitation climatology and produced more realistic variations of the EASM rainfall in terms of its amplitude and principal EOF modes. The coupled model also showed greater skill than the uncoupled RIEMS in reproducing the principal features of climatological intraseasonal oscillation (CISO) of EASM rainfall, including its dominant period, intensity, and northward propagation. Further analysis indicated that the improvements in the simulation of the EASM rainfall climatology and its seasonal variation in the coupled model were due to better simulation of the western North Pacific Subtropical High, while the improvements of CISO simulation were owing to the realistic phase relationship between the intraseasonal convection and the underlying SST resulting from the air-sea coupling. © 2013 Chinese National Committee for International Association of Meteorology and Atmospheric Sciences, Institute of Atmospheric Physics, Science Press and Springer-Verlag Berlin Heidelberg.


Zhang Y.,Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites | Li Y.,Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites | Rong Z.-G.,Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites
Guang Pu Xue Yu Guang Pu Fen Xi/Spectroscopy and Spectral Analysis | Year: 2010

Remote sensors' channel spectral response function (SRF) was one of the key factors to influence the quantitative products' inversion algorithm, accuracy and the geophysical characteristics. Aiming at the adjustments of FY-2E's split window channels' SRF, detailed comparisons between the FY-2E and FY-2C corresponding channels' SRF differences were carried out based on three data collections: the NOAA AVHRR corresponding channels' calibration look up tables, field measured water surface radiance and atmospheric profiles at Lake Qinghai and radiance calculated from the PLANK function within all dynamic range of FY-2E/C. The results showed that the adjustments of FY-2E's split window channels' SRF would result in the spectral range's movements and influence the inversion algorithms of some ground quantitative products. On the other hand, these adjustments of FY-2E SRFs would increase the brightness temperature differences between FY-2E's two split window channels within all dynamic range relative to FY-2C's. This would improve the inversion ability of FY-2E's split window channels.


Wang Y.-Y.,Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites | Li G.-C.,Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites | Zhang L.-J.,Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites | Fan J.-L.,Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites
Guang Pu Xue Yu Guang Pu Fen Xi/Spectroscopy and Spectral Analysis | Year: 2010

Accurate estimation of leaf water content (LWC) from remote sensing can assist in determining vegetation physiological status, and further has important implications for drought monitoring and fire risk evaluation. This paper focuses on retrieving LWC from canopy spectra of winter wheat measured with ASD FieldSpec Pro. The experimental plots were treated with five levels of irrigation (0, 200, 300, 400 and 500 mm) in growing season, and each treatment had three replications. Canopy spectra and LWC were collected at three wheat growth stages (booting, flowering, and milking). The temporal variations of LWC, spectral reflectance, and their correlations were analyzed in detail. Partial least square regression embedded iterative feature-eliminating was designed and employed to obtain diagnostic bands and build prediction models for each stage. The results indicate that LWC decreases quickly along with the winter wheat growth. The mean values of LWC for the three stages are respectively 338.49%, 269.65%, and 230.90%. The spectral regions correlated strongly with LWC are 1587-1662 and 1692-132 nm (booting), 617-687 and 1447-1467 nm (flowering), and 1457-1557 nm (milking). As far as the LWC prediction models are concerned, the optimum modes of spectral data are respectively logarithmic, 1st order derivative and plain reflectance. The diagnostic bands detected by PLS are from SWIR, NIR, and SWIR. Retrieval accuracy at the flowering stage is the highest (Rcv 2=0.889) due to the enhancement of leaf water information at canopy scale via multiple scattering. At the booting and milking stage, accuracies are relatively lower (Rcv 2=0.750, 0.696), because the retrieval of LWC is negatively affected by soil background and dry matter absorption respectively. This research demonstrated clearly that the spectral response and retrieval of LWC has distinct temporal characteristics, which should not be neglected when developing remote sensing product of crop water content in the future.


Xu N.,Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites | Xu N.,National Satellite Meteorological Center | Chen L.,Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites | Chen L.,National Satellite Meteorological Center | And 4 more authors.
Remote Sensing | Year: 2014

FengYun-3 (FY-3) Visible Infrared Radiometer (VIRR), along with its predecessor, Multispectral Visible Infrared Scanning Radiometer (MVISR), onboard FY-1C&D have had continuous global observation more than 14 years. This data record is valuable for weather prediction, climate monitoring, and environment research. Data quality is vital for satellite data assimilations in Numerical Weather Prediction (NWP) and quantitative remote sensing applications. In this paper, the accuracies of radiometric calibration for VIRR onboard FY-3A and FY-3B, in thermal infrared (TIR) channels, are evaluated using the Low Earth Orbit (LEO)-LEO simultaneous nadir overpass intercalibration method. Hyperspectral and high-quality observations from Infrared Atmosphere Sounding Instrument (IASI) onboard METOP-A are used as reference. The biases of VIRR measurements with respect to IASI over one-and-a-half years indicate that the TIR calibration accuracy of FY-3B VIRR is better than that of FY-3A VIRR. The brightness temperature (BT) measured by FY-3A/VIRR is cooler than that measured by IASI with monthly mean biases ranging from -2 K to -1 K for channel 4 and -1 K to 0.2 K for channel 5. Measurements from FY-3B/VIRR are more consistent with that from IASI, and the annual mean biases are 0.84 ± 0.16 K and -0.66 ± 0.18 K for channels 4 and 5, respectively. The BT biases of FY-3A/VIRR show scene temperature-dependence and seasonal variation, which are not found from FY-3B/VIRR BT biases. The temperature-dependent biases are shown to be attributed to the nonlinearity of detectors.New nonlinear correction coefficients of FY-3A/VIRR TIR channels are reevaluated using various collocation samples. Verification results indicate that the use of the new nonlinear correction can greatly correct the scene temperature-dependent and systematic biases. © 2014 by the authors; licensee MDPI, Basel, Switzerland.

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