With remote sensing information products becoming increasingly varied and arguably improved, scientific applications of such products rely on their quality assessment. In an operational context such as the NASA (Natio...With remote sensing information products becoming increasingly varied and arguably improved, scientific applications of such products rely on their quality assessment. In an operational context such as the NASA (National Aeronautics and Space Administration) information production based on the MODIS (Moderate Resolution Imaging Spectroradiometer) instrument on board Earth Observing System (EOS) Terra and Aqua satellites, efficient ways of detecting product anomaly, i.e., to discriminate between product artifacts and real changes in Earth processes being monitored, are extremely important to assist and inform the user communities about potential unreliability in the products. A technique for anomaly detection, known as MAD (the median of absolute deviate from the median), in MODIS land products via time series analysis is described, which can handle intra- and in-ter-annual variation in the data by using MAD statistics of the original data and their first-order difference. This method is shown to be robust and work across major land products, including NDVI, active fire, snow cover, and surface reflectance, and its applicabil-ity to multi-disciplinary products is anticipated.展开更多
In atmospheric data assimilation systems, the forecast error covariance model is an important component. However, the paralneters required by a forecast error covariance model are difficult to obtain due to the absenc...In atmospheric data assimilation systems, the forecast error covariance model is an important component. However, the paralneters required by a forecast error covariance model are difficult to obtain due to the absence of the truth. This study applies an error statistics estimation method to the Pfiysical-space Statistical Analysis System （PSAS） height-wind forecast error covariance model. This method consists of two components： the first component computes the error statistics by using the National Meteorological Center （NMC） method, which is a lagged-forecast difference approach, within the framework of the PSAS height-wind forecast error covariance model; the second obtains a calibration formula to rescale the error standard deviations provided by the NMC method. The calibration is against the error statistics estimated by using a maximum-likelihood estimation （MLE） with rawindsonde height observed-minus-forecast residuals. A complete set of formulas for estimating the error statistics and for the calibration is applied to a one-month-long dataset generated by a general circulation model of the Global Model and Assimilation Office （GMAO）, NASA. There is a clear constant relationship between the error statistics estimates of the NMC-method and MLE. The final product provides a full set of 6-hour error statistics required by the PSAS height-wind forecast error covariance model over the globe. The features of these error statistics are examined and discussed.展开更多
NASA is developing the Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission to provide accurate measurements to substantially improve understanding of climate change. CLARREO will include a Reflect...NASA is developing the Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission to provide accurate measurements to substantially improve understanding of climate change. CLARREO will include a Reflected Solar (RS) Suite, an Infrared (IR) Suite, and a Global Navigation Satellite System-Radio Occultation (GNSS-RO). The IR Suite consists of a Fourier Transform Spectrometer (FTS) covering 5 to 50 micrometers (2000-200 cm-1 wavenumbers) and on-orbit calibration and verification systems. The IR instrument will use a cavity blackbody view and a deep space view for on-orbit calibration. The calibration blackbody and the verification system blackbody will both have Phase Change Cells (PCCs) to accurately provide a SI reference to absolute temperature. One of the most critical parts of obtaining accurate CLARREO IR scene measurements relies on knowing the spectral radiance output from the blackbody calibration source. The blackbody spectral radiance must be known with a low uncertainty, and the magnitude of the uncertainty itself must be reliably quantified. This study focuses on determining which parameters in the spectral radiance equation of the calibration blackbody are critical to the blackbody accuracy. Fourteen parameters are identified and explored. Design of Experiments (DOE) is applied to systematically set up an experiment (i.e., parameter settings and number of runs) to explore the effects of these 14 parameters. The experiment is done by computer simulation to estimate uncertainty of the calibration blackbody spectral radiance. Within the explored ranges, only 4 out of 14 parameters were discovered to be critical to the total uncertainty in blackbody radiance, and should be designed, manufactured, and/or controlled carefully. The uncertainties obtained by computer simulation are also compared to those obtained using the “Law of Propagation of Uncertainty”. The two methods produce statistically different uncertainties. Nevertheless, the differences are small and are not considered to be important. A follow-up study has been planned to examine the total combined uncertainty of the CLARREO IR Suite, with a total of 47 contributing parameters. The DOE method will help in identifying critical parameters that need to be effectively and efficiently designed to meet the stringent IR measurement accuracy requirements within the limited resources.展开更多
The epidemiology of many rodent-borne diseases in South-East Asia remains ill-defined.Scrub typhus and lep-tospirosis are common and medically significant,while other zoonotic diseases,such as spotted fever group Rick...The epidemiology of many rodent-borne diseases in South-East Asia remains ill-defined.Scrub typhus and lep-tospirosis are common and medically significant,while other zoonotic diseases,such as spotted fever group Rickettsiae have been identified,but their overall medical significance is unknown.Rodent surveillance was con-ducted from June 2002 to July 2004 in 18 provinces from Thailand.Traps were set up for one to three nights.Blood and serum samples and animal tissue samples(liver,spleen,kidney and urinary bladder)were collected.Chigger-mites,ticks and fleas were removed from captured rodents.Atotal of 4536 wild-caught rodents from 27 species were captured over two years of animal trapping.Rattus rattus was the dominant species,followed by Rattus exulans and Bandicota indica.Almost 43000 ectoparasites were removed from the captured animals.Approximately 98%of the ectoparasites were chigger-mites,of which 46%belonged to the genus Leptotrombidium(scrub typhus vector).Other genera included Schoengastia and Blankaartia.Tick and flea specimens together comprised less than 1%of the sample.Among the five species of ticks collected,Haemaphysalis bandicota was the predominant species caught,followed by Ixodes granulatus other Haemaphysalis spp.,Rhipicephalus spp.and Dermacentor spp.Only two species of fleas were collected and Xenopsylla cheopis(rat flea)was the predominant species.Using both commercial diagnostic kits and in-house molecular assays,animal tissue samples were examined and screened for zoonotic diseases.Seven zoonotic diseases were detected:scrub typhus,leptospirosis,murine typhus,tick typhus,bartonella,babesiosis and trypanosomiasis.Most samples were positive for scrub typhus.Other zoonotic diseases still under investigation include borrelosis,ehrlichiosis,the plague,and other rickettsial diseases.Using geo-graphic information systems,global positioning systems and remote sensing technology,epidemiological and environmental data were combined to assess the relative risk in different biotopes within highly endemic areas of scrub typhus in Thailand.展开更多
With the advancement of Lidar technology,bottom depth(H)of optically shallow waters(OSW)can be measured accurately with an airborne or space-borne Lidar system(H_(Lidar) hereafter),but this data product consists of a ...With the advancement of Lidar technology,bottom depth(H)of optically shallow waters(OSW)can be measured accurately with an airborne or space-borne Lidar system(H_(Lidar) hereafter),but this data product consists of a line format,rather than the desired charts or maps,particularly when the Lidar system is on a satellite.Meanwhile,radiometric measurements from multiband imagers can also be used to infer H(H_(imager) hereafter)of OSW with variable accuracy,though a map of bottom depth can be obtained.It is logical and advantageous to use the two data sources from collocated measurements to generate a more accurate bathymetry map of OSW,where usually image-specific empirical algorithms are developed and applied.Here,after an overview of both the empirical and semianalytical algorithms for the estimation of H from multiband imagers,we emphasize that the uncertainty of H_(imager) varies spatially,although it is straightforward to draw regressions between H_(Lidar) and radiometric data for the generation of H_(imager).Further,we present a prototype system to map the confidence of H_(imager) pixel-wise,which has been lacking until today in the practices of passive remote sensing of bathymetry.We advocate the generation of a confidence measure in parallel with H_(imager),which is important and urgent for broad user communities.展开更多
Data from the Moderate Resolution Imaging Spectro-radiometer(MODIS)on-board the Earth Observing System Terra and Aqua satellites are processed using a land water mask to determine when an algorithm no longer needs to ...Data from the Moderate Resolution Imaging Spectro-radiometer(MODIS)on-board the Earth Observing System Terra and Aqua satellites are processed using a land water mask to determine when an algorithm no longer needs to be run or when an algorithm needs to follow a different pathway.Entering the fourth reprocessing(Collection 6(C6))the MODIS team replaced the 1 km water mask with a 500 m water mask for improved representation of the continental surfaces.The new water mask represents more small water bodies for an overall increase in water surface from 1%to 2%of the continental surface.While this is still a small fraction of the overall global surface area the increase is more dramatic in certain areas such as the Arctic and Boreal regions where there are dramatic increases in water surface area in the new mask.MODIS products generated by the on-going C6 reprocessing using the new land water mask show significant impact in areas with high concentrations of change in the land water mask.Here differences between the Collection 5(C5)and C6 water masks and the impact of these differences on the MOD04 aerosol product and the MOD11 land surface temperature product are shown.展开更多
基金Funded by the National 973 Program of China(No.2006CB701302).
文摘With remote sensing information products becoming increasingly varied and arguably improved, scientific applications of such products rely on their quality assessment. In an operational context such as the NASA (National Aeronautics and Space Administration) information production based on the MODIS (Moderate Resolution Imaging Spectroradiometer) instrument on board Earth Observing System (EOS) Terra and Aqua satellites, efficient ways of detecting product anomaly, i.e., to discriminate between product artifacts and real changes in Earth processes being monitored, are extremely important to assist and inform the user communities about potential unreliability in the products. A technique for anomaly detection, known as MAD (the median of absolute deviate from the median), in MODIS land products via time series analysis is described, which can handle intra- and in-ter-annual variation in the data by using MAD statistics of the original data and their first-order difference. This method is shown to be robust and work across major land products, including NDVI, active fire, snow cover, and surface reflectance, and its applicabil-ity to multi-disciplinary products is anticipated.
文摘In atmospheric data assimilation systems, the forecast error covariance model is an important component. However, the paralneters required by a forecast error covariance model are difficult to obtain due to the absence of the truth. This study applies an error statistics estimation method to the Pfiysical-space Statistical Analysis System （PSAS） height-wind forecast error covariance model. This method consists of two components： the first component computes the error statistics by using the National Meteorological Center （NMC） method, which is a lagged-forecast difference approach, within the framework of the PSAS height-wind forecast error covariance model; the second obtains a calibration formula to rescale the error standard deviations provided by the NMC method. The calibration is against the error statistics estimated by using a maximum-likelihood estimation （MLE） with rawindsonde height observed-minus-forecast residuals. A complete set of formulas for estimating the error statistics and for the calibration is applied to a one-month-long dataset generated by a general circulation model of the Global Model and Assimilation Office （GMAO）, NASA. There is a clear constant relationship between the error statistics estimates of the NMC-method and MLE. The final product provides a full set of 6-hour error statistics required by the PSAS height-wind forecast error covariance model over the globe. The features of these error statistics are examined and discussed.
文摘NASA is developing the Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission to provide accurate measurements to substantially improve understanding of climate change. CLARREO will include a Reflected Solar (RS) Suite, an Infrared (IR) Suite, and a Global Navigation Satellite System-Radio Occultation (GNSS-RO). The IR Suite consists of a Fourier Transform Spectrometer (FTS) covering 5 to 50 micrometers (2000-200 cm-1 wavenumbers) and on-orbit calibration and verification systems. The IR instrument will use a cavity blackbody view and a deep space view for on-orbit calibration. The calibration blackbody and the verification system blackbody will both have Phase Change Cells (PCCs) to accurately provide a SI reference to absolute temperature. One of the most critical parts of obtaining accurate CLARREO IR scene measurements relies on knowing the spectral radiance output from the blackbody calibration source. The blackbody spectral radiance must be known with a low uncertainty, and the magnitude of the uncertainty itself must be reliably quantified. This study focuses on determining which parameters in the spectral radiance equation of the calibration blackbody are critical to the blackbody accuracy. Fourteen parameters are identified and explored. Design of Experiments (DOE) is applied to systematically set up an experiment (i.e., parameter settings and number of runs) to explore the effects of these 14 parameters. The experiment is done by computer simulation to estimate uncertainty of the calibration blackbody spectral radiance. Within the explored ranges, only 4 out of 14 parameters were discovered to be critical to the total uncertainty in blackbody radiance, and should be designed, manufactured, and/or controlled carefully. The uncertainties obtained by computer simulation are also compared to those obtained using the “Law of Propagation of Uncertainty”. The two methods produce statistically different uncertainties. Nevertheless, the differences are small and are not considered to be important. A follow-up study has been planned to examine the total combined uncertainty of the CLARREO IR Suite, with a total of 47 contributing parameters. The DOE method will help in identifying critical parameters that need to be effectively and efficiently designed to meet the stringent IR measurement accuracy requirements within the limited resources.
文摘The epidemiology of many rodent-borne diseases in South-East Asia remains ill-defined.Scrub typhus and lep-tospirosis are common and medically significant,while other zoonotic diseases,such as spotted fever group Rickettsiae have been identified,but their overall medical significance is unknown.Rodent surveillance was con-ducted from June 2002 to July 2004 in 18 provinces from Thailand.Traps were set up for one to three nights.Blood and serum samples and animal tissue samples(liver,spleen,kidney and urinary bladder)were collected.Chigger-mites,ticks and fleas were removed from captured rodents.Atotal of 4536 wild-caught rodents from 27 species were captured over two years of animal trapping.Rattus rattus was the dominant species,followed by Rattus exulans and Bandicota indica.Almost 43000 ectoparasites were removed from the captured animals.Approximately 98%of the ectoparasites were chigger-mites,of which 46%belonged to the genus Leptotrombidium(scrub typhus vector).Other genera included Schoengastia and Blankaartia.Tick and flea specimens together comprised less than 1%of the sample.Among the five species of ticks collected,Haemaphysalis bandicota was the predominant species caught,followed by Ixodes granulatus other Haemaphysalis spp.,Rhipicephalus spp.and Dermacentor spp.Only two species of fleas were collected and Xenopsylla cheopis(rat flea)was the predominant species.Using both commercial diagnostic kits and in-house molecular assays,animal tissue samples were examined and screened for zoonotic diseases.Seven zoonotic diseases were detected:scrub typhus,leptospirosis,murine typhus,tick typhus,bartonella,babesiosis and trypanosomiasis.Most samples were positive for scrub typhus.Other zoonotic diseases still under investigation include borrelosis,ehrlichiosis,the plague,and other rickettsial diseases.Using geo-graphic information systems,global positioning systems and remote sensing technology,epidemiological and environmental data were combined to assess the relative risk in different biotopes within highly endemic areas of scrub typhus in Thailand.
基金support by the Chinese Ministry of Science and Technology through the National Key Research and Development Program of China(#2016YFC1400904 and#2016YFC1400905)the National Natural Science Foundation of China(#41941008,#41890803,and#41830102)the Joint Polar Satellite System(JPSS)funding for the NOAA ocean color calibration and validation(Cal/Val)project。
文摘With the advancement of Lidar technology,bottom depth(H)of optically shallow waters(OSW)can be measured accurately with an airborne or space-borne Lidar system(H_(Lidar) hereafter),but this data product consists of a line format,rather than the desired charts or maps,particularly when the Lidar system is on a satellite.Meanwhile,radiometric measurements from multiband imagers can also be used to infer H(H_(imager) hereafter)of OSW with variable accuracy,though a map of bottom depth can be obtained.It is logical and advantageous to use the two data sources from collocated measurements to generate a more accurate bathymetry map of OSW,where usually image-specific empirical algorithms are developed and applied.Here,after an overview of both the empirical and semianalytical algorithms for the estimation of H from multiband imagers,we emphasize that the uncertainty of H_(imager) varies spatially,although it is straightforward to draw regressions between H_(Lidar) and radiometric data for the generation of H_(imager).Further,we present a prototype system to map the confidence of H_(imager) pixel-wise,which has been lacking until today in the practices of passive remote sensing of bathymetry.We advocate the generation of a confidence measure in parallel with H_(imager),which is important and urgent for broad user communities.
基金funded in part by National Aeronautics and Space Administration(NASA)Terrestrial Ecology program Grant/Cooperative Agreement Number:#NNX08AT97ANASA MEaSURES program Grant/Cooperative Agreement Number:#NNX13AJ35ANASA EOS Grant/Cooperative Agreement Number:#NNX14AJ33G.
文摘Data from the Moderate Resolution Imaging Spectro-radiometer(MODIS)on-board the Earth Observing System Terra and Aqua satellites are processed using a land water mask to determine when an algorithm no longer needs to be run or when an algorithm needs to follow a different pathway.Entering the fourth reprocessing(Collection 6(C6))the MODIS team replaced the 1 km water mask with a 500 m water mask for improved representation of the continental surfaces.The new water mask represents more small water bodies for an overall increase in water surface from 1%to 2%of the continental surface.While this is still a small fraction of the overall global surface area the increase is more dramatic in certain areas such as the Arctic and Boreal regions where there are dramatic increases in water surface area in the new mask.MODIS products generated by the on-going C6 reprocessing using the new land water mask show significant impact in areas with high concentrations of change in the land water mask.Here differences between the Collection 5(C5)and C6 water masks and the impact of these differences on the MOD04 aerosol product and the MOD11 land surface temperature product are shown.
