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Comparison of Suomi-NPP OMPS total column ozone with Brewer and Dobson spectrophotometers measurements

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Frontiers of Earth Science 2015年第3期9卷 369-380页

作者： Kaixu BAI Chaoshun LIU Runhe SHI Wei GAO Key laboratory of Geographic Information Science (Ministry of Education) East China Normal University Shanghai 200241 China joint laboratory for environmental remote sensing and data assimilation East China Normal University Shanghai 200241 China Department of Ecosystem Science and Sustainability Colorado State University Fort CoUins CO 80523 USA

The objective of this study is to evaluate the accuracy of the daily nadir total column ozone products derived from the nadir mapper instrument on the Ozone Mapping and Profiler Suite （OMPS） flying onboard the Suomi National Polar-orbiting Partnership satellite （S- NPP） launched as a part of the joint Polar Satellite System （JPSS） program between NOAA and NASA. Since NOAA is already operationally processing OMPS nadir total ozone products, evaluations were made in this study on the total column ozone research products generated by NASA＇s science team, utilizing the latest version of their Backscatter Ultraviolet （BUV） retrieval algorithms, to provide insight into the performance of the operation system. Comparisons were made with globally distributed ground-based Brewer and Dobson spectrophotometer total column ozone measurements. Linear regressions show fair agreement between OMPS and ground-based total column ozone measurements with a root-mean-square error （RMSE） of approximately 3% （10 DU）. The comparison results indicate that the OMPS total column ozone data are 0.59% higher than the Brewer measurements with a standard deviation of 2.82% while 1.09% higher than the Dobson measurements with a standard deviation of 3.27%. Additionally, the variability of relative differences between OMPS and ground total column ozone were analyzed as a function of latitude, time, viewing geometry, and total column ozone value. Results show a 2% bias over most latitudes and viewing conditions when total column ozone value varies between 220 DU and 450 DU.

关键词： ozone mapping and profiler suite totalcolumn ozone Brewer Dobson

Vegetation physiological parameter setting in the Simple Biosphere model 2(SiB2) for alpine meadows in the upper reaches of Heihe river

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Science China Earth Sciences 2015年第5期58卷 755-769页

作者： LI Yuan SUN Rui LIU Shao Min State Key laboratory of remote sensing Science Beijing Normal University and Institute of Remote Sensing and Digital Earth CAS School of Geography Beijing Normal University Beijing Key laboratory of environmental remote sensing and City Digitalization Department of Civil Engineering Monash University

Land surface process modeling of high and cold area with vegetation cover has not yielded satisfactory results in previous applications. In this study, land surface energy budget is simulated using a land surface model for the A'rou meadow in the upper-reach area of the Heihe River Basin in the eastern Tibetan Plateau. The model performance is evaluated using the in-situ observations and remotely sensed data. Sensible and soil heat fluxes are overestimated while latent heat flux is underestimated when the default parameter setting is used. By analyzing physical and physiological processes and the sensitivities of key parameters, the inappropriate default setting of optimum growth and inhibition temperatures is identified as an important reason for the bias. The average daytime temperature during the period of fastest vegetation growth(June and July) is adopted as the optimum growth temperature, and the inhibition temperatures were adjusted using the same increment as the optimum temperature based on the temperature acclimation. These adjustments significantly reduced the biases in sensible, latent, and soil heat fluxes.

关键词： SiB2 land surface process alpine meadow Heihe River Basin Tibetan Plateau

Trend analysis for evaluating the consistency of Terra MODIS and SPOT VGT NDVI time series products in China

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Frontiers of Earth Science 2015年第1期9卷 125-136页

作者： Youzhi AN Wei GAO Zhiqiang GAO Chaoshun LIU Runhe SHI Key laboratory of Geographic Information Science Ministry of Education East China Normal University Joint Laboratory for Environmental Remote Sensing and Data Assimilation ECNU & CEODE CAS Shanghai 200062 China Natural Resource Ecology laboratory Colorado State University Fort Collins CO 80523 USA Yantai Institute of Coastal Zone Research Chinese Academy of Sciences Yantai 264003 China

The Normalized Difference Vegetation Index （NDVI） is an important vegetation greenness indicator. Compared to the AVHRR GIMMS NDVI data, the availability of two datasets with 1 km spatial resolution, i.e., Terra MODIS （MODI3A3） monthly composite and SPOT Vegetation （VGT） 10-day composite NDVI, extends the application dimensions at spatial and temporal scales. An overlapping period of 12 years between the datasets now makes it possible to investigate the consistency of the two datasets. Linear regression trend analysis was performed to compare the two datasets in this study. The results show greater consistency in regression slopes in the semi-arid regions of northern China. Alternatively, the results show only slight changes in the Terra MODIS NDVI regression slope in most areas of southern China whereas the SPOT VGT NDVI shows positive changes over a large area. The corresponding regression slope values between Terra MODIS and SPOT VGT NDVI datasets from the linear fit had a fair agreement in the spatial dimension. However, larger positive and negative differences were observed at the junction of the three regions （East China, Central China, and North China）. These differences can be partially explained by the positive standard deviation differences distributed over a large area at the junction of these three regions. This study demonstrated that Terra MODIS and SPOT VGT NDVI have a relatively robust basis for characterizing vegetation changes in annual NDVI in most of the semi-arid and arid regions in northern China.

关键词： Terra MODIS NDV1 SPOT VGT NDVI,trend analysis correlation analysis

Impact of rain-induced sea surface roughness variations on salinity retrieval from the Aquarius/SAC-D satellite

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Acta Oceanologica Sinica 2015年第7期34卷 89-96页

作者： MA Wentao YANG Xiaofeng YU Yang LIU Guihong LI Ziwei JING Cheng College of Physical and environmental Oceanography Ocean University of China State Key laboratory of remote sensing Science Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences

Rainfall has two significant effects on the sea surface, including salinity decreasing and surface becoming rougher, which have further influence on L-band sea surface emissivity. Investigations using the Aquarius and TRMM 3B42 matchup dataset indicate that the retrieved sea surface salinity （SSS） is underestimated by the present Aquarius algorithm compared to numerical model outputs, especially in cases of a high rain rate. For example, the bias between satellite-observed SSS and numerical model SSS is approximately 2 when the rain rate is 25 mm/h. The bias can be eliminated by accounting for rain-induced roughness, which is usually modeled by rain-generated ring-wave spectrum. The rain spectrum will be input into the Small Slope Approximation （SSA） model for the simulation of sea surface emissivity influenced by rain. The comparison with theoretical model indicated that the empirical model of rain spectrumis more suitable to be used in the simulation. Further, the coefficients of the rain spectrum are modified by fitting the simulations with the observations of the 2-year Aquarius and TRMM matchup dataset. The calculations confirm that the sea surface emissivity increases with the wind speed and rain rate. The increase induced by the rain rate is rapid in the case of low rain rate and low wind speed. Finally, a modified model of sea surface emissivity including the rain spectrum is proposed and validated by using the matchup dataset in May 2014. Compared with observations, the bias of the rain-induced sea surface emissivity simulated by the modified modelis approximately le-4, and the RMSE is slightly larger than le-3. With using more matchup data, thebias between model retrieved sea surface salinities and observationsmay be further corrected, and the RMSE may be reduced to less than 1 in the cases of low rain rate and low wind speed.

关键词： Aquarius salinity remote sensing rain L-band emissivity

Derivation of Regression Coefficients for Sea Surface Temperature Retrieval over East Asia

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Advances in Atmospheric Sciences 2006年第3期23卷 474-486页

作者： Myoung-Hwan AHN Eun-Ha SOHN Byong-Jun HWANG Chu-Yong CHUNG Xiangqian WU remote sensing Research laboratory/Meteorological Research Institute Seoul Korea Office of Research and Applications National Environmental Satellite Data and Information Service National Oceanic and Atmospheric Administration

Among the regression-based algorithms for deriving SST from satellite measurements, regionally optimized algorithms normally perform better than the corresponding global algorithm. In this paper, three algorithms are considered for SST retrieval over the East Asia region （15°-55°N, 105°-170°E）, including the multi-channel algorithm （MCSST）, the quadratic algorithm （QSST）, and the Pathfinder algorithm （PFSST）. All algorithms are derived and validated using collocated buoy and Geostationary Meteorological Satellite （GMS-5） observations from 1997 to 2001. An important part of the derivation and validation of the algorithms is the quality control procedure for the buoy SST data and an improved cloud screening method for the satellite brightness temperature measurements. The regionally optimized MCSST algorithm shows an overall improvement over the global algorithm, removing the bias of about -0.13℃ and reducing the root-mean-square difference （rmsd） from 1.36℃ to 1.26℃. The QSST is only slightly better than the MCSST. For both algorithms, a seasonal dependence of the remaining error statistics is still evident. The Pathfinder approach for deriving a season-specific set of coefficients, one for August to October and one for the rest of the year, provides the smallest rmsd overall that is also stable over time.

关键词： Regional SST algorithm GMS-5 data quality control cloud detection

Multi-year monitoring of paddy rice planting area in Northeast China using MODIS time series data

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Journal of Zhejiang University-Science B(Biomedicine & Biotechnology) 2013年第10期14卷 934-946页

作者： Jing-jing SHI Jing-feng HUANG Feng ZHANG Institute of Agricultural remote sensing and Information Application Zhejiang University Key laboratory of Agricultural remote sensing and Information System of Zhejiang Province Ministry of Education Key laboratory of environmental Remediation and Ecological Health Zhejiang University

e The objective of this study was to investigate the tempo-spatial distribution of paddy rice in Northeast China using moderate resolution imaging spectroradiometer （MODIS） data. We developed an algorithm for detection and estimation of the transplanting and flooding periods of paddy rice with a combination of enhanced vegetation index （EVI） and land surface water index with a central wavelength at 2130 nm （LSW12130）. In two intensive sites in Northeast China, fine resolution satellite imagery was used to validate the performance of the algorithm at pixel and 3x3 pixel window levels, respectively. The commission and omission errors in both of the intensive sites were approximately less than 20%. Based on the algorithm, annual distribution of paddy rice in Northeast China from 2001 to 2009 was mapped and analyzed. The results demonstrated that the MODIS-derived area was highly correlated with published agricultural statistical data with a coefficient of determination （R^2） value of 0.847. It also revealed a sharp decline in 2003, especially in the Sanjiang Plain located in the northeast of Heilongjiang Province, due to the oversupply and price decline of rice in 2002. These results suggest that the approaches are available for accurate and reliable monitoring of rice cultivated areas and variation on a large scale.

关键词： Paddy rice Moderate resolution imaging spectroradiometer(MODIS) Northeast China Enhanced vegetation index Land surface water index

Ocean surface current retrieval at Hangzhou Bay from Himawari-8 sequential satellite images

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Science China Earth Sciences 2020年第7期63卷 1026-1038页

作者： Zhenye ZHU Xupu GENG Shihui LI Ting XIE Xiao-Hai YAN State Key laboratory of Marine environmental Science Xiamen 361005China joint Institute for Coastal Research and Management(joint-CRM) University of Delaware/Xiamen UniversityUSA/China Center for remote sensing College of EarthOcean and EnvironmentUniversity of DelawareNewarkDE 19716USA College of Ocean and Earth Sciences Xiamen UniversityXiamen 361005China Fujian Engineering Research Center for Ocean remote sensing Big data(Xiamen University) Xiamen 361005China

Ocean surface currents play a key role in the earth’s *** affect virtually all processes occurring in the ocean and can also directly affect many important socio-economic ***-8 meteorological satellite has an international advanced geostationary orbit imager sensor,AHI,with high time resolution and spatial coverage,Himawari-8 can be used to observe the subtle changes in marine *** this study,we used Himawari-8 data received from the joint Receiving Station for Satellite remote sensing of Xiamen University to retrieve coastal currents in Hangzhou ***,the Maximum Correlation Coefficient(MCC)and the Generalized Hough Transform(GHT)methods were used to retrieve them *** retrieved sea surface currents are analyzed and verified by the numerical model data of the Taiwan Strait current forecasting system(TFOR).The results show that(1)the Himawari-8 satellite data can be used to effectively estimate the ocean current;(2)The results of the two methods are in agreement with each other,and the error in the current measured using the GHT method is smaller in the Yangtze estuary and offshore areas,where the turbidity characteristic front is stronger.

关键词： Himawari-8 Maximum Correlation Coefficient(MCC) Generalized Hough Transform(GHT) Sea surface current

Detecting Agro-Droughts in Southwest of China Using MODIS Satellite data

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Journal of Integrative Agriculture 2013年第1期12卷 159-168页

作者： ZHANG Feng ZHANG Li-wen WANG Xiu-zhen HUNG Jing-feng Institute of Agricultural remote sensing & Information Application Zhejiang University Key laboratory of environmental Remediation and Ecological Health Ministry of Education/College of Natural Resources and Environmental Science Zhejiang University Institute of remote sensing and Earth Sciences Hangzhou Normal University The Provinical Key Laboratories of Agricultural remote sensing and Information System Zhejiang Province

The normalized difference vegetation index （NDVI） has proven to be typically employed to assess terrestrial vegetation conditions. However, one limitation of NDVI for drought monitoring is the apparent time lag between rainfall deficit and NDVI response. To better understand this relationship, time series NDVI （2000-2010） during the growing season in Sichuan Province and Chongqing City were analyzed. The vegetation condition index （VCI） was used to construct a new drought index, time-integrated vegetation condition index （TIVCI）, and was then compared with meteorological drought indices-standardized precipitation index （SPI）, a multiple-time scale meteorological-drought index based on precipitation, to examine the sensitivity on droughts. Our research findings indicate the followings：（1） farmland NDVI sensitivity to precipitation in study area has a time lag of 16-24 d, and it maximally responds to the temperature with a lag of about 16 d. （2） We applied the approach to Sichuan Province and Chongqing City for extreme drought monitoring in 2006 and 2003, and the results show that the monitoring results from TIVCI are closer to the published China agricultural statistical data than VCI. Compared to VCI, the best results from TIVCI3 were found with the relative errors of -4.5 and 6.36% in 2006 for drought affected area and drought disaster area respectively, and 5.11 and -5.95% in 2003. （3） Compared to VCI, TIVCI has better correlation with the SPI, which indicates the lag and cumulative effects of precipitation on vegetation. Our finding proved that TIVCI is an effective indicator of drought detection when the time lag effects between NDVI and climate factors are taken into consideration.

关键词： time-integrated vegetation condition index (TIVCI) time lag normalized difference vegetation index (NDVI) drought monitor standardized precipitation index (SPI)

Vegetation NPP Distribution Based on MODIS data and CASA Model——A Case Study of Northern Hebei Province

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Chinese Geographical Science 2006年第4期16卷 334-341页

作者： YUAN Jinguo NIU Zheng WANG Chenli State Key laboratory of remote sensing Science Institute of Remote Sensing Applications Chinese Academy of Sciences Belting 100101 China College of Resource and environmental Sciences Hebei Normal University Shifiazhuang 050016 China

Net Primary Productivity （NPP） is one of the important biophysical variables of vegetation activity, and it plays an important role in studying global carbon cycle, carbon source and sink of ecosystem, and spatial and temporal distribution of CO2. remote sensing can provide broad view quickly, timely and multi-temporally, which makes it an attractive and powerful tool for studying ecosystem primary productivity, at scales ranging from local to global. This paper aims to use Moderate Resolution Imaging Spectroradiometer （MODIS） data to estimate and analyze spatial and temporal distribution of NPP of the northern Hebei Province in 2001 based on Carnegie-Ames-Stanford Approach （CASA） model. The spatial distribution of Absorbed Photosynthetically Active Radiation （APAR） of vegetation and light use efficiency in three geographical subregions, that is, Bashang Plateau Region, Basin Region in the northwestern Hebei Province and Yanshan Mountainous Region in the Northern Hebei Province were analyzed, and total NPP spatial distribution of the study area in 2001 was discussed. Based on 16-day MODIS Fraction of Photosynthetically Active Radiation absorbed by vegetation （FPAR） product, 16-day composite NPP dynamics were calculated using CASA model; the seasonal dynamics of vegetation NPP in three subreglons were also analyzed. Result reveals that the total NPP of the study area in 2001 was 25.1877 × 10^6gC/（m^2.a）, and NPP in 2001 ranged from 2 to 608gC/（m^2-a）, with an average of 337.516gC/（m^2.a）. NPP of the study area in 2001 accumulated mainly from May to September （DOY 129-272）, high NIP values appeared from June to August （DOY 177-204）, and the maximum NPP appeared from late July to mid-August （DOY 209-224）.

关键词： NPP distribution MODIS data CASA model Northvrn Hebei Province