GPM is designed to provide the next generation of global satellite precipitation products after TRMM,whose core observation platform has been launched on February 28,2014.The satellite constellation currently consists of 10 satellites,which is likely to expand in the future.To date,however,the latest paper devoted to the GPM mission and its newest products still lack in China.GPM precipitation products are divided into four levels with higher accuracy,greater coverage,higher spatial and temporal resolution compared with previous satellite precipitation products.Particularly,GPM can provide rain and snow data within three hours based on microwave or half hour based on microwave\|IR IMERG algorithm,and is anticipated to promote the development of a multitude of disciplines like hydrology,meteorology,agriculture,and disaster.Compared with the TRMM which focus on the observation of precipitation in tropical and subtropical regions,GPM can capture light rainfall (<0.5 mm·h-1) and solid precipitation more accurately,both critical precipitation types for the high\|latitude and high\|altitude regions.In this paper,we elaborated the GPM core observation,algorithm and products,ground verification and potential application prospects of the GPM mission,aiming to promote global precipitation related research and applications in China.
An explanation of endmember based on physics,algebra and geometry is described.And a classification,with three categories,of endmember extraction algorithms based on algorithm design theory is provided,namely,endmember extraction algorithms designed based on geometry,endmember extraction algorithms designed based on statistics and signal detection theory,and endmember extraction algorithms designed based on combination of spectral and spatial information.Furthmore,the category based on geometry can be subdivided into four conditions according to the different techniques,that is,distance,volume,projection and transformation,optimization.Owing to the classification of endmember extraction algorithms,the defects and improved techniques,research progress of some commonly endmember extraction algorithms including PPI,N\|Findr,UOSP,VCA,ICA,NMF,and AMEE are described.At last,from the point of view on engineering application of hyperspectral remote sensing and the development of unmixing theory,two research prospects on endmember extraction algorithm are pointed out.One prospect is combination of all different techniques used in endmember extraction,and the other is the performance optimization of existing algorithms.
A Classified Split\|Window(C\|SW)algorithm is developed to retrieve Land Surface Temperature(LST)from the thermal infrared data observed by the Multifunctional Transport Satellites\|1R(MTSAT\|1R)using atmospheric radiative transfer model MODTRAN 4.0 and Thermodynamic Initial Guess Retrieval(TIGR)clear\|sky atmospheric profile data.The coefficients of the C\|SW algorithm are divided into several groups according to different ranges of the three parameters,i.e.the atmospheric water vapor content,the land surface emissivity and the satellite zenith viewing angle.The method is applied to the upstream and midstream region of the Heihe river basin.The errors of the LST retrieval caused by the uncertainties of instrument noises,land surface emissivity and atmospheric water vapor content are analyzed.Finally,the retrieved LST from MTSAT\|1R is compared with the simulation data,the ground observations and MODIS LST products over the whole study area and at the experimental sites.The results indicate that the accuracy of LST retrieval is less than 1 K when the sensor viewing zenith angle is close to nadir or atmospheric water vapor is less than 2.5 g/cm2.The comparison between the estimated LST and the in\|situ measurements show that the root mean squared errors(RMSE)are 3.7 K(daytime)/1.4 K(nighttime)at Arou site and 2.4 K(daytime)/2.0 K(nighttime)at Yingke site,respectively.Moreover,the comparison with MODIS products shows consistent spatial pattern over the study area.As a conclusion,the proposed classified split\|window algorithm can be successfully applied to the LST retrievals from MTSAT\|1R data over the study area.
Hyperspectral remote sensing data is one of effective ways which can be used to retrieve salinity quantitatively in soil monitoring.But the quantitative structure-property relationship between soil salinity and soil spectral reflection characters has not been found in yellow river delta region.Genetic Algorithm with Partial Least Square kernel(GA-PLS)method is applied to mine spectral features of volumetric moisture content(V%)and Electrical Conductivity(EC)using the in-stu salinity soil sampling in Yellow River Delta region.MC simulation result shows GA-PLS method mines stable characters numbers and fitness under different of water\|salt level,which prove the robustness of the algorithm.Therefore,the spectral features of V% exist in 365~425,500~515,720~740,755~765 and 955~965 nm bands,compared with the spectral features of EC b appear in 370~385,405~425,500~535,650~660,755~760 and 1 030~1 050 nm bands.According to the experiment result,through 4 different preprocessing approaches,water content model and electric conductivity model of both PLS and GA-PLS are all evaluated by R2t,Predicted Residual Sum of Squares(PRSS)and Residual Predictive Deviation(RPD),GA-PLS models got the better point in prediction accuracy rather than PLS regression.The continuum removal approach leads to the highest prediction accuracy among all other preprocessing methods,with R2,PRSS and RPD equal 0.88,9.36 and 15.80 in soil water content model and 0.71,15.68 and 13.76 in EC model.
Technology of remote sensing has been widely used to obtain hydrological variables and parameters.With snow\|cover of MODIS,precipitation of FY meteorological satellites,air temperature of GLDAS remote sensing data are as the main input variables,the snowmelt runoff model based on multi source remote sensing was established and was used to simulate the snowmelt process in ungauged Nyangqu River Basins in Tibetan Plateau.When obtaived the input variable of snow by snow\|cover of MODIS,as for the instantaneous snowfall largely affects the precision of calculative snow cover,considering the temperature and precipitation,removing the effects of instantaneous snow,daily coverage of snow and ice were obtained by improved linear interpolation which can improve model simulation accuracy.The simulation fit indexes of Nash\|Sutcliffe coefficient(NSE)is 0.681,the volume difference(Dv)is -0.17% and RMSE error is 9.678.The snowmelt runoff model based on remote sensing is applicable in the Nyangqu River Basin.The precision of the simulation model is higher.This study can provide important reference for the research on Ecohydrological models in the cold regions and effective support for application of other river basin especially lack of data area.
Land Surface Temperature (LST) is a key process parameter of global change,and its importance is being increasingly recognized.With the increase of remote sensing data sources,HJ\|1B satellite data has short return cycle and large sensing width is used for land surface temperature retrieval.This paper is based on the HJ\|1B/IRS thermal infrared data,using the methods of Radioactive Transfer Equation (RTE),Qin Zhi\|hao mono\|window algorithm (Qins’) and generalized single\|channel algorithm (JM&S) to retrieve LST in Nanjing,analyzed the results of the three algorithms and use the same phase MODIS land surface temperature product to analyze temperature retrieval results.The results show that three algorithms have consistency.Compared with the MODIS temperature products,the LST has the closest retrieval results with it and lower than 2.1 K when RTE is used;Qins’ retrieval result was only slightly lower 3.87 K;and retrieval result of JM&S significantly lower than 5.96 K for the MODIS temperature products.Combined with the land use type map to analyze the spatial distribution characteristics of the surface temperature of Nanjing,it can be seen that the difference between highest temperature of construction land and the lowest temperature of water is 4.1 K when RTE is used;the difference between construction land and water is 4.38 K when Qins’ is used;the difference between the highest temperature of construction land and the lowest temperature of water is 2.15 K when JM&S is used.The temperature results of the RTE and Qins can reflect the temperature difference among the different land use types and its contribution to the urban heat island.
In absolute altimeter calibration campaigns,the Sea Surface Height (SSH) series derived from the in\|situ Differential GPS (DGPS) buoys always include high frequency errors such as wind waves and instrumental noises.The former can be removed by low pass filters ,while the latter can not,because the noises are white and can spread in the whole frequency band of interest.In this paper,the Singular Spectrum Analysis (SSA) method was applied to solve the problem,and select criteria of the embedding dimension and intercepting length.Simulations based on this innovative method were executed,the effectiveness in removing the instrumental noise and the selction criteria was validated.Finally,SSH series derived from an in\|situ DGPS buoy experiment were processed by this method,and the study suggested that the processed series were smoother compared to the original series,and had some improvements in accuracy.Therefore,the validity of the SSA method was demonstrated.
The change detection method is adopted to estimate the relative soil moisture by using ENVISAT/ASAR global mode data with 1 km resolution in the upper reaches of Heihe River Basin.Then the relative soil moisture is convert to absolute soil moisture by the Van Genuchten formula based on the soil bulk.The comparison analysis and validation during the period from 2008 to 2011 by using the 10 cm observations at A’rou freeze/thaw observation station,show that the root mean square error (RMSE) of the estimated volumetric soil moisture from ASAR is 0.11 cm3/cm3.The indirect validation in the spatial domain by using the mean values of observations at 36 WATERNET nodes,shows that there are 19 nodes which RMSE range from 0.03 cm3/cm3 to 0.11 cm3/cm3,there are 15 nodes which RMSE range from0.11 cm3/cm3 to 0.16 cm3/cm3,and there are 2 nodes which RMSE range from 0.16 cm3/cm3 to 0.19 cm3/cm3.The theoretical maximum estimation errors of volumetric soil moisture range from 0.03 cm3/cm3 to 0.12 cm3/cm3,and that 91.77% of grids is below 0.06 cm3/cm3,the result also shows that the perform of this algorithm at flat topography is better than the mountains.
Radiometric calibration of Synthetic Aperture Radar (SAR) using corner reflectors is a simple,practical and high precision external calibration approach.The key technologies in the calibration process includes a power estimation of the reflector impulse response,antenna pattern fitting and the determination of absolute calibration factor.In order to compare and analyze the applicability of the two common estimation methods of reflector impulse response,i.e.,peak method and integral method,on airborne high\|resolution SAR images,two radiometric calibration experiments based on two groups of trihedral corner reflectors (C30 and C10) in different sizes are conducted.In view of the unstable platform of airborne SAR,a new method of antenna fitting is proposed in this paper.Six criterions including the estimation value of medium incidence angle,RMSE,MEAN,STDEV,coefficient of variation (C.V) and precision of calibration are used to evaluate the applicability of the two methods.Experimental results show that the precision of peak method and integral method is similar when used the C30 corner reflector group,and the peak method performs is better than integral method when used the C10 group.The high resolution SAR image has a strong ability to represent the details of ground objects so that it difficult to select homogeneous background to estimate impulse response in the integral method,so a relatively large size reflectors with a large background should be used.When the imaging system is focused well,the peak method is suggested,otherwise,the integral method should be used.
The precision of model states assimilation is affected by various factors.For the problem of the uncertain parameters of the model in the process of states assimilation,simultaneous states and parameters estimation is a preferred approach to solve it which obtains the rational estimation of parameters during states assimilation.Establish the framework of simultaneous estimation based on Lorenz model,and compare the differential performances among the following three methods:AEnKF(Augmented Ensemble Kalman Filter),DEnKF(Dual Ensemble Kalman Filter) and SODA(Simultaneous Optimization and Data Assimilation) by changing ensemble size,observation variance and the number of observation to judge the merits and applicability of these methods.According to the final comparative studies,the RMSE of states in the AEnKF algorithm was the largest one when ensemble size was not more than 20,and decreased slowly along with ensemble size increasing; the RMSE of all the three algorithms added when observation variance increased,but the discrimination among the three is tiny; the results of algorithms got worse for the number of observation turned to one,and this situation was especially obvious in AEnKF.
According to the characteristics of the spatiotemporal data collected by Field Wireless Sensor Network,common spatiotemporal outlier detection methods were summarized,an method regarding time series similarity as spatiotemporal neighborhood was proposed to gain precisely mine outlier information of those spatiotemporal data .This method is verified by observation data acquired by 13 sites of Heihe Watershed Ecological and Hydrological Wireless Sensor Network on July 5th,2012,and the result indicates that anomaly of spatiotemporal data of the wireless sensor network was effectively identified,and several fake anomaly which caused by artificial irrigation and rainstorm were also identified,and this method is of certain guidance significance for other data processing exploratory studies.
According to the characteristics of the spatiotemporal data collected by Field Wireless Sensor Network,common spatiotemporal outlier detection methods were summarized,an method regarding time series similarity as spatiotemporal neighborhood was proposed to gain precisely mine outlier information of those spatiotemporal data .This method is verified by observation data acquired by 13 sites of Heihe Watershed Ecological and Hydrological Wireless Sensor Network on July 5th,2012,and the result indicates that anomaly of spatiotemporal data of the wireless sensor network was effectively identified,and several fake anomaly which caused by artificial irrigation and rainstorm were also identified,and this method is of certain guidance significance for other data processing exploratory studies.
Cultivated land is an important agricultural resources and how to extract information quickly and accurately using remote sensing technology is an research hotspot currently.In this paper,time series of MODIS/EVI data was used to extract cultivated resource in GuanZhong during 2000.According to the classification basis,the different land type exhibiting distinctive seasonal patterns of EVI variation have strong periodic characteristic.Harmonic Analysis of Time Series was applied to EVI time\|series data in order to minimize the influence of noise on information extraction.After performed MNF transformation and PPI algorithm,four endmembers are selected including vegetation,cultivated land,urban and water using n\|Dimensional Visualizer Tool of ENVI software.And then,cultivated land was estimated based on a Linear Spectral Mixture Model (LSMM).Through comparison validation of the 1∶10 000 land use data of the study area.This study finds that the total accuracy of cultivated land is 83%.The results indicated that high accuracy of cultivated land of quantitative information is available based on mixed pixel decomposition according to the characteristic difference of different land type,as well as EVI time\|series data reconstruction using the Harmonic Analysis of Time Series.This method can provide technical reference for long\|term,large\|scale,dynamic remote sensing monitoring of the distribution and change of cultivated land and
To improve the image quality of band 5 and band 27 which contain stripe noises acquired by Moderate Resolution Imaging Spectroradiometer (MODIS) level_1B,based on MODIS scanning characteristics,a method of using the max mean of each swath to judge the stripe noises was proposed.When destriping noises,according to the thought of single line stripe interpolation on band 5,an interpolate method of using the adjacent multi\|line stripe noises on band 27 was proposed.Finally,comparison diagram,mean diagram and numeric analysis between original data and processed data were compared to validate the effect of destriping noises.The results show that the method can judge all the stripe noises exactly on both bands,and can remove the stripe noises well.The process of destriping noises is easily and suitable for the complex remote sensing scenes.
The aim of validation is to get the accuracy of satellite remote sensing products using cruise data or higher quality remote sensing products as the true data.It is necessary for the applications of remote sensing products.In this paper,we analyzed the applicability of various statistical algorithms for accuracy evaluation,including root mean square error,mean absolute error and mean relative error.Furthermore,we determine a practical validation process for ocean color products and sea surface temperature (SST) products.The validation results of SST derived from MODIS show that the provided validation process is feasible.The validation results also show the distribution of the products,which represented by the mean deviation and the standard deviation can lead to different validation results,and the mean value of sample is high correlative to mean relative error.
The efficiency of data acquisition can be greatly improved by imaging with low overlap in the UAV platform to meet the demands of the timeliness requirements for aerial reconnaissance and emergency rescue.However,the features that low overlap and serious rotation angle can bring greater errors with the conventional process of orthophoto mosaic.In this paper,an algorithm based on ASIFT with low overlap UAV image registration is proposed.Then the sparse bundle adjustment is used to constrain the space relationship of the sequence of images.A multi\|resolution spline mosaics technique with optimal transformation matrix of overlap images is presented.Experimental result shows that the proposed method can obtain a large number of stable correspondences and transformation matrix of overlap images for further seamless image stitching,which can be useful for low overlap UAV images stitching.
A flight experiment is an important experimental step that needs to be conducted in the prelaunch for Chinese\|French Oceanic SATellite (CFOSAT).Functionally,performance and data validation of spaceborne scatterometer should be verified to ensure in\|orbit work status.In this flight experiment,return signal simulator is used to conduct ground\|based system testing and calibration for CFOSAT,which proposes a method to use return signal simulator for spaceborne scatterometer system calibration.This method is helpful to ground\|based calibration experiments for CFOSAT.Return signal simulator could provide a known echo signal.The results in flight experiments verify the feasibility and accuracy by return signal simulator to conduct the ground\|based calibration for spaceborne scatterometer.
The single Logistic function curve fitting is one of the most important methods of the NDVI time series reconstruction and key phenophase division in phenology remote sensing.The method is more adapted to complex environment as it does not need to set the threshold or empirical coefficient.However,in some mountain areas,the fitting precision of single logistic function is still low if the NDVI values are contaminated too much.In this paper,using the NDVI time series data of the sampling area in the Qinling Mountains from 2001 to 2013 to analysis the stability of the maximums and the minimums of the NDVI curves,we found that the maximums are more stable in the NDVI time series data than the minimums,and then we modified the form of the single logistic model on the basis of the above analysis.Finally,a more stable method was proposed to improve the accuracy of the NDVI time series reconstruction with large noise in complex mountains.In this paper,in order to measure the ability to keep vegetation growth season features and retain high quality original true values of the modified method and original method,the means of correlation coefficient and root mean squared error of the two methods for fitting NDVI data of the sampling area in the Qinling Mountains from 2011 to 2013 were calculated.And then the two indices of the modified method were evaluated by comparing with the original one.The results show that the modified method has a better performance than the original one in both above aspects.The modified method has a better applicability in the NDVI time series reconstruction with large noise,which can provide reference for the research related phenology remote sensing in complex mountains.
Temperature control is a simple and effective way to improve the system stability of the total\|power\|type microwave radiometer,the full\|polarimetric microwave radiometer can achieve high precision measurement for retrieving the sea surface wind vector by the method.Using a 23.8 GHz digital\|correlation full\|polarimetric microwave radiometer,considering the effects of temperature on calibration of the polarimeter and adopting a special temperature control scheme,a constant temperature control system was designed to make the radiometer work stably.The experimental results show that the constant temperature control scheme can make the radiometer work in a stable state which can simplify the calibration process,make the calibration cycle longer and ensure the accuracy requirement of the calibration.
A method using Simulink to build the simulation model of the microwave interferometric radiometer (MIR) system is introduced in this paper.Two\|element interferometer is the basic unit of the MIR system.By the Simulink platform,a simulation model of the two\|element interferometer was built and the measurement process of the random noise was simulated.Through the simulation of the full power measurement achieved interference measurement of single channel and two channels.Quantitative analysis of the radiometric accuracy and radiometric sensitivity were achieved in the time domain.
As the boundary that separates snow\|covered areas from snow\|free areas,the snowline is the most sensitive indicator for monitoring climatic behavior among all the cryosphere elements.In this paper,the snowline altitude over the Tibetan Plateau (TP) during 2000 to 2011 are extracted using the cloud\|removed MODIS fractional snow cover products combining with DEM,and the spatiotemporal changes of snowline altitude are examined.The proposed MODIS\|based snowline altitude extracting methodology include the determination of snowline pixel and its altitude,and the establishment of snowline altitude field.The results show that due to the complex terrain,the snowline altitude in the interior of the TP is obviously higher than the peripheral mountainous area.A strong seasonal and interannual variability of snowline altitude is discovered,although there is no obvious trend of snowline altitude change during the examined period.Especially,the east and south of the TP,due to the influence of summer monsoon,there are very large interannual fluctuations of snowline altitude in the summer months.The MODIS-based snowline altitude extracting method was described in this paper,which has a good application potential in SLA monitoring for any other regions.
Crops planting structure and spatiotemporal change information have become the focus of the current agricultural remote sensing application.However,using the spectral characteristics and vegetation index of multi\|temporal remote sensing data to extract the crops planting structure was still few in our country.The paper took Wensu county as the study area,used Landsat8 OLI satellite data,analyzed the difference of spectral characteristics and vegetation index of the main land cover types according to the crop phenological calendar,and modeled a decision tree to identification crops,then used the model to extract crops planting structure precisely on Wensu county.The results suggested that:① The optimal choice to identify paddy rice is near infrared band on May 20 and NDVI value on July 23;NDVI change value from May 20 to September 9,which is most helpful for the identification of cotton and corn;NDVI change value from May 20 to July 23,which is the best choice for wheat and forest fruit.② the decision tree classification based on multi\|temporal Landsat8 OLI images outperformed the single\|temporal supervised classification results with the overall accuracy increased 7.90% and Kappa coefficient increased 0.10.③Landsat8 OLI satellit data has high spatial resolution and convenient access,so it is a potential data source for crops information identification,monitoring,extracting in the future.
In this study,The Tibet Karuola glacier area change has been analysed from 1972~2010 by GIS spatial analysis method based on Landsat land resources satellite.The results showed that Tibet Karuola glaciers have vetreating retreat nearly 38 years.The glacier area changes is obviously in 1972~1978 and 1999~2010.In particular,the most obvious of glacier area is thange in glacier terminus and southeast slope area,combined with analysis of climatic factors of Langkazi meteorological station showed that the regional temperature and precipitation have increased,especially cold season temperature rise is the main reason that lead to glacier retreat.
Satellite remote sensing technology has become one of the important techniques for sea ice monitoring.The method of sea ice information extraction such as distribution,type and thickness over Hebei coastal zone using the EOS,HY\|1B and HJ\|1A/B satellite remote sensing data was introduced.In this paper sea ice classification and sea ice thickness estimation according to the corresponding relationship between sea ice type and sea ice thickness were mainly studied using HJ\|1A/B satellites remote sensing data.Finally,based on the above method and the satellite remote sensing data on 17 th January,2013,the sea ice information was extracted and the related thematic product was produced.The result showed that using a variety of satellite remote sensing data for sea ice monitoring can not only complement each other but also improve the monitoring efficiency and accuracy,which generate more refined sea ice monitoring products.This study provides important information for the Hebei marine administrative departments to make measurements for sea ice disaster prevention and mitigation.
Based on the object\|oriented classification technology and land\|use change model,this paper focuses on Dongjiang river basin which is undergoing intense environmental change and analyzes its land use change characteristics from 1980 to 2008.The results shows that:①The object\|oriented classification method of remote sensing in SPOT5 high\|resolution remote\|sensing image classification has high accuracy(overall accuracy reaches 87.7%),and it can reduce effectively the “pepper and salt phenomenon”.②Significant changes in both land use ways and temporal\|spatial pattern have taken place in Dongjiang river basin during the period of 1980~2008.Dramatically the farmland decreased 2 854.4 km2,most of which were converted into forestland and urban construction land.The garden land decreased 667 km2,most of which were converted into forestland.The forestland increased 1 988.7 km2,being in the state of fluctuations.The grassland ratio decreased from 4.9% to 2.0%.Water body first decreased and then increased.The urban construction land showed a trend of dramatic increase with an annual increasing rate of 186.23%.Enhancing farmland protection and placing appropriate restriction on urban construction land is of great very importance to regional sustainable development.
Remote sensing technology has been widely applied in monitoring inland water environment.Satellite remote sensing data commonly used in monitoring water environment which has both advantages and disadvantages.The GF-1 satellite was launched in April,2013,carrying a Wide Field of View Camera (WFV),which provides a new data source for monitoring water environment.By comparing with Landsat8 OLI and HJ-1 CCD data,the radiant,spectral and spatial characteristics of GF-1 WFV data were evaluated,and the advantages and disadvantages of applying WFV data in monitoring inland water environment were analyzed.The results show that:①GF-1 WFV is superior to HJ-1 CCD in radiometric resolution and SNR,and the WFV data,which is quantified in 10 bits that can meet the accuracy requirement of monitoring water environment,the current calibration coefficient of WFV should be corrected when it is used in monitoring water;②GF-1 WFV is similar to HJ-1 CCD but inferior to Landsat8 OLI in spectral resolution,and it can't well identify subtle spectral features of inland waters;③The spatial resolution and swath of WFV are obviously superior to that of HJ\|1 CCD and Landsat8 OLI.In short,GF-1 WFV has much potential in dynamically monitoring large zone middle\|to\|small scale inland water bodies.
The basic functions of the libraries are literature collection,sorting and retrieval.Furthermore,the libraries have also made a lot of researches and obtain abundant achievements.We can get beneficial references by making the information mining from these literatures.The change tendency of the paper publications can be obtained for different countries by using trend line analysis.The spatial and temporal migration characteristics of the center of the world libraries’ papers can be described by using the centroid method.The results indicate that the two methods are successfully used in the bibliometrics analysis,which afford the new methodologies for the bibliometrics studies.
