Rapid urbanization has changed surface properties of city and its surroundings,which already modified local and regional climate change.Currently regional climate models were used to analyze the climate effect influenced by urban expansion and explore its induced environmental issues.However,the Overlapping Parabolic Interpolation (OPI) method is used for surface parameterization of climate models mainly focused on the maximum information of land cover types,and it would neglect minor signals of land surface parameters,especially in highly mixture surface in city surroundings,further affected the accuracy of model simulation.In order to quantify the impact of OPI method on urban land surface parameters derivation,this study tried to examine radiative forcing of surface albedo change influenced by urban identification deviation in mega\|cities of China based on Earth’s energy budget measurements,then CO2 emission offsets from surface albedo change were used to analyze modification of OPI method on urban climate.The results showed that deviation of urban area identified by OPI method has became larger with spatial resolution increase,which resulted in urban effect underestimation for climate analysis due to surface albedo increase.Case study in the summer of 2009 showed that increasing albedos of urban area identification deviation in urban agglomeration of Beijing,Tianjin and Hebei of China will induce a negative radiative forcing equivalent to offsetting about 2.28×105 tons and 1.81×106 tons of CO2 emissions respectively.
Space astronomy satellite mission planning is a complex NP\|hard problem.Expanding the application of STK/Scheduler commercial software from the field of Earth observation mission planning to space astronomy satellite mission planning field is important for obtaining reliable results,quickly building ground transport controlling simulation environment and providing solution reference point.According to the problem of space astronomy satellite mission planning taking,maximum scientific return as object of a multiple constrained mission planning model was established and the solution and instance validation of space astronomy satellite mission planning based on STK/Scheduler was developed.The results show that the use of STK/Scheduler in space astronomy satellite mission planning can adapt to a variety of planning sessions and solution requirements,and it can meet basic needs of space astronomy satellite mission planning due to its characteristics of derivation stability.
A method of convective cloud detection based on multi\|thresholds is introduced.First of all,convective clouds are detected by single threshold method with different thresholds.And then the cloud numbers,scale information (length of long axis) and shape factor (eccentricity) are calculated based on the FY2E cloud imagery form June to July 2010.With thees statistic results,three bright temperature thresholds for three steps of convective cloud detection are selected.Finally,the convective clouds,which have been detected by three thresholds,are classified into 18 kinds by cloud factors;those are the length of long axis,the eccentricity and the minimum bright temperature.based on a typical case application at 09:30 on 13 July 2010,it is shown that not only the convective systems in the large scale cloud system (such as Meiyu Front and Typhoon) can be detected,but also the small scale convective cloud in the sheet stratus can been found.So the application result shown that the method is usable for convective cloud detection.
Multi\|polarization (HH/HV) ENVISat ASAR imagery and conventional optical remotely sensed imagery of the Landsat TM (band1~5,7) were used in this study to investigate flooding extent of Zhalong Natural Reserve.Differences between backscattering coefficients of ASAR and different bands reflectance of Landsat TM imageries were conducted in different land cover types (flooded vegetation,non\|flooded vegetation,open water,bare soil).Moreover,the classification and regression tree (CART) algorithm was employed to extract spatial distribution of wetland vegetation flooding extent with two types of imageries based on selecting training samples while ground\|truth GPS samples were used to validate classification results of two data sources.The findings demonstrate that the backscattering coefficients of water under the vegetation canopy were different from other land cover types in HH/HV polarization imagery data.The overall accuracy was satisfactory (79.49%) with higher accuracy in extracting flooded vegetation;the kappa coefficient was 0.7.However,the results of flooded vegetation with TM imagery data appeared higher classification error in some regions where water was covered with vegetation.Consequently,the SAR imagery data plays a critical role in improving the accuracy of flooding extent extraction.Furthermore,the results reported here verify that it is effective to analysis the wetland eco-hydrological processes with SAR,which is very important for rational use of water resources of natural reserve and biodiversity conservation.
Winter wheat is one of the main food crops in Guanzhong Region,master its planting area has great significance for yield estimation of winter wheat.HJ satellite image of heading stage of Winter wheat is applied in this study.According to the administrative division,many kinds of remote sensing monitoring methods,such as the maximum likelihood classification,mahalanobis distance classification,Support vector machine classification,and ISODATA classification,were used in winter wheat planting area extraction,the final extraction accuracy is 95.64% in Guanzhong region.The result shows that the heading stage is the best phase for winter wheat extraction using remote sensing image in Guanzhong region,also shows that HJ satellite image can be used to monitor a wide range of winter wheat planting area,and could get high accuracy.In the future,in order to improve extraction accuracy,study area can be divided according to the terrain differences and the planting structure of winter wheat for each study area using different remote sensing monitoring method.
Unauthorized mining of ion\|absorbed rare earth ore deposits have become more and more serious with rising of the price of rare earth,and the mining of rare earth ore leads to a series of environmental problems.The quick and accurate investigation of mining has thus become government administrators’ major concern.To solve the problem of investigating the ion\|absorbed rare earth ore,south Jiangxi areas were selected as the study area,and high resolution remote sensing data was used for investigation.Investigation study includes three aspects,which were unauthorized mining,environmental pollution and change monitoring.Unauthorized mining investigation was conducted in Xunwu area using IKONOS data.The interpretation criteria were built,and unauthorized mining areas were delineated with the help of the mining right data.Then environmental pollution investigation was studied in Xunwu area using IKONOS data.Land desertification was extracted using spectral angle mapping method,and the water pollution level was identified in four classes using ISODATA classification method.Finally,change monitoring was studied in Dingnan area using two periods of QuickBird data,and the reduction and increase of mining areas were calculated using remote sensing and geographic information system analysis.The results indicated that high resolution remote sensing processing can provide a good method for quick,accurate and dynamic investigation of ion\|absorbed rare earth ore.
In this paper,MODIS data from 2001 to 2010 is used to analyze MODIS\|NDVI and MODIS\|EVI time\|varying characteristic differences between different levels of karst rocky desertification area in Guangxi.The all\|time series and 16d average sequence of 10 years are used to analyze the correlation between NDVI and EVI.Fitting results of NDVI and EVI series,including logarithmic model and linear regression model are compared.The results shows that:With the rocky desertification levels from severe to potentially,the difference between NDVI and EVI increases with the increasing of vegetation coverage.That is as the lower of the vegetation coverage,vegetation characteristics change exhibit more similar between NDVI and EVI.The NDVI peak value appears later than that of EVI.Vegetation changes trends display in NDVI sequence are more consistent with ground surveys,but its value are higher.Logarithmic model is better than linear regression model for fitting the relationship between NDVI and EVI of different levels of rocky desertification.The corelation between NDVI and EVI increases with the redution of vegetation coverage for both series.The corelation between the two indices for mild and moderate rocky desertification are opposite for the two series.
Drought,especially spring drought,prevails almost every year in the eastern region of Qinghai.It had a great impact on agriculture,while lacking of an effective remote sensing monitoring method.The values of Perpendicular Drought Index (PDI) of the agricultural meteorological stations,which were extracted from HJ\|CCD,fitted relationship among soil moisture of different depth,their unbiased correlation coefficients(R) were all above 0.7.Especially,the relationship at the depth of 0~20 cm(y=-489.00x+188.78)was best(R=0.7985).And it was used for the soil moisture inversion on the fixed period of Huangyuan agricultural meteorological station,the result showed that the time series trend of soil moisture from remote sensing inversion and manual measurement were similar.And this method was used to monitor the Spring Drought on Xining agricultural region of Qinghai in 2013.It showed that the drought regions were mainly distributed in the river valley of Datong and Huangshui,the drought of Huangyuan was the most serious,it was comparatively unanimous to develop with the real drought.
Snow is an indicator of climate change,and its changes have a profound effect on the energy and radiation balance and water cycle.Thus,it is the best demonstration of regional response to study the relationship between snow and climate change.Temporal and spatial variation of snow depth,snow cover and snow line of Tibet Plateau and its response to climate change were examined using geostatistics and spatial analysis of GIS function based on MODIS snow cover from March 2000 to February 2011,snow depth daily data (passive microwave remote sensing) during 1979~2010,DEM and surface meteorological data.The results showed that the snow depth varied with regions and displayed high in the periphery and low in the middle of the study area.The mean snow depth increased significantly with a linear trend rate of 0.26 cm/10a during the period of 1979~1999 and decreased between 1999 and 2010.The regression analysis indicated that the number of pixels with increasing mean annual snow depth,accounted for 76.9% of the total pixels in the study area,while only 23.1% for the opposite.The snow coverage generally decreasd between 2001 and 2010 with a linear trend rate of -38 900 km2/10a in the Tibet Plateau.Large areas were still covered by snow all the year around in the Nyenchen Tanglha,the Himalayas,the Gangdise and Kunlun mountains,and parts of Plateau hinterland.The mean annual snow line tended to ascend slightly with a linear trend rate of 6.54 m/10a in Tibet Plateau.The mean snow line variation in autumn contributed to the mean annual one mostly.The value of snow line in Tibet Plateau increased slowly from the southeast to the northwest.The correlation analysis between snow parameters and climate factors indicated that the snow depth was mainly impacted by wind speed and sunshine hours in spring and autumn,precipitation in summer and wind speed in winter.Temperature is the main factor influencing on snow coverage for every season.In four seasons,temperature had more significant effect on snow cover than other factors.However,in spring and autumn,the snow line was positively and negatively related to temperature in spring and autumn respectively.
Due to the backscattering amplitude of water follows Gamma distribution in SAR images,an automatic water extraction method is proposed based on water’s scattering characterstics.The proposed method mainly includes the following two aspects:first,Gaussian model is used to fit the image backscattering amplitude,and combine with the Gamma model,the optimal threshold is set.Then a optimization criteria is established to realize the adaptive iterative solution procedure.Second,with the introduction of the block selection criteria,the non\|target block is removed,and the optimal threshold for each target block is obtained.Then the average of the target blocks is considered as the optimal threshold of the whole image.This method greatly reduces the running time and increases the accuracy rate.Radarsat\|2 data of Huainan area is used to verify the method .The experimental results show that the method enables the extraction process of water in SAR image rapidly,accurately and automatically.
Phosphogypsum is a typical industrial solid waste.In China,with the development of phosphate fertilizer industry,the volume of phosphogypsum is increasing.And massive phosphogypsum are piled up in the open air which presents a critical problem for the environment.For obtaining the information of locations and areas of phosphogypsum,Fuquan in Guizhou province of China is selected as our study area.And an object\|oriented method is employed for detecting the phosphogypsum from HJ satellite imagery.The object\|oriented were we adopted consists of the following steps:firstly,multi\|scale segmentation method is adopted to segment the remote sensing images for obtaining the object\|based images.The heterogeneity in features of different objects is analyzed.According to the feature heterogeneity,then an object\|oriented decision tree rule set is built.Then,based on this decision tree rule set,the phosphogypsum can be identified automatically from remote sensing images.And information of phosphogypsum is extracted.The results show that:the identification of phosphogypsum producer and user accuracy are 88.89% and 84.21%,respectively.The overall accuracy and Kappa coefficient of classification are 91.75% and 0.817,respectively.Thus,the object-oriented method provides an effective method for detecting the phosphogypsum.
The Fraction of Absorbed Photosynthetically Active Radiation (FPAR) is a physiological parameter described the vegetation structure and the exchange of carbon and energy between vegetation canopy and atmosphere.In this paper,a method for retrieving vegetation canopy reflected and soil absorbed radiation components of incident PAR was analyzed by non\|linear mixing pixel model,and a simplified semi\|empirical model of estimate FPAR base on Principle of Energy Balance (FPEB) was presented firstly.Then,the FPEB model were examined using four independent field at Nagqu district,Tibet Autonomous Region in 2011 and 2013,Dangxiong county,Tibet Autonomous Region in 2011 and Hailar district,Inner Mongolia Autonomous Region in 2013.And the FPEB model was also compared with the traditional Normalized Difference Vegetation Index (NDVI) model.The results showed that the accuracy of FPEB model was better than NDVI\|based model,and that the FPEB model was universal and valid for different regions or vegetation types.
FY-3B MWRI uses the 10.65,18.7,23.8 and 36.5 GHz microwave brightness temperatures which are sensitive to ocean surface roughness and dielectric properties,to retrieve sea surface geophysical parameters.In order to obtain an algorithm for global use,the microwave radiation is emitted from the wind\|roughed ocean surface and measured by MWRI,which is simulated by the JCSDA Community Radiative Transfer Model CRTM and the ECMWF sampled databases of 60-level atmosphere profiles.Based on this simulation,a semi\|empirical algorithm is established.The in\|situ buoy measurements and WindSat wind speed production are used to validate the semi\|empirical algorithm.Furthermore,the retrieval error caused by the wind direction relative to the radiometer azimuth is analyzed.RMS/ATBV-TBH look-up-table is made to correct the relative wind direction error.After the relative wind direction error correction,the rms accuracy is reduced to 0.9775 m/s.
For the problem of rare snow observation stations,this paper proposed a new scheme to produce spatial distribution of snow depth on based on different kriging interpolation methods,which can not only consider elevation effects,but also fuse MODIS snow cover products.This scheme uses snow\|free pixels in the cloud\|removed MODIS snow cover image to build virtual stations with zeros snow depth to compensate for the scarcity and uneven distribution of stations.Additionally,the universal co\|kriging interpolation method is used to consider the impact of elevation on snow depth.The daily snow depth observations at 50 meteorological stations in northern Xinjing province are chosen to evaluate the proposed scheme.Four types of kriging methods are also compared such as ordinary kriging,universal kriging,ordinary co\|kriging and universal co-kriging.Results show that universal co\|kriging can achieve the best performance with a larger snow cover area and a bigger value of correlation coefficient between snow depth and elevation.Otherwise,the best performance is achieved by the ordinary kriging.The added virtual stations can improve the accuracy of interpolation and reduce smoothing effect in kriging interpolation.
Because of the similar spectral characteristics of cloud and snow cover in the visible and far\|infrared bands,the snow cover monitoring through optical remote sensing is seriously limited by weather condition.How to reduce the cloud obscuration of MODIS Snow Cover Fraction (SCF) product in a sub\|pixel scale becomes a pressing problem.This study eliminates the cloud contamination of MODIS SCF product using the method of kriging spatial interpolation based on the analysis of SCF spatial variability,and we conduct experiment by Ordinary Kriging (OK) and Ordinary Co\|Kriging (OCK),respectively.The experimental results of eleven different dates show that both OK and OCK method are approved the good accuracy for cloud\|removal of MODIS SCF products,especially in the case of that cloud cover rate is less than 20% and the performance of OCK is superior to OK.Although the performance of OK is slightly better than OCK,both of them have significantly worse performance and the obviously smooth effect when the cloud coverage is greater than 20%.
Albedo is a key parameter of climate model.Global albedo products retrieved from Multi\|angular satellites has been used in Climate modeling investigation.But the consistencies among these albedo products have not been sufficiently analyzed.So this paper compared the Level\|3 directional\|hemispherical reflectance (DHR) products (snow\|free area only) retrieved from MODIS,MISR and POLDER.Two broadband DHR were used,namely,shortwave (DHR_SW,300~5 000 nm) and visible (DHR_VIS,300~700 nm).The results revel that six\|year average of these products shows an evident relationship of POLDER>MISR>MODIS.There are systematic differences among these products.The differences on global means of DHR_SW (DHR_VIS) are 0.01~0.02(0.01~0.03) for MODIS and MISR,0.02~0.05(0.03~0.07) for MODIS and POLDER,and 0.01~0.03(0.01~0.04) for MISR and POLDER,respectively.Differences are larger in visible band than shortwave band.The zonal means of the three products show relative large differences in latitudes higher than 35°N,which may accumulate snow in winter and snow\|melt in spring.The correlations among the three products are high,in which MODIS and MISR is the highest,MISR and POLDER is the lowest,the correlation coefficients in shortwave band are 0.939 and 0.911,respectively.Although the difference between MODIS and POLDER is the largest,their correlation is still high,e.g.0.937 in shortwave.The correlations are higher in visible than in shortwave.The differences are almost similar to all land cover types,which shows it is not sensitive to the land cover type.The differences in Aerosol Optical Depth(AOD) between MISR and POLDER may contribute to the corresponding discrepancy in DHR,but cannot explain the differences between MISR and MODIS.Although the three products utilized different retrieve algorithm,they showed good correlation,the main discrepancy may come from the atmospheric correction process,which shows that their albedo retrieval algorithm are practicable.
As the terrain like the mountain and hills have a great influence on the remote sensing data,a new algorithm is developed to atmospheric correction.Based on the MODIS data,the Look Up Table (LUT) was built by 6S to retrieve the model and optical thickness of aerosol.The TM of the same time and the same area was used to calibrate CCD data.Finally,atmospheric correction has been applied in CBERS\|02’s CCD date based on the ATCOR3.The results show that the algorithm has a good effect on mountain and hills.
For their excellent temporal and spatial coverage,Atmospheric motion vectors(AMVs) have dispalyed great application perspective in improving the initial fields and numerical forcasts.In Geostationary Opertional Meteorological Satellite FY\|2E infrared imagery,AMVs in Clear\|sky regions,which have been retrieved by the time difference technique.However,the study on the height assignment of AMVs data in Clear\|sky regions is very lacking.In order to adjust the height of AMVs in Clear\|sky regions,the standard profile is used to compute weight response between Water vapor content and Satellite Infrared Radiation at different heights that is replaced by the practical atmospheric profile.Then statistical test and error analysis to AMVs in Clear\|sky regions is compared before and after height adjustment for Typhoon cases.At last,the Sensitivity experiments is performed in the three\|dimensional meso\|scale assimilation model WRF\|3DVAR.As a result,using the weight response calculated by practical atmospheric profile to determining AMVs height assignment is superior to weight response calculated by standard profile.And the height of AMVs in Clear\|sky regions is distributed in 600~900 hPa;After height assignment,the root\|mean\|square error and standard deviation of AMVs at every level in Clear\|sky regions have decreased apparently.The result of assimilation test confirm that the forcast track error of Typhoon is reduced in 48 hours with the assimilation of AMVs in Clear\|sky regions.Therefore this height assignment can improve the quality of AMVs in Clear\|sky regions.
The application of remote sensing products become more and more popular in many fields.Validation is an important assurance for the application of remote sensing products,which becomes urgent priority and it is also one of the major hot issues in the field of remote sensing research in recent years.Firstly,this paper summarizes the recent research advances and main methodologies of the LAI product validation.Then the validation of the LAI products with different resolutions in the middle parts of the Heihe River Basin was performed as an application case.Two different scale transformation strategies were used to validate the MODIS LAI product and the scale effect of LAI was analyzed.One strategy is to use the high\|resolution images as an intermediate\|scale for the scale transformation and the other is to realize the scale transformation directly from ground measured point LAI data.The results indicated that the correlation coefficients of two different scale transformation strategies are only 0.57 and 0.39.And the former strategy is better than the later.In the Heihe River Basin,MODIS LAI product is obviously underestimated,and the maximum deviation reaches 2.26.
With the development of aerospace technology and remote sensing techniques,the number of airborne and spaceborne thermal infrared sensors have been increasing in China.The evaluation for radiation performance of thermal infrared payloads,can not only obtain its real capability indices,but also provide quantitative criteria for the subsequent data products.However,the current evaluation process of thermal infrared payloads is very complex,and the operational running has not yet been accomplished.To resolve the problems mentioned above,this paper adopts modularized programming concept to design and implement a Thermal Infrared Payload Capability Evaluation System (TIPCES) based on the hybrid programming technique of C# and IDL.The atmospheric radiative transfer model MODTRAN4 is integrated to conduct relative computations of radiation transmitting and the Microsoft Access is applied in the system to manage data.Results of the validation experiment using simulated data demonstrate that:① the system can carry out the evaluation from three aspects:radiometric calibration,radiometric resolution and dynamic range;② the use of hybrid programming technology avoids the complicated operations of radiation transmitting model;③ the well\|designed databases is convenient for the management and update of data;and ④ the process\|oriented design of the system is well able to meet the need of streamline operations.In addition,the system has also good module portability and platform applicability,with each functional module being able to either run separately or be integrated into a higher level module,and which has lowered the requirements for hardware.The system designed and implemented in this paper has not only practical value for the development and performance evaluation of thermal infrared payloads in China,but also has the theoretical reference meaning for the future software design in remote sensing area.
Light Detection And Ranging (LiDAR) provides a rapid,accurate and efficient method for three\|dimensional spatial data acquisition.LiDAR technique provides a new method for heritage preservation and management.This paper introduces the principle and characteristics of LiDAR and discusses the application of the heritage preservation and management using LiDAR technology in detail.Finally,the current situation and problems of heritage preservation using LiDAR are analyzed,finally some solutions are proposed,which give some new ideas and methods to protectors and researchers of heritage.
TG-1 has accumulated large number of hyper-spectral data,which could be widely use for a variety of scientific research,including land resources,agroforestry and Oil-gas resources,etc.However,a very large percentage of those imageries are severely contaminated by atmosphere.So the atmospheric correction procedure which could remove the atmosphere effects is a critical preprocessing step required for quantitative remote sensing applications.In this study,we developed a atmospheric correction procedure based on Moderate Resolution Imaging Spectrometer(MODIS)atmospheric characterization products and the Second Simulation of a Satellite Signal in the Solar Spectrum(6S)radiative transfered code for TG\|1 hyper\|spectral imagery.Then the atmospheric correction precision was assessed by using ground\|measured reflectance and MODIS reflectance.The result showed that the surface reflectance retrieved from TG\|1 hyper\|spectral is consistent with the ground measurements,with the R is bigger than 0.97,and a mean root mean square error(RMSE)is less than 0.088.And the comparison result for TG\|1 hyper-spectral and MODIS showed that the regression coefficients is closed to 1,with the R2 bigger than 0.8.
Based on decomposing and composing the thermal infrared band pixel,with the logical combination of the tasseled cap transformation (K-T) and Normalized Difference Bareness Index (NDBaI),a new Bareness Index (BI) was developed.And it has been applied in extracting the bare\|soil areas in Pearl River Delta using Landsat ETM+ data in 2003.The results show that the BI not only has a good effect on the enhancement of bare soil information,and the inhibition of the background information,but also improve the accuracy of detection.The results of this study could be of scientific and practical merits in regional remote sensing monitoring and improve the accuracy of land use classification.
There are a lot of hydrological spatio\|temporal series image data in the input and output of remote sensing hydrological model.Visualization makes people discover implicit rules from these data seemingly.The visualization analysis process is separated and has low efficiency at present.Therefore remote sensing spatio-temporal series data visualization analysis system was developed based on IDL(Interactive Data Language) and was applied in the data analysis of EcoHAT(Ecohydrological Assessment Tools) System.Using IDL’s powerful image processing and data calculation capabilities,visualization analysis system can realize such functions:the remote sensing spatio\|temporal series data management,image display and diagramming.Visualization makes more efficient use of the massive remote-sensed hydrological data.
The demands for remote sensing data in Geo\|hazard investigation,monitoring,early\|warning and rescuing are briefly analyzed.With the increasingly extensive applications of the high resolution remote sensing technology in Geo\|hazard field,Geo\|hazard information is becoming massive,heterogeneous and multivariate.Taking the regional characteristics of Geo\|hazard as a basis,the research on the Geo\|hazard information management model has been done from the river basin scale.In Geo\|hazard point,administrative division,river basin as the individual object,the multi\|level tree structure Geo\|hazard encoding system is established,and the technical framework of “point\|line\|surface”management is constructed.In the end,the prototype system shows the feasibility of the schema.
Taking ISI Web of Science(SCIE) database as source data,investigated the thesis on water remote sensing in the worldwild from 1994 to 2013 by using the TDA tool and the Ucinet.The results show that water remote sensing research has keep growing,especially notable in the past 10 years;the USA,that has launched many observation satellites,takes the dominant position in this field;highly cited articles are mainly for NDWI index and observation satellite`s introduction;Water remote sensing research mainly concentrated on the researches of soil moisture,evaporation ,water resource,snow,etc,and is mainly used for MODIS satellites data.
