Watershed Allied Telemetry Experimental Research (WATER) is a simultaneous airborne,satellite\|borne and ground\|based remote sensing experiment conducted in the Heihe River Basin,a typical inland river basin in the northwest of China.To develop an open and free,multi\|scale,high quality,and integrated dataset is one of the major objectives of WATER.After a data processing period lasting for two years from mid\|2008 to mid\|2010,the dataset is now available at http://westdc.westgis.ac.cn/water or http://rsdc.bnu.edu.cn for open access.As a preface of the WATER data special issue,we introduce the significance of the WATER data information system,datasets collected during WATER observation periods,data quality control,and data sharing policy.Researchers both in China and globally are invited to use the data in watershed hydrological and ecological modeling,quantitative remote sensing,and other research works.Feedbacks are invited in order to further improve the data quality.
In this paper，the data quality control and management processes were introduced for the ground observation data of the Watershed Allied Telemetry Experimental Research (WATER),except for the eddy covariance fluxes data,meteorological and hydrological data.The main contents include the establishment and implement observation specifications,data standardization processing,data standardization of the data file names,data quality evaluation.There are two objectives of this paper:to provide detailed data quality evaluation information for the data users; and to give some enlightenment on the data quality control and management for the later similar experiments.The data evaluation indicates that the data quality of WATER ground observation data is reliable,which is mainly supported by these data quality control works.The further work is needed to focus on the data analysis and application researches by using these data sets.
The Watershed Allied Telemetry Experimental Research (WATER) is a simultaneous airborne,satellite\|borne,and ground\|based remote sensing experiment aiming to improve the observability,understanding,and predictability of hydrological and related ecological processes at a catchment scale.After the experiment,the efforts have been made to process the data and improve the data quality.A data and information system (WATER\|DIS) are also required to develop to manage these data.Two data service centers have been built up in Cold and Arid Regions of Environmental and Engineering Research Institute,Chinese Academy of Sciences (http://westdc.westgis.ac.cn/water) and Beijing Normal University (http://rsdc.bnu.edu.cn/).The WATER\|DIS is a metadata\|driven system.This paper introduces the architecture,database and function of WATER\|DIS and makes a summary table of the released data of WATER.According to the statistics,about 2.5 TB data are released including the ground data,meteorological and hydrological data,airborne remote sensing data,and satellite\|borne remote sensing data.
In order to improve the performance of network transmission for posting remote sensing data,the Remote Sensing Data Distribution System,which is based on the OPeNDAP,is realized by utilizing the subset\|support features of the OPeNDAP.The system is based on a hierarchical system design which includes data,data management,and network application.A number of application modules such as online quick\|view,data information viewing and data catalog are developed in the system,which realized the aim of posting all of the remote sensing data in multiple formats.By solving the problems caused by multiple data formats and large data quantity,the Remote Sensing Data Distribution System has provided an effective way for posting remote sensing data through network.At last,the application of the OPeNDAP and online quick\|view are illustrated in details.
Eddy covariance (EC) flux data processing and quality control is an important procedure to ensure the data quality of each observation station.A large number of flux data measured by EC system have been accumulated based on the project of “Watershed Allied Telemetry Experimental Research” (WATER) since late 2007.Pre\|processing and quality control were performed using improved EdiRe software developed by Edinburgh University to the original EC data at Yingke oasis station,Arou freeze\|thaw observation station and Guantan forest station.The basic processing steps on the Level\|1 data product including removal of outliers and spikes,tilt correction,sonic virtual temperature correction,time\|lag correction,frequency response correction,and correction for density effects (WPL correction).Level-2 data product is generated with initial quality control steps based on Level\|1 data product,including atmosphere state stationarity test,overall turbulence characteristics test and turbulent flux statistical characteristics analysis.In this paper,taking EC data of Yingke oasis station in July,2008 as an example,the improvements of each correction steps during EC flux data processing and the contribution of different correction methods to the calculation of turbulent flux were analyzed in detail.The results show that:after sonic virtual temperature correction,sensible heat flux decreased about 7.7%; after time\|lag correction,latent heat flux and carbon dioxide flux increased by 3.9% and 2.7% respectively; after frequency response correction,sensible heat flux,latent heat flux and carbon dioxide flux increased by 2.7%,10.5% and 11.6% respectively; after WPL correction,latent heat flux increased by 1.7%,and carbon dioxide flux decreased by 9.8%.Finally,the Level\|1 product and Level\|2 product were compared with the Campbell real\|time processing results,and an overall data accuracy evaluation on each eddy covariance station for these three stations was obtained.It is concluded that the data quality of the Arou freeze\|thaw observation station is the best,and that of the Yingke oasis station is better,and that of the Guantan forest station is poor.
WiDAS(Wide-angle Infrared Dual-mode line/area Array Scanner) is one of the major airborne sensors flew in the WATER(Watershed Allied Telemetry Experimental Research) field campaign.It acquires multi\|angular information about surface reflectance and emission anisotropy through wide\|angle imaging.This paper describes the algorithm and key parameters for WiDAS data processing.The detectors,image resolutions,and object spectral characteristics are much different between WiDAS VNIR bands and TIR/MIR bands.So,we adapt different data processing algorithm for VNIR bands and TIR/MIR bands.In VNIR bands,the CCD cameras are calibrated with integration sphere; images in different bands are aligned with simple warp function; atmosphere correction is performed with 6S model and measured aerosol optical thickness.In TIR/MIR bands,the IR cameras are calibrated with blackbody; image alignment have to use compound wrap function and more complex matching algorithm; and atmosphere correction is performed with MODTRAN model and measured atmosphere profile.The method to extract multiangular observations of ground object from standard WiDAS data products is also described.This paper can be informative when using WiDAS data in quantitative researches.
Watershed Allied Telemetry Experimental Research was hold in Heihe experimental research region in the summer of 2008.During that period,a number of ground LAI measurements and remote sensing LAI products were collected.When validating remote sensing LAI products with ground measurements or matching of LAI products derived from different resolution remote sensing images,scaling issue caused by surface heterogeneity cannot be ignored.So different measured and estimated LAI data can't be directly compared to each other without spatial scaling.In this paper,we developed a spatial scaling method based on Taylor series expansion model.This study mainly included two parts.① Setting high\|resolution image as auxiliary data,ground LAI measurements were converted into middle\|resolution and low\|resolution.② LAI products of low\|resolution were scale transferred with high\|resolution image as sub\|pixel information.based on these results,we find that,scaling method based on Taylor series expansion model is simple and effective.After spatial scaling process,the ground LAI measurements can be consider as reference to validate estimated LAI from remote sensing data.
Data quality control procedures of Automatic Weather Stations (AWS) from Watershed Allied Telemetry Experimental Research (WATER) are divided into two stages,computer automatic control stage (QC1) and human\|computer interaction judging stage (QC2).In the QC1,many quality control techniques are integrated to achieve a better automatic check scheme,including the climate extreme value check,the basic meteorological formula check,the interior consistency check,the temporal consistency check,and the decision\|making algorithm.In the following QC2,all questionable and error data judged by the QC1 stage will be artificially checked again.The error origins are explored,logical errors are corrected,and final data quality is determined.Products from the above quality control procedures are divided into two levels to distribute.The results indicate that the quality check of QC1 can effectively indentify most errors in the AWS data and by the errors correcting in QC2 the AWS data quality of WATER is very good and comes up to the advance experimental expectation.
According to the complementarities of airborne laser scanning (ALS) data and aerial images,an accurate method of classification based on multi\|source remote sensing data is presented.Firstly,DEM,nDSM,the relative intensity of return laser,and vegetation index can be extracted from the ALS data and aerial images,respectively.And then decision tree is adopt to recognize various ground objects.Finally,three typical areas of WATER (Watershed Airborne Telemetry Experimental Research) including city,cropland and water bodies are used to validate this approach.The result shows that the method can divide experimental area into building,high vegetation,low vegetation,cement and bare soil efficiently and reliably.
According to ALOS,SPOT5 high\|resolution remote sensing image analysis and field investigation,we have completed the remote sensing information visual extraction and vegetation mapping in Ulan Buh Desert,while combined with GPS field records,we have finished accuracy evaluation,the result was satisfactory.The accuracy of visual interpretation was about 93.3%,the area Haloxylon Ammodendron was 165 410.62 hm2,accounting for Ulan Buh Desert 17.27% of total land area.Meanwhile,methods of remote sensing image interpretation,which were suitable for Haloxylon forest in the Ulan Buh Desert ,were also discussed.
The high resolution sea surface wind speeds retrieval from SAR image is of great significance in the field of microwave remote sensing.A preliminary study about the high resolution sea surface wind speeds retrieval from SAR image combing with the NCEP/QSCAT blended sea surface wind directions was introduced.As a case study,this method was applied on one scene ENVISat ASAR imaging on Dec.6,2005.The retrieved wind speeds are compared with those from both the NCEP/QSCAT blended sea surface wind speeds and daily averaged Quick Scatter meter sea surface wind speeds.The results gave that they are in good agreement.The root\|mean\|square errors of wind speed are 1.9 m/s and 1.6 m/s respectively,which show that SAR has the ability of retrieving the high resolution sea surface wind speeds,and give the orientation of SAR sea surface wind field business application in future.
In order to show the real three\|dimensional effect of mine\|environmental restoration,virtual reality technology is proposed.The steps of 3D terrain modeling and the methods of virtual 3D scenic are given.And the method of collision detection in virtual system is improved using Shell sort.It is proved to be better than traditional one by the experimental result.Finally,the virtual system of Dingshanling mine is implemented.
It is a fact that storage methods of traditional space environment exploration data is difficult to meet the spatio\|temporal analysis and the depth excavation and hard to be carried out the visual expression based on the three-dimensional spatio\|temporal characteristics.This paper designs and implementations the space environment exploration data management system based on the multi\|base states with amendments on spatio\|temporal data model according to the characteristics of raw space exploration data.The software system can manage the space environment exploration data very well,reduce the store space and promote efficiency in spatio-temporal data index .
Traditionally,hydrological models are running on a local computer together with all necessary driven data and parameters.With the development of the Internet,models and data are increasingly shared across the Internet,which makes public involvements possible when models are used for public decision making.This paper proposed a framework for online hydrological model services using the Web service technology.The system architecture and key implementation issues were discussed.An example client application demonstrates the utilization of such model and data services.The framework is highlighted by accessing data from online data centers.By linking to the online data centers,for example,to the Environmental and Ecological Science Data Center for the West China,the system can obtain most data for the model from the data center,in such way we mitigate the pressure of data transfer between user and model server.The proposed online hydrological model framework makes hydrological model run on remote servers,lowering operation costs.It can be helpful in water related management practices which often use hydrological models and want public to involve.
Some experiments demonstrated anomalous enhancement of microwave radiation at certain frequencies during rock compression and cracking.In this paper,multiple channels brightness temperature (Tb) data observed by AMSR\|E during eight years(2003~2010) in each April are collected.The radiation anomaly index,RAI,is defined from Tb data to detect anomalous microwave radiation.based on atmospheric radiative transfer,emission variations due to physical temperature of land surface and atmospheric water vapor are analyzed in RAI detection.The RAI detection of Yushu area in April 12,2010 (two days before the earthquake in April 14,2010) is obtained,and its anomaly shows good spatial correlation with main seismic bands.
The chlorophyll\|a concentration of water bodies was not only an important indicator for water quality,but also a significant basis of scheme established for water environment protection and water resources development and utilization.based on analyzing of the water qualities experimental data and Hyperion image collected on 19 August,2004,the study discussed the optimal bands of the four\|bands semi\|analytical algorithms for estimating the chlorophyll\|a concentration from Hyperion image.According to the regression analysis based on model calibration dataset (37 stations) and the accuracy estimation based on the model validation dataset (5 stations),it was found that four\|bands semi\|analytical algorithm based on the exponential fitting methods had the highest accuracy for estimation chlorophyll\|a concentration (the correlation coefficient was 0.8913,the mean absolute error was 1.1109 μg/L,the average relative error was 5.69%,and the corresponding wavelength of four bands were 671.02 nm,701.55 nm,711.72 nm and 742.25 nm).Additionally,the study used the four\|bands semi\|analytical algorithm discussed in this study to inverse the chlorophyll\|a concentration from Hyperion imageries.The inversion result showed that the chlorophyll\|a concentration was lower in the central lake and higher around the banks of lake.Comparing with the annual average chlorophyll\|a concentration,22.23 μg/L of Taihu Lake,it was known that the chlorophyll\|a concentration on 19 August,2004,was at the relative high level during the inter\|annual.
The high resolution sea surface wind speeds retrieval from SAR image is of great significance in the field of microwave remote sensing.A preliminary study about the high resolution sea surface wind speeds retrieval from SAR image combing with the NCEP/QSCAT blended sea surface wind directions was introduced.As a case study,this method was applied on one scene ENVISat ASAR imaging on Dec.6,2005.The retrieved wind speeds are compared with those from both the NCEP/QSCAT blended sea surface wind speeds and daily averaged Quick Scatter meter sea surface wind speeds.The results gave that they are in good agreement.The root\|mean\|square errors of wind speed are 1.9 m/s and 1.6 m/s respectively,which show that SAR has the ability of retrieving the high resolution sea surface wind speeds,and give the orientation of SAR sea surface wind field business application in future.
Using the Longuet\|Higgins linear model of ocean wave and JONSWAP spectrum,the ocean wave directional spectrum is represented.Supposing bragg scattering,the mapping transform between ocean spectrum and SAR imagery spectrum is deduced,which is adapted to the linear wave-SAR imaging scope.Using Monte Carlo method,we can generate ocean direction spectrum which have characteristics of random.For Gaussian sea surface,the computation efficiency of the method is moderated.The simulation results are shows that there are distortions,split spectrum in range and the azimuth displacement between ocean spectrum and SAR imagery spectrum.
This paper aims to extracting the copper mine information using Hyperion data from areas with different land cover condition.The L1 level Hyperion data is first preprocessed including band selection,destriping,atmosphere correction and geometric correction.Then different information extraction methods were adopted according to the different vegetation cover conditions.Spectral angle mapping (SAM) method is applied directly in the open canopy area.In vegetated area,we used a vegetation physiology abnormal indicator,which is calculated by hyperspectral vegetation index,to indicate accumulations of copper ion,then to identify copper mine indirectly.The experimental result shows that using complementary information from these two methods synthetically could benefit to extract the copper mine information in the area even covered by complex vegetation distribution.
Three Gorges reservoir regions landslides calamities are serious,using traditional monitoring methods monitor landslides which are inefficient and cost enormously.This paper study new deformation monitoring method\|the repeat\|pass spaceborne SAR interferometry developed rapidly on the recent years.based on the characteristics of atmospheric water vapor near surface vary frequently,this paper analyses atmospheric water vapour effects on the repeat\|pass spaceborne SAR interferometry.After demonstrating Zebker's correlated conclusions,discuss the feasibility of monitoring Three Gorges reservoir regions landslides by using repeat\|pass spaceborne SAR interferometry.
Time\|series of Normalized Difference Vegetation Index (NDVI) datasets have been used in detecting the long\|term vegetation cover changes in regional,continental or global scales.They are also successfully applied to extract the biophysical parameters of vegetation cover.Normally,there are quite frequently fluctuations because of atmospheric condition and sensor effect in the NDVI dataset.According to the comparative analysis of five widely used NDVI reconstruction algorithms,two integrated approaches were developed based on standard deviation weight and characteristics of noise points respectively.The reconstructed results were validated and assessed by using some in\|suit NDVI measurements carried out during late May to early August,2009.The result shows that these two integrated methods are better than the five separate methods above.They do not only retain most of the original data,but also modify the noise to the utmost extent.NDVI time series datasets produced by these two approaches can be better applied in the researches on global and regional environmental change,vegetation dynamic,and so on.
