On the application of DInSAR to deformation monitoring in desert areas

The DInSAR technique is used for monitoring the desert height changes to study sandstorms. Hunshandake Sandy Land, as the test area, is one of the main sources of sandstorms in Beijing. In order to study the sandstorm source and its impact, a pair of EnviSat ASAR images of Oct. 11, 2005, and Oct. 26, 2004, is processed on the basis of analysis of six ERS-2 and EnviSat radar images. After the image configuration, flat earth effect correction, data filtering, phase unwrapping, and geo-coding, a deformation model over Hunshandake desert is built. According to the results, the height decreased in most areas and increased in a few areas, which basically coincides with the strong sandstorm appearing in Beijing in the Spring of 2005. The results show DInSAR has an important role in monitoring of desert surface deformation.

Linear-regression models and algorithms based on the Total-Least-Squares principle

In classical regression analysis, the error of independent variable is usually not taken into account in regression analysis. This paper presents two solution methods for the case that both the independent and the dependent variables have errors. These methods are derived from the condition-adjustment and indirect-adjustment models based on the Total-Least-Squares principle. The equivalence of these two methods is also proven in theory.

Assimilating ASAR Data for Estimating Soil Moisture Profile Using an Ensemble Kalman Filter

Active microwave remote sensing data were used to calculate the near-surface soil moisture in the vegetated areas.In this study,Advanced Synthetic Aperture Radar(ASAR)observations of surface soil moisture content were used in a data assimilation framework to improve the estimation of the soil moisture profile at the middle reaches of the Heihe River Basin,Northwest China.A one-dimensional soil moisture assimilation system based on the ensemble Kalman filter(EnKF),the forward radiative transfer model,crop model,and the Distributed Hydrology-Soil-Vegetation Model(DHSVM)was developed.The crop model,as a semi-empirical model,was used to estimate the surface backscattering of vegetated areas.The DHSVM is a distributed hydrology-vegetation model that explicitly represents the effects of topography and vegetation on water fluxes through the landscape.Numerical experiments were conducted to assimilate the ASAR data into the DHSVM and in situ soil moisture at the middle reaches of the Heihe River Basin from June20 to July 15,2008.The results indicated that EnKF is effective for assimilating ASAR observations into the hydrological model.Compared with the simulation and in situ observations,the assimilated results were significantly improved in the surface layer and root layer,and the soil moisture varied slightly in the deep layer.Additionally,EnKF is an efficient approach to handle the strongly nonlinear problem which is practical and effective for soil moisture estimation by assimilation of remote sensing data.Moreover,to improve the assimilation results,further studies on obtaining more reliable forcing data and model parameters and increasing the efficiency and accuracy of the remote sensing observations are needed,also improving estimation accuracy of model operator is important.

Geometric calibration of high-resolution remote sensing sensors

This paper introduces the applications of high-resolution remote sensing imagery and the necessity of geometric calibration for remote sensing sensors considering assurance of the geometric accuracy of remote sensing imagery. Then the paper analyzes the general methodology of geometric calibration. Taking the DMC sensor geometric calibration as an example, the paper discusses the whole calibration procedure. Finally, it gave some concluding remarks on geometric calibration of high-resolution remote sensing sensors.

Progress in application of MODIS for remote sensing in Polar Regions

The remote sensing technique is widely used in Polar Regions,and Moderate Resolution Imaging Spectroradiomete（MODIS） is one of the most important satellite sensors in the domain of remote sensing.In this article,MODIS sensor,including the information of its satellites,its system constitutes,its hardware characteristic,its large spectra and usual applications are briefly introduced first.Then,there is a particular introduction of MODIS＇s use in Polar Regions,which refers to the polar physiognomy,polar atmosphere and polar ocean,with citing many examples.At last,views about the development of MODIS and its series sensors in the future,including the improved applications in Polar Regions are given.

Similarity Measures of Satellite Images Using an Adaptive Feature Contrast Model

Similarity measurement is one of key operations to retrieve “desired” images from an image database. As a famous psychological similarity measure approach, the Feature Contrast (FC) model is defined as a linear combination of both common and distinct features. In this paper, an adaptive feature contrast (AdaFC) model is proposed to measure similarity between satellite images for image retrieval. In the AdaFC, an adaptive function is used to model a variable role of distinct features in the similarity measurement. Specifically, given some distinct features in a satellite image, e.g., a COAST image, they might play a significant role when the image is compared with an image including different semantics, e.g., a SEA image, and might be trivial when it is compared with a third image including same semantics, e.g., another COAST image. Experimental results on satellite images show that the proposed model can consistently improve similarity retrieval effectiveness of satellite images including multiple geo-objects, for example COAST images.

Overview of the key technologies for high-resolution satellite mapping

As the important infrastructures for land mapping and resource monitoring,highresolution remote sensing satellites(HRSS)are urgently demanded for the development of China.In this article,the key technologies of the main HRSS are summarized,and these technologies include sensor design,attitude and orbit determination,geometric calibration,imaging model construction,and block adjustment,etc.,which involve the mapping accuracy of HRSS.Finally,the system design of the ZY-3 Satellite(China’s first civil stereoscopic surveying and mapping satellite,to be launched in 2012)is introduced,which mainly include satellite technical specifications and strategies design based on these key technologies research.

Comparison of leaf area index inversion for grassland vegetation through remotely sensed spectra by unmanned aerial vehicle and field-based spectroradiometer

Aims Remote sensing technology has been proved useful in mapping grass-land vegetation properties.Spectral features of vegetation cover can be recorded by optical sensors on board of different platforms.With increas-ing popularity of applying unmanned aerial vehicle(UAV)to mapping plant cover,the study aims to investigate the possible applications and potential issues related to mapping leaf area index(LAI)through integra-tion of remote sensing imagery collected by multiple sensors.Methods This paper applied the collected spectral data through field-based(FLD)and UAV-borne spectroradiometer to map LAI in a Sino-German experiment pasture located in the Xilingol grassland,Inner Mongolia,China.Spectroradiometers on FLD and UAV platforms were taken to measure spectral reflectance related to the targeted vegetation proper-ties.Based on eight vegetation indices(VIs)computed from the col-lected hyperspectral data,regression models were used to inverse LAI.The spectral responses between FLD and UAV platforms were com-pared,and the regression models relating LAI with VIs from FLD and UAV were established.The modeled LAIs by UAV and FLD platforms were analyzed in order to evaluate the feasibility of potential integra-tion of spectra data for mapping vegetation from the two platforms.Important Findings Results indicated that the spectral reflectance between FLD and UAV showed critical gaps in the green and near-infrared regions of the spec-trum over densely vegetated areas,while the gaps were small over sparsely vegetated areas.The VI values from FLD spectra were greater than their UAV-based counterparts.Out of all the VIs,broadband gen-eralized soil-adjusted vegetation index(GESAVI)and narrow-band nNDVI2 were found to achieve the best results in terms of the accuracy of the inversed LAIs for both FLD and UAV platforms.We conclude that GESAVI and nNDVI2 are the two promising VIs for both platforms and thus preferred for LAI inversion to carry spectra integration of the two platforms.We suggest that accuracy on the LAI inversion could be improved by applying more advanced functions(e.g.non-linear)con-sidering the observed bias for the difference between the UAV-and FLD-inversed LAIs,especially when LAI was low.

Improving Gravity Anomalies Over China Marginal Sea from Retracked Geosat and ERS-1 Data

The quality of altimeter data and ocean tide model is critical to the recovery of coastal gravity anomalies. In this contribution, three retracking methods (threshold, improved threshold and Beta-5) are investigated with the aim of improving the altimeter data over a shallow water area. Comparison indicates that the improved threshold is the best retracking method over China Sea. Two ocean tide models, NAO99b and CSR4.0, are analyzed. Results show that different tide models used in the processing of altimeter data may result in differences more than 10 mGal in recovered coastal gravity anomalies. Also, NAO99b is more suitable than CSR4.0 over the shallow water area of China Sea. Finally, gravity anomalies over China Sea are calculated from retracked Geosat/GM and ERS-1/GM data by least squares collocation. Comparison with shipborne gravimetry data demonstrates that gravity anomalies from retracked data are significantly superior to those from non-retracked data. Our results have the same order as the other two altimeter-derived gravity models: Sandwell&Smith(V16) and DNSC08.

The tidal signals extraction from GPS data on the Amery Ice Shelf, Antarctica

Tidal motion is the source of short-term vertical motion that an ice shelf experiences, and hence has a significant impact on ice shelves. During the 2003/2004 Austral summer season, five days of GPS measurements were carried out on the front of the Amery Ice Shelf （AIS）, East Antarctica, by the 20th Chinese National Antarctica Research Expedition （CHINARE）. The GPS data was processed using GAMIT/GLOBK software with 2-hour static data segment and the vertical precision is less than 0.18 m. To verify our results for the vertical component, we compare the ice shelf GPS tidal signal with a tidal result derived from tide gauge measurements at China＇s Zhongshan Station on Antarctica. Comparison of the GPS results with the tide gauge were in good agreement in amplitude at the few cm level, which indicates that the tide under the front of Amery Ice Shelf is irregular semidiurnal tide, the maximal tidal differences is approximately 2 m. GPS data can be used to validate the ocean tide model around the Antarctic area and such studies are important to improve our knowledge of the Antarctic ice shelf mass balance and dynamical models of ice sheet/ocean interaction.

Combined multi-kernel support vector machine and wavelet analysis for hyperspectral remote sensing image classification

Many remote sensing image classifiers are limited in their ability to combine spectral features with spatial features. Multi-kernel classifiers, however, are capable of integrating spectral features with spatial or structural features using multiple kernels and summing them for final outputs. Using a support vector machine （SVM） as classifier, different multi-kernel classifiers are constructed and tested using 64-band Operational Modular Imaging Spectrometer II hyperspectral image of Changping Area, Beijing City. Results show that by integrating spectral and wavelet texture information, multi-kernel SVM classifiers can obtain more accurate classification results than sole-kernel SVM classifiers and cross-information SVM kernel classifiers. Moreover, when the multi-kernel SVM classifier is used, the combination of the first four principal components from principal component analysis and wavelet texture provides the highest accuracy （97.06%）. Multi-kernel SVM is therefore an effective approach to improve the accuracy of hyperspectral image classification and to expand possibilities for remote sensing image interpretation and application.

Using object-based analysis to derive surface complexity information for improved filtering of airborne laser scanning data

Airborne laser scanning （ALS） is a technique used to obtain Digital Surface Models （DSM） and Digital Terrain Models （DTM） efficiently, and filtering is the key procedure used to derive DTM from point clouds. Generating seed points is an initial step for most filtering algorithms, whereas existing algorithms usually define a regular window size to generate seed points. This may lead to an inadequate density of seed points, and further introduce error type I, especially in steep terrain and forested areas. In this study, we propose the use of object- based analysis to derive surface complexity information from ALS datasets, which can then be used to improve seed point generation. We assume that an area is complex if it is composed of many small objects, with no buildings within the area. Using these assumptions, we propose and implement a new segmentation algorithm based on a grid index, which we call the Edge and Slope Restricted Region Growing （ESRGG） algorithm. Surface complexity information is obtained by statistical analysis of the number of objects derived by segmentation in each area. Then, for complex areas, a smaller window size is defined to generate seed points. Experimental results show that the proposed algorithm could greatly improve the filtering results in complex areas, especially in steep terrain and forested areas.

A Method for Retrieving Vertical Ozone Profiles from Limb Scattered Measurements

A two-step method is employed in this study to retrieve vertical ozone profiles using scattered measure- ments from the limb of the atmosphere. The combination of the Differential Optical Absorption Spectroscopy （DOAS） and the Multiplicative Algebraic Reconstruction Technique （MART） is proposed. First, the limb radiance, measured over a range of tangent heights, is processed using the DOAS technique to recover the effective column densities of atmospheric ozone. Second, these effective column densities along the lines of sight （LOSs） are inverted using the MART coupled with a forward model SCIATRAN （radiative transfer model for SCIAMACHY） to derive the ozone profiles. This method is applied to Optical Spectrograph and Infra Red Imager System （OSIRIS） radiance, using the wavelength windows 571–617 nm. Vertical ozone profiles between 10 and 48 km are derived with a vertical resolution of 1 km. The results illustrate a good agreement with the cloud-free coincident SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY （SCIAMACHY） ozone measurements, with deviations less than ± 10% （ ± 5% for altitudes from 17 to 47 km）. Furthermore, sensitivities of retrieved ozone to aerosol, cloud parameters and NO 2 concentration are also investigated.

Analysis of error sources on orbital atomic clocks’stability

As a rule,stability calculation of atomic clock requires observations with equivalent sampling interval.Apart from atomic clocks in laboratory,orbital atomic clock stability calculations are impacted of raw data sampling intervals,noncontinuous time series,non-data segment,frequency drift,and other factors.So,the calculated stability results are not so exact.In this article,the impacts of kinds of error sources on Allan and Hadamard variances are analyzed using global positioning system satellite precise clock offset data.And the laws of variety are summarized.

New form of geodetic coordinate system taking two length quantity as coordinate parameters

A new form of geodetic coordinate system based on geodesic coordinates instead of geodetic longitude and latitude was proposed.The vertical and horizontal geodesic coordinates measured with length were defined as coordinate parameters,but the two families of coordinate curves were still meridians and parallel circles.The first fundamental form on the ellipsoidal surface and its three coefficients were deduced by the geodesic coordinate.The formula for the latitudinal scale factor of length for geodetic parallel lines was derived,by which the obtained result conformed to that standard value calculated from geodetic latitude,and it is applicable in the range of 400 km from north to south.Therefore,it lays the foundation for establishing the differential equation and differential relationship based on this type of coordinate parameters;and consequently,it is convenient and accurate enough to operate on the ellipsoidal surface in this new form of geodetic coordinate system.

Application of the RPC model for spaceborne SAR image geometric processing

An increasing number of low,medium,and high resolution SAR satellites creates a demand for a generalized sensor model to replace the rigorous sensor model(RSM).The rational polynomial coefficient(RPC)model is a generic sensor model which accurately fits the object-image geometry for various sensor systems with different coefficient values.It has been widely used as an alternative to RSM for photogrammetric processing of optical images,but its applications to SAR images are rarely discussed in publications.In this paper,the feasibility and practicability of the RPC model for SAR images are studied.The RPC model can not only be used to replace the RSM(range–Doppler model for SAR),but also applied to the processing chain for SAR data,thus facilitating the processing of SAR and InSAR data for end users.

A high-level architecture for a Geomatics Informatization Technology System: the Chinese case

China will,as a component of‘Digital Earth,’establish a Geomatics Informatization Technology System(GITS)which is characterized by real-time acquisition,automatic processing,networking service,and socialized application with fundamental geographical information.The basic composition of GITS is proposed.GITS covers four layers and six platforms.The four layers are data acquisition,processing,management,and application and services.The six platforms are informatic geodetic datum,high-precision geo-spatial data acquisition,automatic geo-spatial data processing,grid-based geo-spatial information management,comprehensive geo-spatial information sharing and service,and geo-spatial information integration and application.The informatic geodetic datum platform provides a carrier for all the four layers and a base for the other five platforms.The high-precision geo-spatial data acquisition platform belongs to the acquisition layer.The automatic geo-spatial data processing platform belongs to the processing layer.The grid-based geo-spatial information management platform belongs to the management layer and is a bridge connecting geospatial data acquisition and spatial information sharing service and integrated applications.The comprehensive geo-spatial information sharing and service platform belongs to the application and service layer.Finally,this paper presents thoughts for constructing GITS.

Application of Inertia Ellipse in Code Marker Matching

In close-range photogrammetry, 3D information acquisition is based on image matching. The application of code marker helps to improve the level of automatic matching and the matching accuracy. This paper inyestigates the application of inertia ellipse algorithm to code marker matching. We can calculate the inertia ellipse of a target with a certain boundary. First, the method is applied to a single code marker; the angle and scaling are valid. Then, the paper introduces the multi code markers matching method by the inertia ellipse. Rotation and scaling changes of homonymy images can be calculated by inertia ellipse algorithm. These parameters can be used for code marker matching in arbitrary attitude close-range photogrammetry.

Ice-sheet surface elevation change from crossover of ENVISAT data

Understanding the current state of the polar ice sheets is critical for determining their contribution to sea-level rise and predicting their response to climate change.Surface elevation time series especially can be used to study ice-sheet dynamics and the mass or volume balance of the ice sheets,which are relevant to global climate change and sea-level rise.During the last two decades,satellite radar altimetry or airborne laser altimetry could obtain accuracy by an order of magnitude greater than the traditional airborne barometric altimetry,which has a precision of typically several tens of meters at best and only a limited coverage.The widest coverage comes from satellites,especially from the ERS1/2 and ENVISAT,which extends to 81.5°of latitude,covering almost all of Greenland and most of Antarctica.In this paper,an algorithm for time series analysis based on crossover was used to obtain 4-year(September 2002–March 2007)ice-sheet elevation changes from ENVISAT data.The height of the whole Antarctic ice sheet has a decline of about 0.4±0.43 cm from September 2002 to March 2007.The time series data present clearly a seasonal and annual signal feature;that the ice sheet thickens in March.From the time series data,the seasonal and annual signal can be observed clearly.

Regional gravity field modeling based on rectangular harmonic analysis

Regional gravity field modeling with high-precision and high-resolution is one of the most important scientific objectives in geodesy, and can provide fundamental information for geophysics, geodynamics, seismology, and mineral exploration. Rectangular harmonic analysis （RHA） is proposed for regional gravity field modeling in this paper. By solving the Laplace＇s equation of gravitational potential in local Cartesian coordinate system, the rectangular harmonic expansions of disturbing potential, gravity anomaly, gravity disturbance, geoid undulation and deflection of the vertical are derived, and so are the formula for signal degree variance and error degree variance of the rectangular harmonic coefficients （RHC）. We also present the mathematical model and detailed algorithm for the solution of RHC using RHA from gravity observations. In order to reduce the edge effects caused by periodic continuation in RHA, we propose the strategy of extending the size of computation domain. The RHA-based modeling method is validated by conducting numerical experiments based on simulated ground and airborne gravity data that are generated from geopotential model EGM2008 and contaminated by Gauss white noise with standard deviation of 2 mGal. The accuracy of the 2.5＇×2.5＇ geoid undulations computed from ground and airborne gravity data is 1 and 1.4 cm, respectively. The standard error of the gravity disturbances that downward continued from the flight height of 4 km to the geoid is only 3.1 reGal. Numerical results confirm that RHA is able to provide a reliable and accurate regional gravity field model, which may be a new option for the representation of the fine structure of regional gravity field.