Land-Parcel Land-Use History as a Key to Site Selection for Documenting Soil Contamination Risk： a Case Study from Australian Suburbia

In that orcharding in early-to-mid twentieth century southeastern Australia involved use of certain heavy metal and As compounds in regular pest-control spray procedures, some interest attaches to the possibility that these landparcels are underlain by soils with above-background Cu, Pb and As levels. Interpreta- tion of Land-cover changes allowed land parcels previously occupied by orchards to be identified in the 1950s through time-series air-photos. A comparison of soil analysis results referring to soil samples from control sites, and from land parcels formerly occupied by orchardists, shows that contamination （above-background） levels of cations in the pesticides can be found in the top 6 cm of former orchard soils. It is clear that digital spatial data handling and culturally-informed air photo interpretation has a place in soil contamination studies, land-use planning （with particular reference to re-development） and in administration of public health.     

Verification of Net Primary Production Estimation Method in the Mongolian Plateau Using Landsat ETM＋ Data

We plan to estimate global net primary production (NPP) of vegetation using the Advanced Earth Observing Satellite-Ⅱ (ADEOS-Ⅱ) Global Imager (GLI) multi-spectral data. We derive an NPP estimation algorithm from ground measurement data on temperate plants in Japan. By the algorithm, we estimate NPP using a vegetation index based on pattern decomposition (VIPD) for the Mongolian Plateau. The VIPD is derived from Landsat ETM multi-spectral data, and the resulting NPP estimation is compared with ground data measured in a semi-arid area of Mongolia. The NPP estimation derived from satellite remote sensing data agrees with the ground measurement data within the error range of 15% when all above-ground vegetation NPP is calculated for different vegetation classifications.     

Quasi-quantitative relationship between soil moisture and polarization characteristics

Besides amplitude, frequency and phase, the polarization is another basic property of the electromagnetic wave. In the remote sensing field, the polarization is mainly applied in active detection systems of radar and lidar. This paper presents the quantitative relationship between soil moisture and polarization signatures in a certain type of soil in a farm. And this relationship is expected to be introduced on agriculture and hydrology ultimately. The experiments were performed both in the laboratory and the field. Soil samples with different moisture contents were measured at three wavebands on visible spectrum, and at several viewing angles in the plane of incidence. The polarization signature was indicated by the multi-band and multi-angle degree of linear polarization (DOLP) in this paper. The soil moisture were divided into five levels according to the properties of DOLP curves, namely, the quasi-quantitative relationship between soil moisture and its polarization signature were established. The percentages of soil moisture of the five levels are: ≤10%, 10%-20%, 20%-40%, 40%-56% and 56%, respectively. Although this division for soil moisture is on a rather large scale, it will meet the precision of application agricultural and hydrologic remote sensing.     

Vertical Crustal Displacements Due to Surface Fluid Changes

Using the model data for surface mass changes of the atmosphere, ocean, soil moisture and snow depth, the vertical crustal displacements of 25 ficual stations in China were calculated according to the ...     

Quasi-quantitative relationship between soil moisture and\npolarization characteristics

Besides amplitude, frequency and phase, the polarization is another basic property of the electromagnetic wave. In the remote sensing field, the polarization is mainly applied in active detection systems of radar and lidar. This paper presents the quantitative relationship between soil moisture and polarization signatures in a certain type of soil in a farm. And this relationship is expected to be introduced on agriculture and hydrology ultimately. The experiments were performed both in the laboratory and the field. Soil samples with different moisture contents were measured at three wavebands on visible spectrum, and at several viewing angles in the plane of incidence. The polarization signature was indicated by the multi-band and multi-angle degree of linear polarization (DOLP) in this paper. The soil moisture were divided into five levels according to the properties of DOLP curves, namely, the quasi-quantitative relationship between soil moisture and its polarization signature were established. The percentages of soil moisture of the five levels are: ≤10%, 10%—20%, 20%—40%, 40%—56% and >56%, respectively. Although this division for soil moisture is on a rather large scale, it will meet the precision of application agricultural and hydrologic remote sensing.     

Application of Remote Sensing and GIS Technology to the Study of Desertification of Arable Lands in North Shaanxi, China

The policy of the Chinese government concerning the horizontal expansion of the cultivated land through the reclamation of desert soils result in a total increase of 665. 985 km^2 during the period 1987-1999 in North Shaanxi. This increase is less than the loss in arable land by urbanization. The accelerated rate of change in agricultural areas calls for more rapid surveys of urbanization and loss of arable land. Remote sensing has a number of advantages over ground-based methods for such surveys. The multi-scale concept of remote sensing data help us study the problem in four towns. Several maps were produced to analyze the situation of urban coverage in different times. The evaluation of the status, rate and risk of urbanization are based on an accepted average of urban increase as 2% of population growth per year.     

Nontectonic signals in reprocessed continuous GPS position time series of CMONOC

The nearly nine-year continuous GPS data collected since 1 March 1999 from the Crustal Motion Observation Network of China(CMONOC) were consistently analyzed.Most of the nonlinear movements in the cumulative position time series pro-duced by CMONOC data center disappeared;and more accurate vertical terms and tectonic signals were extracted.Displacements caused by atmospheric pressure loading,nontidal ocean loading,soil moisture mass loading,and snow cover mass loading using the National Centers for Environmental Prediction(NCEP) Reanalysis I/II models and Estimation of the Circulation and Climate of the Ocean(ECCO) data can explain most of the vertical annual terms at many stations,while only parts can be explained at Lhasa and southern coastal sites,indicating that there are some deformation mechanisms that are still unknown or not modeled accurately.The remarkable differences in vertical position time series for short-baseline sites reveal that GPS stations can be greatly affected by lo-cal factors;and attention should be paid when explaining observed GPS velocity vectors.     

Prediction of hydrothermal copper, gold, silver and lead-zinc in northwestern Yunnan using weight of evidence model

This paper discusses the application of the model in predicting for hydrothermal Cu, Ag, Au and Pb-Zn occurrences in northwestern Yunnan. Geochemical, lineament and lithology data were the selected recognition criteria. The mentioned criteria varied against 75 known hydrothermal occurrences; the geochemical data had a weight of （W^＋= 1. 209 7, W^- =-0. 748 1） being the maximum among the three and the rest lineament and lithology have （W^＋= 0.7424, W^-= -0.449 6）, （W^＋= 0.378 7,W^-=-0.6243） respectively. The application was successful since the predicted results covers about 70% of the known deposits and predicted unknown areas.     

Cross-Coupling Correction for LaCoste ＆ Romberg Airborne Gravimeter

Abstract The cross-coupling corrections for the LaCoste ＆ Romberg airborne gravimeter are computed as a linear combination of 5 so-called cross-coupling monitors. The weight factors （coefficients） determined from marine gravity data by the factory are obviously not optimal for airborne application. These coefficients are recalibrated by minimizing the difference between airborne data and upward continued surface data （external calibration） and by minimizing the errors at line crossings （internal calibration） respectively. An integrating method to recalibrate the above-mentioned coefficients and the beam scale factor simultaneously is also presented. Experimental results show that the systemic errors in the airborne gravity anomalies can be greatly reduced by using any of the recalibrated coefficients. For example, the systemic error is reduced from 4.8 mGal to 1.8 mGal in Datong test.     

基于能量守恒的星间距离变率与地球重力场频谱关系的建立与分析(英文)

The spectral relationship between range-rate measurements and the gravity potential for low-low satellite-to-satellite tracking mission was established based on the energy conservation theory. Then the performances of satellite separation, the orbital altitude, and the accuracy of range-rate measurements in recovering the earth’s gravity field were simulated and analyzed by this method. Finally, the cumulative geoid errors of the reference mode were obtained by using the configuration parameters of the GRAC...     

Semiparametric Regreswsion and Model Refining

This paper presents a semiparametric adjustment method suitable for general cases.Assuming that the regularizer matrix is positive definite,the calculation method is discussed and the corresponding formulae are presented.Finally,a simulated adjustment problem is constructed to explain the method given in this paper,The results from the semiparametric model and G-M model are compared.The results demonstrate that the model errors or the systematic errors of the observations can be detected correctly with the semiparametric estimate method.     

Comparative assessment of the relationship of satellite data with the above ground biomass of Sal trees (<Emphasis Type="Italic">Shorea robusta</Emphasis>) determined from phenologically different time periods

The Above Ground Biomass(AGB) estimates of vegetation comprise both the bole biomass determined through a volumetric equation and litter biomass collected from the ground.For mature trees,the AGB estimated in phenologically different time periods is directly affected by the litter biomass since the Diameter at Breast Height(DBH) and height(H) of such trees that are used in the estimation of bole biomass would remain unchanged over a reasonable time period.In the present study,we have determined the AGB of Sal trees(Shorea robusta) in two contrasting seasons:the peak green period in October being devoid of lit-ter on the ground and the leaf shedding period in February with abundant amount of litter present on the ground.Estimation of AGB for the month of February included the litter biomass.In contrast,the AGB for October represented only the bole biomass.AGB was estimated for ten different plots selected in the study area.The AGB estimated from ten sampling plots for each time period was re-gressed with the individual tree parameters such as the average DBH and height of trees measured from the corresponding plots.The regression analysis exhibited a significantly stronger relationship between the AGB and DBH for the month of October as compared to February.Furthermore,the correlation between the remotely sensed derived data and AGB was also found to be significantly higher for the month of October than February.This observation indicates that inclusion of the litter biomass in AGB will tend to decrease the re-gression relationship between AGB and DBH and also between the remotely sensed data and AGB.Therefore,these conclusions invite careful consideration while estimating AGB from satellite data in phenologically different time periods.     

Unbiased estimation formula of unit weight standard deviation in regularization solution

Regularization method is an effective method for solving ill-posed equation. In this paper the unbiased estimation formula of unit weight standard deviation in the regularization solution is derived and the formula is verified with numerical case of 1000 sample data by use of the typical ill-posed equation, i.e. the Fredholm integration equation of the first kind.     

用气象卫星数据对冬小麦进行估产的试验

The NOAA is a special meteorological satellite. The first and second channels of the AVHRP (the sensor of NOAA) are much similar to the fifth and seventh channels of the resource satellite MSS, and their corresponding spectral response curves are much alike. The AVHRR'S first channel has a higher reflectivity from soil, and the second channel is highly reflected by vegetation. By virtue of its wide sensitivity range, multiple reception orbitals, economical and convenient, it has been used in the W.S.A. in the agricultural estimation.According to the characteristic spectra from the vegetation, and through the digital exchange of the measuraed values on the first and second channels of the NOAA/AVHRR, We established a servies of green models which can be need in making agricultural estimation satisfactorily.As expesimentally showed that these green models highly correlated to the yeild of crops. This has been presently becoming the main information sources for yield estiraatings. With the forecast of the     

Discriminant models for uncertainty characterization in area class change categorization

Discriminant space defining area classes is an important conceptual construct for uncertainty characterization in area-class maps.Discriminant models were promoted as they can enhance consistency in area-class mapping and replicability in error modeling.As area classes are rarely completely separable in empirically realized discriminant space,where class inseparabil-ity becomes more complicated for change categorization,we seek to quantify uncertainty in area classes(and change classes)due to measurement errors and semantic discrepancy separately and hence assess their relative margins objectively.Experiments using real datasets were carried out,and a Bayesian method was used to obtain change maps.We found that there are large differences be-tween uncertainty statistics referring to data classes and information classes.Therefore,uncertainty characterization in change categorization should be based on discriminant modeling of measurement errors and semantic mismatch analysis,enabling quanti-fication of uncertainty due to partially random measurement errors,and systematic categorical discrepancies,respectively.     

GPS rapid static and kinematic positioning based on GPS active network

This paper presents a data processing strategy for GPS kinematic Positioning by using a GPS active network to model the GPS errors in double difference observable.Firstly,the double difference residuals are estimated between the reference stations in the active network.Then the errors at a user station are predicted as the network corrctions to user measurements,based on the location of the user,Finally conventional kinematic positioning algorithms can be applied to determine the position of the user station.As an example,continuous 24-hour GPS data in March 2001 has been processed by this method.It clearly demonstrates that,after applying these corrections to a user within the network,both the success rate for ambiguity resolution and the positioning accuracy have been significantly improved.     

A case study of using external DEM in InSAR DEM generation

Synthetic aperture radar interferometry (InSAR) has been used as an innovative technique for digital elevation model (DEM) and topographic map generation. In this paper, external DEMs are used for InSAR DEM generation to reduce the errors in data processing. The DEMs generated from repeat-pass InSAR are compared. For steep slopes and severe changes in topography, phase unwrapping quality can be improved by subtracting the phase calculated from an external DEM. It is affirmative that the absolute height accuracy of the InSAR DEM is improved by using external DEM. The data processing was undertaken without the use of ground control points and other manual operation.     

Expert Classification Method Based on Patch-Based Neighborhood Searching Algorithm

The expert knowledge has been widely used to improve the remotely sensed classification accuracy. Generally, the ex-pert classification system mainly depends on DEM and some thematic maps. The spatial relationship information in pixel level was commonly introduced into the expert classification. Because the geographic objects were found spatially dependent relationship to a certain degree, the commonly used basic unit of spatial relationship information in pixel greatly limited the efficiency of spatial in-formation. A patch-based neighborhood searching algorithm was proposed to implement the expert classification. The homogene-ous spectral unit, patch, was used as the basic unit in the spatial object granularity, and different types of patches' relationship in-formation were obtained through a spatial neighborhood searching algorithm. And then the neighborhood information and DEM data were added into the expert classification system and used to modify the primitive classification errors. In this case, the classi-fication accuracies of wetland, grassland and cropland were obviously improved. In this work, water was used as base object, and different types of water extraction methods were tested to get a result in a high accuracy.     

Application of GIS to estimate soil erosion using RUSLE

This paper describes the use of the Arc/Info and ArcView GIS tools to estimate soil erosion with Universal Soil Loss Equation (USLE).Calculations are be done by using capabilities available.This study start with a digital elevation model(DEM) of Shaanxi,which was created by digitizing contour and spot heights from the topographic map on 1:250000 scale and grid themes for the USLE K and C factors.It is note worthy that USLE K can be obtained by adding the K factor as an attribute to a soil theme‘s table.The C can be obtained from tables or using the information about land use and management given by USLE program.A land use theme can be used to add the C factors as an attribute field.The purpose of this study is to establish spatial information of soil erosion using USLE and GIS and discuss the analysis of the soil erosion and slope failures in GIS and formulate the possible framework.