随机森林回归模型的悬浮泥沙浓度遥感估算

三峡工程蓄水以来,清水下泄,坝下游河段发生了长时间、长距离的沿程冲刷,河流悬浮泥沙浓度发生改变,给沿岸生态系统带来了不利影响。随机森林算法灵活、稳健,已被广泛应用于各类生态环境变量的回归预测分析,但其在水体悬浮泥沙浓度估算方面的能力尚未得到充分认识。基于泥沙站点监测数据和MODIS卫星遥感反射率数据,通过构建随机森林非参数回归预测模型,对三峡工程坝下游宜昌至城陵矶河段在建坝前后14年间(2002年—2015年)各月的悬浮泥沙浓度进行遥感估算。研究表明:(1)基于随机森林的悬浮泥沙浓度估算模型表现较好,模型预测值与实测值间相关性好、预测精度高,优于其他模型(线性回归、支持向量机、人工神经网络模型)。(2)在参与模型构建的MODIS波段变量中,红波段被认为是最重要的预测变量,但不能单独使用它进行预测,悬浮泥沙遥感预测需要多变量共同参与。(3)将悬浮泥沙数据按季节分类所构建的随机森林模型,其平均误差为0.46 mg/L,平均相对均方根误差为12.33%,估算效果最优,能够满足较高精度下悬浮泥沙浓度估算的需求。综上,可以考虑以季节为划分依据,用随机森林回归模型估算悬浮泥沙浓度,并用于后期坝下游河道悬浮泥沙浓度时空反演。     

Phytoplankton Variability in the Bay of Bengal During Winter Monsoon Using Oceansat-1 Ocean Colour Monitor Data

Quantitative assessment of chlorophyll-a concentration and its variability is an important input for the oceanic primary productivity modeling and also a key parameter in the global carbon cycle studies. This present work is focused to understand the spatial and temporal variability of phytoplankton in the Bay of Bengal (BOB) during winter monsoon season of October 1999 to March 2000 using Ocean Colour Monitor (OCM) sensor onboard OCEANSAT-1 satellite. Daily chlorophyll-a images from OCM sensor were used in the study. Efforts were also put to study the correlation between chlorophyll-a concentrations; NOAA-AVHRR derived Sea Surface Temperature (SST) and QuickSCAT scatterometer derived wind stress data. Analysis of the chlorophyll-a images shows the presence of extensive phytoplankton blooms during mid December 1999 to early January 2000 in the western part of BOB. The bloom dominated regions also exhibit reduced SST (∼24–27°C) and enhanced wind stress indicating upwelling processes leading nutrient entrainment in the upper column of the sea surface. Apart from this, higher phytoplankton biomass associated with the fresh water reverine plumes has also been observed. During October 1999 a super cyclone was active in the BOB, as increase in the productivity was observed in the early November 1999 images of OCM data due to the cyclone induced churning of the water column.     

Can suspended sediment concentrations be estimated from multispectral imagery using only image-derived information?

Sampling for suspended sediment concentrations (SSC) in inland waters is traditionally based on collecting samples at sparse locations and in limited intervals. A number of investigators explored the utility of earth-observing satellites and air-borne sensors for monitoring of SSC over vast areas. Two approaches are commonly deployed: (1) empirical relationships between a chosen remotely sensed quantity and the actual in-situ SSC; and (2) bio-optical models founded on radiative transfer modeling. Unfortunately, in-situ measurements are often unavailable for direct image calibration, and inherent optical properties of optically active constituents (specific scattering and absorption coefficients) are usually unknown. This paper examines the possibility to retrieve SSC from multispectral satellite imagery without any in-situ data, i.e. using only image-derived information. The fundamental principle of image selfcalibration relies on the fact that in the visual domain of wavelengths (∼400–700 nm) the at-sensor reflectance becomes “saturated“ at high SSC, whereas the near-infrared domain (∼700–900 nm) remains almost perfectly linearly related to sediment concentrations. The core idea of the self-calibrating procedure is rather simple and is based on fitting an exponential function between reflectance and SSC, with SSC replaced by a linear relationship between SSC and reflectance in the near-infrared domain. As a first approximation of the non-linearity between reflectance and SSC levels in the 400–700 nm range, we used the equation proposed by Schiebe et al. (1992), although other equations, especially those arising from optical theory could be used as well. The technique is illustrated on a moderately sediment-laden reservoir and two scenes acquired from Landsat ETM+. The standard error of the estimated SSC was below 15 mg/L (i.e. ∼25 % relative error for the observed range of SSC). Although the proposed algorithm does not yield better results than other models mentioned in the literature, the primary advantage of the outlined methodology is that no in-situ measurements (water sampling nor spectral profiling) are needed — i.e. only image-derived information is used.     

Monitoring water turbidity and surface suspended sediment concentration of the Bagre Reservoir (Burkina Faso) using MODIS and field reflectance data

Monitoring turbidity and Surface Suspended Sediment Concentration (SSSC) of inland waters is essential to address several important issues: erosion, sediment transport and deposition throughout watersheds, reservoir siltation, water pollution, human health risks, etc. This is especially important in regions with limited conventional monitoring capacities such as West Africa. In this study, we explore the use of Moderate Resolution Imaging Spectroradiometer data (MODIS, MOD09Q1 and MYD09Q1 products, red (R) and near infrared (NIR) bands) to monitor turbidity and SSSC for the Bagre Reservoir in Burkina Faso. High values ​​of these parameters associated with high spatial and temporal variability potentially challenge the methodologies developed so far for less turbid waters. Field measurements (turbidity, SSSC, radiometry) are used to evaluate different radiometric indices. The NIR/R ratio is found to be the most suited to retrieve SSSC and turbidity for both in-situ spectoradiometer measurements and satellite reflectance from MODIS.The spatio temporal variability of MODIS NIR/R together with rainfall estimated by the Tropical Rainforest Measuring Mission (TRMM) and altimetry data from Jason-2 is analyzed over the Bagre Reservoir for the 2000–2015 period. It is found that rain events of the early rainy season (February-March) through mid-rainy season (August) are decisive in triggering turbidity increase. Sediment transport is observed in the reservoir from upstream to downstream between June and September. Furthermore, a significant increase of 19% in turbidity values is observed between 2000 and 2015, mainly for the July to December period. It is especially well marked for August, with the central and downstream areas showing the largest increase. The most probable hypothesis to explain this evolution is a change in land use, and particularly an increase in the amount of bare soils, which enhances particle transport by runoff.     

杭州湾HJ CCD影像悬浮泥沙遥感定量反演

利用环境小卫星CCD(HJ CCD)影像对杭州湾悬浮泥沙浓度(SSC)进行了反演研究。通过对杭州湾水体遥感反射率(Rrs)与SSC进行相关性分析发现,在690nm和830nm左右出现显著的反射峰,分别位于HJ CCD影像的第3和第4波段范围内;大于700nm波长处的Rrs与SSC相关性较好。基于实测Rrs和SSC之间的相关关系,利用第4和第3波段比值作为遥感因子建立SSC反演模型,模型决定系数达到0.90。借鉴近红外-短波红外(NIR-SWIR)结合的大气校正方法反演出的准同步MODIS气溶胶数据,实现了HJ CCD影像的大气校正,第3、第4波段的大气校正结果相对误差分别为5.54%和6.97%。结果显示,HJ CCD影像反演的SSC相对误差为7.12%;杭州湾悬浮泥沙浓度要显著高于长江口,且内部差异明显。研究表明,通过适当的大气校正方法和反演算法,HJ CCD影像可用于杭州湾悬浮泥沙浓度的估计。     

Mapping of Marine Chl-a and Suspended Solid Concentration Using OCM-2 Sensor

Chlorophyll-a (Chl-a) and Suspended Solid Concentration (SSC) shows the productivity of water and their surrounding environment. These parameters can be effectively estimated through several remote sensing techniques. From the recent reports on the Gulf of Thailand, it is found that Chl-a and SSC are increasing in coastal areas due to changing environment caused by variations in the global carbon cycle, climate change and water pollution linking to anthropogenic conditions such as high population density and rapid urbanization in neighbouring coastal areas deteriorating the coastal and marine environment. Various models are evaluated in this study for estimation of marine Chl-a and SSC by employing Ocean Colour Monitor-2 sensor of Oceansat-2 satellite for Northern Gulf of Thailand. The retrieval of Chl-a and SSC by the atmospheric correction of visible bands from 400 to 700 nm to attain normalized water-leaving radiances and then a suitable algorithm is applied. The In-situ reflectance values of sea waters are measured using the ASD spectroradiometer. The reflectance values of the spectroradiometer are correlated for the same day atmospherically corrected satellite reflectance and the analysis offers high correlation R² 0.73. Satellite derived, Chl-a and SSC are correlated with observed in situ Chl-a and SSC. This analysis offered better correlation of R² 0.86 and 0.85 respectively with the algorithms of Chl-a and SSC.     

Empirical models for estimating the suspended sediment concentration in Amazonian white water rivers using Landsat 5/TM

Suspended sediment yield is a very important environmental indicator within Amazonian fluvial systems, especially for rivers dominated by inorganic particles, referred to as white water rivers. For vast portions of Amazonian rivers, suspended sediment concentration (SSC) is measured infrequently or not at all. However, remote sensing techniques have been used to estimate water quality parameters worldwide, from which data for suspended matter is the most successfully retrieved. This paper presents empirical models for SSC retrieval in Amazonian white water rivers using reflectance data derived from Landsat 5/TM. The models use multiple regression for both the entire dataset (global model, N = 504) and for five segmented datasets (regional models) defined by general geological features of drainage basins. The models use VNIR bands, band ratios, and the SWIR band 5 as input. For the global model, the adjusted R² is 0.76, while the adjusted R² values for regional models vary from 0.77 to 0.89, all significant (p-value < 0.0001). The regional models are subject to the leave-one-out cross validation technique, which presents robust results. The findings show that both the average error of estimation and the standard deviation increase as the SSC range increases. Regional models were more accurate when compared with the global model, suggesting changes in optical proprieties of water sampled at different sampling stations. Results confirm the potential for the estimation of SSC from Landsat/TM historical series data for the 1980s and 1990s, for which the in situ database is scarce. Such estimates supplement the SSC temporal series, providing a more comprehensive SSC temporal series which may show environmental dynamics yet unknown.     

Atmospheric Correction Over Coastal Turbid Waters of Bay of Bengal Using OCEANSAT-I Ocean Colour Monitor (OCM) Data

Space-borne ocean-colour remote sensor-detected radiance is heavily contaminated by solar radiation backscattered by the atmospheric air molecules and aerosols. Hence, the first step in ocean-colour data processing is the removal of this atmospheric contribution from the sensor-detected radiance to enable detection of optically active oceanic constituents e.g. chlorophyll-a, suspended sediment etc. In standard atmospheric correction procedure for OCEANSAT-1 Ocean Colour Monitor (OCM) data, NIR bands centered at 765 and 865 nm wavelengths were used for aerosol characterization. Due to high absorption by water molecules, ocean surface in these two wavelengths acts as dark background, therefore, sensor detected radiance can be assumed to have major contribution from atmospheric scattering. For coastal turbid waters this assumption of dark surface fails due to the presence of highly scattering sediments which causes sufficient water-leaving radiance in NIR bands and lead to over-estimation of aerosol radiance resulting in negative water leaving radiance for λ < 700 nm. In the present study, for the turbid coastal waters in the northern Bay of Bengal, the concept of spatial homogeneity of aerosol and water leaving reflectance has been applied to perform atmospheric correction of OCAEANSAT-1 OCM data. The results of the turbid water atmospheric correction have also been validated using in-situ measured water-leaving radiance. Comparison of satellite derived water-leaving radiance for five coastal stations with in-situ measured radiance spectra, indicates an improvement over the standard atmospheric correction algorithm giving physically realistic and positive values. Root Mean Square Error (RMSE) between the in-situ measured and satellite derived water leaving radiance for wavelengths 412 nm, 443 nm, 490 nm, 512 nm and 555 nm was found to be 1.11, 0.718, 0.575, 0.611 and 0.651%, respectively, using standard atmospheric correction procedure. By the use of spatial homogeneity concept, this error was reduced to 0.125, 0.173, 0.176, 0.225, and 0.290 and the correlation coefficient arrived at 0.945, which is an improvement over the standard atmospheric correction procedure.     

Ground validation of an algorithm for estimating surface suspended sediment concentrations from multi-spectral reflectance data

Pollution of water resources by sediments eroded from degraded watersheds is a critical concern around the world. Current methods for locating these eroding areas and off-site damage to water resources through visual observations and field sampling with subsequent laboratory analysis are time consuming and expensive. There is thus, a justified interest in developing algorithms for quick estimation of suspended sediment concentrations in large water-bodies from remotely sensed data. This paper presents the results of a ground validation study on characterization and quantification of surface suspended sediment concentrations (SSC) in sediment laden water bodies through an n-waveband specific numerical index, total information content. A comparison of SSC-predictive potential of the proposed new index, derived from four broad (100–300 nm) Landsat MSS, five broad (40–300 nm) Landsat TM and eight narrow (20–40 nm) IRS-P4 OCM spectral bands, with that of the conventional (NIR-Red and NIR+Red) indices, computed from the same spectral band data, is also presented. The study reveaied that at SSCs 250 mg/1, the proposed index (derived from either broad / narrow landsat MSS/TM or IRS-P4 OCM spectral data) could lead to SSC predictions (with mean errors within 20%) comparable with those obtained with the conventional indices (derived from the same spectral band data). It could further be observed that, in general, lower sediment concentrations (i.e. SSCs 150 mg/1) were associated with higher prediction inaccuracies. A comparison of the mean errors of predictions associated with the proposed and the conventional (NIR-Red and NIR+Red) indices computed from broad and narrow band data for SSCs 150 mg/I, revealed that an increase in number of wavebands (from 4 MSS to 5 TM or 8 OCM bands) and a decrease in the bandwidth of these wavebands (from broad MSS/ TM bands to narrow OCM bands) led to a significant increase in the prediction accuracy of the proposed new index. These prediction accuracies were observed to be the highest with the proposed index calculated from narrow OCM-P4 spectral data. However this could not be observed with the conventional indices at any of the SSC ranges and with the proposed index at SSCs 250 mg/l. This shows that the lower SSC-predictive potential of proposed index was a significant function of both the number and the bandwidth of spectral bands used for its computation. In fact in one of the cases, lower SSC (150 mg/l) -predictive accuracy of the proposed index was found to be significantly higher than that of the conventional (NIR+R) index. The proposed algorithm could thus compress the information contained in the entire reflectance spectrum of the sediment laden water bodies to their sediment type and concentration specific characteristic values. This characteristic of the proposed index was not shared by any of the conventional indices, based on only two waveband data. In fact the proposed index appears to be the only mean of completely compressing and quantifying the information contained in all the information channels of a narrow band spectrometer (consisting of 200 wavebands) to be shortly launched by ISRO for satellite based inventory of natural resources.     

External atmospheric corrections in geodetic very-long-baseline interferometry

Three methods to correct for the atmospheric propagation delay in very-long-baseline interferometry (VLBI) measurements were investigated. In the analysis, the NASA R&D experiments from January 1993 to June 1995 were used. The methods were compared in correcting for the excess propagation delay due to water vapour, the “wet” delay, at one of the sites, the Onsala Space Observatory on the west coast of Sweden. The three methods were: (1) estimating the wet delay using the VLBI data themselves; (2) inferring the wet delay from water vapour radiometer (WVR) data, and (3) using independent estimates based on data from the global positioning system (GPS). Optimum elevation cutoff angles were 22^∘ and 26^∘ when using WVR and GPS data, respectively. The results were found to be similar in terms of reproducibility of the estimated baseline lengths. The shortest baselines tend to benefit from external measurements, whereas the lack of improvement in the longer baselines may be partly due to the large amount of data thrown away when removing observations at low elevation angles. Over a 2 week period of intensive measurements, the two methods using external data showed an overall improvement, for all baseline lengths, compared to the first method. This indicates that there are long-term systematic errors in the wet delay data estimated using WVR and GPS data. Received: 27 October 1998 / Accepted: 20 May 1999     

Calibration of satellite gradiometer data aided by ground gravity data

Parametric least squares collocation was used in order to study the detection of systematic errors of satellite gradiometer data. For this purpose, simulated data sets with a priori known systematic errors were produced using ground gravity data in the very smooth gravity field of the Canadian plains. Experiments carried out at different satellite altitudes showed that the recovery of bias parameters from the gradiometer “measurements” is possible with high accuracy, especially in the case of crossing tracks. The mean value of the differences (original minus estimated bias parameters) was relatively large compared to the standard deviation of the corresponding second-order derivative component at the corresponding height. This mean value almost vanished when gravity data at ground level were combined with the second-order derivative data set at satellite altitude. In the case of simultaneous estimation of bias and tilt parameters from ∂² T/∂z ²“measurements”, the recovery of both parameters agreed very well with the collocation error estimation. Received: 10 October 1996 / Accepted 25 May 1998     

Generation of Vegetation Fraction and Surface Albedo Products Over India from Ocean Colour Monitor (OCM) Data Onboard Oceansat-2

The use of Local Area Coverage (LAC) data from Ocean Color Monitor (OCM) sensor of Oceansat-2 with its high radiometric resolution (12 bits/pixel) and 2-day repeat cycle for rapid monitoring of vegetation growth and estimating surface albedo for the Indian region is demonstrated in this study. For the vegetation monitoring, normalized difference vegetation index (NDVI) and vegetation fraction (VF) products were estimated by maximum value composite approach fortnightly and were resampled to 1 km. The surface albedo products were realized by converting narrow-band eight-band spectral reflectance OCM data to a) visible (300–700 nm) and b) broad band (300–3,000 nm) data. For validation, the derived products were compared with respective MODIS global products and found to be in good agreement.     

Accurate absolute GPS positioning through satellite clock error estimation

 An algorithm for very accurate absolute positioning through Global Positioning System (GPS) satellite clock estimation has been developed. Using International GPS Service (IGS) precise orbits and measurements, GPS clock errors were estimated at 30-s intervals. Compared to values determined by the Jet Propulsion Laboratory, the agreement was at the level of about 0.1 ns (3 cm). The clock error estimates were then applied to an absolute positioning algorithm in both static and kinematic modes. For the static case, an IGS station was selected and the coordinates were estimated every 30 s. The estimated absolute position coordinates and the known values had a mean difference of up to 18 cm with standard deviation less than 2 cm. For the kinematic case, data obtained every second from a GPS buoy were tested and the result from the absolute positioning was compared to a differential GPS (DGPS) solution. The mean differences between the coordinates estimated by the two methods are less than 40 cm and the standard deviations are less than 25 cm. It was verified that this poorer standard deviation on 1-s position results is due to the clock error interpolation from 30-s estimates with Selective Availability (SA). After SA was turned off, higher-rate clock error estimates (such as 1 s) could be obtained by a simple interpolation with negligible corruption. Therefore, the proposed absolute positioning technique can be used to within a few centimeters' precision at any rate by estimating 30-s satellite clock errors and interpolating them. Received: 16 May 2000 / Accepted: 23 October 2000     

Mapping of suspended sediments using site specific seasonal algorithms

This article reports a preliminary work in which two site specific seasonal algorithms have been proposed for estimating the suspended sediments concentration (SSC) from the digital numbers recorded on Indian Remote sensing Satellite, IRS-P4 Ocean Colour Monitor (OCM) sensor. For estimation of SSC, the proposed algorithms utilize dark pixel deduction atmospheric correction technique. The computations are performed with respect to north east monsoon phase situations of Palk Strait coastal stretch. The algorithms performance was satisfactory during the north east monsoon period. Although the results obtained cannot be generalized, we suggest that the authority of proposed algorithms can be extended to other seasons with the addition of more temporal experimental validation data sets and with numeric constants adjusted to present existing conditions. (As this area was severely affected by Tsunami, it may have dissimilar conditions at present).     

Landscape characterization of Sariska National Park (India) and its surroundings

Landscape characterization gives an overall information on the status of Land Use and Land Cover(LULC),changes in its composition and the impact of natural and human influences operating at different spatial and temporal scales.This information can be used to monitor changes in natural forest resources and protected areas,delineate potential conservation areas and can serve in effective management of ecologically fragile landscapes.In the present study,geo-spatial tools were used to characterize the landscape of Sariska National Park and its surroundings.Satellite data was used to prepare LULC maps for 1989 and 2000,change detection analysis and computation of landscape metrics.Climatic data,field records and modeling tools were used to map the po-tential spread of two invasive species,Prosopis juliflora and Adhatoda vasica.The results show that the forest area increased from 1989 to 2000,indicating better management practices.Landscape metrics(PAFRAC,PLADJ and AI)also support this argument.Improvements in the degraded forest can further enhance this effect.The entire reserve however is suitable for the invasion of P.juliflora and A.vasica but is more pronounced in Boswellia serrata and Anogeissus pendula-Acacia catechu(open)forests.A detailed landscape characterization map can help forest managers to make important policy decisions concerning issues such as in-vasive species.     

Estimation of surface runoff in Malattar sub-watershed using SCS-CN method

Nowadays watershed management plays a vital role in water resources engineering. Watershed based on water resources management is necessary to plan and conserve the available resources. Remote Sensing (RS) and Geographic Information System (GIS) techniques can be effectively used to manage spatial and non spatial database that represent the hydrologic characteristics of the watershed use as realistically as possible. The present study area is Malattar subwatershed (4C2B2) lies in the region Gudiyattam Block, Vellore District, Tamil Nadu. The daily rainfall data of Gudiyattam rain gauge station (1971–2007) was collected and used to predict the daily runoff from the watershed using Soil Conservation Service — Curve Number (SCS — CN) method (USDA, 1972) and GIS. Monthly and annual runoff have been calculated from the monthly rainfall data for the years of 1971 to 2007 in the watershed area. The average minimum and maximum rainfall for the years of 1971 to 2007 is 35.30 mm and 111.61 mm respectively and average runoff for the year of 1971 to 2007 is 31.87 mm³ and 47.04 mm³ respectively. The developed rainfall-runoff model is used to understand the watershed and its runoff flow characteristics.     

Vertical angles and refraction in mountain areas

Summary The paper contains an analysis of the character and the quantity of variations of vertical angles, and an analysis of dependences of those variations upon meteorological elements, made on the basis of results of observations carried out at four points in the Polish Tatra Mountains (Figure 1). The analyses comprise four measurement periods: July 1963, June 1964, October 1964 and May 1965. The observations of the vertical angles and of the meteorological factors had been made simultaneously at three points. The meteorological findings have been complemented by data obtained from the mountain meteorological stations. The analysis of results reveals a fairly good consistency between the refraction variations and the changes in the mean temperature gradients for observations from the mountain peaks and for the sight lines with a quite great distance from the ground—provided a steady weather permits for observations of the zenith distance to be made during several days.     

Study of dems derived from ERS-1/2 SAR and SRTM data

The DEM of the Bhuj earthquake affected area of 50 x 50 km was generated using the ERS-1/2 SAR tandem data (May 15—16,1996). Region growing algorithm coupled with path following approach was used for phase unwrapping. Phase to height conversion was done using D-GPS control points. Geocoding was done using GAMMA software. A sample data of DEM of Shuttle Radar Topography Mission (SRTM) of the Bhuj area is made available by DLR Germany. The intensity image, DEM and Error map are well registered. The spatial resolution of this DEM is about 25 m with height accuracy of a few meters. The DEM derived through ERS SAR data is prone to atmospheric affects as the required two images are acquired in different timings where as SRTM acquired the two images simultaneously. An RMS height error of 12.06 m is observed with reference to SRTM though some of the individual locations differ by as much as 35 m.     

Combined processing of the IGS and the IGEX network

 Since the beginning of the International Global Navigation Satellite System (GLONASS) Experiment, IGEX, in October 1998, the Center for Orbit Determination in Europe (CODE) has acted as an analysis center providing precise GLONASS orbits on a regular basis. In CODE's IGEX routine analysis the Global Positioning System (GPS) orbits and Earth rotation parameters are introduced as known quantities into the GLONASS processing. A new approach is studied, where data from the IGEX network are combined with GPS observations from the International GPS Service (IGS) network and all parameters (GPS and GLONASS orbits, Earth rotation parameters, and site coordinates) are estimated in one processing step. The influence of different solar radiation pressure parameterizations on the GLONASS orbits is studied using different parameter subsets of the extended CODE orbit model. Parameterization with three constant terms in the three orthogonal directions, D, Y, and X (D = direction satellite–Sun, Y = direction of the satellite's solar panel axis), and two periodic terms in the X-direction, proves to be adequate for GLONASS satellites. As a result of the processing it is found that the solar radiation pressure effect for the GLONASS satellites is significantly different in the Y-direction from that for the GPS satellites, and an extensive analysis is carried out to investigate the effect in detail. SLR observations from the ILRS network are used as an independent check on the quality of the GLONASS orbital solutions. Both processing aspects, combining the two networks and changing the orbit parameterization, significantly improve the quality of the determined GLONASS orbits compared to the orbits stemming from CODE's IGEX routine processing. Received: 10 May 2000 / Accepted: 9 October 2000     

The US Gravimetric Geoid of 2009 (USGG2009): model development and evaluation

A new gravimetric geoid model, USGG2009 (see Abbreviations), has been developed for the United States and its territories including the Conterminous US (CONUS), Alaska, Hawaii, Guam, the Commonwealth of the Northern Mariana Islands, American Samoa, Puerto Rico and the US Virgin Islands. USGG2009 is based on a 1′ × 1′ gravity grid derived from the NGS surface gravity data and the DNSC08 altimetry-derived anomalies, the SRTM-DTED1 3′′ DEM for its topographic reductions, and the global geopotential model EGM08 as a reference model. USGG2009 geoid heights are compared with control values determined at 18,398 Bench Marks over CONUS, where both the ellipsoidal height above NAD 83 and the Helmert orthometric height above NAVD 88 are known. Correcting for the ellipsoidal datum difference, this permits a comparison of the geoid heights to independent data. The standard deviation of the differences is 6.3 cm in contrast to 8.4 cm for its immediate predecessor— USGG2003. To minimize the effect of long-wavelength errors that are known to exist in NAVD88, these comparisons were made on a state-by-state basis. The standard deviations of the differences range from 3–5 cm in eastern states to about 6–9 cm in the more mountainous western states. If the GPS/Bench Marks-derived geoid heights are corrected by removing a GRACE-derived estimate of the long-wavelength NAVD88 errors before the comparison, the standard deviation of their differences from USGG2009 drops to 4.3 cm nationally and 2–4 cm in eastern states and 4–8 in states with a maximum error of 26.4 cm in California and minimum of −32.1 cm in Washington. USGG2009 is also compared with geoid heights derived from 40 tide-gauges and a physical dynamic ocean topography model in the Gulf of Mexico; the mean of the differences is 3.3 cm and their standard deviation is 5.0 cm. When USGG2009-derived deflections of the vertical are compared with 3,415 observed surface astro-geodetic deflections, the standard deviation of the differences in the N–S and E–W components are 0.87′′ and 0.94′′, respectively.