几种地形校正方法的研究

本文推证了三种典型的地形校正方法(局部地形改正(C),剩余地形改正(RTM)爱黎-海斯卡宁型地形均衡改正(t_C)之间的数学关系,对其特性进行了分析比较;讨论了它们实现的途径(数据处理方法)及其计算特征;最后还应用某地区的实测地形高数据进行了实际计算,得出了一些有益的结论。     

水体对精化局部似大地水准面的影响

在精化局部似大地水准面时,由于对大地水准面精度的要求不高或者精化区域的水下地形数据缺乏等因素,往往很少考虑湖泊水体对局部似大地水准面的影响。本文将通过分析水体对局部地形改正和地形均衡改正的影响,然后通过实例计算得出了湖泊水体对精化局部似大地水准面的影响。     

地形起伏对大地水准面的影响的探讨

通过一个实例得到两个重要的结论：1．计算地形起伏改正时应该使用公式δN=πGρhp^2/γ-Gρ/6γ∫∫（h^3-hp^3)/l^3dxdy而不能用公式δN=Gρ/γ∫∫（h-hp/l）dxdy-Gρ/6γ∫∫（h-hp）^3/l^3dxdy;2.在海拔较低的地区，即使地形起伏比较大，但是地形起伏改正数却很小，可以直接采用几何拟舍而无须考虑地形改正。     

珠穆朗玛峰峰顶大地水准面与似大地水准面差值计算及其验证

本文利用登山路线上的实测重力点,通过试算分析确定了珠穆朗玛峰地区应采用的均衡模型及均衡深度,并利用该均衡模型推估了珠穆朗玛峰峰顶地形均衡重力异常与珠穆朗玛峰峰顶重力值。根据正常高和正高换算关系的需要,计算了珠穆朗玛峰峰顶沿垂线方向至黄海平均海平面的重力值的平均值与正常重力值的平均值,在此基础上完成了珠穆朗玛峰峰顶正常高和正高的换算,即大地水准面与似大地水准面差值计算,并对此结果采用其他方法进行了验证。     

地形对确定高精度局部大地水准面的影响

以计算香港大地水准面为例 ,着重研究了以下几点 :①DTM的分辨率对地形改正的影响 ;②质量柱体地形模型与质量线地形模型对计算地形改正的差异 ;③采用Helmert凝聚改正法 ,计算地形对大地水准面的间接影响 ;④比较经典Stokes Helmert方法与Sj¨oberg方法计算地形对大地水准面的影响     

无锡市厘米级似大地水准面的研究

利用大地水准面逼近的严密理论M olodenskii级数解和重力归算的地形均衡理论,结合全球定位系统(G PS)、水准和重力资料在无锡确定了精度达厘米级的似大地水准面,并讨论了无锡G PS控制网的布设及数据处理。通过检核,所确定的2.5'×2.5'似大地水准面精度为2.2cm。     

Regional Quasi-Geoid Refining Considering Corrections of Terrain and Complete Spherical Bouguer Anomaly＇s Gradient Term

推证顾及地形与完全球面布格异常梯度改正的完全到一阶项的物理大地测量边值问题的严密解式,并在某试验区综合利用地形、重力、GPS／水准等数据进行区域似大地水准面的计算与检验。通过对高程异常计算绝对与相对精度的比较分析,结果表明,完全球面布格异常梯度改正项对高程异常的影响能够达到厘米的量级。因此,提高区域似大地水准面的建模精度,尤其是在地形起伏较大的区域,除需顾及地形改正项影响外,还应考虑完全球面布格异常梯度改正项对高程异常的影响。     

顾及地形与完全球面布格异常梯度项改正的区域似大地水准面精化

推证顾及地形与完全球面布格异常梯度改正的完全到一阶项的物理大地测量边值问题的严密解式,并在某试验区综合利用地形、重力、GPS/水准等数据进行区域似大地水准面的计算与检验。通过对高程异常计算绝对与相对精度的比较分析,结果表明,完全球面布格异常梯度改正项对高程异常的影响能够达到厘米的量级。因此,提高区域似大地水准面的建模精度,尤其是在地形起伏较大的区域,除需顾及地形改正项影响外,还应考虑完全球面布格异常梯度改正项对高程异常的影响。     

"移去-拟合-恢复"算法进行高程转换和地形改正计算公式探讨

针对在山区和丘陵地区不能简单地采用数学拟合而必须考虑地形起伏对大地水准面的影响的事实,提出应该采用"移去-拟合-恢复"的基本思路,通过实例证实这种算法的有效性,同时通过计算和理论分析对地形改正的两个公式进行检验,对公式的适用性进行探讨,得到一些有益的结论.     

提高1∶50000重力调查中测地工作精度的几种方法

介绍了1∶50 000重力勘查中提高测地工作的新思路,提出了采用GPS-RTK方法,利用CORS网站测定重力测点点位3维坐标的作业方法、消除高程异常影响而建立似大地水准面模型的方法及建立DTM数字高程模型在计算机上进行地形改正方法等。     

How to handle topography in practical geoid determination: three examples

 Three different methods of handling topography in geoid determination were investigated. The first two methods employ the residual terrain model (RTM) remove–restore technique, yielding the quasigeoid, whereas the third method uses the classical Helmert condensation method, yielding the geoid. All three methods were used with the geopotential model Earth Gravity Model (1996) (EGM96) as a reference, and the results were compared to precise global positioning system (GPS) levelling networks in Scandinavia. An investigation of the Helmert method, focusing on the different types of indirect effects and their effects on the geoid, was also carried out. The three different methods used produce almost identical results at the 5-cm level, when compared to the GPS levelling networks. However, small systematic differences existed. Received: 18 March 1999 / Accepted: 21 March 2000     

不同重力归算方法与地形的相关性分析

比较了完全布格改正、残余地形模型方法、赫尔默特第二质量凝聚法和艾里-海斯卡涅均衡改正四种不同重力归算方法的改正效果,分析了其与地形的相关性,得出相应的结果。     

综合EGM2008模型和SRTM/DTM2006.0剩余地形模型的GPS高程转换方法

利用SRTM以及DTM2006.0全球地形模型构建剩余地形模型（RTM）数据,并将其转换为RTM高程异常。通过GPS/水准点的优化选择法,选择少量GPS/水准点的实测高程异常,扣除EGM2008模型以及SRTM与DTM2006.0模型求得的剩余模型高程异常,对残余高程异常进行拟合,从而进一步提高GPS高程转换的精度。最...     

Retrieval of land surface temperature and emissivity from satellite data: Physics, theoretical limitations and current methods

Remote sensing from satellites is the only means to obtain land surface temperature (LST) and emissivity on a larger scale. LST has many applications, e.g., in radiation budget experiments and global warming, and desertification studies. Over the last decades, substantial amount of research was dedicated towards extracting LST and emissivity from surface-leaving radiance and de-coupling the two from each other. This paper provides the physical basis, discusses theoretical limitations, and gives an overview of the current methods for space-borne passive sensors operating in the infrared range, e.g., NOAA-AVHRR, Meteosat, ERS-ATSR, TERRA-MODIS, and TERRA-ASTER. Atmospheric effects on estimated LST are described and atmospheric-correction using a radiative transfer model (RTM) is explained. The methods discussed are the single channel method, the split window techniques (SWTs), and the multi-angle method.     

Comparative analysis of different retrieval methods for mapping grassland leaf area index using airborne imaging spectroscopy

Fine scale maps of vegetation biophysical variables are useful status indicators for monitoring and managing national parks and endangered habitats. Here, we assess in a comparative way four different retrieval methods for estimating leaf area index (LAI) in grassland: two radiative transfer model (RTM) inversion methods (one based on look-up-tables (LUT) and one based on predictive equations) and two statistical modelling methods (one partly, the other entirely based on in situ data). For prediction, spectral data were used that had been acquired over Majella National Park in Italy by the airborne hyperspectral HyMap instrument. To assess the performance of the four investigated models, the normalized root mean squared error (nRMSE) and coefficient of determination (R²) between estimates and in situ LAI measurements are reported (n = 41). Using a jackknife approach, we also quantified the accuracy and robustness of empirical models as a function of the size of the available calibration data set. The results of the study demonstrate that the LUT-based RTM inversion yields higher accuracies for LAI estimation (R² = 0.91, nRMSE = 0.18) as compared to RTM inversions based on predictive equations (R² = 0.79, nRMSE = 0.38). The two statistical methods yield accuracies similar to the LUT method. However, as expected, the accuracy and robustness of the statistical models decrease when the size of the calibration database is reduced to fewer samples. The results of this study are of interest for the remote sensing community developing improved inversion schemes for spaceborne hyperspectral sensors applicable to different vegetation types. The examples provided in this paper may also serve as illustrations for the drawbacks and advantages of physical and empirical models.     

Solution to the spectral filter problem of residual terrain modelling (RTM)

In physical geodesy, the residual terrain modelling (RTM) technique is frequently used for high-frequency gravity forward modelling. In the RTM technique, a detailed elevation model is high-pass-filtered in the topography domain, which is not equivalent to filtering in the gravity domain. This in-equivalence, denoted as spectral filter problem of the RTM technique, gives rise to two imperfections (errors). The first imperfection is unwanted low-frequency (LF) gravity signals, and the second imperfection is missing high-frequency (HF) signals in the forward-modelled RTM gravity signal. This paper presents new solutions to the RTM spectral filter problem. Our solutions are based on explicit modelling of the two imperfections via corrections. The HF correction is computed using spectral domain gravity forward modelling that delivers the HF gravity signal generated by the long-wavelength RTM reference topography. The LF correction is obtained from pre-computed global RTM gravity grids that are low-pass-filtered using surface or solid spherical harmonics. A numerical case study reveals maximum absolute signal strengths of \(\sim 44\) mGal (0.5 mGal RMS) for the HF correction and \(\sim 33\) mGal (0.6 mGal RMS) for the LF correction w.r.t. a degree-2160 reference topography within the data coverage of the SRTM topography model (\(56^{\circ }\hbox {S} \le \phi \le 60^{\circ }\hbox {N}\)). Application of the LF and HF corrections to pre-computed global gravity models (here the GGMplus gravity maps) demonstrates the efficiency of the new corrections over topographically rugged terrain. Over Switzerland, consideration of the HF and LF corrections reduced the RMS of the residuals between GGMplus and ground-truth gravity from 4.41 to 3.27 mGal, which translates into \(\sim 26\)% improvement. Over a second test area (Canada), our corrections reduced the RMS of the residuals between GGMplus and ground-truth gravity from 5.65 to 5.30 mGal (\(\sim 6\)% improvement). Particularly over Switzerland, geophysical signals (associated, e.g. with valley fillings) were found to stand out more clearly in the RTM-reduced gravity measurements when the HF and LF correction are taken into account. In summary, the new RTM filter corrections can be easily computed and applied to improve the spectral filter characteristics of the popular RTM approach. Benefits are expected, e.g. in the context of the development of future ultra-high-resolution global gravity models, smoothing of observed gravity data in mountainous terrain and geophysical interpretations of RTM-reduced gravity measurements.     

Prediction of vertical deflections from high-degree spherical harmonic synthesis and residual terrain model data

This study demonstrates that in mountainous areas the use of residual terrain model (RTM) data significantly improves the accuracy of vertical deflections obtained from high-degree spherical harmonic synthesis. The new Earth gravitational model EGM2008 is used to compute vertical deflections up to a spherical harmonic degree of 2,160. RTM data can be constructed as difference between high-resolution Shuttle Radar Topography Mission (SRTM) elevation data and the terrain model DTM2006.0 (a spherical harmonic terrain model that complements EGM2008) providing the long-wavelength reference surface. Because these RTM elevations imply most of the gravity field signal beyond spherical harmonic degree of 2,160, they can be used to augment EGM2008 vertical deflection predictions in the very high spherical harmonic degrees. In two mountainous test areas—the German and the Swiss Alps—the combined use of EGM2008 and RTM data was successfully tested at 223 stations with high-precision astrogeodetic vertical deflections from recent zenith camera observations (accuracy of about 0.1 arc seconds) available. The comparison of EGM2008 vertical deflections with the ground-truth astrogeodetic observations shows root mean square (RMS) values (from differences) of 3.5 arc seconds for ξ and 3.2 arc seconds for η, respectively. Using a combination of EGM2008 and RTM data for the prediction of vertical deflections considerably reduces the RMS values to the level of 0.8 arc seconds for both vertical deflection components, which is a significant improvement of about 75%. Density anomalies of the real topography with respect to the residual model topography are one factor limiting the accuracy of the approach. The proposed technique for vertical deflection predictions is based on three publicly available data sets: (1) EGM2008, (2) DTM2006.0 and (3) SRTM elevation data. This allows replication of the approach for improving the accuracy of EGM2008 vertical deflection predictions in regions with a rough topography or for improved validation of EGM2008 and future high-degree spherical harmonic models by means of independent ground truth data.     

Combining EGM2008 and SRTM/DTM2006.0 residual terrain model data to improve quasigeoid computations in mountainous areas devoid of gravity data

A global geopotential model, like EGM2008, is not capable of representing the high-frequency components of Earth’s gravity field. This is known as the omission error. In mountainous terrain, omission errors in EGM2008, even when expanded to degree 2,190, may reach amplitudes of 10 cm and more for height anomalies. The present paper proposes the utilisation of high-resolution residual terrain model (RTM) data for computing estimates of the omission error in rugged terrain. RTM elevations may be constructed as the difference between the SRTM (Shuttle Radar Topography Mission) elevation model and the DTM2006.0 spherical harmonic topographic expansion. Numerical tests, carried out in the German Alps with a precise gravimetric quasigeoid model (GCG05) and GPS/levelling data as references, demonstrate that RTM-based omission error estimates improve EGM2008 height anomaly differences by 10 cm in many cases. The comparisons of EGM2008-only height anomalies and the GCG05 model showed 3.7 cm standard deviation after a bias-fit. Applying RTM omission error estimates to EGM2008 reduces the standard deviation to 1.9 cm which equates to a significant improvement rate of 47%. Using GPS/levelling data strongly corroborates these findings with an improvement rate of 49%. The proposed RTM approach may be of practical value to improve quasigeoid determination in mountainous areas without sufficient regional gravity data coverage, e.g., in parts of Asia, South America or Africa. As a further application, RTM omission error estimates will allow refined validation of global gravity field models like EGM2008 from GPS/levelling data.     

A Method to Upscale the Leaf Area Index (LAI) Using GF-1 Data with the Assistance of MODIS Products in the Poyang Lake Watershed

A leaf area index is a key parameter reflecting the growth changes of vegetation and one of the most important canopy structural parameters for performing quantitative analyses of many ecological and climate models. Although using high-resolution satellite data and the radiative transfer model (RTM) can be used to generate high resolution LAI products, the RTM method has some problems because its temporal resolution is low, the input parameters are more appropriate for a physics model, and some parameters are difficult to obtain. Problems that urgently need to be solved include improving the temporal-spatial resolution for LAI products and localizing LAI products. To explore an applicable method for the high-resolution LAI products in a small basin and to improve the inversion accuracy, we propose an approach for GF-1 WFV LAI retrieval using MOD15A2 data and the measured LAI of the Poyang Lake watershed. Empirical models were used to retrieve high resolution LAI values, and the results show that these models are well designed for analyzing time-series satellite data. Good correlations were obtained between the NDVI of the GF-1 WFV data, the retrieved LAI values and the MODIS LAI data from samples acquired in both summer and winter. The exponential NDVI model obtained the best LAI value estimation results from the GF-1 WFV data (R2 = 0.697, RMSE = 1.100); the best synthetic validation of the RMSE is 0.883, close to the optimum model. Therefore, the retrieval results more fully reflect the growth process of the different features. This study proposed an upscale method for developing a high spatial resolution GF-1 satellite standard LAI products retrieval model using MODIS data. The proposed method will be helpful for efficiently improving the temporal-spatial resolution of LAI products to benefit the extraction of vegetation parameter information and dynamic land use monitoring.     

Gravity anomalies from satellite altimetry: comparison between computation via geoid heights and via deflections of the vertical

The accumulation of good quality satellite altimetry missions allows us to have a precise geoid with fair resolution and to compute free air gravity anomalies easily by fast Fourier transform (FFT) techniques.In this study we are comparing two methods to get gravity anomalies. The first one is to establish a geoid grid and transform it into anomalies using inverse Stokes formula in the spectral domain via FFT. The second one computes deflection of the vertical grids and transforms them into anomalies.The comparison is made using different data sets: Geosat, ERS-1 and Topex-Poseidon exact repeat misions (ERMs) north of 30°S and Geosat geodetic mission (GM) south of 30°S. The second method which transforms the geoid gradients converted into deflection of the vertical values is much better and the results have been favourably evaluated by comparison with marine gravity data.