Accuracy analysis of GNSS-IR snow depth inversion algorithms

In recent years, with the continuous development of Global Navigation Satellite System (GNSS), it has been applied not only to navigation and positioning, but also to Earth surface environment monitoring. At present, when performing GNSS-IR (GNSS Interferometric Reflectometry) snow depth inversion, Lomb-Scargle Periodogram (LSP) spectrum analysis is mainly used to calculate the vertical height from the antenna phase center to the reflection surface. However, it has the problem of low identification of power spectrum analysis, which may lead to frequency leakage. Therefore, Fast Fourier Transform (FFT) spectrum analysis and Nonlinear Least Square Fitting (NLSF) are introduced to calculate the vertical height in this paper. The GNSS-IR snow depth inversion experiment is carried out by using the observation data of P351 station in PBO (Plate Boundary Observatory) network of the United States from 2013 to 2016. Three algorithms are used to invert the snow depth and compared with the actual snow depth provided by the station 490 in the SNOTEL network. The observations data of L1 and L2 bands are respectively used to find the optimal combination between different algorithms further to improve the accuracy of GNSS-IR snow depth inversion. For L1 band, different snow depths correspond to different optimal algorithms. When the snow depth is less than 0.8 m, the inversion accuracy of NLSF algorithm is the highest. When the snow depth is greater than 0.8 m, the inversion accuracy of FFT algorithm is higher. Therefore, according to the different snow depth, a combined algorithm of NLSF + FFT is proposed for GNSS-IR snow depth inversion. Compared with the traditional LSP algorithm, the inversion accuracy of the combined algorithm is improved by 10%. For L2 band data, the results show that the accuracy of snow depth inversion of various algorithms do not change with the variations of snow depth. Among the three single algorithms, the inversion accuracy of FFT algorithm is better than that of LSP and NLSF algorithms.     

Estimating canopy LAI and chlorophyll of tropical forest plantation (North India) using Sentinel-2 data

With the free and full access to images from Sentinel-2 satellite, the interest to use this data for quantitative retrieval of vegetation parameters is ever-increasing. LAI and chlorophyll are two key variables which are desired for studying productivity, nutrient and stress status of vegetation. Studies carried out on croplands using simulated Sentinel-2 MSI and parametric approach have identified vegetation indices (VIs) with high sensitivity to LAI and chlorophyll. To test how Sentinel-2 red-edge based VIs perform for retrieval of LAI and Chlorophyll of tropical mixed forest canopies, this study has been performed. The field measurements of LAI and chlorophyll content were recorded in a total of 28 ESUs (Elementary Sampling Units) in Bhakra range in the Tarai Central Forest Division, Uttarakhand (India). The in-situ measurements were statistically correlated with Sentinel-2VIs and strength of correlation was validated using Predicted Residual Error Sum of Squares (PRESS) statistic. Field LAI corrected for foliage clumpiness effect improved correlation of VIs with LAI. Among all VIs tested, Normalized Difference Index (NDI) offered highest positive correlation (R² = 0.79, p < 0.05) with LAI while Red-Edge Chlorophyll Index (RECI) (R² = 0.83, RMSE = 0.24 g/m², p < 0.05) and Simple Ratio (SR) 740/705 (R² = 0.79, RMSE = 0.27 g/m², p < 0.05) were the most closely related to chlorophyll content. VIs with red-edge and NIR combinations offered best results.     

Development of a regional rain retrieval algorithm for exclusive mesoscale convective systems over peninsular India

The present study emphasize the development of a region specific rain retrieval algorithm by taking into accounts the cloud features. Brightness temperatures (T_bs) from various TRMM Microwave Imager (TMI) channels are calibrated with near surface rain intensity as observed from the TRMM – Precipitation Radar. It shows that T_b–R relations during exclusive-Mesoscale Convective System (MCS) events have greater dynamical range compared to combined events of non-MCS and MCS. Increased dynamical range of T_b–R relations for exclusive-MCS events have led to the development of an Artificial Neural Network (ANN) based regional algorithm for rain intensity estimation. By using the exclusive MCSs algorithm, reasonably good improvement in the accuracy of rain intensity estimation is observed. A case study of a comparison of rain intensity estimation by the exclusive-MCS regional algorithm and the global TRMM 2A12 rain product with a Doppler Weather Radar shows significant improvement in rain intensity estimation by the developed regional algorithm.     

High vertical resolution water vapour profiles in the upper troposphere and lower stratosphere retrieved from MAESTRO solar occultation spectra

An algorithm has been developed that retrieves water vapour profiles in the upper troposphere and lower stratosphere from optical depth spectra obtained by the Measurements of Aerosol Extinction in the Stratosphere and Troposphere Retrieved by Occultation (MAESTRO) instrument onboard the SCISAT satellite as part of the Atmospheric Chemistry Experiment (ACE) mission. The retrieval relies on ro-vibrational absorption of solar radiation by water vapour in the 926–970 nm range. During the iterative inversion process, the optical depth spectra are simulated at the spectral resolution and sampling frequency of MAESTRO using the correlated-k approximation. The Chahine inversion updates the water vapour volume mixing ratio (VMR), adjusting all retrieval layers simultaneously, to match the observed differential optical depth due to absorption by water vapour and ozone at each tangent height. This approach accounts for significant line saturation effects. Profiles are typically obtained from ∼22 km down to the cloud tops or to 5 km, with relative precision as small as 3% in the troposphere. In the lower stratosphere, the precision on water vapour VMR is ∼1.3 μmol/mol in an individual retrieval layer (∼1 km thick). The spectral capability of MAESTRO allows for the clear separation of extinction due to water vapour and aerosol, and for the fitting quality to be quantified and used to determine an altitude-dependent convergence criterion for the retrieval. In the middle troposphere, interhemispheric differences in water vapour VMR are driven by oceanic evaporation whereas in the upper troposphere, deep convection dominates and a strong seasonal cycle is observed at high latitudes.     

The effect of spatial truncation error on variance of gravity anomalies derived from inversion of satellite orbital and gradiometric data

The spatial truncation error (STE) is a significant systematic error in the integral inversion of satellite gradiometric and orbital data to gravity anomalies at sea level. In order to reduce the effect of STE, a larger area than the desired one is considered in the inversion process, but the anomalies located in its central part are selected as the final results. The STE influences the variance of the results as well because the residual vector, which is contaminated with STE, is used for its estimation. The situation is even more complicated in variance component estimation because of its iterative nature. In this paper, we present a strategy to reduce the effect of STE on the a posteriori   variance factor and the variance components for inversion of satellite orbital and gradiometric data to gravity anomalies at sea level. The idea is to define two windowing matrices for reducing this error from the estimated residuals and anomalies. Our simulation studies over Fennoscandia show that the differences between the 0.5°×0.5°$0.5°\times 0.5°$ gravity anomalies obtained from orbital data and an existing gravity model have standard deviation (STD) and root mean squared error (RMSE) of 10.9 and 12.1 mGal, respectively, and those obtained from gradiometric data have 7.9 and 10.1 in the same units. In the case that they are combined using windowed variance components the STD and RMSE become 6.1 and 8.4 mGal. Also, the mean value of the estimated RMSE after using the windowed variances is in agreement with the RMSE of the differences between the estimated anomalies and those obtained from the gravity model.     

Observation of aphelion cloud belt over Martian tropics,its evolution,and associated dust distribution from MCS data

The present study uses five Martian years of observations from Mars Climate Sounder onboard Mars Reconnaissance Orbiter for investigating the Aphelion Cloud Belt (ACB) over the tropics. Analysis of zonal mean water ice column opacity suggests that the spatial extension of the ACB is mainly confined over the tropics and mid-latitudes (-20 – 40°N) during L_S ~ 45 – 135° (L_S = 0° signifies northern spring equinox). The ACB is seen primarily in the nighttime only due to the truncation of the daytime profile observations at significantly higher altitudes (at ~30 km). Zonal mean ice extinction profiles show ACB’s altitudinal range within ~10 – 40 km, and the existence of a thin cloud band in the absence of a thick ACB during aphelion season. Three phases of the ACB could be identified as the formation phase during L_S = 45 – 75° (phase 1), the peak phase during L_S = 76 – 105° (phase 2), and the decaying phase during L_S = 106 – 135° (phase 3). Observation of the cloud latitude belt shows a northward movement starting from phase 2, prominent over regions nearby Lunae Planum and Xanthe Terra. During this phase, the top level of thick clouds within the ACB decreases to ~20 km in the southern hemisphere, while it increases a little over the northern hemisphere (NH). The decreasing tendency continues in phase 3 over the entire region ?10 – 10°N, and the thick cloud base moves higher over the NH, though the vertical depth of it becomes narrower than phase 2. Temperature profiles do not show any noticeable influence on the northward evolution of the ACB. However, the study at a regional level indicates a possible association of upper tropospheric dustiness with the ACB’s evolution. The mechanism is evident in the correlation analysis mostly at an altitude range of ~18 – 35 km. The migrating semidiurnal tide (SMD) as a proxy of dust or water ice forcing, and the calculated upper tropospheric dust radiative heating, shows an apparent northward movement of their peak amplitude within the three phases of the ACB. This match between the spatiotemporal variations of the SMD and the water ice was not observed previously. However, the correlating behavior seems to be prominent in the areas nearby Lunae Planum and Xanthe Terra and the upper-tropospheric region of the atmosphere.     

Cramér-rao lower bound for pulsar rotation parameters estimation with X-ray pulsar observation data

In this paper, the Cramér-Rao Lower Bound (CRLB) for estimating the rotation parameters of pulsars using X-ray pulsar observation data is deduced, and the calculation equation is presented. In order to verify the correctness of the deduced equation, we use the X-ray pulsar observation data to estimate pulsar rotation parameters, and obtain the root mean square error (RMSE) of the estimated pulsar rotation parameters through conducting repeated experiments. The experimental results suggest that when the observation time increases, the RMSE gradually approaches the estimated CRLB, and that when the observation time is 2.4 × 10⁶ s, the error between the RMSE of pulsar frequency estimation and the CRLB stays at 10^?11 order of magnitude. This verifies that the CRLB expression deduced in this paper is the theoretical lower bound for estimating pulsar rotation parameters. The deduced CRLB in this paper helps determine the minimum variance estimator for pulsar rotation parameter estimation using X-ray pulsar data, providing a benchmark for the comparison between the minimum variance estimator and other estimators.     

Impact of rain on wave retrieval from Sentinel-1 synthetic aperture radar images in tropical cyclones

The main objective of our work was to investigate the impact of rain on wave observations from C-band (~5.3 GHz) synthetic aperture radar (SAR) in tropical cyclones. In this study, 10 Sentinel-1 SAR images were available from the Satellite Hurricane Observation Campaign, which were taken under cyclonic conditions during the 2016 hurricane season. The third-generation wave model, known as Simulating WAves Nearshore (SWAN) (version 41.31), was used to simulate the wave fields corresponding to these Sentinel-1 SAR images. In addition, rainfall data from the Tropical Rainfall Measuring Mission satellite passing over the spatial coverage of the Sentinel-1 SAR images were collected. The simulated results were validated against significant wave heights (SWHs) from the Jason-2 altimeter and European Centre for Medium-Range Weather Forecasts data, revealing a root mean square error (RMSE) of ~0.5 m with a 0.25 scatter index. Winds retrieved from the VH-polarized Sentinel-1 SAR images using the Sentinel-1 Extra Wide-swath Mode Wind Speed Retrieval Model after Noise Removal were taken as prior information for wave retrieval. It was discovered that rain did indeed affect the SAR wave retrieval, as evidenced by the 3.21-m RMSE of SWHs between the SAR images and the SWAN model, which was obtained for the ~1000 match-ups with raindrops. The raindrops dampened the wave retrieval when the rain rate was < ~5 mm/hr; however, they enhanced wave retrieval for higher rain rates. It was also found that the portion of the rain-induced ring wave with a wave number > 0.05 rad/m (~125 m wavelength) was clearly observed in the SAR-derived wave spectra.     

基于DTW的HJ-1B卫星地表温度产品质量检验

HJ-1B卫星热红外数据应用广泛,但其地表温度反演产品的质量检验工作尚不完善。以黑河流域为研究区,利用普适性单通道算法得到HJ 1B地表温度,基于7个地面站点（下垫面为荒漠、沙漠、植被、农作物、雪地和湿地）同步观测资料和MODIS地表温度产品（MOD11A1）,引入动态时间规整方法（DTW）对站点处HJ 1B地表温度进行验证。试验结果表明：HJ 1B地表温度反演产品与地面观测值的偏差值在沙漠和荒漠站点为1K以内,均方根误差在05K左右;对于植被和农作物站点的偏差在2K以内,均方根误差为1~2K;基于DTW的验证对时序不匹配的数据评价结果与现有指标表现一致。HJ-1B地表温度反演产品与地面站点的相对偏差均低于其与MODIS地表温度反演产品的相对偏差。     

Decline of geomagnetic and ionospheric activity at earthquake during spotless Sun

We investigate the geomagnetic and ionospheric effects of seismic activity during 1954 Sun spotless days (SSL) from 1995 to 2020. Two subsets of earthquakes (EQ) are evaluated for 676 events observed with the depth D1 ≤ 30 km and 1278 events with D2 > 30 km and the total set SSL. Newly developed 1 h geomagnetic index Hpo and the ionospheric W_EQ index are used for the comparisons with the daily peak earthquake. The ionosphere W_EQ index is derived at the EQ epicenter from JPL GIM-TEC map within the cell of 2.5°×5°, in latitude φ and longitude λ surrounding the epicenter at radius of about 200 km. We use the method of superposed epoch with the zero epoch time t₀ taken at EQ to extract peak values of Hpo and W_EQ during t₀-24 h ≤ t < t₀ (preEQ) and t₀ < t ≤ t₀ + 24 h (postEQ). It is found that the magnitude of Hpo(t₀) is less that the both peaks of Hpo(preEQ) and Hpo(postEQ) in 91 % of events independent of EQ’s depth. Similar effect is observed with the peak of the positive/negative ionosphere indices and the absolute values of |W(preEQ)| and |W(postEQ)| the both exceeding |W_EQ| in 77 % of events. The seismic activity tends to increase towards the solar minimum when SSLs occur. Our results provide evidence that EQ-related geomagnetic and ionospheric activities experience decline of intensity at the time of EQ under SSL.     

铝基微结构光栅几何参数反演

微结构光栅是一种广泛应用的电子元件。采用随机微粒群优化(SPSO)算法反演了一维铝基衬底矩形光栅的几何结构参数。首先介绍了严格耦合波分析(RCWA)法和微粒群优化算法的基本原理,并采用RCWA法求解了光栅内电磁场问题;然后根据正问题求得的光栅光谱反射率建立目标函数,并采用SPSO算法优化目标函数,反演得到单槽和双槽矩形光栅的周期、凸脊宽度和凹槽深度;最后分析了种群大小和搜索区间对反演结果的影响。结果表明,SPSO算法可以准确地反演光栅几何结构参数,并推荐种群数取30。     

Retrieval and validation of aerosol optical depth using GF-1 WFV cameras data

Conventional AOD (Aerosol Optical Depth) retrieval is restricted to the global and regional scale due to the limited spatial resolution of satellites. This does not allow for aerosol monitoring at the city level. The Chinese GF-1 Wide Field of View (WFV) sensors have sufficiently fine resolution as a data source for AOD retrieval with fine spatial resolution and a 4-day revisit time. In this study, principles similar to those in the Deep Blue (DB) and Dark Target (DT) algorithms were used to retrieve AOD at 100 m spatial resolution from GF-1 WFV images supported by Moderate Resolution Imaging Spectraradiometer (MODIS) surface reflectance (SR) products (MOD09A1). The derived GF-1 WFV AOD were compared with a combination of MOD04_3K DT AOD and MOD04_L2 DB AOD (MODIS AOD) to find that they yield reasonable Spearman correlations (R_S > 0.82) over Taiwan and Beijing. The derived GF-1 WFV AOD were also validated against Aerosol Robotic Network (AERONET) AOD; the Spearman correlation values were R_S = 0.911 in Beijing and R_S = 0.858 in Taiwan.     

A multilayer perceptron and multiclass support vector machine based high accuracy technique for daily rainfall estimation from MSG SEVIRI data

The current paper introduces a new multilayer perceptron (MLP) and support vector machine (SVM) based approach to improve daily rainfall estimation from the Meteosat Second Generation (MSG) data. In this study, the precipitation is first detected and classified into convective and stratiform rain by two MLP models, and then four multi-class SVM algorithms were used for daily rainfall estimation. Relevant spectral and textural input features of the developed algorithms were derived from the spectral MSG SEVIRI radiometer channels. The models were trained using radar rainfall data set colected over north Algeria. Validation of the proposed daily rainfall estimation technique was performed by rain gauge network data set recorded over north Algeria. Thus, several statistical scores were calculated, such as correlation coefficient (r), root mean square error (RMSE), mean error (Bias), and mean absolute error (MAE). The findings given by: (r = 0.97, bias = 0.31 mm, RMSE = 2.20 mm and MAE = 1.07 mm), showed a quite satisfactory relationship between the estimation and the respective observed daily precipitation. Moreover, the comparison of the results with those of two advanced techniques based on random forests (RF) and weighted ‘k’ nearest neighbor (WkNN) showed higher accuracy obtained by the proposed model.     

基于SRCKF的多传感器融合自适应鲁棒算法

为解决模型误差和异常量测值发生时平方根容积卡尔曼滤波（SRCKF）算法滤波性能下降甚至滤波发散的问题,提出了一种多传感器融合自适应鲁棒算法。基于新息协方差匹配原则设计了鲁棒子系统以抑制量测异常值,同时为克服模型误差使用基于新息修正的低复杂度自适应SRCKF(LCASRCKF)算法设计了自适应子系统,根据2种子系统的特点和局限提出全局融合架构,使系统可以充分平衡并利用滤波过程中先验的模型预测值信息和后验的量测值信息,最终降低估计误差。仿真结果表明：相比鲁棒多渐消因子容积卡尔曼滤波（RMCKF）等算法,所提融合算法在滤波精度、稳定性和收敛速度等方面有明显优势。     

Temporal extrapolation of TEC using WNN during 2007–2018 and comparison against GIM,IRI2016 and Kriging

In this paper, a new method of temporal extrapolation of the ionosphere total electron content (TEC) is proposed. Using 3-layer wavelet neural networks (WNNs) and particle swarm optimization (PSO) training algorithm, TEC time series are modeled. The TEC temporal variations for next times are extrapolated with the help of training model. To evaluate the proposed model, observations of Tehran GNSS station (35.69°N, 51.33°E) from 2007 to 2018 are used. The efficiency of the proposed model has been evaluated in both low and high solar activity periods. All observations of the 2015 and 2018 have been removed from the training step to test the proposed model. On the other hand, observations of these 2 years are not used in network training. According to the F10.7, the 2015 has high solar activity and the 2018 has quiet conditions. The results of the proposed model are compared with the global ionosphere maps (GIMs) as a traditional ionosphere model, international reference ionosphere 2016 (IRI2016), Kriging and artificial neural network (ANN) models. The root mean square error (RMSE), bias, dVTEC = |VTEC_GPS ? VTEC_Model| and correlation coefficient are used to assess the accuracy of the proposed method. Also, for more accurate evaluation, a single-frequency precise point positioning (PPP) approach is used. According to the results of 2015, the maximum values of the RMSE for the WNN, ANN, Kriging, GIM and IRI2016 models are 5.49, 6.02, 6.34, 6.19 and 13.60 TECU, respectively. Also, the maximum values of the RMSE at 2018 for the WNN, ANN, Kriging, GIM and IRI2016 models are 2.47, 2.49, 2.50, 4.36 and 6.01 TECU, respectively. Comparing the results of the bias and correlation coefficient shows the higher accuracy of the proposed model in quiet and severe solar activity periods. The PPP analysis with the WNN model also shows an improvement of 1 to 12 mm in coordinate components. The results of the analyzes of this paper show that the WNN is a reliable, accurate and fast model for predicting the behavior of the ionosphere in different solar conditions.     

The N4,5 - OO Auger and “N3” N4,5O2,3 Coster-Kronig spectra of xenon induced by electron impact

The N_4,5OO Auger electron spectrum in the kinetic energy region (14–37) eV has been measured with high resolution at electron incident energies between 71 eV and 2019 eV. The Auger and satellite lines are assigned by comparison with previous literature data. Several states which correspond to the resonant Auger transitions from the 4d_{3/2, 5/2} 6p states are observed. The PCI effects on the N₅-O_2,3O_2,3(¹S₀) Auger peak when the incident electron energy approaches to the N₅ edge (67.55 eV) is investigated and it is found that the dependence of the energy shift on the excess energy, E_exc, is well represented by the function E_exc^β with β = (-1.40 ± 0.05). The ^“N₃^” N_4,5O_2,3 Coster-Kronig spectrum is measured at various electron incident energies. The assignments of the features are made in comparison with a similar spectrum from synchrotron radiation measured by Kivimäki et al. [J. Electron Spectrosc. Relat. Phenom. 1999, 101–103, 43–47]. The Auger spectrum in the kinetic energy regions (68–78) eV and (90–138) eV is observed for the first time in an electron impact experiment and a comparison is made with the photoionization experiment by Hikosaka et al. [Phys. Rev. A 2007, 76, 032708].     

Sensing snow height and surface temperature variations in Greenland from GPS reflected signals

The in situ measurements of snow surface temperature (SST) and snow height (SH) are very difficult with high costs, particularly in Greenland Ice Sheet (GrIS). Since the snow depth variations coupling with surface temperature are related to GPS multipath, it is possible to estimate the snow depth and surface air temperature variations by incorporating GPS-Reflectometry (GPS-R). In this paper, the reflected signals from ground GPS receivers are used to sense the SST and SH variations based on the thermophysical behavior and variations of snow layer from April to June 2010 at SMM1 site and from March to December 2010 at MARG site in Greenland. The results show that the mean daily changes in the ionospheric geometrical-free linear combination (GPS-L4) of dual-frequency GPS signals are related to daily SST and SH variations. The nonparametric bootstrapping model in direct (forward) and inverse models are developed and applied to estimate the SST and SH variations. The mean biases of SST and SH estimates are 0.18 °C and 0.23 m at SMM1 site, respectively, and 3.8 °C and 0.13 m at MARG site, respectively.     

Optimum parameter for estimating phase fluctuations on transionospheric signals at high latitudes

Transionospheric radio signals may experience fluctuations in their amplitude and phase due to irregularity in the spatial electron density distribution, referred to as scintillation. Ionospheric scintillation is responsible for transionospheric signal degradation that can affect the performance of satellite based navigation systems. Usually, the scintillation activity is measured by means of indices such as the normalised standard deviation of the received intensity S₄ and the standard deviation of the received phase σ_? typically calculated over 1 min of data. Data from a GPS scintillation monitor based on 50 Hz measurements recorded at Dirigibile Italia Station (Ny-Alesund, Svalbard), in the frame of the ISACCO project ( De Franceschi et al., 2006) are used to investigate possible adoption of an alternative parameter for the estimate of phase fluctuations: i.e., the standard deviation of the phase rate of change S_?. This parameter is shown to better correlate with S₄ being much less detrending dependent than σ_?. The couple (S₄, S_?) should be then considered a more physical proxy of radio scintillation than the couple (S₄, σ_?).     

Synergetic retrieval of terrestrial AOD from MODIS images of twin satellites Terra and Aqua

Aerosol optical depth (AOD) is one of the most important indicators of atmospheric pollution. It can be retrieved from satellite imagery using several established methods, such as the dark dense vegetation method and the deep blue algorithm. All of these methods require estimation of surface reflectance prior to retrieval, and are applicable to a certain pre-designated type of surface cover. Such limitations can be overcome by using a synergetic method of retrieval proposed in this study. This innovative method is based on the fact that the ratio K of surface reflectance at different angles/geometries is independent of wavelength as reported by Flowerdew and Haigh (1995). An atmospheric radiative transfer model was then established and resolved with the assistance of the ratio K obtained from two Moderate Resolution Imaging Spectroradiometer (MODIS) spectral bands acquired from the twin satellites of Terra and Aqua whose overpass is separated by three hours. This synergetic method of retrieval was tested with 20 pairs of MODIS images. The retrieved AOD was validated against the ground observed AOD at the Taihu station of the AErosol RObotic NETwork (AERONET). It is found that they are correlated with the observations at a coefficient of 0.828 at 0.47 μm and 0.921 at 0.66 μm wavelengths. The retrieved AOD has a mean relative error of 25.47% at 0.47 μm and 24.3% at 0.66 μm. Of the 20 samples, 15 and 17 fall within two standard error of the line based observed AOD data on the ground at the 0.47 μm and 0.66 μm, respectively. These results indicate that this synergetic method can be used to reliably retrieve AOD from the twin satellites MODIS images, namely Terra and Aqua. It is not necessary to determine surface reflectance first.     

Assessment of depth to magnetic sources using high resolution aeromagnetic data of some parts of the Lower Benue Trough and adjoining areas,Southeast Nigeria

High resolution airborne magnetic data acquired between 2005 and 2010 were used to determine depth to shallow and deep magnetic sources in some parts of Southeastern Nigeria. Various depth estimation methods such as standard Euler deconvolution (SED), source parameter imaging (SPI), spectral depth analysis (SDA) and two dimensional (2-D) forward modeling were applied. Results obtained from SED, SPI and models of profiles 1 and 2 indicate that the Abakaliki Anticlinorium (AA) and Ikom-Mamfe Rift (IMR) regions are dominated by short wavelength magnetic anomalies caused by extensive tectonic events. The SED map showed depth to shallow and deep magnetic sources ranging from ~ 16.6 to ~ 338.3 m and ~ 394.3 to ~ 5748.1 m respectively. Likewise, depth estimates from the SPI map varies from ~ 147.1 to ~ 554.2 m (shallow magnetic sources) and ~ 644.2 to ~ 6141.6 m (deep magnetic sources). The result obtained from SDA revealed depths to deep magnetic basement in the range of ~ 769 to ~ 6666 m with an average of ~ 3449 m. Also, it showed that depth to shallow magnetic sources vary between ~ 119 and ~ 434 m with mean of ~ 269 m. The 2-D forward modelling showed maximum depth values of ~ 4700, ~4600 and ~ 6500 m in the models of profiles 1, 2 and 3 within the Anambra Basin (AB), Afikpo Syncline (AS) and Calabar Flank (CF) respectively. Generally, from all the various methods applied the results indicate that AB, AS and CF are dominated by long wavelength anomalies. The 2-D models indicated that the basement framework is undulant. Also, depth estimates involving the various methods used in this study correlate strongly with each other in the AB, AS and CF geological regions.