Study region: Yunnan Province. Study focus: Using vertical displacement data from 43 GNSS stations across Yunnan Province, this study first inverted terrestrial water storage anomalies (TWSA) for 2011-2019, then developed the novel GNSS Combined Climatologic Deviation Index (GNSS-CCDI) through integration with precipitation observations, ultimately employing XGBoost modeling to quantify key driving factors. New hydrological insights for the region: The retrieved TWSA agrees well with GRACE and GLDAS data, yet the latter two underestimate TWSA changes. The GNSS-CCDI is consistent with other drought indices. Five drought events occurred from 2011 to 2019, with the severest starting in July 2011 for 9 months. Main factors influencing TWSA vary across regions, with soil moisture, lake, and snow having the greatest impact in Yunnan.

Spherical harmonic analysis (SHA) and synthesis (SHS) are widely used by researchers in various fields. Both numerical integration and least-squares methods can be employed for analysis and synthesis. However, these approaches, when calculated via summation, are computationally intensive. Although the Fast Fourier Transform (FFT) algorithm is efficient, it is traditionally limited to processing global grid points starting from zero longitude. In this paper, we derive an improved FFT algorithm for spherical harmonic analysis and synthesis. The proposed algorithm eliminates the need for grid points to start at zero longitude, thereby expanding the applicability of FFT-based methods. Numerical experiments demonstrate that the new algorithm retains the computational efficiency of conventional FFT while achieving accuracy comparable to the summation method. Consequently, it enables direct harmonic coefficient calculation from global grid data without requiring interpolation to align with zero longitude. Additionally, the algrithm can generate grid points with equi-angular spacing using the improved FFT algorithm, starting from non-zero longitudes. To address the loss of orthogonality in latitude due to discrete spherical grids, a quadrature weight factor—dependent on grid type (e.g., regular or Gauss grid)—is incorporated, as summarized in this study.

The nominally coarse spatial resolution (300 similar to 400 km) of gravity recovery and climate experiment (GRACE) and a 11-month data gap with GRACE follow-on (GRACE-FO) limits applications at the individual ice sheet drainage basin scale and complicates the evaluation of regional ice sheet mass changes. While numerous works have downscaled GRACE-estimated water storage, research on downscaling ice mass change in Antarctica is limited. This study employs joint partial least-squares regression (PSLR) and support vector machine (SVM) method to reconstruct GRACE-derived spatiotemporal data for the Antarctic ice sheet (AIS). The pixel-temporal downscaling (PTD) of random forest (RF) and pixel-spatial downscaling (PSD) of multiscale geographically weighted regression (MGWR) enhance spatial resolution of ice mass changes from 0.25 degrees (similar to 120 km) to 1.92 km. The downscaled results show consistent temporal variation and reduced noise compared to other reconstruction methods. Both RF and MGWR results exhibit high consistency with original GRACE data, with MGWR achieving a correlation coefficient (CC) of 0.99. The MGWR model effectively captures finer signals related to ice flow velocity. When compared to independent free air gravity anomalies, MGWR outperforms RF with improvements of 41.51% and 56.25% in mean correlation for group 1 and group 2 observation points, respectively. In addition, MGWR shows improvements of 16.90%/29.69% for flight Line A and 11.84%/19.72% for flight Line B compared to RF and original GRACE results. The enhanced spatial resolution offers valuable insights into ice dynamic changes within the Western AIS and Eastern AIS and smaller regions such as the Antarctic Peninsula.

The global gravitational model can be expressed as a series of spherical harmonic coefficients computed up to a certain degree and order. The main ordering characteristic can depend on the degree, order, or type of coefficient. When determining the spherical harmonic coefficients using the least squares method, it is essential to analyze the ordering pattern of these coefficients and their positions (e.g., indices) in the vector or matrix. A systematic analysis on the type of coefficient arrangement is presented in this paper. Moreover, the index algorithm for each coefficient ordering pattern is provided. Additionally, the structure of the normal equation matrix with different coefficient arrangement patterns is analyzed. Based on the analysis and the algorithm presented in this paper: (1) we can calculate the index of each coefficient in the vector or matrix of the normal equation; (2) we can change the structure of the normal equation matrix of the Earth's gravity field from one type of coefficient arrangement to another. Furthermore, (3) we can directly combine different structures of the normal equation matrix, calculated from different types of gravity satellite missions, to form combined normal equations. This approach is beneficial for the determination of Earth's gravitational model using multi-type observation data.

Since April 2002, the Gravity Recovery and Climate Experiment Satellite (GRACE) has provided monthly total water storage anomalies (TWSAs) on a global scale. However, these TWSAs are discontinuous because some GRACE observation data are missing. This study presents a combined machine learning-based modeling algorithm without hydrological model data. The TWSA time-series data for 11 large regions worldwide were divided into training and test sets. Autoregressive integrated moving average (ARIMA), long short-term memory (LSTM), and an ARIMA–LSTM combined model were used. The model predictions were compared with GRACE observations, and the model accuracy was evaluated using five metrics: the Nash–Sutcliffe efficiency coefficient (NSE), Pearson correlation coefficient (CC), root mean square error (RMSE), normalized RMSE (NRMSE), and mean absolute percentage error. The results show that at the basin scale, the mean CC, NSE, and NRMSE for the ARIMA–LSTM model were 0.93, 0.83, and 0.12, respectively. At the grid scale, this study compared the spatial distribution and cumulative distribution function curves of the metrics in the Amazon and Volga River basins. The ARIMA–LSTM model had mean CC and NSE values of 0.89 and 0.61 and 0.92 and 0.61 in the Amazon and Volga River basins, respectively, which are superior to those of the ARIMA model (0.86 and 0.48 and 0.88 and 0.46, respectively) and the LSTM model (0.80 and 0.41 and 0.89 and 0.31, respectively). In the ARIMA–LSTM model, the proportions of grid cells with NSE > 0.50 for the two basins were 63.3

The Gravity Recovery and Climate Experiment (GRACE) mission provides uniquely high-precision observations for monitoring ocean mass changes (OMC), allowing for the establishment and evaluation of the ocean mass budget in conjunction with satellite altimetry and temperature and salinity observations. However, it is challenging to perform OMC closed-loop validation in the East China Sea (ECS) due to potential biases in the individual model and the lack of certain data processing. In this study, we comprehensively analyze the ocean mass budget in the ECS during the GRACE era (2005-2015) by utilizing multiple datasets, mainly consisting of three official GRACE RL06 solutions, three altimetry products, and four ocean reanalysis products. The effect of ocean bottom deformation, neglected in previous studies, is -0.38 +/- 0.06 mm/yr, and we estimate a more accurate ensemble sea level change to be 4.05 +/- 1.50 mm/yr in the ECS from the altimetry products. There are discrepancies between leakage-corrected GRACE OMC observations and steric-corrected altimeter OMC estimations in both the seasonal signals and the long-term trends (e.g., 6.25 mm/yr vs. 4.22 mm/yr). These discrepancies are strongly correlated with sediment runoff from the Yangtze River and in-situ sediment observations, suggesting that ocean sediment accumulation should be considered in the ocean mass budget in the ECS. Since in-situ sediment data are estimated over similar to 100 years, we employ an empirical estimation method to determine the corresponding data during the period 2005-2015, to avoid potential biases caused by inconsistencies in observational timespans. The results show that sediment mass changes can explain about 96 % of residual trends. Our results emphasize the significant impact of sediment on improving the ocean mass budget in the ECS, offering a novel perspective for estimating ocean mass changes in other coastal regions.

The research focuses on the long-term sustainable monitoring of Terrestrial Water Storage Anomalies (TWSA), which is crucial for understanding water cycle processes and efficient regional water resource management. To address data gaps during the operation of GRACE (Gravity Recovery and Climate Experiment) and GRACE-FO (Follow-On) satellites, the research introduces a combined model of Bidirectional Long Short-Term Memory neural network (Bi-LSTM) with X-11 for rolling prediction of TWSA through the inversion of GRACE spherical harmonic coefficients. To assess the applicability of the combined model in various basins, we use TWSA data from January 2003 to December 2014 as training set, with TWSA data from January 2015 to December 2016 as a reference, and the missing month data in GRACE observations are filled using cubic spline interpolation. We compare the performance of the Autoregressive Integrated Moving Average (ARIMA) model, Long Short-Term Memory neural network (LSTM), Bi-LSTM, and the combined Bi-LSTM with X-11 model for model training and rolling prediction. Evaluation metrics include Root Mean Square Error (RMSE), standardized RMSE (R*), Pearson correlation coefficient (P), and Nash-Sutcliffe Efficiency coefficient (NSE). Results indicate that all four methods perform well in regions with strong periodicity. Among them, the Bi-LSTM with X-11 combined model shows the highest prediction accuracy and good generalization. In the Amazon River basin, the combined model achieves an RMSE of 4.7 cm, R*, of 0.305, P of 97.6

SUMMARY In this study, we analysed the impacts of errors in background force models and observed non-gravitational forces on the pseudo-observations (pre-fits) during gravity field recovery based on the Gravity Recovery and Climate Experiment (GRACE) satellite gravity mission. To reduce these effects, we introduced the stochastic parameters into the functional model of the variational equation integration approach to absorb this type of noise contribution. Simultaneously, the prior variances of observed orbits and K-band range rates used in traditional method are re-estimated with least-squares variance component estimation (LS-VCE) after considering these stochastic parameters. To improve the computing efficiency, a modified method of the calculation of sensitivity matrices related to the introduced stochastic parameters is proposed. Compared to the method of variation of constants widely used in the precise orbit determination and gravity field recovery, the modified method decreases the computational time of these matrices by about four times. Furthermore, an efficient LS-VCE algorithm is derived in a more generalized case. The efficient algorithm only costs 1 per cent of the time of the unoptimized method. With the GRACE data, we analysed the benefits of these refinements in gravity field recovery, and the results show that these improvements can mitigate the impacts of errors in background force models and accelerometer data on recovered gravity field models, especially in the high-degree signals. Furthermore, the quality of results has less dependence on parametrization.

在详细分析非差运动学精密定轨原理和步骤基础上,采用平滑卡尔曼滤波算法,通过自主研发的精密定轨软件对 GRACE-FO卫星进行非差运动学精密定轨.结果表明,与官方科学轨道相比,平滑滤波不仅能提高定轨开始阶段的精度,而且整体上定轨精度也得到提升,GRACE-FO C 星轨道残差为 2～4 cm,GRACE-FO D星轨道残差为 3～5 cm.

The high-precision static satellite gravity field models have important applications in fields such as global ocean circulation research and global/regional digital elevation datum determination. In this paper, we discussed the determination of high-degree static satellite gravity field models with GOCE observation, GRACE observation and the joint of them. We first constructed a 300 degree Satellite Gravity Gradiometry (SGG) normal equation with the high-precision gravitational gradient components V-xx, V-xy, Vz(z) and V-xz throughout the entire mission of GOCE by the Direct least squares method, and a 130-degree Satellite-to-Satellite Tracking (SST) normal equation with the SST observation data by the point-wise acceleration approach. The 300-degree GOCEonly satellite gravity field model GOSGO2S is determined by combining SGG and SST normal equations with variance component estimation. The 180-degree model SWPU-GRACE2021S is then determined based on the dynamic approach with the GRACE data throughout the entire mission cycle of 15 years, and the normal equation is combined with GOCE normal equation to determine WHU-SWPU-GOGR2022S, a joint model of GOCE and GRACE. Finally, the XGM2019 model and GPS/leveling data are used for precision analysis of GOSGO2S, SWPU-GRACE2021S and WHU-SWPU-GOGR2022S in frequency domain and space domain respectively. The results show that the accuracy of GOSGO2S and WHU-SWPU-GOGR2022S is comparable to GO_CONS_GCF_2_ DIR_R6, GO_CONS_GCF_2_TIM_R6, GO_CONS_GCF_2_SPW_R5, G00006s and Tongji-GMMG2021S that use the entire mission data of GOCE satellite and the accuracy differences are in the order of millimeters. The SWPU-GRACE2021S model has the same accuracy below degree/order 160 as the international mainstream of GRACE satellite gravity field models, i. e., ITSG-Grace2018s and Tongji-Grace02s.

利用广义三角帽法评估 5 个最新版本 GRACE/GRACE-FO 时变重力场模型反演全球流域陆地水储量变化的不确定性,并探讨地理位置、气候类型和流域面积对不确定性的影响.结果表明:1)COST-G、CSR、JPL、ITSG和 GFZ时变重力场模型反演全球流域陆地水储量变化的平均不确定性分别是 0.41 cm、0.63 cm、0.66 cm、0.81 cm和 0.97 cm;2)流域陆地水储量变化的不确定性与流域面积和地理位置存在较强的相关性,与气候类型的相关性较小;3)当观测数据质量较差时,不同模型反演的流域陆地水储量变化存在较大差异.

Droughts have damaging impacts on human society and ecological environments. Therefore, studying the impacts of climate variability and human activity on droughts has very important scientific value and social significance in order to understand drought warnings and weaken the adverse impacts of droughts. In this study, we used a combined drought index based on five Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On solutions to characterize droughts in the Pearl River basin (PRB) and its sub-basins during 2003 and 2020. Then, we accurately quantified the impact of climate variability and human activity on droughts in the PRB and seven sub-basins by combining the hydrometeorological climate index and in situ human activity data. The results show that 14 droughts were identified in the PRB, particularly the North River basin with the most drought months (52.78%). The El Niño-Southern Oscillation and the Indian Ocean Dipole were found to have important impacts on droughts in the PRB. They affect the operation of the atmospheric circulation, as well as the East Asia summer monsoon, resulting in a decrease in precipitation in the PRB. This impact shows a significant east–west difference on the spatial scale. The middle and upper reaches of the PRB were found to be dominated by SM, while the lower reaches were found to be dominated by GW. Human activity was found to mainly exacerbate droughts in the PRB, but also plays a significant role in reducing peak magnitude. The sub-basins with a higher proportion of total water consumption experienced more droughts (more than 11), and vice versa. The Pearl River Delta showed the highest drought intensification. Reservoir storage significantly reduces the drought peak and severity, but the impact effect depends on its application and balance with the total water consumption. Our study provides a reference for analyzing the drought characteristics, causes, and impacts of sub-basins on a global scale.

培养学生解决复杂工程问题能力是工程教育认证和高等工程教育发展面临的重要挑战.结合工程教育认证理念,通过对当前高等教育和高等工程教育的新形势、新要求阐述,分析了复杂测绘工程问题的特征;根据学校办学定位与特色,设置了测绘工程专业培养目标,提出了基于实践教学能力的毕业要求;通过绘制实践教学-能力培养路线图,构建了支撑复杂工程问题能力培养的实践教学课程体系;通过课程中对学生层次化、模块化能力培养,保证了解决复杂工程问题培养目标达成,可为测绘工程及相关专业的人才培养方案修订与实践教学课程设置提供借鉴.

本文在三维加速度点质量模型法的基础上，融合不等式约束处理条带噪声，模拟计算结果表明该方法相比零阶Tikhonov约束，信噪比提高4.23%。利用不等式约束的三维加速度点质量模型法，采用GRACE与GRACE-FO重力卫星数据对2002年4月至2021年4月华北地区水储量进行了估算。研究结果表明，2002年4月至2021年4月，附有不等式约束的三维加速度点质量模型法计算的华北地区水储量以-1.36cm/a的速率下降，Mascon与球谐系数法所获得的亏损速率分别为-1.52cm/a、-0.80cm/a，表明华北地区水储量处于明显的亏损趋势，并由亏损速率空间分布可知，水储量在河北省与山西省交界处亏损最为明显，亏损中心区域超过-3.0cm/a。将研究时间段分为两部分分别进行拟合后发现，2011年至2021年华北地区水储量亏损趋势大于2002年至2010年。研究时间段内，2003年水储量存在明显的上升趋势，结合TRMM降雨数据对该时间段降雨时空分布进行研究，结果表明重力卫星数据计算结果相比降雨数据较为滞后，2003年春季时期的水储量的上升主要由于2002年下半年降雨的影响。

由于遥感对"地"观测仅对直接的遥感影像进行了可译的物像分析解释,而对此现象背后"人"的观测与解读不足.该文提出结合人类动力学和遥感相关理论的人类动力学遥感,利用遥感科学与技术解决人类动力学对人类活动的定量反演问题,揭示由人与其活动物要素的相互转换机制,对人群数量做出快速估计;最后以2020年初武汉火神山医院建设时期遥感图像为例,实验表明此方法的可行性,且为应急救援提供快速监测评估和人员调度等方面的多手段支持.

在附有空间约束的三维加速度点质量模型法的基础上引入水文模型进行约束,利用水文模型计算地理点之间的相关性,采用L曲线法确定最优正则化参数.计算结果表明,引入水文模型的三维加速度点质量模型法相比零阶Tikhonov约束的三维加速度点质量模型法信噪比大于0的比例更高.采用该方法对2010年中国西南地区干旱情况进行监测;同时,在剔除季节性信号后,利用主成分分析法对水储量异常进行分析.结果表明,西南地区在2009年秋至2010年春存在明显的水储量负异常特征.

三维加速度点质量模型法为反演陆地水储量变化提供了新的途径,采用三维加速度点质量模型法计算了中国华北地区2003-2014年的水储量变化.为了检验反演结果,采用球谐系数法以及德克萨斯大学空间研究中心(Center for Space Research,University of Texas at Austin,CSR)发布的 RL06 Mascon模型进行对比分析.研究结果表明,两种方法反演结果均反映出华北地区陆地水储量长期处于亏损趋势,但不同方法计算的亏损速度有一定的差别,三维加速度点质量模型法采用CSR提供的RL06数据反演的华北地区陆地水储量亏损速度为-3.09 cm/a,而球谐系数法反演结果为-2.60 cm/a;三维加速度点质量模型法特征点的反演结果与Mascon法相关系数更高,而球谐系数法与三维加速度点质量模型法结果之间的差异主要是由条带噪声约束平滑策略不一致导致的.

针对测绘工程专业培养目标、毕业要求、课程体系难以满足新时代测绘高等教育新要求的问题，文章在分析新时代中国高等教育特征、高等工程教育新要求的基础上，结合测绘地理信息行业新发展，探讨了测绘高等教育面临的新形势。以西南石油大学测绘工程专业为例，总结了人才培养的定位与理念，结合学校办学定位，确定了人才培养方案优化调整的原则，探讨了2019级本科人才培养方案优化调整的具体措施。研究成果可为相关高校结合高等教育新形势开展测绘工程等专业人才培养方案修订提供有益借鉴和参考。

若尔盖高原作为全国三大草原牧区之一,牧草资源丰富,但受放牧的影响,该地区的生态环境相继出现了湿地和草地的退化、土地沙化等现象.为准确、快速估测若尔盖区域尺度放牧情况,合理安排人类活动,为保护生态环境提供数据与理论支持,本研究利用MODIS-NDVI数据,结合地面实测数据及气象数据,分别模拟了地上生物量及净初级生产力(aboveground net primary productivity,ANPP),并在此基础上分析了2010?2019年若尔盖高原放牧强度.结果表明:模拟放牧强度的模型效果较好,R2值为0.7813,达到极显著相关水平(P<0.05),且均方根误差(root mean square error,RMSE)较小,精度可达到70％以上,能将不同放牧程度的区域区分开;若尔盖高原2019年平均放牧强度为1.87 AU·hm?2,处于过度放牧状态,且整体放牧强度呈现出东南部偏高、西北部偏低的分布态势.在时间变化上,若尔盖高原2010?2019年放牧强度整体呈增加趋势,在2010?2014、2014?2019年分别出现先增加后减少的变化过程;地上净初级生产力和地上生物量的分布态势与放牧强度的大小具有一定的关联性.