Optimal Model for Geoid Determination from Airborne Gravity   总被引：2，自引：0，他引：2  

Novák  Pavel 《Studia Geophysica et Geodaetica》2003,47(1):1-36

Two different approaches for transformation of airborne gravity disturbances, derived from gravity observations at low-elevation flying platforms, into geoidal undulations are formulated, tested and discussed in this contribution. Their mathematical models are based on Green's integral equations. They are in these two approaches defined at two different levels and also applied in a mutually reversed order. While one of these approaches corresponds to the classical method commonly applied in processing of ground gravity data, the other approach represents a new method for processing of gravity data in geoid determination that is unique to airborne gravimetry. Although theoretically equivalent in the continuous sense, both approaches are tested numerically for possible numerical advantages, especially due to the inverse of discretized Fredholm's integral equation of the first kind applied on different data. High-frequency synthetic gravity data burdened by the 2-mGal random noise, that are expected from current airborne gravity systems, are used for numerical testing. The results show that both approaches can deliver for the given data a comparable cm-level accuracy of the geoidal undulations. The new approach has, however, significantly higher computational efficiency. It would be thus recommended for real life geoid computations. Additional errors related to regularization of gravity data and the geoid, and to accuracy of the reference field, that would further deteriorate the quality of estimated geoidal undulations, are not considered in this study.  相似文献   

机载激光测深中的波浪改正技术   总被引：3，自引：0，他引：3  

黄谟涛  翟国君  欧阳永忠  陆秀平 《武汉大学学报(信息科学版)》2003,28(4):389-392

基于我国新研制的机载激光测深系统基本配置，提出了3种可供选择的波浪改正计算方案(也称为深度值归算方案)，具体分析了3种方案的适用条件和应用范围，并从理论上对3种改正模型的计算精度进行了估算。  相似文献   

用机载多普勒雷达资料进行三维风场解析反演 II. 多重解析多普勒方法应用于在CaPE现场实验中获取的机载雷达实测资料          下载免费PDF全文

窦贤康  G. Scialom  Y. Lemaitre 《大气科学》1997,21(4):426-436

模拟结果证明，在机载雷达的技术参数下，多重解析多普勒（MANDOP）方法能够提供误差可以接受的三维风场反演。 1991年夏在美国的佛罗里达州举行的CaPE现场实验中首次应用了机载双束多普勒雷达，并获取了珍贵的雷达实测资料。用MANDOP方法分析1991年8月9日观测到的一个飑线，取得类似于以往用地基雷达资料得到飑线内部大气环流结构。另外，机载雷达资料与 地基雷达资料联合反演的结果与纯粹用机载雷达资料反演的结果之间很好的相关性证明了机载雷达资料的可靠性。  相似文献   

提高航空物探网格化精度的一种方法     

闫永利  陈本池  周凤桐 《物探与化探》1997,21(2):81-90

本文针对航空物探测量的特点,提出了一种在最佳拟合航空物探测量点基础上的网格化方法。从而,有效地保证了航空物探测量数据的网格化精度。  相似文献   

用光盘转录航空物探数据     

戚巧俊  雍卫华 《物探与化探》1997,21(3):225-227

航空物探数据具有较高的保存开发价值,由于磁带保存的有效年限较短,航空物探勘查所获资料存在着丢失的危险。航空物探数据光盘转录将解决这些难题,为航空物探资料的二次开发和利用创造条件。本光盘数据从任一与RICOHRS-5060E型光盘机兼容的光盘机上均可读出。  相似文献   

航空短波红外分光谱遥感技术直接寻找油气藏的有效性及应用实例   总被引：1，自引：0，他引：1  

杨琨  杨柏林 《矿物学报》1996,16(3):321-326

采用航空短波红外分光谱遥感技术，在新疆准噶尔盆地和塔里木盆地某些油气区，进行直接寻找油气资源的试验研究后发现，油气区含油岩系，油气藏上方盖层土壤的光谱在２３００和２３５０ｎｍ波段具有双吸收特征。  相似文献   

Exploration of remotely sensed forest structure and ultrasonic range sensor metrics to improve empirical snow models          下载免费PDF全文

Andrés Varhola  Nicholas C. Coops  Younes Alila  Markus Weiler 《水文研究》2014,28(15):4433-4448

Current methods to estimate snow accumulation and ablation at the plot and watershed levels can be improved as new technologies offer alternative approaches to more accurately monitor snow dynamics and their drivers. Here we conduct a meta‐analysis of snow and vegetation data collected in British Columbia to explore the relationships between a wide range of forest structure variables – obtained from Light Detection and Ranging (LiDAR), hemispherical photography (HP) and Landsat Thematic Mapper – and several indicators of snow accumulation and ablation estimated from manual snow surveys and ultrasonic range sensors. By merging and standardizing all the ground plot information available in the study area, we demonstrate how LiDAR‐derived forest cover above 0.5 m was the variable explaining the highest percentage of absolute peak snow water equivalent (SWE) (33%), while HP‐derived leaf area index and gap fraction (45° angle of view) were the best potential predictors of snow ablation rate (explaining 57% of variance). This study reveals how continuous SWE data from ultrasonic sensors are fundamental to obtain statistically significant relationships between snow indicators and structural metrics by increasing mean r² by 20% when compared to manual surveys. The relationships between vegetation and spectral indices from Landsat and snow indicators, not explored before, were almost as high as those shown by LiDAR or HP and thus point towards a new line of research with important practical implications. While the use of different data sources from two snow seasons prevented us from developing models with predictive capacity, a large sample size helped to identify outliers that weakened the relationships and suggest improvements for future research. A concise overview of the limitations of this and previous studies is provided along with propositions to consistently improve experimental designs to take advantage of remote sensing technologies, and better represent spatial and temporal variations of snow. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

Inference and uncertainty of snow depth spatial distribution at the kilometre scale in the Colorado Rocky Mountains: the effects of sample size,random sampling,predictor quality,and validation procedures          下载免费PDF全文

J. L. McCreight  A. G. Slater  H. P. Marshall  B. Rajagopalan 《水文研究》2014,28(3):933-957

Historically, observing snow depth over large areas has been difficult. When snow depth observations are sparse, regression models can be used to infer the snow depth over a given area. Data sparsity has also left many important questions about such inference unexamined. Improved inference, or estimation, of snow depth and its spatial distribution from a given set of observations can benefit a wide range of applications from water resource management, to ecological studies, to validation of satellite estimates of snow pack. The development of Light Detection and Ranging (LiDAR) technology has provided non‐sparse snow depth measurements, which we use in this study, to address fundamental questions about snow depth inference using both sparse and non‐sparse observations. For example, when are more data needed and when are data redundant? Results apply to both traditional and manual snow depth measurements and to LiDAR observations. Through sampling experiments on high‐resolution LiDAR snow depth observations at six separate 1.17‐km² sites in the Colorado Rocky Mountains, we provide novel perspectives on a variety of issues affecting the regression estimation of snow depth from sparse observations. We measure the effects of observation count, random selection of observations, quality of predictor variables, and cross‐validation procedures using three skill metrics: percent error in total snow volume, root mean squared error (RMSE), and R². Extremes of predictor quality are used to understand the range of its effect; how do predictors downloaded from internet perform against more accurate predictors measured by LiDAR? Whereas cross validation remains the only option for validating inference from sparse observations, in our experiments, the full set of LiDAR‐measured snow depths can be considered the ‘true’ spatial distribution and used to understand cross‐validation bias at the spatial scale of inference. We model at the 30‐m resolution of readily available predictors, which is a popular spatial resolution in the literature. Three regression models are also compared, and we briefly examine how sampling design affects model skill. Results quantify the primary dependence of each skill metric on observation count that ranges over three orders of magnitude, doubling at each step from 25 up to 3200. Whereas uncertainty (resulting from random selection of observations) in percent error of true total snow volume is typically well constrained by 100–200 observations, there is considerable uncertainty in the inferred spatial distribution (R²) even at medium observation counts (200–800). We show that percent error in total snow volume is not sensitive to predictor quality, although RMSE and R² (measures of spatial distribution) often depend critically on it. Inaccuracies of downloaded predictors (most often the vegetation predictors) can easily require a quadrupling of observation count to match RMSE and R² scores obtained by LiDAR‐measured predictors. Under cross validation, the RMSE and R² skill measures are consistently biased towards poorer results than their true validations. This is primarily a result of greater variance at the spatial scales of point observations used for cross validation than at the 30‐m resolution of the model. The magnitude of this bias depends on individual site characteristics, observation count (for our experimental design), and sampling design. Sampling designs that maximize independent information maximize cross‐validation bias but also maximize true R². The bagging tree model is found to generally outperform the other regression models in the study on several criteria. Finally, we discuss and recommend use of LiDAR in conjunction with regression modelling to advance understanding of snow depth spatial distribution at spatial scales of thousands of square kilometres. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

Quantitative estimation of submarine groundwater discharge using airborne thermal infrared data acquired at two different tidal heights     

Ki‐mook Kang  Duk‐jin Kim  Yunjee Kim  Eunhee Lee  Bong‐Gwan Kim  Seung Hee Kim  Kyoochul Ha  Dong‐Chan Koh  Yang‐Ki Cho  Guebuem Kim 《水文研究》2019,33(7):1089-1100

Submarine groundwater discharge (SGD) plays an important role in coastal biogeochemical processes and hydrological cycles, particularly off volcanic islands in oligotrophic oceans. However, the spatial and temporal variations of SGD are still poorly understood owing to difficulty in taking rapid SGD measurements over a large scale. In this study, we used four airborne thermal infrared surveys (twice each during high and low tides) to quantify the spatiotemporal variations of SGD over the entire coast of Jeju Island, Korea. On the basis of an analytical model, we found a linear positive correlation between the thermal anomaly and squares of the groundwater discharge velocity and a negative exponential correlation between the anomaly and water depth (including tide height and bathymetry). We then derived a new equation for quantitatively estimating the SGD flow rates from thermal anomalies acquired at two different tide heights. The proposed method was validated with the measured SGD flow rates using a current meter at Gongcheonpo Beach. We believe that the method can be effectively applied for rapid estimation of SGD over coastal areas, where fresh groundwater discharge is significant, using airborne thermal infrared surveys.  相似文献   

真三维立体显示技术在不动产登记统一平台中的应用研究     

陈育新 《测绘与空间地理信息》2016,(5):107-109

随着国家不动产统一登记制度的实施,城市房屋、林地、草原、土地等不动产统一整合、调查和管理工作迫在眉睫。基于机载多角度倾斜摄影和激光雷达扫描技术的创新,真三维数据可为不动产登记提供真实统一、高精度、多层次的空间载体,保证了城市不动产登记应用创新和制度创新。  相似文献