The determination of potential difference by the joint application of measured and synthetical gravity data: a case study in Hungary

In an elementary approach every geometrical height difference between the staff points of a levelling line should have a corresponding average g value for the determination of potential difference in the Earth’s gravity field. In practice this condition requires as many gravity data as the number of staff points if linear variation of g is assumed between them. Because of the expensive fieldwork, the necessary data should be supplied from different sources. This study proposes an alternative solution, which is proved at a test bed located in the Mecsek Mountains, Southwest Hungary, where a detailed gravity survey, as dense as the staff point density (~1 point/34 m), is available along a 4.3-km-long levelling line. In the first part of the paper the effect of point density of gravity data on the accuracy of potential difference is investigated. The average g value is simply derived from two neighbouring g measurements along the levelling line, which are incrementally decimated in the consecutive turns of processing. The results show that the error of the potential difference between the endpoints of the line exceeds 0.1 mm in terms of length unit if the sampling distance is greater than 2 km. Thereafter, a suitable method for the densification of the decimated g measurements is provided. It is based on forward gravity modelling utilising a high-resolution digital terrain model, the normal gravity and the complete Bouguer anomalies. The test shows that the error is only in the order of 10⁻³mm even if the sampling distance of g measurements is 4 km. As a component of the error sources of levelling, the ambiguity of the levelled height difference which is the Euclidean distance between the inclined equipotential surfaces is also investigated. Although its effect accumulated along the test line is almost zero, it reaches 0.15 mm in a 1-km-long intermediate section of the line.     

Using gravity and topography-implied anomalies to assess data requirements for precise geoid computation

Many regions around the world require improved gravimetric data bases to support very accurate geoid modeling for the modernization of height systems using GPS. We present a simple yet effective method to assess gravity data requirements, particularly the necessary resolution, for a desired precision in geoid computation. The approach is based on simulating high-resolution gravimetry using a topography-correlated model that is adjusted to be consistent with an existing network of gravity data. Analysis of these adjusted, simulated data through Stokes’s integral indicates where existing gravity data must be supplemented by new surveys in order to achieve an acceptable level of omission error in the geoid undulation. The simulated model can equally be used to analyze commission error, as well as model error and data inconsistencies to a limited extent. The proposed method is applied to South Korea and shows clearly where existing gravity data are too scarce for precise geoid computation.     

A hierarchical model for estimating methane emission from wetlands using MODIS data and ARIMA modeling

A three-step hierarchical Semi Automated Empirical Methane Emission Model (SEMEM) has been used to estimate methane emission from wetlands and waterlogged areas in India using Moderate Resolution Imagine Spectroradiometer (MODIS) sensor data onboard Terra satellite. Wetland Surface Temperature (WST), methane emission fluxes and wetland extent have been incorporated as parameters in order to model the methane emission. Analysis of monthly MODIS data covering the whole of India from November 2004 to April 2006 was carried out and monthly methane emissions have been estimated. Interpolation techniques were adopted to fill the data gaps due to cloudy conditions during the monsoon period. AutoRegressive Integrated Moving Average (ARIMA) model has been fitted to estimate the emitted methane for the months of May 2006 to August 2006 using SPSS software.     

非平行结构建筑化简方法的探讨

平行结构建筑是3维城市中建筑的主体,随着建筑风格的多元化,非平行结构建筑所占的比重越来越大,因此必须对其多尺度表达的方法进行研究.此处根据复杂程度的不同将建筑分为简单建筑和特殊建筑两类.在简单建筑的化筒中,首先讨论了倾斜房顶的几何表示方法,在此基础上建立了房顶的关系信息,采用成组处理与斜面的扯直拉平算法相结合的方式实现了简单建筑的化简.在分析复杂建筑倾斜面结构特点的基础上设计了适于复杂建筑的化简方法,并针对两类典型建筑进行了实验.     

肾综合征出血热疫情与NDVI的时间关系——以内蒙古自治区大杨树镇为例

利用月度肾综合征出血热发病人数和长时序月度NDVI值的相互关系, 对肾综合征出血热的发病趋势及发病人数进行预测。研究区大杨树镇2001—2005年共有144例完整的HFRS病人资料, 以及同期详细的宿主动物捕获数据。基于Landsat TM影像以及Google earth 影像, 大杨树地区土地利用分为4种类型, 山地、林地、农田以及居民点。各类土地利用类型的NDVI数据由SPOT-4 卫星的 VGT-S10数据集(10d最大化合成的NDVI数据)提供。对HFRS病例与NDVI之间的关系进行图解分析、相关分析和回归分析。研究表明, NDVI的峰值多出现于8月, 而HFRS发病人数的峰值多出现在11月。前朔3个月的农田NDVI值与HFRS病例数之间的相关系数为0.67(P值<0.001)。农田NDVI峰值比HFRS病例的峰值提前了3个月。研究量化了NDVI与HFRS之间的关系, 为HFRS早期预警系统的建立提供了依据。     

3S技术支持下的小型遗址提取方法

针对仅利用地物光谱分析方法不能识别某些小型遗址的现状,提出基于地物空间关系知识,多源信息复合提取遗址的思路获取目标信息。以安徽省巢湖柘皋地区为例,利用SPOT-5卫星影像和地形图数据,综合运用3S技术进行小型遗址信息提取研究。经过和巢湖文管部门普查记录对比,证明了该方法有效性。该方法可缩小遗址探查范围,为考古普查工作节约大量时间、人力和物力。     

近红外波段(900—2500 nm)水吸收系数测量

根据水在红外波段强吸收且吸收能力变化大的特点,在所提出可见光波段水吸收系数测量系统基础上增设了薄层水测量装置,使得测量水层厚度可在0.04—350 mm之间变化。在此基础上对厚度为0.04—150 mm的多个厚度水层进行了吸收系数测量,并对消除杂质影响后的测量数据进行了有效整合,得到900—2500 nm波段纯水吸收系数。由于确保了各波段数据均在仪器最佳探测区间取得,所得结果精度较高,且与被普遍接受的前期研究结果相一致,可作为相关定量遥感的基础数据。     

新疆油田CORS系统的建立与应用

新疆油田CORS基站网是我国首批针对整个油田应用的连续运行参考站网络系统,它在全准噶尔盆地13万km2范围内建立了永久性参考站,并进行精化似大地水准面的工作,以实现高精度三维测量,从而构成新一代的网络化的大地测量系统,可以向各级测绘用户提供高精度、连续的时间和空间基准,使油田井位测量、勘探踏勘、地面工程规划设计和空间数据采集等工作效率得到极大提高,成为数字新疆油田基础设施之一。     

3维GIS面向对象数据模型的研究与应用

3维数据模型是3维GIS研究中亟待解决的一个核心问题。在充分分析现有3维数据模型的基础上，从实际应用出发，针对传统模型的不足，提出1种3维GIS面向对象数据模型，以解决空间不规则实体本身，以及实体间复杂关系的描述、表达和组织等关键问题，并给出此模型应用实例，证明此模型的可行性和实用性。