基于灰关联分析的GPS高程拟合加权平均函数模型权函数优选

基于灰色系统理论的灰关联分析方法,提出了权函数的优选方法,实例分析表明其具有较好的实用价值.     

GPS网平差观测量选取的理论分析

由多台GPS接收机在不同时段进行静态观测而组成的观测网形,当采用高精度的科研软件与常用商用软件解算基线时,其基线向量的方差阵不同,前者的方差阵结构是完全的、严密的。同时,在进行GPS网平差时,选取GPS基线的方式及数量的不同,构造的网形也就不同,采用不同的数学模型其得到的平差结果和精度指标也不相同。文章先从理论上进行分析,后用示例进行比较论证。     

工程建筑沉降预测的非等间距灰色建模

介绍了传统灰色GM(1,1)模型建立的基本思路及其精度评定方法,着重探讨了非等间距数列的灰色预测建模问题,给出了详细的建模过程。并结合高层建筑沉降监测实例进行分析,取得了较好效果。     

论《GIS空间分析》课程建设

综述了GIS空间分析理论的相关知识面和知识点,分析了课程的教学适应性,提出了课程建设的几点建议.     

小波分析若干应用模型及在测绘中的应用和展望＊

小波分析是８０年代中期发展起来的应用数学理论,在众多学科领域取得了广泛的应用。文中首先对小波分析的发展作了简要概述,然后介绍了小波分析在测绘中的应用,对小波分析若干与测绘相关的应用模型进行了分析和讨论,并对小波分析在测绘中的应用前景作了展望。     

空间直角坐标和大地坐标的转换

目前国内在空间直角坐标和大地坐标转换公式使用问题上 ,还明显缺乏必要的统一性。针对这个问题 ,本文作者在全面分析和比较国内外现有各种转换方法的基础上 ,重点推荐和介绍根据 Bowring研究思路导出的转换公式 ,这组公式既简单又具有很高的计算精度 ,能够满足各个部门的使用要求     

Prediction of soil properties using imaging spectroscopy: Considering fractional vegetation cover to improve accuracy

Spectroscopic techniques have become attractive to assess soil properties because they are fast, require little labor and may reduce the amount of laboratory waste produced when compared to conventional methods. Imaging spectroscopy (IS) can have further advantages compared to laboratory or field proximal spectroscopic approaches such as providing spatially continuous information with a high density. However, the accuracy of IS derived predictions decreases when the spectral mixture of soil with other targets occurs. This paper evaluates the use of spectral data obtained by an airborne hyperspectral sensor (ProSpecTIR-VS – Aisa dual sensor) for prediction of physical and chemical properties of Brazilian highly weathered soils (i.e., Oxisols). A methodology to assess the soil spectral mixture is adapted and a progressive spectral dataset selection procedure, based on bare soil fractional cover, is proposed and tested. Satisfactory performances are obtained specially for the quantification of clay, sand and CEC using airborne sensor data (R² of 0.77, 0.79 and 0.54; RPD of 2.14, 2.22 and 1.50, respectively), after spectral data selection is performed; although results obtained for laboratory data are more accurate (R² of 0.92, 0.85 and 0.75; RPD of 3.52, 2.62 and 2.04, for clay, sand and CEC, respectively). Most importantly, predictions based on airborne-derived spectra for which the bare soil fractional cover is not taken into account show considerable lower accuracy, for example for clay, sand and CEC (RPD of 1.52, 1.64 and 1.16, respectively). Therefore, hyperspectral remotely sensed data can be used to predict topsoil properties of highly weathered soils, although spectral mixture of bare soil with vegetation must be considered in order to achieve an improved prediction accuracy.     

三维探地雷达在城市地下管线探测中的应用

城市的扩建、旧城的改造以及水生态建设等都离不开对城市原有地下管线的调查,精准探测地下管线的分布情况是保障管线安全和确保市政工程正常运行的重要工作.为提高城市地下管线探测精度,本文采用三维探地雷达在东莞进行管线探测研究.结果表明,三维探地雷达能显示不同方向、不同埋深、不同类型的地下管线,在城市地下管线探测工作中应用效果显...     

利用稀少卫星影像控制点生产1:10 000 DOM——以阿拉善盟测区为例

青藏铁路沿线地表受多年冻土的影响会产生抬升和沉降,形变监测对于其安全运行至关重要。本文采用41景C波段Sentinel-1A升轨数据,结合均匀网格划分子区域的方法,探测分布相对均匀的永久散射体,以作为SBAS InSAR技术的地面控制点,对青藏线羊八井站至乌玛塘站段铁路及其沿线地表进行形变监测。试验结果表明,该段铁路年形变速率范围为-8~2 mm/a,该区域形变受周围冻土的影响随季节呈周期性变化;SBAS InSAR技术和本文的PS-SBAS InSAR技术在同名点形变趋势与形变程度方面的对比结果保持一致性,进一步说明了本文方法的可靠性。     

Land quality index assessment for agricultural purpose using multi-criteria decision analysis (MCDA)

In this study, an attempt has been made to apply Remote Sensing (RS) and geographic information system (GIS) to determine land quality for agriculture purpose using analytic hierarchy process technique. In this study, various thematic layers were used like organic matter content, soil texture, soil depth, soil pH, soil P, soil K, geomorphology, run-off potential, slope and land use/land cover to assess the land quality index of the study area for the agriculture purpose which were generated in the RS and GIS environment. The study area can be divided into four zones, viz. high quality, moderately quality, marginally quality and low quality according to their suitability of land quality for agriculture purpose. It was found that about 39.09, 31.24, 20.41 and 9.26% of the study area falls under high quality zone, moderately quality, marginally quality and low quality zone, respectively, for agricultural purpose.