测船处瞬时潮位的GPS精密确定

利用GPS载波相位差分测量技术，借助时间偏差改正、姿态改正、高程转换、信号处理和吃水改正，获得了测船处精密在航潮位。该方法已在几个GPS在航潮位测量实验中得到了验证，并取得了理想的结果。     

关于BP神经网络转换GPS高程的若干问题

BP神经网络用于GPS高程转换有着较高的精度,但也存在不少问题,如网络的隐含层和隐含层单元个数选取、参加学习的样本的质量如何影响仿真精度等。结合实例分析上述问题,得出一些结论。     

似大地水准面的定义及在空中测量中涉及的问题

本文讨论了高程异常和似大地水准面的定义以及高程异常随空间位置的变化,提出了将似大地水准面称为正常高系统的高程基准面的不恰当性,给出了由地面测量至空中点几何高差确定空中点正常高的改正方法。其目的主要是针对当前已经扩展到了空中的测量,引导正确地认识正常高系统的基本问题。     

Characterization of the horizontal structure of the tropical forest canopy using object-based LiDAR and multispectral image analysis

This article's goal is to explore the benefits of using Digital Surface Model (DSM) and Digital Terrain Model (DTM) derived from LiDAR acquisitions for characterizing the horizontal structure of different facies in forested areas (primary forests vs. secondary forests) within the framework of an object-oriented classification. The area under study is the island of Mayotte in the western Indian Ocean. The LiDAR data were the data originally acquired by an airborne small-footprint discrete-return LiDAR for the “Litto3D” coastline mapping project. They were used to create a Digital Elevation Model (DEM) at a spatial resolution of 1 m and a Digital Canopy Model (DCM) using median filtering. The use of two successive segmentations at different scales allowed us to adjust the segmentation parameters to the local structure of the landscape and of the cover. Working in object-oriented mode with LiDAR allowed us to discriminate six vegetation classes based on canopy height and horizontal heterogeneity. This heterogeneity was assessed using a texture index calculated from the height-transition co-occurrence matrix. Overall accuracy exceeds 90%. The resulting product is the first vegetation map of Mayotte which emphasizes the structure over the composition.     

Spectral discrimination of giant reed (Arundo donax L.): A seasonal study in riparian areas

The giant reed (Arundo donax L.) is amongst the one hundred worst invasive alien species of the world, and it is responsible for biodiversity loss and failure of ecosystem functions in riparian habitats. In this work, field spectroradiometry was used to assess the spectral separability of the giant reed from the adjacent vegetation and from the common reed, a native similar species.The study was conducted at different phenological periods and also for the giant reed stands regenerated after mechanical cutting (giant reed_RAC). A hierarchical procedure using Kruskal–Wallis test followed by Classification and Regression Trees (CART) was used to select the minimum number of optimal bands that discriminate the giant reed from the adjacent vegetation. A new approach was used to identify sets of wavelengths – wavezones – that maximize the spectral separability beyond the minimum number of optimal bands. Jeffries Matusita and Bhattacharya distance were used to evaluate the spectral separability using the minimum optimal bands and in three simulated satellite images, namely Landsat, IKONOS and SPOT.Giant reed was spectrally separable from the adjacent vegetation, both at the vegetative and the senescent period, exception made to the common reed at the vegetative period. The red edge region was repeatedly selected, although the visible region was also important to separate the giant reed from the herbaceous vegetation and the mid infrared region to the discrimination from the woody vegetation. The highest separability was obtained for the giant reed_RAC stands, due to its highly homogeneous, dense and dark-green stands. Results are discussed by relating the phenological, morphological and structural features of the giant reed stands and the adjacent vegetation with their optical traits. Weaknesses and strengths of the giant reed spectral discrimination are highlighted and implications of imagery selection for mapping purposes are argued based on present results.     

基于Surfer软件的高程拟合应用

充分利用Surfer软件强大的插值功能和绘制图件能力,分析了其在GPS高程拟合中的应用,一是基于Surfer所显示的高程异常三维表面显示图的起伏情况,分区域选择最能表达地形的数学模型,使得高程拟合达到最佳效果;二是对离散点的高程异常进行内插计算,获得一定间隔的格网高程异常模型,根据该模型内插待求GPS点的高程异常,从而将GPS大地高转换为正常高。通过实验分析了此两种应用的可行性。     

提高GPS高程拟合模型精度的有效方法

在调兵山地区,选择76大地高和正常高都已知的点作为原始数据,采用多项式拟合加权平均法建立该地区大地水准面,包括泰勒二次多项式加权平均法和双二次多项式加权平均法。通过实例发现,泰勒二多项式曲面加权平均法和双二次多项式加权平均法对高程异常的短波项有很好的改进效果,拟合残差值比较大的点采用泰勒二次多项式曲面加权平均法和双二次多项式加权平均法残差值变小,大大提高了拟合模型的精度,改善了拟合模型。     

贯通测量误差来源及质量控制技术探讨

贯通测量是矿山测量的的一项重要工作。贯通工程质量的好坏,直接关系到整个矿井的建设、生产和经济效益。本文从地面控制网误差、陀螺定向、导入高程、井下控制网误差四个大的方面对贯通测量的误差来源进行了分析,并从贯通测量的各个环节对质量控制技术进行了详细的探讨。     

Mapping saltcedar (Tamarix ramosissima) and other riparian and agricultural vegetation in the Lower Colorado River region using multi-spectral Landsat TM imagery

Saltcedar (Tamarix ramosissima), an invasive shrub species, has successfully invaded large extents of several riparian zones in the western United States and northern Mexico. Mapping the distribution and abundance of saltcedar over these large areas through a multi-seasonal, cost-effective monitoring approach using satellite remote sensing is very essential. Ground truth surveys were conducted at 79 locations where the spectral reflectance measurements of vegetation, type of plant species, plant heights, soil samples and GPS co-ordinates were recorded. All the sampling was designed to coincide with the satellite overpass period. The Landsat TM colour-composite spectral ratio image (normalized difference vegetative index (NDVI), R _1,5 and R _1,7 as green, blue and red) can clearly identify and map the areas infested with saltcedar. The Landsat image analysis shows that these spectral ratios can be applied to multiple satellite overpasses for monitoring the seasonal progression of the saltcedar growth over time.     

Characterization of forests and deforestation in Cambodia using ALOS/PALSAR observation

In this study, we have demonstrated the capability of full polarimetric ALOS/Phased Array L-band Synthetic Aperture Radar data for the characterization of the forests and deforestation in Cambodia, to support climate change mitigation policies of Reducing Emission from Deforestation and Forest Degradation (REDD). We have observed mean backscattering coefficient (σ°), entropy (H), alpha angle (α), anisotropy (A), pedestal height (PH), Radar Vegetation Index (RVI) and Freeman–Durden three-component decomposition parameters. The observations show that the forest types and deforested area are showing variable polarimetric and backscattering properties because of the structural difference. Evergreen forest is characterized by a high value of σ° HV (?12.96 dB) as compared with the deforested area (σ° HV=?22.2 dB). The value of polarimetric parameters such as entropy (0.93), RVI (0.91), PH (0.41) and Freeman–Durden volume scattering (0.43) is high for evergreen forest, whereas deforested area is characterized by the low values of entropy (0.36) and RVI (0.17). Based on these parameters, it is found that σ° HV, entropy, RVI and PH provide best results among other parameters.