基于Global Mapper的DEM检查方法

Global Mapper是一款地图绘制软件。本文结合辽宁省测绘局1∶10000 DEM制作项目,阐述了利用Global Mapper软件对DEM最终成果进行质量检查的具体检查方法。     

基于Global Mapper的地貌晕渲制图——以西安幅(Ⅰ-49)为例

地貌晕渲图自动制图是以计算机软、硬件为基础,对DEM数据实现的一种三维立体可视化表达。本文从地貌晕渲的基本理论出发,以我国1:100万标准分幅的西安幅(1-49)为例,采用Global Mapper软件实现了计算机地貌晕渲自动制作的全过程,主要内容包括:计算机地貌晕渲关键技术的实现,地貌晕渲效果与参数设置之间的关系,Global Mapper软件中各种参数设置的合理性分析,使用分层设色的办法对晕渲图进行色彩的设计,并利用PHOTOSHOP软件对结果进行整饰等。该方法可实现地貌晕渲图的自动制图。     

基于Global Mapper的地貌晕渲图设计与制作

地貌晕渲图是指利用数字高程模型（ DEM）来生成,可以很好地反映地形、地势的变化,具有较好立体感的地图。本文以地貌晕渲基本理论为出发点,利用Global Mapper软件实现对制图数据的地貌晕渲图自动生成。对制图区域内的地形地势特征,地貌晕渲图在计算机上实现的关键技术,整体性考虑对地貌晕渲图效果的影响,合理分析设置Global Mapper软件中的各类参数,并利用Photoshop软件对地貌晕渲图进行调整。     

Monitoring land changes in an urban area using satellite imagery,GIS and landscape metrics

Monitoring land changes is an important activity in landscape planning and resource management. In this study, we analyze urban land changes in Atlanta metropolitan area through the combined use of satellite imagery, geographic information systems (GIS), and landscape metrics. The study site is a fast-growing large metropolis in the United States, which contains a mosaic of complex landscape types. Our method consisted of two major components: remote sensing-based land classification and GIS-based land change analysis. Specifically, we adopted a stratified image classification strategy combined with a GIS-based spatial reclassification procedure to map land classes from Landsat Thematic Mapper (TM) scenes acquired in two different years. Then, we analyzed the spatial variation and expansion of urban land changes across the entire metropolitan area through post classification change detection and a variety of GIS-based operations. We further examined the size, pattern, and nature of land changes using landscape metrics to examine the size, pattern, and nature of land changes. This study has demonstrated the usefulness of integrating remote sensing with GIS and landscape metrics in land change analysis that allows the characterization of spatial patterns and helps reveal the underlying processes of urban land changes. Our results indicate a transition of urbanization patterns in the study site with a limited outward expansion despite the dominant suburbanization process.     

Linking pesticides and human health: A geographic information system (GIS) and Landsat remote sensing method to estimate agricultural pesticide exposure

Accurate pesticide exposure estimation is integral to epidemiologic studies elucidating the role of pesticides in human health. Humans can be exposed to pesticides via residential proximity to agricultural pesticide applications (drift). We present an improved geographic information system (GIS) and remote sensing method, the Landsat method, to estimate agricultural pesticide exposure through matching pesticide applications to crops classified from temporally concurrent Landsat satellite remote sensing images in California. The image classification method utilizes Normalized Difference Vegetation Index (NDVI) values in a combined maximum likelihood classification and per-field (using segments) approach. Pesticide exposure is estimated according to pesticide-treated crop fields intersecting 500 m buffers around geocoded locations (e.g., residences) in a GIS. Study results demonstrate that the Landsat method can improve GIS-based pesticide exposure estimation by matching more pesticide applications to crops (especially temporary crops) classified using temporally concurrent Landsat images compared to the standard method that relies on infrequently updated land use survey (LUS) crop data. The Landsat method can be used in epidemiologic studies to reconstruct past individual-level exposure to specific pesticides according to where individuals are located.     

ETM+卫星影像极地云层检测及分析

云一直是遥感图像预处理和分析中的一大难点,本文在分析南极地区成像特点的基础上,试图利用增强型主题成像传感器(ETM+)获取影像的多波段特点,对南极格罗夫山地区ETM+卫星影像进行云的检测。结果表明,该方法不仅能比较成功地检测极地云层像元,而且能有效地去除部分厚云的影响。     

Illumination effects on the differenced Normalized Burn Ratio's optimality for assessing fire severity

The influence of illumination effects on the optimality of the dNBR (differenced Normalized Burn Ratio) was evaluated for the case of the 2007 Peloponnese (Greece) wildfires using a pre/post-fire Landsat TM (Thematic Mapper) image couple. Well-illuminated pixels (south and south-east facing slopes) exhibited more optimal displacements in the bi-spectral feature space than more shaded pixels (north and north-west exposed slopes). Moreover, pixels experiencing a small image-to-image difference in illumination obtained a higher optimality than pixels with a relatively large difference in illumination. To correct for illumination effects, the c-correction method and a modified c-correction technique were applied. The resulting median dNBR optimality of uncorrected, c-corrected and modified c-correction data was respectively 0.58, 0.60 and 0.71 (differences significant for p < 0.001). The original c-correction method improved the optimality of badly illuminated pixels while deteriorating the optimality of well-illuminated pixels. In contrast, the modified c-correction technique improved the optimality of all the pixels while retaining the prime characteristic of topographic correction techniques, i.e. detrending the illumination–reflectance relationship. For a minority of the data, for shaded pixels and/or pixels with a high image-to-image difference in illumination, the original c-correction outperformed the modified c-correction technique. In this study conducted in rugged terrain and with a bi-temporal image acquisition scheme that deviated up to two months from the ideal anniversary date scheme the modified c-correction technique resulted in a more reliable change detection.     

Monitoring wetland ditch water levels in the North Kent Marshes,UK, using Landsat TM imagery and ground-based measurements

Abstract

An understanding of hydrology is a prerequisite for ensuring the successful management, conservation and restoration of wetland environments. Frequently, however, little is known about historical hydrological conditions, such as water levels, within wetlands. Moreover, many channel and ditch systems in wetlands are not routinely monitored, except perhaps for research purposes. A methodology is presented herein which makes use of satellite imagery to indirectly provide remotely sensed observations of water levels within channels and ditches. Using multi-temporal Landsat Thematic Mapper (TM) imagery and simultaneous ground-based measurements of water levels, statistical relationships are established between satellite-derived effective wet ditch widths and measured water levels in the drainage system of the Elmley Marshes, southeast England. These relationships can be used subsequently to estimate historical ditch water levels and to monitor contemporary ditch water levels in the wetland. The study shows that satellite imagery has much to offer in monitoring changes in the hydrological regime of wetlands and in providing complimentary approaches to field monitoring.     

铁路测量中坐标系的建立与转换

在铁路测量中,长度投影变形要求小于2．5cm／km。但是由于铁路为典型的线性工程,通常横跨多个投影带,因此采用国家标准3。带难以满足铁路测量精度要求,本文通过分析高斯投影长度变形,提出分段建立独立坐标系的方法,控制长度投影变形,满足精度要求,最后介绍利用GlobalMapper软件实现两个独立坐标系的转换。     

Clustering based on eigenspace transformation – CBEST for efficient classification

Large remote sensing datasets, that either cover large areas or have high spatial resolution, are often a burden of information mining for scientific studies. Here, we present an approach that conducts clustering after gray-level vector reduction. In this manner, the speed of clustering can be considerably improved. The approach features applying eigenspace transformation to the dataset followed by compressing the data in the eigenspace and storing them in coded matrices and vectors. The clustering process takes the advantage of the reduced size of the compressed data and thus reduces computational complexity. We name this approach Clustering Based on Eigen-space Transformation (CBEST). In our experiment with a subscene of Landsat Thematic Mapper (TM) imagery, CBEST was found to be able to improve speed considerably over conventional K-means as the volume of data to be clustered increases. We assessed information loss and several other factors. In addition, we evaluated the effectiveness of CBEST in mapping land cover/use with the same image that was acquired over Guangzhou City, South China and an AVIRIS hyperspectral image over Cappocanoe County, Indiana. Using reference data we assessed the accuracies for both CBEST and conventional K-means and we found that the CBEST was not negatively affected by information loss during compression in practice. We discussed potential applications of the fast clustering algorithm in dealing with large datasets in remote sensing studies.