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.     

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.     

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。     

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.     

Hydrocarbon Alteration Characteristics of Soils and Mechanism for Detection by Remote Sensing in East Sichuan Area,China

The type, strength, and spatial distributions of hydrocarbon alteration of the surface soil are studied in two sections in East Sichuan area through the simultaneous analysis of soil organic geochemistry, soil mineralogy, and soil chemistry. The spectral response and remote-sensing mechanism are studied through the soil spectral analysis in the range of VIS--NIR bands. The results of this study demonstrate that long-time hydrocarbon microseepage can induce mineral and chemical alteration of surface soil, including the increase of clay-mineral content and carbonate-mineral content, the increase of ferrous-iron content, and decrease of ferric-iron content. Soil mineral components related to hydrocarbon alteration have spatial coincidence with soil organic geochemical components. Increase of clay- and carbonate-mineral contents in the soil can cause decrease of reflectance in VIS–NIR bands and increase of Landsat band ratio TM5/TM7. Increase of ferrous-iron content and decrease of ferric-iron content in the soil may cause increase of reflectance in the range of 400 nm to 600 nm, and higher reflectance of Landsat band ratios of TM1/TM3 and TM2/TM3.     

遥感监测墨西哥湾溢油目标识别算法

为了及时监测溢油事故相关信息,防止污染扩张,该文利用2010年4月29日、5月17日及5月24日3个时相的中分辨率MODIS数据,以2010年发生的墨西哥湾溢油事故为例进行目标提取与识别。提取算法考虑到油膜和背景海水易混分的现象,采用了辅加纹理特征量的光谱角匹配算法进行油膜提取;同时,对比了常用的最小距离和支持向量机分类方法;并基于混淆矩阵对结果进行精度验证。结果显示,改进的光谱角匹配算法可以更准确地提取海面目标,精度高达90%以上,能够较好地监测出大面积溢油,可以用于海面溢油灾害的动态监测。     

基于ER Mapper的水土流失地形因子提取技术初探

介绍了新一代图像处理系统ER Mapper及其应用，分析了不同空间尺度下影响水土流失的地形因子，针对ER Mapper的图像处理功能，对地形因子的提取技术进行了初步探讨，并取得了一定的成果。     

Calcite patchiness in Lake Constance as viewed by LANDSAT-TM

Calcite precipitation is a phenomenon occuring in most hardwater lakes world-wide. On May 5th, 1990, a whiting in Lake Constance was observed by LANDSAT for the first time. Physical, chemical and biological ground data sets prove that the observed structures are caused by calcite precipitation. This satellite observation provides information about the patchiness of calcite crystals suspended in the surface water of the lake western basin.     

青岛近海浒苔光谱特征研究

针对从2008年以来,每年夏季我国黄海南部暴发大面积的浒苔(Enteromorpha)灾害,对海洋环境及经济造成不利影响的状况,为了进一步研究浒苔特性,为利用遥感手段监测浒苔提供一定的理论依据,通过实地测量不同条件下浒苔的光谱反射率曲线,定性分析了浒苔的光谱特征。结果表明,浒苔的基本光谱特征表现为在蓝光波段和红光波段形成反射谷,在绿光波段形成反射峰,而在近红外波段反射率明显增大,形成高反射峰。因此将红光波段和近红外波段作为敏感波段,利用NDVI(归一化植被指数)提取遥感图像上的浒苔信息,可取得较好效果,有利于浒苔监测。