利用NOAA卫星图像和水文资料研究东海水文的变化

本文利用ＮＯＡＡ卫星图像处理结果与同期水文观测资料，对东海表层水团的分布和转移特征作了初步分析。结果表明，东海表层水温的分布与结构同该海区的水团和环流发展相联系，水团消长和东海冬季高密水核心上层环流的发展可诱导长江口外混合水向外海扩散，表层水块的移动速度可达２６ｃｍ／ｓ，与动力学估算和同期漂移浮标所得的结果一致     

一种DMSP/OLS稳定夜间灯光影像中国区域的校正方法

随着遥感技术的快速发展,国防气象卫星计划作战线扫描系统（DMSP/OLS）夜间灯光图像开始更多的应用于人文经济研究中。由于原始影像存在较多问题,如DN值饱和、年际不连续问题等,因此在使用之前需要对影像进行校正。“传统不变区域法”是应用较为广泛的校正方法,但仍存在部分问题,如未考虑目标区域长时间尺度上的微弱变化以及连续校正前基准年份的选取。本文对传统不变目标区域法进行改良,以黑龙江鹤岗市作为不变目标区域,选取3期辐射定标影像作为参考影像对DMSP/OLS稳定夜间灯光影像进行饱和校正,通过对比各年份影像饱和校正情况,选出最为合理的基准年份,从而对饱和校正后的影像进行连续性校正。为验证影像校正精度,本文从国家像元DN值、省级GDP与电力消费量、地级市GDP和县域GDP 4个层面与对应DN值进行线性回归检验,结果显示经改进方法校正后DMSP/OLS稳定夜间灯光影像TDN与市级GDP的拟合度（R2）平均值为0.85,远大于传统方法校正TDN与市级GDP拟合度（R2）平均值的0.53,且随着时间推移,传统不变目标区域法校正后拟合度逐渐降低至2013年的0.40,而利用改进后方法进行校正的拟合度未出现递减现象,2013年其R2仍为0.88,表明与传统不变区域法相比校正精度明显提高,饱和问题得到较大改善。     

Sub-pixel classification of SPOT-VEGETATION time series for the assessment of regional crop areas in Belgium

Global time series of low resolution images are available with high repeat frequency and at low cost, but their analysis is hampered by the presence of mixed pixels and the difficulty in locating detailed spatial features. This study examined the potential of sub-pixel classification for regional crop area estimation using time series of monthly NDVI-composites of the 1 km resolution sensor SPOT-VEGETATION. Belgium was selected as test zone, because of the availability of ample reference data in the form of a vectorial GIS with the boundaries and cover type of the large majority of agricultural fields. Two different methods were investigated: the linear mixture model and neural networks. Both result in area fraction images (AFIs), which contain for each 1 km pixel the estimated area proportions occupied by the different cover types (crops or other land use). Both algorithms were trained with part of the reference data and validated with the remainder. Validation was repeated at three different levels: the 1 km pixel, the municipality and the agro-statistical district. In general, the neural network outperformed the linear mixture model. For the major classes (winter wheat, maize, forest) the obtained acreage estimates showed good agreement with the true values, especially when aggregated to the level of the municipality (R² ≈ 85%) or district (R² ≈ 95%). The method seems attractive for wide-scale, regional area estimation in data-poor countries.     

基于 C4.5决策树的多特征遥感分类方法

以钱塘江流域为研究区域,利用2010年ETM,MODIS和DEM多源数据,进行土地利用分类研究。在分析土地类型的光谱特性和植被指数年度变化基础上,运用光谱指数法和代数法从数据中提取各种土地覆被类型特征。利用WEKA软件平台下的C4.5决策树算法构建决策树分类模型,对钱塘江流域土地覆被类型进行分类研究,取得较高的分类精度。     

面向序列影像的三维场景重建方法

针对序列影像三维场景重建过程中存在的自动化程度不高、模型精度不够等问题,该文提出了一种基于序列影像的三维场景重建方法。该方法利用尺度不变特征变换算子获得了大量稳定的特征点后,结合K-D树搜索策略以及随机抽样一致性误匹配剔除方法得到稳定的匹配点对,然后采用稀疏光束法平差获取序列影像的相对位置姿态参数,最后采用多视密集匹配方法实现场景目标的密集重建。实验结果表明:该文所提方法可以快速得到准确、完整的三维重建结果。     

Channel bar feature extraction for a mining-contaminated river using high-spatial multispectral remote-sensing imagery

Mapping and monitoring changes of geomorphological features over time are important for understanding fluvial process and effects of its controlling factors. Using high spatial resolution multispectral images has become common practice in the mapping as these images become widely available. Traditional pixel-based classification relies on statistical characteristics of single pixels and performs poorly in detailed mapping using high resolution multispectral images. In this work, we developed a hybrid method that detects and maps channel bars, one of the most important geomorphological features, from high resolution multispectral aerial imagery. This study focuses on the Big River which drains the Ozarks Plateaus region in southeast Missouri and the Old Lead Belt Mining District which was one of the largest producers of lead worldwide in the early and middle 1900s. Mapping and monitoring channel bars in the Big River is essential for evaluating the fate of contaminated mining sediment released to the Big River. The dataset in this study is 1 m spatial resolution and is composed of four bands: Red (Band 3), Green (Band 2), Blue (Band 1) and Near-Infrared (Band 4). The proposed hybrid method takes into account both spectral and spatial characteristics of single pixels, those of their surrounding contextual pixels and spatial relationships of objects. We evaluated its performance by comparing it with two traditional pixel-based classifications including Maximum Likelihood (MLC) and Support Vector Machine (SVM). The findings indicate that derived characteristics from segmentation and human knowledge can highly improve the accuracy of extraction and our proposed method was successful in extracting channel bars from high spatial resolution images.     

Appraisive images of tourist areas: application of personal constructs

Personal construct theory was used to study the appraisive images held by tourists visiting the North Coast of New South Wales. In the first stage of the research, subjects produced a wide variety of constructs in differentiating between tourist places. This enabled the identification of six key evaluative constructs. In the second stage of the research, these constructs were incorporated into repertory grids that revealed how places were viewed. Principal components analysis showed that very similar images were held by tourists irrespective of age and sex, but that slight differences emerged between the images held by tourists and those held by workers in the tourist industry. The evaluative constructs identified may provide a general basis for understanding tourist perceptions.     

河北省太行山南段东坡第四纪冰川遗迹的遥感解译

利用大比例尺黑白航空像片首次在太行山南段东坡发现了大面积保存较完好的冰川遗迹如角峰、刃脊、冰斗、悬谷、冰蚀盆地及冰蚀槽谷等,经系统组合、配套后认为,第四纪时期,该区曾发育过三一四期冰川活动,第I、II冰期冰川属于山谷一山麓冰川类型,而第IⅡ、IV(?)期冰川则为冰斗冰川。本文详述了各类冰蚀地貌的期次,分布、类型及发育特征,为该区第四纪古冰川活动的研究提供了新的证据。     

山东水道—冯家幅能谱数据图像处理及地质解译效果

应用美国S101图像处理系统,对山东水道—冯家幅能谱(U、K、Th、Tc)数据作了图像处理.能谱比值合成图像反映了原图件未显示的线性、环形构适、蚀变带等,其中一些环形构造与MSS图像上反映的环形构造一致.依据地质图件,应用能谱图像,详细划分岩性,圈定了构造、岩体和蚀变带,取得了满意的地质解译效果.     

Spatial predictions of geological rock mass properties based on in-situ interpretations of multi-dimensional seismic data

The article presents a statistical approach to characterize and predict engineering geological conditions in the up to 2000 m deep Faido tunnel and Gotthard base tunnel in Switzerland. Seismic investigations were conducted to improve the technology of interpreting seismic tomographic images. Overall, the goal of this study was to predict spacial maps of geological rock mass properties, such as, uniaxial compressive strength or total fracture spacing, by using up to six seismic features in combination, e.g., compression-wave and shear-wave velocities and dynamic Poisson's ratio. Self-Organizing Mapping (SOM), an artificial intelligent method, was used for the purposes of interpreting multi-dimensional geophysical attributes derived from seismic profiles of tomographic images along tunnel sidewalls. The SOM-method was applied in the Faido tunnel to delineate complex physical relations between the geological and seismic parameters. Then, the method was applied to predict geological properties around a segment of the Gotthard base tunnel with unknown geological–geotechnical conditions. The results illuminate that correlation analyses (pairwise parameter classification) are substantially less powerful than the SOM-method (multi-parameter classification) in order to interpret geological features from seismic in-situ data. Moreover, predicted spatial distributions of the total fracture spacing and the uniaxial compressive strength, for example, corresponded well with drill core and tunnel mapping results. The SOM-approach was a helpful tool for practitioners in predicting zones of instabilities and geological complexity during underground excavation processes of the Gotthard base tunnel. It is suggested to use such an interpretation method as decision support for purposes of sub/surface exploration and long-term geophysical monitoring of large-scale geoengineering projects, such as, disposals of nuclear waste and greenhouse gases or geopower plants for renewable energy (geothermal, biosoils).