Long-term hydrology and aquatic biogeochemistry data from H. J. Andrews Experimental Forest,Cascade Mountains,Oregon     

Sherri L. Johnson  Don Henshaw  Greg Downing  Steve Wondzell  Mark Schulze  Adam Kennedy  Greg Cohn  Stephanie A. Schmidt  Julia A. Jones 《水文研究》2021,35(5):e14187

The H. J. Andrews Experimental Forest (HJA) encompasses the 6400 ha Lookout Creek watershed in western Oregon, USA. Hydrologic, chemistry and precipitation data have been collected, curated, and archived for up to 70 years. The HJA was established in 1948 to study the effects of harvest of old-growth conifer forest and logging-road construction on water quality, quantity and vegetation succession. Over time, research questions have expanded to include terrestrial and aquatic species, communities and ecosystem dynamics. There are nine small experimental watersheds and 10 gaging stations in the HJA, including both reference and experimentally treated watersheds. Gaged watershed areas range from 8.5 to 6242 ha. All gaging stations record stage height, water conductivity, water temperature and above-stream air temperature. At nine of the gage sites, flow-proportional water samples are collected and composited over 3-week intervals for chemical analysis. Analysis of stream and precipitation chemistry began in 1968. Analytes include dissolved and particulate species of nitrogen and phosphorus, dissolved organic carbon, pH, specific conductance, suspended sediment, alkalinity, and major cations and anions. Supporting climate measurements began in the 1950s in association with the first small watershed experiments. Over time, and following the initiation of the Long Term Ecological Research (LTER) grant in 1980, infrastructure expanded to include a set of benchmark and secondary meteorological stations located in clearings spanning the elevation range within the Lookout Creek watershed, as well as a large number of forest understory temperature stations. Extensive metadata on sensor configurations, changes in methods over time, sensor accuracy and precision, and data quality control flags are associated with the HJA data.  相似文献   

Regional soil organic carbon prediction model based on a discrete wavelet analysis of hyperspectral satellite data     

《International Journal of Applied Earth Observation and Geoinformation》2020

Most studies have the achieved rapid and accurate determination of soil organic carbon (SOC) using laboratory spectroscopy; however, it remains difficult to map the spatial distribution of SOC. To predict and map SOC at a regional scale, we obtained fourteen hyperspectral images from the Gaofen-5 (GF-5) satellite and decomposed and reconstructed the original reflectance (OR) and the first derivative reflectance (FDR) using discrete wavelet transform (DWT) at different scales. At these different scales, as inputs, we selected the 3 optimal bands with the highest weight coefficient using principal component analysis and chose the normalized difference index (NDI), ratio index (RI) and difference index (DI) with the strongest correlation with the SOC content using a contour map method. These inputs were then used to build regional-scale SOC prediction models using random forest (RF), support vector machine (SVM) and back-propagation neural network (BPNN) algorithms. The results indicated that: 1) at a low decomposition scale, DWT can effectively eliminate the noise in satellite hyperspectral data, and the FDR combined with DWT can improve the SOC prediction accuracy significantly; 2) the method of selecting inputs using principal component analysis and a contour map can eliminate the redundancy of hyperspectral data while retaining the physical meaning of the inputs. For the model with the highest prediction accuracy, the inputs were all derived from the wavelength range of SOC variations; 3) the differences in prediction accuracy among the different prediction models are small; and 4) the SOC prediction accuracy using hyperspectral satellite data is greatly improved compared with that of previous SOC prediction studies using multispectral satellite data. This study provides a highly robust and accurate method for predicting and mapping regional SOC contents.  相似文献   

The 2019 Brumadinho tailings dam collapse: Possible cause and impacts of the worst human and environmental disaster in Brazil     

《International Journal of Applied Earth Observation and Geoinformation》2020

On 25th January 2019, the tailings dam of the Brumadinho iron mine operated by Vale S/A failed catastrophically. The death toll stood at 259 and 11 people remained missing as of January 2020. This tragedy occurred three years after Mariana’s tailings dam rupture – the most significant tailing dam disaster in Brazilian history. Thus far, a systematic investigation on the cause and effect of the failure has yet to be conducted. Here, we use satellite-driven soil moisture index, multispectral high-resolution imagery and Interferometric Synthetic Aperture Radar (InSAR) products to assess pre-disaster scenarios and the direct causes of the tailings dam collapse. A decreasing trend in the moisture content at the surface and the full evanescence of pond water through time (2011–2019) suggest that the water was gradually penetrating the fill downwards and caused the seepage erosion, saturating the tailings dam. Large-scale slumping of the dam (extensional failure) upon the rupture indicates that the materials of the fill were already saturated. InSAR measurements reveal a dramatic, up to 30 cm subsidence in the dam (at the rear part) within the past 12 months before the dam collapse, signifying that the sediments had been removed from the fill. Although the information on the resistance level of the tailings dam to infiltrations is not available, these pieces of evidence collectively indicate that the seepage erosion (piping) is the primary cause for the chronic weakening of the structure and, hence, the internal “liquefaction” condition. Upon the collapse, the fully saturated mud tailings flowed down the gentle slope area (3.13 × 10⁶ m²), where 73 % were originally covered by tree, grass or agricultural tracts. The toxic mud eventually reached the Paraopeba River after travelling 10 km, abruptly increasing the suspended particulate matter (SPM) concentration and the toxic chemical elements in the river, immediately affecting the local livelihoods that depend on its water. The Paraopeba River is a major tributary of the San Francisco River, the second-longest river in Brazil reaching the Atlantic Ocean. We anticipate that the environmental repercussions of this toxic seepage will be felt throughout the entire basin, especially riverine communities located downstream.  相似文献   

面向数字孪生城市的智能化全息测绘   总被引：2，自引：0，他引：2  

顾建祥  杨必胜  董震  杨常红 《测绘通报》2020,(6):134-140

以大数据、物联网、人工智能、虚拟现实、云计算、智能驾驶等新技术为代表的信息化浪潮席卷全球，数字世界与物理世界正形成两大平行发展、相互作用的体系，数字孪生技术应运而生。随着物联网技术（IOT）的发展，数字孪生的理念被引入到智慧城市建设中来，深刻影响着城市规划、建设与治理。笔者所在单位面向数字孪生城市和自然资源统一监管对测绘地理信息的新需求，在全国开创性地开展了面向数字孪生城市的智能化全息测绘试点工作。本文结合上海市智能化全息测绘试点工作，从数字孪生城市、数字孪生城市对地理信息的新需求、智能化全息测绘关键技术及测绘成果等方面展开了论述，重点介绍了智能化全息测绘的技术体系和产品体系，以及在社会各领域的应用成果。  相似文献   

运用GD-PBIBD编码的矢量空间数据数字指纹算法     

陈金萍  张黎明  蒋美容  王昊 《测绘通报》2020,(8):81

针对矢量空间数据叛逆者追踪难及编码效率低的问题，本文提出了一种运用GD-PBIBD码的指纹算法。首先运用GD-PBIBD构造指纹编码，将待嵌入指纹序列运用Logistic映射置乱，通过D-P算法提取矢量空间数据的特征点，对特征点实施DFT变换得到相位系数和幅度系数；然后运用QIM方法将指纹嵌入DFT变换域的幅度系数上；最后应用DFT逆变换得到含指纹的矢量空间数据。试验选取部分中国路网数据和某区域绿地数据，运用该算法嵌入指纹后，对其进行线性和非线性模拟攻击，成功提取指纹序列，利用汉明距离追踪出合谋者。该算法编码构造简单，在码长一定的情况下，较BIBD码可容纳更多的用户，效率高；算法抗单用户指纹攻击及多重攻击的稳健性较好，也能够抵抗多用户最小值和最大最小值攻击，追踪到所有叛逆者，可用于矢量空间数据版权保护，为矢量空间数据叛逆者追踪提供依据。  相似文献   

基于OSM的浮动车轨迹数据校正方法     

胡向勇  郭圆 《测绘通报》2020,(10):139

浮动车轨迹数据具有覆盖范围广、更新周期短、获取成本低等特点，对于地图的生产和更新具有重要意义，但是由于受到卫星信号被遮挡及多路径效应的影响，其精度普遍较低。本文采用一种基于OSM作为参考数据的方式对浮动车轨迹数据进行校正。首先通过一种分层时空地图匹配的方式将轨迹数据与OSM进行匹配；然后采用引力模型对数据进行校正；最后在武汉市出租车轨迹数据上进行了试验。结果表明，本文提出的数据校正方法可以有效地提高浮动车轨迹数据的精度。  相似文献   

基于点云数据的不规则文物三维重建——以经幢为例     

喜文飞  李灵索  杨勇  李国柱  李春梅  李金平 《测绘通报》2020,(12):87-89

海量点云数据可以较好地构建文物的三维建模，针对文物复杂的表面结构，传统的算法很难达到精细建模，为了解决复杂模型表面的空间三角网构网问题，本文结合空间三角形的法向量构建三角网，以空间三角网表面的曲率为约束条件，构建物体表面的空间三角网，然后对构建的空间三角网进行精细建模。以昆明市文物——经幢为例进行三维重建试验，结果表明，新方法适合室内文物的三维建模，可以达到较好的效果。  相似文献   

BDS卫星钟差半参数平差模型异常数据探测与处理     

李文涛  颜雄  夏磊  任青阳  陈洁  潘雄 《测绘学报》2020,49(1):55-64

针对北斗卫星钟差数据中出现钟跳、粗差等异常数据频次较高的问题,将半参数平差模型引入BDS的钟差数据的处理过程中。首先,在考虑系统误差的同时,改进了常用的钟差模型;其次,综合考虑异常数据和系统误差,利用补偿最小二乘原理和极值求解方法,详细推导了分离异常数据前后参数和非参数估计值与相应观测值改正数的关系表达式,实现了异常数据的定值、参数求解和系统误差分离。在此基础上,引入Cook距离,给出了利用参数分量和非参数分量的Cook距离及混合Cook距离,去判断异常值的位置,并给出了一些参数的选取方法及相应的处理措施,实现了卫星钟差异常数据的定位和定值以及部分系统误差的分离。最后,采用武汉大学GNSS中心提供的采样间隔为5 min的北斗卫星精密钟差数据,将本文方法与常用方法进行了试验对比。试验结果表明,本文方法能够有效地识别并处理卫星钟差数据中的异常值,有效克服了基于经验阈值钟差异常数据探测方法的不足,且该方法对于量级较小的异常钟差数据也有很好的探测效果,一定程度丰富了现有的BDS钟差数据质量控制方法。  相似文献   

融合多源数据的三维建模方法及精度分析     

祖立辉 《北京测绘》2020,(3):347-351

以地面相机影像、低空无人机影像和地面三维激光点云数据为融合对象,研究空地影像融合、低空影像融合地面三维激光点云和低空影像融合三维白模进行三维建模的方法,并对其三维建模精度和建模效果进行综合分析。这3种融合方法进行三维建模丰富了三维模型的色彩纹理信息,提高了三维模型的几何结构精度,能满足较大场景的三维实景模型的建模要求,为数字化古建筑(古文物)保护提供具有较高价值的参考数据。  相似文献   

基于时相变化的晴空条件下Himawari-8 AHI火点检测     

鄢俊洁  瞿建华  冉茂农  张芳芳 《遥感学报》2020,24(5):571-577

Himawari-8静止气象卫星具有高空间分辨率、高观测频次和高时效特点,对于火点检测具有很强优势。对Himawari-8卫星的3.9μm和11.2μm两通道亮温进行了连续时相变化研究,得出两通道的亮温在时间上的变化差值稳定且规律明显。根据两通道的亮温时相特征,考虑白天可见光对3.9μm通道的影响,并结合火点产生时引起的亮温变化特征,提出了适用于晴空条件下改进的火点检测算法。在多处进行了此算法的实验,例如2018-11-27 T 16:40(UTC时)河北张家口市桥东区一化工厂附近发生的严重爆炸起火事件以及2019-02-28澳大利亚西南部发生的火灾事件,均快速有效的检测到了火点。实验表明,改进的火点检测算法能很好的进行火点检测,并能解决晨昏交界、冰雪下垫面、常规火源点、太阳耀光等火点检测的难题。  相似文献