电磁卫星地面对比观测原型系统地电场观测资料特征分析          下载免费PDF全文

周卫东  牛延平  田野  苏小芸  陈丽君 《地震工程学报》2020,42(6):1517-1522

通过对电磁监测试验卫星地面对比观测原型系统中古丰、寺滩和坪城地电场观测数据特征研究，结果表明：（1）3个台站的地电场观测数据均具有较为明显的正常日变化形态；（2）在磁暴发生期间，地电场各测向均记录到了同步的地电暴变化，其最大变幅均明显高于正常日变；（3）寺滩地电场记录到临震前的数据异常现象，在时间和空间上都与地震事件吻合较好。  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   

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   

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   

Sentinel-2卫星落叶松林龄信息反演   总被引：1，自引：0，他引：1  

唐少飞  田庆久  徐凯健  徐念旭  岳继博 《遥感学报》2020,24(12):1511-1524

林龄结构信息能够有效反映区域森林群落不同生长阶段的固碳能力，对于评估森林生态系统的健康状况具有重要意义。本研究以中国温带典型优势树种落叶松林为研究对象，分别选择其芽萌动期、展叶期和落叶期时段的Sentinel-2影像，采用多元线性回归（MLR）、随机森林（RF）、支持向量机回归（SVR）、前馈反向传播神经网络（BP）以及多元自适应回归样条（MARS）等5种方法依次构建落叶松林龄反演模型。通过相关性分析首先确定最佳遥感反演物候期，并在此基础上根据相关性差异筛选出5个最优特征变量用于模型反演，分别为冠层含水量（CWC），归一化水体指数（NDWI），叶面积指数（LAI），光合有效辐射吸收率（FAPAR）和植被覆盖度（FVC）。研究结果表明，展叶期为落叶松林最佳遥感反演物候期。除植被衰减指数（PSRI）以及落叶期的NDVI、RVI外，落叶松林龄与各指标之间均呈负相关关系，其中与冠层含水量（CWC）的相关性最高，pearson相关系数达到-0.74（p<0.01）。此外，不同模型反演结果表明，随机森林模型（RF）为最佳落叶松林龄估测模型，其平均决定系数R²和平均均方根误差RMSE分别为0.89和2.91 a；多元线性回归模型（MLR）的林龄估测结果最差，其平均决定系数R²和平均均方根误差RMSE仅为0.57和5.69 a，非线性模型能更好的解释林龄与建模变量之间的关系。  相似文献   

Integrating spectral and non-spectral data to improve urban settlement mapping in a large Latin-American city     

Feilin Lai 《地理信息系统科学与遥感》2020,57(6):830-844

ABSTRACT

Information on urban settlements is crucial for sustainability planning and management. While remote sensing has been used to derive such information, its applicability can be compromised due to the complexity in the urban environment. In this study, we developed a remote sensing method to map land cover types in a large Latin-American city, which is well known for its mushrooming unplanned and informal settlements. After carefully considering the landscape complexity there, we designed a data fusion method combining multispectral imagery and non-spectral data for urban and land mapping. Specifically, we acquired a cloud-free Landsat-8 image and two non-spectral datasets, i.e., digital elevation models and road networks. Then, we implemented a set of experiments with different inputs to evaluate their merits in thematic mapping through a supervised protocol. We found that the map generated with the multispectral data alone had an overall accuracy of 73.3% but combining multispectral imagery and non-spectral data yielded a land cover map with 90.7% overall accuracy. Interestingly, the thermal infrared information helped substantially improve both the overall and categorical accuracies, particularly for the two urban classes. The two types of non-spectral data were critical in resolving several spectrally confused categories, thus considerably increasing the mapping accuracy. However, the panchromatic band with higher spatial resolution and its derived textural measurement only generated a marginal accuracy improvement. The novelties of our work are with the successful separation between the two major types of urban settlements in a complex environment using a carefully designed data fusion approach and the insight into the relative merits of the thermal infrared information and non-spectral data in helping resolve the issue of class ambiguity. These findings should be valuable in deriving accurate urban settlement information which can further advance the research on socio-ecological dynamics and urban sustainability.  相似文献   

基于 SRP 概念模型的祁连山地区生态脆弱性评价   总被引：1，自引：0，他引：1       下载免费PDF全文

刘佳茹  赵军  沈思民  赵彦军 《干旱区地理》2020,43(6):1573-1582

基于生态敏感性-生态恢复力-生态压力度（SRP）概念模型，从地形、气候、植被和社会经济 因子选取 8 个评价指标，利用遥感和 GIS 技术，采用主成分分析方法求取权重，对祁连山地区启动 水源涵养区生态环境保护和综合治理规划研究前后近 10 a 的生态脆弱性程度进行系统、定量地评 估，旨在揭示生态脆弱性的分布特征、时空演变及动因，为区域生态保护、资源利用和可持续发展 提供参考。结果表明：（1）从研究区生态脆弱性分布来看，祁连山地区主要以轻度和重度脆弱为 主，脆弱性程度从西北向东南地区逐渐减弱，西北地区植被覆盖度小，海拔高，生态环境较为恶劣 是导致脆弱性程度较高的原因；（2）祁连山地区 3 期生态脆弱程度呈逐渐下降趋势，综合指数分别 为 3.307、3.118 和 3.103；2005 年 生 态 脆 弱 性 较 高 ，极 度 脆 弱 面 积 为 28 610 km²，2010 年 下 降 为 11 723 km²，2015 年降低为 6 174 km²，极度脆弱面积逐渐减少；（3）从祁连山地区生态脆弱性演变动 因来看，8 个指标对生态脆弱性影响均较为显著，但在不同的时间影响程度各不相同，2005—2015 年 3 期数据中对生态脆弱性影响最大的均为植被指数，降水次之，地形因子影响最小。总体来看， 近年来祁连山地区生态脆弱性程度有所降低，但仍然需要加强保护力度，促进生态环境可持续 发展。  相似文献   

“一带一路”沿线国家石油资源流动类型演变     

孙琪  赵媛  张新林  夏四友 《世界地理研究》2020,29(2):337-345

综合运用石油自给率、流动比率等方法，以“一带一路”沿线国家为研究对象，对1995—2014年各国石油资源流动类型时空演变进行研究。结果表明：1）1995—2014年石油净补给型国家数量较为稳定，无产型或低产型国家的石油贸易倾向变化相对较小；基本自给型国家数量占比最大，1995年占比1/2，其余四个年份占比稳定在1/3；净支出型国家数量显著增加，至2014年其中有5个国家保持不变，表明这些国家的石油产量具有较大的优势。2）1995年和2014年汇地国家均为39个国家，其中有34个国家一直保持汇地职能，空间分布上呈东多西少，南多北少，东西分化以西亚、中亚、东欧为界；有14个国家一直保持源地职能，其空间分布格局与汇地相应，西多东少，南多北少，主要分布于西亚、东欧及中亚；交流地数量较少，呈分散分布，且分布地不稳定。3）从数量变化来看，研究期内汇地略有增加，源地略有减少，交流地略有增加；“一带一路”源地总出口量与汇地总进口量的比呈逐年降低趋势。  相似文献   

陕北地区退耕还林还草工程土壤保护效应的时空特征   总被引：1，自引：1，他引：0  

刘文超  刘纪远  匡文慧 《地理学报(英文版)》2020,30(3):401-422

This paper looks at the Green for Grain Project in northern Shaanxi Province.Based on remote sensing monitoring data,this study analyzes the locations of arable land in northern Shaanxi in the years 2000,2010 and 2013 as well as spatio-temporal changes over that period,and then incorporates data on the distribution of terraced fields to improve the input parameters of a RUSLE model and simulate and generate raster data on soil erosion for northern Shaanxi at different stages with a accuracy verification.Finally,combined with the dataset of farmland change,compared and analyzed the characteristics of soil erosion change in the converted farmland to forest(grassland)and the unconverted farmland in northern Shaanxi,so as to determine the project’s impact on soil erosion over time across the region.The results show that between 2000 and 2010,the soil erosion modulus of repurposed farmland in northern Shaanxi decreased 22.7 t/ha,equivalent to 47.08%of the soil erosion modulus of repurposed farmland in 2000.In the same period,the soil erosion modulus of non-repurposed farmland fell 10.99 t/ha,equivalent to 28.6%of the soil erosion modulus of non-repurposed farmland in 2000.The soil erosion modulus for all types of land in northern Shaanxi decreased by an average of 14.51 t/ha between 2000 and 2010,equivalent to 41.87%of the soil erosion modulus for the entire region in 2000.This suggests that the Green for Grain Project effectively reduced the soil erosion modulus,thus helping to protect the soil.In particular,arable land that was turned into forest and grassland reduced erosion most noticeably and contributed most to soil conservation.Nevertheless,in the period 2010 to 2013,which was a period of consolidation of the Green for Grain Project,the soil erosion modulus and change in volume of soil erosion in northern Shaanxi were significantly lower than in the previous decade.  相似文献