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1.
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   
2.
阿伯德尔国家公园位于号称肯尼亚“水塔”的阿伯德尔山脉上,是肯尼亚重要的旅游景区和珍稀动植物保护区,开展该地生态环境质量评价对肯尼亚水资源保护与可持续发展具有重要的意义。本研究基于1987-2018年的Landsat系列遥感数据,通过计算综合遥感生态指数RSEI,结合趋势线分析法对阿伯德尔国家公园近32年间生态环境质量变化进行客观定量分析。研究结果显示:① 1987-2018年研究区RSEI均值从0.62下降到0.51,生态环境质量退化的区域面积为551.52 km 2,占总面积的71.85%,表明在气候变化和人类活动影响下,1987-2018年研究区的环境状况呈恶化趋势;②环境质量显著恶化的区域主要分布于亚高山植被区和东部低海拔森林覆盖区,亚高山地区植被生态系统结构单一,稳定性差,对气候变化和人类活动更为敏感;而东部区域存在过度开发,非法砍伐森林等现象,且旅游开发强度大,环境恶化与人类活动密切相关。  相似文献   
3.
To support the adoption of precision agricultural practices in horticultural tree crops, prior research has investigated the relationship between crop vigour (height, canopy density, health) as measured by remote sensing technologies, to fruit quality, yield and pruning requirements. However, few studies have compared the accuracy of different remote sensing technologies for the estimation of tree height. In this study, we evaluated the accuracy, flexibility, aerial coverage and limitations of five techniques to measure the height of two types of horticultural tree crops, mango and avocado trees. Canopy height estimates from Terrestrial Laser Scanning (TLS) were used as a reference dataset against height estimates from Airborne Laser Scanning (ALS) data, WorldView-3 (WV-3) stereo imagery, Unmanned Aerial Vehicle (UAV) based RGB and multi-spectral imagery, and field measurements. Overall, imagery obtained from the UAV platform were found to provide tree height measurement comparable to that from the TLS (R2 = 0.89, RMSE = 0.19 m and rRMSE = 5.37 % for mango trees; R2 = 0.81, RMSE = 0.42 m and rRMSE = 4.75 % for avocado trees), although coverage area is limited to 1–10 km2 due to battery life and line-of-sight flight regulations. The ALS data also achieved reasonable accuracy for both mango and avocado trees (R2 = 0.67, RMSE = 0.24 m and rRMSE = 7.39 % for mango trees; R2 = 0.63, RMSE = 0.43 m and rRMSE = 5.04 % for avocado trees), providing both optimal point density and flight altitude, and therefore offers an effective platform for large areas (10 km2–100 km2). However, cost and availability of ALS data is a consideration. WV-3 stereo imagery produced the lowest accuracies for both tree crops (R2 = 0.50, RMSE = 0.84 m and rRMSE = 32.64 % for mango trees; R2 = 0.45, RMSE = 0.74 m and rRMSE = 8.51 % for avocado trees) when compared to other remote sensing platforms, but may still present a viable option due to cost and commercial availability when large area coverage is required. This research provides industries and growers with valuable information on how to select the most appropriate approach and the optimal parameters for each remote sensing platform to assess canopy height for mango and avocado trees.  相似文献   
4.
The fractional vegetation cover (FVC), crop residue cover (CRC), and bare soil (BS) are three important parameters in vegetation–soil ecosystems, and their correct and timely estimation can improve crop monitoring and environmental monitoring. The triangular space method uses one CRC index and one vegetation index to create a triangular space in which the three vertices represent pure vegetation, crop residue, and bare soil. Subsequently, the CRC, FVC, and BS of mixed remote sensing pixels can be distinguished by their spatial locations in the triangular space. However, soil moisture and crop-residue moisture (SM-CRM) significantly reduce the performance of broadband remote sensing CRC indices and can thus decrease the accuracy of the remote estimation and mapping of CRC, FVC, and BS. This study evaluated the use of broadband remote sensing, the triangular space method, and the random forest (RF) technique to estimate and map the FVC, CRC, and BS of cropland in which SM-CRM changes dramatically. A spectral dataset was obtained using: (1) from a field-based experiment with a field spectrometer; and (2) from a laboratory-based simulation that included four distinct soil types, three types of crop residue (winter-wheat, maize, and rice), one crop (winter wheat), and varying SM-CRM. We trained an RF model [designated the broadband crop-residue index from random forest (CRRF)] that can magnify spectral features of crop residue and soil by using the broadband remote sensing angle indices as input, and uses a moisture-resistant hyperspectral index as the target. The effects of moisture on crop residue and soil were minimized by using the broadband CRRF. Then, the CRRF-NDVI triangular space method was used to estimate and map CRC, FVC, and BS. Our method was validated by using both laboratory- and field-based experiments and Sentinel-2 broadband remote-sensing images. Our results indicate that the CRRF-NDVI triangular space method can reduce the effect of moisture on the broadband remote-sensing of CRC, and may also help to obtain laboratory and field CRC, FVC, and BS. Thus, the proposed method has great potential for application to croplands in which the SM-CRM content changes dramatically.  相似文献   
5.
潮滩作为动态变化的后备土地资源,对其研究具有重要意义。文章以江苏省如东县为研究区,使用环境资源卫星(HJ1A/1B)影像为数据源,应用面向对象技术创建分类规则,实现批量半自动提取水边线,随后利用DSAS软件处理水边线集获得潮位点集,基于最外边界法实现高(低)潮位点的提取,进而获得潮滩范围,估算的如东县潮滩面积为55 182hm~2。最后利用误差矩阵进行精度验证(Kappa系数为0.945)。结果表明:该方法对于潮滩面积提取具有适用性,无论在空间域还是时间域都具有一定的推广性。  相似文献   
6.
高分辨率遥感图像处理经常面临程序执行时间过长和内存空间不足的问题,虽然并行计算技术可以提高遥感图像的处理速度,但是无法降低算法占用的巨大内存空间。为了解决这一问题,本文提出了一种利用CUDA和内存映射文件的高分辨率遥感图像快速处理方法,并以K-Means算法为例进行了实现。其中,CUDA技术可以有效利用GPU强大的并行计算能力,而内存映射文件技术降低了磁盘I/O速度较慢对算法性能的影响。实验结果表明,本文方法比传统K-Means聚类算法计算速度提高了30倍左右,内存使用量降低了90%以上。  相似文献   
7.
The West Junggar Orogenic Belt(WJOB)in northwestern Xinjiang,China,is located in the core of the western part of the Central Asian Orogenic Belt(CAOB).It has suffered two stage tectonic evolutions in Phanerozoic,before and after the ocean–continental conversion in Late Paleozoic.The later on intracontinental deformation,characterized by the development of the NE-trending West Junggar sinistral strike-slip fault system(WJFS)since Late Carboniferous and Early Permian,and the NW-trending Chingiz-Junggar dextral strike-slip fault(CJF)in Mesozoic and Cenozoic,has an important significance for the tectonic evolution of the WJOB and the CAOB.In this paper,we conduct geometric and kinematic analyses of the WJOB,based on field geological survey and structural interpretation of remote sensing image data.Using some piercing points such as truncated plutons and anticlines,an average magnitude of^73 km for the left-lateral strike-slip is calculated for the Darabut Fault,a major fault of the WJFS.Some partial of the displacement should be accommodated by strike-slip fault-related folds developed during the strike-slip faulting.Circular and curved faults,asymmetrical folds,and irregular contribution of ultramafic bodies,implies potential opposite vertical rotation of the Miao’ergou and the Akebasitao batholiths,resulted from the sinistral strike-slipping along the Darabut Fault.Due to conjugate shearing set of the sinistral WJFS and the dextral CJF since Early Mesozoic,superimposed folds formed with N–S convergence in southwestern part of the WJOB.  相似文献   
8.
Efficient forest fire management requires precise and up-to-date knowledge regarding the composition and spatial distribution of forest fuels at various spatial and temporal scales. Fuel-type maps are essential for effective fire prevention strategies planning, as well as the alleviation of the environmental impacts of potential wildfire events. The aim of this study was to assess and compare the potential of Disaster Monitoring Constellation and Landsat-8 OLI satellite images (Operational Land Imager), combined with Object-Based Image Analysis (GEOBIA), in operational mapping of the Mediterranean fuel types at a regional scale. The results showcase that although the images of both sensors can be used with GEOBIA analysis for the generation of accurate fuel-type maps, only the OLI images can be considered as applicable for regional mapping of the Mediterranean fuel types on an operational basis.  相似文献   
9.
Saliency detection is an effective approach to extract regions of interest (ROIs) for remote sensing images. However, existing saliency detection models mainly focus on ROI extraction from a single image and usually are not able to produce satisfactory results because of complex background interference in remote sensing images. The employment of mutual information in a set of remote sensing images can provide an effective solution to this issue. In this paper, we propose a novel saliency detection model for multiple remote sensing images to simultaneously extract ROIs and identify images without ROIs. First, common salient feature analysis based on synthesized feature clustering and global contrast is implemented to exploit global correspondence in the synthesis feature domain, thereby highlighting preliminary ROIs against background interference and assigning lower saliency values to images without ROIs. Then, we design an exclusion criterion based on saliency value judgment to remove images without ROIs, and the remaining saliency maps are refined by an enhancement strategy. Finally, the enhanced maps serve as a feedback to yield a homogenous synthesized feature space in which integral ROIs with subtle borders are extracted by the reused cluster-based saliency calculation. Experiments reveal that our model outperforms seven state-of-the-art models by achieving the best ROC curve (AUC = 0.945) and maximal F-measure at 0.729.  相似文献   
10.
随着遥感数据获取技术和能力的全面提高,遥感数据呈现出明显的大数据特征。发展适应于遥感大数据的智能分析和信息挖掘技术,成为当前遥感技术研究的前沿。高分二号(GF-2)卫星数据是我国首颗自主研发的亚米级高分辨率卫星数据,具有观测幅宽、重访周期短、高辐射精度、高定位精度等优势,为未来我国地质灾害的长期、动态地监测和研究提供了高精度、稳定可靠的数据源。本文选取安徽谢桥煤矿2015年1月8日的GF-2卫星影像为研究数据,在对煤矿区主要地质灾害遥感地学分析的基础上,采用面向对象的影像分析方法对研究区由采煤活动所诱发的地质灾害信息进行自动提取。结果表明:利用GF-2卫星数据能够有效地识别地质灾害体的位置、范围、形态等空间分布特征;面向对象的自动提取方法对于煤矿区大面积的积水塌陷盆地、小规模的塌陷坑和线性的地裂缝都有很高的提取精度,识别精度达90% 以上;基于逐层剔除的思路构建的提取规则,为GF-2数据在地质灾害调查和大数据分析中的应用提供了很好的技术支持,也为其它地物目标的提取提供了参考,但在特征的选择和阈值的设定上需要具体分析。  相似文献   
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