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1.
赵佳琪 《地质与勘探》2023,59(1):122-133
利用地物光谱仪识别具有光谱诊断性吸收特征的蚀变矿物,并分析其空间分布及组合特征,是后续利用航空、航天高光谱遥感开展找矿预测的重要理论依据。本文以位于甘肃柳园地区花牛山矿集区的花西山金矿床为例,首先利用FieldSpecPro FR便携式光谱仪对采集样品进行光谱测量,通过The Spectral Geologist 8软件对获得的光谱数据进行分析解译,揭示了与矿化关系密切的地表蚀变矿物为绢云母(白云母和多硅白云母)+黄钾铁矾+赤铁矿+针铁矿,外围蚀变矿物主要为绢云母(钠云母)+绿帘石+绿泥石+蒙脱石+水铝石。基于这一认识,对矿区及周边开展CASI/SASI航空高光谱遥感蚀变矿物信息提取,综合地表及航空高光谱解译信息,建立了花西山式金矿床的高光谱遥感找矿预测模型,并基于该找矿预测模型在外围圈定了预测区1处,经野外查证,预测区内发现有明显金异常。研究结果表明,在分析和总结调查区成矿地质背景和蚀变特征的基础上,结合高光谱遥感信息可快速地、更有针对性地发现成矿有利区段,为矿产勘查部署提供重要参考资料。  相似文献   
2.
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   
3.
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   
4.
Sentinel-2卫星落叶松林龄信息反演   总被引:1,自引:0,他引:1  
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   
5.
海洋叶绿素a质量浓度遥感产品是海洋初级生产力与海洋生态系统固碳能力研究的重要数据源,为了保证数据的可靠性,对遥感产品进行精度验证以及验证误差的成因分析尤为重要。遥感产品的验证过程中,由于空间变异的存在,使得遥感像元尺度内的实测数据具有不同的离散程度和统计分布特征,并由此产生了不同的误差统计结果。本文选择MODIS-Aqua、MODIS-Terra、MERIS、SeaWiFS等卫星传感器叶绿素a质量浓度遥感产品为研究对象,统计分析了数据产品的空间变异与验证精度的关系。结果表明:空间变异是造成验证误差的直接原因之一,平均绝对百分比误差(Mean Absolute Percentage Error:MAPE)与空间变异系数(Coefficient of Variation: CV)呈幂指数模型关系;当CV<0.05时,MAPECV的增加明显;当CV>0.15时,MAPE的变化趋于平缓。不同卫星传感器叶绿素a质量浓度产品验证结果表明,SeaWiFS精度最高,MERIS次之,MODIS-Terra精度最低。  相似文献   
6.
标志点等距映射(L-ISOMAP)作为一种降维方法,在高光谱图像可视化中极具潜力.针对L-ISOMAP算法标志点代表性不足以及计算代价较高的问题,提出了基于K-medoids聚类算法的改进型L-ISOMAP算法(KL-ISOMAP),进而形成可视化方法.该可视化方法由以下几部分组成:1)通过改进型K-medoids算法选择标志点;2)根据相似度剔除相似像元;3)实现剩余像元的非线性降维;4)完成降维结果的可视化.实验结果表明,KL-ISOMAP算法一方面有效地提高了标志点的内在结构代表性,进而取得了更好的可视化效果;另一方面可通过对相似阈值的设置,加快算法的运算速度.由此形成的可视化方法有着较好的视觉效果、距离保持特性以及像元可分性.  相似文献   
7.
Accurate atmospheric temperature and moisture information with high temporal/spatial resolutions are two of the key parameters needed in regional numerical weather prediction(NWP) models to reliably predict high-impact weather events such as local severe storms(LSSs). High spectral resolution or hyperspectral infrared(HIR) sounders from geostationary orbit(GEO) provide an unprecedented source of near time-continuous, three-dimensional information on the dynamic and thermodynamic atmospheric fields—an important benefit for nowcasting and NWP-based forecasting. In order to demonstrate the value of GEO HIR sounder radiances on LSS forecasts, a quick regional OSSE(Observing System Simulation Experiment)framework has been developed, including high-resolution nature run generation, synthetic observation simulation and validation, and impact study on LSS forecasts. Results show that, on top of the existing LEO(low earth orbit) sounders, a GEO HIR sounder may provide value-added impact [a reduction of 3.56% in normalized root-mean-square difference(RMSD)] on LSS forecasts due to large spatial coverage and high temporal resolution, even though the data are assimilated every 6 h with a thinning of 60 km. Additionally, more frequent assimilations and smaller thinning distances allow more observations to be assimilated, and may further increase the positive impact from a GEO HIR sounder. On the other hand, with denser and more frequent observations assimilated, it becomes more difficult to handle the spatial error correlation in observations and gravity waves due to the limitations of current assimilation and forecast systems(such as a static background error covariance). The peak reduction of 4.6% in normalized RMSD is found when observations are assimilated every 3 h with a thinning distance of 30 km.  相似文献   
8.
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
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   
9.
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  
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   
10.
The acquisition of spatial-temporal information of frozen soil is fundamental for the study of frozen soil dynamics and its feedback to climate change in cold regions. With advancement of remote sensing and better understanding of frozen soil dynamics, discrimination of freeze and thaw status of surface soil based on passive microwave remote sensing and numerical simulation of frozen soil processes under water and heat transfer principles provides valuable means for regional and global frozen soil dynamic monitoring and systematic spatial-temporal responses to global change. However, as an important data source of frozen soil processes, remotely sensed information has not yet been fully utilized in the numerical simulation of frozen soil processes. Although great progress has been made in remote sensing and frozen soil physics, yet few frozen soil research has been done on the application of remotely sensed information in association with the numerical model for frozen soil process studies. In the present study, a distributed numerical model for frozen soil dynamic studies based on coupled water-heat transferring theory in association with remotely sensed frozen soil datasets was developed. In order to reduce the uncertainty of the simulation, the remotely sensed frozen soil information was used to monitor and modify relevant parameters in the process of model simulation. The remotely sensed information and numerically simulated spatial-temporal frozen soil processes were validated by in-situ field observations in cold regions near the town of Naqu on the East-Central Tibetan Plateau. The results suggest that the overall accuracy of the algorithm for discriminating freeze and thaw status of surface soil based on passive microwave remote sensing was more than 95%. These results provided an accurate initial freeze and thaw status of surface soil for coupling and calibrating the numerical model of this study. The numerically simulated frozen soil processes demonstrated good performance of the distributed numerical model based on the coupled water-heat transferring theory. The relatively larger uncertainties of the numerical model were found in alternating periods between freezing and thawing of surface soil. The average accuracy increased by about 5% after integrating remotely sensed information on the surface soil. The simulation accuracy was significantly improved, especially in transition periods between freezing and thawing of the surface soil.  相似文献   
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