黔东松桃西溪堡南华系大塘坡组超大型锰矿床地质特征与找矿预测

贵州松桃西溪堡锰矿床是近年运用古天然气渗漏沉积型锰矿床成矿模式与找矿模型理论发现的又一个隐伏超大型锰矿床。矿体呈似层状、层状产出,厚度与延展规模巨大。通过对西溪堡锰矿区中两界河组、含锰岩系地层柱状对比研究和含锰岩系、菱锰矿体和大塘坡组的沉积厚度等值线研究,发现控制超大型锰矿形成和分布的西溪堡地堑盆地长轴方向为北东60°左右,而非北东30°左右的地层走向。西溪堡地堑盆地中心相、过渡相和边缘相等古天然气渗漏喷溢沉积微相特征清楚,存在2个渗漏喷溢沉积中心。西溪堡地堑盆地锰矿找矿潜力巨大,预测其锰矿资源总潜力应是目前已控制锰矿资源量的2倍,是一个新的世界级超大型锰矿床。      

Land-cover survey in northeast China using remote sensing and GIS

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基于遥感蚀变信息提取巴林格撞击坑周边铁陨石

目前地球上已经得到确认的撞击坑有190余个，其中直径小于1 km的简单撞击坑绝大部分是由铁质撞击体撞击形成的。由铁质撞击体撞击而成的撞击坑周边存在大量的铁陨石物质，这些铁陨石物质的空间分布特征对研究撞击坑的撞击过程和机理具有重要意义。铁元素的异常富集也可作为探寻地球表面疑似撞击坑的重要信息。为了获取撞击坑周围的铁陨石残片，早期主要通过人工方式进行实地调查，但这种方法效率低下且需要投入大量人力物力。基于铁陨石独特的光谱特征，利用遥感蚀变信息提取手段可以很方便地获取撞击坑周边的铁陨石物质。根据铁陨石矿物的波谱特征，以美国亚利桑那州巴林格撞击坑（Barringer Meteor Crater）为研究对象，基于Landsat 8 OLI数据，采用目前提取蚀变信息的常用方法:波段比值（BandMath）—主成分分析法进行撞击坑周边铁陨石信息的提取。提取结果与前人实地调查获取的铁陨石分布情况契合程度较好。撞击坑东侧、东南侧、西南侧等处的铁陨石聚集区在提取结果图上均有较好的反映。表明利用波段比值-主成分分析方法提取巴林格撞击坑周边铁陨石信息是可行的，实验结果准确地获得了该撞击坑周围的铁陨石空间分布信息，为探寻地球表面撞击成因的环形构造提供了可行方案，同时为未来同类撞击坑信息提取提供了重要的方法参考。      

Extraction of altered minerals from Aster remote sensing data in Gongchangling iron deposit of Liaoning,China

The precision of Aster data is higher than that of Landsat series of multispectral remote sensing data, which can more accurately reveal the distribution of altered minerals. It plays an important role in prospecting, but it is rarely used in areas with complex terrain and high vegetation coverage. Based on this purpose, this study used Aster remote sensing data, and took Gongchangling iron deposit as a case study. It combined the mineral spectrum theory and the basic geologic data of the study ...     

多源遥感影像数据融合方法在地学中的应用

应用遥感影像数据融合理论，研究了光学遥感、热红外遥感、微波遥感卫星在地质学中的应用，论述了不同类型的遥感数据及其他地学数据在不同层次上的同一传感器多波段数据融合、不同SAR图像数据融合、HIS变换、遥感影像与地球物理、地质和航磁等数据的融合。结果表明，数据融合技术在突出地质特征信息方面具有能突出线性构造、断裂构造、地形地貌的优势。     

Classification of vegetative types in Changbai Mountain based on optical and microwave remote sensing data

Highly accurate vegetative type distribution information is of great significance for forestry resource monitoring and management. In order to improve the classification accuracy of forest types, Sentinel-1 and 2 data of Changbai Mountain protection development zone were selected, and combined with DEM to construct a multi-featured random forest type classification model incorporating fusing intensity, texture, spectral, vegetation index and topography information and using random forest Gini in...     

Fusion and classification of Beijing-1 small satellite remote sensing image for land cover monitoring in mining area

In order to promote the application of Beijing-1 small satellite(BJ-1) remote sensing data,the multispectral and panchromatic images captured by BJ-1 were used for land cover classification in Pangzhuang Coal Mining.An improved Intensity-Hue-Saturation(IHS) fusion algorithm is proposed to fuse panchromatic and multispectral images,in which intensity component and panchromatic image are combined using the weights determined by edge pixels in the panchromatic image identified by grey absolute correlation degree.This improved IHS fusion algorithm outper-forms traditional IHS fusion method to a certain extent,evidenced by its ability in preserving spectral information and enhancing spatial details.Dempster-Shafer(D-S) evidence theory was adopted to combine the outputs of three member classifiers to generate the final classification map with higher accuracy than that by any individual classifier.Based on this study,we conclude that Beijing-1 small satellite remote sensing images are useful to monitor and analyze land cover change and ecological environment degradation in mining areas,and the proposed fusion algorithms at data and decision levels can integrate the advantages of multi-resolution images and multiple classifiers,improve the overall accuracy and produce a more reliable land cover map.     

Vegetation change of ecotone in west of Northeast China plain using time-series remote sensing data

Multi-temporal series of satellite SPOT-VEGETATION normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) data from 1998 to 2007 were used for analyzing vegetation change of the ecotone in the west of the Northeast China Plain. The yearly and monthly maximal values,anomalies and change rates of NDVI and NDWI were calculated to reveal the interannual and seasonal changes in vegetation cover and vegetation water content. Linear regression method was adopted to characterize the trends in vegetation change. The yearly maximal NDVI decreased from 0.41 in 1998 to 0.37 in 2007,implying the decreasing trend of vegetation activity. There was a significant decrease of maximal NDVI in spring and summer over the study period,while an increase trend was observed in autumn. The vegetation-improved regions and vegetation-degraded regions occupied 17.03% and 20.30% of the study area,respectively. The maximal NDWI over growing season dropped by 0.027 in 1998–2007,and about 15.15% of the study area showed a decreasing trend of water content. Vegetation water stress in autumn was better than that in spring. Vegetation cover and water content variations were sensitive to annual precipitation,autumn precipitation and summer temperature. The vegetation degradation trend in this ecotone might be induced by the warm-drying climate especially continuous spring and summer drought in the recent ten years.     

Geometrical feature analysis and disaster assessment of the Xinmo landslide based on remote sensing data

At 5:39 am on June 24, 2017, a landslide occurred in the village of Xinmo in Maoxian County, Aba Tibet and Qiang Autonomous Prefecture(Sichuan Province, Southwest China). On June 25, aerial images were acquired from an unmanned aerial vehicle(UAV), and a digital elevation model(DEM) was processed. Landslide geometrical features were then analyzed. These are the front and rear edge elevation, accumulation area and horizontal sliding distance. Then, the volume and the spatial distribution of the thickness of the deposit were calculated from the difference between the DEM available before the landslide, and the UAV-derived DEM collected after the landslide. Also, the disaster was assessed using high-resolution satellite images acquired before the landslide. These include Quick Bird, Pleiades-1 and GF-2 images with spatial resolutions of 0.65 m, 0.70 m, and 0.80 m, respectively, and the aerial images acquired from the UAV after the landslide with a spatial resolution of 0.1 m. According to the analysis, the area of the landslide was 1.62 km2, and the volume of the landslide was 7.70 ± 1.46 million m3. The average thickness of the landslide accumulation was approximately 8 m. The landslide destroyed a total of 103 buildings. The area of destroyed farmlands was 2.53 ha, and the orchard area was reduced by 28.67 ha. A 2-km section of Songpinggou River was blocked and a 2.1-km section of township road No. 104 was buried. Constrained by the terrain conditions, densely populated and more economically developed areas in the upper reaches of the Minjiang River basin are mainly located in the bottom of the valleys. This is a dangerous area regarding landslide, debris flow and flash flood events Therefore, in mountainous, high-risk disaster areas, it is important to carefully select residential sites to avoid a large number of casualties.     

Comparison of remote sensing data with in-situ wind observation during the development of the South China Sea monsoon

Wind measurements derived from QuikSCAT data were compared with those measured by anemometer on Yongxing Island in the South China Sea (SCS) for the period from April 2008 to November 2009. The comparison confirms that QuikSCAT estimates of wind speed and direction are generally accurate, except for the extremes of high wind speeds (>13.8m/s) and very low wind speeds (<1.5m/s) where direction is poorly predicted. In-situ observations show that the summer monsoon in the northern SCS starts between May 6 and June 1. From March 13, 2010 to August 31, 2010, comparisons of sea surface temperature (SST) and rainfall from AMSR-E with data from a buoy located at Xisha Islands, as well as wind measurements derived from ASCAT and observations from an automatic weather station show that QuikSCAT, ASCAT and AMSR-E data are good enough for research. It is feasible to optimize the usage of remote-sensing data if validated with in-situ measurements. Remarkable changes were observed in wind, barometric pressure, humidity, outgoing longwave radiation (OLR), air temperature, rainfall and SST during the monsoon onset. The eastward shift of western Pacific subtropical high and the southward movement of continental cold front preceded the monsoon onset in SCS. The starting dates of SCS summer monsoon indicated that the southwest monsoon starts in the Indochinese Peninsula and forms an eastward zonal belt, and then the belt bifurcates in the SCS, with one part moving northeastward into the tropical western North Pacific, and another southward into western Kalimantan. This largely determined the pattern of the SCS summer monsoon. Wavelet analysis of zonal wind and OLR at Xisha showed that intra-seasonal variability played an important role in the summer. This work improves the accuracy of the amplitude of intra-seasonal and synoptic variation obtained from remote-sensed data.     

GF-2遥感数据在盖孜河流域典型第四纪地层调查中的应用

国产高分辨率卫星遥感技术的发展为第四系宏观、局部及细部特征调查提供了新的手段。中巴经济走廊东段地区分布较多的冲洪积扇、河谷阶地、冰川堆积等地貌类型,为了研究国产高分数据在该地区第四纪地质调查中的适用性,以高分二号（GF-2）影像为主要数据源,借助数字高程模型构建三维场景,选取中巴公路沿线盖孜河流域乌鲁阿特山前冲洪积扇、盖孜河河谷阶地与克拉牙依拉克冰川堆积物3处典型第四纪地层为研究对象,建立了遥感解译标志,并进行了精细尺度遥感解译;经过野外实地验证,查明了其物质组成与变化规律,修正了前人关于克拉牙依拉克冰川不同期次冰碛物的划分范围;通过对盖孜河河谷阶地分析,盖孜河流域晚更新世以来经历了至少5次阶段性构造抬升,阶地基座冰碛物至少由两期冰川作用形成。研究表明,GF-2影像能快速从宏观尺度上识别地貌、松散堆积物变化特征,能够看到常规方法无法观察到的地质现象;满足大比例尺解译、制图要求,特别是在微地貌识别以及第四纪地层解译中,能够提升精细地质解译水平。研究成果能为盖孜河流域河流、冰川的发展演化过程研究提供基础地质资料,为中巴公路沿线第四纪土体遥感调查提供典型案例。