高植被覆盖区遥感找锰矿实验研究——以桂西—滇东南的下雷—大新地区为例

桂西—滇东南区域植被覆盖茂盛,高覆盖的植被遥感信息相对于地质遥感信息而言是一个很强的干扰。本文以桂西—滇东南的锰矿化信息较为丰富、植被覆盖度高的下雷—大新区域TM遥感影像为例,利用基于主成分变换的铁染遥感异常信息、羟基异常信息和泥岩碳酸岩异常遥感信息提取,以及基于SAM和实地地物光谱测量的基础上提取的氧化锰露头的遥感信息,研究结果与已知锰矿化信息的空间分布区域有较高的吻合度。研究结果表明,本文的研究方法对于遥感找锰矿的宏观靶区框选有较高的参考价值。     

广东梅县地区矿产远景遥感调查研究

利用遥感技术获取构造信息和异常信息,探讨了线环形构造和蚀变异常的遥感示矿模型,通过成矿关系分析提高找矿效果,为梅县地区矿产远景勘查提供了有利的科学依据。研究建立起植被高覆盖区遥感信息提取的一套有效的技术体系,在遥感地质找矿中具有一定的参考和应用价值。     

不同植被覆盖率地区遥感矿化蚀变提取研究

从遥感图像上识别出的围岩蚀变信息往往是一种弱信息。地表植被和第四系覆盖的干扰,增加了遥感蚀变信息提取的难度。为了研究不同植被覆盖条件下的矿化蚀变信息提取方法,分别选取内蒙古西部戈壁荒漠基岩裸露区（温根地区）、中北部中覆盖草原区（达来庙地区）和东北部高覆盖森林草原区（颇格鲁山地区）,利用TM数据进行遥感蚀变信息提取方法研究,得出以下结论：在基岩裸露地区,利用比值法、主成分分析法均能较好地提取出矿化蚀变信息;在中覆盖草原区,利用掩膜对图像进行预处理,再利用主成分分析法提取矿化信息效果比较好;在高覆盖森林草原区,利用掩膜技术和抑制植被信息方法对遥感数据进行综合处理,再利用比值-主成分分析方法能够提取部分矿化蚀变信息。这些方法对今后在类似地区开展遥感蚀变信息提取工作具有一定的指导意义。     

遥感蚀变信息提取应用研究

围岩蚀变是成矿作用发生的重要标志之一、从遥感图像中提取蚀变信息也成为一种重要手段、以波谱理论为基础，以遥感信息提取理论为依据，根据ETM 数据特征，选择多种遥感图像处理方法，对吉林省东部小西南岔铜金矿南山矿区(地表植被覆盖严重)、北山矿区(地表裸露)及其外围的金泉岗地区(地表植被覆盖严重)的遥感图像处理后进行彩色合成，对色调信息运用统计学原理进行评估，提取蚀变信息，经野外实地验证，取得较好的找矿效果。     

西南山区遥感蚀变异常信息提取综合研究——以云南酒房地区为例

遥感蚀变异常信息现已广泛的用于矿产勘查,并在一些地区取得了良好的效果,但由于西南地区地形地貌复杂,地表覆盖严重,给遥感蚀变异常提取带来了很大的困难。如何因地制宜的进行西南地区遥感蚀变异常信息提取工作是我们面临的重要问题。本文以云南酒房地区为例,探讨了西南地区遥感蚀变异常信息提取中遇到的主要问题,结合地形地貌特征进行干扰信息的去除;结合地质背景、成矿条件进行遥感异常信息提取类别的选择;以及结合化探异常进行异常信息后处理等几个方面完善了异常提取的方法,使得遥感蚀变异常提取方法更加具有针对性,通过与现有地质资料的分析,证明本文异常提取方法可以有效的提取西南地区与矿相关的蚀变信息。     

福建武夷山植被覆盖区遥感地质信息提取

植被覆盖区遥感地质信息提取一直是国内外遥感地质领域的研究重点之一。介绍了利用间接证据链,通过追溯植被冠层温度-气孔阻力-植物水势-根系实际吸水-土壤供水-土壤水分含量,最终以土壤水分含量异常与断裂构造表观特征建立联系。使用TVDI、PDI、MPDI、SPSI遥感土壤水分反演模型提取福建大小矾山地区植被覆盖下的断裂构造信息。     

重庆高燕锰矿植被覆盖区遥感矿化信息提取

遥感找矿在大多植被覆盖区效果并不明显。在重庆高燕锰矿区采用了Landsat 8多光谱遥感数据的植被覆盖区矿化信息提取方法,该方法与传统提取遥感矿化蚀变信息找矿的方法不同,通过提取植被覆盖相对较小的含矿层顶底板岩层的遥感异常,查明含矿层位置。该方法采用特定的膜技术剔除植被、水体、云雪等干扰,再利用比值法在高植被覆盖区提取有价值的遥感蚀变信息,然后将多个波段比的遥感异常进行假彩色合成,再将遥感异常与地质事实结合,最终解译出锰矿含矿层顶底板遥感异常特征,确定找矿线索。     

基于小波变换的遥感纹理信息提取

遥感纹理信息是地物空间特征的综合反映,综合纹理信息是进行专题信息提取获取的重要依据.遥感数据具有复杂性、统计性和随机性,同时,遥感图像中地学信息,如地质构造、蚀变信息及岩性分界等高频信息具有一定的方向性;小波变换具有"变焦性"、对称性、正则性等特点,可以较为快速地检测到奇变信号.利用小波变换可以快速、有效地提取遥感纹理高频奇变信息.     

现代遥感技术在地质找矿中的应用

文章论述了现代遥感技术在地质找矿中的应用,包括遥感岩性识别、矿化蚀变信息提取、地质构造信息提取和植被波谱特征的找矿应用等;总结了遥感地质找矿技术的若干新发展,即多光谱遥感蚀变信息提取技术、高光谱遥感技术、遥感生物地球化学技术,以及它们在地质找矿应用中的新发展;对遥感技术在地质找矿中的应用提出了几点认识及展望.     

蚀变矿物的遥感信息提取研究——以北山方山口为例

北山地区植被稀疏、地势平坦,而且基岩出露好,是遥感地质研究的理想区域。文章利用ASTER数据,采用主成分分析法对北山方山口地区的铁染与羟基蚀变矿物信息进行了提取研究。结果表明,提取结果中蚀变矿物的属性特征能够较好地与实际地质属性相符,且通过野外实地验证蚀变矿物信息发现了矿化点,即利用ASTER数据进行蚀变矿物信息提取可为北山地区矿产资源勘查提供有效的矿化指示遥感信息。     

吉林西部多时相遥感数据分类方案的构建及应用

为了深化遥感监测方法在生态环境调查中的应用,本文以吉林西部为试验区,设计了一种多时相遥感数据分类方案。该方案以物候信息为主,结合地物特征变量(植被、水体和土地信息)构建的多维特征空间数据集用于土地覆被分类。该遥感分类方案提取了9种地表覆被类型,结果表明:地表植被季节变化信息和土地利用信息的引入能明显改善土地覆被的分类精度;与基于原始波段的分类方案相比,多时相遥感数据分类方案的分类精度最好,总体分类精度为95.50%,Kappa系数为95.04%。     

基于Landsat 8的辽宁弓长岭区遥感蚀变信息提取

在详细解读辽宁弓长岭区Landsat 8影像数据的基础上,结合矿物光谱理论和弓长岭地区（地表植被覆盖严重）的基础地质资料,采用主成分分析法与比值法相结合的方式对该区2017-05和2017-08两个时段的Landsat 8多光谱遥感数据的蚀变异常信息进行了提取。结果表明：利用主成分分析法与比值法相互结合所形成的波段组合比单独运用主成分分析所提取的蚀变异常信息更加明显;此次研究中2017-05数据所提取出的羟基蚀变信息及2017-08数据所提取的铁染蚀变信息主要分布于弓长岭一矿区、二矿区、三矿区和独木-八盘岭矿区地表出露矿体的外围。这也说明将主成分分析法与比值法相结合对于植被覆盖严重区域的蚀变信息提取仍具有较好的效果。     

Dynamic analysis of eco-environmental changes based on remote sensing and geographic information system: an example in Longdong region of the Chinese Loess Plateau

The Chinese Loess Plateau is suffering from severe soil erosion. The eco-environmental changes of the plateau are believed to have an important influence on global eco-environmental sustainability; hence, this problem has attracted considerable attention from scientists around the world. This study has two purposes; application of remote sensing (RS) and geographic information system (GIS) techniques in the dynamic analysis of eco-environmental changes in the semiarid zone; and using the Longdong region of the Chinese Loess Plateau as an example, to make dynamic analysis of the eco-environmental changes of the region during the 1986–2004 period and identify controlling factors. Landsat Thematic Mapper (TM) data at a spatial resolution of 30 m were used for analysis. Two training areas were selected in Jingning and Qingcheng counties for analysis using 10-m resolution SPOT and Landsat TM data. The satellite RS images were obtained from the Institute of Remote Sensing Application (IRSA), Chinese Academy of Sciences (CAS). Each images was rectified by Albers Equal Area Conic projection based on 1:50,000 scale topographic maps after spectrum preparation of the images. To make the precision within 1 or 2 pixels, the accurate coordinative control points of the two systems were identified. Then the interpretation key was established based on the land use/cover survey in the study area. The images were classified into six primary environmental types (farmland, forest, grassland, water, construction area, and desert) and 25 sub-types using a visual image interactive interpretation method to obtain vector and attribute data. The resultant accuracy of the land use/cover classification reached 95%. Finally, the transformation areas and ratios of various eco-environmental types in the region were calculated to obtain the transition matrixes of eco-environmental types in the two training areas, Jingning and Qingcheng. This study demonstrates that satellite RS and GIS techniques are effective tools to monitor and analyze the eco-environmental changes in the semiarid region. Visual image interactive interpretation based on GIS technique provides comprehensive information on the direction, rate, and location of eco-environmental changes. The transition matrix model can be used to precisely analyze the variation and rates of the eco-environmental types and their spatial distribution. Great land use changes have taken place Longdong during the 1986–2004 period. These eco-environmental changes were driven by natural and human factors. Natural factors influencing the Longdong region of the Chinese Loess Plateau mainly include temperature, water condition, terrain, soil, and erosion; while human activities include over-cultivation, overgrazing, and fuelwood cutting. As viewed from the extent and severity of the influences, human activities play a very important role in altering the eco-environment of the semiarid region. The study results indicate a need for future research and observation in the semiarid region.     

Post-flood land use damage estimation using improved Normalized Difference Flood Index (NDFI<Subscript>3</Subscript>) on Landsat 8 datasets: December 2014 floods,Kelantan, Malaysia

Floods in Malaysia have been increasing in frequency and magnitude as reflected in the Kelantan Flood event in 2014 that resulted in a huge loss of lives and properties. Whereas remote sensing (RS) and geographical information system (GIS) tools have been extensively applied in flood disaster management, there are few reports and studies on the impact of floods on the land use/land cover environment in a post-disaster assessment. In this study, an integrated modelling approach was developed that used Landsat 8 OLI TIRS (Operational Land Imager (OLI) and Thermal Infrared Sensor) data, flood indexing and classification processes to estimate the impact of flood on the environment. The Normalized Difference Flood Index-3 (NDFI₃) is an improvement on NDFI₂ that takes into account the effects of cloud shadow in the images when extracting flood index areas. The flood model developed showed good agreement when compared with flooded areas shown in SAR (synthetic-aperture radar) image. The results of the flood extent as a proxy for damage estimation showed that the total flooded area was 502.34 km² for the Kelantan Flood event in 2014, with plantation and built-up area accounting for 43 and 34.6% respectively. The least affected land uses/land covers were deforested area and forest, which accounted for 12.2 and 10.2% respectively. The RS and GIS technique developed in this post-disaster damage assessment is effective, relatively inexpensive and simple to implement by local authorities in support of post-flood disaster planning and decision-making.     

Extraction and Analysis of Land Cover Heterogeneity over China

Spatial heterogeneity exists in land surface at every scale, and it is one of key factors to bring uncertainty to land parameter retrieval from remote-sensed data. This paper proposed a methodology to use the boundary length among different land cover types to characterize and quantify land surface heterogeneity based on high-resolution land cover images. Then the heterogeneity feature at 1 kilometer scale in China was extracted from “GlobalLand30” land cover datasets with the spatial resolution of 30 m. The mixed structure, degree of fragmentation and intra-heterogeneity of eight main vegetation biomes from MODIS land cover product over heterogeneous surface in china were analyzed. Mountain area and ecotone are more heterogeneous than other regions. Savanna biome (average boundary length is 7 426 meters) is the most heterogeneous zone followed by forest, grass/crop and shrub biome with average boundary length of 4 323, 3 160, 1 779 meters, respectively.     

多源遥感数据综合分析可地浸砂岩型铀矿成矿地质条件研究 ——以鄂尔多斯盆地杭锦旗研究区为例

可地浸砂岩型铀矿床上方异常信息微弱,直接寻找具有一定的困难,为了准确寻找可地浸砂岩型铀矿,笔者提出借助多源遥感图像所提取的岩性、构造、矿化蚀变等信息来提取可地浸砂岩型铀矿源相关信息,并以鄂尔多斯盆地杭锦旗地区为例,依据提取的信息,对其成矿地质构造环境和可地浸砂岩型成矿条件进行了详细分析和阐述,初步预测了研究区的铀成矿有利区域。     

Deep learning based classification of rock structure of tunnel face

The automated interpretation of rock structure can improve the efficiency,accuracy,and consistency of the geological risk assessment of tunnel face.Because of the high uncertainties in the geological images as a result of different regional rock types,as well as in-situ conditions(e.g.,temperature,humidity,and construction procedure),previous automated methods have limited performance in classification of rock structure of tunnel face during construction.This paper presents a framework for classifying multiple rock structures based on the geological images of tunnel face using convolutional neural networks(CNN),namely Inception-ResNet-V2(IRV2).A prototype recognition system is implemented to classify 5 types of rock structures including mosaic,granular,layered,block,and fragmentation structures.The proposed IRV2 network is trained by over 35,000 out of 42,400 images extracted from over 150 sections of tunnel faces and tested by the remaining 7400 images.Furthermore,different hyperparameters of the CNN model are introduced to optimize the most efficient algorithm parameter.Among all the discussed models,i.e.,ResNet-50,ResNet-101,and Inception-v4,Inception-ResNet-V2 exhibits the best performance in terms of various indicators,such as precision,recall,F-score,and testing time per image.Meanwhile,the model trained by a large database can obtain the object features more comprehensively,leading to higher accuracy.Compared with the original image classification method,the sub-image method is closer to the reality considering both the accuracy and the perspective of error divergence.The experimental results reveal that the proposed method is optimal and efficient for automated classification of rock structure using the geological images of the tunnel face.     

基于面向对象分类技术的沈阳市土地利用动态变化研究

基于RS和GIS技术,采用面向对象分类技术,根据沈阳市的实际情况,建立土地利用类型解译标志,利用多尺度分割方法进行影像分割,然后利用决策树法和最近邻的分类方法,建立分类规则,提取区域土地利用信息,得到该区域的两期土地利用/土地覆被数据,并对研究区的土地利用动态变化及引起这种变化的驱动力进行分析.研究中所采用的面向对象的分类方法在地表景观信息提取中充分利用了地物的光谱信息、纹理特征等特征,最大程度上克服由于不同地物光谱信息相似、相同地物光谱信息不同而造成的混分现象.     

基于遥感数据的全球及区域土地覆盖制图--现状、战略和趋势

土地利用／土地覆盖变化研究是近年来全球变化研究的焦点之一。全球和区域尺度的土地覆盖特征对全球环境状况的评估、模拟未来全球环境的情景有重要的作用。2000年在Internat ionalJournalofRemoteSensing杂志上出版了题为"GlobalandRegionalLandCoverCharacterizat ion from Remotely Sensed Data"的专辑。在此基础上,介绍、总结了国际上利用遥感影像进行全球和区域等大尺度土地覆盖研究的新进展。分别从数据源与制图的时空尺度、制图方法（数据预处理、分类、精度评估）等方面进行了介绍,并对现今的两个全球土地覆盖数据库进行了比较分析。