APPlication of SPace Remote Sensing to ExPloration for the Carlin一tyPe Gold DePosites in QianGui Area

研究了黔桂地区卡林型金矿的宕矿石光谱特征，TM波段比值与岩矿石化学成分的相关性，并在此基础上进行了图像处理，提取与金矿化有关的性变信息，取得了满意的结果。     

航天遥感在卡林型金矿探测中的应用─—以黔桂地区为例

研究了黔桂地区卡林型金矿的岩矿石光谱特征，ＴＭ波段比值与岩矿石化学成分的相关性，并在此基础上进行了图像处理，提取与金矿化有关的蚀变信息，取得了满意的结果。     

一种基于波段组合的遥感图像彩色合成新方法

研究了面向土地沙化的基于波段组合的遥感图像彩色合成问题。通过计算陆地卫星TM(Thematicmapper,TM)数据波段间的协方差、相关系数矩阵和主要统计特征参量,获取TM波段组合的基础数据;然后采用信息量分析法确定土地沙化研究的优劣波段,通过波段间的相关性分析筛选适合于土地沙化分析的波段集,基于该波段集,采用最佳指数法给出优化波段组合,在优化波段组合与彩色图像合成基础上进行遥感图像预处理。以河北省沽源县的TM数据为例,对河北省沽源县TM各波段及监督分类中沙化样本各波段信息进行了处理,结果表明TM4、7、1为该区域土地沙化研究的最佳波段组合。     

中高分辨率遥感数据铁染信息提取及找矿预测

苍山地区铁矿资源丰富,但地表覆盖较重,在区域范围内常规方法提取蚀变信息效果差。针对此问题,结合使用ASTER与GF-1卫星影像数据,从分析典型矿物光谱吸收特性出发,综合影像色彩、波段特征等多种信息采用了"主成分分析+波段比值+假彩色合成"和"主成分分析+密度分割"2种蚀变信息提取模型。方法主要运用了主成分分析思想去除冗余数据,前者辅助波段比值及彩色合成技术突出铁染信息,后者以选取最佳阈值的方式对高分辨率数据进行密度分割,优化了提取效果。2种方法结合有效提取了铁染蚀变信息,综合提取结果与区域控矿断裂特征,圈定了4处成矿靶区。对研究区进行实地采样验证,Kappa系数分别为0.826和0.87,精度较高。该方法的实现为同类地区的找矿工作提供了有利依据。     

The APPlication of Band Ratio ComPosite And Feature一oriented PrinciPal ComPonent Seleetion in the Extraction of Oil一gas Signature

根据烃类徽渗漏性变物质的波谱特性，在TM影像上研究了三种计算机提取油气信息的方法:(1)比值合成法;(2)六波段特征主成分选择~IHS逆变换~彩色合成;(3)四波段特征主成分选择~IHS逆变换~彩色合成。利用这些方法有效地提取了油气信息，取得了较好的实际效果。     

RapidEye卫星影像质量分析与彩色合成方案研究

RapidEye卫星是由德国负责运行的5颗卫星群,具有覆盖范围大、重访率高、分辨率适中以及丰富的多光谱信息等特点。本文对该卫星影像的数据质量进行了分析和评价,同时对其多光谱数据模拟真彩色的彩色合成方案进行了研究,提出了红波段、新绿波段和蓝波段组合的最佳合成方案。     

用混合像元线性模型提取中等植被覆盖区的粘土蚀变信息

基于混合像元线性分解模型,针对中等植被覆盖区提出了一种提取粘土蚀变信息的新方法。主要分3步实现:用混合像元线性分解模型提取植被覆盖丰度;对线性模型进行完善,并依此重构不含有植被信息的新的多波段图像;利用TM5/TM7增强粘土蚀变信息。经验证,提取的植被信息以及粘土类蚀变信息与实际吻合较好,与基于比值-主成分分析的方法相比有明显的优越性。
     

利用ASTER数据评价ETM+遥感数据自身融合效果

ETM+自身融合后的遥感影像折中了全色波段的高空间分辨率和多光谱波段的光谱分辨能力。通过同一季相和同一地区的ASTER影像和ETM+自身融合后影像的极限放大进行对比分析,发现ETM+自身融合后的彩色合成影像的空间分辨力达不到15 m,但能保证到17.3 m;通过ASTER影像和ETM+融合后影像的NDVI植被指数的对比分析,发现ETM+自身融合后的彩色合成影像的综合光谱分辨能力仍能保持ETM+彩色合成影像的73%以上。ETM+自身融合效果的好坏与融合算法优劣也具有一定的关系。     

黔桂地区微细浸染型金矿蚀变信息提取机理

本文围绕与微细浸染型金矿有关的硅化，褐铁矿化，粘土矿化，碳酸盐化等蚀为标志，在黔桂地区进行了相关的地球化学和光谱信息研究。通过对岩矿的光谱特征，地球化学因子，ＴＭ波段比值因子与地球化学因子的相关性等研究，探索从室内光谱数据中提取与金矿化密切相关的蚀变信息，并以此为依据做图象处理，取得了满意的结果。     

马尾藻遥感信息提取

以Landsat数据为基础,分析马尾藻的图像和波谱特征,对比分析单波段提取法、双波段比值法、双波段差值法和归一化植被指数法对马尾藻信息的提取结果,并利用IKONOS数据来验证4种方法的提取精度.结果表明:马尾藻在Landsat真彩色(TM3、TM2、TM1)和假彩色(TM4、TM3、TM1)合成图上均呈黄色,其生长边界在假彩色合成图上更为清晰.马尾藻水体与非藻类水体在TM4的差异最大,在TM3也存在细小差异,单波段提取法(TM4)、双波段比值法(TM4/TM3)、双波段差值法(TM4-TM3)和归一化植被指数法((TM4-TM3)/(TM4+TM3))都可以从自然水体中提取出马尾藻信息,与IKONOS的提取结果相比,归一化植被指数法的提取精度最高.     

Factor analysis approach for composited ASTER band ratios and wavelet transform pixel-level image fusion: lithological mapping of the Neoproterozoic Wadi Kid area,Sinai, Egypt

In this study, we have adopted an approach for objective optimization of the selection of band ratios in forming Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) band ratio composites, based on factor analysis loadings and specific variances. The factor loadings and specific variances of all 72 possible spectral band ratios of the visible and near infrared (VNIR) and the short-wave infrared (SWIR) of ASTER data from Wadi Kid, southeastern Sinai Peninsula, Egypt, were utilized to construct two separate rankings of band ratios in an ascending manner in order to determine the best ASTER band ratio combinations for lithological mapping in the study area. Two ASTER band ratio composites ((band 6/band 3–band 1/band 3–band 9/band 5) and (8/6–8/7–4/7) in blue–green–red (BGR)) were built, based on the rankings of factor loadings and specific variances, respectively. These two composites were fused together based on a discrete wavelet transform (DWT) decomposition, which enables decomposition of an image into (high-pass) details and (low-pass) approximations at various levels of resolution, resulting in improved lithological discrimination of granitic and meta-sediments rock units and a reduction in the BGR imprints of topographic reliefs.     

Assessment of image processing techniques and ASTER SWIR data for the delineation of evaporates and carbonate outcrops along the Salt Lake Fault,Turkey

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) multispectral sensor allows a variety of minerals to be diagnosed with the availability of six shortwave infrared (SWIR) bands. The study area located in a semi-arid region in central Turkey was flanked by the Salt Lake Fault in the west. ASTER SWIR bands and the adopted image processing techniques such as decorrelation stretch, band ratio, and feature-oriented principle component selection (FPCS) were applied for mapping both gypsum and carbonate rocks in the study area. Initially, the application of the decorrelation stretch method with a novel band combination successfully delineated the gypsum and carbonate outcrops. In addition to that, the principle component 4 (PC4) image obtained from the FPCS technique applied to a new band selection of ASTER data distinguished explicitly the carbonate outcrops. The resultant images, consistent with the geologic map of the study area, were compared with another and demonstrated that the gypsum and carbonate rocks were clearly identifiable. In addition to that, quantitative analyses of parallelepiped supervised classification images, band 9/band 8 ratio, and PC4 images in particular, yielded very compatible results.     

Detection of sandy soil surfaces using ASTER‐derived reflectance,emissivity and elevation data: potential for the identification of land degradation

Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) reflectance and emissivity data were used to discriminate nonphotosynthetic vegetation (NPV) from exposed soils, to produce a topsoil texture image, and to relate sand fraction estimates with elevation data in an agricultural area of central Brazil. The results show that the combination of the shortwave infrared (SWIR) bands 5 and 6 (hydroxyl absorption band) and thermal infrared (TIR) bands 10 and 14 (quartz reststrahlen feature) discriminated dark red clayey soils and bright sandy soils from NPV (crop litter), respectively. The ratio of the bands 10 and 14 was correlated with laboratory measured total sand fraction. When applied to the image and associated with topography, a predominance of sandy soil surfaces at lower elevations and clayey soil surfaces at higher elevations was observed. Areas presenting the largest sand fraction values, identified from ASTER band 10/14 emissivity ratio, were coincident with land degradation processes.     

Study on Extraction Method of Abandoned Farmland based on the Seasonal Variation Characteristics of Remotely Sensed Images

In southwestern China, the cultivation conditions are poor, the plots are relatively fragmented, and the types of plots are complex. Therefore, the use of low and medium resolution remote sensing data is not able to satisfy the needs of abandoned farmland extraction. This paper explored the ability of single or multi-phased high resolution remotely sensed images in detecting abandoned farmland in southwest China, using Xiuwen County, Guizhou Province, China as a case study area. Remote sensing based monitoring methods for abandoned farmland were developed, providing a reference for the statistical survey of abandoned farmland in southwest China.The extraction method of abandoned farmland was proposed based on the field survey data, considering different types of abandoned farmland. Sensitive feature sets of different types of abandoned farmland were identified from a series of features including the spectral characteristics, vegetation indices and multi-temporal difference vegetation indices. The CART decision tree classification method was applied on the selected sensitive features to extract abandoned farmland. The results showed that:(1) There was a significant difference in the recognition ability of single-phase image in extracting different types of abandoned farmland, so it was difficult to use only single-phase image to extract abandoned farmland with high accuracy; (2) The vegetation index change characteristics of different time phases had strong recognition ability for abandoned farmland, and the ratio vegetation index was better than the difference vegetation index and normalized vegetation index; (3) The spatial distribution map of abandoned farmland and the statistical analysis of abandoned farmland area were carried out in Xiuwen County, Guizhou Province. The area of abandoned farmland in Xiuwen County was about 6,460 hectares, accounting for 13% of the cultivated land area.（4）Based on multi-temporal high-resolution remote sensing data, the method of detecting abandoned farmland using seasonal variation characteristics can meet the requirements of high-precision extraction of abandoned farmland in southwest China, and the results provided technical reference for remote sensing survey and mapping of abandoned farmland in large-scale.     

基于季相变化特征的撂荒地遥感提取方法研究

在我国西南地区耕种条件差,地块比较破碎,地块类型比较复杂,中低分辨率遥感数据难以满足撂荒地提取的需要。选取贵州修文县为试验区,基于高分辨率卫星遥感数据（哨兵2号）,探索单期或多期影像在中国西南地区的撂荒地检测能力,构建撂荒地遥感监测方法,为今后我国西南地区撂荒地统计调查提供参考。结合野外调查数据,在划分不同撂荒地类型基础上,综合遥感影像的光谱特征、植被指数特征以及多时相植被指数变化特征分析,优选不同类别撂荒地遥感提取敏感特征集,利用CART决策树分类方法,提取不同类型的撂荒地。结果表明：①单个时相对不同类型的撂荒地识别能力差异显著,基于单时相影像,难以开展撂荒地高精度遥感监测提取;②不同时相的植被指数变化特征对撂荒地的识别能力较强,其中比值植被指数优于差值植被指数和归一化植被指数;③以贵州修文县为例,开展了撂荒地空间分布制图及撂荒面积统计分析,修文县撂荒地面积约为6 460 hm²,占修文县耕地面积的13%;④基于多时相高分辨遥感数据,通过季相变化特征构建的撂荒地检测方法,能够满足我国西南地区撂荒地高精度遥感监测提取,为大范围撂荒地遥感调查和制图提供技术参考。     

甘肃北山辉铜山地区镁铁岩体遥感识别方法研究

ASTER(先进星载热发射和反射辐射仪)已被广泛应用于岩性识别研究中,但在国内综合采用多种方法增强并识别镁铁-超镁铁岩体信息的研究较少。以甘肃北山辉铜山地区为研究区,综合应用比值法、最小噪声分离和镁铁岩指数等方法处理研究区ASTER数据,以突出辉铜山地区镁铁-超镁铁岩信息。将处理结果与地质图对比、综合分析,圈定了11处疑似辉长岩体,对其中9处进行野外验证,全部与遥感分析结果吻合,证明了结果的有效性。该方法可以应用于西部地区镁铁-超镁铁岩体识别工作中。     

Regional scale prospecting for non-sulphide zinc deposits using ASTER data and different spectral processing methods

ABSTRACT

The Ravar-Kuhbanan-Bahabad belt (RKBB) in Central Iran contains several carbonate-hosted non-sulphide Zn (zinc)-Pb (lead) deposits. The Gujer Zn mine area located in the middle of the RKBB was selected as the case study. Due to its large extent, dolomitic envelope in carbonate host rocks can be considered as a more appropriate exploratory target than small Zn-rich gossans or blind karst filling ore. Based on previous studies, the occurrence of red sandstone as a candidate of supplying metal for mineralization and evaporate as sulphate source for mineralized liquids in the vicinity of carbonate rocks can be important exploratory key in the RKBB. Non-sulphide Zn deposits were formed through oxidation of primary Mississippi Valley-type (MVT) deposits in the study area. Remote sensing studies were undertaken using visible to near-infrared (VNIR) and shortwave infrared (SWIR) bands of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) with the objective of lithological mapping. Five traverse lines containing a total of 81 samples were designed and followed with subsequent chemical analysis, thin section studies, and spectroscopy to verify the results. Two types of carbonates, namely, magnesian dolomite as host rock and surrounding calcitic limestone, were realized through using magnesium oxide (MgO) to calcium oxide (CaO) ratio. Based on spectroscopy studies, calcite and dolomite showed distinct absorption features at 2.35 µm and 2.32 µm, respectively, in ASTER band 8 while a shoulder at 2.25 µm was seen in ASTER band 7 for dolomite. Three image processing methods including spectral angle mapper (SAM), linear spectral unmixing (LSU), and mixture-tuned matched-filtering (MTMF) were applied to separate dolomite and limestone. The accuracy of image classification was numerically estimated using a confusion matrix. Limestone with the accuracy of 95.83% was more precisely enhanced using MTMF method compared to SAM and LSU methods. Highest accuracy of 75% for dolomite was obtained through using LSU method. Red sandstone and evaporate units were classified using MTMF and SAM/LSU methods, respectively. Rock units with the highest accuracy were selected and simply overlain on an image of ASTER in a GIS platform to create the potential map of the study area. Results showed that ASTER data can be successfully used to prepare a potential map for regional scale prospecting for carbonate-hosted non-sulphide Zn-Pb deposits in geological setting and climate condition similar to the RKBB.     

Lithological discrimination of the Phenaimata felsic–mafic complex,Gujarat, India,using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)

This study deals with an evaluation of the efficacy of an Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) image for lithological mapping. ASTER level-1B data in the visible near-infrared (VNIR), short wave infrared (SWIR) and thermal infrared (TIR) regions have been processed to generate a lithological map of the study area in and around the Phenaimata igneous complex, in mainland Gujarat, India. ASTER band combinations, band ratio images and spectral angle mapper (SAM) processing techniques were evaluated for mapping various lithologies. The reflectance and emissivity spectra of rock samples collected from the study area were obtained in the laboratory and were used as reference spectra for ASTER image analysis. The original data in the scaled digital number (DN) values were converted to radiance and then to relative reflectance by using a scene-derived correction technique prior to SAM classification. The SAM classification in the VNIR–SWIR region is found to be effective in differentiating felsic and mafic lithologies. The relative band depth (RBD) images were generated from the continuum-removed images of ASTER VNIR–SWIR bands. Four RBD combinations (3, 5, 6 and 8) were used to identify Al-OH (aluminium hydroxide), Fe-OH (iron hydroxide), Mg-OH (magnesium hydroxide) and CO₃ (carbonate) absorption from various lithological components. ASTER TIR spectral emittance data and the laboratory emissivity measurements show the presence of a number of discrete Si-O spectral features that can differentiate mafic and felsic rock types reflecting the lithological diversity around the regions of Phenaimata igneous complex. SAM classification using emittance data failed to distinguish the felsic and mafic lithology due to the wider spectral bandwidth. The felsic class comprises the granitoid composition of rocks. RBD12 and 13 images in the TIR region were used to derive the mafic index (MI) and the silica index (SI). The MI shows the highest value in regions of gabbro–basalt occurrence, while the SI indicates regions of high silica content. The MI is lowest in regions where granophyres occur. The complimentary attributes based on the spectral reflectance and emittance data resulted in the discrimination of silica-rich and silica-poor lithologies.     

BERS-CCD数据土地利用/覆盖信息 提取最佳波段选择——以贵州喀斯特山区为例

最佳波段选择是遥感数据处理重要基础工作,不仅影响遥感信息提取目视解译效果,而且影响计算机分类精度和效率。以贵州喀斯特山区CBERS-CCD数据土地利用/覆盖信息提取为例,依据最佳指数（OIF）模型,基于波段间信息量和地物间可分性试验,从定性和定量角度评价试验结果,得出:① CBERS-CCD数据所有可能3个波段组合中,B3-4-1波段组合RGB合成假彩色影像最适宜多数土地利用/覆盖类型信息提取;② CBERS-CCD数据第5波段对水田和草地等地类信息提取有重要贡献,应予充分利用;③ 不同波段组合对不同地类信息提取贡献有别,仅仅依靠某个波段组合即便是最佳波段组合也难以获得很高精度,需要继续研究CBERS-CCD数据与其它数据融合,以及决策树与多特征提取等多种遥感信息提取方法。