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高光谱遥感以其超高的光谱维数据优势,使对地物的精细识别和区分能力较传统多光谱遥感数据有质的提升。以HyM ap高光谱数据和高分五号高光谱数据为数据源,选择中国西部基岩区区域开展了高光谱遥感岩性-构造解译工作。通过图像增强处理后,对研究区地层单元、岩体/脉、构造等进行了遥感地质解译。对比已有的地质调查结果,发现高光谱遥感数据相较多光谱/高分数据对岩性-构造信息的展布情况显示得更加清晰和直观,同时其对不同岩性段、不同岩相带,以及细小构造等区分能力突出,表现出明显的技术优势。研究认为,高光谱遥感可为基岩区区域地质填图提供更加客观、真实的地质体、构造展布情况,能提高地质调查填图的效率和质量。 相似文献
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在哈密黄山铜镍矿区,采用PIMA(便携式短波红外矿物分析仪)进行野外光谱测试,用新引进的TSG(光谱地质专家)软件进行了矿物种类及相对含量识别、光谱处理分析,为蚀变矿物光谱分析起到了示范作用。详细论述了几类典型蚀变矿物的光谱特征;对绿泥石特征光谱吸收强度D(Fe-OH)、D(Mg-OH)与矿物成分的关系进行了探讨。结果表明,绿泥石Fe-OH和Mg-OH吸收强度比值可以大体上代替Fe2+/Mg2+比值,D[Mg-OH)/(Fe-OH)+(Mg-OH)]值绝大部分在0.4~0.8之间。用HyMap数据做地质信息半定量反演,准确反映了各岩相主要金属元素含量的变化。研究结果对高光谱技术识别矿物种类、反演岩矿成分具有重要意义。 相似文献
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成像光谱矿物识别和填图技术是中国国土资源调查和监测重点发展的高新技术之一。笔者以国土资源调查应用为主要目标,研究了成像光谱矿物识别和矿物填图技术实用化中的一些关键技术问题。分析了白云母和绿泥石两种重要蚀变矿物的光谱特征及光谱变异特征;以新疆东天山黄山地区的HyMap数据为例,对目前已较为系统化的成像光谱识别技术(如MNF变换、像元纯度指数PPI和N维可视化端元识别NDVI)在典型蚀变矿物识别和填图中的应用进行介绍。 相似文献
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面向地质应用的天宫一号成像光谱数据评价 总被引：1，自引：1，他引：0
天宫一号高光谱数据是继美国Hyperion之后,另一种可应用于地质领域的成像光谱数据.面向地质应用特点与需求,针对反射率产品开展全面、定量的数据质量评价对于深化应用研究具有重要意义.但是,由于航天成像光谱数据与地面实测波谱空间尺度差异甚大,在荒漠戈壁区选取自然地物进行波谱测试,并对其开展评价,特别是定量评价,非常困难.本文以航空HyMap数据为传递,完成了天宫一号成像光谱数据质量的定量评价.结果表明,在矿物识别采用的主要短波红外谱段,天宫一号高光谱数据的信噪比明显优于Hyperion数据.采用2190—2230 nm、2310—2355 nm两个谱段的吸收深度初步对天宫一号高光谱短波红外数据真实性进行了评价,经过校正后,天宫一号数据Al-OH、Mg-OH/CO32-矿物大类或组合的漏提率从71%、67%减小至29%、28%,可有效提高弱信息的检出率. 相似文献
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Estimation of green grass/herb biomass from airborne hyperspectral imagery using spectral indices and partial least squares regression 总被引：7，自引：0，他引：7
Moses Azong Cho Andrew Skidmore Fabio Corsi Sipke E. van Wieren Istiak Sobhan 《International Journal of Applied Earth Observation and Geoinformation》2007,9(4):414-424
The main objective was to determine whether partial least squares (PLS) regression improves grass/herb biomass estimation when compared with hyperspectral indices, that is normalised difference vegetation index (NDVI) and red-edge position (REP). To achieve this objective, fresh green grass/herb biomass and airborne images (HyMap) were collected in the Majella National Park, Italy in the summer of 2005. The predictive performances of hyperspectral indices and PLS regression models were then determined and compared using calibration (n = 30) and test (n = 12) data sets. The regression model derived from NDVI computed from bands at 740 and 771 nm produced a lower standard error of prediction (SEP = 264 g m−2) on the test data compared with the standard NDVI involving bands at 665 and 801 nm (SEP = 331 g m−2), but comparable results with REPs determined by various methods (SEP = 261 to 295 g m−2). PLS regression models based on original, derivative and continuum-removed spectra produced lower prediction errors (SEP = 149 to 256 g m−2) compared with NDVI and REP models. The lowest prediction error (SEP = 149 g m−2, 19% of mean) was obtained with PLS regression involving continuum-removed bands. In conclusion, PLS regression based on airborne hyperspectral imagery provides a better alternative to univariate regression involving hyperspectral indices for grass/herb biomass estimation in the Majella National Park. 相似文献
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以Sacramento-San Joaquin三角洲水域为研究区,利用2007年覆盖研究区的64个航带的HyMap数据,分别用混合调谐匹配滤波(MTMF)和决策树进行藻类信息的分类提取,在此基础上均采用Kappa系数作为标准进行精度评价。结果表明:混合调谐匹配波(MTMF)分析方法对藻类进行分类的结果,Kappa系数是0.634;用基于指数的决策树方法对藻类进行分类的结果,Kappa系数是0.613,两种结果都具有高度的一致性。这说明这两种方法在提取水生物种方面比价有效。 相似文献
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以西班牙Barrax地区的HyMap数据为例,利用K-L变换、波段指数、分段K-L变换、小波变换和可分性准则等常见的特征选择和提取方法,进行了特征提取和特征选择;然后,基于常用的监督分类法,通过各自的分类精度对各特征提取和特征选择法进行了比较和分析。实验结果表明使用可分性准则进行的特征选择时,基于波段指数、离散度平均值的分类精度相对较高;基于变换的特征选择中,K-L变换、分段K-L变换和小波变换的分类精度较高,三者基本上一致。而在监督分类方法的比较分析上,平行六面体法相对较差,最小距离法分类精度则相对较高,而最大似然法则比较稳定。 相似文献
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P.R.C. Fearns W. KlonowskiR.C. Babcock P. EnglandJ. Phillips 《Continental Shelf Research》2011,31(12):1249-1259
During April 2004 the airborne hyperspectral sensor, HyMap, collected data over a shallow coastal region of Western Australia. These data were processed by inversion of a semi-analytical shallow water optical model to classify the substrate. Inputs to the optical model include water column constituent specific inherent optical properties (SIOPs), view and illumination geometry, surface condition (based on wind speed) and normalised reflectance spectra of substrate types. A sub-scene of the HyMap data covering approximately 4 km2 was processed such that each 3×3 m2 pixel was classed as sand, seagrass, brown algae or various mixtures of these three components. Coincident video data were collected and used to estimate substrate types. We present comparisons of the habitat classifications determined by these two methods and show that the percentage validation of the remotely sensed habitat map may be optimised by selection of appropriate optical model parameters. The optical model was able to retrieve classes for approximately 80% of all pixels in the scene, with validation percentages of approximately 50% for sand and seagrass classification, and 90% for brown algae classification. The semi-analytical model inversion approach to classification can be expected to be applied to any shallow water region where substrate reflectance spectra and SIOPs are known or can be inferred. 相似文献
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AbstractSulphide mine waste extensively contaminates the Odiel River (southwest Spain), releasing sulphuric acid into the water body. Acidic water in this river precipitates and dissolves variably hydrated iron sulphate in a complex geological pattern controlled by climate. Local abrupt changes in the water pH in the vicinity of highly contaminated tributaries can be mapped by means of imaging spectroscopy using hyperspectral remote sensing (HyMap) data. Also, increased pH through mixing of acidic river water with marine water can be detected when the river reaches the area influenced by sea tides. Mapping the quality of water with hyperspectral data is confounded by vegetation, either dry or wet, rooted or floating. The spectral features of acidic water measured with a field spectrometer revealed the spectral influence of green vegetation, similar to the influence of the depth and transparency of water. Careful mapping of such parameters with HyMap data must therefore precede any spectral evaluation of water related to acidity in a river course. The spectral features detectable by HyMap data and associated with pH changes caused by contamination in river water by iron sulphide mine waste, and their controls, are described and references established for routine monitoring through hyperspectral image processing. 相似文献
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