共查询到20条相似文献，搜索用时 31 毫秒
1.
Hyperspectral remote sensing technique is widely applied for geological studies including the study of extra-terrestrial rocks.
Since it has many spectral bands, discrimination between rocks and minerals can be done more precisely. To perform chemical
and mineralogical mapping and to study the rocks on the lunar surface, India has proposed to launch its first lunar remote
sensing satellite Chandrayaan-1 in the year 2008. For mineralogical mapping, the mission will carry a Hyperspectral Imager
(HySI) instrument, which operates in the VNIR region. This paper presents-an attempt to study the spectral response of lunar-akin
terrestrial rocks, in the VNIR region (as in the case of the proposed HySI on-board Chandrayaan-1). For this purpose, rocks
similar to those present on the lunar surface were collected and their spectral response in the 64 simulated bands of HySI
sensor were studied using a spectro-radiometer. Petrographic studies and modal analysis were carried out using thin sections
of the rock samples. On studying the spectral response of the lunar-like rock samples in the 64 HySI bands, it is seen that
there are distinct absorption features in bands 58 (923.75nm-927.5nm) and 63 (942.5nm-946.25nm) of the NIR wavelength ranges,
for basalt rocks; distinct reflectance features in band 20 (590nm to 600nm) for ganmbbro: distinct reflectance features in
band 19 (580nm to 590nm) and absorption in band 18 (570-580nm) for gabbroic anorthosite and distinct reflection features in
band 63 (942.5nm to 946.25nm) for anorthosite. Thus, this study demonstrates the possibility of identifying the minerals and
rocks on lunar surface using the hyperspectral approach and the spectral signatures of lunar-like rocks present on Earth. 相似文献
2.
N. K. Patel R. K. Saxena Ajay Shiwalkar 《Journal of the Indian Society of Remote Sensing》2007,35(1):73-79
A field experiment was conducted to study the effect of vegetation cover on soil spectra and relationship of spectral indices with vegetation cover. Multi-date spectral measurements were carried out on twelve wheat fields. Five sets of measurements were taken during the growth period of wheat crop. Field reflectance data were collected in the range 350 to 1800 nm using ASD spectroradiometer. Analysis of data was done to select narrow spectral bands for estimation of ground cover. The ratio of reflectance from vegetation covered soil and reflectance from bare soil indicated that spectral reflectance at 670 and 710 nm are the most sensitive bands. Two bands in visible (670 and 560 nm), three bands in near infrared (710, 870 and 1100 nm) and three bands in middle infrared (1480, 1700 and 1800 nm) were found highly correlated with fractional cover. Vegetation indices developed using narrow band spectral data have been found to be better than those developed using broad- band data for estimation of ground cover. 相似文献
3.
4.
TM图像的光谱信息特征与最佳波段组合 总被引：2，自引：0，他引：2
本文分析了北自黑龙江省寒温带缓岗平原、南至广东省南亚热带丘陵等9个不同景观类型样区的TM图像数据,查明TM图像的光谱信息具3—4维结构,其物理含义相当于“亮度”、“绿度”和“热度”、“湿度”。在TM7个光谱图像中,一般以第5波段包含的地物信息最丰富。3个可见光波段(即第1,2,3波段)之间,两个中红外波段(即第5,7波段)之间相关性很高,表明这些波段的信息中有相当大的“重复性”或“冗余性”。第4,6波段则颇特殊,尤其是第4波段与各波段的相关性都很低,表明这个波段的信息有很大的独立性。计算20种组合的熵值的结果表明,由一个可见光波段、一个中红外波段及第4波段组合而成的彩色合成图像,一般具有最丰富的地物信息,其中又常以4,5,3或4,5,1波段的组合为最佳。 相似文献
5.
Kumar Arun Prasad Vaithilingam Selvam Ramasamy Ramasubramanian Chandra Sekar Kar 《国际地球制图》2015,30(5):580-599
Development of a spectral library is a prerequisite for the higher order classification of satellite data and hyperspectral image analysis to map any ecosystem with rich diversity. In this study, sampling methodology, collection of field and laboratory spectral signatures and post-processing methodologies were investigated for developing an exclusive spectral library of mangrove species using hyperspectral spectroscopic techniques. Canopy level field spectra and leaf level laboratory spectra were collected for 34 species (25 true and 9 associated mangroves) from two different mangrove ecosystems of the Indian east coast. Post-processing steps such as removal of water vapour absorption bands, correction of drifts which occur due to the thermal properties of the instrument during data collection and smoothing of spectra for its further utilisation were applied on collected spectra. The processed spectra were then compiled as spectral library. 相似文献
6.
Spectral Characteristics of Domestic and Wild Mammals 总被引：1，自引：0，他引：1
《地理信息系统科学与遥感》2013,50(4):597-608
Few studies have recorded the spectral signatures of domesticated live animals and in particular few have examined wild species. Using in situ radiometry we acquired visual and near infrared spectral signatures of wild elk (Cervus elaphus) and domesticated cattle (Bos taurus) and horses (Equus caballus). Signatures were significantly different among species across all bands with the exception of cattle and horses in the red band. Further research is needed to determine if the shallower slopes in the red-shift region of the animal signatures would allow for distinction from vegetation using various remote sensors. Application of in situ spectral signatures to remotely sensed imagery could provide an efficient method for counting wildlife. 相似文献
7.
Pouran Behnia 《地球空间信息科学学报》2013,16(2):98-103
Four data fusion methods, principle component transform (PCT), brovey transform (BT), smoothing filter-based intensity modulation (SFIM), and hue, saturation, intensity (HSI), are used to merge Landsat—7 ETM+ multispectral bands with ETM+ panchromatic band. Each of them improves the spatial resolution effectively but distorts the original spectral signatures to some extent. SFIM model can produce optimal fusion data with respect to preservation of spectral integrity. However, it results the most blurred and noisy image if the coregistration between the multispectral and pan images is not accurate enough. The spectral integrity for all methods is preserved better if the original multispectral images are within the spectral range of ETM+ pan image. 相似文献
8.
Comparison Between Four Methods for Data Fusion of ETM＋ Multispectral and Pan Images 总被引：2，自引：0，他引：2
PouranBehnia 《地球空间信息科学学报》2005,8(2):98-103
Four data fusion methods, principle component transform (PCT), brovey transform (BT), smoothing filter-based intensity modulation(SFIM), and hue, saturation, intensity (HSI), are used to merge Landsat--7 ETMq- multispectral bands with ETM panchromatic band. Each of them improves the spatial resolution effectively but distorts the original spectral signatures to some extent. SFIM model can produce optimal fusion data with respect to preservation of spectral integrity. However, it results the most blurred and noisy image if the coregistration between the multispectral and pan images is not accurate enough. The spectral integrity for all methods is preserved better if the original multispectral images are within the spectral range of ETM pan image. 相似文献
9.
Ravinder Kaur Sunita Rabindranathan 《Journal of the Indian Society of Remote Sensing》1999,27(4):235-251
Pollution of water resources by sediments eroded from degraded watersheds is a critical concern around the world. Current methods for locating these eroding areas and off-site damage to water resources through visual observations and field sampling with subsequent laboratory analysis are time consuming and expensive. There is thus, a justified interest in developing algorithms for quick estimation of suspended sediment concentrations in large water-bodies from remotely sensed data. This paper presents the results of a ground validation study on characterization and quantification of surface suspended sediment concentrations (SSC) in sediment laden water bodies through an n-waveband specific numerical index, total information content. A comparison of SSC-predictive potential of the proposed new index, derived from four broad (100–300 nm) Landsat MSS, five broad (40–300 nm) Landsat TM and eight narrow (20–40 nm) IRS-P4 OCM spectral bands, with that of the conventional (NIR-Red and NIR+Red) indices, computed from the same spectral band data, is also presented. The study reveaied that at SSCs 250 mg/1, the proposed index (derived from either broad / narrow landsat MSS/TM or IRS-P4 OCM spectral data) could lead to SSC predictions (with mean errors within 20%) comparable with those obtained with the conventional indices (derived from the same spectral band data). It could further be observed that, in general, lower sediment concentrations (i.e. SSCs 150 mg/1) were associated with higher prediction inaccuracies. A comparison of the mean errors of predictions associated with the proposed and the conventional (NIR-Red and NIR+Red) indices computed from broad and narrow band data for SSCs 150 mg/I, revealed that an increase in number of wavebands (from 4 MSS to 5 TM or 8 OCM bands) and a decrease in the bandwidth of these wavebands (from broad MSS/ TM bands to narrow OCM bands) led to a significant increase in the prediction accuracy of the proposed new index. These prediction accuracies were observed to be the highest with the proposed index calculated from narrow OCM-P4 spectral data. However this could not be observed with the conventional indices at any of the SSC ranges and with the proposed index at SSCs 250 mg/l. This shows that the lower SSC-predictive potential of proposed index was a significant function of both the number and the bandwidth of spectral bands used for its computation. In fact in one of the cases, lower SSC (150 mg/l) -predictive accuracy of the proposed index was found to be significantly higher than that of the conventional (NIR+R) index. The proposed algorithm could thus compress the information contained in the entire reflectance spectrum of the sediment laden water bodies to their sediment type and concentration specific characteristic values. This characteristic of the proposed index was not shared by any of the conventional indices, based on only two waveband data. In fact the proposed index appears to be the only mean of completely compressing and quantifying the information contained in all the information channels of a narrow band spectrometer (consisting of 200 wavebands) to be shortly launched by ISRO for satellite based inventory of natural resources. 相似文献
10.
This study presents a deep extraction of localized spectral features and multi-scale spatial features convolution (LSMSC) framework for spectral-spatial fusion based classification of hyperspectral images (HSIs). First, adjacent spectral bands are grouped based on their similarity measurements, where the whole hypercube is partitioned into several sub-cubes, each corresponding to one band group. Then, the proposed localized spectral features extraction (LSF) strategy is used to extract localized spectral features, which are extracted from each band group using the 1D convolutional neural network (CNN). Meanwhile, the proposed HiASPP strategy is employed to extract the multi-scale features from the first several principal components of each sub-cube. Finally, the extracted spectral and spatial features are concatenated for spectral-spatial fusion based classification of HSI. Experiments conducted on three publicly available datasets have demonstrated that the proposed architecture outperforms several state-of-the-art approaches. 相似文献
11.
This study presents the calculation of spectral angle beyond two endmember vectors to the n-dimensional solid spectral angle (NSSA). The calculation of the NSSA is used to characterize the local spectral shape difference among a set of endmembers, leading to a methodology for band selection based on spectral shape variations of more than two spectra. Equidistributed sequences used in the quasi-Monte Carlo method (ESMC) for numerical simulations are shown to expedite the calculation of the NSSA. We develop a band selection method using the computation of NSSA(ϑn) in the context of a sliding window. By sliding the window over all bands available for varying band intervals, the calculated solid spectral angle values can capture the similarity of the endmembers over all spectral regions available and for spectral features of varying widths. By selecting a subset of spectral bands with largest solid spectral angles, a methodology can be developed to capture the most important spectral information for the separation or mapping of endmembers. We provide an example of the merits of the NSSA-ESMC method for band selection as applied to linear spectral unmixing. Specifically, we examine the endmember abundance errors resulting from the NSSA band selection method as opposed to using the full spectral dimensionality available. 相似文献
12.
Bauxite deposits of Jharkhand in India are resulted from the lateritization process and therefore are often associated with the laterites. In the present study, ASTER (Advanced Space borne Thermal Emission and Reflection Radiometer) image is processed to delineate bauxite rich pockets within the laterites. In this regard, spectral signatures of lateritic bauxite samples are analyzed in the laboratory with reference to the spectral features of gibbsite (main mineral constituent of bauxite) and goethite (main mineral constituent of laterite) in VNIR–SWIR (visible-near infrared and short wave infrared) electromagnetic domain. The analysis of spectral signatures of lateritic bauxite samples helps in understanding the differences in the spectral features of bauxites and laterites. Based on these differences; ASTER data based relative band depth and simple ratio images are derived for spatial mapping of the bauxites developed within the lateritic province. In order to integrate the complementary information of different index image, an index based principal component (IPC) image is derived to incorporate the correlative information of these indices to delineate bauxite rich pockets. The occurrences of bauxite rich pockets derived from density sliced IPC image are further delimited by the topographic controls as it has been observed that the major bauxite occurrences of the area are controlled by slope and altitude. In addition to above, IPC image is draped over the digital elevation model (DEM) to illustrate how bauxite rich pockets are distributed with reference to the topographic variability of the terrain. Bauxite rich pockets delineated in the IPC image are also validated based on the known mine occurrences and existing geological map of the bauxite. It is also conceptually validated based on the spectral similarity of the bauxite pixels delineated in the IPC image with the ASTER convolved laboratory spectra of bauxite samples. 相似文献
13.
针对高光谱影像分类问题,提出了一种显著性特征提取方法。首先,利用超像素分割算法将高光谱影像3个相邻波段分割为若干个小区域。然后,基于分割得到的小区域计算反映不同区域的显著性特征。最后,沿着光谱方向采用大小为3、步长为1的滑窗法获得所有波段的显著性特征。进一步将提取的显著性特征与光谱特征进行结合,并将结合后的特征输入到支持向量机中进行分类。利用Pavia大学、Indian Pines和Salinas 3组高光谱影像数据进行分类试验。试验结果表明,与传统的空间特征提取方法和基于卷积神经网络的高光谱影像分类方法相比,提取的显著性特征能够获得更高的高光谱影像分类精度,且结合光谱特征能够进一步提高分类精度。 相似文献
14.
15.
Remote sensing of grassland–shrubland vegetation water content in the shortwave domain 总被引：1，自引：0，他引：1
Andrew Davidson Shusen Wang John Wilmshurst 《International Journal of Applied Earth Observation and Geoinformation》2006,8(4):225-236
This study compares the ability of spectral approaches operating in the shortwave optical domain to predict absolute and relative vegetation water content (AWC and RWC, respectively) across northern prairie grassland–shrubland. We collected vegetation water content and spectral radiometer data over plots of comparable ground resolution (0.5 m) at seven field sites in the Canadian mixed grass prairie in June 2004. We then aggregated observations to scale these data “up” to an observational scale consistent with that of Landsat-TM satellite imagery (30 m). This allowed us to assess abilities of three spectral approaches to predict AWC and RWC at both observational scales. These approaches were: individual vegetation indices, a combination of spectral bands and a combination of spectral derivatives. Our results showed that (a) the band-combination approach provides the most accurate and precise estimates of AWC and RWC at both 0.5 and 30 m sampling resolutions; (b) the combination of bands providing the greatest predictive abilities are those that emphasize the contrast in reflectance between the NIR and SWIR spectral regions; (c) the band-combination approach predicts AWC with much greater accuracy and precision than RWC and (d) the predictive ability of the band-combination approach decreases only slightly when plot-level data are aggregated to a 30 m sampling resolution. These results are generally consistent with the results of other studies and with theory. While our results suggest that simple spectral methods (e.g. linear band-combinations or indices) are good predictors of AWC over grazed and ungrazed grassland–shrubland landscapes at plot- and Landsat spatial resolutions, they are less encouraging for the estimation of RWC. Despite their good predictive abilities, the temporal and geographical portabilities of the spectral approaches for estimating AWC must be further assessed before they can be considered reliable and robust predictive tools. Thus, the further testing of these techniques over larger geographical extents is required. 相似文献
16.
Yuanjin Xu Zhenfei Zhang Guangdao Hu 《Journal of the Indian Society of Remote Sensing》2010,38(2):169-178
In order to accurately identify ground objects in the hyperspectral imagery by spectral matching, it is important to analyze
the absorption-band parameters. This paper presents a new spectral matching method which is based mainly on analysis of the
absorption-band position. A measured spectrum of a ground object can be subject to shifts from its real wavelength position;
meanwhile an absorption band in the spectrum can also be shifted relatively. Both these shifts are due to the environmental
effects. Our spectral matching method stresses the quantification of the total shift of the absorption-band position, thus
to get a possible offset range of the measured absorption bands. This offset range is taken as a constraint on the matching
process. The pixel spectrum in the image is then compared to each known reference spectrum in a spectral library previously
built, so that the ground object corresponding to the reference spectrum is identified. A case study is conducted in Pulang
Porphyry Copper deposit, Zhongdian county, Yunnan, China. Five types of ground objects were studied and it is shown that our
methods can get more accurate identification results than the approach which does not consider the shift ranges. 相似文献
17.
提出一种稀疏自表达方法来研究高光谱影像分类中的波段选择问题。该方法利用字典矩阵等于测量矩阵的条件来改进多观测向量的稀疏表达模型,将波段子集看作高光谱影像波段集合中的代表子集。稀疏自表达方法将波段选择转换为寻求多观测向量中稀疏系数矩阵的非零行向量问题,通过引入混合范数来限定非零元素行向量的个数,利用快速交替方向乘子方法求解稀疏系数矩阵,并聚类非零行向量,实现波段的有效选择。基于两个公开高光谱影像数据集并对比其他4种波段选取方法来验稀疏自表达方法。实验结果证明,稀疏自表达方法能够在计算效率明显优于基于波段相关性的线性限制最小方差方法的同时,取得与该方法和非负稀疏矩阵分解方法相匹甚至略高的总体分类精度。 相似文献
18.
A. Senthil Kumar V. Keerthi A.S. Manjunath Harald van der Werff Freek van der Meer 《International Journal of Applied Earth Observation and Geoinformation》2010
Classification of hyperspectral images has been receiving considerable attention with many new applications reported from commercial and military sectors. Hyperspectral images are composed of a large number of spectral channels, and have the potential to deliver a great deal of information about a remotely sensed scene. However, in addition to high dimensionality, hyperspectral image classification is compounded with a coarse ground pixel size of the sensor for want of adequate sensor signal to noise ratio within a fine spectral passband. This makes multiple ground features jointly occupying a single pixel. Spectral mixture analysis typically begins with pixel classification with spectral matching techniques, followed by the use of spectral unmixing algorithms for estimating endmembers abundance values in the pixel. The spectral matching techniques are analogous to supervised pattern recognition approaches, and try to estimate some similarity between spectral signatures of the pixel and reference target. In this paper, we propose a spectral matching approach by combining two schemes—variable interval spectral average (VISA) method and spectral curve matching (SCM) method. The VISA method helps to detect transient spectral features at different scales of spectral windows, while the SCM method finds a match between these features of the pixel and one of library spectra by least square fitting. Here we also compare the performance of the combined algorithm with other spectral matching techniques using a simulated and the AVIRIS hyperspectral data sets. Our results indicate that the proposed combination technique exhibits a stronger performance over the other methods in the classification of both the pure and mixed class pixels simultaneously. 相似文献
19.
地物反射光谱对MODIS近红外波段水汽反演影响的模拟分析 总被引：14，自引：1，他引：14
在近红外辐射传输方程的基础上,利用近红外波段水汽的不同吸收属性,在MODTRAN的模拟下,深入分析了基于MODIS近红外数据的可降水汽反演算法,并着重讨论了地物反射光谱非线性在可降水汽反演中的影响。研究结果显示,当波段间反射率之比不等于1时,MODIS近红外波段反演水汽将存在较大偏差。同时,在地物光谱库基础上,计算了不同地物反射率比值,其分布表明,大部分地物波段反射率比值不等于1。研究表明,应用现有MODIS近红外波段水汽反演算法,如果不考虑地表反射率光谱变化的影响,由地表反射光谱造成的误差最大约为反射率比值与1偏差的15倍,同时,这一误差还与大气波段透过率之比有关。 相似文献
20.
The leaf area index (LAI) of plant canopies is an important structural parameter that controls energy, water, and gas exchanges of plant ecosystems. Remote sensing techniques may offer an alternative for measuring and mapping forest LAI at a landscape scale. Given the characteristics of high spatial/spectral resolution of the WorldView-2 (WV2) sensor, it is of significance that the textural information extracted from WV2 multispectral (MS) bands will be first time used in estimating and mapping forest LAI. In this study, LAI mapping accuracies would be compared from (a) spatial resolutions between 2-m WV2 MS data and 30-m Landsat TM imagery, (b) the nature of variables between spectrum-based features and texture-based features, and (c) sensors between TM and WV2. Therefore spectral/textural features (SFs) were first selected and tested; then a canonical correlation analysis was performed with different data sets of SFs and LAI measurement; and finally linear regression models were used to predict and map forest LAI with canonical variables calculated from image data. The experimental results demonstrate that for estimating and mapping forest LAI, (i) using high resolution data (WV2) is better than using relatively low resolution data (TM); (ii) extracted from the same WV2 data, texture-based features have higher capability than that of spectrum-based features; (iii) a combination of spectrum-based features with texture-based features could lead to even higher accuracy of mapping forest LAI than their either one separately; and (iv) WV2 sensor outperforms TM sensor significantly. However, we need to address the possible overfitting phenomenon that might be brought in by using more input variables to develop models. In addition, the experimental results also indicate that the red-edge band in WV2 was the worst on estimating LAI among WV2 MS bands and the WV2 MS bands in the visible range had a much higher correlation with ground measured LAI than that red-edge and NIR bands did. 相似文献