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1.
AbstractThis study proposes the development of a multi-sensor, multi-spectral composite from Landsat-8 and Sentinel-2A imagery referred to as ‘LSC’ for land use land cover (LULC) characterisation and compared with respect to the hyperspectral imagery of the EO1: Hyperion sensor. A three-stage evaluation was implemented based on the similarity observed in the spectral response, supervised classification results and endmember abundance information obtained using linear spectral unmixing. The study was conducted for two areas located around Dhundi and Rohtak in Himachal Pradesh and Haryana, respectively. According to the analysis of the spectral reflectance curves, the spectral response of the LSC is capable of identifying major LULC classes. The kappa accuracy of 0.85 and 0.66 was observed for the classification results from LSC and Hyperion data for Dhundi and Rohtak datasets, respectively. The coefficient of determination was found to be above 0.9 for the LULC classes in both the datasets as compared to Hyperion, indicating a good agreement. Thus, these three-stage results indicated the significant potential of a composite derived from freely available multi-sensor multi-spectral imagery as an alternative to hyperspectral imagery for LULC studies. 相似文献
2.
《International Journal of Digital Earth》2013,6(3):194-216
Information on Earth's land surface cover is commonly obtained through digital image analysis of data acquired from remote sensing sensors. In this study, we evaluated the use of diverse classification techniques in discriminating land use/cover types in a typical Mediterranean setting using Hyperion imagery. For this purpose, the spectral angle mapper (SAM), the object-based and the non-linear spectral unmixing based on artificial neural networks (ANNs) techniques were applied. A further objective had been to investigate the effect of two approaches for training sites selection in the SAM classification, namely of the pixel purity index (PPI) and of the direct selection of training points from the Hyperion imagery assisted by a QuickBird imagery and field-based training sites. Object-based classification outperformed the other techniques with an overall accuracy of 83%. Sub-pixel classification based on the ANN showed an overall accuracy of 52%, very close to that of SAM (48%). SAM applied using the training sites selected directly from the Hyperion imagery supported by the QuickBird image and the field visits returned an increase accuracy by 16%. Yet, all techniques appeared to suffer from the relatively low spatial resolution of the Hyperion imagery, which affected the spectral separation among the land use/cover classes. 相似文献
3.
Gayantha R.L. Kodikara Tsehaie WoldaiFrank J.A. van Ruitenbeek Zack KuriaFreek van der Meer Keith D. ShepherdG.J. van Hummel 《International Journal of Applied Earth Observation and Geoinformation》2012,14(1):22-32
Pleistocene to present evaporitic lacustrine sediments in Lake Magadi, East African Rift Valley, Kenya were studied and mapped using spectral remote sensing methods. This approach incorporated surface mineral mapping using space-borne hyperspectral Hyperion imagery together with laboratory analysis, including visible, near-infrared diffuse reflectance spectroscopy (VNIR) measurements and X-ray diffraction for selected rock and soil samples of the study area. The spectral signatures of Magadiite and Kenyaite, which have not been previously reported, were established and the spectral signatures of trona, chert series, volcanic tuff and the High Magadi bed were also analyzed.Image processing techniques, MNF (Minimum Noise Fraction) and MTMF (Mixture Tuned Matched Filtering) using a stratified approach (image analysis with and without the lake area), were used to enhance the mapping of evaporates. High Magadi beds, chert series and volcanic tuff were identified from the Hyperion image with an overall mapping accuracy of 84.3%. Even though, the spatial distribution of evaporites and sediments in Lake Magadi area change in response to climate variations, the mineralogy of this area has not been mapped recently. The results of this study shows the usefulness of the hypersspectral remote sensing to map the surface geology of this kind of environment and to locate promising sites for industrial open-pit trona mining in a qualitative and quantitative manner. 相似文献
4.
Arecanut is one of the predominant plantation crop grown in India. Yield of this crop depends upon age of the crop and there is no information on the spectral behaviour of arecanut crops across its ages. In this study popular supervised classification algorithms were utilized for age discrimination of arecanut crops using Hyperion imagery. Arecanut plantations selected for the study are located in Channagiri Taluk, Davanagere district of Karnataka state, India. Ground truth information collected involves: (i) GPS coordinates of selected plots, (ii) spectral reflectance of arecanut crops with age ranging from 1 to 50 years, using handheld spectroradiometer with 1 nm spectral resolution. These spectral measurements were made close in time to the acquisition of Hyperion imagery to build age-based spectral library. It is observed from the analysis that crops of ages below 3, 3–7, 8–15 and above 15 years were showing distinct spectral behaviour. Accordingly, crops age ranging from 1 to 50 were grouped into four classes. Classification of arecanut crops based on age groups was performed using methods like spectral angle mapper, support vector machine and minimum distance classifier, and were compared to find the most suitable method. Among the classification methods adopted, support vector machine with linear kernel function resulted in most accurate classification method with overall accuracy of 72% for within class seperability. Individual age group classification producer’s accuracy varied minimum of 12.5% for 3–7 years age group and maximum of 86.25% for above 15 years age group. It may be concluded that, not only age- based arecanut crop classification is possible, but also it is possible to develop age-based spectral library for plantation crop like arecanut. 相似文献
5.
An improved atmospheric correction algorithm for hyperspectral remotely sensed imagery 总被引：2，自引：0，他引：2
There is an increased trend toward quantitative estimation of land surface variables from hyperspectral remote sensing. One challenging issue is retrieving surface reflectance spectra from observed radiance through atmospheric correction, most methods for which are intended to correct water vapor and other absorbing gases. In this letter, methods for correcting both aerosols and water vapor are explored. We first apply the cluster matching technique developed earlier for Landsat-7 ETM+ imagery to Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data, then improve its aerosol estimation and incorporate a new method for estimating column water vapor content using the neural network technique. The improved algorithm is then used to correct Hyperion imagery. Case studies using AVIRIS and Hyperion images demonstrate that both the original and improved methods are very effective to remove heterogeneous atmospheric effects and recover surface reflectance spectra. 相似文献
6.
Tarik Mitran T. Ravisankar M.A. Fyzee Janaki Rama Suresh G. Sujatha K. Sreenivas 《国际地球制图》2015,30(6):701-721
The relationship between soil salinity parameters and their influence on soil spectral characteristics were analyzed using both satellite data (Hyperion) and reflectance data of soil samples collected from parts of Ahmedabad district of Gujarat, India. The soil spectral reflectance curves were assessed using absorption feature parameters by DISPEC software to identify suitable spectral band for salinity characterization. The Hyperion data of the study area were processed and classified into different classes by spectral angle mapper algorithm using spectral library generated from soil spectra. The results showed that among all the observed soil parameters Electrical Conductivity, Exchangeable Sodium Percentage, Cation Exchange Capacity and Mg++ predictions can be made accurately based on partial least square regression models developed from selected wavelengths. Out of the total study area moderately saline-sodic, severely saline-sodic, severely saline and slightly saline soils occupy 23.5, 12.6, 10.9 and 0.04%, respectively. 相似文献
7.
Quantification of the urban composition is important in urban planning and management. Previous research has primarily focused on unmixing medium-spatial resolution multispectral imagery using spectral mixture analysis (SMA) in order to estimate the abundance of urban components. For this study an object-based multiple endmember spectral mixture analysis (MESMA) approach was applied to unmix the 30-m Earth Observing-1 (EO-1)/Hyperion hyperspectral imagery. The abundance of two physical urban components (vegetation and impervious surface) was estimated and mapped at multiple scales and two defined geographic zones. The estimation results were validated by a reference dataset generated from fine spatial resolution aerial photography. The object-based MESMA approach was compared with its corresponding pixel-based one, and EO-1/Hyperion hyperspectral data was compared with the simulated EO-1/Advanced Land Imager (ALI) multispectral data in the unmixing modeling. The pros and cons of the object-based MESMA were evaluated. The result illustrates that the object-based MESMA is promising for unmixing the medium-spatial resolution hyperspectral imagery to quantify the urban composition, and it is an attractive alternative to the traditional pixel-based mixture analysis for various applications. 相似文献
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10.
Diego Gómez Pablo Salvador Julia Sanz Mikhail Urbazaev José Luis Casanova 《地理信息系统科学与遥感》2020,57(6):813-829
ABSTRACT The climate in southern Iceland has warmed over the last 70 years, resulting in accelerated glacier dynamics at the Solheimajoküll glacier. In this study, we compare glacier terminus locations from 1973 to 2018, to changes in climate across the study area, and we derive ice-surface velocities (2015–2018) from satellite remote-sensing imagery (Sentinel-1) using the offset-tracking method. There have been two regional temperature trends in the study period: cooling (1973–1979) and warming (1980–2018). Our results indicate a time lag of about 20 years between the onset of glacier retreat (?53 m/year since 2000) and the inception of the warming period. Seasonally, the velocity time series suggest acceleration during the summer melt season since 2016, whereas glacier velocities during accumulation months were constant. The highest velocities were observed at high elevations where the ice-surface slope is the steepest. We tested several scenarios to assess the hydrological time response to glacier accelerations, with the highest correlations being found between one and 30 days after the velocity estimates. Monthly correlation analyses indicated inter-annual and intra-annual variability in the glacier dynamics. Additionally, we investigate the linkage between glacier velocities and meltwater outflow parameters as they provide useful information about internal processes in the glacier. Velocity estimates positively correlate with water level and negatively correlate with water conductivity between April and August. There is also a disruption in the correlation trend between water conductivity and ice velocity in June, potentially due to a seasonal release of geothermal water. 相似文献
11.
K. P. Sharma P. K. Garg S. K. Verma 《Journal of the Indian Society of Remote Sensing》1986,14(1):11-16
To utilize the full potential of multispectral data acquired from aerial photographs/satellite imagery increased knowledge of the spectral reflectance characteristics of Landuse/Landcover features are required. Spectro-Radiometer was used to collect the spectral reflectance values in wavelength regions ranging from 0.48 to 0.96 u m, of some Landuse/Landcover features, in Roorkee and its surrounding areas. Spectral reflectance values, thus collected, were used to draw spectral reflectance curves of each feature separately and to determine the optimum wavelength regions for identifying each Landuse/Landcover feature. The wavelength regions, in which two dissimilar Landuse/Landcover features exhibit nearly same tonal variation in B&W aerial photographs/satellite imagery, were also determined from these curves. 相似文献
12.
In this study, we test the potential of two different classification algorithms, namely the spectral angle mapper (SAM) and object-based classifier for mapping the land use/cover characteristics using a Hyperion imagery. We chose a study region that represents a typical Mediterranean setting in terms of landscape structure, composition and heterogeneous land cover classes. Accuracy assessment of the land cover classes was performed based on the error matrix statistics. Validation points were derived from visual interpretation of multispectral high resolution QuickBird-2 satellite imagery. Results from both the classifiers yielded more than 70% classification accuracy. However, the object-based classification clearly outperformed the SAM by 7.91% overall accuracy (OA) and a relatively high kappa coefficient. Similar results were observed in the classification of the individual classes. Our results highlight the potential of hyperspectral remote sensing data as well as object-based classification approach for mapping heterogeneous land use/cover in a typical Mediterranean setting. 相似文献
13.
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
14.
H. Pande Poonam S. Tiwari Shashi Dobhal 《Journal of the Indian Society of Remote Sensing》2009,37(3):395-408
Image fusion is the combination of two or more different images to form a new image by using a certain algorithm. Despite
the fact that the number and kind of satellite imagery are daily increasing, using fusion techniques, in a proper way, to
eliminate the redundancy in data and increase the quality of data is an important challenge in Remote Sensing Image Processing.
Fusion of multispectral images with a hyperspectral image generates a composite image which preserves the spatial quality
from the high resolution (MS) data and the spectral characteristics from the hyperspectral data. For the present study three
fusion algorithms (Principal Component Transformation, Colour Normalized and Gram-Scmidt Transformation) were analysed for
Hyperion and IKONOS MSS data. Their ability to preserve the spectral quality of fused data, in comparison with original hyper-spectral
image, has been investigated. 相似文献
15.
Claudia Spinetti Francesco Mazzarini Ruggero Casacchia Laura Colini Marco Neri Boris Behncke Rosamaria Salvatori Maria Fabrizia Buongiorno Maria Teresa Pareschi 《International Journal of Applied Earth Observation and Geoinformation》2009
Spectral properties of volcanic materials in the optical region (350–2500 nm) of the electromagnetic spectrum are analyzed. The goal is to characterize air-fall deposits, recent lava flows, and old lava flows based on their spectral reflectance properties and on the textural characteristics (grain size) of pyroclastic deposits at an active basaltic volcano. Data were acquired during a spectroradiometric field survey at Mt. Etna (Italy) in summer 2003 and combined with hyperspectral satellite (Hyperion) and airborne LiDAR (Light Detection and Ranging) data. In addition, air-fall deposits produced by the highly explosive 2002–2003 eruption have been sampled and spectrally characterized at different distances from the new vents. The spectral analysis shows that air-fall deposits are characterized by low reflectance values besides variations in grain size. This distinguishes them from other surface materials. Old lava flows show highest reflectance values due to weathering and vegetation cover. The spectral data set derived from the field survey has been compared to corrected satellite hyperspectral data in order to investigate the Hyperion capabilities to differentiate the surface cover using the reflectance properties. This has allowed us to identify the 2002–2003 air-fall deposits in a thematic image just few months after their emplacement. Moreover, the observed differences in the field spectra of volcanic surfaces have been compared with differences in the signal intensity detected by airborne LiDAR survey showing the possibility to include information on the texture of volcanic surfaces at Mt. Etna. The approach presented here may be particularly useful for remote and inaccessible volcanic areas and also represents a potentially powerful tool for the exploration of extraterrestrial volcanic surfaces. 相似文献
16.
Hyperion is a space borne sensor which provides powerful tool in discriminating land cover features including urban area and in preparation of urban maps. It gives hyperspectral images in 242 bands within 400?nm to 2,500?nm wavelength range with 10?nm band-width. The Hyperion image in raw form is badly affected with several atmospheric effects which cause haziness. In this study hyperspectral image is atmospherically corrected by using FLAASH model of ENVI. After atmospheric correction the urban area was mapped using the spectral endmember collected by the procedure which includes minimum noise fraction (MNF), pixel purity index (PPI) and n-dimensional visualization in ENVI software. The aim of this study is to map the urban area using several mapping techniques such as Spectral Angle Mapper (SAM), Mixture Tune Matched Filtering (MTMF) and Linear Spectral Unmixing. The urban land covers displayed noticeable differences from one another in the spectral responses in the Hyperion image. The overall accuracy of the SAM classified map was 89.41%, which indicated good potential of Hyperion image for Classification. Use of the other approaches, linear spectral unmixing and MTMF have improved the classification results. 相似文献
17.
The use of multispectral satellite sensors for generation of hyperspectral indices is restricted because of their coarse spectral resolutions. In this study, we attempted to synthesize a few of these hyperspectral indices, viz. RedEdge Normalized Difference Vegetation Index (NDVI705), Plant Senescence Reflectance Index (PSRI) and Normalized-Difference-Infrared-Index (NDII), for crop stress monitoring at regional scale using multispectral images, simulated from Hyperion data. The Hyperion data were resampled and simulated to corresponding spatial and spectral resolutions of AWiFS, OCM-2 and MODIS sensors using their respective filter function. Different possible combinations of two bands (i.e. simple difference, simple ratio and normalized difference) were computed using synthetic spectral bands of each sensor, and were regressed with NDVI705, PSRI and NDII. Models with highest correlation were selected and inverted on Hyperion data of another date to synthesize respective multispectral indices. Synthetic broad band indices of multispectral sensors with their respective narrow band indices of Hyperion were found to be in good agreement. 相似文献
18.
Because of the pointing capability of the Hyperion/Earth Observing-One (EO-1) to improve the revisit time of the scene, temporal series of narrowband vegetation indices (VIs) can be generated to study the phenology of the Amazonian tropical forests. In this study, 10 selected narrowband VIs calculated from Hyperion nadir and off-nadir data and from different view directions (forward scattering and backscattering) were analyzed for their sensitivity to view-illumination effects along the dry season on the Seasonal Semi-deciduous Forest. Data analysis was also supported by PROSAIL modeling to simulate the spectral response of this forest type in both directions. Hyperion and PROSAIL results showed that the Enhanced Vegetation Index (EVI) and Photochemical Reflectance Index (PRI) were the two more anisotropic VIs, whereas the Normalized Difference Vegetation Index (NDVI), Structure Insensitive Pigment Index (SIPI) and the Vogelmann Red Edge Index (VOG) were comparatively less sensitive to view-illumination effects. When compared to the other VIs and because of the greater dependence on the near-infrared (NIR) reflectance, EVI showed a different spectral behavior. EVI increased from forward scattering to backscattering and with decreasing solar zenith angle (SZA) towards the end of the local dry season, due to reduction in shading and enhancement of the illumination effects. On the other hand, PRI was higher with increasing shading in the forward scattering direction, as deduced from the PROSAIL simulation. Results emphasized the importance of taking into account bidirectional effects when analyzing temporal series of VIs collected over tropical forests by imaging spectrometers with pointing capability or even by multispectral sensors with large field-of-view (FOV). 相似文献
19.
以位于三峡库区的龙门河森林自然保护区为研究区,综合利用线性光谱混合模型和几何光学模型,基于高光谱遥感数据提取森林结构参数是本文研究的重点。在研究区地面调查数据的基础上,通过高光谱数据和混合光谱分解法,获得反演几何光学模型所需的四分量参数,根据背景光照分量与森林植被冠层各参数间的关系,反演得到森林冠层郁闭度及平均冠幅的定量分布图,并利用37个野外实测样本进行结果验证。 相似文献
20.
以福建省平和县琯溪蜜柚为研究对象，利用星载Hyperion高光谱遥感数据对蜜柚叶片进行氮浓度估测。在分析Hyperion数据特征的基础上进行大气校正、几何纠正等预处理，从而得到图像反射率；结合地面光谱测量和蜜柚叶片采样分析，通过逐步回归分析法研究叶片氮浓度与高光谱图像反射率及其衍生量的关系，最终建立其遥感定量监测模型。结果表明，图像反射率的对数变换更有利于氮浓度的定量反演，入选的波段是983 nm、1 245 nm、1 316 nm和1 457 nm，其中1 245 nm波段对氮浓度影响最大，1 457 nm波段最小。利用该模型对氮浓度进行估算的值域与地面调查结果一致，说明利用高光谱进行氮浓度定量反演具有一定的可行性。 相似文献