共查询到20条相似文献，搜索用时 31 毫秒
1.
Habes A. Ghrefat Philip C. Goodell 《International Journal of Applied Earth Observation and Geoinformation》2011
The goal of this research is to map land cover patterns and to detect changes that occurred at Alkali Flat and Lake Lucero, White Sands using multispectral Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Advanced Land Imager (ALI), and hyperspectral Hyperion and Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data. The other objectives of this study were: (1) to evaluate the information dimensionality limits of Landsat 7 ETM+, ASTER, ALI, Hyperion, and AVIRIS data with respect to signal-to-noise and spectral resolution, (2) to determine the spatial distribution and fractional abundances of land cover endmembers, and (3) to check ground correspondence with satellite data. A better understanding of the spatial and spectral resolution of these sensors, optimum spectral bands and their information contents, appropriate image processing methods, spectral signatures of land cover classes, and atmospheric effects are needed to our ability to detect and map minerals from space. Image spectra were validated using samples collected from various localities across Alkali Flat and Lake Lucero. These samples were measured in the laboratory using VNIR–SWIR (0.4–2.5 μm) spectra and X-ray Diffraction (XRD) method. Dry gypsum deposits, wet gypsum deposits, standing water, green vegetation, and clastic alluvial sediments dominated by mixtures of ferric iron (ferricrete) and calcite were identified in the study area using Minimum Noise Fraction (MNF), Pixel Purity Index (PPI), and n-D Visualization. The results of MNF confirm that AVIRIS and Hyperion data have higher information dimensionality thresholds exceeding the number of available bands of Landsat 7 ETM+, ASTER, and ALI data. ASTER and ALI data can be a reasonable alternative to AVIRIS and Hyperion data for the purpose of monitoring land cover, hydrology and sedimentation in the basin. The spectral unmixing analysis and dimensionality eigen analysis between the various datasets helped to uncover the most optimum spatial–spectral–temporal and radiometric-resolution sensor characteristics for remote sensing based on monitoring of seasonal land cover, surface water, groundwater, and alluvial sediment input changes within the basin. The results demonstrated good agreement between ground truth data and XRD analysis of samples, and the results of Matched Filtering (MF) mapping method. 相似文献
2.
Husain A. Alanazi Habes A. Ghrefat 《Journal of the Indian Society of Remote Sensing》2013,41(4):833-844
The Qurayyah Sabkha is located on the western coast of the Arabian Gulf in the Eastern Province of Saudi Arabia. The current study aims to determine the number of land cover endmembers that can be detected and mapped using Landsat 7 ETM + and ASTER. Furthermore, the study also aims to determine the spatial distribution of fractional abundances of these endmembers. Clastic sediments, calcite dominate sediments, gypsum, vegetation, water, and quartz sand were identified at the surface the Qurayyah Sabkha using Minimum Noise fraction (MNF), Pixel Purity Index (PPI), and n-D Visualization. Results from Matched Filtering (MF) and Linear Spectral Unmixing (LSU) methods showed good match and revealed that the spatial distributions of gypsum, clastic sediments, and quartz sand have nearly similar pattern as determined from Landsat 7 ETM + and ASTER data. These results also show good correspondence between spectra of sample and image. The present results also revealed good matching between the results obtained from MF, LSU, spectral analyses, and X-ray diffraction (XRD). 相似文献
3.
对河北省昌黎县闫庄铁矿床的磁铁石英岩型铁矿石261件样品进行了光谱反射率测量，并与其铁含量进行了相关关系研究，目
的是对钻孔岩芯编录的新方法即高光谱岩芯编录在此类矿床中的可行性进行分析。研究结果表明，铁矿石反射率较低，一般为5%~20%
，铁离子的吸收峰主要表现在400~1 100 nm范围内，铁矿石中铁含量与850~900 nm的反射率均值呈现显著指数负相关关系，为高光谱
岩芯编录在此类矿床中的可行性提供了理论依据和技术途径。 相似文献
4.
S. Anbazhagan N. K. Sainaba S. Arivazhagan 《Journal of the Indian Society of Remote Sensing》2012,40(1):145-153
In the present study, The Landsat 7 ETM satellite data was collected for the Sittampundi anorthosites complex and digital
image analysis was carried out. The anorthositic rocks available at Sittampundi complex is considered as an equivalent of
lunar highland rocks. Hence, a remote sensing study comprises of image analysis and spectral profile analysis was carried
out. The satellite data was digitally processed and generated various outputs like band combinations, color composites, stretched
outputs, and PCA. The suitable processed outputs were identified for delineating the anorthosite complex. The diagnostic absorption
features of reflectance spectra are the sensitive indicators of mineralogy and chemical composition of rocks, which are interest
to the planetary scientists. The spectral profile of Landsat ETM plotted for pure and mixed anorthosite pixels and compared
with the field and lab reflectance spectra. The percentages of image spectra vary from 30% to 60% for Sittampundi anorthosite.
The spectral bands 2, 4 and 6 have low reflectance and bands 3 and 5 have high reflectance. The spectral range of bands 2,3,4,5
and 6 are 525 nm–605 nm, 630 nm–690 nm, 750 nm–900 nm, 1550 nm–1750 nm and 10400 nm–12500 nm respectively. The field spectral
curve has weak absorptions at 650 nm and 1000 nm due to the iron transition absorption and low ca- pyroxene respectively available
in the anorthosite, matching with the image spectra. However, hyperspectal image with narrow bandwidth could be more useful
in selecting the suitable spectrum for remotely mapping the anorthosite region, as equivalent test site for lunar highland
region. 相似文献
5.
Cyanobacterial bloom is a growing environmental problem in inland waters. In this study, we propose a method for monitoring levels of cyanobacterial blooms from Landsat/ETM+ images. The visual cyanobacteria index (VCI) is a simple index for in-situ visual interpretation of cyanobacterial blooms levels, by classifying them into six categories based on aggregation (e.g., subsurface blooms, surface scum). The floating algae index (FAI) and remote sensing reflectance in the red wavelength domain, which can be obtained from Landsat/ETM+ images, were related to the VCI for estimating cyanobacteria bloom levels from the Landsat/ETM+ images. Nine field campaigns were carried out at Lakes Nishiura and Kitaura (Lake Kasumigaura group), Japan, from June to August 2012. We also collected reflectance spectra at 20 stations for different VCI levels on August 3, 2012. The reflectance spectra were recalculated in correspondence to each ETM+ band, and used to calculate the FAI. The FAI values were then used to determine thresholds for classifying cyanobacterial blooms into different VCI levels. These FAI thresholds were validated using three Landsat/ETM+ images. Results showed that FAI values differed significantly at the respective VCI levels except between levels 1 and 2 (subsurface blooms) and levels 5 and 6 (surface scum and hyperscum). This indicated that the FAI was able to detect the high level of cyanobacteria that forms surface scum. In contrast, the Landsat/ETM+ band 3 reflectance could be used as an alternative index for distinguishing surface scum and hyperscum. Application of the thresholds for VCI classifications to three Landsat/ETM+ images showed that the volume of cyanobacterial blooms can be effectively classified into the six VCI levels. 相似文献
6.
Landsat 5卫星较低的时间分辨率(16天)使得其很难获得大区域的、时相一致的清晰影像数据集。本文发展了一种基于半物理模型的时空融合算法-即乘性调制融合算法,并借助多时序的MODIS反射率数据来生成多时相的Landsat TM/ETM+反射率合成影像,经镶嵌后得到区域尺度的高时空分辨率地表反射率数据集(Landsat TM/ETM+)。本文利用吉林省2006年—2011年的Landsat 5 TM地表反射率数据以及500 m的MOD09A1反射率产品来生成3个时相的Landsat 5 TM反射率合成数据,从而获得研究区在上述时相下地表反射率数据的镶嵌图。初步分析表明,所生成的Landsat 5 TM反射率数据的光谱分布特征与MOD09A1反射率数据较为一致,且图像在整体上光谱特征的连续性较好。 相似文献
7.
Yahia Othman Caiti Steele Rolston St. Hilaire 《Journal of the Indian Society of Remote Sensing》2018,46(2):211-218
We evaluated the relationships among three Landsat Enhanced Thematic Mapper (ETM+) datasets, top-of-atmosphere (TOA) reflectance, surface reflectance climate data records (surface reflectance-CDR) and atmospherically corrected images using Fast Line-of-Sight atmospheric analysis of Spectral Hypercubes model (surface reflectance-FLAASH) and their linkto pecan foliar chlorophyll content(chl-cont). Foliar chlorophyll content as determined with a SPAD meter, and remotely-sensed data were collected from two mature pecan orchards (one grown in a sandy loam and the other in clay loam soil) during the experimental period. Enhanced vegetation index derived from remotely sensed data was correlated to chl-cont. At both orchards, TOA reflectance was significantly lower than surface reflectance within the 550–2400 nm wavelength range. Reflectance from atmospherically corrected images (surface reflectance-CDR and surface reflectance-FLAASH) was similar in the shortwave infrared (SWIR: 1550–1750 and 2080–2350 nm) and statistically different in the visible (350–700 nm). Enhanced vegetation index derived from surface reflectance-CDR and surface reflectance-FLAASH had higher correlation with chl-cont than TOA. Accordingly, surface reflectance is an essential prerequisite for using Landsat ETM+ data and TOA reflectance could lead to miss-/or underestimate chl-cont in pecan orchards. Interestingly, the correlation comparisons (Williams t test) between surface reflectance-CDR and chl-cont was statistically similar to the correlation between chl-cont and commercial atmospheric correction model. Overall, surface reflectance-CDR, which is freely available from the earth explorer portal, is a reliable atmospherically corrected Landsat ETM+ image source to study foliar chlorophyll content in pecan orchards. 相似文献
8.
TerraSAR-X satellite acquires very high spatial resolution data with potential for detailed land cover mapping. A known problem with synthetic aperture radar (SAR) data is the lack of spectral information. Fusion of SAR and multispectral data provides opportunities for better image interpretation and information extraction. The aim of this study was to investigate the fusion between TerraSAR-X and Landsat ETM+ for protected area mapping using high pass filtering (HPF), principal component analysis with band substitution (PCA) and principal component with wavelet transform (WPCA). A total of thirteen land cover classes were identified for classification using a non-parametric C 4.5 decision tree classifier. Overall classification accuracies of 74.99%, 83.12% and 85.38% and kappa indices of 0.7220, 0.8100 and 0.8369 were obtained for HPF, PCA and WPCA fusion approaches respectively. These results indicate a high potential for a combined use of TerraSAR-X and Landsat ETM+ data for protected area mapping in Uganda. 相似文献
9.
基于Landsat7 ETM+全色数据纹理和结构信息复合的城市建筑信息提取 总被引：3，自引：0，他引：3
提出了利用主成分分析方法有效地复合纹理和结构信息，从Landsat7 ETM^*全色数据中直接提取区域尺度的城市建筑信息的新方法，并在此基础上评估了Landsat7 ETM^ 全色数据和SPOT全色数据在城市建筑信息提取上的相互替代性。 相似文献
10.
Biodiversity mapping in extensive tropical forest areas poses a major challenge for the interpretation of Landsat images, because floristically clearly distinct forest types may show little difference in reflectance. In such cases, the effects of the bidirectional reflection distribution function (BRDF) can be sufficiently strong to cause erroneous image interpretation and classification. Since the opening of the Landsat archive in 2008, several BRDF normalization methods for Landsat have been developed. The simplest of these consist of an empirical view angle normalization, whereas more complex approaches apply the semi-empirical Ross–Li BRDF model and the MODIS MCD43-series of products to normalize directional Landsat reflectance to standard view and solar angles. Here we quantify the effect of surface anisotropy on Landsat TM/ETM+ images over old-growth Amazonian forests, and evaluate five angular normalization approaches. Even for the narrow swath of the Landsat sensors, we observed directional effects in all spectral bands. Those normalization methods that are based on removing the surface reflectance gradient as observed in each image were adequate to normalize TM/ETM+ imagery to nadir viewing, but were less suitable for multitemporal analysis when the solar vector varied strongly among images. Approaches based on the MODIS BRDF model parameters successfully reduced directional effects in the visible bands, but removed only half of the systematic errors in the infrared bands. The best results were obtained when the semi-empirical BRDF model was calibrated using pairs of Landsat observation. This method produces a single set of BRDF parameters, which can then be used to operationally normalize Landsat TM/ETM+ imagery over Amazonian forests to nadir viewing and a standard solar configuration. 相似文献
11.
《地理信息系统科学与遥感》2013,50(2):280-298
The spectroradiometric retrieved reflectance of a local crop, namely, beans (Phaseolus vulgaris), is directly compared to the reflectance of Landsat 5TM and 7ETM+ atmospherically corrected and uncorrected satellite images. Also, vegetation indices from the same satellite images—atmospherically corrected and uncorrected—are compared with the corresponding vegetation indices produced from field measurements using a spectroradiometer. Vegetation Indices are vital in the estimation of crop evapotransiration under standard conditions (ETc) because they are used in stochastic or empirical models for describing crop canopy parameters such as the Leaf Area Index (LAI) or crop height. ETc is finally determined using the FAO Penman-Monteith method adapted to satellite data, and is used to examine the impact of atmospheric effects. Regarding the reflectance comparison, the main problem was observed in Band 4 of Landsat 5TM and 7ETM+, where the difference, for uncorrected images, was more than 20% and statistically significant. Results regarding ETc show that omission or ineffective atmospheric corrections in Landsat 5TM,/7ETM+ satellite images always results in a water deficit when estimating crop water demand. Diminished estimated crop water requirements can result in a reduction in output or, if critical, crop failure. The paper seeks to illustrate the importance of removing atmospheric effects from satellite images designated for hydrological purposes. 相似文献
12.
Spectral analysis technique has been utilized to identify the Bauxite mineral occurrences in Panchpatmali, Orissa, India. Spectral processing of Landsat ETM+ data has been carried out by converting the digital data from quantized and calibrated values to reflectance values. Minimum noise fraction transformation is used to determine the inherent dimensionality of reflected Landsat ETM+ data, to segregate noise in the data, and to reduce the computational requirements for subsequent processing and interactively to locate pure pixels within the data-set, projecting n-dimensional scatterplots. Spectral processing results are displayed in the form of images corresponding to each group of pixels (endmembers). Mixed tune matched filtering method has been applied on Landsat ETM+ images which gave three score (abundance) images for three different classes (endmembers) such as Bauxite, vegetation and soil. Further, mineralized zones are identified using image fusion of ERS-2 SAR and Landsat ETM+ data using intensity-hue-saturation technique. 相似文献
13.
Tyas Mutiara Basuki Andrew K. Skidmore Patrick E. van Laake Iris van Duren Yousif A. Hussin 《国际地球制图》2013,28(4):329-345
A main limitation of pixel-based vegetation indices or reflectance values for estimating above-ground biomass is that they do not consider the mixed spectral components on the earth's surface covered by a pixel. In this research, we decomposed mixed reflectance in each pixel before developing models to achieve higher accuracy in above-ground biomass estimation. Spectral mixture analysis was applied to decompose the mixed spectral components of Landsat-7 ETM+ imagery into fractional images. Afterwards, regression models were developed by integrating training data and fraction images. The results showed that the spectral mixture analysis improved the accuracy of biomass estimation of Dipterocarp forests. When applied to the independent validation data set, the model based on the vegetation fraction reduced 5–16% the root mean square error compared to the models using a single band 4 or 5, multiple bands 4, 5, 7 and all non-thermal bands of Landsat ETM+. 相似文献
14.
A new method was developed in this study for producing a clear-sky Landsat composite for cropland from cloud-contaminated Landsat images acquired in a short time period. It used Thiel–Sen regression to normalize all Landsat scenes to a MODIS image to make all Landsat images radiometrically consistent and comparable. Pixel selection criteria combining the modified maximum vegetation index and the modified minimum visible reflectance selection methods were designed to enhance the pixel selection of land/water over cloud/shadow in the image compositing. The advantages of the method include (1) avoiding complicated atmospheric corrections but with reliable surface reflectance results, (2) being insensitive to errors induced by image co-registration uncertainties between Landsat and MODIS images, (3) avoiding the lack of samples for the regression analysis using the full Landsat scenes (rather than overlay regions), and (4) enhancing cloud/shadow detection. The composite image has MODIS-like surface reflectance, thus making MODIS algorithms applicable for retrieving biophysical parameters. The method was automatically implemented on a set of 13 cloud-contaminated (>39%) Landsat-7 (Scan-Line Corrector-Off) and Landsat-8 scenes acquired during peak growing season in a crop region of Manitoba, Canada. The result was a 95.8% cloud-free image. The method can also substantially increase the usage of cloud-contaminated Landsat data. 相似文献
15.
Surface fires are common in coalfields where coal is mined or exposed to sunlight for long durations of time. The heat energy emitted from these fires affects the signal recorded by sensors operating in the shortwave infrared regions of the electromagnetic spectrum. The Landsat TM/ETM+ band-7 is sensitive to solar reflected radiation as well as emitted radiation from a target. The ‘maximum solar reflection threshold’ method proposed in this study uses the highest spectral radiance that can be attributed to solar reflection as the conservative threshold to segregate the pixels with emitted component from those with reflected component of the EM energy. Investigations with Landsat TM/ETM+ data indicate a reflectance value of 0.23–0.25 as the most representative highest reflectance (threshold) in coal mining areas. The method apparently has the advantage that it is based on the reflectance characteristics of materials (sandstone-shale mixtures) typically found in coal mining areas. 相似文献
16.
17.
Hüseyin Çaldırak Bedri Kurtuluş 《Journal of the Indian Society of Remote Sensing》2018,46(9):1353-1364
This study explores the evidence of recharge locations using hydrogeochemical and physicochemical measurements in an alkaline lake, Lake Salda, in Burdur, Turkey. In-situ measurements have been performed using a conductivity–temperature–depth device to map the physicochemical dynamic of the lake. Water and sediment samples were collected on the surface and floor of the lake. A seismic study was also carried out in order to observe the geometry of the lake floor. In addition, thermal distribution was mapped using the thermal band of Landsat 7 ETM+ and Landsat 8 satellite images. Temperature and specific conductance measurements were mapped using a new technique, Empirical Bayesian Kriging (EBK), from the lake’s surface to the floor. According to interpolation maps obtained from the EBK, possible water inputs were observed close to a fault at the south-eastern part of the lake. The results of thermal band imaging also reveal the probability of a fault effecting the recharge on the surface. The results of water and sediment samples present a richness in Mg2+ and Fe2+ elements respectively on the floor of the lake. Finally, seismic results show some possible recharge zones on the floor of the lake, and sediment results indicate that there should be peridotite occurrence below the alluvium unit. 相似文献
18.
A time series of leaf area index (LAI) of a managed birch forest in Germany (near Dresden) has been developed based on 16-day normalized difference vegetation index (NDVI) data from the Landsat ETM+ sensor at 30 m resolution. The Landsat ETM+ LAI was retrieved using a modified physical radiative transfer (RTM) model which establishes a relationship between LAI, fractional vegetation cover (fC), and given patterns of surface reflectance, view-illumination conditions and optical properties of vegetation. In situ measurements of photosynthetically active radiation (PAR) and vegetation structure parameters using hemispherical photography (HSP) served for calibration of model parameters, while data from litter collection at the study site provided the ground-based estimates of LAI for validation of modelling results. Influence of view-illumination conditions on optical properties of canopy was simulated by a view angle geometry model incorporating the solar zenith angle and the sensor viewing angle. Effects of intra-annual and inter-annual variability of structural properties of the canopy on the light extinction coefficient were simulated by implementing variability of the leaf inclination angle (LIA), which was confirmed in the study site. The results revealed good compatibility of the produced Landsat ETM+ LAI data set with the litter-estimated LAI. The results also showed high sensitivity of the LAI retrieval algorithm to variability of structural properties of the canopy: the implementation of LIA dynamics into the LAI retrieval algorithm significantly improved the model accuracy. 相似文献
19.
For three agricultural crop types, winter wheat (Triticum aestivum L.), barley (Hordeum vulgare L.), and canola (Brassica napus L.), we estimated biophysical parameters including fresh and dry biomass, leaf area index (LAI), and vegetation water content, for which we found the equivalent water thickness (EWT), fuel moisture content per fresh weight (FMCFW), and fuel moisture content per dry weight (FMCDW). We performed these estimations using data from the newly launched Landsat 8 Operational Land Imager (OLI) sensor, as well as its predecessor the Landsat 7 Enhanced Thematic Mapper Plus (ETM+). Progress in the design of the new sensor (i.e., Landsat 8), including narrower near-infrared (NIR) wavebands, higher signal-to-noise ratio (SNR), and greater radiometric resolution highlights the necessity to investigate the biophysical parameters of agricultural crops, especially compared to data from its predecessor. This study aims to evaluate vegetation indices (VIs) derived from the Landsat 8 OLI and the Landsat 7 ETM+. Both the Landsat 8 OLI and Landsat 7 ETM+ VIs agreed well with in-situ data measurements. However, the Landsat 8 OLI-derived VIs were generally more consistent with in situ data than the Landsat 7 ETM+ VIs. We also note that the Landsat 8 OLI is better able to capture the small variability of the VIs because of its higher SNR and wider radiometric range; in addition, the saturation phenomenon occurred earlier for the Landsat 7 ETM+ than for the Landsat 8 OLI. This indicates that the new sensor is better able to estimate the biophysical parameters of crops. 相似文献
20.
Land cover classification using Landsat 8 Operational Land Imager data in Beijing,China 总被引：1，自引：0，他引：1
The successful launch of Landsat 8 provides a new data source for monitoring land cover, which has the potential to significantly improve the characterization of the earth’s surface. To assess data performance, Landsat 8 Operational Land Imager (OLI) data were first compared with Landsat 7 ETM + data using texture features as the indicators. Furthermore, the OLI data were investigated for land cover classification using the maximum likelihood and support vector machine classifiers in Beijing. The results indicated that (1) the OLI data quality was slightly better than the ETM + data quality in the visible bands, especially the near-infrared band of OLI the data, which had a clear improvement; clear improvement was not founded in the shortwave-infrared bands. Moreover, (2) OLI data had a satisfactory performance in terms of land cover classification. In summary, OLI data were a reliable data source for monitoring land cover and provided the continuity in the Landsat earth observation. 相似文献