最新刊期
卷 13 ， 期 2 ， 2009
- 摘要：With the development of quantitative remote sensing, the scaling problems attract more and more attention. The discrepancy between observation scale, model scale and land surface process scale may lead to different conclusions. Now, how to effectively scale remotely sensed information at different scales already becomes one of the most important research focuses of remote sensing. The aim of our research is to compare and analyze two general scaling methods, the Taylor Series Expansion Model （TSM） and the Computational Geometry Model （CGM）, and apply them to the scaling of leaf area index （LAI）. Firstly, the necessity and importance of scaling are analyzed. Secondly, based on the research of description for the same object using different scale data, the mechanism of scaling effects is presented. Then, the two general models, TSM and CGM, are briefly introduced and their advantages and disadvantages are discussed in detail. Finally, through the retrieval of leaf area index, the two models are comprehensively compared and analyzed in three distinct landscapes. The result shows that the relative scaling error increases with the heterogeneity of land surface. The relative scaling error is 2% in the relatively homogeneous woodland; however, it arises up to 7% in crop-water mixed areas. Apparently, the TSM can better characterize the scale effect and obtain more accurate surface parameters when both small scale （high resolution） data and large scale （low resolution） data are available. The relative scaling error can be reduced to less than 1% for all these test landscapes when TSM is used in scaling. In contrast, CGM can not produce rational result and the relative error is still large. It may be due to using inappropriate weights or data ranges in the model. More study about CGM is needed. On the whole, it is necessary to select the suitable scaling model according to the practical applications. The scaling makes the remote sensing products at different scales comparable and the surface parameter retrieval results more accurate. Scaling technique will provide a powerful technical support for applications in resources survey, environment and disaster monitoring, and other relevant fields.关键词：remote sensing;scale effect;scaling;NDVI
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发布时间：2021-06-10 - 摘要：Polarimetric microwave radiometer, a new type of remote sensor, can measure not only the first two Stokes parameters, but also the third and the fourth Stokes parameter of ocean surface radiation. Thus it opens a new field of microwave remote sensing on wind vectors. There is wind direction ambiguity in actually retrieved oceanic wind field using fully polarimetric radiometer data because wind direction signals in Tv and Th are very small comparing with other geophysical parameters, while T3 and T4 are basically two order smaller than those of horizontal and vertical polarization, and meanwhile there are calibration errors in each Stokes parameters. In this paper, we dedicate to improve the calibration accuracy by designing a fully onboard calibrator and reasonably allocating time for calibration and observation during one scan cycle. The theory of polarimetric microwave radiometer calibration is given and the actual considerations of the on-board fully polarimetric calibration standard are demonstrated. An original idea of calibrating polarimetric radiometer on satellite is presented. The relation between scan mode and wind direction retrieval error is analyzed. A new scanning geometry to remove these wind direction ambiguous solutions is devised and modeled. Simulation results show this kind of scanning geometry can remove wind direction ambiguity effectively. The accuracy of wind direction retrieval can be improved to 15°. On the other hand, due to the limited space on satellite, the swath of a single side scan can reach above 760 kilometers.关键词：polarimetric microwave radiometer;ocean wind direction ambiguity;onboard calibration;scanning geometry
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发布时间：2021-06-10 - 摘要：Detection of spatial outliers has been one of the hot issues in the field of spatial data mining and knowledge discovery. So far, the detection of spatial outliers is determined by spatial outlier factor in most of the existing methods, while geometrical distances among their corresponding spatial neighbor are ignored. In this case, these existing methods are inappropriative to the spatial inhomogeneous distribution. To overcome this limitation, this paper presents a new method for spatial outlier detection, named as spatial outlier measure method （SOM for short）. At first, some concepts related to the SOM are defined, such as the attribute gradient, the inverse distance weight and the degree of spatial outlier. The algorithm of the SOM is further presented. One can easily find that the new method considers the distances among the neighborhood and their effects on the attribute values of the target entities, and the degree of spatial outlier is used to check spatial outliers. Finally, a practical example is employed to demonstrate the validity of the method proposed in the paper, where the Cr concentration data of soil in a southern city of China are utilized.关键词：spatial outlier;spatial nearest neighbor;spatial outlier measure;inverse distance interpolation
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发布时间：2021-06-10 - 摘要：A SAR image can be modeled as the multiplication of the noise-free image and speckles. So the noise-free image can be estimated from the observed image with the Bayesian technique. It’s crucial to choose a proper prior model for well matching the SAR images’ characteristics. In this article the Membrane MRF model is employed to model the prior information, which overcomes GMRF’s problem of sensitivity to parameters. And, pixels in homogeneous and non-homogeneous regions are processed separately by adjusting the model’s neighborhood adaptively. Experiments show that not SAR images can be despeckled efficiently while their structures are preserved well.关键词：SAR;speckle;Bayesian;Membrane MRF
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发布时间：2021-06-10 - 摘要：Synthetic Aperture Radar （SAR） image is polluted easily by speckle noise, which can affect further processing of SAR image. Traditional methods employ wavelet transform, which is only effective in representing point singularities. Based on Fast Discrete Curvelet Transform （FDCT）, a de-noising method for SAR image is presented. FDCT is employed to transform the SAR image into the curvelet domain to obtain the curvelet coefficients, and then soft and hard thresholding de-noising processes are performed separately on the Curvelet coefficients of different scales and directions by using adaptive threshold estimation. Finally the SAR image is reconstructed by inverse FDCT. This de-noising method is applied to the experiments of a single look SAR image, and compared with the wavelet de-noising method. Experimental results indicate that based-FDCT de-noising method is a more effective method, which is not only better in reducing speckle, but also of advantage in holding information of target edge and grain.关键词：synthetic aperture radar;speckle;fast discrete curvelet transform （FDCT）;image denoising
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发布时间：2021-06-10 - 摘要：The geometric accuracy of Synthetic Aperture Radar （SAR） is one of key factors influencing its final application. However, the method of quantitative accuracy assessment and error analysis for SAR imagery is still very lacking. This paper chose the representative satellite-borne PALSAR images to implement the experiments on geometric positioning accuracy, through establishing the imaging model with Doppler, slant range and the earth ellipsoid equations, and obtained the quantitative values of the systemic geometric errors and rectification errors. Subsequently, according to the fact that the elevation error is the main error source influencing the geometric rectification precision, computer simulation is used to discuss the systemic influence on the geometric rectification accuracy quantitatively, and the corresponding effect regularity from different facets is put forward, e.g., elevation error to the view angle, the error of view angle to geometric accuracy, and the unit elevation error to the geometric accuracy. It can provide some scientific evidence on the image processing and application of PALSAR images, more important, a new method for quantitative error analysis and geometric accuracy analysis of SAR images.关键词：SAR;geometric accuracy;error analysis;elevation error;PALSAR
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发布时间：2021-06-10 - 摘要：For resolving the problem that there are lots of mixed pixels in the Synthetic Aperture Radar （SAR） images, against the flaw that the traditional Independent Component Analysis（ICA） can not solve the decomposition of mixed pixels effectively, we propose a new algorithm: Supervised Learning ICA algorithm（SL-ICA）. Adding supervised learning restrictive conditions to the negentropy objective function, we implement negentropy and restrictive conditions in a unified objective function, which minimizes the error while maximizing the negentropy. At the same time, we optimize the objective function using a new dual-gradient descent algorithm iteratively, which accelerates the computing speed. By testing SL-ICA and Principal Component Analysis （PCA）. on artificial simulated SAR images and ENVISAT-ASAR （Advanced Synthetic Aperture Radar） images of Beijing, the results show that SL-ICA can get more precise results than the PCA.关键词：Synthetic Aperture Radar （SAR）;decomposition of mixed pixels;Independent Component Analysis （ICA）;remote sensing image;Principal Component Analysis （PCA）
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发布时间：2021-06-10 - 摘要：The geometric active contour model is a classical image segmentation model based on the curve evolution theory and the level set method, which has been successfully applied to the segmentation of medical images. Due to the existence of speckle noise, the model fails in SAR image segmentation. Moreover, there are several disadvantages with this model. First, the evolution equation isn’t obtained with the energy minimization method. Second, the level set function needs to be reinitialized to a signed distance function periodically during the evolution. Finally, the model is computationally inefficient. Based on SAR image edge detectors and the variational level set method, a novel geometric active contour model is proposed under the criterion of energy minimization. The basic idea is that the energy functional is defined directly on the level set function and the original edge indicator function based on gradients is replaced with a new edge indicator function based on the ROEWA operator. Thus, the ability of detecting edges and the accuracy of locating edges are greatly increased, which makes the model very appropriate for SAR image segmentation. In addition, a term penalizing the level set function is added to the energy functional in order to force the level set function to be close to a signed distance function and therefore completely eliminates the need of the costly re-initialization procedure. Thanks to the contribution of this term, the numerical calculation of the model can be implemented by a simple explicit difference scheme; at the same time the evolution speed keeps very fast. The proposed model has several advantages. For example, it can be easily implemented; it results in accurate segmentation boundaries; it converges fast and its level set function doesn’t need to be reinitialized. The experimental results on the simulated image and real data show its efficiency and accuracy.关键词：SAR;image segmentation;the active contour model;the level set method
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发布时间：2021-06-10 - 摘要：The differential box-counting algorithm is introduced to calculate a new discriminating feature named Lacunarity, which is used to distinguish vehicle target from natural clutter in high-resolution SAR imagery in this paper. Lacunarity feature can be used to estimate quantitatively the variation, irregularity and gap size of pixel’s intensity of candidate targets. Based on the theory of scattering center, it can be shown that the vehicle image presents more irregularity and larger gaps than natural terrain’s image. Moreover, lacunarity is robust to speckle noise and is stable under changes in intensity. Finally, the real vehicle target data and natural terrain’s data in MSTAR database are applied to test the above algorithm. The discrimination performance using lacunarity is compared with Hausdorff dimension. The result shows that lacunarity is a good discriminating feature, which can eliminate most false alarms from natural terrains and most interference from the man-made targets with low false alarm probability.关键词：SAR imagery;target discrimination;scattering center;Fractal;lacunarity
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发布时间：2021-06-10 - 摘要：The multi-channel SAR image domain STAP methods, with a long coherent processing time, can achieve very high performance of clutter restrain and moving target detection. However, the array distortion and non-homogeneity environments have not been taken into consideration in the existing image domain STAP methods. This paper studies their influence on the performance of the image domain STAP, and then proposes a new multi-channel SAR image domain STAP method that can cope with array distortion and non-homogeneity environments. The introduced method first applies the Power Selection and Training （PST） method to select the training data, and then proposes a new Improved Sample Matrix Inversion （ISMI） method to remove the moving targets in the training data. With the training data eliminating the moving targets, the covariance matrix of the clutter is estimated. Afterwards the array distortion is estimated based on the covariance matrix, and the array distortion is calibrated later during the image domain STAP processing. The experiments based on real clutter data prove the validity of the introduced method.关键词：STAP;image domain STAP;array distortion;non-homogeneity
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发布时间：2021-06-10 - 摘要：Optimal site search for sitting facilities is crucial for the effective use and management of resources and it is also a common task for urban planning. The brute-force method has difficulty in solving complex site search problems especially in large scale areas. In this study, a location model is proposed based on ant colony algorithms （ACO）. It combines ant colony intelligence and GIS to solve the problems of complicated spatial optimal allocation. ACO has strong search ability for a huge volume of spatial data. At first, the algorithm is modified about the strategy of pheromone update and Tabu table adjusting to fit the sites location problem. Spatial allocation problems usually have a large set of spatial data and only a few targets. The pheromone evaporates very fast because the selected cells only amount to a small percentage of all the cells. The positive feedback is too weak to play a role in the optimization. A modification is to incorporate the strategy of neighborhood pheromone diffusion in defining pheromone updating. At the same time, an optimal result for sites selection usually does not include two near candidate cells together, so a restricted Tabu table updating strategy is adopted which resembles the strategy of neighborhood pheromone diffusion. Then another important modification is to adopt a multi-scale approach to alleviate the computational demand in conducting large-scale spatial search. This includes two phases of optimization. First, a coarser resolution is used for the identification of rough locations of targets using ACO. Then the next round of optimization is implemented by just searching the neighborhood around these initial locations in the original resolution. This two-phase procedure of optimization can thus significantly reduce the computation time. The study area is located in the city of Guangzhou. This optimization problem considers two spatial variables, population distribution and transportation conditions, which are obtained from GIS. The raster layers have a resolution of 100 × 100 m with a size of 250 × 250 pixels. A comparison experiment is conducted among the multi-scale ACO, ACO, genetic algorithms and simple search algorithms. Experiments indicate that this multi-scale ACO method can produce similar results but use much lesser computation time, compared with the single ACO method. This method has better performance than the single search method and the genetic algorithm method for solving site search problems. ACO has obtained the utility improvement of 2.7%—5.5%, compared with the single search method. ACO has slight improvement of the total utility value over the GA method, but is able to reduce computation time significantly. Its computation time is only 12.5%—29.5% and 8.8%—20.3% of those of the single search method and the GA method respectively. In conclusion, integrating ACO with GIS is important for solving real-world site selection problems. The integration allows these two techniques to be mutually benefited from each other. ACO provides an efficient distributed computation algorithm while GIS provides useful spatial information. The comparison experiment indicates that the proposed model has better performance than GA and SSA especially in the computing time for solving site search problems.关键词：ant colony optimization;GIS;site selection;simple search algorithm;genetic algorithms
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发布时间：2021-06-10 - 摘要：Based on Support Vector Machine（SVM）, a technique simulating radiative transfer forward model is presented. Using European Centre for Medium-Range Weather Forecasts （ECMWF） RTTOV87 radiative transfer forward model and 60LSD profile database, we simulate the brightness temperature received in AMSU-A instrument. Combine this brightness temperature datasets and correspondence profile datasets as training and validation database. After training the SVM network, the simulating technique is validated. The results show that SVM network describes the nonlinear projection relationship between input space and output space very well, and the simulated brightness temperature of channel 5—14 is precise. The RMS error of channel 6—14 is less than 0.1K and the mean standard deviation is less than 0.01K. In order to find whether SVM simulated brightness temperature is appropriate for temperature retrieval, muti-regression retrieval method is used to retrieve temperature profile. Experiment result shows that the SVM simulate brightness temperature is appropriate for the purpose, and the retrieval precision is not only equally but also a little more precise than the RTTOV87 simulated brightness temperature.关键词：SVM;radiative transfer forward model;RTTOV
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发布时间：2021-06-10 - 摘要：In order to decrease the spectral distortion while improving the spatial resolution during the fusion of remote sensing images, an image fusion method based on Choquet fuzzy integral is proposed in this paper. Firstly, an intensity-hue-saturation （IHS） transform is performed for multispectral images. Then the panchromatic image and the intensity component of multispectral images are decomposed using discrete wavelet transform respectively. In the wavelet domain, for the low-frequency component, the wavelet coefficients of the I component are selected directly. For the high-frequency component, the wavelet coefficients are selected according to an integrative index which is colligated with the values of variation, average gradient and energy in the local region by Choquet fuzzy integral. Further, the fused intensity component is obtained by inverse discrete wavelet transform. Finally, the fused images are obtained by inverse IHS transform. The experiment results demonstrate our proposed method effectively.关键词：remote sensing images fusion;wavelet transform;fuzzy integral;IHS transform
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发布时间：2021-06-10 - 摘要：In circumstance when there are no pure pixels exits in hyperspectral image, the endmembers extracted by traditional algorithms are usually mixing ones still. In order to solve the problem, this paper proposes an endmember extraction algorithm based on the re-analysis of near-endmember using the linear mixing model. After extracting the pixels which were most close to the pure endmembers in the image, using the convex polyhedron’s geometric characters the algorithm searches the pixels around the near-endmember and finds out the pixels in the edge of the convex polyhedron formed by the pure endmembers. Calculating the mixing coefficients of every endmember in these pixels by the laws of sins, thus, with these coefficients the pure endmember vectors could be extracted according to the constraints of linear mixing model. A hyperspectral image simulated by the real spectrums is used to investigate the performance of the algorithm. Preliminary result indicates the effectivity of the algorithm. Applying the algorithm to a real Hyperion image it can also get a better result.关键词：remote sensing;endmember extraction;linear mixing model;convex polyhedron;endmember
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发布时间：2021-06-10 - 摘要：With the successful implementation of ERS-1/2 tandem and SRTM project, InSAR has been wildly used for topographic mapping; in addition, the new global topographic mission such as TanDEM-X project is ongoing. In this paper, firstly, the impact of incidence angle on interferometric SAR DEM generation is detailed investigated from theoretical viewpoint; then, from the ENVISAT/ASAR multi-angle interferometric SAR data, the three DEMs of IS2, IS3 and IS4 swath images are generated using EvInSAR software of EarthView; finally, the impact of layover and foreshortening on DEM accuracy at different incidence angle are compared and analyzed from quantitative and qualitative viewpoints using SRTM DEM with 90m horizontal resolution and digital topographic DEM with 1∶50000 scale. The results indicate that: （1） the impact of incidence angle on DEM generation is significant and large differences exist in the result DEMs due to radar layover and foreshortening at different incidence angle. For example, the difference is over 6m between the DEMs extracted from IS2 and IS4 swath images. So, the incidence angle must be strictly selected when using InSAR for DEM generation in the mountain area. （2） The decorrelation is significant with the 35-day temporal, which is in prejudice of the overall DEM accuracy evaluation. If the data with large incidence angle and no temporal decorrelation is obtained, the further study and analysis will be implemented from more general quantitative and qualitative viewpoints.关键词：INSAR;multi-angle;DEM;layover;foreshortening
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发布时间：2021-06-10 - 摘要：In this paper, a practical scheme for assimilation of multi-temporal and multi-polarization ENVISAT ASAR data in rice crop model to map rice yield is presented. To achieve this, rice distribution information is obtained first by rice mapping method to retrieve rice fields from ASAR images, and then an assimilation method is applied to use the temporal single-polarized rice backscattering coefficients which are grouped for each rice pixel to re-initialize ORYZA2000. The assimilation method consists of re-initializing the model with optimal input parameters allows a better temporal agreement between the rice backscattering coefficients retrieved from ASAR data and the ones simulated by a coupled model, i.e., the combination of ORYZA2000 and a semi-empirical rice backscatter model through LAI. The SCE-UA optimization algorithm is employed to determine the optimal set of input parameters. After the re-initialization, rice yield for each rice pixel is calculated, and the yield map over the area of interest is finally produced. The scheme is applied over Xinghua study area located in the middle of Jiangsu Province of China during the 2006 rice season. The result shows that the obtained rice yield map generally overestimates the actual rice production by 13%, with a relative error of 11.2% at validation sites, but the tendency of rice growth status and spatial variation of the rice yield are well predicted and highly consistent with the actual production variation.关键词：assimilation strategy;remote sensing;ASAR;rice yield prediction;crop model
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发布时间：2021-06-10 - 摘要：Jinghe River Basin is chosen as a case to study vegetation degradation in Loess Plateau in this paper. Firstly, remote sensing based vegetation index （VI） and climatic aridity index are used to estimate potential vegetation index by regression model approach. The spatial distributions of current vegetation and potential vegetation in Jinghe River Basin are then obtained according to supervised classification of NDVI remote images and potential vegetation index. The status or severity of vegetation degradation is analyzed by means of the transfer possibility between vegetation types. The result shows that the main potential vegetation types of the Jinghe River Basin are broadleaved and coniferous mixed sparse forest （32.44%）, broadleaved deciduous forest （31.28%） and shrub（23.71%）. It is found that 25.08% and 13.32% of the broad leaves forest potential region were converted to cultivated land and broadleaved and coniferous mixed sparse forest, while 13.04% and 14.22% changed to shrub and aridity shrub with only 25.09% potential region remained broad leaves forest. Potential region of the broadleaved and coniferous mixed spare forest changed to cropland（26.01%）, aridity shrub（20.99%）and meadow （17.12% ） whereas potential region for shrub was dominant by meadow （30.29%） and grassland （43.21%）. Vegetation degradation is most serious in loess gully region, followed by loess hilly region in northern basin whereas vegetation degradation in mountain region of Ziwuling in eastern basin and Liupanshan in western basin are relative slight.关键词：potential vegetation;current vegetation;vegetation degradation;the Jinghe River Basin;remote sensing
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发布时间：2021-06-10 - 摘要：Presently the lookup table is adopted when corresponding relation between the position of remote sensing images and the geographic coordinates, which are involved in ground system engineering of geostationary satellites. For the corresponding geographic coordinates of sub-pixel or corresponding point of nonstandard grid nodes, which are not in lookup table, bilinear interpolation have to be introduced so that the precision loses remarkably for the image location. By deducing the formulas of geostationary satellite normalized projection at the condition of three-axis ellipsoidal parameter, the reversible equation from longitude/latitude to position on unit plane is established, which provides the mathematical reliance for lookup table for satellite image engineering. And corresponding match parameter for FY2-C application is provided after comparing with the practicing data of lookup table. The same procedure is applied to the situation of geographic coordinate system, but the inverse problem needs numerical solutions. The inverse method of geocenter coordinate system may be used as approximation when ellipsoidal parameter is close to sphere, while not applicable for fine image processing. The possibility of the application in FY2-C engineering of this reversible formulas is also discussed, with the analysis of the error distribution compared with practical data and the selection of applicable parameters for best fitting actual data.关键词：normalized projection;three-axis ellipsoid;longitude/latitude lookup table;reversible formulas;geostationary satellite;FY2-C
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发布时间：2021-06-10 - 摘要：A new method for spatial matching of data with different resolution was proposed by introducing the concept of standing and contour pixels in histo-variogram theory, and was examined in quality validation using the sea surface temperature data obtained by FY2-C satellite. For comparing satellite data with grid data, this method can reduce the spurious error resulting from changed pixel characteristics in downscaling and upscaling. For comparing satellite data with station data, this method can give relatively accurate results while requiring less precise spatial matching.关键词：histo-variogram;standing pixels;satellite product quality validation;spatial matching
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发布时间：2021-06-10 - 摘要：In this paper, after several-hundred times of comparing calculation of the hyper-spectral and Quickbird data in two land utilization survey areas, The Sym4 and Db2 are determined to be the best wavelet function in the curvature-wave transformation at last. Two hyper-spectral remote-sensing image fusion algorithms, i.e., weighted method and selected method, are given based on the curvature-wave transformation. And then the more precise fusion images are provided. In one research area, the hyper-spectral remote-sensing fusion image is benefited for the land typing and image discrimination after the images to resolve son, ridge-wave transformation, some fusions, and their inversion transformation of the hyper-spectral data. In the other research area, except for the curvature-wave transformation, the remote-sensing image matching of the hyper-spectral and the Quickbird data is finished by calculation of quadratic equation, and the fusion image of the curvature-wave transformation is better than that of wavelet transformation, and similar to the Brovey fusion image and slightly inferior of PCA fusion image after the appraising by observation, information entropy and relation analysis. It is suggested that the hyper-spectral remote-sensing image fusion algorithm can provide more precise information for the land utilization survey based on the curvature-wave transformation.关键词：curvature-wave transformation;wavelet transformation;hyper-spectral remote sensing;land utilization
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发布时间：2021-06-10 - 摘要：Due to urbanization increasing, the quantity of solid wastes in Beijing is increasing rapidly and leads to large numbers of informal solid wastes dumps. Solid wastes in these sites are usually dumped in the open air without certain environmental conservation measures, which influence the urban environment and human healthy badly. It is absolutely necessary to monitor these dumps in order to take some effective measurements to dispose them. Remote sensing technology can provide a rapid and effective way to identify and monitor the dumps, owning to its characteristics of objectivity, real-time and macro-scope view. With high spatial resolution, high frequency of revisiting and broad coverage range, Beijing-1 Microsatellite image is an important data source for urban environment monitoring. Taking the flat plain area of Beijing as study site,this paper establishes the interpretation keys of informal open-air solid waste dumps through studying their characteristics based on Beijing-1 fusion images. Via visual interpretation and automatic change detection methods, the authors studies the location and change of the open-air solid waste dumps. Compared with the field investigation data, it shows high accuracy （about 90.3%） of the indoor visual interpretation result using Beijing-1 images. However, on account of the uncertainty of the solid waste dumps characteristics, automatic change detection method can just be utilized to decrease the work of visual interpretation to find the location instead of replacing it completely.关键词：Beijing-1 Microsatellite;remote sensing;solid waste dumps;interpretation keys;change detection
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发布时间：2021-06-10 - 摘要：Among the surface sediments anomalies caused by hydrocarbon leakage of heavy oil reservoir, bleaching of red beds, enrichment of ferrous-iron and alterations of clay minerals and carbonates exhibit diagnostic spectral features. For heavy oil exploration in the western slope of Songliao Basin, ETM+7 image is used to identify anomaly caused by hydrocarbon leakage. Principal Component Analysis （PCA）, band ratio, and False Color Composition （FCC） are used in image process. Four principal components （PCs） including 1,3,4,5-PC3 （the third component of the PCA on band 1, 3, 4 and 5）, 1,3,5,7-PC3, 2,3,5,7-PC3 and 3,4,5,7-PC4 show steady spectral enhancement for the hydrocarbon-induced minerals. The PCs are combined with band ratios of 3/1, 4/3 and 7/5 for FCC. Four FCC images are selected for hydrocarbon-induced area delineation. Result indicates that the identified anomalous area is related to the geological setting and consistent with the strata sections in most area.关键词：heavy oil;hydrocarbon leakage;ETM+ 7;principal component analysis （PCA）;band ratio;false color composition （FCC）
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发布时间：2021-06-10 - 摘要：Remote sensing time-series have been applied successfully in various fields, such as vegetation change monitoring, phonological （seasonality） information extraction, land use dynamic classification etc. It is one of the most important data sources for kinds of research work & engineering project. However, due to the effect of sensor, cloud, and atmospheric conditions, there are serious residual noise in time-series data. Therefore, prior to further applications, it is need to filter residual noise to reconstruct the series. Many methods have been developed to solve this problem. In this paper, the following methods are summarized first, including Maximum Value Composite （MVC）, Best Index Slope Extraction Algorithm （BISE）, Temporal Windows Operation （TWO）, Asymmetric Gaussian Function Fitting Approach （AGFF）, Savitzky-Golay Filtering （S-GF）, Harmonic Analysis Algorithm （HAA）, Local Maximum Fitting （LMF）. MVC is more acceptable than other methods because it is useful when producing remote sensing time-series products. But the products are the primary ones and contain much residual noise. This method is helpless to reconstruct the series further. In fact, the data needed to reconstruct before applications of the products made according to MVC. BISE uses a sliding time window to capture local maxima. It requires the determination of the sliding period and a threshold for acceptable percentage increase. TWO can reduce the noise caused by cloud and atmosphere without auxiliary data. However, the requirement of the parameters from experience limits its application. AGFF and S-GF are two strategies developed in recent years. LMF, compared with HAA, first filters noise and then reconstructs the data processed. Then three most frequently-used approaches, AGFF, S-GF and HAA, are introduced in detail in terms of the basic theories, application steps and advantages & disadvantages. AGFF employs more than two combinative Gauss-shape curves to fit the series. Every combination simulates a cycle of plant life. Finally, these combinative fitting curve are joined together to represent the reconstructed data. By this strategy, every combination is independent. AGFF which is more flexible than other methods could avoid curve distortion. But the parameter, the running window used to find a consistent set of maxima and minima, is difficult to retrieve. Thus it makes the further process less reliable and steadier. S-GF is a process of smoothing and filtering in essence. Two parameters control the result; one is the scale of the smoothing window, and the other is convoluting integer. The two parameters are all obtained depending on experience. Meanwhile, a new variable, fitting-effect index is introduced to control the iteration stop. It is more advanced than the other methods which terminate the iteration by a given threshold. S-GF has received more concern because its product can clearly reflect long time trendy and local change information. Meanwhile its products are less subject to special scale and remote sensor. HAA is a term standing for a methods set which use harmonic to fit data while simulate the seasonal regulation. These methods make use of sine or cosine to fit the data and simulate the seasonal regulation which is much concerned. Two main methods of HAA are Seller Algorithm and HANTS. At last,some comments are given, discussing the defects of the approaches, and which aspects need to be improved and how to. For example, most of parameters needed in these reconstruction methods have to be decided by experience. Thus subjective errors from operator would affect the reliance and stability of products. So new strategy or improved ones need to solve this problem.关键词：remote sensing time-series;filtering;reconstruction
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发布时间：2021-06-10
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