A simple empirical topographic correction method for ETM+ imagery

A simple topographic correction approach, the Variable Empirical Coefficient Algorithm (VECA), was developed using theoretical and statistic analyses of the radiance values of remotely sensed data acquired for rugged terrain and the cosine of the solar illumination angle (cos i). Visual comparison and statistical analysis were used for evaluation of the proposed algorithm and the performance of the VECA approach was compared with 10 commonly used methods. The test site selected for this study is located on the south hill of the Qinling Mountain in Shanxi province, China, and the remotely sensed data used were from Landsat‐7 Enhanced Thematic Mapper Plus (ETM+) images. The results indicate that the Cosine‐T, Cosine‐C, sun–canopy–senor (SCS) and Cosine‐b correction have the problem of overcorrection, and the other corrections can be classed into three ranks: the VECA, b correction and C models performed the best, followed by the Teillet‐regression correction model, and the SCS+C, Minnaert and Minnaert‐SCS corrections performed the worst. The proposed VECA correction and the b correction are the most capable of removing the topographic effects of the ETM+ image. The VECA is not only simple in theory but also easy to operate, indicating that the VECA is an effective topographic correction tool in remote sensing techniques.     

A simple and effective radiometric correction method to improve landscape change detection across sensors and across time

Satellite data offer unrivaled utility in monitoring and quantifying large scale land cover change over time. Radiometric consistency among collocated multi-temporal imagery is difficult to maintain, however, due to variations in sensor characteristics, atmospheric conditions, solar angle, and sensor view angle that can obscure surface change detection. To detect accurate landscape change using multi-temporal images, we developed a variation of the pseudoinvariant feature (PIF) normalization scheme: the temporally invariant cluster (TIC) method. Image data were acquired on June 9, 1990 (Landsat 4), June 20, 2000 (Landsat 7), and August 26, 2001 (Landsat 7) to analyze boreal forests near the Siberian city of Krasnoyarsk using the normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and reduced simple ratio (RSR). The temporally invariant cluster (TIC) centers were identified via a point density map of collocated pixel VIs from the base image and the target image, and a normalization regression line was created to intersect all TIC centers. Target image VI values were then recalculated using the regression function so that these two images could be compared using the resulting common radiometric scale. We found that EVI was very indicative of vegetation structure because of its sensitivity to shadowing effects and could thus be used to separate conifer forests from deciduous forests and grass/crop lands. Conversely, because NDVI reduced the radiometric influence of shadow, it did not allow for distinctions among these vegetation types. After normalization, correlations of NDVI and EVI with forest leaf area index (LAI) field measurements combined for 2000 and 2001 were significantly improved; the r² values in these regressions rose from 0.49 to 0.69 and from 0.46 to 0.61, respectively. An EVI “cancellation effect” where EVI was positively related to understory greenness but negatively related to forest canopy coverage was evident across a post fire chronosequence with normalized data. These findings indicate that the TIC method provides a simple, effective and repeatable method to create radiometrically comparable data sets for remote detection of landscape change. Compared to some previous relative radiometric normalization methods, this new method does not require high level programming and statistical skills, yet remains sensitive to landscape changes occurring over seasonal and inter-annual time scales. In addition, the TIC method maintains sensitivity to subtle changes in vegetation phenology and enables normalization even when invariant features are rare. While this normalization method allowed detection of a range of land use, land cover, and phenological/biophysical changes in the Siberian boreal forest region studied here, it is necessary to further examine images representing a wide variety of ecoregions to thoroughly evaluate the TIC method against other normalization schemes.     

矢量阵一种简单的相位误差校正方法

分析了矢量水听器阵的阵列流型和误差模型,针对矢量水听器阵列声压和振速通道存在相位误差问题,应用常规波束形成方法和MUSIC方法进行方位估计误差大。并对通道存在估计性能下降的问题,提出了一种简单的相位误差校正方法。利用阵列流型向量在信号子空间的投影,得出存在相位误差的阵列流型向量就是信号子空间的特征值为＂一＂的特征向量,通过与精确的阵列流型向量比较求出矢量阵的相位误差。最后,修正矢量阵的相位误差,得到准确的方位估计能力。通过计算机仿真,验证了算法的可行性和准确性。     

SIFT特征匹配的辐射畸变图像相对校正新方法

针对常规相对辐射校正方法对未配准的主从图像对校正效果欠佳的问题,在分析了辐射畸变图像的成因与特点以及相对校正的优势之后,提出了一种基于SIFT特征匹配的相对辐射校正算法.从SIFT特征的不变性出发,分别提取主从图像对的SIFT特征并进行匹配,对匹配点的灰度值进行最小二乘回归分析,得到线性变换系数,最后通过线性变换得到校正结果.实验结果表明,此方法能够有效地减小未配准主从图像对之间的辐射差异,并在复杂光照环境下的光流场计算中得到成功的应用.     

Image correction for radiometric effects in remote sensing

A general classification of radiometric correction methodologies yields new insights into related procedures as they are implemented typically on image analysis systems. Incorrect results can be obtained from the inappropriate application of different types of corrections related to physical phenomena which give rise to radiometric distortions in a scene. The major types of radiometric correction are reviewed as they apply to digital images acquired by satellite sensors in the visible and infrared portions of the spectrum.     

An approach for the relative calibration of radar imagery

In this paper an approach for the relative calibration of a SLAR image is discussed. By the use of a calibration curve, it has proved possible to transform raw radar image data into a relatively calibrated form. The results obtained by the use of such procedure show that various features on a radar image are separable across the whole swath.     

A simple correction method for the MODIS surface reflectance product over typical inland waters in China

The Moderate Resolution Imaging Spectroradiometer (MODIS) has the advantage of providing continuous, global, near-daily spatial measurements, and has greatly aided in understanding physical, optical, and biological processes in the global ocean biosphere. However, little research has been implemented for the remote-sensing monitoring of global inland waters. One important factor is that there is no operational atmospheric correction method designed for global inland waters. The MODIS surface reflectance product (MOD09) provides surface reflectance data for land at the global scale, but it does not offer accurate atmospheric correction over inland waters because of the constraints of its primary correction algorithm. The purpose of this article is to provide a simple and operational correction method for the MOD09 product to retrieve the water-leaving reflectance for large inland waters larger than 25 km². The correction method is based on an analysis of additive noises in MOD09 data over inland waters and on the adoption of two assumptions. Field-measured data collected in three typical inland waters in China were used to assess the performance of the correction method to ensure its applicability for waters in different conditions. The results show acceptable agreement with field data over the three inland waterbodies, with a mean relative error of 17.1% in visible bands. Our study demonstrates that the MOD09 correction method is moderately accurate when compared with the optimal method for specific waterbodies, but it has the potential for use in operational data-processing systems to derive water-leaving reflectance data from MOD09 data over inland waters in a variety of conditions and large regions.     

A sun glint correction method for hyperspectral imagery containing areas with non-negligible water leaving NIR signal

Present sun glint removal methods overcorrect data collected in very shallow (less than 2 m) waters if the sensors used do not have bands in far infrared part of the spectrum. The reason is assuming of zero water leaving signal at near infrared (NIR) wavelengths. This assumption is not valid in very shallow waters, but also in areas where aquatic vegetation reaches water surface and in case of phytoplankton blooms that reach very high biomass or form surface scum. We propose an alternative method that can be used for successful glint removal even if the sensor does not have spectral bands beyond 800 nm. The proposed method utilises the presence and depth of the oxygen absorption feature near 760 nm as an indicator of glint contamination. This method allows removing sun glint from hyperspectral imagery preserving shape and magnitude of reflectance spectra in the cases where the negligible water leaving NIR signal is not valid.     

A simple method for detection and counting of oil palm trees using high-resolution multispectral satellite imagery

In the past, oil palm density has been determined by manually counting trees every year in oil palm plantations. The measurement of density provides important data related to palm productivity, fertilizer needed, weed control costs in a circle around each tree, labourers needed, and needs for other activities. Manual counting requires many workers and has potential problems related to accuracy. Remote sensing provides a potential approach for counting oil palm trees. The main objective of this study is to build a robust and user-friendly method that will allow oil palm managers to count oil palm trees using a remote sensing technique. The oil palm trees analysed in this study have different ages and densities. QuickBird imagery was applied with the six pansharpening methods and was compared with panchromatic QuickBird imagery. The black and white imagery from a false colour composite of pansharpening imagery was processed in three ways: (1) oil palm tree detection, (2) delineation of the oil palm area using the red band, and (3) counting oil palm trees and accuracy assessment. For oil palm detection, we used several filters that contained a Sobel edge detector; texture analysis co-occurrence; and dilate, erode, high-pass, and opening filters. The results of this study improved upon the accuracy of several previous research studies that had an accuracy of about 90–95%. The results in this study show (1) modified intensity-hue-saturation (IHS) resolution merge is suitable for 16-year-old oil palm trees and have rather high density with 100% accuracy; (2) colour normalized (Brovey) is suitable for 21-year-old oil palm trees and have low density with 99.5% accuracy; (3) subtractive resolution merge is suitable for 15- and 18-year-old oil palm trees and have a rather high density with 99.8% accuracy; (4) PC spectral sharpening with 99.3% accuracy is suitable for 10-year-old oil palm trees and have low density; and (5) for all study object conditions, colour normalized (Brovey) and wavelet resolution merge are two pansharpening methods that are suitable for oil palm tree extraction and counting with 98.9% and 98.4% accuracy, respectively.     

A new method for mapping macromolecular topography

A new method, using circular variance, is introduced for mapping macromolecular topography. Circular variance, generally used to measures angular spread, can be used to characterize of molecular structures based on a simple idea. It will be shown that the circular variance of vectors drawn from some origin to a set of points is well correlated with the degree to which that origin is inside/outside the chosen points. In addition, it has continuous derivatives that are also easy to compute. This concept will be shown to be useful for: (i) distinguishing between atoms near the surface of a macromolecule and those in either the deep interior or remote exterior; (ii) identifying invaginations (even shallow ones); and (iii) detecting linker regions that interconnect two domains.     

Effects of corn on C- and L-band radar backscatter: A correction method for soil moisture retrieval

This paper discusses the effects of vegetation on C- (4.75 GHz) and L- (1.6 GHz) band backscattering (σ^o) measured throughout a growth cycle at incidence angles of 15, 35 and 55°. The utilized σ^o data set was collected by a truck mounted scatterometer over a corn field and is supported by a comprehensive set of ground measurements, including soil moisture and vegetation biomass. Comparison of σ^o measurement against simulations by the Integral Equation Method (IEM) surface scattering model (Fung et al., 1992) shows that the σ^o measurements are dominated either by an attenuated soil return or by scattering from vegetation depending on the antenna configuration and growth stage. Further, the measured σ^o is found to be sensitive to soil moisture even at peak biomass and large incidence angles, which is attributed to scattering along the soil-vegetation pathway.For the simulation of C-band σ^o and the retrieval of soil moisture two methods have been applied, which are the semi-empirical water cloud model (Attema & Ulaby, 1978) and a novel method. This alternative method uses the empirical relationships between the vegetation water content (W) and the ratio of the bare soil and the measured σ^o to correct for vegetation. It is found that this alternative method is superior in reproducing the measured σ^o as well as retrieving soil moisture. The highest retrieval accuracies are obtained at a 35° incidence angle leading to RMSD's of 0.044 and 0.037 m³ m^− 3 for the HH and VV-polarization, respectively. In addition, the sensitivity of these soil moisture retrievals to W and surface roughness parameter uncertainties is investigated.     

A standard index of spatial resolution for distributed targets in synthetic aperture radar imagery

In this article we outline the need for a consistent method of quoting synthetic aperture radar (SAR) resolution given the influence of speckle upon SAR images. Standard measures of resolution depend upon the separability of point targets; however, this is not a useful analogy in the context of SAR. We contend that quoting resolution for a 3–4-look product may be unrealistic given the influence of speckle. Our approach considers the separability of targets that differ in intensity by a known contrast ratio, with a ratio of 2, that is, 3 dB difference, used as the threshold value. It is demonstrated that 12 looks represents a more realistic estimate of the capabilities of the system and should be used to quote an equivalent spatial resolution (ESR) when describing potential instrument performance.     

Application of parallel computing methods to the processing of sea-surface radar imagery

The capabilities of advanced parallel computing methods in processing and identification of seasurface radar imagery are investigated. Their application for the real-time analysis of large-area images is justified. Based on the methods developed by the authors of this paper, estimates are given for the mass, dimensions, and power consumption of a special-purpose onboard processor needed for processing sea-surface radar imagery.     

A method to account for shoot scale clumping in coniferous canopy reflectance models

The three-dimensional structure of a coniferous shoot gives rise to multiple scattering of light between the needles of the shoot, causing the shoot spectral reflectance to differ from that of a flat leaf. Forest reflectance models based on the radiative transfer equation handle shoot level clumping by correcting the radiation attenuation coefficient with a clumping index. The clumping index causes a reduction in the interception of radiation by the canopy at a fixed leaf area index (LAI). In this study, we show how within-shoot multiple scattering is related to shoot scale clumping and derive a similar, but wavelength dependent, correction to the scattering coefficient. The results provide a method for integrating shoot structure into current radiative transfer equation based forest reflectance models. The method was applied to explore the effect of shoot scale clumping on canopy spectral reflectance using simple model canopies with a homogeneous higher level structure. The clumping of needles into shoots caused a wavelength dependent reduction in canopy reflectance, as compared to that of a leaf canopy with similar interception. This is proposed to be one reason why coniferous and broad-leaved canopies occupy different regions in the spectral space and exhibit different dependency of spectral vegetation indices on LAI.     

Signature extension through space for northern landcover classification: A comparison of radiometric correction methods

Northern landcover mapping for climate change and carbon modeling requires greater detail than what is available from coarse resolution data. Mapping landcover with medium resolution data from Landsat presents challenges due to differences in time and space between scene acquisitions required for full coverage. These differences cause landcover signatures to vary due to haze, solar geometry and phenology, among other factors. One way to circumvent this problem is to have an image interpreter classify each scene independently, however, this is not an optimal solution in the north due to a lack of spatially extensive reference data and resources required to label scenes individually. Another possible approach is to stabilize signatures in space and time so that they may be extracted from one scene and extended to others, thereby reducing the amount of reference data and user input required for mapping large areas. A radiometric normalization approach was developed that exploits the high temporal frequency with which coarse resolution data are acquired and the high spatial frequency of medium resolution data. The current paper compares this radiometric correction methodology with an established absolute calibration methodology for signature extension for landcover classification and explores factors that affect extension performance to recommend how and when signature extension can be applied. Overall, the new normalization method produced better extension and classification results than absolute calibration. Results also showed that extension performance was affected more by geographical distance than by differences in anniversary dates between acquisitions for the range of data examined. Geographical distance in the north-south direction leads to poorer extension performance than distance in the east-west direction due in part to differences in vegetation composition assigned the same class label in the latitudinal direction. While extension performance was somewhat variable and in some cases did not produce a best classification result by itself, it provided an initial best guess of landcover that can subsequently be refined by an expert image interpreter.     

A method for the correction of drift in movement analysis

A method is proposed for the correction of drift over cyclic three-dimensional kinematic data during treadmill locomotion. An adaptive least-squares drift correction algorithm (ALSDC) is developed from the operational definition of no drift. This method includes automatic selection of least-squares polynomial degree and sequential processing of large data sets.     

The geometric correction of SAR imagery for the analysis of lineaments

The geometric correction of SAR images is required for many applications that entail the merging of SAR images with other data sources. One example of such applications is the mapping of geological features from SAR images. An accurate model-based geometric correction is computer and labour intensive. When a large number of images are used, this task can be prohibitive and it is then quicker to use an empirical method. This approach has been compared to the model approach and the reported results are conflicting. In some studies it has been argued that the empirical method can produce accurate geocorrection in areas of limited relief. In other studies, however, the positional accuracy using that method has been found to be unacceptable. In this Letter it is argued that in some applications, positional accuracy may not be of utmost importance and that more relevant measures such as the accuracy of orientation should be used. A geometrical method is designed to investigate the bias in orientation when an empirical method is used.     

Normalization of Landsat thermal imagery for the effects of solar heating and topography

This paper is an investigation of three simple normalization procedures for suppressing the effects of solar heating and topography in daytime thermal data. The first method is the hyperspherical direction cosine (HSDC) transformation, which separates the pixel vector into an illumination/albedo component and a spectral component. The second method, a model correction, is based on the assumption that, once an elevation correction using the normal lapse rate has been applied, temperatures are proportional to the instantaneous solar heating as measured by the cosine of the solar illumination incidence angle. The third method is a statistic-empirical correction. These three normalization methods were applied to a test site in the Humboldt Range, Pershing County, Nevada, using Landsat Thematic Mapper data. It was found that geological patterns were much clearer in the normalized data than in the original temperature information. The HSDC correction brought out lithological differences, helped discriminate between gravels and spectrally similar sedimentary rocks and resulted in a significant increase in classification accuracy. The model correction appeared to inadequately compensate for the cool temperatures found at high elevations, and therefore underestimates the actual decline in temperature with elevation. Nevertheless, the rock contacts are relatively clear, and the classification produced the second highest overall accuracy. The statistic-empirical classification resulted in improved elevation correction, but it over-corrected north-facing slopes and produced only intermediate improvements in accuracy.     

Geometric correction and radiometric normalisation of NOAA AVHRR data for fisheries applications

Sea surface temperature (SST) has been found useful for locating potential fishing grounds (PFGs). Thermal data of the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) was acquired using a microcomputer (PC/AT 486) based Direct Reception and Processing Terminal (DRPT) developed in-house to map surface thermal fronts. Geometric correction using orbital ephemeris and ground control points (GCPs) resulted in locational accuracy of 1·73 km by 2·1 km. Besides, the corrections for artificially lowering SST in case of passes with large satellite zenith angles (LSZA) through a radiance normalization based on the mean vectors and dispersion matrices to make it comparable with small satellite zenith angle (SSZA) pass is presented in this letter.