Canopy spectral reflectance and red edge parameters were compared in different nitrogen fertilizer levels and different removing treatments in this study. It was also analyzed about the correlation between nitrogen content of ear, leaf, stem and their corresponding red edge parameters. The results indicated that canopy spectral reflectance changed with different treatments and nitrogen levels. In addition, it showed that red edge position moving to the longer or shorter wavelength in different degree, which not only reflected that senescence became more and more serious with the leaf position descended, but also showed that disturbance of soil background increased with the vegetation coverage decreased. The first derivative curve of red edge reflectance had two peaks, and the latter peak showed higher than the former one. Furthermore, their first derivative of reflectance showed N1>N2>N0. The correlation between leaf nitrogen content of different leaf position and red edge parameters increased with their contribution to canopy increasing, and some of them were in significant levels. The red edge peak shapes of ears, leaves and stems removed from plants were different for their different nitrogen fertilizer levels. Besides, their first derivative curve of red edge reflectance had three peaks, which was needed to further study. The results can help to understand the contribution of nitrogen content in different organs or leaf position to canopy spectra, and be favor to fertilizing in times using the lower leaf who had more sensitive to nutrient deficiency.
The maximum likelihood classification (MLC) is one of the most popular methods in remote sensing image classification. Because the maximum likelihood classification is based on spectrum of objects, it cannot correctly distinguish objects that have same spectrum and cannot reach the accuracy requirement. In this paper,we take an area of Langfang of Hebei province as an example and discuss the method of combining texture of
panchromatic image with spectrum to improve the accuracy of CBERS02 CCD image information extraction.Firstly, analysis of the textures of the panchromatic image(CCD5) is made by using texture analysis of Gray Level Coocurrence Matrices and statistic index. Then optimal texture window size of angular second moment,contrast, entropy and correlation is obtained according to variation coefficient of each texture measure for each
thematic class. The chosen optimal window size is that from which the value of variation coefficient starts to stabilize while having the smallest value. The output images generated by texture analysis are used as additional bands together with other multi-spectral bands(CCD1-4) in classification. Objects that have same spectrums such as grass land and cultivate land are distinguished. Finally, the accuracy measurement is compared with the classification based on spectrum only .The result indicates that the objects with same spectrum are distinguished by using texture analysis in image classification, and the combination improves more than spectrum only in classification accuracy.
A remote sensing study on the urban impervious surface and its relation with urban heat island has been carried out taking Quanzhou city of SE China as an example. The remotely-sensed data have been obtained from two Landsat TM images of 1989 and 1996. Ridd (1995) indicated that the impervious surface area(ISA) and the fractional vegetation cover (Fr) have an inversely relation in urban areas. Accordingly, we obtained the spatial patterns of the impervious surface area by calculating fractional vegetation cover derived from the NDVI. The study revealed that the impervious surface area of the study area increased significantly from 1989 to 1996, expanding mainly southeastwards. Furthermore, this paper discussed the quantitative relation between the impervious surface area and the urban heat islands. The land surface temperature has been obtained from band 6 of the Landsat TM images. Based on the regression analysis between the impervious surface area and the land surface temperature, it can be concluded that the impervious surface area has a direct response to the increase of the urban heat island phenomenon.
For pre-launch field radiometric calibration for the visible channel of scanning radiometer of satellite FY-2-05, the traditional radiation calibration method has been adopted, on the other hand, a novel method called Detector Based Reflectance Calibration (DBRC) which is independent of spectral response function of scanning radiometer has been advanced. Because the integral radiation of the Standard White Reference is in
direct proportion to that in a certain narrow wave band, through the selection of bands from the eight channels of the high accuracy Multi-channel radiance standard detector, the integral response radiation of the FY-2scanning radiometer can be replaced by the narrow wave band response radiation of the high accuracy Multichannel radiance standard detector. Therefore, the calibration coefficients can be determined directly by the
high accuracy Multi-channel radiance standard detector. The uncertainty of traditional radiation calibration is about 6. 0%～6. 4%, while the uncertainty of DBRC reaches 5. 4%. The results of the experiments demonstrate that the uncertainty of BRDC, which is based on the high accuracy cryogenic radiometry system,is much higher than that of the traditional radiation calibration which is based on the standard radiation source.
Land surface temperature in six specific time since 1980 s were retrieved from TM and ETM+remotely sensed data. The temporal-spatial evolvement patterns were analyzed and the results showed that the range of urban heat island in Shanghai city enlarged, and so did intensity. The concentrated distributions of UHI gradually turned to dispersed situation. The sprawl of built-up area is the main cause of enlargement of UHI' s range and intensity. Correlation and regression analysis suggest that there is obvious negative correlationship between vegetation abundance and land surface temperature. It is very important to decrease UHI by increasing vegetation abundance in urban environmental management.
The obvious limitation of deriving cloud motion winds is that cloud-free regions are left unsampled. So in this paper we derive winds from water vapour images of geostationary meteorological satellite. Water vapour motion vector of the tracers in water vapour images can be computed by cross-correlation technique. For the determination of the height of water vapour motion wind in cloud-free regions, the average weight value of water vapour brightness temperature of water vapour tracer is compared with the vertical temperature profile.The comparision of derived water vapour motion winds and rawinsonde winds or NCEP winds shows that thederived water vapour winds are correct, which can make for the limitation of derived cloud motion winds to some extent.
Ground survey is restricted by the difficulty of access to wide-range and dynamic tidal flat. The lack of terrain handicaps exploration and development of tidal flat. In this article, we selected Chongming Dongtan as an experiment area. On the analysis of spectrum characteristics of multi-temporal remote sensing images(1999～2004), waterlines were extracted from different bands according to tidal conditions. The assignment of an elevation to the waterlines was performed according to two elevation survey profiles. The waterlines labeled elevation were used to construct TINs(Triangulated Irregular Networks).Then an interpolation for each grid elevation was performed in accordance with the associated triangle. Finally, quantitative check of the result was examined according as the other two measurement profiles. The results indicate that the standard deviation of the approach is 0.4 m and 0.7 m, respectively, which eliminates the effects of unavailable tidal height and discrepancy of waterlines on DEM precision.
The spatial interpolation methods of Inverse Distance Weighted (IDW), Spline and Kriging are utilized for comparison study on spatial interpolation of annual average snow depth from 113 observatories in the west of China (79.05°～103.57°E,27.17°～48.05°N). The principles of these three methods are different from each other. IDW determines cell values using a linear-weighted combination set of sample points. Spline estimates values using a mathematical function that minimizes overall surface curvature. And ordinary Kriging is a powerful statistical interpolation method which assumes that the distance or direction between sample points reflects a spatial correlation that can be used to explain variation in the surface. Compared with the unsatisfactory interpolation results of IDW and Spline, the result of ordinary Kriging is more close to the real snow depth distribution and can represents the spatial structure of snow depth distribution better. The main reasons which affect the precision are the small number of observatories and their asymmetric spatial distribution. However, the accuracy of spatial interpolation can be improved through reasonable design of sampling, combining deterministic and stochastic methods, and considering the influencing factors of snow distribution such as the terrain and climate.
Water is the most actively factor in the world and presents all kinds of configurations, which formed from a long time. We can open out the pattern of temporal and spatial change and forecast the trend of feature.Based on the remote sensing image and ARCGIS、ENVI, we set up spatial information database and chose pattern indexes, such as patch density, edge density, shape index, to analyze the evolution and spatial pattern of water in the west part of jilin province. The research indicated that, total area of water in the study area was 2 018.22 km2in 1979, while in 2001 reduced to 1 488.12 km2, spatial pattern of water landscape has taken grate changes, the main effect factor is the land desertification, grassland degradation and overexploitation of human. We express the characteristic of water change based on the Landscape exponential calculating of water element.
The interactive visualization of geological field practical scenery has reproduced field geological information, boosted up the disciplinary and essential cognition of acquired data in the theoretic research and practical application of geological teaching. This paper is mainly discussed establishment of real time emulational environment based on Vega.We can get the GIS data which is from relief map ,and then change the planar dispersed data into three-dimensional continuous data ,lastly, we will build three-dimensional terrain surface and space object model. Simultaneously, as the RS data can record real information of terrain surface continuously, we can use it as the dummy landscape texture mapping to reflect actual geological scenery. A three-dimensional visual ramble of the geological scenery in the geological field practical base has been achieved.
Remote sensor imagery geometric precision correction is an indispensably technological preparation for imagery processing. In this paper, a method of ETM imagery geometric precision correction for Areletuobie,Xinjiang based on ERDAS IMAGINE is discussed: firstly, have the coordinate of the relief maps matching based on ArcGIS; secondly, do geometric rough correction; finally, do geometric precision correction. Through the error analysis for correction result and compared with the vector data of that area we can draw a conclusion that the correction accuracy of this method was less than one pixel and this method could be used to achieve the demand of work.
As for a distribute target, the change of radar look angle and topographical slopes will arouse the polarization orientation angles shifts. On the contrary, when the radar look angle is known, topographical slopes can be estimated from the variance of the polarization orientation angle. Thus, in this paper, we review and summarize all kinds of estimation techniques proposed for the polarization orientation angles induced by terrain slopes so far, and evaluate the merit and deficiency of those methods. At the same time, besides the selection of algorithms, others factors that affect the accuracy of orientation angle estimations are discussed, and the current research and applications fields of orientation angles will also be presented.
The optimal polarization for sea surface ship detection with synthetic aperture radar (SAR) has been studied using SIR-C SAR C-band and L-band full-polarization data. The radar backscattering properties of the sea surface ship and the ratio of the ship' s normalized radar cross section to the ocean' s normalized radar cross section have been analyzed. It is shown that the main imaging mechanism of the sea surface ship is the two-corner backscattering. The HV polarization has the largest signal to noise ratio of the normalized radar cross section among the linear polarizations. However, the circular polarization is better than the linear polarization for sea surface ship detection. The C-band radar backscattering properties are different from L-band radar backscattering properties. The signal to noise ratio of the normalized radar cross section at L band is larger than the signal to noise ratio of the normalized radar cross section at C band. The results indicate that the optimal polarization for sea surface ship detection with SAR is the circular polarization at L band.
Target decomposition comprises coherent target decomposition based on Sinclair matrix and part-coherent target decomposition based on Mueller matrix, Krogager decomposition is a kind of coherent target decomposition. By Krogager decomposition, a symmetric Sinclair matrix can be decomposed into three components: sphere component, diplane component, and helix component. This is an important way to extract properties from polarimetric synthetic aperture radar (SAR) image. In this paper, decomposition coefficients of three components are acted as polarimetric scattering properties. Samples are composed of three decomposition coefficients. Multi-class classifier can be designed using support vector machines (SVM) based on statistical learning theory, a new algorithm of target classification is proposed, and classification experiments to polarimetric SAR data are done. The results indicate it is feasible and efficient to classify polarimetric SAR image by combining Krogager decomposition and SVM. Discrimination of classification results by choosing different parameters is rather big. Thus, parameters selecting is very important to SVM classifier.
The registration of the complex SAR images is a key step for interferometric synthetic aperture radar(InSAR). The gross error of control-points in the registration of the complex SAR images will decreasregistration accuracy. This paper investigates the reasons of the control-point gross errors. And a new method,which integrates overall test and Baarda data snooping, is proposed to detect and eliminate the gross errors.Two pairs of ENVISAT ASAR images from BAM, Iran were used to test the proposed method. The testing results show that the error from registration of the complex SAR images is less than 0.1 pixel (RMS). Thus,the SAR image registration accuracy is improved significantly.
With the all-weather and day-night time imaging capability, Synthetic Aperture Radar (SAR) plays an important role in detecting inundate extent, and has the advantaged advantage. The traditional pixel-based methods have limitation in detecting inundate extent, so an object oriented methodology has been introduced here. In this paper, we mainly discuss the potential of object oriented method used in automatic detecting inundate extent using multi-polarized ENVISAT ASAR image. This method can provide a new method for flood monitoring, assessment and extract the flood extent.
Different ground objects have different backward scatter energy to the electromagnetic wave that the SAR transmits. The total dynamic range of a X-band SAR' s receiving signal is greater than 70 dB.Unfortunately, the quantization bit of the ADC that can be used for Space-borne system is normally 8 bits,which equal to about a dynamic range of 48 dB. The AGC technology can be used to match the dynamic range between the receiving signal and ADC. According to the implementing method, AGC can be sorted into Analog AGC and Digital ADC. Both Analog and Digital ADC automatically adjust the receiver' s gain according to the changing of the receiving signal amplitude, but the adjust method of Analog AGC is analog, the feedback
control signal is continuous analog signal, so the gain value tuned by the AGC circuit can not be exactly recovered in the imaging processing in the ground. However, because the gain adjust value is digital, it can be exactly recovered in the imaging processing in the ground in a Space-borne SAR system with the Digital AGC circuit. By this reason, the Digital AGC is usually adopted in a Space-borne SAR system that has radiation precision requirement. In the first, this paper introduces and compares the implementing methods of the analog AGC and digital AGC. A new gain control method called“two-threshold step-tune”for the Digital AGC is given. The“two-threshold step-tune”method use step-tune versus one-time adjust method to attenuate the receiving signal step by step when the signal level feed the ADC exceeds the ADC dynamic range. Two thresholds versus one threshold are set as a judging level to switch the AGC function. The“two-threshold” method can effectively eliminate the surge phenomenon that“one-threshold”brings. Working with the Digital Attenuator,“two-threshold step-tune”method is very applied to implement a digital AGC circuit. In the end,this paper gives some the experiment results about the“two-threshold step-tune”Digital AGC, the experiment results indicate that the digital AGC design powered by this method has good astringency, and the signal passing through this digital AGC circuit can exactly resume its amplitude in the post signal processing.
In high spatial resolution sensing image, it was hard to discriminate inshore ships from harbors because of the similarity of gray and texture for both targets. The half ellipse shape of the inshore ship in the contour was one of the features with better distinguish ability. An alterable included angle chain (AIAC)-based curve description was introduced to describe the inshore ship contours in this paper, which was invariant to rotation, scaling and translation. In the following an improved AIAC generation method was presented. Finally an AIAC-based inshore ship detection approach was proposed by describing and matching the counter feature of inshore ship by AIAC. Experiments based on the satellite sensing image demonstrated that the algorithm proposed could solve the inshore ship detection problem in a certain extent.
Satellite multi-spectral images which captured from independent camera photography system of smallsatellite have nonlinear errors in spatial position. To this complicated problem, the paper introduces an automatic registration method to match multi-spectral images automatically, in which the mutual information,genetic algorithm and MQ geometric correction models are intergraded. In its algorithm, the mutual information is used as a similarity function of the registration problem, which can achieve an accurately registration precision; and the genetic algorithms are utilized to search the optimization value fast by its characteristics of finding global optima rapidly and efficiently; Meanwhile, the MQ geometric correction models are also adopted to develop a correspondence between the input and output images quickly. From the experimental results, it seems that this method can achieve a better accurate automatic registration results in bands nonlinear geometric relationships between multi-spectral images, whose error of the entire matching is less than a pixel.
The nonlinear least square (NLS) method is used to estimate the mispointing on radar altimeter, and the results of analysis and simulation show that this estimation accuracy meets the requirements. A new method is also brought forward to correct the altitude measurement error introduced by the mispointing.
Interferometric Synthetic Aperture Radar (InSAR) has many inimitable advantages in the field of digital terrain modeling. In application, the phase of the earth' s surface of water in the scene derived is not reliable, because the backscattering coefficient of these areas is very small and the coherence is of low quality.These areas have a bad effect on the quality of DEM, so as the quality of radar orthophoto map. In this paper, we present an approach in the field of phase for the earth' s surface of water based on radar-terrain imaging geometry. Experiment result of DEM generated by data obtained from the air-borne InSAR platform shows the quality of DEM has been improved much, this demonstrates effectiveness of the algorithm.
SAR system has important properties at the operational level, such as its capability of acquiring data in all weather and time conditions. SAR imagery is an important source data for change detection and its application is so promising. In this paper, we systematically describe the whole process of change detection using SAR images. Firstly, we present the pre-process of SAR images, which comprise of calibration and geometric correction. In the second part, we present the art in SAR change detection, including the methods of difference image, hypothesis test, predictive models and coherence models. As the development of SAR technique and computer science, more and more new approaches for change detection using SAR images are proposed; in this paper, we illustrate some representative works. Then, the principles for performance evaluation and the post-process of change detection are discussed. Lastly, the oriented development of SAR change detection is discussed at our viewpoint. We hope that our classification of algorithm using SAR images into a relatively small number of categories will provide useful guidance to the algorithm designers in SAR researcher field.
With the availability of multisensor, multitemporal, multiresolution and multifrequency image data from operational Earth observation satellites, the fusion of digital image data has become a valuable tool in remote sensing image processing. For the full exploitation of increasingly sophisticated multisource data, a lot of image fusion algorithms have been developed. In order to comprehensively understand the development of image fusion technologies in China, this paper reviews the traditional fusion algorithms and some improved fusion algorithms based on traditional HIS, Brovey, PCA and Wavelet fusion in detail. In addition, some new fusion algorithms are also introduced. Problems and prospects of image fusion are addressed simply for the attention of future researches in related fields. As multisource image fusion is a widely applied technique for various research fields, a comprehensive understanding of the image fusion algorithms would be beneficial for the choice of data and image quality control for different purposes of researches.
