The Permanent Scatterers Technique with Large Application Potential
Though in some areas of good condition remarkable application results have been achieved by using differential synthetic aperture radar interferometry (D-InSAR), to be regrettable, temporal decorrelation strongly confines the wide application of D-InSAR, and atmospheric phase screen also affects the accuracy of D-InSAR measurements. This two problems can be overcome in large extent by using Permanent Scatterers Technique (PST) developed in late years. Even if no fringes can be seen generating single interferogram, surface deformation measurements with millimetric accuracy can be obtained by using PST which based on series of temporal SAR images and on a subset of image pixels corresponding to phase stable areas. So PST greatly enhances the circumstances applicability of interferometry measurement and its accuracy, having been considered as an important breakthrough in interferometry research fields, which can produce large actual application potential. This paper introduces with emphasis on the principle of PST and its procedures, then discusses the application examples of PST and the contrast relation between PST and conventional D-InSAR. We expect the paper will be helpful for civil research work and applications of this advanced interferometry processing method.
In this paper, the hyperspectral data of cotton canopies grown in north Xinjiang at the main growing stage under water stress are derived by using an ASD spectrocoparator made in USA, the rededge integral areas are used to estimate the total N content in leaves of cotton canopies, and the analyzing method based on the spectral position variables is derived from the first differential spectral data. An analysis on the correlation between the red-edge integral areas (used as the independent variables) and the total N contents in leaves of cotton canopies (used as functions) is carried out so as to develop a mathematical model about the correlation between the red-edge integral areas and the total N contents in canopy leaves of cotton variety of Xin Luzao No.6. The correlations between the chlorophyll contents and the total N contents in separate leaves of cotton canopies under the different irrigation water volumes are researched. The results show that there is a significant positive correlation between the chlorophyll content and the total N content in leaves of cotton canopies (R=0.8723, n=39), and the data of chlorophyll contents can be used to effectively estimate the total N content in separate cotton leaves; there is also a significant correlation between the red-edge integral areas and the total N contents in leaves of cotton canopies,and the correlation coefficient is 0.7394 (n=40). The total N contents in canopy leaves of cotton varieties of Xin Luzao No. 6 and No.8 can be accurately estimated by using the developed model, and the values of RMSE are 0.3859 and 0.4272 respectively. It is considered that there is a potentiality to use the variables of red-edge integral areas for predicting the total N contents in leaves of cotton canopies, and it is also feasible that the data of displacement and change of red-edge extent can be used to recognize the moisture stress of cotton plants if a rational recognition system is develop. The conclusions of the study are as follows: (1) The physiological and biochemical properties of both cotton leaves and canopies are changed with cotton growth; (2) There is a significant correlation between the chlorophyll content and total N contents in cotton leaves (R=0.8723, n=38), and the total N contents in cotton leaves can be estimated by a mathematical model; (3) The analyzing method based on the variables of spectral position of "red edge" of cotton leaves, derived from the first differential spectral data, reveals that the change extent, shape and area of the "red edge" contain the information of various wavebands, and the capability of predicting Nnutrient in cotton leaves and canopies can be provided by using the developed model based on the variables from these wavebands; (4) It is reveals that the moisture supply is sufficient, the N metabolizing in cotton plants is hearty, the cotton plants grow luxuriantly, and the red edge of cotton leaves shifts towards blue light if the chlorophyll content in cotton leaves is high. It is feasible that the data of displacement and change of red-edge extent can be used to recognize the moisture stress of cotton plants if a rational recognition system is develop.
Evapotranspiration is an important parameter in the balance of the earth' s surface energy and water, the development of remote sensing has promoted the study of regional evapotranspiration. Based on the equation of the balance of energy, using remote sensing data including VIS/NIR/TIR and a few of weather data, the SEBAL model can calculate the daily regional evapotranspiration. In this paper, theory、flow and method to retrieve main parameters of this model are expresses in detail, using Landsat7 ETM+ data and SEBAL model, the evapotranspiration of Luancheng County in Hebei Province is studied, we got several surface character parameters and evapotranspiration map in one day. Adopting P-M equation, the quantity of evapotranspiration is 5.64 mm·d-1,the quantity evapotranspiration in sullage-irrigation area retrived from model is 5.4~7.4 mm·d-1,because the soil water and crop situation in sullage-irrigation area are better than others,it shows the result of simulation is in reason.
To develop a remote sensing model for monitoring the spatial distribution of rangeland grasshopper infestation in the regions around Qinghai Lake, 198 site grasshopper density (GD) data, and three TM5 images were collected during the last ten days of June and the first ten days of July in 1997, the middle and last ten days of August in 1999, the middle and last ten days of 2000. Ten vegetable indexes (VI),for example the normalized deviation vegetable index (NDVI) and brown vegetable index (BVI), were calculated from TM5 images. The correlations between the GD and VI were investigated with statistics methods. It shows that though the linear correlation between GD and the ten VI are not significant, GD is sensitive to NDVI and BVI, 86% of high GD samples appear in the span 0.2<NDVI<0.5 and 75<BVI<110, and just 29% low GD samples appear in this bound. This implicate that NDVI and BVI are good indicators of rangeland grasshopper location, so that can be used as predictors for rangeland grasshopper remote monitoring.
The development of remote sensing has offered abundant observing the data to mankind. And a trend of quantitative analysis of remotely sensed information is gradually realizing information extracted from the image automatically. It is not only the demand of the remote sensing application but also the advance of the remote sensing self-development. There is a very important demand at present in automatic classification of topographical objects by utilizing the remotely sensed image. However, automatic classification based on computer systems is still a challenge field because of the limitations of the complexity of natural conditions and remote sensing technology itself. The aim of this paper is to study classification approach of topographical objects with Multispectral image. In this thesis, a new method is presented, which is based on Sub-area and Hierarchical theory and consists of two parts. The first part is image automatic Sub-area based on spectrum analysis of topographical objects. The second part is multi-layers extracting
of topographical objects with data of the spectrum characteristics before PCA and after PCA. In terms of the new method, a Hierarchical classification algorithm is developed, then applied to the classification of topographical objects in the partial region of Daqing. The experimental result shows the classification accuracy by our approach is obviously higher than the results by the traditional approaches.
Conventional pixel-based image analysis is used frequently to extract land cover feature from remotely sensed data. Therefore only the spectral information is used in the process of classification. However ,object-oriented image analysis can overcome the limitation stated above. It is based on fuzzy logic functions, uses multiscale image segmentation techniques, allows the integration of a broad spectrum of different object features,such as sepctral values,shape and texture. In the paper, the need of land cover classification is satisfied by the result of object oriented analysis in the middle of Fenjie county of the Three Gorges Area, as well as the feature extraction. At the mean time , there is a validation by using in-situ observation ,which shows that the overall accuracy is 89.2%.
Aerosol plays an important role in global climate change and remote sense provides a better
method to retrieve aerosol optical thickness (AOT) at large scale. Currently dark object subtraction and
contrast reduction method are two widely used methods for MODIS data to get AOT. Due to the facts that
there are few pixels whose reflectance in urban area are not small enough, the urban aerosols are from
multi-sources and their components are difficult to verify, dark object method may lead to big errors if it is
used in urban area. Here the different response of MODIS band 7, 3, 1 to aerosol are used together with
the ground based measurements, a formula is put forward asτ= 4.4376×ρ7+50.5579×ρ3-24.3317×ρ1
-3.5575 to calculate AOT in urban area. The error analysis shows that the error of 81% results is less
than 10% and 61% is less than 6%. This formula is derived from the data observed in one day. The more
accurate result can be derived from the meteorological data provied by hundreds of weather sations.
Terrain Visualization is an important part in Research of Virtual Geographic Environments. A reasonable data structure and an efficient algorithm of constructing Terrain Model can ensure real-time rendering, query and interactive operation . Based on Standard Template Library in C++, The paper has designed a data structure of TIN, and improved Zhang Xiao-can' s algorithm. At last, an application example is given.
Studying the mechanism of integrating IDL(Interactive Data Language) with .Net Environment.Introduce a new viable approach of sharing matrix transmission mechanism between IDL and .Net Environment. By the new way system memory consumption is reduced greatly when mass data was transmitted. The mechanism of Events response and conversion between IDL and Visual C# is discussed through several routine instances also. The method, improving on the original mechanism, effectively developed speed during running. The principle is that the data from dataset was divided into many units, which were as large as the minimal saving unit that was defined before data transmitted. According to the method, every data unit entered the IDL environment by the minimal sharing array created between IDL and C#. After all of the units completed, those was integrated in the IDL environment. The mechanism adequately covered C# strongpoint that had flexibility on the developing and stability on the executing, and IDL merit that had strongly ability to compute on the science.
Based on the analysis of high resolution satellite image valued process at present, it points out several factors which restrict the present process automation. In order to improve valued process automation, a new process was proposed and multi spatial database was established to improve the process with the necessity of developing such system, according to which a prototype system was developed. The running results demonstrate that the improved valued process is well-designed and feasible.
Spatial resolution of image is a critical index of image quality, and also is an important parameter in the area of image application. However, there are many factors which can lower and degenerate the quality of images in the process of capturing images. An effective solution to this problem is the super-resolution image reconstruction, that means reconstructing a high resolution (HR) image from some low resolution (LR) images, and eliminating the additive noise and blur which is caused by the size of the detector and optical at the same time. In this paper,one of project of convex set method for reconstructing a superresolution image from multiframe undersampling images is introduced.First,a very important factor-the model of the process of imaging in spatial domain iterative method for super-resolution image reconstruction is mentioned. Next the reconstruction model and its steps are introduced through introducing the theory of project of convex set method. At last, the technique is available by experiments. The result indicates the project of convex set method for super-resolution image reconstruction has preferable effect on multiframe undersampling remote sensing images, and the technique of super-resolution image reconstruction
can used in lots of fields such as remote sensing, computer vision, public security, physic imaging and so
on.
The merging of multi-origin images is a embranchment of the theory of data merging applied in remote sensing. It becomes a hotspot. SPOT-5 multi-spectral image has abundant spectrum information,although the PAN image has high space resolving power. Using pixel merging in SPOT-5 PAN and multispectral images, we can improve the multi-spectral image' s space resolving power. Preparing for specialty drawing, terra classify, identified and so on.
With the development of satellite SAR. and wide application of SAR image, the geometric rectification of satellite SAR image becomes more and more important in order to locate it accurately. A new algorithm based on simulated imaging point is presented in this paper through combining two exiting rectification algorithms. The paper describes the theory, establishment of mapping model and realization steps of the new algorithm, and makes a comparison with two other algorithms of their flow chart. Finally, the precision is evaluated with a test on real RADARSAT image, and some conclusions are given.
Imaging radar (SAR) posseses unique capabilities, which can work all day/all night and allm weather, can penetrate some special objects and can detect the shapes of ground objects. Especially, with the developments of new imaging radars,such as polSAR, InSAR, and data processing technologies, environmental remote sensing using SAR can provide more and more information about terrestrial ecosystems.All these can greatly propel and improve the SAR applications to ecological environment. The paper reviews the demonstrated capabilities of imaging radars for investigating terrestrial ecosystems, including four broad categories:①land cover classification and vegetation mapping;②estimation of woody plant biomass;③monitoring the extent and timing of inundation and wetland; and④monitoring other temporally-dynamic processes. Finally, the selection of optimal parameters of SAR system for different ecological applications are listed and anzlyzed. It can provide significant reference for ecological applications using SAR data in China.
