In this paper , on the basis of thinking of the harm to pr incipal component analysis from the multi-correlation betw een the factors of remote sensing and GIS depicting the sample plot in the monitoring area, through the selection of variable screening , the main factors of remote sensing and GIS depicting sample plot is determined in the monitoring area. The distribution of sample plots and the detection of abnormal sample plots in monitoring area are studied by means of principal component analysis according to these factors. Comparing the results of thinking of the multi-correlation before and latter and the practical distribution of sample plots in the monitoring area, the harm from multi-correlat ion to principal component analysis and how to using principal component analysis to comprehend the distribution of sample plot in monitoring area are studied systematically .
In recent years, red tides appear to have increased in frequency, intensity and geographic distribution. It has been one of familiar ocean disasters in near shore area of China. It had serious impacts on ecosystem, economic and life of inhabitants of the coast . In this paper , based on comparing the spectrum of red tides and its around water , and analyzing the changing characters of chlorophyll-a concentration in the period of red tide occurring, we developed a method of extracting red tide information with EOS/MODIS data. The method considers the ratio of channel 4 and channel 3 reflectance and the ratio of channel 11 and channel 9 water-leaving radiance, combined with suspended sediments. In 15th June 2002 and 31st May 2004, red tides occurred in Bohai Sea of China. We analyzed the EOS/ MODIS data of the Bohai Sea of China using the method during the red tides. Results indicate that the method is useful to retrieval red tides information from the surrounding waters.
Ocean wave is an important ocean environment parameter. It has significant meaning for harbor
construction, navigation and exploitation of oilfield. Synthetic Aperture Radar (SAR ) is a primary
instrument to measure ocean wave in large-scale area. SAR estimates wavelength and direction of
propagation quite well, But it is very difficult to provide quantificationally amplitude of ocean wave as well
as relation between SAR image intensity and ocean surface. Besides, it is complex to obtain ocean wave
spectrum from SAR image spectrum. Along-Track Interferometric Synthetic Aperture Radar (ATI-SAR )
is an act ive coheren t imaging system , w hich has two an tennas separated along the platform flight
direction. The phrase image of ATI-SAR less depend on real aperture radar modulat ion transfer function
than synthetic aperture radar. Therefore, ATI-SAR is more suitable to measure ocean wave. This paper
introduces the imaging mechanism of ocean wave by Along-Track Interferometric Synthetic Aperture
Radar, It establish firm foundation to inverse ocean wave directional spectrum further. Finally, we discuss
some issues in present study and research orientation in the future.
Data sets of 11 cloud/surface classes are collected from daytime geostationary satellite imagery
data over middle latitude and low latitude regions in summer . 656 samples are randomly selected, and then
116 spectral and textural features derived from these samples are statistically investigated, curves of all
features are drawn and analyzed. After feature selection, sensitivity tests of two classifiers-stepwise
cluster and fuzzy cluster are explored by using of more significant feature arrays. For spectral features,
results of feature curves analysis indicate that spectral characteristics are more significant than those of
textural characteristics, the spectral features of IR or WV except Std show more distinguishingly than
those of VIS, especially for low - or mid-level and cirrus; both results of sensitivity tests from two
classifiers suggest that spectral features provide the major information of cloud classification, which are
main indexes of cloud pattern discrimination. Results of textur al feature curves indicate first order
probability vectors ( FOPV ) demonstrate more obviously than those of gray level difference vectors
( GLDV) , especially CON of four channels and HOM of WV; results of tests show that textural features
play an important role in cloud type identification, both classifiers give higher accuracies after adding
textural features, combing FODV and spectral features significantly improve classification results achieved
using only spectral features, but the accuracy of adding GLDV based on FODV and spectral features has
little distinction with those of adding FOPV based on spectral features, which indicates that textural
characteristics of FODV have more encouraging ability to distinguish between cloud/ surfaces than those of
GLDV, consisting with results of feature curves analysis.
A new method for land use classification from remote sensing image based on Support Vector Machine( SVM) and So ectoal Similarity Scale ( SSS ) is presented. The SSS is used to determine spectral similarity by simultaneously measuring the size and shape between two spectrum. SVM, a machine learning algorithm which is based on statistical learning theory , is characteristic in solving limit samples,non-linear and high dimension model recognizing problems, and can be largely used in other arears. Firstly by field investigation, interest region then is set up on the remote sensing image using accurate boundary lines. Select some training sample points and then draw the samples which have been purified to make a sample refer ence spectrum corresponding with the image's spectrum of each wave band. By drawing some amount of training samples using SSS and constructing classifies using SVM, the land use classification to the whole remote sensing image then can be done. Based on the landsat 7 ETM+ data and ground true data, the paper takes Putian city as interest region for land use classification using SSS and compares its result with that of MLC. Randomly selecting 200 sample points from each type, it can be seen from the two result images that the precision of this method has reached 89. 5%, 7. 9% higher than that of MLC.The classification speed has also been improved obviously . It has obvious superiority and application prospect .
Land covers in urban areas tend to change drastically over a short period of time due to rapid urbanization. Therefore, it is very important to quickly obtain the distributions and area of urban landuse. Remote sensing images are ideally used to monitor current land cover changes thanks to their rapid up-date capability. In this paper, the method of ex tracting urban landuse from Landsat TM data is discussed. Firstly, the mechanism of remote sensing for urban landuse is analyzed. Secondly, the differences of urban landuse and other landuse type are discussed. Third, the structure feature among pectrum of urban landuse and the other landuse types is analyzed. Vegetation and water can be extracted by NDVI and NDWI with suitable threshold. Urban landuse and bareness areas can be distinguished by the formula such as TM 3- TM 2> 0 and TM 4- TM 3> 0. This method is much faster and better accurate. The experiment results show that this method is very simple and effective to the sem iautomatic extraction of the urban landuse.
To observe snowmelt information is an important part of snow observation. Using Remote Sensing methods to observe snowmelt information hasmany advantages, such as large area of observation,abundant information of receiving, high speed to acquire information and realtime of observation etc. In this paper, we present the method of observing snowmelt information by using MODIS images. Based on Snow and water spectral curves under different status, we propose the concept of snowmelt index (SMI) through MODIS band 4 and band 5, and then analyze variation law of SMI in each stage of snowmelt from snowmelt theories and discipline of absorption by snow , melted snow and water. At the end, we take Urumchi in Xinjiang province as the case study, analyze the whole snowmelt process between winter in 2002 and spring in 2003, use the snow depth, days of snow , temperature in local area to simulate snowmelt map in the field since there is no snowmelt map observed directly, and then compare the snowmelt map with SMI map in the corresponding time span. Finally, we validate the law , which is proposed in this paper that the decline rate of SMI becomes small when the content of water in snow increases, and at last stay at a low value.
By ARC/ INFO AML programming and RS methods, a vectorized Vegetation Indices ( VI ) database for Yuzhong Monitoring Area in the process of Tillage Reverting to Woodland or Grassland ecosystems was completed, it contains 3 spatial datasets representing the vegetation status of the July-August in 2000, 2001 and 2002, as the results of 3 TM imageries. VI's including IDV, NDVI, Greenness of Tasseled Cap were selected to reflect the differences of land covers and changes in the 3 year period.Land covers were categorized into 3: Tillage Reverting lots, land use types and basic classes of forest in
the National Nature Protection Region. Comparisons of VI's and analysis on the relations to land cover at tributes were approache, and apprehension of VI's on monitoring Tillage Reverting to Woodland or Grassland ecosystems was discussed.
In the present study, the vegetation, soil brightness, moisture and heat indices are extracted from multi-band enhanced thematic mapper remote sensing image to describe ecosystem status. Pearson correlation analysis was applied to find the relationship between the background value of remote sensing and these indices, climate data, and other geographical auxiliary information. In each index type, there was an index was selected as the evaluation index for its correlation variab les was the biggest. These indices were considered as independent variables, the background value of remote sensing was considered as dependent variable, and a regression equation of ecological environment background value was built using mult ilinear regression analysis. Then the ecological environment background value of the whole Fujian province was calculated using this regression equation. The result was compared with the result assessed by the ecoenvironment quality evaluation, wh ich was used by the China national environmental monitoring center. The tendency of ecological environment quality assess by the two method was uniform. The general ecological environment quality of Fujian province was good. The ecological environmen t quality of mountain region in west and north was better, followed by the town, eroded/deforested hill,and coast land.
Pulse Doppler radar provides important application in GMTI. Space-based GMTI radar system is widely given at tentio n because its detection performance and adaptability excel that of airborne system. In this paper , based on the character istics and recent research of space-based distributed sparse aperture GMTI radar system, the characteristics of space-based GMTI radar system are deeply investigated. The antenna pattern of sparse aperture space-based GMTI radar and the full-DOA opt imum STAP SINR loss characteristics are provided and analyzed. By analyzing sparse aperture space-based GMTI radar space-t ine 2D filtering algorithm, the RD-ST AP ( reduced dimension STAP) algorithms including ADPCA, post-Doppler and PRI-stag gered STAP algorithm are introduced. Based on the space-based distributed uniform linear array GMTI radar system parameters, the performance compare of the STAP algorithms are obtained. Results show that the RD-ST AP algorithms obtain the satisfied SINR loss performance with limited training samples. In the end, the prospects of the space-based GMTI radar system and signal processing research are provided.
Accurate inter-band registration is indispensable to exploit inherent spectral information in hyperspectral remote sensing imagery. Due to wide spectral range of hyperspectral senso r, there is a general lack of similarity between the pairs of images from widely separated wavelengths, which makes registration of hyperspectral imagery difficult to carry out. On the other hand, huge volume of hyperspectral dataset also limits some complex registration algorithms to be adopted. A multireso lution registration method using mutual information combined with a stochastic optimization technique is presented to solve these problems. First, mutual information is used as the similarity metric in registration, which is robust against variations of spectral characteristic of images. Then, the second-order simultaneous perturbation stochastic approximation ( 2SPSA ) method applied in mutual information maximization is more computational efficient for the multivariate optimization problem than several popular optimization algorithms, because it requires only five object function measurements at each iteration,independent of the problem dimension. Moreover, the multiresolution implementation of the registration algorithm based on a rotation- and translation-invariant wavelet and on a coarse-to-fine updating strategy effectively reduces the searching region and ensure that the algorithm can reach the global maximum. In experiment some pairs of band images, which are misaligned by rotation and/or translation, are registered by our scheme. And the results show the algorithm is efficient for registering hyperspectral imagery and yield sub-pixel accuracy.
Image fusion is the most effective technological means to deal with multi-sources remote sensing images. Choosing the best fusion is a key to improve the picture quality according to different data sources. This paper tests to merge panchromatic wave band images and multi-spectrum wave band images of QuickBird on the basis of the theory, algorithm and the merging course of Brovey fusion and Wavelet fusion, then analyzes and evaluates the two merging results from quality and uant ity respectively .Qualitative analysis includes hue, texture and definition, and quantitative analysis includes entropy ,averageg radient and spectrum authenticity . The testing result shows: the image adopting Wavelet fusion keeps higher resolut ion ratio and better spectrum character ; the image adopting Brovey fusion may keeps high resolution ratio, but spectrum information loses relatively heavy , so Brovey fusion is not suitable for dealing with QuickBird remote sensing images.
Aiming at resolving the problem of great variances of remote sensing image in the Three Gorges Reservoir Area, this paper not only builds up the automatically classifying system of land cover and finishes such tasks as correcting the topographical spectrum, producing auxiliary data, forming the needed image in its subsystem but puts forward a kind of manual controlled computer-automatic categorized method. Taking the specialized image analysis software-eCognition as the platform, the research not only achieves the goal of classifying through choosing samples, picking out the best Wavebands, producing the identifying functions, but also dispels the influence of such phenomena as the same thing with different spectrums, dif ferent things with the same spectrum, and border transitions, etc. The research does certain exploration in the aspect of technological route and method of the use of GIS and automatic classification of the remote sensing image to obtain the Information of land cover for the regions whose ground objects have complicated spectrum as well.
The region characteristic and the space relativity of environmental geochemistry offer the possibility to unite g eography information System with the environmental geochemistry . Geography can combine the space data management with the at tribute data management and has the higher visibility . In this paper, making use of the reconstruction function of MapGIS, an environmental geochemistry information system is exploited, which includes the regional geology introduction subsystem, the attribution database management and analyse subsystem, the spatial database management and analyse subsystem. The realization and the design method of the system is introduced, especially the basic principle and the pivotal technique about GIS applying in the environmental geochemistry such as the buffer region, the contour, the shortest path, the water quality index , etc. , and the spatial database management and analyse subsystem is elaborated. Then the system has been applied to the region of Hubei Huangshi to analyze and quality evaluates to the environmental geo chemistry data, which has proved the validity and feasibility of the system.
