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Mapping Cloud Mask of FY-3A VIRR to IRAS
CAO Guang-zhen,QI Cheng-li,MA Gang,ZHANG Feng-ying,WU Xue-bao
Remote Sensing Technology and Application    2008, 23 (1): 89-92.   DOI: 10.11873/j.issn.1004-0323.2008.1.89
Abstract12486)      PDF(pc) (758KB)(899)       Save

Look-up table method is applied to test the match between FY-3A VIRR(Visible and InfraRed
Radiometer)cloud mask and IRAS(Infrared Atmospheric Sounder).Therefore,the mapped cloud mask has
the same spatial resolution as IRAS which is helpful for the retrievement of atmospheric temperature and
humidity profiles from IRAS.The simulated VIRR cloud mask and IRAS data are used and the matched re-
sult is compared with original VIRR cloud mask.

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Design and Implementation of Eco-hydrological Data Acquisition System based on SDI-12 Bus
Bai Yulong,Dong Cunhui,Shan Jiming,Wang Zuocheng,Jin Rui,Kang Jian
Remote Sensing Technology and Application    2013, 28 (3): 453-458.   DOI: 10.11873/j.issn.1004-0323.2013.3.453
Abstract11382)      PDF(pc) (2132KB)(1000)       Save

This paper gives an introduction about a new kind of data acquisition system which can collect certain kinds of eco-hydrological data such as soil temperature,humidity,salinity and conductivity.The system is based on microcontroller.The sensor interface circuits,communication timing control circuits,SD storage circuits and display circuits were designed for the Hydra Probe II soil property sensor.Based on the requirements of Eco-hydrological wireless sensor network in Heihe river basin,the communication protocol between data acquisition systems and the sensors were realized by SDI-12 bus.The Eco-hydrological data can be measured,stored and transfered by the proposed system.Combined with Network communication and Watershed data management platform,an eco-hydrological wireless sensor network can be easily realized.

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Comparisions of Estimating Methods of Vegetation Fraction Based on “BJ-1” Microsatellite Imagery
LIU Ya-Lan, REN Yu-Huan, CHEN Tao, ZHANG Long-Ji
Remote Sensing Technology and Application    2007, 22 (5): 581-585.   DOI: 10.11873/j.issn.1004-0323.2007.5.581
Abstract10512)      PDF(pc) (960KB)(1285)       Save

BJ-1 Microsatellite is the advanced member of the Disaster Monitoring Constellation (DMC) with two powerful cameras.One camera can monitor coverage of 600km by 600km , while the other developed by Sira, can capture images of a 24km wide strip of ground with a resolution of four metres.Vegetation fraction coverage is an important parameter for describing vegetation quality and indicating ecosystem change.Inthis study, BJ-1 images were used to detect and analyze the vegetation fractional coverage in the basin of Miyunreservoir.Based on the analysis of the current methods, this paper uses three kinds of methods, including Dimidiate PixelModel from Normalized Difference Vegetation Index (NDVI),3-bands Grads Difference Method and a new method based on Renormalized Difference Vegetation index (RDVI).According to the experimentation, the estimating values by RDVI method has abetter relationship with the verification values, while the other two methods appeared a bigger difference with the groundtrue values.On the whole, RDVI method shows good characteristics and can be used in estimating of vegetation fraction in conjunction with BJ-1 satellite image data.

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Application of Satellite Remote Sensing Technology to Wetland Research
ZHOU De-min, GONG Hui-li, HU Jin-ming, WU Feng-lin
Remote Sensing Technology and Application    2006, 21 (6): 577-583.   DOI: 10.11873/j.issn.1004-0323.2006.6.577
Abstract10339)            Save

Wetland specifies with both ecologic and scientific values. Because of most wetlands located too far to be monitored, satellite imagery characters with quantity information, multi-temporal, multi-platform , comparability will largely favor wetland research, so remotely sensed data have been widely proved an effective too lin wet land investigation in the past decades. The application of satellite RS technology on wet land research in China is reviewed from the aspects of the survey of wet land resource inventory, the model of wet land identification and classification, research of wetland dynam ic change, wetland vegetation biomass estimation and lately development trends as well as its principal characters of satellite RS research of wetland. Particularly, the paper introduces some progress of RS application on urban wet and in China.The detection study on dynamic change of wetland as natural resources by RS methods is also presented in a wide scope from in land plain wet land, deltaor riverine wetland to plateau wetland. Both academic Achievements and prospect comments are also presented in the paper by reviewing both home and abroad researches. The application trends of remote sensing in wetland research will be the following three aspects: much more multi-temporal and multi-spatial RS platforms will be provided for future research, the scale of research on wetland will be smaller due to the continuous loss of wetland as well as its fragmentation, and in tegration of RS, GIS, GPS and wetland will be much more emphasized.

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GDP Spatialization in China based on DMSP/OLS Data and Land Use Data
Han Xiangdi,Zhou Yi,Wang Shixin,Liu Rui,Yao Yao
Remote Sensing Technology and Application    2012, 27 (3): 396-405.   DOI: 10.11873/j.issn.1004-0323.2012.3.396
Abstract10146)      PDF(pc) (4564KB)(1314)       Save

GDP is a key indicator of socioeconomic development,urban planning,and environmental protection,accurate estimates of the magnitude and spatial distribution of economic activity have many useful applications in resources and environmental sciences.Developing alternative methods may prove to be useful for making estimates of gross domestic product when other measures are of suspect accuracy or unavailable.Based on the summary and analysis of existing economic activity spatialization approaches,this paper explored the potential for spatializing GDP through China using night-time satellite imagery(DMSP/OLS) and land-use data.In creating the GDP linear regression model of secondary industry and tertiary industry,night-time light intensity and lit areas,under different types of land use,were employed as predictor variables,and the GDP statistical data was as dependent variable,meanwhile,model of primary industry based on the landuse data.To improve model performance,31 zones were created according to provincial administrative boundary.The model of primary industry is observed to have a correlation(R2) ranging from 0.7 to 0.95 in majority zones and R2 of secondary industry and tertiary industry modle is ranging from 0.8 to  0.98 in majority zones.A comparison of the results of this research with other researches shows that spatialized GDP density map,prepared on night-time imagery and land-use data,which reflects the GDP distribution characteristics more explicitly and greater detail.Meantime,the density map is significant sustainable economic development policies and basically explores the relationship between socioeconomic and regional ecological environment interaction.

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Drought Remote Sensing Monitoring Based on the Surface Water Content Index(SWCI) Method
ZHANG Hong-wei,CHEN Huai-liang,SHEN Shuang-he
Remote Sensing Technology and Application    2008, 23 (6): 624-628.   DOI: 10.11873/j.issn.1004-0323.2008.6.624
Abstract10090)      PDF(pc) (880KB)(1564)       Save

Soil Moisture and Vegetation Growth are the most important and direct index in drought monitoring,and the spectral interpretation of vegetation and soil are serious factors in the judgment of drought degree.Based on the spectral character of water,recently,a new model of Surface Water Content Index(SWCI) has been put forward,and the index is more sensitive to the surface water content,and suit for regional drought monitoring.The comparative analysis showed that SWCI is more sensitive than NDVI to monitoring surface soil water content,it is available in real-time soil drought monitoring.

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A Highly Efficient Atmospheric Correction Method for HJ-1A/HSI and the Exploration on Its Application Capability
MA Ling-ling, WANG Xin-hong, TANG Ling-li
Remote Sensing Technology and Application    2010, 25 (4): 525-531.   DOI: 10.11873/j.issn.1004-0323.2010.4.525
Abstract9851)      PDF(pc) (3674KB)(1474)       Save

A Hyper-Spectral Imaging sensor (HSI) developed independently by China was loaded on the HJ\|1A satellite and put into service on March 30,2009.As a new type of sensors,the applications of HSI are still in the exploration stage.In order to make full use of HSI data and carry out effective remote sensing applications,the first thing need to do is to eliminate the atmospheric effect in the process of imaging and obtaining the real land surface radiation information.The FLAASH (Fast Line of Sight Atmospheric Analysis of Spectral Hypercubes) atmospheric correction model is used to correct the atmospheric effect of HJ-1A/HSI data.The corrected spectral reflectance is compared with the apparent reflectance,and the validity of atmospheric effect correction method is well demonstrated.Meanwhile the preliminary application effect of HSI data is exhibited by the retrievals of modified soil adjusted vegetation index (MSAVI) and leaf area index (LAI) based on the atmospherically corrected spectral reflectance image.
 

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Automatic Registration of Quad-Rotor UAV Imagery based on SIFT and TPS Algorithm
Chen Benqing,Yang Yanming,Zheng Linghong,Wen Hongtao
Remote Sensing Technology and Application    2013, 28 (4): 604-609.   DOI: 10.11873/j.issn.1004-0323.2013.4.604
Abstract9786)      PDF(pc) (2753KB)(964)       Save

As an important complementarity of remote sensing technique,Unmanned Aerial Vehicle (UAV) is attractive to various applications such as target searching,island management,disaster monitoring and low-altitude photogrammetry.The quad-rotor UAV,Compared to fixed-wing UAV,has the advantages of Vertical-Taking-of-Landing (VTOL) and low-altitude flexible flight.However,the quad-rotor UAV has small-volume and light-weight and is more easily influenced by the wind,the acquired imagery maybe have bigger tile angle and more obvious geometry distortion will would result in more difficulty on the image feature matching and  image mosaic. For this question,we apply the Scale Invariant Feature Transformation (SIFT) to image feature matching and Thin Plate Spline (TPS) transformation to automatic registration of the micro quad-rotor UAV imageries in this paper.The registration imagery based on TPS transformation is then compared to that based on the affine transformation and the polynomial transformation by evaluating the visual effect of the mosaic imagery and Root Mean Square (RMS) statistic,which shows that after precise SIFT feature matching,the registration RMS accuracy and the visual effect of mosaic imagery of TPS transformation are best,and satisfies the demand of rapid registration and mosaic of micro quad-rotor UVA imagery,since TPS transformation considered both rigid transformation and partial nonlinear distortion of the micro quad-rotor UAV imagery.

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Validation of the MODIS Land Surface Temperature Products—A Case Study of the Heihe River Basin
Yu Wenping,Ma Mingguo
Remote Sensing Technology and Application    2011, 26 (6): 705-712.   DOI: 10.11873/j.issn.1004-0323.2011.6.705
Abstract9181)      PDF(pc) (1497KB)(2139)       Save

This paper analyzes the key factors that result in the estimation errors of the MODIS land surface temperature products.Then the principle methods of validating the MODIS LST was discussed and compared.Normally there are bigger uncertainties of MODIS LST products in the semi\|arid and arid regions.As a case study,the Heihe river basin was selected to estimate the accuracy of MODIS LST products in Chinese arid and semi-arid regions.The two kinds of ground-measured observation data were obtained from the automatic meteorological stations:Infrared Radiation Thermometer data and longwave radiation data.The comparisons were performed for the validation based on these two types of observation data over three typical land cover types.The result demonstrates that:it is more reasonable to use long\|term nighttime surface longwave radiation data to validate the MODIS LST products.The validation results indicate that mean absolute error is less than 2.2 ℃ in the selected stations.

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Retrieving Evapotranspiation of Loess Hilly-gully Region Using TSEB Parallel Model Based on Remote Sensing Image
PAN Jing-hu, LIU Chun-yu
Remote Sensing Technology and Application    2010, 25 (2): 183-188.   DOI: 10.11873/j.issn.1004-0323.2010.2.183
Abstract8959)      PDF(pc) (2215KB)(3021)       Save

Evapotranspiation retrievals in conditions of rugged terrain and arid/semiarid sparse vegetation are always the hotspot in estimation of regional evapotranspiration from remote sensing images.Concerning with the complex characteristics of the loess hilly-gully region,such as undulating topography,un-unique land use/covers and less vegetated land surface,etc,land surface characteristic parameters and flux was retrieved,and the instantaneous vegetation transpiration and soil evaporation was estimated with the TSEB parallel model by using the Landsat TM data for an experimental study site located on the conjuncture area of Shaanxi and Gansu where the terrain surface is very undulating with less vegetation developed,heavy soil and water loss loess plateau.And then the calculated result was merged into daily evapotranspiration,also the spatial pattern of the daily evapotranspiration was analyzed.Actual evapotranspiration of the study area was calculated with the extra resistance method and Penman-Monteith equation to compare with the TSEB parallel model estimated,which suggested that the TSEB parallel model can be used for the accurate estimation of evapotranspiration in loess hilly-gully region.

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A New Method for Automatic Geometric Rectification Based on Image Matching in Remote Sensing Image
ZHANG Duo-kun,TIAN Zhao-shen,LONG Hui,WANG Hong-qi
Remote Sensing Technology and Application    2008, 23 (5): 545-550.   DOI: 10.11873/j.issn.1004-0323.2008.5.545
Abstract8943)      PDF(pc) (3269KB)(2486)       Save

New method for automatic geometric rectification based on image matching in remote sensing image is proposed,which can solve the problem of lower-precision and time-consumption in traditional manual geometric rectification.First,the pictures contained ground control points (GCPs) are gained in the remote sensing image which has been processed with basic geometric correction method.Secondly,the accurate matching between remote sensing image and GCPs pictures are found.Then,the outliers of GCPs are detected.Finally,the remote sensing image is precisely corrected by the GCPs.Also in this paper,a new multicriterion image matching algorithm is proposed to detect precise matching.The experimental results demonstrate the robustness and effectiveness of the proposed automatic geometric rectification method.

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Applications of GRACE in Hydrology:A Review
Cao Yanping,Nan Zhuotong
Remote Sensing Technology and Application    2011, 26 (5): 543-553.   DOI: 10.11873/j.issn.1004-0323.2011.5.543
Abstract8911)      PDF(pc) (939KB)(1037)       Save

The Gravity Recovery and Climate Experiment (GRACE) satellite has provided a new means to study the deep earth structure and to keep track of mass changes of earth surface.In this paper,applications of GRACE data in the scope of hydrology are summarized on the basis of extensive reviews of relevant literature.This paper starts with a brief introduction of the common available scientific GRACE data sets.Applications in estimating oceanic and terrestrial water storage,as well as those of polar and alpine glaciers are then reviewed,and the approaches to validate the GRACE estimates are followed.Technical issues encountered in hydrological applications and their possible solutions are examined in details.We concluded that it is critically important and valuable to employ the GRACE satellite data to monitor global or regional scale water balance to meet the challenges of global/regional hydrology monitoring and research.

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Correlation Analysis between NDVI and Climate in Northeast China based on AVHRR and GIMMS Data Sources
Mao Dehua,Wang Zongming,Luo Ling,Yang Guang
Remote Sensing Technology and Application    2012, 27 (1): 77-85.   DOI: 10.11873/j.issn.1004-0323.2012.1.77
Abstract8866)            Save

Based on the AVHRR GIMMS NDVI and MODIS NDVI,this paper constructed yearly maximum NDVI sequence covering Northeast China from 1982 to 2009 using per-pixel unary Linear Regression Model.The constructed NDVI through the consistency check and well be used in the temporal analysis and correlation analysis with climatic factors.Results showed that there were three change stages in the past 28 years:A modest increase trend during 1982~1992,slow decrease trend during 1982~2006 and a recovery during 2006~2009.Result from variation analysis on spatial pattern showed that obvious changes occurred mainly in Inner Mongolia Automomous Region (IMAR) arid and semi-arid zone.Mean NDVI value in 2000s and 1990s were bigger than 1980s.Change value ranged from -0.3 to 0.3 and increase trend were mainly found in Chifeng and west of Songnen plain which have a proportion about 6.45% in total area.A high spatial heterogeneity was observed in the correlation between yearly maximum NDVI and climate (temperature and precipitation).Pixels which had a bigger coefficient of partial correlation between NDVI and temperature than between NDVI and precipitation account for 54% of all pixels.At whole scale,temperature was the dominate influence factor compared with precipitation.For different vegetation types,the yearly maximum NDVI was affected by annual average temperature as follows:forests>grasslands>marshes>shrubs>crops; and by precipitation:grasslands>crops>shrubs>marshes>forests.

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Discussion on UAV Remote Sensing Image Capture and Disposal
HONG Yu,GONG Jian-hua,HU She-rong,HUANG Ming-xiang
Remote Sensing Technology and Application    2008, 23 (4): 462-466.   DOI: 10.11873/j.issn.1004-0323.2008.4.462
Abstract8824)      PDF(pc) (1061KB)(3230)       Save

As an important complementarity of aerial remote sensing,the UAVRSS(Unmanned Aviation Vehicle Remote Sensing System) has many advantages in specific field.Firstly,the paper  described 4 times aviation experimentations,then based on the experiment images and aviation data of UAV,all images were  mosaicked to a panorama image.And the mosaicked image was analyzed from many factors for evaluating the image quality.Finally,some improvements to the UAV image quality were discussed.

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Endmember Extraction Algorithm Based on RMS Error Analys is in Hyperspectral Imagery
XUE Qi, KUANG Gangyao, LI Zhiyong
Remote Sensing Technology and Application    2005, 20 (2): 278-283.   DOI: 10.11873/j.issn.1004-0323.2005.2.278
Abstract8772)            Save

The linear mixed mixture is a commonly accepted model for hyperspectral data processing. As the important parameter of the linear mixed mixture, endmember represents a certain ground component whose spectral is changeless comparatively. Over the past years, several techniques have been developed for accomplishing the determination of the endmembers in the literatures. Aimed at the disadvantages of these existing methods, this paper presents an automatic endmember extraction algorithm based on RMS error analysis. The new algorithm overcomes the insufficiency of other methods and needs less prior information. Not only the mean spectrum of the imagery is extracted, but also the anormaly is reserved.This algorithm also depends on the linear mixed mixture, it is executed directly on the data with no previous dimensionality reduction. The mean spectrum of the data is chosen to start the process, and then,a series of constrained unmixing operations is performed, each time selecting as endmembers the pixels that minimize the remaining RMS error in the unmixed image. This process is continued until the required number of endmembers is found or the unmixing error is below some threshold. The results of simulated and real hyperspectral data show the validity of the algorithm by a detailed comparative analysis with PPI.

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Expectation and Evaluation of the Methods on RemoteSensing Image Classifications
DU Feng-lan, TIAN Qing-jiu, XIA Xue-qi
Remote Sensing Technology and Application    2004, 19 (6): 521-525.   DOI: 10.11873/j.issn.1004-0323.2004.6.521
Abstract8755)            Save

This paper is based on the concept and characteristic of Remote Sensing classifications, combining thepredecessors' fruits, then sums up all the methods (including traditional and new classifications, such as: objec-t-oriented, sub-pixel classification etc.), detailed analyzes and evaluates each of them. Afterwards, it attemptsto analyze the methods and the arithmetic of classifications, such as principles, effects, functions and limitedconditions. It also compares the excellence, the defects and adapting conditions of each method, and summa-rizes all of the methods in different views. Finally, summary and prospect are described, in order to give guid-ance to practical work.

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Research on Observing Sea Surface Temperature (SST) based on Microwave Remote Sensing by Satellite
Sun Guanglun,Guan Daoming,Zhao Dongzhi,Wang Xinxin,Wang Xiang
Remote Sensing Technology and Application    2013, 28 (4): 721-730.   DOI: 10.11873/j.issn.1004-0323.2013.4.721
Abstract8654)      PDF(pc) (1255KB)(942)       Save

With the rapid development of remote sensing technology,it is possible to observe sea surface temperature (SST).As one of the major methods of observing SST,microwave remote sensing by satellite has received increasing attention.The course of development on microwave remote sensing for SST observations and the advantages compared with infrared observations are summarized,basic retrieval theory and two major retrieval algorithms:Multiple Linear Regression Algorithm and Non-Linear Iterative Algorithm are concluded,moreover,operating parameters and the channel characteristics and other advanced microwave radiometers carried on of TMI,AMSR-E FY-3 and HY-2 are introduced with the retrieval algorithms for each sensor,finally,the effective factors of SST retrieval are analyzed,the problems at present are listed,and subsequent studies are prospected.

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Comparison between Algorithms of Ortho-rectification forRemote Sensing Images
LUAN Qing-Zu, LIU Hui-Ping, XIAO Zhi-Qiang
Remote Sensing Technology and Application    2007, 22 (6): 743-747.   DOI: 10.11873/j.issn.1004-0323.2007.6.743
Abstract8571)      PDF(pc) (889KB)(2268)       Save

There are kinds of methods for ortho-rectification in application of remote sensing images,including Collinearity Equation Model,Strict Geometric Model based on Affine Transformation,Improved Polynomial Model,Rational Function Model,Method based on Neural Network,and so on.But there is lack of system comparison among these methods.On the basis of introducing the principle of the methods above,advatanges and drawbacks about these algorithms are summarized in this paper.Specific emphasis is the mathematical derivation and algorithm design of FM.Tikhonov method is taken to the progress of computation  of RFM.Two kinds of algorithm based on neural network was taken in application of ortho-rectification.To compare accuracy and effectiveness between the above methods,we make some experiments.The result shows that: on the condition of the same GCPs distribution,Rational Function Model that can reach sub pixel accuracy is the best of all from the viewpoint of precision and can be used in practice in spite of its relatively slower speed.

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A Review of Monitoring Change in Lake Water AreasBased on Remote Sensing
WANG Hai-Bo, MA Ming-Guo
Remote Sensing Technology and Application    2009, 24 (5): 674-684.   DOI: 10.11873/j.issn.1004-0323.2009.5.674
Abstract8543)      PDF(pc) (1552KB)(2248)       Save

The global environment change has become one of the three global environmental issues with the greatest global impact.Lake is of great ecological significance in regional ecosystem study.Dynamic change as one of three main lake environmental problems of lakes has became the key point of the research area.Remote sensing techniques,as scientific tools of rapid investigation and monitoring,have been widely applied in the research of dynamic change in lakes.Main progress around of the world in areas of lake dynamic change research by means of remote sensing techniques are introduced in the aspects of basic principles and remote sensing data sources,remote sensing classification and dynamic change monitoring methods of lake information | especially,the advantages and disadvantages of remote sensing data source and dynamic analysis methods are analyzed deeply.In addition,some existing problems and the development trends of the recent lake dynamic change research are discussed.

 

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Review on Correlation Analysis of Independent Variables in Estimation Models of Vegetation Biomass Based on Remote Sensing
XU Xiao-jun,DU Hua-qiang,ZHOU Guo-mo,FAN Wen-yi
Remote Sensing Technology and Application    2008, 23 (2): 239-247.   DOI: 10.11873/j.issn.1004-0323.2008.2.239
Abstract8434)      PDF(pc) (1093KB)(2339)       Save

Applying remote sensing to estimate vegetation biomass has been paid more attention.When using the remote sensing information parameters and other parameters to construct models,researchers often need choose some parameters as independent variables which have obvious influence on biomass.Therefore,identifying the number of independent variables and choosing independent variables play an important role in the reliability and precision of estimation models.From single-variable models,multi\|variables models and nonparametric models,the article reviews on correlation analysis of independent variables in estimation models of vegetation biomass based on remote sensing,which offers some referenced value for choosing the independent variables in estimation models of vegetation biomass.

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Research on the Method of Extracting Water Body Information |from ASTER Remote Sensing Image
HUANG Hai-bo,ZHAO Ping,CHEN Zhi-ying,GUO Wei
Remote Sensing Technology and Application    2008, 23 (5): 525-528.   DOI: 10.11873/j.issn.1004-0323.2008.5.525
Abstract8421)      PDF(pc) (622KB)(3051)       Save

To take Wuhu in Anhui province for example.Firstly,the author analysed the water body in Wuhu and the spectral characters of the earth's surface,then,summarized every class separability of the water information and the earth's surface in every band of ASTER Remote Sensing Image,after repeated experiments and analysis constructed the extracting model of water body which based on threshold of bands and relation of spectrum:B2>B3,B1+B6<127,B3+B4<54 and B3<24.In the end,the author compared and evaluated the conclusion of extracting model of water body with the conclusion of unsupervised classification,supervised classification and NDVI.The result of experiment indicated that this method is feasible and more simple,but higher demands were needed in the selected samples of the analysing process of spectral characters.

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A Study on the Accurate Classification Approaches for Remote Sensing Image Based on GIS
DU Hong-yan, ZHANG Hong-yan, ZHANG Zheng-xiang
Remote Sensing Technology and Application    2004, 19 (4): 244-248.   DOI: 10.11873/j.issn.1004-0323.2004.4.244
Abstract8202)            Save

How to get high accuracy of classification by remote sensing image processing technology is oneof the difficulties in applications of wetland data. The paper discusses the methods to enhance the accuracyof classification for the wetland of Zhalong. First we can noise reductions enhance and tasseled cap enhanceto improve its accuracy. Then compare the classification results of original image with those of the othertwo enhance methods. The results are very similar, i.e., 83.91% of original image, 78.88% of noisereduction and 90.13% of tasseled cap respectively, checked by GPS sample points gained from fields, landcover data of 2000 and Kappa accuracy assessment. Each method has its own advantage in differentiatingthe classes, especially the accuracy in the wetland boundary after noise reduction enhance and the accuracyin the sub classes of wetland after tasseled cap enhance. But none of them is very satisfied. So based onknowledge and the technique of GIS, we can put the advantages of each methods together to gain anexcellent result. The new method is the kernel of this paper, using spatial algebra, which combines thetechnique of RS and GIS together, and it can greatly improve the accuracy and reflect the actual land typesbetter in classification of wetland. Its accuracy can get to 96% after checked by GPS sample points,landcover data of 2000 and visual interpretation. Then we can draw a conclusion that as far as wetlandclassification is concerted, the image enhance before classification can improve its accuracy in some parts,but using spatial algebra based on GIS technology can put the advantage together and get the best result.

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A Methodology for Road Extraction from High Resolution Remote Sensing Images
Zhou Anfa,Zhou Jiaxiang
Remote Sensing Technology and Application    2012, 27 (1): 94-99.   DOI: 10.11873/j.issn.1004-0323.2012.1.94
Abstract8194)            Save

The road is a very important geographic dataset and it plays an important role in national economy and national defense. Research on the automatic or semi-automatic road extraction has always been regarded as a hot and difficult topic. Although lots of theories and methods have been proposed,there is no one that is widely used in production environment. Since road extraction from high resolution remote sensing images is difficult,in this paper,we propose a new method for road extraction. Firstly,a RGB color space image is converted to HSV color space image and an improved regional segmentation algorithm is used to separate the road regions. Then,a combined mathematical morphology operation (such as erode,dilate etc.) with regional shape indices (such as area,compactness etc.) is applied to separate the road objects and non-road objects. The experiment results over several complex road images show that this method can be used to extract roads under more complex conditions.

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Classifying Method of Forest Fuels by Using MODIS Data——Demonstration in Hei Longjiang Province
QIN Xian-lin, YI Hao-ruo
Remote Sensing Technology and Application    2004, 19 (4): 236-239.   DOI: 10.11873/j.issn.1004-0323.2004.4.236
Abstract8125)            Save

Forest fuel is a key factor of three factors of Forest Inflammation Cycle Theory. It' s the innerfactor of forest fire. It is important for Forest Fire Prevention, such as Forest Fire Danger RatingPrediction, Forest Fire Behavior Prediction (FBP), Forest Fire Extermination and Forest Fire Salvation.A method for classifying forest fuels by integrating MODIS data and GIS technique is tested in Heilongjiang province. In studying, five forest fuels have been classified after serials process, such as derivingthe Max Normalized Difference Vegetation Index (MNDVI ) over sixteen days' data by usingMultitemporal MODIS data, Analysising the MNDVI data by using Principal Components Analysis(PCA), Unsupervised classification method and Supervised classification method. It makes a strong basefor further studying National forest fuels classification method by using modernistic informationtechniques.

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Advances in Technologies and Methods for Satellite Remote Sensing of Atmospheric CO2
LIU Yi,LV Da-|ren,CHEN Hong-bin,YANG Dong-xu,MIN Min
Remote Sensing Technology and Application    2011, 26 (2): 247-254.   DOI: 10.11873/j.issn.1004-0323.2011.2.247
Abstract8085)      PDF(pc) (869KB)(1088)       Save

This paper summarize recent progresses in the technologies and methods of satellite\|based instruments for atmospheric CO2 remote sensing, discuss the basic theory and retrieval method, and analyze the factors debasing the precision of CO2 measurement. Three kinds of instruments are discussed in detail:① Currently  operating satellite instruments, which observe atmospheric CO2 and other components, such as Atmospheric Infrared Souner (AIRS), Scanning Imaging Absorption Spectrometer (SCIAMACHY) and Infrared Atmospheric Sounding Interferometer (IASI);② Specific instruments for detecting CO2 content in the lower troposphere, such as Orbiting Carbon Observatory (OCO) and Greenhouse gas Observing Satellite (GOSAT);③ Satellite projects focus on active instrument\|laser lidar,such as Active Sensing of CO2 Emissions over Nights,Days,and Seasons (ASCENDS) and Advanced Space Carbon and Climate Observation of Planet Earth (A\|SCOPE).In addition,we introduce technical basic in hyper spectral instrument in China.Validation,data assimilation and potential development of CO2 satellite remote sensing are discussed at the end of paper. 

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Comparative Analysis of Global Vegetation Phenology based on AVHRR and MODIS
Liu Lingling,Liu Liangyun,Hu Yong
Remote Sensing Technology and Application    2012, 27 (5): 754-762.   DOI: 10.11873/j.issn.1004-0323.2012.5.754
Abstract8067)      PDF(pc) (4555KB)(1468)       Save

The AVHRR and MODIS satellites have played a vital role in monitoring vegetation phenology responses to climate change at a global scale.It is important to examine whether the derived phenological parameters from AVHRR are consistent with from MODIS.In this paper,a dynamic threshold method was applied to extract the phenological metrics based on GIMMS AVHRR NDVI and MODIS 13A2 NDVI dataset smoothed with HANTS in 2005,such as Start of Season (SOS),End of Season (EOS),and Duration of Season (DOS).Then,the comparative analysis was performed on the phenological metrics between AVHRR and MODIS.The results showed the SOS appeared between 100th and 140th days,the EOS occurred between 260th and 300th days,the DOS mainly existed from 130th to 180th days in most regions.The phenological variation along latitude based on AVHRR was consistent with based on MODIS,a trend of later SOS,an earlier EOS and a shorter DOS with increase of latitude were observed.The SOS,EOS and DOS from AVHRR and MODIS data were quite consistent with a correlation coefficient larger than 0.9 for the deciduous forests and grasslands in Eurasia and North America.

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Estimation and Spatial-temporal Distribution Characteristics of PM2.5 Concentration by Remote Sensing in China in 2015
Shimei Wei, Jinghu Pan, Wenliang Tuo
Remote Sensing Technology and Application    2020, 35 (4): 845-854.   DOI: 10.11873/j.issn.1004-0323.2020.4.0845
Abstract7992)   HTML15279)    PDF(pc) (4522KB)(995)       Save

Air pollution characterized by PM2.5 pollutants poses severe challenges to the sustainable development of society and human health. Therefore, it is of great significance to clarify the spatial-temporal distribution and evolution of PM2.5 pollutants in China for regional joint prevention and control of PM2.5 pollutants. Based on the MODIS satellite aerosol products, meteorological basic data and PM2.5 pollutant monitoring site monitoring data, a geographically weighted regression model was established to simulate and estimate PM2.5 pollutant concentration in China in 2015 on the basis of aerosol and meteorological data pre-processing. In addition, the spatial distribution pattern, the seasonal evolution characteristics of PM2.5 pollutant concentration were analyzed. The results showed that: (1) the PM2.5 concentration values in China in 2015 as a whole showed obvious spatial zonal differentiation characteristics. The concentration of pollutants in the north is significantly higher than that in the south, and the areas with high PM2.5 concentrations are mainly concentrated in the Beijing-Tianjin-Hebei region, the Jianghuai plain, the Sichuan basin, and the Takaramalkan desert. The area has a wide spatial distribution and significant continuity; (2) The PM2.5 concentration in the fourth quarter showed obvious seasonal adaptive evolution characteristics. The PM2.5 concentration changed significantly in the season. PM2.5 pollution was the heaviest in the fourth quarter, followed by the first quarter of the third quarter and the lowest in the second quarter. The maximum occurred in the fourth quarter (165 μg/m3). The minimum appeared in the second quarter (4.3 μg/m3). Seasonal changes in PM2.5 concentrations were influenced by meteorological factors and human social activities; and (3) The accuracy of the inversion of PM2.5concentration by a multi-factorial, geographically weighted regression model was higher, with relative errors in the four quarters being 10.2%, 7.0%, 9.3%, and 8.6%, respectively.

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Review on Applications of DMSP/OLS Night-time Emissions Data
YANG Mei,WANG Shi-xin,ZHOU Yi ,WANG Li-tao
Remote Sensing Technology and Application    2011, 26 (1): 45-51.   DOI: 10.11873/j.issn.1004-0323.2011.1.45
Abstract7980)      PDF(pc) (734KB)(2021)       Save

The Defense Meteorological Satellite System(DMSP) Operational Linescan System (OLS) has a unique low\|light imaging capability developed for the detection of clouds lit by mooolight.In addition to moonlit clouds,the OLS sensor also detects nocturnal lights from the earth surface.Hence,DMSP/OLS night\|time emissions data becomes well known as a means of monitoring human activities.In this paper,we reviewed a number of applications that had been developed or proposed based on the DMSP/OLS night\|time emissions data,such as monitoring city lights,light pollution,fires,fishing boats and gas flare,and estimating socioeconomic data.Finally,the advantages and disadvantages of night light data were listed and more applications are expected in the future based on the available light emission data.

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Experiment and Accuracy Analysis of Automated Registration and Orthorectification for Landsatlike Images based on AROP
Li Ainong,Jiang Jingang,Bian Jinhu,Lei Guangbin,Huang Chengquan
Remote Sensing Technology and Application    2012, 27 (1): 23-32.   DOI: 10.11873/j.issn.1004-0323.2012.1.23
Abstract7968)            Save

Accurate registration and orthorectification of remote sensing image is the important fundament for image fusion,change detection,image mosaic,quantitative remote sensing modeling,and synergy application of multitemporal and multisensor images.This paper takes the program package named LEDAPSAROP (Landsat Ecosystem Disturbance Adaptive Processing SystemAutomated Registration and Orthorectification Package) of NASA as a case,to illustrate its principle and program design,and analyze its accuracy of registration and orthorectification.The experiment shows that AROP can search enough control points in reference image,and these points distribute evenly.The error of registration and orthorectification is no more than 0.5 pixels,which can meet the requirement of remote sensing quantitative application in mountainous regions.The characteristic of errors presents that the lateral error is obviously bigger than the course error,and the errors seem correlate to the DEM and slope.At present,AROP can be used to process the registration of CBERS image,but still need study further for deal with HJCCD image.

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Removing Thin Cloud Cover from Remote Sensing Images
Jiang Hongyue,Zhou Jianhua
Remote Sensing Technology and Application    2013, 28 (4): 640-646.   DOI: 10.11873/j.issn.1004-0323.2013.4.640
Abstract7869)      PDF(pc) (4038KB)(783)       Save

Removing thin cloud/fog cover is one of regular tasks in remote sensing image processing.In this study,it is found that the effects from thin cloud cover to spectral signal usually have a performance of low-frequency characteristic and lead to both increased brightness V and reduced saturation S of the image signals.As the thickness of the cloud gradually changes from the center of cloud to the edge,the corrections for V and S also vary gradually.Therefore the relations between image distance D and S and between D and V divided by S  were obtained by image sample and regression analysis.And then through a pixel-by-pixel correction in both S and V with the two relations,the spectral signals can be recovered well.When added a parameter of orientation angle,these relations can also be used to remove cloud in an asymmetric cloudy field.It has been demonstrated by several tests that the spectral signals can be recovered quite well with above mentioned method and has a low calculating costs for sampling,regression and correction.

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Review of Road Extraction from Remote Sensing Images
WANG Pei-fa,WANG Li,FENG Xue-zhi,XIAO Peng-feng
Remote Sensing Technology and Application    2009, 24 (3): 284-290.   DOI: 10.11873/j.issn.1004-0323.2009.3.284
Abstract7787)      PDF(pc) (681KB)(2243)       Save

With the rapid development of remote sensing and information extraction technology,it is possible to automatically update the geographic information.The road is important manmade object and is component of geographic information data.Road information exacted from remotely sensed imagery to update the GIS database has become a hot research spot for many years.This paper summarizes the course of development on road extraction from imagery,and review main methods of road extraction,template matching,knowledge method,Snakes model,dynamic programming,ridge and valley exaction method,morphological method,Hough transform,multi-scale method,method based on segmentation and other techniques for road exaction as well.The characteristics of various methods and insufficient of road extraction from remote sensing imagery were analyzed.Finally,subsequent studies were prospected.

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Ship Target Detection from Optical Satellite Remote Sensing Image based on GLRT
Xu Junyi,Ji Kefeng,Lei Lin,Du Chun
Remote Sensing Technology and Application    2012, 27 (4): 616-622.   DOI: 10.11873/j.issn.1004-0323.2012.4.616
Abstract7683)      PDF(pc) (1965KB)(1151)       Save

The technology in optical satellite remote sensing develops quickly,which is important to seek how to detect the ship target from large amounts of optical satellite remote sensing images.Aiming at the problem that traditional CFAR detection cannot detect the black polar target,a ship target detection method based on GLRT (Generalized Likelihood Ratio Test) is proposed.Like CFAR detection,this method uses a sliding window to detect target.Assuming the intensity of the background and target follow Gaussian distribution,detects the target through the judge that the distribution in the background window and target window is the same by the GLRT theory,which considers both the white and black polar target.Detection is operated in the image blocks and morphological operation is used for target cluster.The images used in Experiments come from SPOT5 and CBERS.Assume that the intensity of the background follows Gaussian distribution is validated.The result of detection in two images shows that this method can detect the black polar target and have fewer false alarms than CFAR detection.The ROC curve and the cost time that is 40% less than CFAR detection,and further show that this method is more superior.

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Integration of Airborne Hyperspectral CASI and SASI Data for Tree Species Mapping in the Boreal Forest,China
LIU Lijuan,PANG Yong,FAN Wenyi,LI Zengyuan,LI Mingze
Remote Sensing Technology and Application    2011, 26 (2): 129-136.   DOI: 10.11873/j.issn.1004-0323.2011.2.129
Abstract7681)      PDF(pc) (4653KB)(489)       Save

Integrating CASI and SASI airborne hyperspectral data could help acquire both continuous narrow-band spectra covered the visible\|near infrared\|shortwave infrared range and high spatial resolution information.It provides a new method for tree species identification in high coverage rate forest.However,due to the different spectral response of the two sensors,there were differences between the received radiances.How to integrate the two dataset effectively for tree species classification is still a problem.CASI and SASI data have both different coverage of spectrum and atmosphere impact.According to the characteristic of reflectance and absorption spectra of vegetation,experience linear method based on statistical model and MODTRAN model based on radiative transfer theory were used for atmospheric correction of CASI and SASI data respectively to retrieve the real spectral reflectance of ground object.Then CASI and SASI data were integrated (CASI + SASI) by Savitzky-Golay filter function smoothed continuue removal spectra to reduce noise and abnormal points.Compared the integration of CASI + SASI spectrum with the field measured spectrum showed that the two curves matched well each other.In addition,the integrated spectra have richer spectral information for tree species distinction than any single one.Tree species mapping was realized base on the integration of CASI and SASI data using SVM classifier.An overall accuracy of 86.21% and Kappa coefficient of 0.8297 were obtained.And the result indicated that the proposed method to integrate CASI and SASI data is feasible for a more accuracy in forest tree species classification,and it would be a reference for the later research.

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Classification and Verification of Land Use/Cover in Australia Using MODIS Time-series Data
JIA Ming-ming, LIU Dian-wei, SONG Kai-shan, WANG Zong-ming, JIANG Guang-jia, DU Jia, ZENG Li-hong
Remote Sensing Technology and Application    2010, 25 (3): 379-386.   DOI: 10.11873/j.issn.1004-0323.2010.3.379
Abstract7669)      PDF(pc) (2764KB)(1412)       Save

his study is to classify land use/cover of Australia in 2000 based on data MOD13Q1,for it's sensitive to climate change.In order to reconstruct high quality NDVI time series data,Savizky-golay filtering method was applied for the NDVI data set.In this study,a combination of unsupervised classification of ISODATA and hierarchical decision tree was applied for the land use/cover classification over the whole country of Australia,and NDVI values of specific season,transformed NDVI values,and principal component analysis were also performed on the data set for decision tree threshold value choosing.Based on area of contract and spatial location matching to assess the accuracy of the classification,comparison the classification results of MOD12Q1,GLC_2000 with the results was done for this study.Random selected samples and generate confusion matrix.The overall classification accuracy of 63.65% and the Kappa coefficient of 0.56 were achieved in this study.This result is better than the result achieved in MOD12Q1 and GLC_2000.

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The Spectral Characteristics Separability Analysis of Spectral Database of Typical Objects of Land Surface based on Bhattacharyya Distance
Cheng Xi,Shen Zhanfeng,Zhou Ya nan,Xia Liegang,Luo Jiancheng
Remote Sensing Technology and Application    2013, 28 (4): 707-713.   DOI: 10.11873/j.issn.1004-0323.2013.4.707
Abstract7666)      PDF(pc) (1802KB)(683)       Save

Typical land surface spectrum data are mainly applied in related basic research of quantitative remote sensing and image classification.We selected representatively spectral library set of vegetation spectrum(73 items),manmade spectrum(100 items)and soil spectrum(30 items) from USGS and JHU  spectral  library,and analysed typical separability features of materials spectral features in 4.2~2.5 μm wavelength range within a hierarchical classification scheme,Application of Bhattacharyya distance to quantitatively calculated among different categories objects spectrum spectral differences:the calculation results show that spectrum separability metal,brick and concrete manmade material spectrum for vegetation,soil and other natural materials spectrum have greater spectral differences,and separability of plastic between natural features is smaller.Additionally,an evaluation of the most suitable wavelengths for separation of spectral library set identified specific spectral features that provided the best separation.Based on the statistical characteristics of spectral differences could reflect the optimal band.The study provides a basic knowledge reference of spectral discrimination analysis in a variety of material spectrum and also have the certain reference significance of remote sensing image land classification in a larger scale.

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Monitoring Spatial Patterns of Vegetation Phenology in Heihe River Basin based on Remote Sensing
Yang Yongmin,Tian Jing,Rong Yuan,Long Aihua
Remote Sensing Technology and Application    2012, 27 (2): 282-288.   DOI: 10.11873/j.issn.1004-0323.2012.2.282
Abstract7659)      PDF(pc) (3205KB)(1407)       Save

Monitoring vegetation phenology is very important for many aspects,such as seasonal appearance of plant,crops production,global change,ecological study.Vegetation index is an excellent index for monitoring vegetation appearance.With the development of remote sensing,it has become a new way to extract vegetation phenology.We use the filter of Savitzky-Golay to rebuild the time-series of SPOT Vegetation NDVI,then we extracted the spatial patterns of vegetation phenology in Heihe river basin.The results show:Vegetation phenology information obtained using this method is in good agreement with the farming calendar of this region.Vegetation phenology have clear spatial patterns in Heihe river basin.Arctic-alpine meadow in the upper-stream have shortest growing season.While ,the oasis in the middle-stream have much longer growing season.In the middle-stream,human activities greatly influenced vegetation growth,vegetation phenology is in good agreement with the farming calendar.

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Road Network Extraction based on Airborne LiDAR and High Resolution Remote Sensing Imagery
Gao Lipeng,Shi Wenzhong,Lv Zhiyong,Zhang Hua
Remote Sensing Technology and Application    2013, 28 (4): 562-568.   DOI: 10.11873/j.issn.1004-0323.2013.4.562
Abstract7636)      PDF(pc) (3086KB)(666)       Save

The conventional mathematical morphology method using single data source to extract road network which could not take full advantage of the road characteristics,the extracted road information was not complete.In view of this drawback,and base on the airborne LiDAR data can provide elevation information,this paper proposes a method which combines the airborne LiDAR data with high resolution remote sensing images to extract city road network.The airborne LiDAR data and high resolution remote sensing QuickBird images of Xuzhou were taken as the experimental data,the precise registration between them were first done,then the FRIR (False Road Information Removing) method was used to remove the vegetation and buildings separately,so the basic road contour was displayed.Finally,this paper achieved an Improved Road Trimming (IRT) algorithm under the ArcGIS and Matlab programming environment,the road network was trimmed by the algorithm,then a smooth and continuous city road network was obtained.The result of the accuracy evaluation indicates that the method was proposed can be used to avoid the influence of the building shadow,city squares,parking lots and the vegetation groups on both sides of the road to the road centerlines extraction well,and the recognition accuracy of the road network is more than 84%.

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Monitoring and Assessment of Highway Disaster after Ms 7.0 Lushan,Sichuan Earthquake based on Remote Sensing
Ren Yuhuan,Xu Qing,Liu Mengmeng,Liu Xianglong,Wu Zhongyi,Zhang Huaizhen,Liu Yalan
Remote Sensing Technology and Application    2013, 28 (4): 549-555.   DOI: 10.11873/j.issn.1004-0323.2013.4.549
Abstract7629)      PDF(pc) (1583KB)(732)       Save

After the 7.0 magnitude Sichuan Lushan earthquake occurred on Apr.20th,2013,the secondary geological disasters caused many damages of highway.It was an important and basic job of emergency relief for highway disaster monitoring fastly and accurately.There was a mature and effective way of obtaining highway disaster information based on remote sensing images and information extraction technology.Utilizing domestic remote sensing satellite images as well as airborne aerial images acquired by Institute of Remote Sensing and Digital Earth,Chinese Academy of Sciences,it focused on highway disasters monitoring with image\|based visual interpretation and analysis methods.After information extraction,433 geological disasters were found around roads and collapse was the main types of disaster.197 disasters have impacted highway and the total length of damaged sections was about 10 km.Meantime,there were 63 disasters became a serious threat to highway,which should be paid attention to analyse.The field investigation proved the road disaster extraction results were reliable.The highway disaster monitoring result was provided to the Ministry of Transport of People’s Republic of China within two days after the earthquake,and it was a sufficient basis for carrying out road repair scientifically and effectively.

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Review on Methods for SNR Estimation of Optical Remote Sensing Imagery
ZHU Bo, WANG Xin-hong, TANG Ling-li, LI Chuan-rong
Remote Sensing Technology and Application    2010, 25 (2): 303-309.   DOI: 10.11873/j.issn.1004-0323.2010.2.303
Abstract7605)      PDF(pc) (794KB)(2633)       Save

The signal-to-noise ratio (SNR) is one of the most important indices which can be used to evaluate the data quality obtained by a remote sensor.To a great extent,the SNR of an image reflects the SNR of the remote sensor.Several typical methods to estimate the SNR of optical remote sensing imagery are summarized in this paper,and their merit and restrictions are presented.And this paper also performs the comparison and analysis between these methods based on their own principles,from six aspects including the automatic computation,the computing time,the stability,the applicability,the suitable sensor category,and the uniformity of estimating areas.In addition,the paper points out that the comparison and analysis between methods in various specific applications should be done in the future.The study will help to choose a reasonable SNR estimating method aiming at different remote sensors and different types of remote sensing images.

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Estimation of Evapotranspiration in Yellow River Delta Wetland based on Two=Source Energy Balance (TSEB) Model
Li He,Wang Hong,Kong Yan,Li Ling
Remote Sensing Technology and Application    2012, 27 (1): 58-67.   DOI: 10.11873/j.issn.1004-0323.2012.1.58
Abstract7605)            Save

Evapotranspiration(ET)as the main form of exchanges between the water and heat to the soil—atmosphere of the wetland ecosystem greatly affects the water thermal equilibrium.Estimation of the evaporation quantity reasonably and accurately is one of great significance to study hydrologic recycle,energy balance and scientific management of the wetland ecosystem.Wetland in Yellow River Delta(YRD),which is the most integrated,broadest,youngest wetland ecological system in warm temperate zone of the earth,is not only sensitive to climate change,but also fragile to the environment change.Remote sensing technique was used to estimate ET in YRD in our case study.Coupling the model of Surface Energy Balance Algorithm for Land(SEBAL)and Two=Source Energy Balance(TSEB),SEBAL was used to calculate land surface characteristic parameters and flux,and TSEB was used to calculate vegetation transpiration,soil evaporation and total ET separately of YRD by Considering the inner structure of the surface layer which could be divided into two sub layers representing soil and vegetation.Actual evapotranspiration of the study area was meatured from stations and calculated with Penman=Monteith equation to compare with results from remote sensing,which showed that the result is reasonable.Then the spatial distribution of the daily ET was analyzed and the characteristics of ET with different features,especially with the typical vegetation of reed marshes and meadows,were also analyzed to help realize the wetland conditions.The results illuminates that daily ET estimated is reasonable.The method can be used for the accurate estimation of ET in YRD.

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