Based on the level 1 data and the relevant ancillary data of the Moderate-resolution Imaging Spectro-radiometer (TERRA/MODIS),the aerosol optical depth over East China Sea was retrieved by International MODIS/AIRS Processing Package (IMAPP) and Two-Channel Aerosol Retrieval Algorithm,the inverse methods were validated with Aerosol Robtic Network (AERONET) solar direct radiance measurements.The distribution characteristics of aerosol optical depth and ngstrm exponent (which symbolizes the width of particle spectrum) over East China Sea during Oct - Nov 2002 were studied.The results indicate that the aerosol optical depth obtained by both methods over East Sea and the open sea area south of Japan are basically in consistent with the result from AERONET.However,due to the influence of Case 2 water,the aerosol optical depth is a bit high along the coastal area of Bohai Sea and Yellow Sea.The characteristics of East China Sea are analyzed,which provide the basic data for retrieval method over East China Sea.
In process of observing ocean wave with nautical radar,the roughness of offing will be changed for emergence of rainfall.So the intensity of echo signal which received from radar will be influenced.In this paper an analyzing and processing method is proposed for rainfall observation data in wave monitoring system by nautical radar.Firstly the statistic characteristic- mean value and variation coefficient of radar echo image are used as classifying criterion to distinguish rainfall and non-rainfall.Then the median filtering algorithm is approached to dealing with rainfall observation data in order to reduce the influence from rainfall.The experimental results indicate that the algorithm proposed in this paper has a good robustness and general performance.
The research of retrieving surface roughness and soil moisture under natural bare soils using SAR data has been refined over the last few years; Researchers have proposed lots of backscattering models and inverting techniques.Based on the backscattering models proposed,this paper established a database including surface parameters and backscattering coefficients as well as the surface parameters using genetic algorithm,backscattering coefficients in the database and the surface parameters; Then,the surface parameters were inverted using SIR-C SAR image based on AIEM and Oh models,respectively,and results were analyzed statistically.Therefore,the algorithm above supplies new idea for retrieving surface parameters using radar images.
The principal goal of this experiment study was to develop an objective,reliable and simple methodology for detection of Robinia Pseudoacacia Planted forest canopy health using Landsat ETM+ image data which would provide a cost-effective first-level indication of forest canopy health for forest managers.Digital procedures to optimize the information content of Landsat ETM+ image data for detection of Robinia Pseudoacacia planted forest canopy health were described.On the basis of phonological calendar of Robinia Pseudoacacia in the local region,imagery acquired on May 2,2000 was calibrated to exoatmospheric reflectance to minimize sensor calibration offsets and standardize data acquisition aspects,and Band 6 was converted into effective at satellite temperature in Kelvin.Then,a nearly pure artificial Robinia Pseudoacacia forest land was selected as the experimental area.Robinia Pseudoacacia forests were classified into healthy or slight dieback,moderate dieback,dead or severe dieback or shrub and grass lands,non-vegetation land using ISODATA classifier with three types of different band composition such as Band 1~5 and 7 (Group 1),normalized Green and Moisture component of Tasseled Cap transform (Group 2),normalized Green and Moisture component of Tasseled Cap transform and normalized effective at satellite temperature converted from Band 6 (Group 3).The results show that ISODATA classification of Group 3 was more effective method for detection of Robinia Pseudoacacia Planted Forest Canopy Health.
Based on the field measured data of corn,this paper established FPAR and LAI estimated models of the vegetation indices（NDVI,RVI,NDWI）,which were used to calculate FPAR and LAI with the MODIS BRDF (Bi-directional Reflectance Distribution Function) product of two periods.MODIS 15A2 FPAR/LAI,FPAR/LAI estimated by the vegetation indices models and BRDF data,and field measured FPAR/LAI data were compared.It can be concluded that NDVI,RVI were efficient to estimate FPAR and LAI for measured data and remote sensing data,NDWI was good for measured data but not for remote sensing data for atmospheric effect.The relation between FPAR/LAI estimated by BRDF data and the MODIS product was dependant on the growth periods,the vegetation indices estimated FPAR and LAI were larger than the product in the prophase of corn growing,but had the close value in the anaphase.The MOD15A2 FPAR and LAI are close to the measured data in the prophase,but smaller than the field data in the anaphase.The results showed that MODIS 15A2 FPAR variation was not sensitive enough for the field FPAR changes,which maybe a factor of restricting FPAR product precision.
Selection of optimum periods of vegetation classification is important for extracting crop planting area.Based on Landsat TM images and Spot-2 images in Beijing,spectral distance between winter wheat and other ground targets was calculated,and the phenological difference of main vegetation types in Beijing was analyzed.Then winter wheat was classified from each individual image or their combinations using maximum likelihood classification algorithm.Finally,based on ground surveyed samples and visual interpretation,the classification results were evaluated by overall accuracy and classification efficiency index for different cases.The results shows that: (1) the optimum periods for extracting winter wheat is early April(rising stage) with an overall accuracy of 92.9％;(2) the optimum combination for winter wheat identification is early April and late May (grain-seeding stage) with an overall accuracy of 94%.
Droughts hazard occurs frequently in nature and has a great impact on agriculture.Timely monitoring and assessment of drought conditions is critical to mitigate its effects.Using NOAA/AVHRR satellite data,we derived the normalized difference vegetation index (NDVI),soil-adjusted vegetation index (SAVI),land surface temperature (LST) and analyzed the spatial characteristics of vegetation indices and land surface temperature.The temperature vegetation dryness index (TVDI) was used to monitor the winter wheat drought conditions from March to May of 2005 in the middle-south part of Hebei Province.The results showed that the correlation of soil moisture with TVDI based on SAVI was better than that based on NDVI.The analysis of TVDI and soil moisture data from weather stations' measurement demonstrated that a good correlation existed between TVDI and relative humidity of soil at 10cm and 20cm.Therefore,TVDI is a better indicator for operational drought monitoring.
Reviewing the patterns of the landuse in the suburb area is greatly important to efficient and reasonable urban planning .Based on remote sensing images of 1988, 2000 and 2006,through classifying and analyzing,we achieve the process of land use change from 1988 to 2006 in Pukou area in Nanjing,then overlay and analyze the images of 2000 and 2006.Using data obtained from interpretation of remote sensing images and other statistical sources,land use changing patterns and their driving forces including economy,population and policies were analyzed.Finally，the trend of the land use change in this area is forecasted.
he paper,as an example of the project of "Return Grazing to Grass with Remote Sensing in Aba,Sichuan Province",discusses that the application and technique of utilizing the "3S" technology (RS、GPS and GIS) to monitor the project.Using the Landsat Thematic Mapper data and the measured grass yield data,the monadic linear regression models and the non\|linear regression models were established,to express the relations between grassland biomass and the different vegetation indices.It was shown that different vegetation indices could reflect most of practical information on plant community dynamic of forage and the biomass difference among different grassland types.For year round unfenced grazing land,the total above ground biomass,overall vegetation coverage,and average plant height were all lower than for fenced land.So,the combination of 3S and the field investigation,which are characteristic of celerity,precision and efficiency,can find the project of Return Grazing to Grass condition with high precision,which available the scientific direction for the government's macro decision\|marking and layout.
：The Grand Canal of China is the longest ancient canal in the world and the alive heritage.As the main artery between the northern and the southern,it plays an important role in history.The Grand Canal is the combination of cultural heritage,intangible cultural heritage and natural heritage.Only by safeguarding the canal well can we realize the goal that Grand Canal can apply the World Legacy successfully.The fact that the spatio\|temporal span of Grand Canal is large made the investigation difficult especially in the conventional way.Remote Sensing plays an increasing important role in the contemporaneity archaeology by right of the advantage of advance,convenient and economic.The RS images record the distributing and the status quo of the canal in different courses of history.The article analyses the spectral and spatial feature in order to extraction the canal automatically with the RS and GIS technology.The extraction of canal can provide the information for the application for World Legacy of the Grand Canal and offer the protection layout deciding support.
Using three images enhancement method (images subtract operation,IHS,density slicing on thermal infrared bands),this paper studied the application of thermal infrared remote sensing on detecting underground hot water,based on TM6 image which can reflect the radiate temperature difference.Combining the geological structure distribution rules and the field investigation,we get the unusual distribution area and the method which can detect underground hot water resource in the Shanxi province.
This paper studies the methods and technical routes using remote sensing technique in dynamic inspection of mining.The method is to collect and interpret the data from remote sensing image integrated with on-the-spot survey,so as to reflect the Mining conditions and the Mine ecological environment objectively.Some action of transgressed mine are in workaround by comparing and analyzing the interpretation results of remote sensing data in different time,which well achieve dynamic inspection of the mining.
Using CBERS-2 CCD data as "ground truth" images and based on the characters of geographic environment and climate in Northeast China, this paper modified the parameters of Salomoson's subpixel snow cover fraction model, retrieved the subpixel snow cover fraction from MODIS data and analyzed the stability and accuracy of the revised model with different ways. The result shows that the modified Salomoson model has stability in different geomorphology\|landscape unit, and the little fluctuation comes from the difference of snow physical character, atmospheric effects, and the errors of snow classification images and image registration. In the Northeast Plain, when NDSI ranges from 0.52 to 0.65, the accuracy of modified model is high. However, because NDSI is based on the non-linear transformation of band reflectance, snow cover fraction is little underestimated. The pixels, snow cover fraction of which is overestimated, are located in suburb and rural residential area. In contrast, the pixels, covering cities, towns and roads have a higher accuracy. The main reason is that human activity frequency influences the degree of spectral character difference between snow part and non\|snow part in one MODIS pixel. In comparison with MODIS snow products (MOD10A2), snow cover fraction provides much richer information than the traditional snow cover mapping methods, but both of them don't give the exact estimation of snow cover fraction in forest zone.
Based on remote sensing and geographical information system,the thermal infrared remote sensing image（Landsat ETM+）was used to retrieve the land surface temperature （LST）and normalized difference vegetation index（NDVI）of Lanzhou city,a valley city in Northwest China.The variance in LST and NDVI values associated with different landscape types was studied using GIS spatial analysis method,and the quantitative relationship was acquired by regressive analysis.Shannon Diversity Index（SHDI）and Contagion Index（CONT）were also introduced to analyze the spatial difference between LST and NDVI under the different spatial compound mode of land use.The result shows that there is an apparent correlativity between LST and NDVI.A significant inverse correlation relationship between LST and NDVI associated with all land use polygons,the same associated with each land type,but correlation coefficients associated with land use types are different. It is more sensitive of LST change on the influence of NDVI in the area of higher CONT or lower SHDI.
The artificial irrigation channel system plays a significant role in the development of the Zhangye oasis in the middle Heihe River Basin,northwest China.By using remote sensing,GIS and GPS approaches,the digital irrigation channel system map of the Zhangye oasis was firstly compiled based on a large number of high spatial resolution topographic maps and satellite images as well.This digital map includes the detailed spatial and property information of the Zhangye oasis' irrigation channel system in three levels (main channel,branch channel and tip channel) and has been widely validated and calibrated by intensive GPS ground\|measurements over all the channel network of the oasis.The channel spatial structure and its relation with the local land use evolution were analyzed in this study.Currently,the total number of the irrigation channels in the Zhangye oasis is about 6300,in which the main channels,the branch channels and the tip channels account for 21.9%,25.54% and 52.54%,respectively.The total length of the whole channel system reaches to 8 749.51 km with an average channel density of 0.47 km/km2.Among the five counties in the Zhangye oasis,the Ganzhou district has the densest irrigation channel distribution,whereas the Shandan county has a relatively poor channel construction.The development of the artificial irrigation channel system and the water resource exploitation in the arid oases could greatly affect and change the local landscape pattern and land use style.
The directly derived landform information can hardly meet the acquisition for the influence of multi\|scales of DEM, the macroscopic and diversity of terrain.At the same time, the precision is uncertain using DEM to extract slope.Taking typically physiographic plain and upland of northwest droughty area for example and using 1:10000 and 1:50000 scale DEM ,the slope driving results are compared and the variation rules are analyzed.The error of slope-extraction in quantity are simulated.
The ground calibration experiment for ESA's SMOS Mission will use an L\|band radiometry to measure soil brightness temperature of Takelamagan Desert.This radiometry's calibration "cold" target is cold sky.Because of the complex condition,in L-band,many factors have effect on brightness temperature of cold sky.This issue establishes a sun radiation model to calculate real\|time brightness temperature when it crosses the view field of antenna to the position relationship between sun and earth， also between sun and antenna.It analyzes briefly the radiometric temperature under the influences of moon,planets in our solar system and galactic radio emission.This issue provides theoretical and numerical reference for choosing the cold sky as "cold" target in calibration.
This paper analyses problems in application of local topographic map updating by using ortho\|rectified CBERS\|02B IHR data (2.5 m high\|resolution images) which is compared with multi\|source data.The experimental research results will hopefully serve as useful feedback information for using ortho\|rectified IHR data combining with land\|use updated surveys or other multi\|sources data to renew 1:10000 topographic maps.Consequently,update cycle of topographic maps is shortened and value of up\|to\|date is improved.
Residential areas are a familiar object which appears in SAR images,and it has many vital applications in various aspects.A new solution of residential areas extraction is presented in this paper.According high gray value and texture feature of residential areas,we convert the SAR image to discrete points of residential areas with Sobel operator and Otsu threshold algorithm,then we segment it in several blocks with Kmeans clustering,finally implement automatic residential areas extraction using Graham algorithm.Both the theoretical analyses and the experimental results indicate that the proposed method is a highly efficient method of residential areas extraction.
The vector contour representation method play an important role on directly distinguishing dock and ships contour from harbor contour.On the analysis of existed contour representation methods and application requirement,the paper designs and implements a specific vector contours representation method.Dock and ship can be distinguished on analysis of adjacent vectors dimensional relation.Experiments indicate the method is effective on detection ships on harbor.
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.
