Chlorophyll-a concentration estimation is an important part of the remote sensing monitoring of water quality parameters,traditional estimation model largely depends on place and time because of sampling limit.Spectral smoothing can improve the common features of different datasets,thereby increasing model prediction precision,smoothing method was used to improve the application accuracy of the chlorophyll estimation model.Based on the datasets of four months in Taihu lake-two months in summer of 2004 and two months in spring of 2011,this study compared the spectrum difference above the turbid water surface before and after Moving average smoothing,Savitzky-Golay smoothing and Kernel Regression smoothing,and discussed its influence on three-band estimation model and model application precision.The result shows that model residual of estimation model after Kernel Regression spectrum smoothing fits the normal distribution better,indicated that the estimation model is more stable.When model in July was used directly in August,2004,RMSE of Chla estimated decreased from 33.56 mg/m3 before smoothing to 25.60 mg/m3 after spectrum smoothing;when model in March was used directly in April,2011,RMSE of Chla estimated decreased from 16.68 mg/m3 before smoothing to 10.57 mg/m3 after spectrum smoothing.It can be concluded that Kernel Regression smoothing of in-situ spectrum can increase the application precision of Chla three-band estimation model,and the improvement is more significant in summer data which has a large chlorophyll-a concentration range.
GLASS is a series of products newly produced by domestic team,which needs validation before further application.Validation of GLASS LAI products is implemented by field measurements in Xilinhot grassland and corresponding Landsat TM data.Besides,validation of MODIS LAI product is taken as a contrast.The results of validation indicate the over-estimation of both GLASS LAI and MODIS LAI.GLASS LAI in the mid-July over-estimates LAI is about 11%,which is obviously smaller than MODIS LAI (36% over-estimation),and the both products in the end of August show the similar extent of over-estimation.GLASS LAI products consist better with the LAI inverted by Landsat TM,and the determination coefficients R2 of the two periods are respectively 0.72 and 0.58,which are both larger than MODIS LAI products (0.61 and 0.27).According to the analysis,the main source of the error of both products,GLASS LAI and MODIS LAI,is the models accuracy,and the error from the data quantification is only less than 5%.These results suggest that GLASS LAI products in Xilinhot grassland have better accuracy and consistency,and are more applicable than MODIS LAI products.
Taking Guangzhou city as the study area,Land Surface Temperature(LST) was calculated by a generalized single-channel algorithm,which was proposed by Jiménez-Munoz & Sobrino’s,basing on the HJ-1A-B thermal infrared data.At the same time,the information of impervious surface area(%ISA) was obtained by one of the Principal Component Analysis-called MNF and the support vector machine.The land use situation,as well as the land cover types,was categorized by the method of orient.After that,the spatial distribution characteristic of UHI(Urban Heat Island) in the study area and its relationship with the land cover types and other affecting factors(including the %ISA,NDVI and Grass) were studied quantitatively.The research result shows that,compared with other single channel methods,the method of JM&S can retrieve the LST well In additional,the LST distribution in Guangzhou is correlated positively to the area of ％ISA,but negatively to NDVI and GRABS information.In all,as the urban expansion of Guangzhou,the UHI is corresponding sprawling,and this phenomenon will keep getting worse and worse.
Land Surface Temperature(LST) is the indicator of soil moisture and vegetation water status.Using Landsat TM data and meteorological data the land surface temperature of Baisha irrigation was retrieved by mono-window algorithm and single channel algorithm.Normalized Difference Vegetation Index(NDVI) to distinguish between land cover types and calculated the surface emissivity using Van de Griend’s empirical formula and typical surface assignment method.The results show that both the two methods could reflect the land surface temperature distribution trend of Baisha irrigation,and mono-window algorithm gets a higher precision result,the absolute error is 1.1 ℃,it is more suitable for the retrieval of Baisha irrigation land surface temperature,which can improve the accuracy of drought remote sensing monitoring in the Baisha irrigation area.
Vegetation Index(VI) is one of the main biophysical performances of vegetation,and a useful tool for global and regional detection.It has been used effectively in nuberous of applications,such as detecting change and derieving biophysical properties.However,the daily VI products are not satisfactory because of cloud and atmospheric contamination,so that a compositing technique for multi\|temporal is usally employed.In this paper,firstly,we investigated the contaminatal sources of VI compositing.Secondly,we classified VI compositing algorithms,including the advantages and disadvantages.And then we summarized the commonly used products of current continental or gloabal VI products,and their products validation.Finally,we made a brief review on current compositing algorithm and proposed a prospect in VI compositng method.
Since the new century,altimetry technology of satellite radar is rapidly developing and shows the new development trends,parts of fields which have entered the business implementation stage.This paper introduces in detail radar altimeter’s application in surveying and mapping of the sea,terrestrial water and glaciers,and analyzes some problems existing in the technology.In the field of radar altimetry,there is still a big gap between China and western developed countries,so it’s very necessary and timely to strengthen the field research.
With the characteristics of wide coverage,high observation frequency and flexibility,geostationary satellite has unique advantages in the national disaster reduction and relief.By detailed review on the development of optical geostationary satellite worldwide,the application status on geostationary satellite for disaster monitoring and early warning,as well as existing problems are discussed in this paper.From the perspective of the practical demands on each phase of disaster management,the potential applications of optical imaging geostationary satellites for disaster reduction are analyzch based on the observation capacities of geostationary satellite and its payloads at present stage.Accounting to the operational implementation requirements for disaster mitigation and relief,the skills and technical capabilities of geostationary satellite are investigated in terms of working mode of satellite,temporal resolution,geometric properties,spectral range and radiation performance,which can support and benefit to the construction of our countrys geostationary satellites for the purpose of disaster prevention and mitigation.
Affected by global warming,the annual outbreak frequency of typhoons tended to increase,China is located in the Pacific Northwest,has become one of the world's few countries suffered the most serious typhoon.For its coverage of wide area imaging and high time resolution,satellite remote sensing data has become the effective data for typhoon disaster damage assessment.In this paper,based on the researches of recent years in typhoon monitoring,we discuss the application of remote sensing technology in typhoon monitoring status quo from the perspective of conventional observational data,meteorological satellite remote sensing data and microwave remote sensing data.What’s more,we also analyzed the problems and advantages of the various data resources and pointed out that meteorological satellite remote sensing data is the most popular data in typhoon monitoring,microwave remote sensing data has strong potential.Finally,we suggest that future studies should focus on the multi\|source data fusion and the typhoon monitoring system development.
“Eco-water(layer)” was provided with special watery features,whose parameters are difficult to be quantified and inverted by common methods,but hyperspectral remote sensing with plenty bands and abundant spectral information provide efficacious data source and method to invert the parameters of Eco-water.Using hyperspectral remotely sensing technology to analyze spectral characters and extracting sensitive bands of vegetation were very important.To meet the need of quantifying the eco-water’s parameters,in this paper,the spectral information of partial vegetation leafs in the study area was collected,the spectral data was derived,the original,the first derived and the second spectral curves of different vegetation leafs were analyzed,and the more different bands of different vegetation were extracted to distinguish the vegetations.Meanwhile,distance statistical method was to verify the validity of different bands.The results show that,there were some differences for extracted bands by three methods,but there were some same points,that is the extracted bands can effectively distinguish the different vegetations,especially the near-infrared bands which was 1 814~1 823 nm,1 874~1 883 nm and 1 890~1 899 nm.
MTF (Modulation Transfer Function) is an important indicator that is used to evaluate the performance of the optical remote sensing payload,and the knife\|edge method has been used in high resolution optical remote sensing payload on\|orbit MTF assessment widely.In this paper,the knife\|edge method is improved by the MTF assessment of the Airborne Linear Array remote sensing optical payload.And an improved accuracy analysis method is given by the factors of attitude impacts.With this accuracy analysis method and the use of the real load gesture data,the simulated knife\|edge images are made,and assessment accuracy of the improved algorithm is analyzed.
Using object’s sparsity,compressive sensing theory is able to breakthrough Nyquist sampling theorem and reconstruct object image from very few observations,which has become a very potential research field to achieve super-resolution image.One of the crucial problems of applying compressive sensing to earth observation remote sensing image is how to pursue effective sparsification method under the complexity of ground scene.It will be more practical for hyperspectral imaging with a large amount of data to search for effective spectral sparsification method using rich redundant spectral information in bands.This paper introduces the basic principle of compressive sensing spectral imaging and spectral sparsification,and trains a redundant dictionary based on K\|SVD method using multiple types of ground objects’ spectral data from ASTER spectral library,reconstructs several typical objects using DCT basis,wavelet basis and training dictionary via simulation experiment and compares the reconstruction results.The result shows using training dictionary as sparse basis performs is better at low sampling rate than DCT basis and wavelet basis,spectral curves can be reconstructed almost perfectly at sampling rate as low as 20%.Our research indicates the great potential for sparse dictionary applied in compressive sensing spectral imaging.
HJ-1A/B satellite is a new one which is studied and developed by China independently.However the study on the application of HJ-1A/B satellite images is not so much.Therefore in order to improve the capabilities of HJ\|1A/B images applied in classification,in this paper,LBV transformation and object\|oriented classification methods were used to HJ-1B images.Although there have been many LBV transformation methods for different remote sensing data,but none of them can be directly used to HJ-1B multi-spectral images.So new LBV transformation equations for HJ-1B multi\|spectral images were specially proposed based on the study of the spectral characteristics of nine typical ground features.And then these equations were used to three HJ-1B images to test and verify their feasibility and generality.At last,the LBV images on 12th November 2010 of Shenzhen city were classified by object-oriented classification method.The result showed that the transformed LBV images were more vivid,which made up the lack of spectral resolution of HJ images.What’s more,the LBV images were better at segmentation than original HJ data,and the classification accuracy could be 93%,which shows that LBV transformation has a good potential in interpreting and classifying for HJ-1B images.
Based on the MODIS NDVI products from 2001 to 2010,the spatio\|temporal characters of vegetation cover in the eastern China are investigated.Study methods include Mann-Kendall and Hurst index.The main results are as follows:The NDVI at pixel scale generally shows two kinds of temporal dynamics,most of the pixels were improving in the past and will go on improving in the future,which is benign changes,and in nearly 30% pixels it was degenerating in the past and will go on degenerating in the future,which is malignant changes.Two sub\|regions in the south China have more pixels that show the malignant changes.
LiDAR is widely used in land and resource survey,topographic survey,forestry,disaster evaluation and other fields,as it can obtain high precision surface model rapidly.The raw data of LiDAR cannot be used directly unless the points position be calculated firstly.So based on the analysis of the principle of the LiDAR System,a model of linear array push\|broom LiDAR points position calculation is derivated,and a method of LiDAR point cloud calculation is put forward.The effectiveness of the method is proved by the experimental results of test flight data.The method is suitable for LiDAR with the same scanning mode.
Spectral mixture analysis has been used to monitor and analyze urban surface composition in recent years. Pure pixel collection is the key procedure of spectral mixture analysis. Taking Xiamen as an example,this paper compared twelve pure pixels collecting methods with different ratios of low to high reflectance pure pixels in both soil and impervious surface endmembers. Liner Spectral Model Analysis was applied in Landsat TM image acquired on January 8,2007 with four endmembers,vegetation,impervious surface,soil and water.Then this paper analyzed the model fitness of those twelve methods and assessed their accuracy through visual interpretation of SPOT 5 image acquired on December 25,2006. Results showed that,when selecting pure pixels of soil,it will improve model fitness and unmixing accuracy by taking both bare soil of low reflectance and bare rock of high reflectance into consideration;it will generally improve the unmixing results of all endmembers by raising the ratio of high reflectance pure pixels for impervious surface,especially for soil and water endmembers.
An algorithm of missing CCD data interpolated by SAR due to cloud was proposed in this paper.The core of this algorithm was:by analyzing the spectral characteristics of the cloud and its shadow,the cloud and its shadow extraction model was put forward;the CCD and SAR matching transformation algorithm as well as the cloud-effected pixel replacement operation were then used to generate the new interpolated CCD data.The correlation between the measured sea surface salinity and the retrieved sea surface salinity which was obtained by the CCD data retrieval algorithm which was used to test the above missing data interpolation algorithm.The results demonstrated that the accuracy of retrieved sea surface salinity in the missing data region of the target sea area was R2=0.8441,RMSE=0.7031.Therefore,the algorithm of missing CCD data interpolated by SAR was generally practical and compatible with different sources of data.Moreover,the algorithm restored the actual condition of the noise underlying surface in some extent,and along with multiple sensors,it could generate the complete space-time data products with high precision.
In this study,MCD12Q1 over North America from 2001 to 2009 were downloaded,and their overlapping area of the permanent wetlands was taken as the study area.GIMMS NDVI from 1982 to 2006 was used to explore the seasonal and inter\|annual dynamics patterns,and their drivers used the Global Historical Climatology Network-Monthly temperature and precipitation.The results showed that there was a single-peak curve for seasonal dynamics of NDVI,and the maximum value was appeared in the summer season.Generally,the average NDVI was increasing from 1982 to 2006 during spring,autumn,and the whole of year,while NDVI was decreasing during summer and winter.A positive significant correlation (P<0.01)was observed between the seasonal variations of NDVI and temperature and precipitation around study area,as well as for annual variations of NDVI during spring,summer,autumn with temperature,and during spring,autumn,winter with precipitation showed positive correlation.However,due to the influence of human activities and other disturbances,some uncertainties still need to be studied in future.
Acquisition of accurate 3-Dimension buildings information in urban environment is of great importance to urban planning and management,disaster risk assessment and prevention.This paper presents a 3D building reconstruction method based on IRS-P5 stereo images and GeoEye-1 high resolution images.Firstly,we performed image fusion to the GeoEye-1 multi-spectral bands and panoramic band to get a high spatial resolution multi-spectral image.Then the image was classified using the object-based classification method.Outlines of buildings were extracted from the classification and modified result.The IRS-P5 stereo images were used to extract Digital Surface Model (DSM).Elevations of above-surface features were calculated by subtracting the registered Digital Elevation Model (DEM) from the DSM.Finally,the 3D buildings were reconstructed by combining buildings’ outlines their elevations.Results of our case study in the Tairi community,Fengxian District,Shanghai prove that our method can produce accurate 3D building information.The method also has great potential of application,furthermore IRS-P5 and GeoEye-1 images are easily available.
Northern Tibet is located in the hinterland of the Qinghai-Tibet Plateau,and abounds in grassland resources.While in recent years,Northern Tibet has experienced serious grassland degradation.In order to investigate the grassland degradation and its main driving factors in the central of the Northern Tibet during recent 20 years,the grassland landscape were classified using hybrid classification method and Landsat images for years of 1990,2000 and 2010.The classification accuracy was 78.0% based on the field data in 2010.The characteristics of the landscape patterns and grassland degradation were analyzed through calculating landscape indices,which included dominance index,evenness index,fragmentation index and diversity index.Finally,the main driving force for the grassland degradation was discussed using the Gray correlation method and the meteorological data.The results showed:the area of degraded grassland increased in 1990~2000,while decreased from 2000 to 2010.After the year of 2000,the grassland degradation is easing due to grassland restoration measures and grassland contract responsibility system.The change of climate has great influence on grassland degradation,and the major influence factors are precipitation,temperature,sunshine duration,and evaporation.The alpine meadows grass was mainly influenced by the average relative humidity and precipitation.The alpine grassland grass was mainly influenced by evaporation,the average relative humidity,precipitation,average minimum temperature,average maximum temperature,and sunshine duration.The desert grass has a close relationship with the average maximum temperature,sunshine duration,and evaporation.
Typhoon is one of the most severe natural disasters.Monitoring the typhoon timely and quickly is very significance for Typhoon disaster evaluation.HJ-1A CCD remote sensing images were used to study the changes before and after typhoon intrusion,taking NO.17 severe NEAST of 2011 as an example.Selected two CCD images,including July 8th,2011 and Dec.25th,2011,then extracted the NDVI information of 7 farms before and after typhoon with the course of image pretreatment and vector cutting.Subsequently,extracted the NDVI of 7 farms from July 5th,2010 and Dec.27th,2010 for comparative analysis.Finally,established a linear model between the changes of NDVI and the distance from farm to eye of wind,applied the method of linear regression analysis.The results show that:①because of the typhoon NESAT influence,the NDVI of 7 farms decreased in different degree;②there was a linear positive correlation between the distance from farm to eye of wind and the decreased degree of NDVI changes,the closer is between the eye and the farms,the more declines NDVI values and vice versa.The research shows that it is possible to monitor typhoon impacts on vegetation by using HJ-1CCD satellite images.
Vegetation is an important element and has a complexity and uncertainty in remote sensing image,the extraction of vegetation by remote sensing is very difficult work.Vegetation is extracted using rich ETM+ data in mineralized alteration zone of west Tianshan,Xinjiang in order to subsequently extract the minerals alteration.In order to ensure better minerals alteration,the feature-oriented principal component analysis adds to optimal density segmentation is proposed based on the careful analysis of spectral feature of vegetation and minerals alteration.The results show that using ETM+ band 3 and band 4 combinations can better extract vegetation and this method has certain feasibility.
This paper takes Zoige Wetland as the study area to get the water and soil loss change and its effects on the shrink of marshes.In the study,the Landsat TM/the ETM data acquired in 1989,2000,2005 and 2010 which have been used to derive the land cover and vegetation fraction data,and Aster DEM derive the grade of slope.According to ‘Standards for classification and gradation of soil erosion (SL190-2007)’,the data in the raster format have been overlaid to assess the status and change trend of soil erosion in Zoige Wetland in last 20 years with the support of spatial analysis of GIS.The results show that the hydraulic soil erosion area is widely spread in Zoige Wetland,but the gradation of water and soil erosion is slight.The degree of soil and water loss is aggravating and sediment deposition resulted from the soil erosion is also one of the main reasons for the rapid shrinkage of marshes before 2000.Its degree has shown the decreasing trend under the ecological environment construction and recovery measures after 2000,and the marsh shrinking speed has also slowed down.
Based on QuickBird high resolution image,which resolution is 0.61 m in Google Earth Software,this paper selected 22 typical crescent dunes in Mu Us Sandy Land,extracted their morphology parameter values in two different periods.Analyzing the change of the dune morphology parameters show that,in this region,the correlation between width and slip face horizontal length is significant.Crescent dunes in the process of moving,width decreases,windward slope horizontal length increases,and slip face horizontal length decreases;Dune movement speed and width have a good correlation,the annual movement speeds are between 3.5 and 9.5m/a.In the course of sand dune movement,some small dunes merged into bigger ones,while some typical barchan dunes degenerated into sand sheets,which illustrates the complexity of dunes movement.
Radar remote sensing is the most appropriate for agriculture monitoring and crops yield estimating as its capability of all-weather and day/night imaging.Especially,cultivated areas are most often cloudy and rainy in South China.The synthetic aperture radar—RadarSat-2 was adopted for winter wheat yield estimating in Guoyang County of Anhui Province.Using multi-polarization(HH/HV/VH/VV),the VV polarization was chosen according to this satellite image.And sampling in experiment lands,the linear yield estimating model was built based on yield and backscatter coefficient.Subsequent the yield estimating in the big areas winter wheat production was processed after winter wheat planting regions were extracted.After computing,above 80% precision yield estimating model and yield estimating results for winter wheat were obtained.Therefore,accurating yield estimating was attained.Applying SAR to yield estimating for winter wheat harvesting before about a week,then providing service to agriculture insurance,it illustrates these idea and method are effective.
The development of high spatial resolution satellite remote sensing data provides a new way for obtaining and updating of landslide hazard data.Loess plateau of Northwest China was chosen as the study area,this paper proposed a method of object-oriented regional landslide identification base on multi-feature,took advantage of single high spatial resolution remote sensing data,using the set and feature combination for landslides identification,experimental results show that this method is one of the effective techniques for landslides identification,which has vital significance for landslide hazard monitor,image understanding and geo-analysis.
With the rapid development of urbanization,the damage of land subsidence is growing.In this paper,taking Langfang City as the study area and using permanent scatterer interferometry (PS-InSAR)technology to get time series of land subsidence evolution characteristics from 2003 to 2007,then analyse the spatial distribution characteristics of Langfang land subsidence.The results showed that:the annual average sedimentation rate of Langfang city is from -19.2 mm/a to 18.7 mm/a,the settlement centers are mainly located in the northern region of urban area,and have a serious impact on city facilities and the construction.
Vegetation plays an important role in environment,so the protection and recovering of vegetation are the core of highway ecological environment construction.The traditional evaluation methodology of ecological environment is not able to reflect the vegetation environment generally and timely,so the practical work can not be satisfied.With the Changtan section of G5 highway as the test site,this study makes full use of the spectral advantage of RS,combines with physical method and mathematical analysis to build the HVHI model.The model calculating result can fits to the field test result well,which can conduct the preventive treatment of highway environment and lay the solid foundation for the operation of highway environment RS monitoring.
