Urban built-up land is a complex land-use class and has a heterogeneous characteristic in reflected electromagnetic spectrum. Therefore, it is difficult to be extracted from remote sensing imagery.This paper proposes a new index-based built-up index (IBI) by careful study of spectral features of urban built-up land. The new index distinguished from other traditional indexes for its use of thematic index-derived bands rather than original image bands. The application of the IBI in ASTER and Landsat ETM+imagery has shown that the new index can significantly enhance the urban built-up land information.Moreover, like vegetation and water indexes, the IBI can also be used for digital computation and thus make it possible to quantitatively study the relationship between urban built-up land and urban eco-environment. The case studies in Xiamen and Fuzhou Cities of south China shows that the IBI has a positive relationship with the land surface temperature (LST) and negative with water and vegetation indexes. Moreover, this study has discovered that the IBI has an exponential relationship with the LST,rather than a simple linear relationship. This suggests that the areas with high built-up land percentage will accelerate the increase of LST much more than the areas with low built-up land percentage and thus contribute much more to the development of the urban heat island.
Based on the analysis of the relationship between building-height and shadow-width in the high resolution satellite image-QuickBird, the paper applies the result of extracting building heights from shadow in image to the field of estimating FAR, and realizes estimating building density and FAR fast and efficaciously. Taking YuZhong District, ChongQing city for instance, by comparative analyzing the building density and FAR of the district, it can be found that the urban layout is profoundly affected by economy. The general laws are with the growing of economy, FAR improves, while the building density falls. The validating result shows that the accuracy of estimating floor-number has reached 88.3%, which has demonstrated prospecting applications of satellite remote sensing for urban purpose.
This work was to give an identification mode of petroleum pollution concentration within water body using remotely sensing technique. For this purpose the field data, including the spectral data of water body and the petroleum pollution concentration within water, were collected at Huanjiang river, Rouyuan river and Malian river in Qingyang city, Gansu province from April 6 to April 7,2006 and from October 15 to October 17,2006. The samples collected in the first field were employed to establish the identification mode of petroleum pollution concentration according to Fisher multiclass discriminant rule. By the actual status and the national standard, the petroleum concentration were classed three level. The field spectral
data were processed as corresponding bands of Landsat/TM. And the petroleum concentration can be identified as the following equations
class1=-132.003TM1+1088.964TM2-613.444TM3+113.629TM4 (1)class2=-108.2TM1+1135.458TM2-645.701TM3+87.264TM4 (2)class3=9.369TM1+1018.522TM2-619.677TM3+89.38283TM4 (3)Where TM1, TM2, TM3, TM4 are respectively the corresponding band of Landsat/TM, and class1,class2, class3 represent three level of petroleum concentration. The accuracy reaches 89% with the validation of the samples collected in the secondary field. Further, the model was applied to the two Landsat/TM images collected on Oct. 16, 2005 and Apr. 10, 2006 in order to obtain the distributing image of petroleum pollution concentration in the rivers. By mean of the image the temporal change and spatial distribute of the petroleum concentration within the three rivers were analyzed. The result shows that the establishment of identification mode based on remotely sensing provides an effective means to obtain rapidly and low-cost the concentration of petroleum pollution concentration in water environment.
Ocean architectures such as oil platforms will probably produce ocean pollution. SAR (Synthetic Aperture Radar) can detect both ocean stationary targets and ocean pollution such as oil leakage. Ocean stationary targets can also be regarded as reference points for precise location of ocean SAR images. 2LIHP(Two-Looks Internal Hermitian Product) method is capable of detecting ocean stationary targets.However, the moving ships also be detected at the same time as false targets. Based on the results obtained by 2L-IHP, shape measurement method and sub-aperture moving targets detection method are used cooperatively for distinguishing stationary targets from moving targets in this paper. It is tested by using EnviSat ASAR SLC (Single Look Complex) data obtained in Bohai Sea, China. The experimental results show that the method proposed in this paper can detect
The significance of crop yield estimation is well understood in China. In this paper, the authors devised a remote-sensing-based winter wheat yield estimation model in Huanghuaihai Plain in China. The authors selected the Shijiazhuang City, Hengshui City and Xingtai City as a case study region which is located in the Plain. The monthly 8-km NOAA-NDVI MVC data and the yearly county-level statistic production data of winter wheat were used. The data lasts 20 years and is from 1981 to 2001. We selected the NDVI value between 0.20 and 0.80 and calculated the sum of NDVI value in each county to build the relations with the winter wheat production because the NDVI of terrestrial vegetations steadily increases with canopy cover in this range. In Huanghuaihai Plain, the period from March to May is critical to the winter wheat yield. The authors obtained the relations between the 3 months NDVI data and the final production respectively at the county level. The authors also provided the validation results about each statistical model and analyzed the precision. The results are satisfactory.
In this article, the author compared decisin tree classification technology with classic automatic classification technologies using Landsat ETM+ image data and GIS data of Tangshan City in Hebei. The result of this research showed: accuracy of decision tree classification compared with classic automatic classification technology was improved about 18. 29%, Kappa coefficient was increased by 0. 1878;classification accuracy was improved about 19.52% when DEM and its derivative data were used as ancillary data in the mountainous area, Kappa coefficient was increased by 0. 281; the classification accuracy was improved by 15.86% when the DN(Digital Number) values were converted to at-satellite reflectance values; tasseled cap transformation could cause classification accuracy to be reduced appreciably accompanied by compression of data amount.
There are still many problems needed to resolve about extracting road from remote sensing image, although a lot of efforts have been put in the area. The phenomenon of different objects with same spectrum is one of the problems, which often decreases the accuracy of classification based on spectral feature when we extract roads. In order to avoid this problem, the paper proposes the method that spectral feature and shape feature are all used to identify the road. The shape feature of the road is described by three shape parameters in this paper. The experimentation uses the image coming from the fusion of multispectral and panchromatic data. After the image is classified based on spectral feature, the objects that have same spectrum with road are removed in the classified image because their shape parameters are not like road' s shape parameters. According to the result of experimentation, the proposed approach can extract the main roads in the image effectively.
In the paper, after calculating DRE from ground-measured spectra of rice canopy in 32 small experimental areas, it is combined with the ground-measured LAI to create statistic model, of which the square relative coefficient can reach 0.6859. After pre-processing, atmosphere correction and mixture-pixel processing of the hyperion of Jiangyan and Taizhou, the DRE image is derived and then the LAI image is deduced based on the created statistic model. We also evaluate it with the ground-measured LAI from a large area. The result shows that our approach for deducing LAI from the statistic model is credible, as the linear coefficient between the ground-measured LAI and deduced LAI is about 0.84784.
In this study, a retrieval algorithm has been developed by multi-linear regression method based on a microwave radiative transfer model and a preliminary validation has been implemented. According to the retrieval results and microwave images of AMSR-E, a primary analysis of MATSA and TALIM has been done about the course of their occurrence and development. The results indicate that the retrieval results can achieve the precision of the operational product closely and accord with the actual condition in general. And the microwave images can indicate properly the dynamic characters of typhoon in the course of its occurrence and development. The condition of atmosphere and sea surface in the cloud and under the
cloud can be measured by space-borne microwave radiometric, which is a valid method in the analysis of typhoon. However the AMSR-E ocean products are not meant for real-time, operational analysis or forecasting of typhoon. The microwave remote sensing data can be used as the input of the typhoon forecasting model to improve the precision of the typhoon forecasting results.
As a modern global observation technology which can obtain the three-dimensional coordinate of surface of objects directly, Lidar (light detection and ranging) remote sensing can extracted Digital Elevation Model(DEM) quickly. In the study, the point-clouds data from Lidar system were filtered and
classified to separate the information of pure terrain from that of the objects, DEM was extracted and then the orthophoto map for Aerial Photos which were simultaneous with the Lidar data were produced. It will be based for information acquisition, quantitative analysis and substantiality modeling in further research.
MODIS data, with its advantages of high temporal resolution, larger-scale monitoring, free receipt, and convenient and timely obtainment, has become the vital information resource of the land-use research. This research, taking the zone of 38 degree of latitude in Hebei province as the experimental area, calculates the NDVI of MODIS data, according to the regular patterns of the leaf area while they growing, observe the change of the Normalized Difference Vegetation Index (NDVI), establishes the regulation of the classification and derives the area of the main vegetation. Under the support of GIS software, in the factors of area and shape of the region which was abstracted, we evaluated the accuracy of MODIS data classification comparing with TM data classification whose accuracy is 91% in the pixel scale.
Bursaphelenchus xylophilus, a alien species, has destroyed lots of forests in China. As a advanced spatial information technology, RS(Remote sensing)has more advantages in monitoring forests suffered by pests and diseases, and the spectral characteristics analysis is very important for studying forests suffered by pests and diseases with RS. In this research, 4 different types of Pinus massoniana were studied by measuring reflectance, plotting spectrum and differential spectrum. Then, the reflectance comparison in green,,red and near infrared bands among 4 types was finished. This study can provide an experimental reference to harmed forest dynamic monitoring with RS.
This paper explored the potential of using the remote sensing data of MERIS(Medium Resolution Imaging Spectrometer)and AATSR(Advanced Along-Track Scanning Radiometer) collected during the LOess Plateau land surface process field EXperiment 2005(LOPEX05) studies. By comparing with the daily ground observation to validate the satellite reflectance data, we established relationships between the vegetation water content and satellite remotely sensed indices. The two indices were NDVI (Normalized Different Vegetation Index) from MERIS and NDWI(Normalized Different Water Index) from AATSR.We used the daily ground observation to demonstrate that the NDVI was saturated during the study period while the NDWI continued to reflect the changes in VWC. NDWI was suggested to be superior based upon a quantitative analysis of bias that is 1.030 64 kg·m-2and 0.940 45 kg·m-2respectively. Therefore the NDWI was recommended to retrieval the vegetation water content.
Satellite-derived beginning and end dates of growing season at 7 sites of the temperate steppe area and 5 sites of the warm temperate deciduous broad-leaved forest area in China were determined with the measures of seasonal midpoint NDVI (SMN), inflection point by Moulin (MOULIN) and by Zhang(LOGISTIC), and moving average (MA) using NOAA/AVHRR NDVI time series data from 1982 to2000. The four measures were matched to surface observations and then their stabilities, accuracies, and validities were studied via compare of absolute error distributions, standard deviations, mean absolute errors, and correlation coefficients and so on. The results show that LOGISTIC is the most appropriate of the four measures in determining beginning date of growing season in both the steppe area and the forest area. As to satellite-derived end date of growing season in the steppe area, SMN performs best, followed by LOGISTIC with the senescence point defined as end date. In the forest area, of the four satellite-derived end date of growing season measures, LOGISTIC with the dormancy point defined as end date, is the most preponderant one. This paper provided a typical case and method to surface validation of the satellite-derived vegetation growing season and selection of various measures.
On the base of image preprocessing and collection of auxiliary materials, a kind of automatic category method for the land utilization patterns is put forward. Base on the great variance of remote sensing images in the Alpine and Gorge Region, the structure feature among spectrum of the land-use is analyzed. After using the data of RVI, NDVI and DEM, the single binary image is obtained with a suitable threshold. By taking the software ArcGIS9.0 as the platform, the single binary images are composed and exported .With this method, the influence by the same thing with different spectrums,
different things with the same spectrum is greatly decreased. The experiment results show that the method is very simple and effective to the semi-automatic extraction of the Alpine and Gorge Region land-use, and far superior to the traditional maximum likelihood classification method.
The spatial distribution and dynamic change of vegetation cover in the Huanghe-Huaihe-Haihe(HHH) zone are analyzed based on 8 km NOAA AVHRR-NAVI data from 1982 to 2000. The average value method, difference value method were used to analyze the monthly and annual changes.The linear regression of one variable was used to simulate the change trend of the NDVI values. As a result, the vegetation cover of the research area trends to increase as a whole, and the average NDVI value of the end of 1990s increased nearly 0.03 in contrast with that of the beginning of 1980s.The simulating results indicate that the NDVI vale of most regions increased, and the significantly increased regions mainly
appear in west and northwest parts of Shandong,east part of Henan,north part of Hebei and north part of Jiangsu, in which regions the significant level of F test reach to 99%.However, there are only some regions of Beijing, Tianjin, and middle of Shanxi where vegetation cover decreased.The monthly changes of NDVI of different vegetation types display intense seasonality,while the annual NDVI trend to increase fluctuantly.
In this study, based on analyzing the characteristic of the hot spot spectral radiance using related MODIS bands data, a new model named Normalized Difference Thermal Index(NDTI) was developed for the fire detection and monitoring. The algorithm of this model was discussed and given in details. Further well, the NDTI model was validated through a day fire case and a night fire case occurred in Heyuan China. Like NDVI, This dual-channel ratio index has the advantages that could attenuate conventional equipment noise and atmospheric effects. Research shows that the combination of fire radiation Channel 4μm and 11μm background components highlight the fire spots information access, by choose an appropriate NDTI threshold, the fire pixels could be accurately detected, the recognition rate can reach 93%. The NDTI may be widely used on sensor of the EOS-MODIS, NOAA-AVHRR, GOES-VAS,future NPP-VIIRS, future Chinese FY3 and more.
The principle of Interferometric Passive Microwave Imager (Aperture Synthesis Interferometric Radiometers) is to sample the spatial frequency spectrum of the field of view (FOV) with different baselines,each of which is composed of a couple of interferometric antennas. The output is called visibility function or spatial sample spectrum. Then, the images of FOV can be reconstructed with different algorithms and methods, such as Fourier transformation, Clean algorithm, Maximum entropy method
(MEM) and so on.
This paper introduces the basic concept of Interferometric Passive Microwave Imager first, and presents several features of 2-D frequency spectrum, from which some special brightness distributions of the FOV can be concluded. On basis of those features, the directions and positions of baselines with errors can be identified approximately, when the oscillations in the reconstructed images are obvious.
There are still residual system errors after calibration, which affect the spatial resolution, brightness resolution and accuracy. Therefore, four important errors (antenna position error, amplitude error and phase error in channels, and antenna pattern error), are analyzed in the paper, and baseline absence,which can be caused by antenna or correlator malfunctions, is also considered. And the effects caused by those errors in the reconstructed images, are presented.The analyses in the paper can provide the evidences to identify the error types and sources ofInterferometric Passive Microwave Imager, and also can supply important references to design enhancement algorithm.
To resolve the problem of antenna aims at synchronous satellite automatically in plane, we designed control method of antenna trails based on TMS320LF2407 Chip by counting quadrature encoded pulses(QEP). The quadrature encoded pulses consist of two sequences of pulses with variable frequencies and fixed phase shifts of a quarter of a period (90 degrees).The method used position and speed closed-loop to achieve preferable dynamic response and trail precision, at the same time gave software flow chart in scheme. In addition to, the article deduced calculational formula of antenna trailling angle.
Retracking is a key phase in the data processing for ocean radar altimeter to extract the precise ocean parameters. Traditional ocean retracking model didn' t consider the bias introduced by the instruments, and the bias can reduce the accuracy of estimates. This paper brings forward a new retracking model for radar altimeter, in which the point target response and weight window are utilized to revise the bias of signal model, therefore the accuracy of estimates is improved. This new retracking model is used to process the data of SZ-4 radar altimeter, and the results show that this model can effectively improve the accuracy of the estimates.
The Catalogue and Archive System, an important part for National Spatial Information Infrastructure, is crucial for searching and browsing data in the remote sensing satellite application. In the first part of this paper, the necessity of developing high compatible Catalogue and Archive System is explained. And the concept of compatibility of Catalogue and Archive System in this paper is given. Then the difficulties encountered in implementing high compatible system are pointed out. Finally, based on the new development of computer science, several outlines of implementing high compatible Catalogue and Archive System are described.
This paper proposed the calibration of view angle when retrieving land surface temperature using Moderate Resolution Imaging Spectroradiometer (MODIS) data. MODIS instrument provides high radiometric sensitivity in 36 spectral bands ranging in wavelength from 0.4μm to 14.4μm with resolution of 250 m, 500 m, and 1km at nadir. Two MODIS instruments integrated on Terra and Aqua provide global coverage every one to two days. These MODIS instruments offer a look at terrestrial, atmospheric, and
ocean phenomenology for a wide and diverse community of users throughout the world. The view angle can reach±55°with a 2 330 km swath at the EOS orbit of 705 km. The transmittance path will be great different with the view angle from 0～55°which will cause a big impact on the accuracy of land surface temperature retrieval. The impact of view angle to atmosphere transmittance and land surface temperature is discussed in detail. An example of bohai region indicate that the maximum view angle of MODIS data on the image edge can reach 55.02°, which can bring to the error of 0.086 for the atmosphere transmittance and 3.64℃for the land surface temperature.
Image registration plays an import role in image processing and computer vision. An automated image registration method based on corner feature is proposed to deal with the registration of image of similarity geometric distortion in this paper. Corners are extracted by an improved technique based on Harris and then compose virtual triangles. According to the principle that the corresponding virtual triangles are similar in the reference and sensed images under the similarity transformation, the most
similar two virtual triangles can be found. Their corresponding vertexes are used as control points and the parameters of similarity transformation are obtained. The proposed method is guaranteed to register images if only three corresponding corners are extracted from the reference and sensed images. Another advantage of the method is that there is theoretically no limited to scale, translation and rotation of two images. The experiment results prove that the proposed method is accurate and effective.
Based on the analysis of targets' polarimetric coherent scattering properties, we improved the polarimetric decomposition and unsupervised classification algorithm proposed by Cloude and Lee, making it adaptable to the complex terrain and target details in high-resolution Pol-SAR images. Our experiment results demonstrate that, compared with the conventional ones, the proposed method is able to further preserve the detailed target features, obtain much more accurate estimation of targets' polarimetric coherency matrix, and thus leading to a better decomposition and classification result. In addition, the proposed method is with good convergence and robustness.
This paper discusses the methods previously used in striping removal of TM, MSS, SPOT and presents a new method aiming at post classification images using IDL, ENVI and ERDAS. And I choose2005 SPOT image of Beijing as sample area to testify this method. The application results show that the new method can achieve a better result than the previously used methods mentioned in this paper in removing striping noise. The most important point is that this method can avoid some problems caused by striping removal process before supervised classification. They include calculating the striping pixels value incorrectly and the effects on non-striping pixels. So it can improve the precision of remote sensing classification. The new method is also applicable in striping removal of other multisensor remote sensing data.
Noise removing is an important part on preprocessing of satellite remote sensing image. Noise can be classified by representation as periodical noise and random noise, and also be classified by the reason of noise as periodical offset and apparatus electromagnetism. Noise depressed the image quality,sometimes even make true information invisible.Different noise phenomena often have different removing method. The noise remove method includes space field filtering method and frequency field filtering method are introduced at the same time. This paper introduce the noise phenomena and their removing method including pixel offset, bits offset , image line error, scan-Line noise from Landsat TM are described.We program methods above using VC++ considering the character of satellite, and the methods are proved to be correct by practice.
With the rapid development of technique on remote sensing image fusion, the methods of fusion have been ameliorated from pixel level to decision level recently.But how to quantificationally evaluate the resultant image impersonality and comprehensively is also a question. This paper brings forward brightness information, spa-texture information and spectrum distortion information by analysing and summarizing current methods of quantitative evaluation on remote sensing image fusion. Those parameters have been actualized via a program.At last,the multi-spectral bands and panchromatic band image of QuickBird sensors are fused with IHS(Intensity-Hue-Saturation)fusion and PCA(Primary Component Analysis)fusion. By evaluation the resultant with the parameters,it shows that quantitative evaluation is more available and comprehensive than qualitative evaluation.So the quantitative evaluation is suitable to evaluate the fused image.And it can support how to choose the appropriate method of image fusion.
Microwave remote sensing is influenced slight by cloud and atmosphere, which makes it have more advantage in study of global changing. In the developing of microwave remote sensing, the microwave radiometry has been proved as one of the best methods to retrieve soil moisture during the last25 years. However, many studies have shown that soil moisture is an important parameter in numerical weather-prediction model that lead to significant forecasting improvement in the physics of land surface processes on regional and global scales. But it is very difficult to obtain the soil moisture by ground measurement in both time and space, especially at large spatial scales. Thus satellite microwave owns these advantages. This paper introduces many modes and algorithms for retrieving soil moisture. The Q/P model is mainly suitable for bare soil and-model is mainly suitable for land surface covered by vegetation.There are two types retrieval algorithm are introduced. One is algorithm based on statistical method, and
the other is based on forward model. Finally, the prospect of passive microwave for soil moisture retrieval is discussed with the development of microwave remote sensing technique.
Wetland landscape ecological study is a rising research field for wetland study, which is based on landscape ecology. Remote sensing(RS) and Geographic Information System(GIS) have been widely used in wetland research in recent years. The advance of the two techniques has been providing new method and technical support for wetland landscape ecological study. On the basis of correlative research literatures in recent years, this paper respectively evaluated the application of RS and GIS techniques in wetland landscape ecological study. Four research areas were discussed for the application of RS, included:landscape pattern study, landscape function study, landscape dynamic study, landscape scale study. The application of GIS was summarized from four aspects as follow: assisted for landscape classification,landscape mapping and landscape index statistic, landscape dynamic information acquirement and analysis, landscape programming and management. In this paper, the advantages of using the two techniques in wetland landscape ecological study were analyzed, the problems existed at present were also discussed.
The prospect of the application of RS and GIS in wetland landscape ecological study was brought forward at the end of the paper.
