Aimed at retrieving internal wave parameters from a series of SAR images, this paper introduces a simulation-revision based method. This method first uses the RLW equation and M4S model to simulate the propagation of internal wave in a series of SAR images and then compares the simulation result with real SAR internal wave image to revise the retrieved internal wave parameters. Experiments show that this method overcomes the historical hydrographic data precision dependency and SAR image condition restriction of the traditional methods. The coherence between the retrieval results and in-situ data records indicates that this method has a higher retrieval precision and a wider applicability scope than the traditional methods.

A new filtering algorithm named regional growing filer is proposed in this paper. The principle of the regional growing filer is similar to the regional growing used to process digital images. First, reliable seeds are selected, then the growing rule is formulated. If the height difference between the seeds and the selected points is lower than the threshold, the selected point is regarded as the ground point, otherwise the point is removed as a feature point. When there are no laser points that can meet the rule, the growing ends. The processed point clouds use regional growing filter with no need of original data interpolation and iteration, and hence the filtering speed is fast. Experiments show that the effects of the regional growing filer is better than the results of such traditional algorithms as the maximum local slope filer and the expansion of window height threshold filer.

Fraction of Photosynthetically Active Radiation (FPAR) is a key parameter in the study of such topics

as ecological system function and global changes, and hence it is important to estimate FPAR accurately. Based on

an analysis of hyperspectral and photosynthetical active radiation data of the corn, this paper studied the

feasibility of Principal Component Analysis (PCA) for hyperspectral information extraction and corn canopy FPAR

estimation, and analyzed the potential of near-shortwave infrared hyperspectral data for FPAR estimation. The

results show that the PCA method can be used effectively to compress hyperpsectral information, and will give a

better performance than vegetation indices for FPAR estimation. Near-infrared and shortwave band hyperspectral

reflectance has a great potential for estimating FPAR and hence can help improve the precision of FPAR estimation.

Texture analysis has become an important means for improving the accuracy of remote sensing image

classification. As the texture feature is closely related to image scale, the determination of a scale for texture

analysis applied in remote sensing image classification is very important and corresponds to the choice of an

appropriate size of texture window for gray co-occurrence matrix texture analysis. The authors studied the spatial

relationship between the adjacent pixels in the remote sensing image, and selected the lag distance of the semi-

variogram that was determined when the value of the semi-variogram tended to be constant as the co-occurrence

window size. Under the restraint of the Maximum Likelihood supervised classification results, the co-occurrence

features were computed with a timely changeable co-occurrence window size according to the semi-variogram

analysis. This paper introduced a method of reasonable scale texture analysis for remote sensing image

classification and had an image taken in Changping District, Beijing as an example. The texture feature was

extracted from SPOT5 remote sensing data in the Titan Image secondary development environment and involved in

classification. A comparison of the results using the method proposed in this paper shows that the classification

accuracy has been improved effectively.

 With the RADARSAT radar image as the data source, the authors carried out the variation detection study

in Chengdu area. By choosing proper distribution and utilizing maximum likelihood regularity, the image variation

in the urban area was investigated. On the basis of the detection of RADARSAT data variation, the urban area

variation was divided into two types, namely smooth transition and abrupt change, which were assigned respectively

to homoplasmic area and alloplasmic area. These two types were detected separately by algorithm. Practice shows

that the result is fairly satisfactory.

This paper has compared the effectivenesses of different water body indices which are applied to

identify water bodies based on the MODIS data. The results show that the Combined Index of NDVI and MIR for Water

Body Identification (CIWI) is the most effective index for water body identification when the MODIS data are used.

In calculating CIWI by using the MODIS reflectance data with 0 as the distinguishing value, the constant in the

expression of CIWI is -0.85. It is also shown that the MODIS data are unsuitable for small water body

identification because their spatial resolution is not very high.

A practical method is proposed in this paper for building extraction from remote sensing images with

high spatial resolution. Relevant features between building and its neighboring shade were used to establish the

method. The steps of the approach were as follows: First，the high-resolution merged image was constructed, which

combined the Grey Level Concurrence Matrix （GLCM） homogeneity texture feature and the normalized difference

vegetation index (NDVI) segmented by arithmetic of multi-resolution segments and two scale feature unit layers.

Second, water and land were separated by a threshold of normalized difference water indices (NDWI) based on the

larger scale object and then the underlying building region was extracted by the decision rule based on spectral

and shape features of the object from the land region according to the larger scale object layer. Third, shade was

extracted by the knowledge rule based on the mean value of the near infrared band of objects in the small-scale

objects layer. After that, the class-related feature neighboring the shade was defined. Finally, a building was

extracted from the building region by searching feature unit objects neighboring the shade. The experimental

result based on the QuickBird image shows that the proposed method is very effective and suitable for building

extraction from high spatial resolution remote images.

Fundamental knowledge is necessary for establishing a statistical model between LAI and vegetable

indices to perform the inversion of LAI with remotely sensed data. The authors processed the canopy spectral data

of winter wheat in Beijing area obtained by ASD Spectrometer with spectral response function of the TM sensor，and

got the canopy NDVI of the wheat. Two different kinds of non-linear statistical data of LAI and NDVI were

constructed in this paper. The experimental results show that there exists a close exponent correlation between

LAI and NDVI.

the relationship between the microwave backscattering coefficient and the leaf area index (LAI) in

Tropical Plantation Forest area was studied, and a method for estimating leaf area index retrieved from Radarsat-1

SAR based on the modified WATER-CLOUD Model was presented. The method was applied over Leizhou site in Guangdong

Province, with the correlation of the main species being approximately 0.7. Based on characteristics of forest and

radar images, the method can effectively estimate plantation forest LAI in the cloud-prone and raining area.

Based on studying spectral characteristics of sandstone that has undergone reducing alteration of gas

and oil in the Bashibulake ore district, this paper has dealt with the technologies of reverse enhancement based

on ETM data and the direct enhancement based on ASTER data for extracting the reducing alteration information from

Cenozoic strata, and analyzed distribution features of the alteration information. It is discovered that the

sandstone in the west part of the narrowly-exposed NWW-trending Cenozoic strata has undergone strong reducing

alteration of gas and oil, but the middle and east parts have experienced less alteration. The result provides

some important information for uranium exploration in the periphery of the Bashibulake uranium ore district.

Field experiments were conducted in a split plot with three rice varieties. Rice samples were exposed to

sulfur dioxides of different concentrations inside a fumigation chamber. After the measurement of visible and near

infrared radiance of the canopies of rice，leaves of rice canopy were sampled to analyze pH of extracted leaf

fluid and chlorophyll concentration and sulfur content of rice leaves. The correlation between these biophysical-

biochemical indices and the first derivative spectral reflectance shows that the first derivative spectral

characteristics which are significantly correlated with sulfur content, pH and cholorophyll concentration can be

selected to estimate the biophysical-biochemical indices with regression models using 689nm, 584nm and 570nm at

the tiller stage, and using 689nm, 584nm and 585nm at the heading stage respectively. The first derivative

spectral reflectance of 689nm, 584nm and 570nm at the jointing stage, and 689nm, 584nm and 585nm at the filling

stage can be used to test the accuracy of regression models. The correlation coefficients between measured values

of the jointing stage and estimated values of the tiller stage for estimating models are 0.498 (estimated sulfur

content), 0.884 (estimated pH) and 0.63 (estimated chlorophyll concentration) respectively. In addition, the

correlation coefficients between measured values and estimated values are 0.66 (sulfur content), 0.768

(chlorophyll concentration) and 0.50 (pH) respectively.

In this paper, first the land surface brightness temperature was retrieved by single channel algorithm

based on multi-temporal Landsat TM/ETM+ data, then NDVI, MNDWI, NDBI and NDBaI indices were calculated to classify

the land use/cover types in the study area by the decision tree method and, finally, the spatial and temporal

changes of Urban Heat Island (UHI) and the relationship between UHI and land use/cover change in Changsha City

were studied. The results show that the extent of UHI increases with the expansion of the built-up area in

Changsha City, that the change of land use/cover types is likely to cause the variation of the spatial

distribution of Land Surface Temperature (LST), and that the built-up area and the barren land seem to be the

major factors responsible for UHI intension, while the water body and the forest land play an important role in

reducing LST. Regression analysis shows that there exists a significant correlation between LST and the four

indices, and there also exist remarkable LST differences in different land use/cover types.

The urban residential unit is intimately related to people's life, and the traffic environment of  a

residential unit constitutes a key standard for the environment assessment of the unit. The spatial resolution of

the high-resolution remote sensing image makes it possible to study the traffic environment on the scale of the

urban residential unit. According to characteristics of the high-resolution image, a multi-level index system for

the assessment of traffic environment of urban residential units was constructed, which took into account the

traffic environment and road accessibility. In this paper 50 representative urban residential units in Xiamen City

were chosen and all the indices mentioned above were computed and further analyzed. The results indicate that the

utilization of the high resolution image for the assessment of city traffic environment quality is an economical,

simple and feasible method.

As a new spatial observation technology, the remote sensing technology has been applied in various

fields. This paper deals with some application results of remote sensing technology in the study of some ancient

settlement villages in Chaohu area to probe into the vista of applying the remote sensing technology in this

aspect.

The Ming Great Wall in Ningxia and Shaanxi area was so considerably destroyed by natural and man

activities that a part of the wall disappeared from the Earth's surface and was buried by sand. Therefore, it is

very important to detect the spatial location and trend of the Ming Great Wall by remote sensing technology,

especially by combining the SAR method which can penetrate the Earth's surface and the optical remote sensing

method. The authors used pixel image fusion between SAR image and optical image which were HIS transform fusion

and PC transform fusion respectively. After comparing the fusion result between HIS and PC, the skeleton method

was used to extract the Ming Great Wall automatically based on the PC fusion image and thus acquired satisfactory

results. The spatial location of the Ming Great Wall was eventually detected.

Miyun County of Beijing not only provides water resource for Beijing but also possesses a great priority

in supporting Beijing's outward expansion. However, as Miyun County is developing along with Beijing's rapid high

-tech and economic development, its eco-environment is confronted with strong pressure caused by the increase of

population as well as the social and economic activities. Using Landsat and Beijing-1 satellite images, the

authors obtained several eco-environment factors with the help of RS and GIS technologies. This paper has dealt

with the land use maps of three terms and, on the basis of land use, analyzed vegetation coverage and landscape

indexes to disclose the variation. In addition, land surface temperature was calculated from the ETM+ image of

1999. The above factors detected in 1999 and their relationships are also discussed for different ecological

regions.

Based on multi-spectral remote sensing image data of CBERS and using information quantity, correlation

matrix and OIF method, the authors analyzed image band characteristics and obtained the overall cognition of image

data. Through drawing spectral curves of land cover sample average values, this paper deals with land cover

spectral characteristics in five bands and describes land cover reflection characteristics of each band. Based on

typical land cover sample data, the authors drew the box plots for five bands and two means of PC1 and NDVI and

further analyzed land cover characteristics. Using the Z-test method, this paper got the optimal texture measures

for the discrimination of different land covers. Using the object-oriented classification technique, the authors

carried out classification experiments, and the results obtained have verified the effectiveness of applying CBERS

remote sensing imagery to wetland cover classification, enriched methods for inland wetland cover extraction, and

expanded the application field of CBERS remote sensing image.

On the basis of a case study in Miyun area of Beijing, a new strategy of classification of land-

use/cover integrated with the up-scaling methods and object multi-features in the high resolution SPOT fused image

was introduced. Multi-resolution dataset was built using up-scaling methods, and optimal resolution images were

selected by semi-variance analysis. Relevant optimal spatial resolution images were adopted for different classes.

Object multi-features, which included spectral information, generic shape features, class related features, and

new computed features, were introduced. A multi-scale decision tree was set up based on object multi-features, and

different classes were extracted from multi-resolution images. Afterwards, further discussion and comparison for

improving the efficiency and accuracy of classification were presented. The results show that the proposed image

analysis approach can successfully decrease the heterogeneity, smooth the noise influence, reduce computational

and storage burdens and improve the classification efficiency in the high spatial resolution image.

The growth of vegetation is affected by water/thermal conditions and, in a certain area, there exists a

definite relationship between the water/thermal condition and the climate. It is hence very important to probe

into the influence of water/thermal conditions on vegetation growth. In this paper, the remote sensing data

different from data based on the points in the traditional method were used to do research work in Qinghai-Tibet

Plateau. The authors analyzed the remote sensing data of 2003 and the results show that in the time domain, there

exists a good correlation between LAI and temperature, soil moisture, and precipitation, and in the spatial

domain, the correlation in most of the area is also good. Nevertheless, there also exist some weak and negative

correlations, which are also discussed in this paper.  

In this study, the Spectral Angle Mapper method was used to extract such kinds of desertification

information as flow sand, semi-fixed sand, fixed sand and sandy plantation, and the Mu Us sandy land was chosen as

a typical study area. CBERS-2, Landsat-5 TM, SPOT-5, TM and SPOT-5 fusion images were obtained as the source of

data to study and compare the extraction precision from different sensors. The results show that the extraction

precisions from different sensors all reach 80%. The fusion image has the highest extraction precision, the SPOT-5

image possesses the second place, and the CBERS-2 and TM images have different advantages in extracting different

sorts of desertification information, but the precision of CBERS-2 is on the whole higher than that of TM. It is

concluded that there exists a positive relationship between the extraction results and the space resolution of

image, i.e., the higher the space resolution, the higher the extraction precision.

Abundant spectral and continuous spatial information of the satellite TM data is being applied

extensively. On the basis of analyzing spectral characteristics of TM image data and according to spectral

characteristics of rocks and ores as well as the theory of extracting information from remote sensing data，this

paper utilized such methods as band ratio, principal component analysis and principal component analysis after

ratio strengthening to extract mineralization-alteration information. Through sieving and evaluation, the

prospecting target can be delineated and the remote sensing map can be drawn.

World Wind is one of the most popular digital terrestrial platforms whose technology is advanced and can

provide abundant data. The utilization of the published data to expand its data application through net

application and the combination of the user's application data or data from other sources and the data published

on WorldWind are problems that remain to be solved. With the WebService technology for publishing geographic

information services, the utilization of GeoServer as a map server, and the integration of OpenGIS Webservice

norms and PostGIS spatial database, network spatial data expansion can be used by WorldWind clients and integrated

with its data services. On the World Wind platform, spatial data expansion and publication can be dealt with

freely, and a more extensive and in-depth expansion can be achieved.