Based on experimental data of maize canopy spectrum, leaf area index (LAI) and multi-angle

vegetation fractional cover (VFC), this paper deals with the estimation of VFC by remote sensing and its

affecting factors. Two widely used models based on vegetation index for estimating VFC were compared and

three factors affecting the estimation, namely, LAI, vegetation spatial distribution and observing zenith

angle, were analyzed. Some conclusions have been reached: the Normalized Difference Vegetation Index (NDVI)

is the best for the VFC estimation using both models； the effect of LAI on the relationship between

vegetation index and VFC increases with the growth of the vegetation; vegetation spatial distribution has

little effect on the vertical VFC estimation; for the four types of vegetation distribution, VFC presents a

symmetry spatial distribution toward view zenith angle (VZA); in the burgeon phase of the corn, VFC increases

with the increase of VZA and has the minimum value at VZA=0°, while with the growth of the corn, VFC

decreases with the increase of VZA and has the maximum value at VZA=0°.

 For the purpose of accomplishing wave information inversion, precise correction of sea clutter data is necessary. In this paper, a correction algorithm is proposed for processing sea clutter data. First, for tackling geometric aberrance of radar imaging, a fast geometric correction method based on the separation of azimuth and range is proposed combined with the real working parameters. Then, for coping with radiation quantity aberrance of sea clutter data along with scanning beam, a nonlinear relative radiometric correction method along with scanning beam is put forward to deal with the data. An analysis of the correction results shows that, after correction, both the data processing speed and the image quality and precision achieve the engineering practice requirement of wave analysis.

 In the interferometric SAR (InSAR) processing, the interferogram flattening is a key procedure for eliminating the flat-earth phase and decreasing the density of fringes. In this paper, two different techniques for flattening, using respectively the orbit data and the interferogram spectrum, are analyzed. Various error sources, their comparisons and especially their influence on final DEM accuracy are discussed in detail. According to the sample data experiment, several conclusions can be drawn: the flattening algorithm based on geometry parameters with precise orbit data can remove the flat earth phase accurately and constrain the DEM error to a low level, which is obviously better than that based on interferogram spectrum. When the mean spatial frequency of the interferogram spectrum is equal to zero, relatively low DEM error will be retrieved with the flattening algorithm based on interferogram spectrum. However, if precise orbit data cannot be obtained, DEM reconstruction can’t meet high accuracy requirement with the flattening algorithm based on geometry parameters or interferogram spectrum.

In the past decades, researchers have successfully rebuilt the digital elevation model (DEM) using such Interferometric synthetic aperture radar data (InSAR) as SIR-C/X SAR and ERS1/2. As a new generation of synthetic aperture radar, Phased Array type L-band Synthetic Aperture Radar (PALSAR) , which is onboard Advanced Land Observing Satellite (ALOS), works at a longer wave length-L band. Its penetrating depth is deeper than the radars that work at C band. Thus it has advantages in the construction of DEM. However, there have been few reports about the DEM extraction from this technology. The open source program-package ROI_PAC version3.0 provided by NASA/JPL can be used to rebuild DEM from PALSAR Level 1.0 data that is not calibrated. Therefore, ROI_PAC version 3.0 was modified in this study to make it rebuild DEM from PALSAR Level 1.1 data. The workflow of ROI_PAC was described. The method introduced in this paper was validated by a set of PALSAR Level 1.1 data. A comparison between InSAR DEM and reference DEM was made. The difference between them is 0.27 m, with a standard deviation of 9.24 m. There are more than 80% pixels having height errors within 10 m. The results show that the method proposed in this study is useful.

Sea Surface Temperature (SST) has an important application value in the field of fishery environment and is also a key environmental element in scientific survey. In this paper, the thermal infrared band of Landsat-5 TM was used to retrieve SST with three different methods, i.e., QIN et al.’s mono-window algorithm, Jiménez-Munn~oz single-channel method and Weng’s algorithm. The first two are simplified models that only consider the atmospheric parameter of water vapor content, QIN et al.’s model contains the atmospheric temperature of the average value as well, but Weng’s algorithm has no elimination of atmospheric parameter. The retrieved data were mapped to analyze the distribution of SST in the Daya bay, and the results are compared with data from 12 sampling points. The results show that distribution characteristics of SST obtained from the three methods are similar to each other, and the diffusion of warm water from the Daya and the Lingao nuclear power stations can be observed clearly. The three methods show an error of -2.21℃, 0.19℃ and -4.68℃ respectively, with the error of the Jiménez-Munn~oz single-channel method being the lowest.

It is a key problem to select optimal features from the total set where spectral, geometric, shape, texture features and some other features are extracted by the process of image segmentation in object-oriented classification. In this paper, the authors present a method for selecting good features from object-oriented image segmentation according to the maximal statistical mutual information dependency criterion so as to improve the classification accuracy of high spatial resolution image. The proposed method is a three-step classification routine that involves the integration of (1) image segmentation with eCoginition software, (2) feature selection by mutual information minimum redundancy and  maximum relevance criterion, and (3) support vector machine for classification. The experiment was conducted on QucikBird image in Zhangzhou city, Fujian province. Furthermore, the proposed method and the well-known feature selection methods such as Tabu search algorithm and fisher discriminate analysis are evaluated and compared with each other. The result shows that the mean error ratio decreases by 4% with the proposed method and that the proposed method for feature selection outperforms the other methods in terms of McNamara’s test.

Change detection based on remote sensing is one of the important aspects in remote sensing application. Traditional remote sensing change detection methods usually use spectral information alone and ignore the correlation between multitemporal images. This paper proposes to quantitatively express the temporal correlation between multitemporal images by multivariate texture, which is measured by pseudo cross variogram, a geostatistical tool. The obtained multitemporal texture, as an additional band, is incorporated into multitemporal classification for change detection. The results show that, compared with the result of using spectral information alone, the inclusion of multitemporal classification in change detection can significantly improve the overall accuracy. The experimental results also validate the effectiveness of the proposed method.

The principal component analysis (PCA), a classical linear feature transformation method based on mathematical statistics, is effective in the analysis of linear data. Nevertheless, PCA is likely to result in distortion and loss of data information for non-linear hyperspectral Remote Sensing（RS）image data. In this paper, the fuzzy mathematical theory and the theory of kernel in pattern recognition is proposed for the purpose of effectively overcoming the shortcomings of traditional PCA. The test results show that the fuzzy kernel principal component analysis (FKPCA) designed in this paper can acquire competitive image feature extraction results.

Quaternary, the newest geological period in the history of the earth, is closely related to the survival and development of human beings. With the characteristics of wide range and macroscopic dynamic monitoring, the remote sensing technique has played a more and more important role in Quaternary geological researches. Exemplified by the Huzhou City, the authors carried out the computation of the ETM+ data with different wave bands to acquire the NDVI index, NDWI index and NDBI index. The special information obtained was used to carry out the PCA transformation for extracting the Quaternary geomorphologic feature information. The information was compared with that from the 7,4,3 false color composite methods. The result shows that the new method is very effective.

24 plots composed of commercial districts, school areas, residential areas and parks in Beijing were selected to extract land surface temperatures by using remote sensing and GIS method. Land cover types were acquired, and the pattern of ecological green space was evaluated by a landscape software. The authors investigated the relationship between land surface temperatures of various plots and underlying ground structures. The results show that the water region and the ecological green space have the cooling function, while the concrete surface can heat the land surface. The proportions of the above three types strongly affect the average land surface temperature of the explored plots. The effect of selected ecological green space indices on temperature is in decreasing order of ‘green space ratio’, ‘division’, ‘average area of patch’, ‘cohesion index’, ‘shape index’, and ‘fractal dimension’. There is a positive correlation between ‘resolution’ and temperature, and a negative correlation between temperature and other quantities. Among all kinds of the selected plots, the descending order of their temperatures is from commercial districts through school areas and residential areas to parks. The temperature distributions of parks are extremely scattered, while those of commercial districts are the most concentrated.

Numerous spectroradiometric measurements were carried out in the Caofeidian offing and, on such a basis, correlation was made between the average reflectance and the concentrations of surface suspended particulate matter (SPM). The empirical relationships were established between remote-sensing reflectance (Rrs) in TM-HRV bands and SPM concentrations. The results show that the remote-sensing reflectance increases with SPM concentrations. When the SPM concentrations are lower than 20 mg/L, the amplitudes of remote-sensing are wider in the 570 nm than in the 670 nm, but when the SPM concentrations are higher than 20 mg/L, things are just the opposite. The best correlations are obtained for Rrs (TM3) and SPM concentrations, which show remarkable exponential correlations. As a result, SPM concentrations within the surface waters in Caofeidian offing are estimated with an average accuracy better than ±28%.

Buerdong gulley is located in pisha sandstone distribution area along the middle reaches of the Yellow River. Strong erodibility of pisha sandstone together with concentrated precipitation have caused the continuous erosion of the edge lines of the slope, affecting the living conditions of local residents. Therefore, it is necessary to study the erosion rule of pisha sandstone. In this paper, the erosion distance of pisha sandstone was calculated by using remote sensing and GIS technology, and the effecting factors were analyzed.

The high resolution QuickBird imagine provides abundant anomaly information on geological structures in the study of the Laochang ore deposit, and hence is very useful to the study of geological structure and prospecting. The linear-ring texture displays the ore-controlling ring structure and information of concealed structures, and the anomaly hue speckles show areas of alteration. The remote sensing anomaly information is well in accordance with the anomaly of geophysical and geochemical prospecting.

Wetlands play a key role in regional and global environments and are critically linked to many major issues such as climate change, water quality, hydrological and carbon cycles, and wildlife habitat and biodiversity. Mapping wetlands and monitoring their change constitute a long-term task. Remote Sensing characteristics with macrocosm, dynamics, quantity, and comparability will largely favor wetland research. The radar remote sensing, which is not affected by climate conditions, has been especially proved to be an effective tool in wetland monitoring. In this paper, the unique polarimetric data of Radarsat-2 were investigated for wetland classification, and the target decomposition was used for optimum characterization of wetland target scattering. It is shown that the polarimetric information provided by Radarsat-2 permits  discriminating eight classes of land surface, and leads to an effective unsupervised and supervised Wishart classification of Poyang Lake wetland. Hence, the combination of Radarsat-2’s polarimetric and all-weather capabilities is likely to provide unique information for operational mapping and monitoring of wetlands.

 In order to understand the HJ-1 satellite image application potential in the land use field，the authors studied image quality through analyzing visual quality，spectral characteristics，noise features and geometry correction precision. The image land use classification precision was investigated through selecting characteristic variables，optimizing training samples，establishing classification templates and constructing Maximum Likelihood, Minimum Distance and Mahalanobis Distance so as to make land use classification and evaluate the classification precision．The results show that the HJ-1 satellite image quality is satisfactory and the land use classification precision is high. The image can become the main data source for remote sensing data renewal in land use research．

Using the land-use dynamic degree model, conversion matrix and landscape pattern indexes obtained by the RS and GIS，the authors quantitatively analyzed the dynamic process of the coastal wetland landscape pattern in Yancheng city during the past 15 years (from 1992 to 2007)．Some conclusions have been reached: (1) Owing to the development of coastal economic and the increasing requirement for land resources, the area proportion of natural landscape in Yancheng coastal zone decreased by 12.63%, while the proportion of man-made landscape rose continuously. (2) The area of original natural landscape types was reduced by 763.62 km2 totally, the number of patches decreased, the total edge shrank, the shape of the patches tended to become more irregular, the preservation ratio became lower, the massive original natural landscape types were converted to the artificial landscape types, and hence the wildlife’s habitat decreased badly. During the same period, the area of Spartina alterniflora was expanded, resulting from the initial introduction of 144.92 km2 by 2007, which occupied a large area of tidal flats between the Sheyang river and the Liangduo river in Yancheng coastal zone. (3) The dominant conversion processes indicate that the human reclamation of coastal wetland was enhanced, and the effect of human activities on the change of local environment was also intensified gradually.  The achievements in this study can provide scientific basis for the sustainable utilization of land resources and the protection of coastal wetland resources in Yancheng．

 Based on 3S technique, surveying and statistic analysis, this paper takes the landscape pattern change in Shenzhen city as a case study. Shenzhen is a rapid urbanization zone in China as well as a constructed city with holistic planning. In this paper, the relationship between the process of a typical rapid urbanization and the landscape spatial pattern was studied. The landscape and class-level pattern indices in the whole Shenzhen city were comparatively studied. The results show that the landscape structure complexity and the fragmentation in Shenzhen have gradually changed from the center to the fringe. The intensity and the development tendency of the gradient zone were also analyzed. The results show that the diversity indexes increased firstly and decreased lastly according to the pattern grads: the index was lower in the city center but higher in the connective area between the city and the country; patch density index and edge density index were also lower in the city center than those in the connective area; the closer the connective area, the higher the heterogeneity. Shape index and fractal dimension also indicate that human disturbance has become stronger from the city to the country. In conclusion, the landscape structure and distribution are evidently associated with human activities.

Based on remote sensing and GIS technology, the authors extracted Beijing rural residential land by using multi-source remote sensing data (MSS Landsat images, TM or ETM+ image, “Beijing 1” small satellite data). The status of Beijing occupied residential land in 2005 was fully analyzed by referring to the DEM data. The districts of Beijing were reclassified by improving the traditional method for defining the geographical borderline. Beijing rural residential land was dynamically monitored in three periods (1980~1995, 1995~2000, and 2000~2005). Some indices were used to analyze the spatial-temporal and landscape characteristics of rural residential land in Beijing. 14 social economic indices were chosen to analyze the driving forces that affect the change of rural residential land by using the principal composition analysis method. The results of this study can play a guiding role in rural reasonable planning.

 The relevant governments have attached great importance to the overall coordination and development of the Beijing-Tianjin-Hebei Metropolitan Circle. At the same time, Beijing, Tianjin and Hebei Province, in an ecological environment, have formed a posture of common influence and radiation. Supported by the temperature anomaly map, the authors chose the heat environment, an aspect of the ecological environment, to make an analysis of the urban heat island intensity and its variation regularity at different periods and places, according to the land surface temperatures of Beijing-Tianjin-Hebei Metropolitan Circle in 2001-2008 based on MODIS Data. On the basis of the information from landscape studies, the authors also chose NP, CONTAG and SHDI to make a qualitative description of the spatial pattern of the thermal environment of Beijing and Tianjin according to the evaluation system of thermal landscape spatial pattern. Except for summer, the thermal landscape pattern of Beijing was in a dispersion condition from 2001 to 2004,  and then tended to become agglomerate; in 2008, the pattern was in a agglomeration condition. Summer was different from other seasons: the thermal landscape fragmentation was more obvious and the urban thermal field was in dispersion state in 2008. The change of the landscape pattern of Tianjin is not significant.

The urban land information of central Liaoning province in 1954, 1975, 1986, 2000 and 2005 was extracted with the remote sensing images, relief maps and statistical data, and the spatial pattern characteristics, the spatial-temporal changes of these urban lands as well as their causes were studied with the help of index analytic method, GIS spatial analysis and geographical statistics function. The results show that, since the early 1950s, the urbanized land in the study area has been increased continually, and the urban expansion was the fastest from 1954 to 1975, with different cities having different expansion rates. From 1986 to 2005, the function intensity between cities was growing geminately, the spatial radiancy function of urbanization was enhanced, the trend of regional urban development of cities was obvious, and the function of Shenyang as the central city in this highly urbanized area became distinct, with other cities in the area moving towards Shenyang. From 1975 to 2000, small towns developed rapidly. The spatial distribution of relatively high annual urban growth rate was consistent with the direction of the urban center transfer. The causes for these changes are also analyzed in this paper.

 The transformation methods such as Brovey, HIS, PCA and Pan Sharpening were employed to perform fusion of QuickBird images, and the effects of these fusion methods were evaluated qualitatively and quantitatively. The results show that the Pan Sharpening fusion method can not only increase the spatial information of surface features but also better reserve the original multispectral information. Hence the Pan Sharpening fusion method is a means suitable for the fusion of QuickBird data.

Data grid is the fundamental work of graphics drafting, scientific computation and the realization of spatial analysis. Using dynamic grid and assigning technology of spatial data, the authors have implemented interoperability of multiple-sources data. The assigned grid has multi-attributes and applies the geographic information system (GIS) and the external program to implement overlay analysis and other complicated spatial analysis functions. The merits of the dynamic grid system lie in a complete vector format and the implementation of multiple-source data merging and massive data spatial analysis. This paper has realized the land suitability evaluation through the assigning technology and the dynamic grid system.