Three campaigns including 37 valid samplings were made to measure field spectra together with some water quality parameters including suspended substance concentration and other data. Field spectra were measured with a portable Field Spec FR spectroradiometer (ASD Inc.), in a wavelength range of 350-2500 nm. And the concentrations of water quality parameters were measured according to the corresponding investigation criteria about lakes of China. Based on the correlative analysis between field spectra and suspended substance concentrations of different ranges, we divided all the 37 samples into different groups according to the analyzed threshold concentrations. Then some reflectance variables at some bands were used to do the correlative analysis with suspended substance concentrations of different groups to find out the better indicative bands. Because of no evident indicative bands existing with the general method in some groups, the first and second derivative method was also used. The results showed that the best variable is not a constant when the concentration is low and the range or span is narrow. Otherwise, the best variable is the reflectance first derivative near 878 nm, and then the average reflectivity in the range of 810-820 nm, or the reflectivity at 820 nm. Generally, the derivative method is better to estimate suspended substance concentration with hyperspectra.

The Taihu Lake in China is shallow and turbid. Its water body covers 2338 km², and water depth varies between 2 and 4 meters. To monitor water quality in such a large lake, TM is probably the best remote sensing data due to its spatial resolution. While some modeling works have been done on relationships between total suspended sediment concentration (SS) and reflectance in TM image, the TM bands being used in the model are still under discussion. In this paper, a model was developed on relationships between SS and ETM in summer and winter in Taihu Lake. ETM image is geo-referenced with 1:50,000 topographic map and digital number of pixel is converted to planetary reflectance. An index called NDSS from ETM image is introduced, where NDSS= (B3-B1)/(B3+B1). The ETM monitoring model of SS in summer and winter was built through regression analysis. The basic model form is SS=f(NDSS), goodness-of-fit statistics R² is from 0.51 to 0.72, and the model is significant under p=0.005. Obvious difference exists between the summer model and winter model. In the summer model, spatial variation of water body must be considered due to the dynamic water environment. The same variation, however, can be ignored in winter model.

Retrieving water components in case 2 waters by remote sensing is a crucial problem in evaluating ocean first productivity and monitoring various disasters. But it is difficult to accurately and universally develop both bio-optical models and remote-sensing reflectance model because independent temporal and spatial variation of dissolved organic matter (CDOM), chlorophyll and total suspended matter (TSM), high concentration of TSM, as well as the local characters of different regions. Currently Linear algorithms such as principal component analysis (PCA), factor analysis (FA), matrix inversion technique and semi-analytical algorithm are widely used in the field of ocean color. Remote sensing reflectance model is derived from the radiative transfer equation, which is significantly featured by non-linearity and negative feedback. In our study, the chlorophyll absorption model and some other parameters of bio-optical models are adjusted. The adjustment is based on the water components concentration measured simultaneously with remote sensing data in the Yellow Sea and the East Sea of China. Then the equation of remote-sensing reflectance model can be changed into linear matrix of water components and coefficients, we find the spectrum curves of total suspended matter coefficient and chlorophyll coefficient turn out significant negative correlation. As a result, when performing matrix retrieval algorithm, chlorophyll concentration and CDOM concentration are out of required accuracy except some special conditions. Experiment results suggested that the TSM had the greatest influence on the linear model.

Retrieval of concentrations of total suspended matter, chlorophyll, and CDOM constitutes a concern in remote sensing of Case 2 ocean water. Based on former research achievements, this study established a linear model of Reflectance of Remote Sensing (Rrs) of Case 2 coastal water of China. Experimental simulation was also carried out. The results show that the concentrations of TSM and chlorophyll are relatively less sensitive to the model errors, while CDOM is more sensitive. Remote sensing data of Yellow Sea and East Sea of China provided by National Satellite Ocean Application Service of China were applied in this paper. Spectral profiles calculated from the linear model show the similar trend with measured results form the Yellow Sea and the East Sea. The linear relationships between band 443 nm and band 490, and 510 and 555 nm match well with real situations. The spectral curves of TSM and chlorophyll in our model yield some useful information for calculating the concentration of CDOM.

An attempt has been made to compare and analyze the ST (surface temperature) between MODIS (Moderate Resolution Imaging Spectroradiometer) on the Terra satellite and AWS (Automatic Weather Station) data for monitoring the establishment of UHI (urban heat island) in this study. Results show that they are in good agreement. From the distribution of ST from MODIS, the highest values of ST appear in the center of urban. The UHI is evident in the urban area and its suburb towns. Another focus of this study is to analyze the relationship between ST, land cover and NDVI (Normalized Difference Vegetation Index) over urban area in order to improve the understanding of UHI. A negative correlation is observed between NDVI and ST correlation coefficient of - 0.73. The ST over urban is the largest among all other land-covers. The mean differences of ST between urban and rural from MODIS are about 2.29K and 1.22K at about 10:30 and 22:30 in April of 2004, respectively. Through this study, it could be clarified the surface temperature characteristics of spatial distribution for urbanization in the rural area. In summary, the relationships between NDVI, land cover and surface temperature will be regarded as one of effective methodologies to make manifest urban heat island. The difference of NDVI between urban and rural region appears to be an indicator of the difference in surface properties between the two environments that are responsible for difference in urban and rural surface temperature.

Salinization is one of serious disasters in Minqin Oasis, northwestern China, and it has close relationship with natural changes and human activities. Using TM time-series images temperature and NDVI are evaluated and salt lands have special distribution in the two dimensions space. With the three principal components of the original images these two useful layers were used to get the distributions of salt lands in the four years. The changes of salt lands are diagramed that tell us that the trend of salinization in Minqin Oasis is in reduction from 1987 to 2000 year and it is the result of reduction of groundwater. With regard to analyzing the reason of salt land changes nature and manmade influences are discussed.

The ecological system in mountain area plays a key role in the biodiversity conservation in global scale and regional sustainable development at the down-stream area of drainage basin for water, wood, and other resources supply. But as dealing with the problem, there is often no available meteorological and climatic data. With the operation of NOAA in 1990s and Terra and Aqua in the new million, it is possible to estimate some meteorological and climatic parameters by the use of satellite remote sensing. Furthermore, we can explore the spatial pattern of the parameters, for example, lapse rate of temperature, by means of a synthetic analysis with other geospatial data, such as digital elevation model, and get useful information about the ecological system in mountain area. In this paper, land surface temperature (LST) is estimated after Becker and Li's local split window algorithm by using Terra-MODIS data. Combined with Digital Elevation Model (DEM), the Land surface temperature and digital elevation data in same region are picked up on the ±1 degree of right direction of east, south, west and north. The correlation between the LST and altitude is analyzed, and 1-order linear expressions between them are got. The results show that on the time when the Terra-MODIS collects data, the LST lapse rate varies from 4.52~6.56°C/km, the minimum value happens at the direction of sunshine, which are approximate 4.52°C/km on the right south side of mountains; the maximal values happens at the opposite side of sunshine, which are 6.56°C/km at the north side of mountains.

In Earth Observing System (EOS) plan, MODerate-resolution Imaging Spectroradiometer (MODIS) is loaded on both the two polar-orbit satellites: Terra (EOS-AM1) and Aqua (EOS-PM1). MODIS data has 16 Thermal InfraRed (TIR) channels (3.5~14.5 μm) among all of its 36 channels. Land Surface Temperature (LST) is an important indicator of earth surface energy balances and climate changes, as well as a key parameter in physical processes of land surface on both global and regional scale. LST is widely applied in the research of disciplines such as meteorology, hydrology, ecology, biochemistry, etc1. Therefore, retrieving LST from appropriate MODIS TIR bands is one of the important applications. First of all, this paper introduces theoretical foundations of retrieving LST from remote sensing data, such as the method of selecting appropriate TIR bands by conditional analysis of atmospheric window. Then, this paper provides an overview of LST retrieving algorithms up to now, including Single Window Algorithm, Split Window Algorithm, Improved Split Window Algorithm, Generalized Split Window Algorithm and Day/Night Algorithm. And at last, towards to the limitations of LST retrieving algorithm, the authors indicates their specific perspectives on the directions of further correlative research in two aspects: improving LST retrieving algorithm and increasing LST retrieving accuracy.

As a promising application, quantitative remote sensing of urban heat island (UHI) can facilitate our understanding of urban/suburban environment and its relationship with urbanization. This paper investigates the urban heat island effect of Lanzhou, China, a densely built up city in a valley, based on Landsat ETM+ image acquired on April 22, 2000, whose spatial resolution is fitly sufficient for measurement of some important environmental parameters. For better quantification, Land surface temperature (LST) was retrieved using the mono-window algorithm, vegetation fraction was derived using vegetation-impervious surface-soil spectral mixture model, and Normalized Difference Vegetation Index (NDVI) was also derived from the corrected image. Then the relationship between LST and NDVI as well as vegetation fraction was estimated. Results show that Lanzhou city's urban heat island effect is significant, which could be visually characterized by the spatial pattern, extent, heterogeneity and intensity of retrieved thermal properties and the maximum urban/suburban temperature difference approximately reaches 10K. Moreover, by analyzing urban composition, it is revealed that LST possessed a strong negative correlation with the vegetation abundance and suggested that vegetation is a key factor controlling the spatial distribution of land surface heat flux. Particularly, due to the scarcity of vegetation, some hotspots are bare soil distributing on suburban surrounding hill, the surface temperature of which is even slightly higher than downtown. These results can help us develop countermeasures to thermal environmental problems in urban areas.

The plain region in Turpan Basin, Xinjiang, China is a typical arid area. As its conditions of physical geography are terrible and the human influence on it, the problems of desertification and other eco-environment is getting severe. The fused images of Landsat TM with SPOT-4 (Panchromatic) and SPOT-5 (XS/XI) data were used to calculate the extent of different land-cover types and their changes each other in the plain region. Through combining supervised classification and unsupervised classification the maps of 1990, 1999 and 2004 of vegetation, wind erosion, desertification and salinization were obtained, and then their changes were detected by Geographic Information System (GIS). The relations among climate, soil, vegetation, terrain, salinization, human and desertification were analyzed. The results showed that although the area of desertification in plain region of Turpan Basin appears to be reduced during recent years from macroscopical sense, the area of desert and salinization is increasing continually. Simultaneously, the extent of oasis is expanding on the whole, but the types of land cover between oasis and desert is decreasing. The results not only reflect the changes of desertification in Turpan Basin, Xinjiang, but also could support the sustainable development of this region.

Using the idea of confidence level and different geographical ecotypes classification in the MODIS cloud mask algorithm, two kinds of test groups (visible and infrared) were combined. The method of cloud detection was introduced to give cloud mask input for thermodynamic phase recognition. The brief flow chart of cloud phase retrieval was also afforded. The MODIS composite image was presented and cloud top particle's phase distribution of the typhoon "Noguri"(Jun, 2002) was retrieved, comparing with the 1.38 thin cirrus detection. The analysis indicates that the technique of multispectral cloud phase retrieval can be applied in practice.

Remote sensing detection model of damaged forest by tomicus piniperda was studied. It analyzed different detection models using multiple types of remote sensing data, such as TM, CBERS-1, AVHRR and MODIS data. The spectral features of the above remote sensing data (March, 2001) were given. And two detection models were put forward according to the spectral changing characteristics. One was named Difference Rate (DR) model with NIR and VIR data, which applied for TM, CBERS-1, AVHRR and MODIS. If DR was bigger, the forest grew healthier. Based on the typical sample, the different guidelines distinguished healthy and damaged forests were obtained. The other model was named Disaster Index (DI) model with thermal and NIR data, only suitable for MODIS. The guidelines of healthy and damaged forest were determined too. Greater DI was, the forest was stricken more badly. In conclusion, it will help monitor and assess the vermin occurrence and impact by remote sensing detection model.

This article proposed a method for the recognition of the sea ice in a SAR image. It's based on the Artificial Neural Network (ANN). We use a BP neural network model incorporating with image texture features extracted by Gray Level Co-occurrence Matrix from the SAR image. The BP neural network fed with the feature vector of SAR image presents the analysis of texture features and outputs the estimation results of the sea ice. The BP neural network is trained using sample data set to the neural network. And then the BP neural network trained is tested to recognize sea ice in a SAR image waiting for the classification . The results of tests show that the BP network model for the sea ice recognition in SAR image is feasible. The BP network output shows the recognition accuracy of the model for the sea ice recognition in SAR image can be 86%. Among the 4 directions for computing the texture features, the most valuable direction is 0°, the next is 90°, and then is 135°. The two most distinguishing texture features are inertia moment and entropy.

Plant canopy reflectance is affected not only by the optical properties of canopy components, but also by canopy structure. In this paper, the radiative transfer model was used to simulate rice canopy bi-directional reflectance to determine its sensitivity to leaf area index (LAI) and inclination. In simulating canopy bi-directional reflectance over 400-940 nm, LAI was changed from 1 to 7 at an increment of 1; leaf inclination was changed from 50^o to 85^o at an interval of 5^o. All other parameters in the model were measured in the field or deduced from references. It is found that with the rise in LAI, nadir reflectance decreases in visible light but increases in near infrared wavelengths. It tends to become stabilized when LAI is sufficiently large (e.g., >4). Decreasing with leaf inclination, canopy nadir reflectance becomes more sensitive to leaf inclination at a larger LAI. At 550nm and 670nm, bi-directional reflectance decreases with LAI regardless of view zenith. At 830nm, it is proportional to LAI over the view zenith angles of -85^o - 40^o. However, it is inversely related to LAI when it exceeds 3. Similar to nadir reflectance, bi-directional reflectance tends to become stabilized at a larger LAI at all view zeniths.

Studies of albedo over urban/rural surface are important to better understand the land surface process in the ABL(atmospheric boundary layer). Urban landscape is the most heterogeneous surface that strongly influences the structure and development of the ABL. In this paper, the directional hemispherical reflectance (black-sky albedo, BSA), the bihemispherical reflectance (white-sky albedo, WSA) and the actual albedo (blue-sky albedo, A) are retrieved from the MODIS BRDF/albedo product (MOD43B1) for three broadbands (0.3- 0.7μm, 0.7-5.0μm, 0.3-5.0μm) in the Changjiang Delta of China. Particular attention is directed to examine the difference of surface albedos over urban and rural areas. The seasonal and spatial variations are investigated. Validation has also been done against field observation and showed that the albedo from MODIS is less than the observed. Albedo in visible broadband (0.3-0.7μm) over urban area is larger than that over rural area, but is less in near infrared broadband (0.7-5.0μm). For the total short broadbrand, it is difficult to reach qualitative conclusion because of urban complexity. The correlations of albedos and NDVI are strongly influenced by the spectral band and land cover. They are positive for the visible and the total broadbands, but negative for the near infrared in same season.

How to extract exactly urban land-use information is always very important in application of remote sensing. There are various methods of extracting urban land-use information based on Landsat image. The approaches studied were Normalized Difference Built-up Index (NDBI), spectrum threshold extraction, supervised classification by computer and interactive visual interpretation; however, each of them has its own advantages and disadvantages in specific application. The main objective of this paper is to compare the efficiencies and accuracies between the multiple methods, and to analyse their potential to improve the efficiencies and accuracies. For instance, the NDBI method is ameliorated by setting a threshold to improve its accuracy. In this study, we take Quanzhou city as study area, and utilize Landsat ETM+ image acquired in 2000 to extract the urban land-use information using the abovementioned methods respectively. By comparison, the study result reveals that these ameliorated methods can work better than before, and NDBI can extract information easily and quickly, and Spectrum Threshold Extraction can acquire high accuracy at the cost of complexity.

Image classification is an important technology in the application of remote sensing. Traditional methods of image classification are based on low or medium-resolution images, and the accuracy of classification is always very low. In recent years, high-resolution remote sensing images have significant improvements, but there is still no good method of classification. Studies showed that the accuracy of classified high-resolution images is even lower than that of low or medium -resolution images by traditional classification methods. This turns out that traditional classification technologies appeared to have serious error when using high-resolution images. In this paper, a method of multi-feature classification was introduced to high-resolution remote sensing image, thus avoiding the method of single-feature and pixel-based classification. In this method, pixel-based high-resolution images are changed into object-based images by segmentation. Models of area, perimeter, length, width, symmetry, ratio of length and width, rectangular fit and compactness were established to measure features of segmented objects. More over, the new method of using spectral and texture features to classify high-resolution images was completed. The result showed that the accuracy of image classification can be up to 91.6% by the multi-featured classification, which proved to have improved high-resolution remote sensing image classification.

Spectral similarity measure plays important roles in hyperspectral Remote Sensing (RS) information processing, and it can be used to content-based hyperspectral RSimage retrieval effectively too. The applications of spectral features to Remote Sensing (RS) image retrieval are discussed by taking hyperspectral RS image as examples oriented to the demands of massive information management. It is proposed that spectral features-based image retrieval includes two modes: retrieval based on point template and facial template. Point template is used usually, for example, a spectral curve, or a pixel vector in hyperspectral RS image. One or more regions (or blocks with area shape) are given as examples in image retrieval based on facial template. The most important issues in image retrieval are spectral features extraction and spectral similarity measure. Spectral vector can be used to retrieval directly, and spectral angle and spectral information divergence (SID) are more effective than Euclidean distance and correlation coefficient in similarity measure and image retrieval. Both point and pure area template can be transformed into spectral vector and used to spectral similarity measure. In addition, the local maximum and minimum in reflection spectral curve, corresponding to reflection peak and absorption valley, can be used to retrieval also. The width, height, symmetry and power of each peak or valley can be used to encode spectral features. By comparison to three approaches for spectral absorption and reflection features matching and similarity measures, it is found that spectral absorption and reflection features are not very effective in hyperspectral RS image retrieval. Finally, a prototype system is designed, and it proves that the hyperspectral RS image retrieval based on spectral similarity measure proposed in this paper is effective and some similarity measure index including spectral angle, SID and encoding measure are suitable for image retrieval in practice.

In this paper, to develop novel methods for satellite optical remote sensing of severe storms, chaotic time-series analysis is carried out and the time delay embedding technique is used for phase space reconstruction, which is relied strongly on a choice of good time delay and the embedding dimension. A new approach for calculations of the mutual information for the choice of time delay for a time series with any probability distribution is proposed. To confirm the validity of the approach developed, the tests using simulated nonlinear time series for some famous chaotic attractors are performed. Then, application of the approach in the time series of GMS-5 11μm IR channel brightness temperature observations of rainstorm occurred in Wuhan area in China on 21-27 July 1998 is discussed. The results show that the new method proposed is a good tool for the best choice of time delay in time series analysis.

The characteristics of rock distortion mainly rely on different aspects of rock fractures, such as fracture structure, aperture, and especially tiny apertures and stuffing. The usual method for image segmentation of fracture apertures and stuffing is mainly according to the information of gray-level images and it is lack the filling material (stuffing) analysis. The main focus of this work is to perform automatic extract the information of the stuffing of fracture by using two illumination systems (visible light and ultraviolet waves light), acquiring two different color images on the same rock samples. Before image fracture delineation, the noise on the images is removed by the fusion of the information of the two images. Finally, the fractures and stuffing are automatically extracted by using the algorithm based on region growing and edge tracing. As tested, the method is satisfactory.

Remote sensing signal reflected from natural background is of important significance in the field of geography. However the signal we can get is always polluted by additive noise. Since it has been proved that the remote sensing signal reflected from natural background always has some fractal characteristics, just like the background it came from, it is possible for us to deal with it with the theory of fractal. For the perfect analytical function on both time and scale, the wavelet theory is used to analyze the remote sensing signals in this paper. Shannon entropy represents how much information in an information source, so it is possible to estimate the remote sensing signal from noise based on the radio of information entropy at different scales. In this paper, the Shannon entropy of remote sensing signals' wavelet coefficients and that of additive noise in different scales are discussed respectively. And then a method for estimating the Shannon entropy of signal's wavelet coefficients is discussed. Finally, the wavelet coefficients belonging to signal are estimated, and the signal is estimated from the added noise at last. In order to demonstrate the effectiveness of this method, some simulation studies are performed in this paper. Since it doesn't need to estimate the fractal parameter of remote sensing signal, this method is suitable in many situations.

The present public health system has continually struggled to combat ongoing and emerging public health threats and emergencies. The main impediment to improving public health readiness is the lack of an effective Public Health Emergency Response System. Although many health systems have been built and large amount of data collected, it is hard to analyze these data in depth and use them efficiently. An effective PHEMS should be able to manage data, produce information and provide services. Based on digital city, such a PHEMS has a most possible chance to be built. Detailed analysis of the architecture of the PHEMS, including (1) the surveillance system for data collection, (2) the consolidated information model based on HL7 Reference Information Model (RIM), (3) and the public health service framework, is focused in this paper. As a test-bed, the implementation of a prototype, which is a part of Digital Beijing Pilot, is illustrated. In the end, some operational and technical difficulties are discussed.

Traditional approaches to path querying problems are not efficient and convenient under most circumstances. A more convenient and reliable approach to this problem has to be found. This paper is devoted to a path querying solution on mobile devices. By using an improved Dijkstra's shortest path algorithm and a natural language translating module, this system can help people find the shortest path between two places through their cell phones or other mobile devices. The chosen path is prompted in text of natural language, as well as a map picture. This system would be useful in solving best path querying problems and have potential to be a profitable business system.

In this paper we present a new method for three-dimensional (3D) computerized modeling of geological objects from sets of intersected cross-sections. Geometric reconstruction from a set of topological and polygonal cross-sections is used in many cases of geological reconstruction now. However, most of current methods require that cross-sections must be parallel. Our method is based on sets of intersected cross-sections. With the help of cross-sections at another direction, this method can effectively solve the correspondence problem, matching components in adjacent sections. Besides, many complex geological phenomena can be reconstructed precisely, for example, stratum dying out position can be well defined in another directional sections. Last but not least, because sections at different directions are used to construct geological surfaces, model quality is greatly improved. The major steps and key algorithms in this method are all discussed in detail. A 3-D software platform has been developed based on this method. A case study in An Shan, Liao Ning Province, P.R. China shows that the method can be applied to practical and complex geological areas.

Presently, there exist many problems in the establishment of digital city, such as repetitive establishment, insufficiency of data updating mechanism, information islands, etc. Based on investigation and research, the paper analyzes the main reasons bring forth those problems, proposes an urban geographic information engineering concept and corresponding methodology, and introduces a practical application case. The urban geographic information engineering methodology is put forward through a lot of research and practice under the background of system engineering and information engineering theory, according to the current Chinese municipal government management system situation, together with the characteristic of geographic information science technology. It mainly includes urban geographic information engineering concept, urban geographic information engineering overall construction plan, urban geographic information engineering construction method system model and data acquisition, processing parallel project method.

Based on the analysis of the general disciplinarian and the particularity for the application of Cellular Automata in geography and hydrology respectively, according to the basic principle of hydrological model and Cellular Automata, a watershed routing model based on GIS and Cellular Automata, HydroCA was created in this paper. A simulation system, Hydro_CA, by combining the HydroCA model for runoff routing with TOPMODEL model for rainfall-runoff simulation was developed and used to simulate runoff process from 1 April 1998 to 31 August 1998 in the study area LeAnhe Catchment in the northeast of JiangXi Province. The results of the simulation prove that the precision of TOPMODEL simulation can be improved by using HydroCA routing model from 64.7% to 71.0%. It is shown that HydroCA model is feasible to simulate the watershed runoff routing. Cellular Automata model will contribute to the distributed watershed hydrological model research and development.

The paper designs the framework of real time traffic information service system and discusses baseline model and data transmission in order to realize real time GIS-T. The author designs a database and puts forward a uniform and independent benchmark for real time traffic information, managing real time traffic information and GIS data independently, so as to easily realize GIS data share and upgrade motion real time traffic information. This paper details the structure of the traffic information service system framework and the real time traffic information flow.