Gridded population distribution data are increasingly expanding their uses in a wide range of fields, such as resource utilization, disaster response and relief, environment protection, and economic research. The enhancement of resolution with detailed precision is a perpetual topic in population gridding research. In this paper, a 100m gridded population dataset was established for Yan’an city by developing a method that distributed the population based on the land use data with improved settlement information. Data used here include township boundary data, township-level demographic data, land use data, TM image, town-village settlement point data, and DMSP/OLS nighttime light images. Two approaches were used to improve the detailed information of settlement distribution. First, we identify the rural settlement information from land use data and enhance the information by the village point data obtained from Google Earth. Second, we downscale the DMSP/OLS data by spatial interpolation. The sum of light emission, lit area and unlit area under different land use types in each town were counted to be used as the independent variables, and the statistical population of each town were used as the dependent variable. A stepwise regression method was adopted to simulate their relationship. Finally, the sum of night light emission, the unlit area of build-up area, the unlit area of grassland, and the lit area of farmland were put into constructing the ultimate equation. All variables were significant under the level of 0.01 and the coefficient of multiple correlation is 0.872. We estimated the population at township level for selected towns as a validation. Through using the equation, we found that the mean error between the estimation and the statistical population is lower than 5%. The above analysis suggests that the proposed modeling strategy is highly efficient. As a result, we calculate the weight and distribute the population through the equation in the formation of 100m grid, by taking township as the unit. In summary, the gridding method used in this study can obviously improve the output resolution and the distribution details. Also, the expression of the final equation is relative simple. As a conclusion, this paper has its significance in guiding the population gridding research in the county level areas like Yan’an city.

Along with the continuous development of computer technology, internet and wireless communication technology, digital map visualization, as the core of geographic information system, has been widely used. At the same time, with the increasing number of embedded software and hardware, a variety of heterogeneous platforms bring great challenges to the development of embedded geographic information system. Therefore, it is important to study the digital map visualization method for cross-platform purpose. Firstly, after comparing the differences of middleware between the embedded system and desktop system, this paper summarizes the characteristics of the embedded middleware, and analyses the platform differences and resource restrictions for digital map visualization in the embedded environment. Based on the concept of middleware, a cross-platform middleware of digital map visualization with three layers: EMD_MW was constructed. The middleware utilizes the operating system abstraction layer to prevent the heterogeneity from different embedded operating systems, and to abstract the operating system message forwarding and the graphic interfaces associated with the digital map visualization. Meanwhile, the model utilizes the framework layer to dispel the differences among data storage services, to improve the base graphic interfaces, and to provide relevant digital map display interfaces through the function layer. Then, the abstraction layer, service framework and function layer of EMD_WM were designed and realized. Finally, several engineering applications based on EMD_MW were presented. These examples indicate that, the embedded cross-platform middleware model for digital map visualization has a good cross-platform performance, and it can effectively solve the problem of digital map display on different embedded platforms.

Great changes have taken place in China's urban scale system during the last 30 years. The driving forces that cannot be ignored include following factors: the population urbanization propelled by its aggregation, the land urbanization driven by its revenue, and the economic urbanization promoted by GDP. Using the analytical tools of GIS integrating three factors of resident population, built-up area and economic output, we constructed Zipf-PLE model for a in-depth research on the spatial pattern of China's urban scale system. The result shows that: (1) in 2010, China's urban scale system is matured with completed levels of hierarchy, which is reflected by a relatively rational pyramid-shaped pattern with larger scale locates in the middle while smaller scale stays at the bottom. The urban scale system structure in the western region has the highest rationality, which presents a pyramid-shaped pattern with larger scale at the bottom and smaller scale at the top. The urban scale system structure in the eastern regions is relatively sound and contains the largest quantity of medium-sized cities, indicating a pyramid-shaped pattern with larger scale in the middle and smaller scale at both ends. The urban scale system structure in the central regions is featured by its incomplete urban system hierarchy, which lacks megacities especially, and presents a pattern with larger scale in both the middle and the bottom, while having smaller scale at the top. (2) The overall urban scale system in China at the provincial level is rational, with 90.32% of the provinces being moderately rational. Among all 27 provinces, except 4 municipalities, the urban scale system patterns of 8 provinces are inclined to disperse and the other 19 tend to concentrate. (3) Furthermore, we allocate the provincial urban scale systems in China into different categories according to their rationality rankings, which are: the high-level (with 11 provinces and municipalities including Beijing, Shanghai, Tianjin, Chongqing, Xinjiang, Heilongjiang, Guangxi, Gansu, Fujian and Jilin), the relatively high-level (with 12 provinces of Guangdong, Shanxi, Yunnan, Hunan, Guizhou, Liaoning, Jiangxi, Jiangsu, Zhejiang, Sichuan, Hebei and Henan), the medium-level (provinces of Hubei, Shandong and Anhui), the low-level (provinces of Hainan, Mongolia and Ningxia), and the irrational areas (provinces of Qinghai and Tibet).

Runoff nodes, which could be captured from every watershed on earth, are one type of the real geographical entities within the river-network. Generally, runoff nodes often locate at sites where lower grade of runoffs merging themselves into a more advanced trunk stream. It is clear that runoff nodes carry a lot of hydraulic and landform information. Although many reports have documents related to runoff nodes, the quantitative measuring researches, that concerning the geographical information of runoff nodes and taking advantages of valid theories or methods, are still rare. This may prevent people from further understanding the existence of runoff nodes in nature. Aimed to solve the aforementioned issue, this paper employs the Theory of Rough Sets (TRS) to develop a new landscape metric for perfectly characterizing the geographical features of runoff nodes. Firstly, according to current knowledge about runoff nodes, this paper extracts the potential information carried by runoff nodes. Secondly, this paper reviews some typical valid methods on how to extract runoff nodes from Digital Elevation Models (DEM). Thirdly, this paper presents the feature information index of runoff nodes (FIIRN) and illustrates the relevant computing procedures. Based on these researches and preparations, this paper carries out a case study of FIIRN for seven special regions from the Loess Plateau of China (which well represents the typical loess landscapes existed in the world). The experimental materials of DEM data are predominantly characterized with 5 meters of resolution. With the help of ArcGIS 10.1 software, this paper extracts all runoff nodes from the experimental sample regions according to their geometric features in the runoff network. Then, this paper computes the values of FIIRN using Excel 2003 and MATLAB 7.7. Surprisingly, the results show that FIIRN can effectively map the complete geographical information of a given watershed unit. Therefore, as we concluded in this paper, that FIIRN can play a valuable role for mining the information from watershed units in future. In fact, FIIRN should be considered as an optimal parameter for analyzing the morphological patterns of watershed units.

Nowadays, issues regarding to housing affairs can be easily dealt through online queries and transactions, which provide a brand new data source for researches about residential space. This article mainly focuses on the causes of variations in activeness degree for different second-hand housing areas in Nanjing, through web data mining and a series of kernel density estimations. Based on three typical case studies of the Hexi district, Daguang district and Confucius Temple area, this article summarizes the underlying influential mechanism for the second-hand housing activeness in Nanjing. Research result has shown that the second-hand housing in Nanjing has a structure of “one core with three blocks”, in which the Gulou and Jianye districts are considered to be the core. Meanwhile, the sales volume in districts with highly educated inhabitants, such as Xuanwu district which lies in the eastern part of Nanjing and Jiangning district which lies in the southern part, have a low degree of activeness due to the solidified and sophisticated residential space development. There are two main factors contributing to the differentiation of activeness in second-hand housing, which are summarized as the internal factor and the external factor. The multivariate regression analysis model suggests that the internal factor is consists of the housing price, the number of building stories, the percentage of greenery coverage, and the house decoration condition. The external factor is considered to be consist of the accessibility and quality of adjacent subway stations, schools and other supporting facilities and services.

Land change survey is an important survey for investigating national conditions and national strength. The purpose of land change survey are: identify the nationwide land use status and changes in the year of concern; maintain the accuracy and timeliness of national land survey data and the basic information of the comprehensive land and resource supervision platform; and meet the requirements of land and resource management as well as economic and social development. Officially released land change survey results are the basis for the implementation of planning, management, protection and reasonable utilization of land and resources, the strategic planning of national economic and social development, and other relevant special-purpose plans. There still are problems that need to be solved, such as how to ensure the authenticity and accuracy of land change survey results, how to improve the work efficiency of land change survey with new technology, and how to shorten the error modification time. The purpose of this paper is to evaluate the quality of land change survey database and analyze the causes of database errors. For a quantitative analysis of the changes of database quality in 2010, 2011 and 2012, comparative methods were employed. Methods known as Moran's I and local Moran's I were adopted to analyze the spatial dependence in observations of database errors among administrative units, and to reveal the change of spatial distribution and the anomaly characteristics of database errors in local areas. To be specific, five steps are required for quality evaluation and pattern analysis. Firstly, the descriptive chart of original errors at the county level is processed in batch transaction by software, and then is aggregated into database tables. Secondly, since the quality inspection rules were found inconsistent among 2010, 2011 and 2012, it is impossible to use a comparison analysis method, thus we preprocessed the data and acquired the common quality inspection rules for the three-year period. The third step is to use the comparison analysis method to assess the database quality from different aspects, including the defect levels, the main check items of errors and the spatial distribution. The fourth step is to define the database errors by observing through the global autocorrelation method in analyzing the land change survey of Hebei province, and obtaining the spatial distribution characteristics and the influential factors of database errors. Finally, the spatial pattern of the phenomenon was reflected and the causes of database errors were explained. The results showed that the quality of the database of Hebei province in 2012 have been improved significantly according to the number of errors, the defect levels and the spatial distributions in assessment. In addition, the distribution of Hebei’s database errors were high autocorrelated with the fluctuation of aggregation level, while the generation of local anomaly was usually derived from artificial error. It is concluded that throughout the quality analysis of the research database and its space distribution pattern in three years, we can evaluate the changes of database quality objectively and identify the causes of database errors effectively, therefore provide a forecasting and monitoring approach to new land change surveys.

Land cover refers to the complex of various materials of the earth's surface and its natural attributes and characteristics. Land cover data at global scale is fundamental and indispensable for global change studies, and its data quality has been the focus of a variety of international communities. In 2010, China launched the project of 30 m Global Land Cover remotely sensed products with 10 classifications for the base years of 2000 and 2010, which takes a four year period to complete, and the data quality issue will affect its subsequent applications. This paper mainly studies the accuracy assessment method for regional land cover data, as a preliminary of global validation. First, the spatial characteristics of land cover data are discussed, such as being massive, multi-dimensional, and heterogeneous. Then, a general approach based on spatial stratified sampling method for the accuracy assessment of regional land cover product is proposed to improve the traditional sampling method. Considering the spatial characteristics, this article presents the method of spatial stratified sampling: stratified sampling is conducted according to land cover type, the total sample size is calculated using probability and statistics optimal model, and the sample size of each layer is allocated according to the area ratio; while in the sample spatial allocation process, the representative of sample, which implies that the spatial correlation between samples should be low, needed to be considered. In each layer, each sample's spatial correlation is calculated by Moran's I index, and by setting a threshold value, the representative samples are chosen. The final sample set of each layer is randomly selected based on spatial analysis. The spatial sampling scheme is divided into three parts: sampling method, determination of sample size and the sample allocation. We have made an improvement in this paper, by designing a two-step scheme, which are quantitative estimation of sample size and spatial allocation. A case study of Shaanxi Province of China shows the method and process of accuracy assessment for regional land cover product. 1467 samples are selected by spatial stratified sampling in 7 strata. According to the confusion matrix, the overall accuracy is 79.96% and kappa index is 0.74. User's accuracies of all land cover types are more than 75%, while producer's accuracies fluctuate due to the low sample size caused by the low area ratio, which have little impact on the overall accuracy. Experimental results show that the proposed method is applicable to accuracy assessment of regional land cover product. Study on global land cover product will be performed as a main research direction in future.

With the development of high resolution satellites, the attitude jitter, which is a common and complex phenomenon, has become a key problem in the applications of high resolution remote sensing images. It leads to the degradation of image quality, and non-steady and lower precision for the attitude measurement data. Therefore, in this paper, a jitter detection and analysis method based on remotely sensed imagery is proposed. It took the advantage of the imagery data to detect jitter without additional involvement of high-performance sensors or a large quantity of GCPs. Two different jitter detection methods for different types of sensors are presented, which consist of: (1) jitter detection methods based on multispectral images utilizing parallax between two different bands in the image, and (2) jitter detection methods based on stereo images using triplet stereo images and rational polynomial coefficients (RPCs). With the jitter detection methods, the relative registration error is obtained. Afterwards, we can retrieve the time-dependent attitude jitter. Consequently, the frequency and amplitude of the attitude jitter can be achieved by analyzing and modeling the jitter using cosine functions. To reduce the jitter effect on geo-positioning process, the true attitude information should be estimated from the detected jitter components. An improved sensor model is introduced to take into account the compensation for the attitude jitter. The performance of the improved sensor model is assessed in direct georeferencing. Experiments are conducted with images acquired from the first civilian three-line-array stereo mapping satellite ZY-3. A periodic pattern with a frequency of about 0.65Hz has been detected. Based on the theories and methods mentioned above, the detection and analysis of satellite attitude jitter system based on remote sensing imagery has been developed using VC++. An image sub-blocking and a parallel computation scheme based on the computer performance is performed, which can improve the efficiency. Test results show that the system can efficiently detect the attitude jitter of 0.1 pixels. Meanwhile, it can model the regular jitter and correct the jitter effect on geo-positioning process. The accuracies for the plain and height directions are improved from 2.1799 m and 3.2497 m to 1.4396 m and 0.7453 m, respectively. This system has a good stability and robustness and has been successfully applied to the ZY-3 ground application system.

With the rapid development of remote sensing techniques, higher precisions of the vegetation remote sensing are required. Therefore, before using the time-series data, how to select the optimal algorithms to reconstruct it has been a hot research topic. Based on the five main land cover types in Northeast China, the reconstruction quality of three commonly used algorithms that included in TIMESAT tools has been qualitatively analyzed. Then, the fidelity performance and the capability to keep main characteristics of the three algorithms on EVI with respect to different land cover types were compared. The result shows that the S-G algorithm has a better performance in reconstructing the peak and the width of the EVI curves in the growing seasons, but it is prone to keep the noise data due to excessive fittings, especially common in land cover types of steppe and shrub. AG and DL algorithms generally present similar performances and the results are much closer to the true values for land cover types of steppe, shrub and arable land. But AG algorithm is easily influenced by noises for fitting the peak of the cures, which reduces the maximum EVI and causes the decline of vegetation growth. Spatial patterns of the fidelity performance and the capability to keep main characteristics of the three algorithms are all related to the distribution of vegetation types. Finally, we found that AG is a better algorithm to be used for the land cover types of steppe and shrub, DL is better for arable land, while S-G is better for the broadleaved deciduous forest and coniferous deciduous forest.

Geographic grid system is a set of related global grids at various scales which tessellate the earth into a hierarchy of areal cells and associated cell points. As a frontier research of geographic information science, geographic grid system is not only a geospatial framework, but also a model for geographical feature expression. According to the needs of data management and sharing in integrated scientific investigation of resources and environment, this paper presents a detailed analysis on Chinese national standard of geographic grid. We discover that according to the standard, the apertures of grids are sometimes too large and incongruous, when they are used in multi-resolution applications. In order to making up the inadequacies, the paper extends the radix between one degree (minute) and one minute (second) from 60 to 64 in logical space, where a formal quadtree-like recursive subdivision can be implemented until the one second grid is reached. Grids finer than one second can also be subdivided in a similar manner and be expressed by taking the negative exponentials of 2 as the interval. The paper also designs the extension encoding scheme for quadtree-like grids, so that it could be compatible with the existing national standard of geographic grid. A prototype of multi-level grid generation and management named GridVis 1.01 is developed to validate the feasibility of the proposed schema. Experiments on the real-time 3D visualization of various resources and environmental data are designed to examine the frame refresh rate of the scenes in GridVis. When the 1-degree-grid is used to organize the national 1:250,000 county administrative region data of China, the GTOPO 30 digital elevation model of China, and the 1 km spacing national vegetation cover data of China respectively, the frame refresh rate is 33~52 frames/second (FPS). When the 10-minutes-grid is used to organize the 1 km spacing national land use data, the average frame refresh rate is 30 FPS. When the 1 km grid is used to match the 1 km spacing population data of Ansai county (which locates within Yanan city of Shanxi province), the average frame refresh rate is 50 FPS. All the experimental results suggest that the proposed schema could satisfy the demands of real-time applications.

A Discrete Global Grid System (DGGS) is a set of related global grids at various scales which tessellate the earth into areal cells and associated cell points. As a promising global reference model it supports fast, seamless assimilation of numerous and disparate geo-data sources and sensor networks, regardless of scale, origin, datum, or projection. Compared with square and triangle grids, hexagon grids are uniform adjacency and they have better symmetry and more quantizing efficiency. These properties have made hexagon grids the potential data structure for massive geospatial modeling, integration and analysis. This paper presents a new octahedron-based construction algorithm which yields all types of hexagon DGGSs. It combines two adjacent triangle facets of an octahedron into a logical quad structure on which a three-axis coordinate system is established to describe the location of multi-resolution grid cells produced by different types of hexagon partitions. According to the characteristics of the algorithm, an object oriented software model is designed. Experiments are carried out to examine the feasibility, validity and efficiency of the model. The results indicate that the proposed algorithm employs a uniform mathematical model to describe all types of hexagon DGGSs. The corresponding software model separates the unique features of an individual DGGS from the commonness of all DGGSs, which makes the model extendable and flexible. The results also reveal that the efficiency of the algorithm remains stable regardless the increase of partition level. Two dominant factors are found to be responsible to the phenomenon. One is the maximum processing ability of the computer in which the experiments were carried out. The other is the I/O bottleneck of the computer which makes the CPU idle during the procedure of data export.

Discrete Global Grid System (DGGS) provides methods for constructing new spatial data models. It is a promising computer representation of global geo-referenced data sets based on regular, multi-resolution partitions of polyhedra. The object of our research is hexagonal DGGS, and we propose a new optimized target function to evaluating the geometrical properties of discrete global grids. Based on this function, this paper designs a new construction idea of hexagonal DGGS which combines the numerical projection transformation and heuristic global optimization. In addition, according to the weakness of DGGS: spatial measurement, this paper discusses the area measurement, the lineal measurement and the angle measurement based on the hexagonal DGGS. Its purpose is to develop a spatial measurement system for the hexagonal DGGS. In the end, the conclusions and the further studies of this paper are given.

Land type (in the former Soviet Union, it is known as "landscape", and in Europe and the United States it is known as "land system") research has an important role in the integrated physical geography. Although the study on land type has made many achievements in the domestic and foreign research and there were a lot of land type mapping practices, there are still three key academic problems to be solved: (1) how to perform the basic land type classification and hierarchy and how many levels of hierarchy are needed, while the proof of land type classification system is lacked in previous mapping practices; (2) how to choose the land type indicators at all levels; (3) how to realize computerized cross scaling graphics technology using multi-source data. In this paper, a building method of land type indicator database has been designed, which could solve these problems based on the national standard geographic grid. A four-level standard grid system model is built, and the land type classification indicators are expressed respectively by the grid cells at different grid levels. We choose area, landform, soil and vegetation, which are often used in land type research, to be the indicators in designing the building framework of the multi-level standard geographic grid indicator database. Through the design and analysis process, we point out that the multi-level geographical grid classification system has its physical basis: all earth sciences have multi-scale research features and the hierarchical classification system for each subject could be expressed by multi-level standard geographic grid system model. Especially, the three elements of landform, soil and vegetation that are often used in land type classification system research are typical, due to the interactions among them. These lead to a conclusion that the number of classification levels for the three land types’ classification systems and the scale of grid cells at each level should be identical or similar. Therefore, the building framework presented in this paper is feasible and will help to address the three issues mentioned above. This framework should be used to guide the establishment of database and further land type research.

The semi-variogarm has been widely applied in many fields such as mining, soil science, and environmental science to acquire the impact range of spatial process. In remote sensing, it could be used to analyze the spatial structure of remote sensing images or obtain appropriate scales for ground features in the images. Nevertheless, images with huge sizes make the application of semi-variogram on remote sensing different from other disciplines. The computers, on which the semi-variogram curves are calculated and fitted, need more memory and stronger CPUs, which is seemingly impossible to always meet the requirement. A common solution is to decrease the data volume by random sampling, under this circumstance. Specifically, a small amount of samples are selected randomly from the population and analyzed for supposed result instead of using the whole population. This method does decrease the requirement of analysis for computing capacity and memory of computers. However, the accuracy of analysis drops simultaneously, because the result derived from samples in one single sampling is likely to contain errors. To solve this problem that related to spatial structure analysis, this study proposed a method based on Monte Carlo simulation in which a small amount of samples are taken from the huge-volume population for enormous times and then analyzed respectively. In this way, the amount of computation in a single simulation can be reduced to the level that an average computer could tolerate, meanwhile the accuracy can be guaranteed. Also, the parallel computing technology was introduced in this study in order to minimize the time needed for simulation. The parallel computing of semi-variogram was executed in MATLAB whose parallel computing service is simple and easy to manipulate. The experimental area is a rectangular part of An'sai County of Shaanxi Province, China, with an area of 41.32 square kilometers. In this area, there are many types of ground features such as forest, grass, water, farmland and built area. Among all these features, grass is the dominant one. The simulation result shows that, this method could acquire appropriate scales for the common ground features while keeping the estimation errors low.

The Discrete Global Grid System (DGGS) is a new type of global spatial data model and is the extension of the plane grid on a sphere. Hexagon is usually used in the construction of DGGS for its advantageous geometric structure. Since sphere is unextended, in the process of plane grid mapping, the distance and direction of the grid will change greatly. As a result, the accuracy of drawing vector data in the global grid cannot be guaranteed. This has been a critical choke point for the display of vector data in DGGS and has directly restricted the establishment of spatial measurement relationship on a spherical grid. In order to solve the drawing problems of vector line data in hexagon DGGS, this paper has studied the distortion regularity that the plane-sphere mapping process affects the linear direction, and control the accuracy of vector line data grid transformation. As a result, the vector drawing method on a plane grid can also be adopted to deal with high-accuracy drawing on a spherical grid, and it guarantees that the spherical grid drawing errors of the vector data can be controlled strictly in one cell of the current layer´s grid. This paper also lays the theoretical foundation for high-accuracy display of grid transformation data and the establishment of spherical grid spatial measurement.

In vector data watermarking technology, the geometric transform attack is commonly difficult to cope with. The existing algorithms that can resist the attacks of geometric transformation, however always cannot resist vertexes attacks. Therefore, a blind watermarking algorithm for vector data is proposed based on the idea of data normalization to solve this problem. In this algorithm, the coordinate values of spatial data were normalized before embedding the watermarks, in order to keep invariant with respect to translation and zooming. Watermarks were embedded in the normalized values of the vertex coordinate data for several times. There are no original data needed in the procedure of watermark detecting. The experiments show that the algorithm is robust against a series of different attacks, such as translation or scaling transformations, vertex insertion and removal, cropping, compression, reordering and data format conversion. In addition, it can control and limit the relevant errors of the watermarked spatial data that produced during the watermark embedding.

Located in the northwest frontier of China, Xinjiang holds an important strategic position. Carrying out a study on the distribution of suitable arable land resources of Xinjiang may have a great significance in promoting the rational development of Xinjiang's land resources and ensuring our country's arable land and food security. Based on multi-source natural geographical data, through building an evaluation model with GIS, this article made a multi-level comprehensive evaluation from the spatial aspect on the suitability of land cultivation in Xinjiang. First of all, choosing 10 indicators from 4 factors including topography, climate condition, edaphic condition and ecological condition, making use of the function of spatial analysis in GIS, and combining comprehensive index method with limiting conditions, this article constructed the evaluation model of arable land resources in Xinjiang, from the standpoint of the suitability of land cultivation. Furthermore, the modeling results were compared with the actual arable area extracted from topography, which would be used to determine the classification standard of the results, so that we can evaluate the quantity, quality and spatial pattern of arable land resources in Xinjiang. At last, using the data of cultivated land resources in 2000, 2005 and 2013 in Xinjiang, the research effectively proved the scientificity and rationality of the evaluation model, and also figured out the necessity for further improvements.

Satellite Infrared remote sensing (RS) technologies, which include the near-infrared, shortwave infrared, middle infrared, and thermal infrared RS, have been widely used over the world, and it has been playing an important role in the field of environmental protection in China. This paper focuses on introducing the recent applications of RS, including: monitoring the straw burning, dust storm, aerosol optical depth, particle matters, and haze pollution for air environment quality monitoring; monitoring the blue algae, water quality (factors include chlorophyll-a, suspended sediment, transparency, and nutrition condition index), water surface temperature, thermal-water pollution, and warm water discharge of nuclear power plant for water environment quality monitoring; and monitoring the soil water content, vegetation water content, drought, evapotranspiration, land surface temperature, and urban heat island for ecological environment quality monitoring. Some typical application cases are illustrated in this paper, including the distribution of straw burning sites in China using satellite data; the monitoring of warm water discharge for Dayawan nuclear power plant; and the monitoring of Beijing urban heat island. In the end, we point out the existing limitations for remote sensing application, such as the low application level of domestic satellites due to its low spatial and temporal resolution, the limited signal to noise ratio, the deficiency in radiation calibration, the lack of original created algorithms, and the deficiency in ground observation and validation. Meanwhile, we proposed suggestions for further development, such as vigorously developing domestic infrared remote sensors, enhancing the level of satellite and ground radiation calibration, studying the original algorithms for environment monitoring, and constructing comprehensive ground experiment bases, etc. The development of satellite RS techniques, especially for the Project of China High Resolution Earth Observation, which is designed to carry various advanced infrared RS payloads, will significantly improve the quantitative monitoring level of environmental application in China.

Since land subsidence was firstly discovered in the 1950s in Beijing city, it has revealed a rapid developing trend. In the past few decades, land subsidence has been increasing in both its range and speed year by year and become one of the most serious disasters affecting the safety and development of Beijing ^[1]. In this paper, we choose four typical subsidence locations as the study area. The land subsidence information of the typical area in Beijing plain during 2004-2010 was used as the primary data source. This is acquired by Permanent Scatterers Synthetic Aperture Radar Interferometry (PS-InSAR) method, which has high accuracy and been widely used in deformation monitoring and land subsidence research. Meanwhile, the conventional monitoring data (1955-2010) was adopted as the supplement data. Then, we analyzed subsidence evolution characteristics from two aspects: spatial distribution and temporal evolution. Combing with the groundwater dynamic monitoring data, the land-use data from remote sensing and the using of GIS spatial analysis, we study the spatial and temporal respond and the important factors affecting land subsidence. The result shows that the seriously affected areas of ground subsidence in Beijing had expanded unceasingly, and the degree of unevenness has been gradually increasing. During the study period, the change of groundwater level had a high consistency with land subsidence in temporal and spatial distribution. In the process of urban development, engineering activities were considered another factor affecting the characteristics of spatial and temporal distribution of land subsidence. In this paper, our research indicated that the excessive exploitation of groundwater is the main influence factor for the subsidence in Beijing; and the rapid development of city leading to large-scale construction is also one of the factors that make the subsidence worse and more serious. The results have considerable referential importance and can provide a scientific basis for the prevention of land subsidence in Beijing.

Machine learning technology has been widely used in remote sensing image classification. Extreme learning machine (ELM) is proposed recently for image classification, but the regularization and kernel parameters (C, σ) of ELM have significant influence on classification performance. In this paper, an ELM classifier with firefly algorithm (FA)-based parameter optimization is proposed for hyperspectral image classification. Firstly, FA algorithm is used for band selection in order to reduce the computational load of hyperspectral image classification. Then, the parameters (C, σ) of ELM are optimized by FA with respect to the classification accuracy. In our experiments, the firefly algorithm is also compared with other parameter optimization algorithms such as genetic algorithm (GA) and particle swarm optimization (PSO). In addition, the support vector machine (SVM)-based classification algorithm is also implemented for comparison purpose. The experiments are conducted on three classical hyperspectral remote sensing data. Results indicate that the performance of ELM method is better than SVM method from the aspects of classification accuracy and running time. Our experiments successfully prove that the proposed algorithm can provide a better performance for hyperspectral image classification.

Assimilating remote sensing information into crop growth model is an important approachto estimate regional crop yield. The assimilation algorithm and corresponding assimilation variables are the keys of the assimilation system, which greatly impact the accuracy of assimilation results. In thepaper, the default irrigation parameters of WOFOST were optimized firstly with the help of calibrating WOFOST crop model parameters. Then, ET data was chosen as the assimilation variable to build the cost function of time series trends using MODIS ET products (MOD16A2) and WOFOST simulation. And LAI data was assimilatedwith the cost function of four dimensional variational data assimilation method using MODIS LAI (MCD15A3) products and WOFOST simulation. Furthermore, parameters including the crop initial dry matter(TDWI), the lifetime of crop in 35℃(SPAN) and the irrigation(RIRR) were optimizedcontinuously by SCE—UA algorithm, which would stop running the program when the cost function isoptimal. The estimatedcrop yield results were obtained usingfour methods comparatively under water limited mode, including the method thm²t does not assimilate and methods thm²t assimilateET, assimilateLAI and assimilate both ET and LAI.We address the assimilation of double variables to be the methodthm²t ET and LAI arebothm²ssimilated. Finally, the accuracies of yield estimation by assimilating double variables and a single variable under water limited mode were compared and analyzed. The results indicated thm²t the method of assimilating double variables was better than assimilating a single variable, which got the highest accuracy (R²=0.432, RMSE=721 kg/hm²). The method of assimilating high precision LAIsignificantly improved the accuracy of yield estimation (R²=0.408, RMSE=925 kg/hm²). The method of assimilating ET demonstratedbetter performance when the WOFOST model simulates the water balance during crop growing period, but had a limited impacton improving the accuracy of yield estimation (R²=0.013, RMSE=1134 kg/hm²) compared with model simulation (R²=0.006, RMSE=1210 kg/hm²). This research provided a reference for studies in other areas on predicting crop production at regional scale thm²t based on assimilating double variables.

High Accuracy Surface Modeling (HASM) method has theoretically solved issues of hill peak smoothing and oscillation phenomenon at edges, and its modeling accuracy is much better than the traditional interpolation methods such as Inverse Distance Weighting (IDW), Spline and Kriging. HASM has been successfully applied to the spatial mapping in multiple fields, such as population density, soil properties and climatic elements, etc. However, as the number and distribution of meteorological rain gauges are limited, getting the accurate precipitation distribution maps based on HASM is still a challenge. Additionally, remote sensing rainfall estimation data, which can provide better spatial information of the precipitation, but without accurate rainfall values, may play an important role. Therefore, in this study, we combine these two data sets together based on HASM model to estimate regional rainfall. Central and western China (25°~35°N, 105°~115°E), which are featured by extensive high mountains and plains, is chosen as the study area to model the spatial distribution of its total precipitation in 2010. Using satellite rainfall estimation, the Tropical Rainfall Measuring Mission (TRMM) 3B43 data is chosen as the background field for HASM modeling. Then, we compare its results with respect to the classical methods (including IDW, Spline and Kriging) based (also used as background fields) HASM modeling. Results show that TRMM based HASM method has higher accuracy and its results exhibit a better spatial pattern for precipitation simulation than those from the other methods. The MAE and RMSE of TRMM based HASM simulation results are 125.15 mm and 155.80 mm, respectively. The simulation errors of the best simulation results using the other methods are respectively 53.6% and 54.5% higher than TRMM based HASM simulation results. Besides, its relative error in each sub-region is also smaller than the other methods. In the multiple applications of spatial elements modeling, e.g. meteorological elements modeling, where there is not enough sampling sites to characterize the spatial structure of an element, the accuracy of HASM modeling will be limited. Therefore, combining it with supplementary information to compensate the deficiency of limited sampling sites will contribute to the production of better results for HASM applications.

Confirming the existence of spatial differences among different parts of urban areas, based on the 1:1 million digital geomorphic database and DMSP/OLS nighttime light data from 1992 to 2012, we explored the spatial characteristics of urban development in Beijing-Tianjin-Hebei region for recent 21 years, including the change of urban barycenter migration, the development difference of internal urban area and the relative development rate. Besides, we compared the development difference of urban areas among different macro-scale geomorphologies. The results show that: the barycenter of Beijing-Tianjin-Hebei region has moved south-west, north-east and south-west in sequence, and different cities have different barycenter migration routes and directions; the development level of Beijing-Tianjin-Hebei region has been steadily increasing, while the disparities between cities in this region have been reduced; for cities with different types of geomorphologies, the disparities between their own municipal districts have different changing patterns over time. For plain cities, the disparity basically keeps stable; for mountainous-plain or plain-mountainous cities, an implicit downtrend is indicated; and for mountainous cities, the disparity between their municipal districts declines gradually. The migration of mountainous cities’ urban barycenter is more obvious than cities dominated by other geomorphologic types, but these cities have an overall low development level. At last, we discussed the advantages of using DMSP/OLS nighttime light data, with the premise that heterogeneity exists in each city. We also pointed out that with regard to a long time series, there is evident relevance between urban development and urban geomorphology. A deep investigation into the relevance between the spatial characteristics of urban development and urban geomorphology is significant to understand the nationwide changes of urban development.

Urban expansion, in which the non-urban land use is converted to urban land use, is an important aspect of urbanization. Three Landsat time-series images for 2000, 2006 and 2013 of Zhangzhou city, which is located in Southern Fujian Golden Triangle Region, have been used to study the urban expansion of Zhangzhou urban area with the assistance of remote sensing and GIS technology. The index-based built-up index (IBI) was used to extract urban build-up land information of Zhangzhou from the three images. The extended urban range and expanded urban area were obtained by applying overlay analysis on the vectorized maps allocated in eight quadrants. The result indicated that during the 13-year study period, the urban built-up area of Zhangzhou had a net increase of 13.69 km², which was 66.9% more than the area in 2000. The calculation showed that the built-up land expanded more rapidly in the period between 2000 and 2006. The urban area expanded toward the northwest direction in a planar and linear way, which was mainly along the three main traffic lines of Zhangzhou. The buffer analysis showed that the traffic line distribution had a significant impact on urban expansion. Driving force analysis indicated that the fast economic development and population increase were the driving forces to the expansion of Zhangzhou urban area. Socio-economic data showed that Zhangzhou´s urban expansion was closely related to the growth rate of the city´s secondary industry. Its expansion pattern belonged to the industry oriented expansion. Besides, the different growth rates of population in different regions also played an important role in Zhangzhou urban area growth, which resulted in the expansion of urban area toward the north-west district. Overall, the imbalanced growth ratio between urban land area and population implied the irrational urban land development in this city. The urban expansion derived by industrial development can be represented with a traditional urban-development model. Therefore, a faster development of tertiary industry for Zhangzhou is crucial to improve the city´s developing quality. Nevertheless, when shifting the planning focus from industrial structure to tertiary industry, the decision makers should pay attention to the intelligent use of urban land.

Cloud and shadow contained in satellite images usually causes inaccuracy in water extraction and brings difficulty to time-series analysis of water resources. In this paper, we took HJ-1 as the primary data and ZY-3 data as the auxiliary data to extract water information and monitor water distribution changes. To find the potential location of water, we randomly selected a series of check points using ZY-3 data. Based on the uniformly distributed check points calculated from the ZY-3 data, we examined the integrity of the water extraction result of HJ-1 data. If the extraction result was not integrated, we supplemented it with the water extraction result from images that are obtained within an adjacent time period, according to a check points based strategy. These supplemented extraction results in different periods formed a completed time-series dataset that provided a reliable way to monitor the water resources and distribution changes. The experiment was carried out on analyzing the Anhui section of Huaihe River watershed, and its results showed that this method took full advantage of the images within adjacent time. Even if the image quality was poor, this method managed to produce a more integrate result in comparison with the use of a single HJ-1 image. The randomly calculated check points minimized the manual intervention, thus provided an accurate and effective way to monitor the time-series of water resources. In the study area, 8295 check points were extracted. The results revealed the water resources of the study area in the rainy seasons (July and August) were more abundant than dry seasons (March and April) in 2013; especially, many temporary water bodies had been detected in the south of the watershed in the rainy seasons. The total water area had increased 22.1% in the rainy seasons compared to the dry seasons.

The impact of tsunami hazard to the coastal countries and regions is a hot topic within the field of tsunami research. One of the main reasons that cause a tsunami is submarine earthquake. Since the Manila Trench and a part of China´s territory cover across the South China Sea, and the trench has frequent seismic activity, it becomes a potential tsunami source which may influence the south China. A hypothetical tsunami is simulated by adopting the COMCOT numerical tsunami model, to research its effects on the area of Hainan Island and Beibu Gulf. The tsunami is triggered by an earthquake in the Manila Trench, and the entire source is discretized into 33 rectangular elements, which would produce an earthquake with a magnitude of M_w=9.0. The tsunami wave characteristics and its impacts on this region are analyzed with the help of records from the virtual tidal stations installed in the study area. The majority of tsunami energy is directed northward to the coast of China. The results indicate that the tsunami waves propagating to the Beibu Gulf Zone have distinct nonlinear characteristics, and spread more slowly than in the deep ocean. After 2 hours and 10 minutes when the earthquake occurs, the head wave propagates to the east coast of Hainan Island with the amplitude of 2.6 meters, which could bring great impacts or hazards to this area. However, because of sea bottom friction and the blocking of Hainan Island, it takes another six hours for the head wave to reach Beihai offshore, and the wave amplitude then is reduced to be less than 50 centimeters. The energy of tsunami undergoes a great loss, and it may have little impacts on the southern coast of Guangxi Province and the Beibu Gulf area. And yet, the additive effects of the tsunami and the tidal currents in the gulf area require further research.

With the implementation of "coordinating urban and rural construction land" policy and "people linked to land" policy, it is of great significance for relieving the contradiction existing in the construction land between supply and demand, and in addition to grasp the laws of spatial pattern and arrange reasonable layouts for rural residential patches that have large renovation potential. Based on the "Land Use Change Survey Database 2010" and "Jilin Statistical Yearbook 2011", the laws of spatial pattern of the present rural residential land for different administrative districts in Changchun-Jilin consolidated metropolitan area were quantitatively analyzed using GIS method combined with landscape ecology method. The spatial relationships between the layouts of rural residential land and slope, river, road, and railway were also discussed in the same way. As a multi-factor comprehensive evaluation method was used to evaluate the locational suitability of rural residential patches, we divided rural settlements into different types of renovation, which could provide a theoretical support and reference for the comprehensive management of territory. The results indicate that: (1) the land distribution of rural settlements is uneven, and both the quantity and density have big deviations in different administrative regions. (2) The terrain conditions (slope), water conditions (river), traffic conditions (roads and railways) all have effects on the spatial layouts of the rural residential land in the study area, but the effects are different. Different grades of road (trunk road and branch) and different forms of railway (rail lines and stations) have different effects on the spatial pattern of rural settlements. (3) On this basis, according to the role of influence factors that have effects on rural settlements, we divided the spatial locations of rural residential patches into different suitability grades. Therefore, the rural residential patches were further divided into corresponding types, including the priority development areas, the retaining development areas and the limited development areas. Then, we pointed out and discussed the improvement directions for each rural residential type.

Geo-tagged video contains location information, and it is critical for true geographic representation. The geospatial representation of geo-tagged video is the key feature for the integration of video and GIS. Regarding to the disadvantage of geo-tagged representation methods for video objects with monotone spatial semantic information, a geographic representation framework for geo-tagged video objects is proposed. On the basis of extending OGC specifications for geographic information, this paper defined the respective objects in 7 types from 3 categories to describe the spatial information on two levels, including the video frame and video clip. The 3 categories include: (1) the video positions (point) to represent the location and attitude as the camera taking shoots; (2) the video trajectories (line) to portray the track of the video clip; and (3) the video field of view in plain view (polygon) or 3D (solid) space to describe the spatial extent of the video scene. The framework consists of the main spatial objects including the point, line, polygon and solid. It is more competent for demonstrating video spatial information. Meanwhile, the framework supports different levels of video data, such as the video frame and video clip. It achieves the loosely-coupled and perfectly-integrated integration of video and GIS, which does not need to alter the data structures. This paper discussed the data acquisition methods for the spatial information of video frames or clips in detail, which take use of the GPS receiver and 3D digital compass. We also developed 9 tables and defined their relations for the logical model to realize the geographic representation of geo-tagged video objects, and we analyzed the data visualization and retrieval methods by taking them as the application cases. The results show that the geographic representation framework for geo-tagged video extends the current spatial database standard. It is easy to implement and applicable in geographic visualization, video retrieval and spatial analysis or data mining.

This paper delineates the relationship between remote sensing monitoring indexes and malaria incidences using genetic programming (GP) method based on factors derived from remote sensing data. Thus, the spatial distribution of malaria incidence is predicted, the prediction results are analyzed, and the modeling precision is evaluated. Malaria is considered to be the severest parasite disease and Anhui Province is one of the typical mid-latitude areas coping with high malaria risk. This paper studies the issue of predicting malaria spatial distribution using GP method, as GP is a striking optimization method which has the capability of exploring a proper solution for sophisticated issues through evolutionary algorithms. And this process is further explained with an example adopting the monthly average malaria incidences in each county of Anhui Province from 2004 to 2010. Also, remote sensing data is regarded to be the main source of factors, considering its large spatial scale and fast data acquisition, and that various meteorological and environmental indexes, could be converted from remote sensing data. These factors include remote sensing indexes, such as normalized difference vegetation index (NDVI) and land surface temperature (LST), plus natural attribute (elevation) and social attributes (population, immigrant and GDP data) in the county level. Results demonstrate that NDVI and LST have influences of two months’ and one month’s lag respectively. Compared with the result of linear regression (R² = 0.470 for training data and R² = 0.408 for test data), the predicting precision is improved using GP method (R² = 0.558 for training data and R² = 0.429 for test data), which is benefited from illustrating the non-linear relation between remote sensing indexes and malaria incidences. GP method contributes to increase the precision of predicting the spatial distribution of malaria incidence. Conclusively, this paper provides a basis for future scientific research on predicting spatial distribution and mapping malaria using remote sensing data.