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.

There is a pressing need to extract building height rapidly based on high-resolution remote sensing images without parameters in the field of urban construction and land management. Current studies are mostly based on remote sensing images with parameters, however the images used for extraction are difficult to get, and current extraction methods have a lot of restrictions. In this paper, a new method is proposed with the use of four types of characteristic lines. The characteristic lines are comprehensively formed by the characteristic points on a single image, which is used to convert the building height based on high-resolution images without parameters. The four types of characteristic lines include: the connection line of the roof displacement point and roof shadow point, the displacement of the roof image point caused by the building height, the full-length shadow, the remaining length of the shadow excluding the part occluded by building. Four types of calculation model for acquiring building height based on the corresponding characteristic lines are deduced. According to the known heights of a small amount of constructions and using the four calculation models, the relevant parameters of remote sensing images can be derived conversely. Then, we can select the characteristic lines that are extracted most accurately on each building , and use the corresponding model to convert the building height. With the application of this method, a large number of building heights can be calculated quickly and accurately. The method is verified based on Google Earth image in Nanjing city and the results show: the images used in this approach are easy to acquire; the method of comprehensive measurement and calculation does not merely rely on the use of shadow lengths to calculate building height, so it significantly increases the practicality of extracting building height on a single image; it solves the issue that there is no related angle parameters of the sun and the satellite position when calculating the building height. Case study indicated that the precision of the proposed method is high, and it can extract the building height quickly in a large area. Generally, the method proposed in this paper has significant practical value in production applications.

Hydrological analysis module supported by GIS extracts information about the hydrological characteristics of research area by using Digital Elevation Model. In this paper, Zhengzhou-Luoyang region is selected as the research area. And Peiligang cultural period, early Yangshao cultural period, later Yangshao cultural period and Longshan cultural period are selected as the time series. The paper uses hydrological analysis to get the information of drainage basins in Zhengluo region, which is proved to be viable and rarely used in previous researches about the relationship between prehistoric settlement sites and drainage basins. According to the information of drainage basins, this paper analyzes its relationship with the spatial distribution of settlement sites in Zhengluo region. Besides, the relationship between the area of the drainage basin and the growth rate of its settlement sites, and the relationship between the area of the drainage basin and the number of its settlement sites are studied in the paper. The above relationships are clearly displayed in a digital way using the correlation analysis. And the results suggest that there is a significant positive correlation between the area of drainage basins and the number of settlement sites. There is also a positive correlation between the area of drainage basins and the change trend of settlement sites. When studying the characteristics of spatial and temporal distribution of settlement sites in each drainage basin, it can be found that during Peiligang cultural period, the distribution density of settlement sites in the eastern region is greater than the western region. And among the other three cultural periods, the distribution density of settlement sites in the central and western region is greater than the eastern region. Due to the different modes of production, there is a great difference among the residential environment within which the settlement sites are located. As time goes on, people′s dependence on drainage basins is gradually decreasing with the change of the modes of production. Therefore, the research on the relationship between prehistoric settlement sites and drainage basins extracted using the hydrological analysis is highly significant.

Water surface temperature (including sea surface temperature and lake water surface temperature) is a key parameter for studying global or regional climate change and numerical weather prediction (NWP), as well as being an essential controlling variable in the exchange of heat, moisture and gases between water surface and atmosphere. It has important significance for understanding the biophysical processes of water body. Satellite measurements of water surface temperature are well established with 30 years' collection of practical data and have incomparable advantages over traditional observations. Their limitations and challenges are also identified at the same time. There are more than 30 types of infrared/microwave radiometers which can be used for measuring SST/LWST, and their resolutions, advantages and disadvantages are summarized and compared in this paper. SST/LWST measurements depend on a combination of atmospheric properties and water surface radiances. Therefore, it is necessary to adjust and correct the atmospheric effect and water surface processes. The basic principles and the main types of algorithms for water surface temperature inversion using infrared and microwave data are illuminated and reviewed briefly. There are many uncertainties associated with SST/LWST measurements, and the magnitude of these uncertainties has put restrictions on the application or interpretation of SST/LWST measurements. A detailed analysis about these uncertainties in both infrared and microwave SST/LWST retrieval including undetected cloud, water vapor, aerosols, emissivity and skin effect is conducted. In order to determine the uncertainties in satellite-derived surface temperature, the validation of surface temperature retrieval is an indispensable step. Finally, a prospection about the trend of water surface temperature retrieval is proposed. Additionally, a strategy is advised for assimilating measurements from multi-sensor data in order to take the advantage of their complementary strengths.

The availability of precipitation data with high spatial resolution is critical for several applications, such as hydrology, meteorology and ecology. The Tropical Rainfall Measuring Mission (TRMM) data sets can provide effective precipitation information, but at a coarse resolution (0.25°). Therefore, it is very necessary to improve its resolution. The existing TRMM-downscaling methods tend to use ordinary linear regression (OLS), which is known as a global model. However, it ignores the local characteristics. In this paper, the relationship between TRMM and Normalized Difference Vegetation Index (NDVI) was explored by using a local regression analysis approach that is known as geographically weighted regression (GWR). The relationship was used to construct the precipitation downscaling model, which then produces 1 km downscaled precipitation data. The OLS model and GWR model were tested for the data of Northeast China from 2000 to 2010. The accuracy of the downscaled data was validated by the observed precipitation data from 93 meteorological stations located in the study area. Some conclusions can be drawn from our study: (1) there is a strong correlation between TRMM data and the observation data obtained from meteorological stations (R = 0.9172). Overall, the TRMM precipitation is higher than the observed data at all stations. (2) Two downscaling methods were applied in this study, and the results show that the downscaled precipitation based on GWR model produces better results. It produces better R values and the reduced RMSE. Thus, the GWR model is more suitable for the spatial downscaling of TRMM. (3) The correlation coefficient between the downscaled precipitation based on GWR model and the observed data is ranging between 0.44 and 0.97, and its spatial distribution is disperse. (4) The downscaled precipitation data improves the spatial resolution (from 0.25° to 1 km), which can better reflect the characteristics of the precipitation in the study area. It could provide more accurate and realistic precipitation data for the studies at small scales.

Ruminant livestock accounts for the major proportion of methane emissions within the agricultural sector. In China, cattle dominates the livestock due to its huge population and large size in comparison to sheep. The latest studies have paid little attention to the spatial variations and seasonal changes of the livestock methane emission factors, though a lot of direct measurements and modeling estiamtions have been made to improve the quality of the national inventories. In this study, we analyzed the spatial variarions and seasonal changes of the methane emission factors of cattle by studing the spatio-temporal differences in the body weight for 46 cattle species, the feeding and diet, and the draft and milk production in different places of China are also discussed . The Tier 2 equations of IPCC (2006) were used to calculate the methane emission factors from both the enteric and the manure management emissions. The calculation showed that the enteric emission factor was general low in summer (4.48 kg head^-1 month^-1) and high in other seasons, while the emission from manure management was high in summer (0.44 kg head^-1 month^-1) and low in other seasons. Spatially, northwestern China has a higher enteric methane emission factor (71.0 kg head^-1 year^-1) than southwestern China (55.2 kg head^-1 year^-1). The methane emission factor from manure management was low (0.1 kg head^-1 year^-1) in Tibetan plateau and high (5.4 kg head^-1 year^-1) in southeastern China.

Vegetation dynamics and their coupled relations with climate are current research hot spots in exploring how terrestrial ecosystems respond to climate systems. Beijing-Tianjin-Hebei Metropolis Circle, one of the three major economic circles located in the eastern part of China, has been experiencing a rapid development as well as a severe change in eco-environment. The analysis of NDVI’s (Normalized Difference Vegetation Index) spatial-temporal dynamics and the exploration of relevant key climatic driving factors have special significance in the research of ecological environment change in Beijing-Tianjin-Hebei Metropolis Circle. In order to explore the vegetation dynamics and the impact of climate change on vegetation cover in Beijing-Tianjin-Hebei Metropolis Circle from 2001 to 2013, we adopted NDVI data of MOD13A3 to study the trend and spatial pattern of this region using linear regression, with the assistance of precipitation and average temperature data from the growing season. The climatic driving forces of vegetation cover change were discussed using partial correlation analysis and multiple correlation analysis. The results indicate that NDVI had increased gradually during this period, which showed a good development trend for the vegetation cover in this region. The average partial correlation coefficients between NDVI and precipitation, and between NDVI and average temperature are 0.20 and -0.14 respectively, which indicate that NDVI is positively correlated with precipitation and negatively correlated with the average temperature during the growing season at the annual variation level. Furthermore, the impact of precipitation on NDVI is greater than temperature. Analysis of the driving factors on vegetation change shows that about 89.63% of the study area was impacted by non-climatic driving factor, while 5.68% was driven by a combined climatic factor of both precipitation and temperature, and 4.51% and 0.18% was driven by precipitation and temperature separately. As a result, it is evident to conclude that the vegetation change in this region is mainly affected by human activities.

Over the past decade, WebGIS has been widely adopted in various applications to visualize and share geospatial information over the Internet. To address the Internet transmission problems regarding large-volume vector data, streaming transmission based on streaming media transmission protocol is proposed. This paper focuses on the organization mode and the streaming transmission mechanism of vector data, and a service framework for vector data streaming transmission is put forward. The framework consists of server-side vector data preprocessing, streaming progressive transmission, client-side vector data reconstruction and application. A vector data structure is designed which is taken to be an independent group storage. Each group is a separate transmission unit, and the grouped features can be handled immediately after they arrive at the client side. This structure can support the data structure of point, polyline, polygon and other basic geometrics and abide by the OpenGIS standard encoding specification. The server-side preprocessing divides the originally stored vector data into several groups for progressive transfer. Referencing to the multimedia model, we propose an RTP-based streaming transmission schema on the basis of analyzing the packet headers of the RTP and RTCP. The RTP payload format is called vector data stream (VDS), and it is composed of a stream header and a stream body. The combination of RTP method with UDP for streaming transmission has better transmission efficiency than the XML-based WFS for web mapping applications. The error control method and security mechanism we proposed make up UDP's unreliable connection issue. The results are compared with WFS using 1:100 million Chinese basic geographic databases. The comparison reveals that the transfer size of WFS is larger than VDS and the transfer time of streaming transmission is approximately half of WFS's. Thus, the outline of a large-volume vector data map could be viewed quickly based on the proposed mechanisms and algorithms. The experimental results demonstrate the technical feasibility and usability of this approach.