Comprehensive scientific expedition is one of the important approaches to acquire regional resources and environment background data. China is a vast country with complex geographical conditions. However, the incompatibly weak capacity in data collection has raised great attention to Chinese government for the long-term development of integrated environmental and scientific investigation. Nonetheless, many setbacks exist in the integrated applications of acquired data due to the differences in spatio-temporal scales, survey contents and technical standards of historical scientific investigations. Thus, although we have acquired more and more data during long term investigations, it is still quite difficult to use these data correlatively, which also leads to the lack of understanding about the country’s natural resources and surrounding environment. Thereby, some questions arise, such as is it possible to get and further manage the investigated data by the methods of gridding; are there any existing norm standards, which are suitable for the investigation of natural resources and environment, to help aggregate the long-term accumulated data and guide the dynamic monitoring process in the near future; and is it truly feasible to build a long term medium scale system for natural resources and environment survey? Based on an ongoing integrated investigation on natural and environmental resources, this paper, brings up with some in-depth thoughts, such as the grid system for resources and environment surveys, the standards and subdivision of geographical grids, the norm standards of resources and environment investigation, the appropriate scale for resources and environment survey, the gridding process of attribute data, the acquisition and management of grid-based data, and the sharing and application of resources and environmental data.
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.
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.
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.
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.
Earth observation technology has developed rapidly nowadays, accumulating a great amount of data for studying earth system science and other global issues. But when facing the massive, multi-source and multi-resolution global data, how could it be rationally organized and managed to improve the efficiency of data analysis has become a challange. The geospatial information subdivision organization, as a new organizational idea of spatial information, is regarded as a potential solution. Among various domestic and international geospatial information subdivision organization frameworks, the GeoSOT-3D subdivision framework, proposed by the team of Professor Cheng Chengqi from Peking University, has obtained extensive close attention. Nevertheless, the spatial data at global scale are often massive and rich in content, resulting in a contradiction that the amount of data to be processed is far beyond the processing ability of the computer when expressing geospatial objects. To solve this problem, this paper combines the geospatial information subdivision model with the existing 3D rapid visualization technology, and proposes a clipping and hidden face removal strategy assisted by the octree to achieve the rapid subdivision expression of geospatial objects based on the GeoSOT-3D. Taking the expression of space electromagnetic field for example, we developed a demo system and discussed the simulation results. The simulation results demonstrate that the proposed method exhibited a better effect and to some extent resolved the issue of efficiency in the expression of spatial objects.
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.
Terrain texture is an important basis to distinguish different types of landform. Due to its purity in representing terrain surface topography and its derivability in terrain analysis, the analysis of DEM based terrain texture has become one of the important research subject in digital terrain analysis. But little research has focused on the scale effect of DEM based terrain texture. In this paper, DEM with 25 m resolution from 6 sample areas that represent the different landform types in Shanxi Province were selected as the source data and were further resampled into different resolutions ranging from 25 m to 325 m with a fixed interval of 50 m. The experiment dataset contains the DEM and its derivatives (slope, hillshading and roughness). A quantitative analysis was conducted on the textural features using gray level co-occurrence matrix (GLCM) model to discuss the variation characteristics of DEM based terrain texture with respect to the varied data resolution. Experiments show that the parameters of DEM and roughness data are the most sensitive factors with respect to the changes in data resolution. When considering different types of sample areas, the variation coefficients of angular second moment (ASM) and contrast (CON) have the biggest values among the six parameters, showing that they have the strongest ability to distinguish different types of landforms. In addition, ASM has relatively high scale-dependency and its distinguish ability declines dramatically with the change of data resolution (the values of standard deviation change from 0.032 to 0.011 and from 0.101 to 0.038), which indicates that ASM is suitable for recognizing the detailed terrain texture. On the contrary, the ability of CON to distinguish landform revealed an increase trend from 25 m to 325 m resolution (the values of standard deviation change from 0.145 to 0.241 and from 0.325 to 0.783), and it has relatively low scale-dependency that indicating its suitability in recognizing the wide-range terrain texture. Overall, this study is significant for a better understanding of DEM based terrain texture, and the scale effects of other texture models will be investigated in further studies.
This paper depicts a terrain section line generation method using the contour line. The method is adaptive to the relatively weak performance of mobile platform which has smaller internal and external storage capacity and lower computing ability of processor compared to a desktop platform. On the desktop platform, digital elevation model (DEM, including triangular irregular network and regular grid) is often used to generate terrain section line, which is also the basis of our proposed method. By comparing it with two other methods for generating terrain section line through digital elevation model, we found that the proposed method in this paper is much simpler and faster in calculation, more convenient in operation, and meanwhile has an appropriate accuracy in the result chart. It is quite suitable for mobile GIS use. In addition, this paper presents a solution for the case that a route is located between two contour lines. In other words, the route has no intersection with the closest contour lines while the traditional algorithm cannot figure out its elevation value. By making a horizontal straight line and a vertical straight line across a certain point on the route, the four intersections of the straight lines and the point's two nearest contour lines are obtained. Then, the elevation value of this point could be calculated using the four intersections' elevation values. With this method, enough elevation points could be obtained to generate the final terrain section line. It solves the problems encountered in the practical applications with a good result. In summary, the proposed method in this paper contains eight steps. Step1: thinning the measured route for reducing the amount of computation. Step2: finding out the intersection set of the thinned route and the contour lines, and then obtaining the elevation value for each intersection. Step3: checking whether the intersection set is empty. If yes, then execute step 4, if not, jump to step7. Step4: at a certain point, make a horizontal line and a vertical line across it for obtaining the intersections with the contour lines. Step5: obtaining the four intersections' elevation values and calculating the distances between the four intersection points and the certain point. Step6: calculating the elevation value of the certain point using a formula, and then use the same approach to obtain enough amount of points' elevation values. Step7: to ensure the final section line is smooth, more elevation points are acquired through interpolating to the existing elevation points. Step8: drawing the final terrain section line by sequentially connecting the elevation points. Finally, the proposed algorithm is applied in the production of regional geological survey, and achieves good results.
Space-time clustering, which is one of the main research focuses in the field of data mining, has important application values in the field of environment protection, disease prevention and control, and crime prevention and combat. The time "distance" is considered to be a substantial interval within the existing space-time clustering methods. However, crime cases with social attributes have obvious cyclical characteristics in different time-scales. It would be difficult to find the real rules of time and space for crime cases if these characteristics are ignored. Therefore, based on DBSCAN, an algorithm considering multiple time-scales and equivalent spatio-temporal neighborhood (MTS-ESTN DBSCAN) was put forward. In this algorithm, the various time attributes in multiple time-scales were considered, the equivalent spatio-temporal neighborhood was built, and the concept of the classical density clustering algorithm was cited. In the equivalent spatio-temporal neighborhood, the Euclidean distance (L2-norm) is adopted as the measurement of spatial neighborhood for the space domain. With the improved function of HDsim, which is a method used to measure the unified similarity of high dimensional data, we defined the similarity of time domain. Based on the crime cases data in the urban area of Fuzhou city during 2013, cluster analysis was conducted, and the resultant clustering quality was evaluated using several indicators such as CH (Calinski-Harabasz), Sil (Silhouette), DB (Davies-Bouldin) and KL (Krzanowski-Lai). The results showed the feasibility of the method in space-time cluster analysis of crime cases. Compared with the traditional algorithm of ST-DBSCAN, this algorithm has produced better quality of clustering. In addition, this algorithm can find the accumulation characteristics behind the rules of human´s work, rest and other social activities in a long period. It has certain significances and application values for the advanced study of criminal geography in urban area.
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.
Airborne interferometric synthetic aperture radar (InSAR) is one of the key methods to generate digital elevation model (DEM). As the accuracy of DEM would be affected by errors of InSAR system parameters, it is necessary to correct system parameters and compensate system errors using interferometric calibration. Most of the solving methods for airborne InSAR calibration establish the sensitivity matrix with antenna baseline length, baseline obliquity and phase bias jointly to calibrate parameters’ errors, which can be referred as the parameters-coupled solving methods. Since the sensitivity of phase bias is much smaller than baseline length and baseline obliquity, it would easily cause the sensitivity matrix to be ill-conditioned when establishing the sensitivity matrix with the three parameters together. In this situation, errors of the solution vector could be amplified, which consequently affects the interferometric calibration accuracy, and increase the sensitivity of corner reflectors’ locating heights to calculations. This paper presents a parameters-separated solving method for airborne InSAR calibration by separating the baseline length, baseline obliquity and phase bias during the calibrating-solving process. The method establishes the sensitivity matrix with baseline length and baseline obliquity firstly, to calibrate these two parameters. Then, the phase bias was fitted individually, and afterwards we acquire the integrated calibration result of all three parameters. According to the validation result of real SAR data obtained by the dual antenna airborne InSAR system, the condition number of sensitivity matrix established by the parameters-separated solving method drops from 1.07E+06 to 5.02 comparing with the parameters-coupled solving method. Also, the average deviation of height, which accounts for the differences between DEM that generated by the calibrated airborne InSAR system and the reference DEM with high accuracy, drops from 14.98 m to 6.51 m. The interferometric calibration accuracy is improved significantly. Furthermore, the result of simulation analysis demonstrates that the locating height of corner reflectors has no distinctive impact on interferometric calibration accuracy when using the parameters-separated solving method. Therefore, the parameters-separated solving method has a higher adaptability regarding to different locating heights of corner reflectors, which can effectively reduce the intensity of field works for airborne SAR interferometric calibration.
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.
