Geographical information explodes with the emergence of Internet, which also adopts brand new ideas to obtain geospatial data with traditional GIS methods. With the abundant geospatial information on the web, we proposed a toponym co-occurrences network model by extracting the toponym entities from web page texts using nature language process methods, as well as uniforming the toponyms, in order to conduct a comprehensive analysis of the web pages. The network set up in this paper is a weighted directed graph, of which every vertex represents a distinct toponym, and the co-occurrence of each two toponyms is displayed as one edge of this network. The frequency of geographic names is taken into consideration synthetically, which shows the weight of each network edge, as well as explains the co-occurrence relationship and transformation occurrence characteristics of those toponyms. On this basis, a method of toponym extraction from web page texts based on link analysis is carried out, taking advantage of the PageRank algorithm to calculate the link weight of every toponym in the co-occurrence network and rank each geographical name with a PageRank score. In this way, the importance of the toponym is calculated and the core geographic names with remarkable features or navigation features in all huge network resources can be found. A case study based on the actual data extracted from People’s Daily and Sina News Sport web pages is carried out to verify the technical solution, which shows that the proposed solution is both feasible and practically effective, which can also be applied to geographical information retrieval. Results show that the core toponym of co-occurrence network differs in different themes of web pages, and when the time sequence factor is taken into account, the core toponym results may also be different within a single theme of web pages.
Geodata has been increasing at a tremendous speed in what we call the new era of Geographic Information. It is a challenge to accurately find the needed data in a real-time fashion amongst the massive spatial data and to recommend the associated required data intelligently to users. In light of the problem that the data retrieval by traditional searching methods based on keywords and topic words cannot satisfy the real needs emerged in the geoscience research, this study built a Geodata Spatial-Ontology Model through a detailed expression of the concepts, characteristics, relationship and instances of spatial data. In addition, this article presents the qualitative and quantitative spatial relationship, which plays an inestimable role in describing the inner connection between spatial objects. Then a Geodata Spatial-Ontology is built according to the Geodata Spatial-Ontology Model, and most of the concepts, instances and the relationship between them are elaborated. At the end of this paper, an application has been developed to parse the ontology and extract the semantic information using Apache Jena, which is a free and open source Java framework designed to build the Semantic Web and linked data applications. By associating the Geodata Spatial-Ontology with the Data Sharing Infrastructure of Earth System Science, the experiment in this research proves that the proposed ontology shows a significant improvement in data discovery. The Geodata Spatial Ontology constructed in this paper will have an important significance to the accurate data discovery and data sharing in the era of big data.
Marine Abnormal Event (MAE) is an abnormal decrease or increase of marine environmental parameters, which covers a specified spatial domain and lasts for a specified temporal duration. Marine abnormal event can provide the temporal and spatial characteristics of regional sea-air interactions and global climate change, which has an important scientific significance. Based on the above information, we propose a novel algorithm to extract the MAE from the long-term raster datasets, named as MAESTEM (Marine Abnormal Event Spatio-Temporal Extraction Method). The MAESTEM has three key steps: the extraction of MAE at a temporal dimension, the extraction of MAE at a spatial dimension, and the tracking of MAE. At the temporal dimension, each grid pixel within an image is taken to be the one-dimensional time series, and its mean and standard deviation are taken as the criteria to define its abnormal snapshot status. If and only if the abnormal snapshot and its subsequent ones are not smaller than the specified threshold, i.e. T, the abnormal snapshots are defined as a temporal MAE, denoted by TMAE. We utilize the spatial neighborhood statistics method to count the number of spatial neighborhoods of a raster pixel which belongs to TMAE and to obtain the marine abnormal events at the spatial dimension, denoted as SAME, by using the spatial dimension abnormal extracting method. In the final step, we use the spatial topological relationship of SMAE to identify whether the SAMEs at the previous and post snapshots belongs to the same event. If they overlap, they are considered being in the same event. If the temporal duration of the event exceeds the temporal threshold, save the event, otherwise, delete it. Finally, the Pacific Ocean is taken as a research area, and its monthly averaged sea level anomaly (SLA), which is obtained from the remote sensing imagery during a period from January 1993 to December 2012, is used to test the feasibility and efficiency of MAESTEM.
The Pre-Quaternary underlying terrain profoundly controls the evolution and formation of loess landform. Obvious relationships, i.e. the geomorphological inheritance, could be found between the underlying terrain and the modern terrain. As a consequence, the Pre-Quaternary underlying terrain in the Loess Plateau should be regarded as the key factor for the understanding of the loess landform evolution. Among numerous numerical calculation methods, spatial interpolation has been regarded as an important method to reconstruct the DEM of underlying terrain by using the sampled bedrock outcrop points selected from a geological map. However, the sampling density has a great impact on the accuracy of the reconstructed underlying terrain. In this paper, the Suide geological map area (1:200 000) was selected as the study area, and then the influence of sampling density on the accuracy of the reconstructed underlying terrain was investigated using spline method. By adopting cross-validation method to evaluate reconstructed underlying terrain, the result shows that, different interpolation methods cause uncertainties to different degrees during the reconstruction of underlying terrain, particularly the spline method. On a basis of high density outcrop points and spline function interpolation process, the morphology of underlying terrain exhibits a typical “Runge phenomenon”. This phenomenon was always resulted from a polynomial interpolation process. With an increased sampling density, the error in underlying terrain appears a slowly decrease tendency firstly, and then it keeps stable. Meanwhile, the number of the extracted features has a linear upward trend. The result also shows that the sampling density of 1.7-2.0 points per square kilometer could achieve a good balance between the accuracy and underlying terrain feature reservation. The aforementioned results adjust our previous understandings that spline function could smooth the interpolated surface to some extent. And the result also provides guidance for the selection of a reasonable spatial sampling density.
Based on the analysis of the status quo on web map publishing, particularly the status quo on thematic map publishing, a new concept of layout based web map was proposed. The layout based web map changes the GIS system tendency and static images map tendency of thematic map publishing. It provides the high fidelity map quality, meanwhile realizes the simultaneous publishing of thematic data and thematic map. This paper introduces the design and implementation techniques of the publish system on layout based web map. These techniques decompose the thematic map image and the polygon data into a quad-tree mode. On one hand, it divides the thematic map image into a map tile pyramid with given regular grid size. On the other hand, the thematic data features (mostly are the polygon features) are decomposed into grid dataset with variable resolution. It records every grid attribute based on a unique identification and stores the complex thematic data with information of its region, time, index and value as a data element, which increase the efficiency in thematic data query. In addition, this paper introduces two application scenarios. The first one is a topographic map document published in the EPS format. The second one is a layout based web map publishing system for the “Atlas on Population and Environment, People′s Republic of China”. A comparison of the merits and demerits was made among five web map publishing modes, including WebGIS, static images, PDF/GeoPDF map, SVG map and layout based web map. The layout based web map approach with high fidelity and interactive maps is considered to be promising for the digital thematic map publishing in the web mapping field.
Monitoring and gathering the earthquake disaster information by authorities, and then informing the public along with guidelines on the countermeasures is currently the dominating information circulation model for earthquake prevention and disaster reduction. However, with this unilateral model, there are no accesses and channels for the masses to query and feed back the disaster information actively, which hinders the preparedness and reduction of earthquake disaster and the post-disaster reconstruction. As a consequence, the public may not be fully prepared, causing the occurrence of huge damages as well as the long term recovery afterwards. Intended to offer a resolution to these problems, this paper summarized the characteristics and applications of PPGIS in supporting public participation. Also, to facilitate the design of the database and functions of the platform, this paper classified the earthquake disaster information into four categories according to the stages in disaster management. Furthermore, this article discussed the functions of a public earthquake information service platform, which is based on PPGIS, in providing people with seismic disaster knowledge and information, and in enabling the crowd to submit and return the emergent rescue needs and to participate in the reconstruction. The data quality and method of quality control have been discussed too. At the end of this paper, the authors designed and developed the prototype system of PPGIS based public earthquake information service platform. This prototype has put forward an applicable solution to enable the public to acquire and feed back the disaster information, and provides a reference for the design and implementation of other similar systems.
People′s movement in a city is driven by purpose. Moreover, the distribution of urban spatial structure can cause the phenomenon of human convergence or dispersion, and this phenomenon is always changing over time. Therefore, understand the spatio-temporal patterns of human convergence and dispersion could provide us a good knowledge of human travel demand in the urban context, so that the better decisions can be carried out to meet the demands of citizens. With the rapid development and widespread use of location-aware devices, it becomes relatively easy to collect the large-scale human sensor datasets and to bring new opportunities and challenges to the study of urban human mobility. Especially in recent years, mobile phone data has become a rich resource for research and it is widely used to study the human mobility patterns from various aspects, with regard to its advantage in tracking the long-term and large-volume of urban citizens with low cost. In this paper, taking Shenzhen City as an example, we firstly extracted the origin-destination flow matrix from the mobile phone location data and employed Local Moran′s I to identify people’s convergence or dispersion areas. And then a time series matrix was constructed according to the temporal signatures of these areas. SOM algorithm was selected to cluster the matrix into nine typical human convergence-dispersion patterns. Based on the land use data, we have calculated the percentage of different land use types for each pattern to explain the human convergence-dispersion phenomenon, thus we could understand the relationship between human mobility patterns and urban spatial function. This study helps us to acquire a good knowledge of the daily human convergence and dispersion patterns within different urban functional areas. The findings derived from this study could give us the insights about where and when the convergence and dispersion of people would occur in Shenzhen. This knowledge is helpful for the city planners to improve the urban local planning and makes it more suitable for human mobility applications, such as making targeted adjustments to optimize the urban transportation facilities to improve their service efficiency.
In the process of rapid urbanization, how to effectively protect the quantity and quality of cultivated land is an important scientific proposition. Through constructing Logistic Cellular Automata model (Logistic-CA) for urban expansion and carrying out the simulation and forecast of cultivated land evolution, this paper intend to explore the characteristics and mechanisms of cultivated land evolution under the rapid urban expansion in a case study of Dongguan city in Guangdong province, so as to provide a scientific reference to the sustainable development planning of the city and the protection of cultivated land resources. Firstly, the mechanism of urban expansion and cultivated land evolution is explored through analyzing the conversion relationship between different land use types of Dongguan city in 1998-2013. Based on the result, the optimal factor combination is chosen to define the conversion rule of CA by comparing the simulation results of cultivated land evolution using geographical, economic and policy factors respectively, and the Logistic-CA model is constructed. Finally, in accordance with the general planning of land use in Dongguan city from 2006 to 2020, the evolution of the cultivated land is predicted using Logistic-CA model built based on the optimal factor combination, and the analysis of quantity, quality and spatial patterns is carried out. Simulation results show that 71.96% and 80.86% of the new urban land in Dongguan city directly or indirectly come from the cultivated land in the 2003-2008 and 2008-2013 two periods, and the quantity of the cultivated land supplementation is far less than its loss in the corresponding period. The spatial evolution pattern of the cultivated land has the characteristics that large tracts are turning into fragmentary lands toward the margin, and the fragmentary land parcels gradually disappear. The forecast results show that 8205.41 hectares of the cultivated land will disappear by 2020. At the same time, 5.16% of the top level and 5.27% of the high level cultivated land will disappear.
For the purpose of simulating rainstorm waterlogging scenarios in the urban areas that have specific terrain surface characteristics, a comprehensive methodology derived from the hydrology/hydrodynamic theory and the geographic information system (GIS) is proposed in this paper. Moreover, a modified SCS model is utilized for the runoff producing simulation, while a locality volume equation and a hydrodynamic model are used for runoff converging simulation. Taking the central urban area of Shanghai as an example, rainstorm scenarios with 100-year return period are designed for the simulation. Meanwhile, based on the same runoff producing process, the locality volume equation and hydrodynamic model are used to simulate the waterlogging course respectively. Thereafter, a comparison is made to reveal the distinction of accuracy among the results acquired from these diverse models. The results indicate that: (1) it is easier for the runoff converging calculation to use the locality volume equation, but the results are obviously influenced by the temporal distribution of the rainfall course, especially at the period before the peak, as well as by the intensity, thus this model is more feasible for fast waterlogging simulation if the rainfall pattern is determined in advance. As for the hydrodynamic model, the runoff converging calculation is more complicated, but shows a better performance and higher precision when being used for simulating a longer rainfall process. Furthermore, the results have a closer relationship with the rainfall duration. (2) Specifically, these two models are verified based on the inundation data measured during the typhoon “Matsa”. A comparison between the simulation results and the historical data predicts that, although more or less a deviation is inevitable, the hydrodynamic model performs better in fitting the characteristics of urban rainstorm waterlogging, thus basically it's found more suitable for simulating the waterlogging hazard in the central urban area of Shanghai.
Urban land expansion in mountain area is constrained by the hill-shaped terrain, mountain hazards and some other geographic factors, making it difficult to be expressed by the commonly used land use models, thus the research in this area is relatively inadequate. By modifying the Dyna-CLUE model and combining it with the SDM, the advantages of land allocation in microcosmic aspect and scenario simulation in macroscopic aspect are well developed. Moreover, this method clearly expresses the constraining effect of the geographic constraint factors toward mountainous urban land expansion. Therefore, it provides an effective approach to the scenario simulation of urban land expansion in mountain area. This article takes the upper reaches of Minjiang River as the study area. The mountainous urban land SDM is built based on historical statistical data of the study area and is used to simulate urban land demands under three different developing scenarios, which are slow development, inertial development and fast development. Combining with the modified Dyna-CLUE model, the distributions of urban land from 2011 to 2030 for the corresponding developing scenarios are predicted respectively. The results indicate that, the faster the mountainous town develops, the faster it comes up to the upper limit of the geographic restricted filed for downtown areas, then it will expand toward both ends along the intermountain plain. The arable land is influenced by the urban land expansion much more evidently than the other land use types. The closer it is to the downtown areas, the more it is influenced. As the urban land expansion reaches a higher level, its influence to eco-environment is getting more intense. The simulation result of the model can offer effective technical support to mountainous urban planning, estimating the environmental problem caused by urban expansion and making relevant policy.
To strengthen the protection of the rare animal species of Syrmaticus humiae, we assessed the habitat suitability of Syrmaticus humiae in Jinzhongshan Nature Reserve. Based on the field survey data, we selected the vegetation type, vegetation coverage, altitude and slope as the evaluation factors and built the habitat suitability model using GIS technology. The results showed that: (1) the deciduous broadleaved forest area with the altitude of 1000-1850 m, the slope of 5-25o and the vegetation coverage higher than 70% are the most suitable habitat for Syrmaticus humiae, so these areas should be taken as the key protection habitat; (2) there are a total of 25 kinds of habitat types for Syrmaticus humiae to settle, however, considering the efficiency and cost of the conservation, 15 kinds among the habitat types with bigger area are selected as the potential habitat, and 54.31% of the potential habitat is distributed in the core zone of the nature reserve, 15.75% of the potential habitat is distributed in the buffer zone, and 29.94% of the potential habitat is distributed in the experiment zone; (3) the assessment of the habitat suitability showed that the area of the suitable habitat is about 74 km2 and takes almost 36.30% of the total area of Jinzhongshan Nature Reserve. Based on the habit assessment of Syrmaticus humiae, a series of conservation strategy was proposed respectively.
Since its launch in 2009, the WorldView-2 satellite has provided a large amount of high-quality images to the world. The WorldView-2 has two near infrared spectral bands NIR1 and NIR2, which make it different from the numerous other previously launched satellite sensor data. Up to date, however, the differences between the two NIR bands in applications are not clear. Therefore, taking Pinus Massoniana forest in the Changting county of Fujian, China as an example, this paper utilized the two NIR bands respectively to compute three vegetation indices, which are the Normalized Difference Vegetation Index (NDVI), the Atmospherically Resistant Vegetation Index (ARVI), and the Normalized Difference Mountain Vegetation Index (NDMVI), to explore the differences between the two bands in the retrieval of vegetation information. The results show that the accuracy of the extracted Pinus Massoniana information using the indices derived from the NIR1 band is always higher than that derived from the NIR2, and the NIR1-derived indices can gain more vegetation information than the NIR2-derived indices, which is 8.0% higher in NDVI, 12.3% higher in ARVI, and 7.3% higher in NDMVI, respectively. As for the retrieval of fractional vegetation coverage, NIR1 also show a higher accuracy than NIR2, as it shows a higher degree of agreement and lower root mean square error when compared with the actual fractional vegetation coverage. The performance differences between the two NIR bands are caused by the higher reflection rate of Pinus Massoniana in NIR1 wavelength than in the NIR2 spectral range.
Urban green space is an important element of ecological networks. Conservation policies urge the protection of urban green space in cities possessed by dense buildings and focus on the improvement of intercommunity relationships among the green space plots within different areas. Urban green space forms an indispensable part of urban ecosystems. Quantifying the urban green space is of substantial importance for urban planning and development. In order to solve the problem of measuring the proximity of residents to green space (PRG), this paper proposed a method of urban green index (UGI) based on multi-spectral remote sensing data and Lidar data (LiDAR), which provide the accurate information of urban buildings and green spaces. In this study, the urban green index of the central pixel is developed based on calculating the area of urban green space and a fixed window area. The results show that the urban green index can be an effective method to measure the proximity of residents to green space and its spatial distribution characteristics. It avoids the edge effects generated by grid method, overcomes the discontinuity problem occurred in the buffer space, and could obtain the urban green index of any point in the region. At the same time, the newly constructed model can be used to identify the key protection regions that will have typical demonstration effects. The input parameters of the model can be obtained from the remote sensing images, which are easier to obtain than from the field measurements. Therefore, it could be considered to be a new method for studying the urban green space and could offer effective technical assistances to urban planning and management. The quantitative evaluation of the urban green space will provide the scientific support to urban greening and urban environmental protection. This study exploits the advantages of multi-source remote sensing data with high ground resolution in extracting building and vegetation information.
The quality assessment of remote sensing land cover data is the premise and guarantee of using it reasonably, and it's helpful to improve remote sensing mapping methods. In this study, the 1:100000 land use data of Taoyuan county in 2010 was used as the reference data to validate four different resolution land cover data: RapidEye_5 m, FROM_GLC (30 m), GlobCover2009 (300 m) and MODIS_V005 (500 m). We evaluated the four different resolution land cover data from three aspects, including area relevance and consistency, spatial consistency, and window analysis based on the conversion of classification systems. The results show that: the overall accuracy of RapidEye_5 m data is the highest, MODIS_V005 and FROM_GLC are intermediate, and GlobCover2009 data is relatively lower. The land cover data with higher resolution have a certain superiority for classifications of residence, transportation land, water and other fine material, and the area relevance and the overall consistency of primary types is higher than secondary types. Producer accuracy and user accuracy of the four types of land cover data in crop land, woodland and water is better, while in the construction land and other unused land is lower. Moreover, the spatial consistency of FROM_GLC and MODIS_V005 data is poor in the shrub grassland. The spatial consistency of the four different resolution land cover data is better in the flat areas. Confusion occurred mainly among shrub grassland, woodland and crop land. With the increase of resolution for land cover data, more and more land cover types can be distinguished. The number of land cover types separated from RapidEye_5 m and FROM_GLC (30 m) land cover data focuses on the range of 7-16, in contrast, data with lower resolution focuses on the range of 1-5. Furthermore, data with higher resolution are better to distinguish the grand objects in hilly and mountainous areas.
By taking MODIS daily land surface temperature (LST) data and AMSR-E brightness temperature (BT) data from 2007 to 2008 as the input, combining with the land cover type data, the statistics and analysis of the relativity between MODIS_LST and AMSR-E_BT in different land cover types, channels and polarization ways are produced. Based on the International Geosphere-Biosphere Program (IGBP) vegetation classification scheme, land cover data is re-classified into seven types, including water, forest land, grass land, farmland, urban land, desert land and other land cover types. The statistical result shows that the correlation is apparent between MODIS_LST and AMSR-E_BT in 18.7 GHz, 23.8 GHz and 36.5 GHz channel, and it reveals a higher correlation in the vertical channel compared to the horizontal channel. Moreover, this paper finds out that the microwave channel of AMSR-E_BT, which has the highest relativity with MODIS-LST, is different with respect to different land cover types. In addition, by considering the impact of mixed pixel, this paper analyzes the correlation between MODIS_LST and AMSR-E_BT for 25 types of land cover type combinations. It is inferred that the correlation declines as the quantity of land cover types in the single mixed pixel increases. Finally, according to different land cover type combinations, the inversion model is established by adopting the multivariate linear regression method, and this model has been applied to inverse MODIS_LST in a part of the study area. Inversion results reveal that the error is limited in ±3.15 K in average, and the inversion accuracy is raised by 1.5 K successfully in comparison with the inversion model without considering land cover type combination. However, there are some problems with MODIS land surface temperature inversion by using AMSR-E brightness temperature, such as the space resolution variation between MODIS LST and AMSR-E_BT, changes of land cover type with changing seasons and the influence of relative humidity of land cover on the retrieval accuracy. Therefore, selecting land surface bright temperature with a high quality and space resolution, considering season variations and classification accuracy of land cover type factors are future research directions.
