地理图象信息系统的判读与应用（三）

等值线图的判读与应用。常见的等值线图有等高线图、等深线图、等温线图、等压线图、等降水量线图、等震线图、等盐度线图、等太阳辐射量线图、等PH值线图等。等值线图的共同特征是相邻等值线的数值差相等，等于等值距，有时相邻两条等值线数值相等，数值差为零；

地理图象信息系统的判读与应用（一）

一、地理分布图的判读与应用 地理分布图是反映地理事物空间分布及其规律的重要专题地图。由于地理研究对象上的广阔性，这就要求我们将地理分布对象同它所处的空间位置和空间分布联系起来进行思维，因此，阅读地理分布图是培养和发展地理空间思维的重要工具。

地理图象信息系统的判读与应用（二）

景观图反映的是某一特定区域内的自然和人文景象，一般分为自然景观(火山喷发、草场、雨林等)和人文景观(如城市、农田、村落等)。景观图使人身临其境，不但加强了直观效果，而且在一定程度上弥补了文字语言描述的不足，它与一般地图的不同之处在于：它不是用符号表示地理事物，而是用画面直接表示地理事物，这就要求具有直接通过画面图象解译地理知识的能力。

配电网地理信息管理系统的应用分析

配电网地理信息管理系统将配电网与地理信息系统有效地结合在一起,具有图形编辑与管理、地理图综合查询、系统分析与管理、系统资源扩展等功能,能正确、全面、及时地获取电力企业的各种资源信息,使得对电力线路的管理方便快捷,既优化了管理功能,又提高了工作效率。

SYSTEM FOR AUTOMATIC GENERALIZATION OF TOPOGRAPHIC MAPS

With the construction of spatial data infi＇astructure, automated topographic map generalization becomes an indispensable component in the community of cartography and geographic information science. This paper describes a topographic map generalization system recently developed by the authors. The system has the following characteristics： 1） taking advantage of three levels of automation, i.e. fully automated generalization, batch generalization, and interactive generalization, to undertake two types of processes, i.e. intelligent inference process and repetitive operation process in generalization; 2） making use of two kinds of sources for generalizing rule library, i.e. written specifications and cartographers＇ experiences, to define a six-element structure to describe the rules; 3） employing a hierarchical structure for map databases, logically and physically; 4） employing a grid indexing technique and undo/redo operation to improve database retrieval and object generalization efficiency. Two examples of topographic map generalization are given to demonstrate the system. It reveals that the system works well. In fact, this system has been used for a number of projects and it has been found that a great improvement in efficiency compared with traditional map general- ization process can be achieved.

Spatial/temporal indexing and information visualization genre for environmental digital libraries

Protecting and preserving our environmental systems require the ability to understand the spatio-temporal distri- bution of soils, parent material, topography, and land cover as well as the effects of human activities on ecosystems. Space-time modelling of ecosystems in an environmental digital library is essential for visualizing past, present, and future impacts of changes occurring within such landscapes (e.g., shift in land use practices). In this paper, we describe three novel features, spa- tio-temporal indexing, visualization, and geostatistical genre, for the environmental digital library, Environmental Visualization and Geographic Enterprise System (ENVISAGE), currently in progress at the University of Florida.

Discussion research of digital construction of mine

Analyzed and compared with some digitizeed mine build state first.Secondly analyzed opportunity and challenge that the Chinese mine faces,and pointed out certainty and necessity of building digitization of mine,Summarized the present task that charac- teristic,DM,MGIS of the digital mine develop and construct and employ finally,and carry on the summary to structure and function of the component mine integrated information system.

Comprehensive assessment method for environmental impact of railway based on geographic information system

By integrating the merits of the map overlay method and the geographic information system (GIS), a GIS based map overlay method was developed to analyze comprehensively the environmental vulnerability around railway and its impact on the environment, which is adapted for the comprehensive assessment of railway environmental impact and the optimization of railway alignments. The assessment process of the GIS based map overlay method was presented, which includes deciding the system structure and weights of assessment factors, making environmental vulnerability grade maps, and evaluating the alternative alignments comprehensively to obtain the best one. With the GIS functions of spatial analysis, such as overlay analysis and buffer analysis, and functions of handling attribute data, the GIS based map overlay method overcomes the shortcomings of the existing map overlay method and the conclusion is more reasonable. In the end, a detailed case study was illustrated to verify the efficiency of the method.

The Demographic Impact on Credit Scores＂ Evidence From Statistical Methods and Geographic Information Systems （GIS） Mapping

Average credit scores for people in the United States （US） differ from state to state. Some states have high, and some states have low average credit scores. Since lenders and employers use credit scores to make loan and employment decisions, people living in states where average credit scores are high should experience the benefits of living where credit scores tend to allow more favorable loan and employment decisions. Although credit scores are the direct result of credit histories, credit histories may be impacted by demographic factors. If the demographic factors that impact credit histories are identified, ways to improve credit scores are likely to be discovered and available to people and state government policymakers. This study looks for demographic factors to indirectly explain the average credit scores for people living in each state of the US. The methodology includes statistical analyses and geographic information systems （GIS） mapping. Statistical analyses provide evidence to suggest that state average credit scores are explained by the demographic factors of education, family, income, and health. GIS mapping reveals clusters of states with similar demographics and credit scores.

Navigation System for Foreign Tourists in Japan

The present study aimed to design, develop, operate and evaluate a sightseeing navigation system in order to support foreign tourists＇ efficient acquisition of sightseeing spot information in Japanese urban tourist areas, about which a variety of information is transmitted, by enabling information to be accumulated, shared and recommended. The system was developed by integrating Web-GIS （Geographic Information Systems）, SNS （Social Networking Services） as well as the recommendation system into a single system. The system used the non-language information such as signs, marks and pictograms in addition to English information, and displayed sightseeing spot information and conduct navigation on 2D and 3D digital maps of the Web-GIS. Additionally, the system was operated for two weeks in the central part of Yokohama city in Kanagawa Prefecture, Japan, and the total number of users was 54. Based on the results of the web questionnaire survey, all of the specific functions are highly evaluated, and the usefulness of the system when sightseeing was excellent. From the results of the access analysis of users＇ log data, it is evident that it can be said that the system was mainly used before sightseeing and users confirm their favorite sightseeing spots and made their tour planning in advance, using 2D and 3D digital maps.

Application of graph overlay method to environmental impact assessment of railway noise

The graph overlay method is used to evaluate the noise impact of route alignment and the results can serve as a reference for the route alignment optimal selection. The geographic information system(GIS), with its powerful function of handling attribute data and spatial analysis, is adopted to calculate the noise comprehensive impact area of each alignment. With the graph overlay method, the noise vulnerability and noise impact distribution are both taken into account in the noise impact assessment of route alignment. With GIS, the efficiency of work and the reliability of result are greatly improved. By a combination of them, the noise impact on environment is fully presented in a visual way and the assessment result has vital value in route alignment optimal selection. A detailed case study is illustrated and the efficiency of the method is verified.

STUDY ON THE SUBSIDING LAND EXTRACTION FROM LANDSAT TM IMAGE SUPPORTED BY GIS AND DOMAIN KNOWLEDGE

The subsiding land can be extracted from Remote Sensing image based on itsspectral and spatial features. The features of subsiding land caused by raining, especially its RSinformation features and relative knowledge are proposed. Three methods can be used to extractsubsiding land from RS image. The first is to categorize the region into different blocks (orlayers) according to their features and apply corresponding strategies for each block, the second isto identify the changeable region based on GIS firstly and then to classify those regions, and thethird is to post-process the classified image by traditional methods or ANN (Artificial NeuralNetwork) methods based on domain knowledge and GIS. Two direct extraction methods are introducedalso. One is the extraction based on the water accumulating property of subsiding land, and theother is based on the dynamic change of land cover in subsiding land.

RS-and-GIS-Supported Forecast of Grassland Degradation in Southwest Songnen Plain by Markov Model

By taking Daan city in Jilin Province as a research object and by using TM image in 1989 and ETM + image in 2001 from American LANDSAT satellite,all kinds of maps and documentation,information of grassland,saline-alkalized land,cropland,water area and forestland is extracted by man-computer interactive interpretation method with ArcView and ArcInfo GIS software, and statistics data is acquired. On the basis of this the changing trend of land use types in the next ten years is forecasted and analyzed with Markov model. The results indicate that the problem of grassland degradation in the study area is quite serious.

Semi-automatic Building Extraction from Quickbird Imagery

Automatic extraction features and buildings in particular from digital images is one of the most complex and challenging task faced by computer vision and photogrammetric communities. Extracted buildings are required for varieties of applications including urban planning, creation of GIS databases and development of urban city models for taxation. For decades, extraction of features has been done by photogrammetric methods using stereo plotters and digital work stations. Photogrammetric methods are tedious, manually operated and require well-trained personnel. In recent years, there has been emergence of high-resolution space borne images, which have disclosed a large number of new opportunities for medium and large-scale topographic mapping. In this paper, a semi-automatic method is introduced to extract buildings in planned and informal settlements in urban areas from high resolution imagery. The proposed method uses modified snakes model and radial casting algorithm to initialize snakes contours and refinement of building outlines. The extraction rate is 91 percent as demonstrated by examples over selected test areas. The potential, limitations and future work is discussed.

Mapping Deciduous Broad-leaved Forested Swamps Using ALOS/Palsar Data

Accurate, updated information on the distribution of wetlands is essential for estimating net fluxes of greenhouse gases and for effectively protecting and managing wetlands. Because of their complex community structure and rich surface vegetation, deciduous broad-leaved forested swamps are considered to be one of the most difficult types of wetland to classify. In this research, with the support of remote sensing and geographic information system, multi-temporal radar images L-Palsar were used initially to extract the forest hydrological layer and phenology phase change layer as two variables through image analysis. Second, based on the environmental characteristics of forested swamps, three decision tree classifiers derived from the two variables were constructed to explore effective methods to identify deciduous broad-leaved forested swamps. Third, this study focused on analyzing the classification process between flat-forests, which are the most severely disturbed elements, and forested swamps. Finally, the application of the decision tree model will be discussed. The results showed that: 1) L-HH band(a L band with wavelength of 0–235 m in HH polarization mode; HH means Synthetic Aperture Radars transmit pulses in horizontal polarization and receive in horizontal polarization) in the leaf-off season is shown to be capable of detecting hydrologic conditions beneath the forest; 2) the accuracy of the classification(forested swamp and forest plat) was 81.5% based on hydrologic features, and 83.5% was achieved by combining hydrologic features and phenology response features, which indicated that hydrological characteristics under the forest played a key role. The HHOJ(refers to the band created by the subtraction with HH band in October and HH band in July) achieved by multi-temporal radar images did improve the classification accuracy, but not significantly, and more leaf-off radar images may be more efficient than multi-seasonal radar images for inland forested swamp mapping; 3) the lower separability between forested swamps dominated by vegetated surfaces and forest plat covered with litter was the main cause of the uncertainty in classification, which led to misleading interpretations of the pixel-based classification. Finally, through the analysis with kappa coefficients, it was shown that the value of the intersection point was an ideal choice for the variable.

Classification Method Research to Remote Sensing Images

With rapid development of remote sensing technology, the resolution of remote sensing images is increasingly improved; then people can extract more useful data and information from these images. Thus, an important information extraction method from remote sensing images - image classification, becomes more and more important. Based on phenopthase and band composition characteristics, this paper firstly discusses the important role of background parameters in remote sensing images classification; then based on geographical infomation system technology, the computerized automatic classification to high-medium-low-yield croplands in Dingxiang County of Shanxi Province in rotate sensing images has been carried out by using eompound layers classification method of multi-thematic information; compared the classification result to the visual interpretation results, the accuracy increases from 70% to above 90%.

Research on management of coal bed methane warehousing and transportation based on GIS

At present Coal Bed Methane （CBM） has become the important part of clean energy in China. and will optimize the energy structure in China unceasingly. However, warehousing and transportation of CBM become one of the core factors that restrain its exploitation and utilization at present, due to the space-time character of natural deposit and modem utilization of CBM. In this paper, according to the character of CBM and the expanding trend of its utilization, the necessity of constructing the CBM＇s warehousing and transportation management system demonstrated. Index system that influence CBM＇s warehousing and transportation is established. And CBM＇s warehousing and transportation model is established by Voronoi diagram. In light of above research, CBM＇s warehousing and transportation management system based on Geography Information System （GIS） is designed, Using this system, CBM＇s warehousing and allocation center in one mining area is optimized. Research shows that to reinforce CBM＇s warehousing and transportation management is one of the key factors for coordinating the development of its development and utilization, thereby ensuring its sustainable development and utilization.

Application of Remote Sensing and GIS to the Study of Land Use/Cover Change and Urbanization Expansion in Basrah Province, Southern Iraq

In recent years, land use/cover dynamic change has become a key subject that needs to be dealt with in the study of global environmental change. In this paper, remote sensing and geographic information systems (GIS) are integrated to monitor, map, and quantify the land use/cover change in the southern part of Iraq (Basrah Province was taken as a case) by using a 1:250 000 mapping scale. Remote sensing and GIS software were used to classify Landsat TM in 1990 and Landsat ETM+ in 2003 imagery into five land use and land cover (LULC) classes: vegetation, sand, urban area, unused land, and water bodies. Supervised classification and normalized difference build-up index (NDBI) were used respectively to retrieve its urban boundary. An accuracy assessment was performed on the 2003 LULC map to determine the reliability of the map. Finally, GIS software was used to quantify and illustrate the various LULC conversions that took place over the 13-year span of time. Results showed that the urban area had increased by the rate of 1.2% per year, with area expansion from 3 299.1 km2 in 1990 to 3 794.9 km2 in 2003. Large vegetation area in the north and southeast were converted into urban construction land. The land use/cover changes of Basrah Province were mainly caused by rapid development of the urban economy and population immigration from the countryside. In addition, the former government policy of "returning farmland to transportation and huge expansion in military camps" was the major driving force for vegetation land change. The paper concludes that remote sensing and GIS can be used to create LULC maps. It also notes that the maps generated can be used to delineate the changes that take place over time.

A Novel Evolutionary Genetic Optimization-Based Adaptive Neuro-Fuzzy Inference System and Geographical Information Systems Predict and Map Soil Organic Carbon Stocks Across an Afromontane Landscape

Soil organic carbon （SOC） pool has the potential to mitigate or enhance climate change by either acting as a sink, or a source of atmospheric carbon dioxide （CO2） and also plays a fundamental role in the health and proper functioning of soils to sustain life on Earth. As such, the objective of this study was to investigate the applicability of a novel evolutionary genetic optimization-based adaptive neuro-fuzzy inference system （ANFIS-EG） in predicting and mapping the spatial patterns of SOC stocks in the Eastern Mau Forest Reserve, Kenya. Field measurements and auxiliary data reflecting the soil-forming factors were used to design an ANFIS-EG model, which was then implemented to predict and map the areal differentiation of SOC stocks in the Eastern Mau Forest Reserve. This was achieved with a reasonable level of uncertainty （i.e., root mean square error of 15.07 Mg C ha-l）, hence demonstrating the applicability of the ANFIS-EG in SOC mapping studies. There is potential for improving the model performance, as indicated by the current ratio of performance to deviation （1.6）. The mapping also revealed marginally higher SOC stocks in the forested ecosystems （i.e., an average of 109.78 M C ha-1） than in the aro-ecosvstems （i.e., an average of 95.9 Mg C ha-l）.