林业有害生物踏查线路地理信息图的制作

结合第三次全国林业有害生物普查,通过实地踏查,构建了基于ArcGIS 10.2软件平台及相关技术的一种操作性强的有害生物踏查地理信息图的制作方案。本方案可以有效降低踏查人员外业工作量,同时提高外业踏查和内业整理的工作效率。

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.

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.

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.

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.

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.

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.

Heavy Metal Distribution Map in Soil by Using GIS Techniques

A detailed investigation was conducted to understand the contamination characteristics and distributions of heavy metal pollution in terms of contributions of the heavy metal concentrations as mg/kg ofCd, Cr, Cu, Ni, Zn, Pb, Fe and Mn in the urban soil in Eskisehir city center. The amount of these heavy metals were determined from 15 soil sample points collected within urban area and every sample point included 6 separated samples for chemical analyses. The results indicated that concentration values of all metals except Ni and Cr in soils were below the risky limit pollution values which are recommended by Turkey Ministry of Environment and Forestry in some sample points. Spatial distribution maps were created and recoded, in terms of these heavy metals concentrations as contribution to heavy metal pollution in soil, through Geographical Information Systems techniques. As a result, risky areas were modeled in terms of contamination of heavy metal and it is shown that, every different risky area can be interpreted based on buildings in city center quickly and easily.

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.

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.

Land-Cover Change Monitoring in Obuasi, Ghana： An Integration of Earth Observation, Geoinformation Systems and Stochastic Modelling

For over twenty years, Obuasi Municipality, Ghana, has experienced land-cover change arising from gold mining and urbanisation. This project quantified the land-cover changes that have taken place and projected likely future land-cover. An integration of EO （earth observation）, GIS （geographical information science） and Stochastic Modelling was examined. Post-classification Change Detection employed Landsat TM or ETM＋ images in 1986, 2002 and 2008. Subsequently, Markov Chain Analysis projected the land-cover distribution for 2020. Seven broad land-use and land-cover classes were identified and mapped, namely： built-up areas, mine sites tailing ponds barren land forestland farmland and rangeland. The results obtained for the 2008 to 2020 projection revealed a continuous expansion of built-up areas （1.63%）, mine sites （0.89%） and farmland （3.4%）, and a reduction of forestland （4.17%） and rangeland （2.59%）. Despite the advent of very high resolution satellite imagery, this use of EO and GIS technology focussed on low-cost and lower resolution satellite imagery, coupled with Markov Modelling and was found to be beneficial in describing and analysing land-cover change processes in the study area, and was hence potentially useful for strategic planning purposes.

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.

Groundwater Quality Assessment for an Indian Urban Habitat： A GIS Approach

Groundwater is an essential source of drinking water for many Indian urban habitats. Large numbers of people consume ground water instead of municipal tap water due to contamination of tap water. Groundwater is extracted from thousands of bore wells, and used for potable purpose without proper testing and treatment. This paper describes a groundwater quality monitoring strategy and database model developed for Gulbarga city, located in Karnataka, India. Sampling wells are selected one each in 55 wards of the city corporation having easy access for regular sampling. Various attributes of sampling wells including their spatial coordinates, location address and a photograph are registered for ready recognition on site. Water samples are collected and analyzed for various physico-chemical parameters. Spatial coordinates and levels of sampling points are measured on site using a hand held GPS instrument. Gulbarga city map is digitized. A GIS database of the measured spatial and water quality data is developed using ArcGIS Desktop 9.3, and ground water quality maps are prepared which may serve as useful tools for developing policy, and regulatory mechanism for sustainable groundwater use.

Detecting Forest Fire Prone Areas Using Object-Based Image Analysis and GIS Techniques： A Case Study in Kayer Khola, Nepal

Every year during summer, natural and human-induced forest fires threaten the environment in the largely forested areas of the Himalayan region and the local population living near these forests. Nepal, with its multitude of forests, is one of the most forest fire-prone areas in the region. This study examines the possibility of averting forest fires, minimizing their frequency and the damage they cause, through advanced mapping of forest fire prone areas using a VHSR （very-high spatial resolution） satellite image of GeoEye-1, DEM （digital elevation data） created from topographic maps and additional data layers （e.g., precipitation, settlements）. The study was conducted in Kayer Khola, Chitwan district, Nepal. The classification of the satellite image has been performed using OBIA （object-based image analysis） techniques taking into account spectral, spatial and context information as well as hierarchical properties. The land cover classification result was thereafter combined with additional data in ArcGIS, where the input layers were reclassified and all classes of the input layers ranked according to their proneness to forest fires. Fire prone areas were delineated in five classes ranging from very high to very low. The study revealed that 82% of fires occur in forest areas. This case study in Kayer Khola shows that OBIA and GIS modeling techniques can be used to successfully identify forest fire-prone areas. The mapping of forest fire-prone areas will enable forest departments in countries of the Himalayan region to delineate forest fire prone areas, which can guide the forest departments set up appropriate fire-fighting infrastructure in these areas and thus help, minimize or avert forest fires.

Elemental Analysis of Soil Phosphorus Neighborhoods Using SEM, Spectral Mapping and GIS

The utility of GIS （geographic information system） methods and spatial statistical analysis on spectral maps of sediment samples were examined. Detailed elemental maps are often constructed using energy dispersive X-ray techniques and SEM （scanning electron microscopy）. The elemental neighborhood associations of a single element, P （phosphorus）, were quantified at a magnification of 3,000 ×. For each of the 170,000 pixels on the images which displayed a strong P concentration, neighborhoods from 0.1μm^2 to 12 μm^2 were examined for associated elemental concentrations. PCA （principal component analysis） revealed two significant neighborhood types associated with P in samples of pH 4, and three neighborhood types at pH 8. These neighborhoods corresponded to Mg-P associations commonly found to be chemically prevalent in river sediments impacted by agricultural operations. Discriminant analysis showed that the greatest accuracy in predicting sample pH could be achieved by using a neighborhood size of 12 ~m2. Potassium at relatively large neighborhood sizes was the element most significant in predicting pH. While many of the chemical associations in close proximity to P could be predicted and explained through mineral solubility, spatial analysis provided some interesting insights into the structure of the samples. Results also indicted differences in the spatial scale associated with different processes.

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.