基于三维GIS的地下电力管线管理系统的设计与实现

电力企业的输配电方式有架空线路和地下电力电缆及管线,它们负责为千家万户传送光明和能量,随着城市电缆化率的提升,地下电缆已变成电力公司重要的基础设施之一,是其赖以生存和发展的"生命线"。本文借助3S技术和传统测绘手段,采集地下电力管网基础数据,开发三维电力管线管理系统,对电缆数据录入建模、绘制各种专题图,实现地下电力管线从规划到建设、从运行到维护的全周期安全管理。     

Application of Earth Remote Sensing and GIS in Mapping Land Cover Patterns in Kinangop Division, Kenya

<正>Land cover is a fundamental variable that links many facets of the natural environment and a key driver of global environmental change.Alterations in its status can have significant ramifications at local,regional and global levels.Hence,it is imperative to map land cover at a range of spatial and temporal scales with a view to understanding the inherent patterns for effective characterization,prediction and management of the potential environmental impacts.This paper presents the results of an effort to map land cover patterns in Kinangop division,Kenya,using geospatial tools.This is a geographic locality that has experienced rapid land use transformations since Kenya's independence culminating in uncontrolled land cover changes and loss of biodiversity.The changes in land use/cover constrain the natural resource base and presuppose availability of quantitative and spatially explicit land cover data for understanding the inherent patterns and facilitating specific and multi-purpose land use planning and management.As such,the study had two objectives viz.(i) mapping the spatial patterns of land cover in Kinangop using remote sensing and GIS and;(ii) evaluating the quality of the resultant land cover map.ASTER satellite imagery acquired in January 23,2007 was procured and field data gathered between September l0 and October 16,2007.The latter were used for training the maximum likelihood classifier and validating the resultant land cover map.The land cover classification yielded 5 classes,overall accuracy of 83.5%and kappa statistic of 0.79,which conforms to the acceptable standards of land cover mapping. This qualifies its application in environmental decision-making and manifests the utility of geospatial techniques in mapping land resources.     

月球遥感制图回顾与展望

对月球探测任务、月球遥感制图技术与产品进行综述。从1958年开始,全世界已开展126次(其中70次成功)月球探测工程任务,其中月球遥感制图是其必需的基础性工作。由于月球环境的特殊性,其遥感制图技术与对地观测制图相比具有很大的挑战和更大的难度。目前,中国嫦娥二号轨道器获取的7 m分辨率立体影像是覆盖全月球分辨率最高的立体影像数据,美国月球侦察轨道器LRO任务的激光雷达高度计LOLA数据是精度和密度最高的激光测高数据,LRO NAC影像的分辨率最高(0.5—2 m)但未覆盖全球。在各个探测任务中,基于月球遥感数据和摄影测量技术,已经制作了大量的全球及区域的影像拼图、正射影像图和数字高程模型等制图产品。对月球遥感制图技术发展进行展望,探讨了利用国际多探测任务数据建立新一代控制网和进行精细制图的必要性及技术思路。     

Role of satellite remote sensing in land system mapping,land resources inventory and land use planning: A sample study of kemang river basin,Arunachal Pradesh

Here an attempt has been made to highlight the importance of satellite remote sensing in land system mapping, land resources inventory and land use planning of a sample river basin (in Arunachal Pradesh) covering an area of 10,186 sq. km. The (Kemang) river basin has been divided intofour land systems viz : structural, denudational, piedmont and fluvial. Each system has been analysed with respect toeight land water-land use (resource) parameters for proper land use and environmental management of the river basin. A tentative‘productivity/development strategy ranking’ is also given for optimum planning of the basin.     

Predictive Analysis for Vegetation Biomass Assessment in Western Ghat Region (WG) Using Geospatial Techniques

Forests play a critical role in ecological functioning, global warming and climate change through its unique potential to capture and hold carbon (C). Biomass is one of the indicator of the status of forests hence accurate assessment and biomass mapping is important for sustainable forest management. The objectives of this study is to estimate above ground biomass (AGB) from field inventory data and to map AGB combining field inventory data, remote sensing and geo-statistical model. In the present study stratified random sampling were used for estimation of biomass in which 59 plots were laid down in different homogenous strata depending on the NDVI values for the region of Maharashtra Western Ghats. The above ground biomass from field ranged from 0.05 to 271 t-dry wt ha^?1 in which trees added maximum towards total biomass followed by shrubs and herbs. This paper evaluates the best vegetation indices to estimate biomass. This study was carried out by using Landsat TM satellite data and field inventory data in the Ratnagiri district of Maharashtra, India. A significant correlation was observed between biomass and vegetation indices. The best fit regression equation developed from field above ground biomass and NDVI with R² value of 0.61 was used for spectral modeling to estimate the geospatial distribution of AGB in the entire region. The results of spatial predictions Geostatistical technique and remotely sensed data as auxiliary variables were compared using statistical error methods. This study employed Mean error, Root-Mean-Square error, Average Standard error and Root-Mean Square Standardized error. The ME, RMSE, Average Standard error and Root-Mean Square Standardized error was 0.078, 8.032, 7.982 and 0.967 respectively. The results showed that cokriging technique is one of the geostatistical method for spatial predictions of biomass in the studied region. The present study revealed that remote sensing technique combined with field sampling provides quick and reliable estimates of above ground biomass and carbon pool and can be used as baseline information for further temporal studies of biomass status of the region and in planning of forest and natural resources management.     

Fuzzy Classification for Mapping Invasive Species from Multispectral Imagery

Vegetation maps are essential tools for planning and evaluation in nature conservation. To a large extend, management objectives can be defined in terms of vegetation attributes. Vegetation maps are frequently used in conservation planning and evaluation. Nowadays, remote sensing is one of the most important sources of vegetation cover classifications at different scales. In this paper, the usefulness of moderate resolution images for invasive species Cirsium arvense and Stachys byzanthina mapping at local scale is evaluated. A fuzzy classification approach is tested for improved discrimination of invasive species. The study was carried out in Vazroud rangelands located in the Mazandaran province of Iran. In this study among the analysed Z-score for uncertainty map creation is found that 0.9, 1.0 for TM image and 1.1 for IRS image in normalized are the best based on known attributes of the study area.     

A SEMINAR ON GEOGRAPHIC INFORMATION SYSTEMS

A paper describing the proceedings of a seminar on geographic information systems sponsored jointly by Tartu University and the USSR Academy of Sciences reveals major thrusts of Soviet research in this emerging field. Topics presented in the seminar include basic types of geographic information systems, the roles played by microcomputers and data base management systems in GIS, use of data from topographic maps in GIS, terrain modeling, remote sensing and GIS, GIS development based on Soviet-produced hardware and software, and the application of information systems in the solution of specific resource management problems. Translated from: Izvestiya AN SSSR, seriya geograficheskaya, 1986, No. 1, pp. 136–138.     

GIS- and RS-based spatial decision support: structure of a spatial environmental information system (SEIS)

Abstract

The development of spatial decision support for environmental resource management, e.g. forest and agroecosystem management, biodiversity conservation, or hydrological planning, started in the 1980s and was the focus of many research groups in the 1990s. The combined availability of spatial data and communication, computing, positioning, geographic information system (GIS)- and remote sensing (RS)-technologies has been responsible for the implementation of complex SDSS since the late 1990s. The regional GIS-based modelling of environmental resources, and therefore ecosystems in general, requires setting-up an extensive geo and model database. Spatial data on topography, soil, climate, land use, hydrology, flora, fauna and anthropogenic activities have to be available. Therefore, GIS- and RS-technologies are of central importance for spatial data handling and analysis. In this context, the structure of spatial environmental information systems (SEIS) is introduced. In SEIS, the input data for environmental resource management are organised in at least seven sub-information systems: base geodata information system (BGDIS), climate information system (CIS), soil information system (SIS), land use information system (LUIS), hydrological information system (HIS), spatial/temporal biodiversity information system (STBIS), forest/agricultural management information system (FAMIS). The major tasks of a SEIS are to (i) provide environmental resource information on a regional level, (ii) analyse the impact of anthropogenic activities and (iii) simulate scenarios of different impacts.     

现代技术在土地利用总体规划实施中的应用

土地利用总体规划是一项复杂的系统工程,现代技术的支持为规划工作的开展提供了便利。文章说明了现代技术体系的特征,结合实例阐述了遥感技术、全球定位系统技术、地理信息系统技术、网络技术在土地利用总体规划实施中的应用状况,并借鉴美国土地资源网络公示模式,提出了土地利用总体规划成果网络公示构想。     

Geographical model for precise agriculture monitoring with real-time remote sensing

This paper presents a remote sensing model for crop monitoring that was developed by the authors in a multi-year study. It also presents two experiments conducted for testing a newly developed application. The model combines remote sensing models using mapping of the spatial distribution of vegetation in an agricultural field, with precision agricultural models that maximize the output (yield) while minimizing the input (cost). This combination enables one to operate a monitoring and management process that includes every sub-unit of the field using remote sensing mapping.The model consists of five steps: (1) Preparing information layers that map the crop-affecting elements, e.g. irrigation and topography; (2) Collecting spectral and plant data simultaneously; (3) Processing and analyzing the data in order to prepare vegetation maps; (4) Decision-making in accordance with the above-mentioned maps or with predicted-yield maps; and (5) Quality control.The experiments showed that although the results were not statistically significant, the application of the proposed model enables one to draw recommendations within 45 h, and that remote sensing monitoring results in more benefits than do traditional control methods. The quality control was not ideal, due to the narrow range of the spectrum used in the remote sensing monitoring.     

Use of cartographic images by expert and novice field geologists in planning fieldwork routes

Topographic maps and aerial photographs are particularly useful when geoscientists are faced with fieldwork tasks such as selecting paths for observation, establishing sampling schemes, or defining field regions. These types of images are crucial in bedrock geologic mapping, a cognitively complex field-based problem-solving task. Geologic mapping requires the geologist to correctly identify rock types and three-dimensional bedrock structures from often partial or poor-quality outcrop data while navigating through unfamiliar terrain. This paper compares the walked routes of novice to expert geologists working in the field (n = 66) with the results of a route planning and navigation survey of a similar population of geologists (n = 77). Results show clearly that those geologists with previous mapping experience make quick and decisive determinations about field areas from available imagery and maps, regardless of whether they are or not physically present in the field area. Recognition of geologic features enabled experts to form and verbalize a specific plan for travel through a landscape based on those features. Novices were less likely to develop specific travel route plans and were less likely to identify critical landscape cues from aerial photographs.     

Large-scale urban functional zone mapping by integrating remote sensing images and open social data

ABSTRACT

Urban functional zones (UFZs) are important for urban sustainability and urban planning and management, but UFZ maps are rarely available and up-to-date in developing countries due to frequent economic and human activities and rapid changes in UFZs. Current methods have focused on mapping UFZs in a small area with either remote sensing images or open social data, but large-scale UFZ mapping integrating these two types of data is still not be applied. In this study, a novel approach to mapping large-scale UFZs by integrating remote sensing images (RSIs) and open social data is proposed. First, a context-enabled image segmentation method is improved to generate UFZ units by incorporating road vectors. Second, the segmented UFZs are classified by coupling Latent Dirichlet Allocation (LDA) and Support Vector Machine (SVM). In the classification framework, physical features from RSIs and social attributes from POI (Point of Interest) data are integrated. A case study of Beijing was performed to evaluate the proposed method, and an overall accuracy of 85.9% was achieved. The experimental results demonstrate that the presented method can provide fine-grained UFZs, and the fusion strategy of RSIs and POI data can distinguish urban functions accurately. The proposed method appears to be promising and practical for large-scale UFZ mapping.     

COMPILING LAND USE MAPS FOR PLANNING PURPOSES

The author outlines a series of recommendations for the compilation of land-use maps used for regional economic planning, based on experience gained in a portion of southwestern Siberia. These recommendations include: (a) selection of an intermediate scale for mapping, suitable for the portrayal of both moderate detail and broad regional patterns, (b) compilation of a series of related environmental-economic maps on a common base, to facilitate comparisons, and (c) portraying on a final map not only land use per se, but incorporating natural limitations and resulting land improvement measures into ratings of existing and potential productivity. An example of the latter is provided, with the map legend organized according to a matrix format. Incorporation of productivity ratings is believed to reduce subjectivity involved in the formulation of planning recommendations. Translated from: Geografiya i prirodnyye resursy, 1985, No. 2, pp. 92-97.     

Choosing pasture maps: An assessment of pasture land classification definitions and a case study of Brazil

Pasture land occupies extensive areas and is increasingly of interest for sustainable intensification, land use diversification, greenhouse gas emission mitigation, and bioenergy expansion. Accurate maps of pasture and other managed land covers are needed for monitoring, intercomparison, assessing potential uses, and planning. Yet, land maps can be generated from different types of classification datasets – i.e. as a land use or land cover type – as well as different sources. In this study our aim was to assess and compare land use and land cover definitions for pasture, and examine variability in the resulting pasture land classification maps. First, we conducted a review of pasture definitions in commonly used mapping databases. We then performed a case study involving Brazil, a dominant global producer of pasture-based livestock. Six geospatial databases were harmonized and compared to each other and to MODIS land cover for Brazil including the Cerrado and Amazon biomes, which are internationally recognized for their ecological value. Total pasture area estimates for Brazil ranged by a factor greater than four, from about 430,000 km² to over 1.7 million km². Our analysis showed high variability in pasture land maps depending on the definitions, methods and underlying datasets used to generate them. The results are illustrative of a symptomatic problem for all manage land datasets, demonstrating the need for land categories studies and geospatial data resources that fully define land terms and describe measurable management attributes. Additionally, the suitability of individual geospatial datasets for different types of land mapping must be better described and reported. These recommendations would help bring more consistency in the consideration of managed lands in research, reporting, and policy development, as demonstrated here for pasture land using six case study datasets from multiple sources.     

Monitoring canopy growth and grain yield of paddy rice in South Korea by using the GRAMI model and high spatial resolution imagery

Monitoring crop conditions and forecasting crop yields are both important for assessing crop production and for determining appropriate agricultural management practices; however, remote sensing is limited by the resolution, timing, and coverage of satellite images, and crop modeling is limited in its application at regional scales. To resolve these issues, the Gramineae (GRAMI)-rice model, which utilizes remote sensing data, was used in an effort to combine the complementary techniques of remote sensing and crop modeling. The model was then investigated for its capability to monitor canopy growth and estimate the grain yield of rice (Oryza sativa), at both the field and the regional scales, by using remote sensing images with high spatial resolution. The field scale investigation was performed using unmanned aerial vehicle (UAV) images, and the regional-scale investigation was performed using RapidEye satellite images. Simulated grain yields at the field scale were not significantly different (p = 0.45, p = 0.27, and p = 0.52) from the corresponding measured grain yields according to paired t-tests (α = 0.05). The model’s projections of grain yield at the regional scale represented the spatial grain yield variation of the corresponding field conditions to within ±1 standard deviation. Therefore, based on mapping the growth and grain yield of rice at both field and regional scales of interest within coverages of a UAV or the RapidEye satellite, our results demonstrate the applicability of the GRAMI-rice model to the monitoring and prediction of rice growth and grain yield at different spatial scales. In addition, the GRAMI-rice model is capable of reproducing seasonal variations in rice growth and grain yield at different spatial scales.     

Satellite data and geographic information systems for fire and resource management in the Canadian arctic

Abstract

A method of analyzing remotely sensed data, a geographic information system, and an intelligent fire management system have been developed to provide integrated resource data for fire and other resources management. Natural and cultural features were digitized from 1:50,000 topographic maps using a geographic information system (GIS) to cover the 29 communities below the tree line in the western Canadian Arctic. Landsat Thematic Mapper data covering the same area were classified into land cover or fuel types. Detailed information on each fire such as location, area burned, date of discovery, fire number, fire zone, fire class and source of ignition was obtained and added to each map sheet as attribute data. A generalized vegetation cover map using NOAA AVHRR data was also obtained. The Intelligent Fire Management Information System (IFMIS) integrates relational data bases, geographic information display, and expert systems. It also has a spatial analysis procedure for forest fire preparedness planning. Linking the weather to the forest fuels through the Fire Weather Index system (FWI) and the Fire Behaviour Prediction System (FBPS), fire danger and fire behaviour are calculated and displayed, cell‐by‐cell. Values‐at‐risk and fire suppression resources are used in the dispatching and planning component of the system. The planning component allows the user to evaluate the coverage of fire suppression resources under the prevalent forecast fire behaviour conditions. Through the integration of data from the above systems, a set of maps were created which were used to analyze fire behaviour potential, identify fire hazards, and provide a basis for settlement protection strategies within the context of other land use activities such as wildlife harvesting and recreational activities.     

COMMENTS ON K.A. SALISHCHEV'S PAPER

A method is described for the mapping of exogenous geomorphologic hazards (mass movements, frost heaving, suffosion, melting of permafrost) in the Lake Baykal area using space imagery. Black-and-white photography from the Salyut-4 space station (1:2,100,000 scale) was used as a base for the preparation of a series of maps depicting natural conditions (morphotectonic and physical geographic regions, faults, climate, dominant exogenous processes) used as a base for compiling a map of planning and engineering measures for the prevention and amelioration of geomorphologic hazards. Translated from: Geografiya i prirodnyye resursy, 1985, No. 2, pp. 59-67.     

Utility of satellite data for land evaluation in land use planning for a part of Northern Karnataka

The study reported herein deals with the utility of satellite remote sensing techniques for land evaluation for agricultural land use planning. False colour composite of Landsat imagery in the scale of 1:250,000 was visually interpreted for physiography that formed the base for mapping soil and land resources in the field. The small-scale soil map thus prepared has thirteen map units with association of soil families. Soil and land resource units shown on these small-scale maps were evaluated for their suitability for growing sorghum crop by matching the relevant land qualities against the land requirements for sorghum. The land evaluation carried out for growing sorghum crop in the study area revealed that about 38.6 per cent is highly suitable (S1), 31.5 per cent moderately suitable (S2) and 24.5 per cent marginally suitable (S3). An area of about 5.4 per cent is not suitable, of which 3.0 per cent is currently not suitable (N1) and 2.4 per cent permanently not suitable for growing sorghum crop.     

Understanding spatial variations of malaria in Vietnam using remotely sensed data integrated into GIS and machine learning classifiers

Abstract

This study examines the potentials of remotely sensed data, GIS and some machine learning classifiers and ensemble techniques in the investigation of the non-linear relationship between malaria occurrences and socio-physical conditions in the Dak Nong province of Viet Nam. Accuracy assessment was determined with Receiver Operating Characteristic (ROC) curve and pair t-test. The results showed that the area under ROC of Random Subspace ensemble model performed better than the other models based on statistical indicators. Comparing pair t-test with Area Under Curve values showed a slight difference of about 1%. Therefore ensemble techniques had significantly improved the performance of the base classifier. However, the performances might vary according to geographic locations. It is concluded that the machine learning classifiers combined with remotely sensed data and GIS is promising for malaria vulnerability mapping, and the derived maps can be used as a fundamental basis for programmes on spatial disease control.     

多源遥感数据快速自动处理技术探讨

甘肃省地图院利用国内外先进的现代测绘技术,构建了集地理信息采集、处理、贮存、管理于一体的信息化测绘生产体系,完成了信息化测绘生产基地的构建[1]。多源遥感数据快速自动处理技术应用研究是信息化测绘生产技术应用研究的一方面,主要是利用以信息化测绘生产基地为依托的遥感影像集群数据处理系统完成。本文主要探讨如何快速自动处理多源遥感数据,并以ADS80数据为例,对集群系统构建前后的效率进行对比实验。