Geothopica and the interactive analysis and visualization of the updated Italian National Geothermal Database

The Italian National Geothermal Database (BDNG), is the largest collection of Italian Geothermal data and was set up in the 1980s. It has since been updated both in terms of content and management tools: information on deep wells and thermal springs (with temperature > 30 °C) are currently organized and stored in a PostgreSQL relational database management system, which guarantees high performance, data security and easy access through different client applications. The BDNG is the core of the Geothopica web site, whose webGIS tool allows different types of user to access geothermal data, to visualize multiple types of datasets, and to perform integrated analyses. The webGIS tool has been recently improved by two specially designed, programmed and implemented visualization tools to display data on well lithology and underground temperatures.This paper describes the contents of the database and its software and data update, as well as the webGIS tool including the new tools for data lithology and temperature visualization. The geoinformation organized in the database and accessible through Geothopica is of use not only for geothermal purposes, but also for any kind of georesource and CO₂ storage project requiring the organization of, and access to, deep underground data. Geothopica also supports project developers, researchers, and decision makers in the assessment, management and sustainable deployment of georesources.     

影像融合技术在土地利用动态遥感监测中的应用研究

国土资源部启动的全国土地利用动态遥感监测项目,通过分析不同时期的卫星影像,从中提取出土地利用变化信息。本文的研究工作,主要是基于作者近几年从事该项目研究与应用的实际,分别以SPOT系列数据、TM数据及QuickBird等中、高分辨率数据作为试验数据,进行影像不同融合算法试验,旨在研究多源遥感影像融合方法在动态监测项目中的应用,并对融合结果进行定性、定量两方面的比较分析,探讨适合土地利用动态遥感监测的融合方法。     

Improving neural network performance on the classification of complex geographic datasets

Neural Networks are now established computational tools used for search minimisation and data classification. They offer some highly desirable features for landuse classification problems since they are able to take in a variety of data types, recorded on different statistical scales, and combine them. As such, neural networks should offer advantages of increased accuracy. However, a barrier to their general acceptance and use by all but `experts' is the difficulty of configuring the network initially.  This paper describes the architectural problems of applying neural networks to landcover classification exercises in geography and details some of the latest developments from an ongoing research project aimed at overcoming these problems. A comprehensive strategy for the configuration of neural networks is presented, whereby the network is automatically constructed by a process involving initial analysis of the training data. By careful study of the functioning of each part of the network it is possible to select the architecture and initial weights on the node connections so the constructed network is `right first time'. Further adaptations are described to control network behaviour, to optimise functioning from the perspective of landcover classification. The entire configuration process is encapsulated by a single application which may be treated by the user as a `black box', allowing the network to the applied in much the same way as a maximum likelihood classifier, with no further effort being required of the user.     

Analysis of the EUREF-89 GPS data from the SLR/VLBI sites

In May 1989, the IAG Subcommission for the European Reference Frame organized a GPS measurement campaign, called EUREF-89, to establish a common European Reference Frame. During a 2-week period various types of GPS receivers were deployed at about 100 different locations in Europe, which included many national geodetic first order points and most of the well-known SLR and VLBI sites. In this study, the measurements from those SLR and VLBI sites, and three additional points in The Netherlands, have been analyzed adopting a fiducial network approach. In the first place, the study provided valuable experience in the use of the GIPSY software for the analysis of GPS data from large networks equipped with a mixture of receiver types. Furthermore, this analysis represents an independent check of the SLR/VLBI network, used as the reference frame for the official EUREF solution. Daily solutions of baselines up to 2500 km in length have been obtained with a repeatability of 0.5–2.0 parts in 10⁸, while the agreement with SLR results is at about the same level. The accuracy of the estimated coordinates is at a level of about 4.0 cm in the horizontal and 6.0 cm in the vertical direction. Of particular interest are the results for some baselines in Greece, which have also been measured by mobile SLR in the framework of the WEGENER/MEDLAS project. The GPS results seem to confirm the trends in the baseline length changes emerging from those SLR studies.     

Impact of sampling rate of IGS satellite clock on precise point positioning

Both static and kinematic testings are investigated by using IGS 5min, 30s and 5s-interval precise satellite clock products in precise point positioning (PPP) solution. Test results show that the sampling rate of IGS satellite clock has very little effect on the static PPP solution. All the three types of sampling intervals of precise satellite clock can satisfy mm-cm level of positioning accuracy; higher sampling rate has no significant improvement for PPP solution. However, sampling rate of satellite clock has a significant impact on the PPP solution in kinematic PPP. The higher the interval of satellite clock, the better the accuracy achieved. The accuracy of kinematic PPP achieved by using 30s-interval precise satellite clock is improved by nearly 30–50 percent with respect to the solution by using 5min-interval precise satellite clock, but using 5s and 30s-interval satellite clock can almost produce the same accuracy of kinematic solution. Moreover, the use of precise satellite clock products from different analysis centers may also produce more or less effect on the PPP solution.     

陆地表层覆盖变化对地表反照率影响的四国对比

陆表覆盖变化影响地表特征从而改变地表能量平衡是理解人类活动对全球气候变化影响的关键环节。选择国际气候谈判主要国家的美国、印度和巴西作为中国的对比国,对比分析不同国别、不同气候带典型陆表覆盖类型的地表反照率时空差异,进而模拟开垦和城市化等陆表覆盖变化对反照率的影响差异。结果表明：(1) 2000年—2015年,中国、美国的地表反照率年际变化存在明显的气候带空间分异特征,中国干旱半干旱区和美国中低纬湿润区表现出降低趋势,而中国亚热带湿润和美国高纬与中部干旱区则表现出明显的升高趋势,印度的地表反照率年际变化呈微弱下降趋势,而巴西为微弱上升趋势。(2)无雪覆盖时,耕地、林地、草地和人造地表反照率具有夏高、冬低的时间变化特征,干旱半干旱区反照率明显高于湿润区。4种类型的国别差异体现在,中国亚热带湿润区地表反照率均以上升为主,干旱半干旱区则相反;美国除耕地在干旱区呈较强的升高趋势外,其余类型基本为降低趋势;印度均表现为降低趋势;巴西则表现为略微升高趋势。(3)与无雪覆盖相比,有雪覆盖时不同陆表覆盖类型地表反照率均有所提高,林地提高幅度最小,约0.06—0.26,耕地提高最大,约为0.17—0.38,且中国林地反照率提高幅度略高于美国。(4)原陆表覆盖为林地时,开垦和城镇化均导致地表反照率升高,且干旱区升高幅度高于湿润区,湿润区的升高幅度随纬度降低而减弱;为草地时,开垦主要在巴西、印度和中、美亚热带湿润区引起地表反照率升高。而城镇化引起的反照率变化则受到原有地表覆盖、季节和气候背景影响存在较复杂的国别和气候带差异。     

Impact of sampling rate of IGS satellite clock on precise point positioning

Both static and kinematic testings are investigated by using IGS 5min, 30s and 5s-interval precise satellite clock products in precise point positioning (PPP) solution. Test results show that the sampling rate of IGS satellite clock has very little effect on the static PPP solution. All the three types of sampling intervals of precise satellite clock can satisfy mm-cm level of positioning accuracy; higher sampling rate has no significant improvement for PPP solution. However, sampling rate of satellite clock has a significant impact on the PPP solution in kinematic PPP. The higher the interval of satellite clock, the better the accuracy achieved. The accuracy of kinematic PPP achieved by using 30s-interval precise satellite clock is improved by nearly 30–50 percent with respect to the solution by using 5min-interval precise satellite clock, but using 5s and 30s-interval satellite clock can almost produce the same accuracy of kinematic solution. Moreover, the use of precise satellite clock products from different analysis centers may also produce more or less effect on the PPP solution.     

地表覆盖自动解译方案在地理国情普查项目中的应用

在地理国情普查项目中,地表覆盖提取工作主要依赖人工解译和自动解译两种作业方式,实践证明,自动解译在一定程度上能够提高地表覆盖提取的工作效率,在地理国情普查项目中自动解译工作占30%的工作量,本文以易康软件为例,结合地理国情普查工作实际,详述地表覆盖自动解译方案。     

Quantitative monitoring of land use changes in relation to hydrology of Bhavani basin using remote sensing techniques — a case study

The paper summarises a part of the results of an on-going project for quantifying the land use changes in Bhavani basin (Geographic co-ordinates N lat 10°55′ - 11°45′,E Long. 76°30′ - 77°45′). Landsat and aerial data have been used in monitoring the dynamic changes in land use patterns. Visually interpreted Landsat MSS data of two different dates in conjunction with the historic data acquired from the Survey of India topographic maps and field data were used in this investigation. Also land use changes over two test-sites in the basin were studied using aerial photographs. During the study, it has been observed that a direct correlation exists between the rainfall and the area irrigated. The repetitive coverage of the satellite data are found to be quite remarkable, especially the 1:250,000 False Colour Composites (FCC) in assessing rapidly the temporal land use changes of a region at a cheaper cost.     

LAND USE SCANNER: An integrated GIS based model for long term projections of land use in urban and rural areas

This paper describes the structure of the LAND USE SCANNER model, a GIS based model developed to generate spatial forecasts for various types of land use for a large number of grids. The model basically allocates land according to bid prices for various types of land use. The possibility of government intervention in land use is taken into account among others by adding aggregate constraints. The model includes all relevant land use types such as residential, industrial, agricultural, natural areas and water. The model is driven by sectoral models providing forecasts of aggregate land use in various land use categories. An application of the first version of the model is given for the Netherlands with some 200,000 grid cells. Further developments and refinements of the model are planned for the near future. Received: 18 February 1998/Accepted: 29 September 1998     

青藏高原生态地质环境遥感调查研究

自2003年始开展的青藏高原生态地质环境遥感调查与监测项目已取得了阶段性的成果，本文就项目涉及到的第四纪基础地质 与第四纪冰川遗迹、现代冰川雪线、湖泊湿地、荒漠化等专题成果进行了简要介绍。本文明确了项目开展的意义，给出了青藏高原 生态地质环境质量的评价结果，强调了地学因素对于青藏高原生态地质环境形成与演化的控制作用，以及近30a来全球气候变化对 高原生态地质环境适应性变化的驱动作用。     

A Platform for Visualizing and Experimenting with Measures of Semantic Similarity in Ontologies and Concept Maps

This article describes research in the ongoing search for better semantic similarity tools: such methods are important when attempting to reconcile or integrate knowledge, or knowledge‐related resources such as ontologies and database schemas. We describe an extensible, open platform for experimenting with different measures of similarity for ontologies and concept maps. The platform is based around three different types of similarity, that we ground in cognitive principles and provide a taxonomy and structure by which new similarity methods can be integrated and used. The platform supports a variety of specific similarity methods, to which researchers can add others of their own. It also provides flexible ways to combine the results from multiple methods, and some graphic tools for visualizing and communicating multi‐part similarity scores. Details of the system, which forms part of the ConceptVista open codebase, are described, along with associated details of the interfaces by which users can add new methods, choose which methods are used and select how multiple similarity scores are aggregated. We offer this as a community resource, since many similarity methods have been proposed but there is still much confusion about which one(s) might work well for different geographical problems; hence a test environment that all can access and extend would seem to be of practical use. We also provide some examples of the platform in use.     

从本科毕业设计选题看武汉大学遥感学科的发展趋势

本科毕业设计是我国高等教育检验学生专业理论知识和实践应用能力的关键一环。本文通过对武汉大学遥感信息工程学院2009~2015年遥感大专业本科毕业设计选题进行分类,分析了近七年各类别选题所占比例的时间变化,并结合课题来源讨论了遥感专业的研究热点及研究兴趣,对武汉大学遥感学科发展趋势做了探讨。本文对武汉大学的遥感学科建设具有一定的指导意义,也为其他高校相关专业的建立和发展提供了一定的参考。     

基于ArcGIS空间建模的矿区土地复垦费用计算

土地复垦总投资与复垦工程量联系紧密,土地复垦工程量计算准确与否直接影响了复垦总投资。本文以计算山西省平定县某煤矿损毁土地复垦费用为例,利用ArcGIS平台建立空间模型,编写VBA代码,可迅速准确地计算出矿区损毁土地的复垦工程量、复垦费用。实现了快速统计权属单位、图斑编号对应的损毁地块的复垦工程量、复垦费用,并可通过GIS软件查询。实例表明计算相同地类的复垦工程量、复垦费用时,依损毁地类为单位建立的计算模型可以被多次、重复利用,能够有效避免使用Excel表格计算时出现的人为误差、工作效率低等问题。     

Tropical land use land cover mapping in Pará (Brazil) using discriminative Markov random fields and multi-temporal TerraSAR-X data

Remote sensing satellite data offer the unique possibility to map land use land cover transformations by providing spatially explicit information. However, detection of short-term processes and land use patterns of high spatial–temporal variability is a challenging task.We present a novel framework using multi-temporal TerraSAR-X data and machine learning techniques, namely discriminative Markov random fields with spatio-temporal priors, and import vector machines, in order to advance the mapping of land cover characterized by short-term changes. Our study region covers a current deforestation frontier in the Brazilian state Pará with land cover dominated by primary forests, different types of pasture land and secondary vegetation, and land use dominated by short-term processes such as slash-and-burn activities. The data set comprises multi-temporal TerraSAR-X imagery acquired over the course of the 2014 dry season, as well as optical data (RapidEye, Landsat) for reference. Results show that land use land cover is reliably mapped, resulting in spatially adjusted overall accuracies of up to 79% in a five class setting, yet limitations for the differentiation of different pasture types remain.The proposed method is applicable on multi-temporal data sets, and constitutes a feasible approach to map land use land cover in regions that are affected by high-frequent temporal changes.     

基于快鸟遥感影像的农地分类方法研究

遥感影像的解译精度受客观因素和主观因素的影响,各种不同解译方法的分类结果精度不一样,并且不同解译方法所适用的地物类型不相同。本文以咸阳市长武县的快鸟遥感影像数据源,运用不同的分类方法,对遥感数据进行解译,并对解译结果进行分析,评价不同解译方法的精度及所适用的地物类型。结果表明,决策树分类方法较适合农地分类。     

Exploitation of TerraSAR-X Data for Land use/Land Cover Analysis Using Object-Oriented Classification Approach in the African Sahel Area, Sudan

Recently, object-oriented classification techniques based on image segmentation approaches are being studied using high-resolution satellite images to extract various thematic information. In this study different types of land use/land cover (LULC) types were analysed by employing object-oriented classification approach to dual TerraSAR-X images (HH and HV polarisation) at African Sahel. For that purpose, multi-resolution segmentation (MRS) of the Definiens software was used for creating the image objects. Using the feature space optimisation (FSO) tool the attributes of the TerraSAR-X image were optimised in order to obtain the best separability among classes for the LULC mapping. The backscattering coefficients (BSC) for some classes were observed to be different for HH and HV polarisations. The best separation distance of the tested spectral, shape and textural features showed different variations among the discriminated LULC classes. An overall accuracy of 84 % with a kappa value 0.82 was resulted from the classification scheme, while accuracy differences among the classes were kept minimal. Finally, the results highlighted the importance of a combine use of TerraSAR-X data and object-oriented classification approaches as a useful source of information and technique for LULC analysis in the African Sahel drylands.     

基于3S技术的采煤沉陷区土地利用变化分析——以淮北闸河矿区为例

以淮北闸河矿区为例,以煤炭资源开发引起的土地资源与环境的演变为研究对象,采用3S技术获取该区主要土地利用类型信息,建立土地利用变化转移矩阵,并对该区的土地利用变化及驱动力因素进行初步分析。研究表明,因矿区内煤炭开采和经济的持续发展,使得矿区土地遭受不同程度的毁损。通过采取合理的城乡规划和土地环境整治工程,矿区的土地仍然得到高效利用。     

Satellite sensor modeling and 3D geo-positioning using empirical models

The need for the use of general empirical mathematical models for satellite sensor modeling and 3D geo-positioning has increased recently, mainly because of the absence of the satellite sensor information of some of the high-resolution satellites. In addition, empirical mathematical models can be applied to different satellite sensors since they are time independent mathematical models and do not require specialized commercial software packages. This paper discusses the applicability of the empirical mathematical models presented by the 3D affine model and the 3D polynomial models for satellite sensor modeling and 3D geo-positioning. The objectives of the paper are to demonstrate that (a) the 3D affine model and its modifications of the 3D polynomial models are applicable to different satellite sensors and different types of terrain, and (b) under some conditions, the empirical models can produce accuracies close to those from rigorous mathematical models.