A Conceptual Poverty Mapping Data Model

GIS is increasingly used in poverty mapping but there is no generic data model for database development. Examples exist already of industry‐specific models. Having such a data model eases the complexity of incorporating spatial data in poverty assessments. This article raises awareness about the need for a generic poverty data model for use in poverty mapping. It seeks to stimulate a lively debate that will lead to the development and adoption of such a data model. The ultimate goal will be to get to some level of standardization for common data types that would facilitate spatial data use in poverty assessment and sharing among poverty projects. This article is a first step at developing a data model for poverty mapping at a conceptual level. Handling multidimensional social problems, such as poverty, using a spatial framework can be challenging because of the myriad of poverty indicators in use. Employing the entity‐relationship approach, a conceptual model is developed in the current article that identifies the key thematic layers, entities, and relationships. The conceptual model produced is useful for modeling the content of the database for use in assessing and monitoring poverty.     

利用FME进行GIS数据的无损转换

在研究FME语义映射文件的组成格式、定义方法、执行过程的基础上,利用修改FME语义影射文件的方法,对DWG到SHAPE格式的数据无损转换进行了研究。结合科研项目,作者实现了数据从AutoCAD的DWG格式到ArcGIS的SHAPE格式的无损、快速、高效地转换,有效地解决了“如何实现数据在不同平台之间的转换,实现数据共享”这个制约GIS项目进度的瓶颈问题。     

Animated Maps of Aggregate Data: Conceptual and Practical Problems

Predictions of the 1960s about the computer's potential to change cartography are finally being fulfilled. Dynamic maps for vehicle navigation, interactive cartographic/statistical tools, and map animation are being investigated actively. As these new environments for mapping become available, we must reevaluate past questions about transformations from reality to data and data to map. In this paper, we consider these transformation questions in the context of statistical map animation. The issues discussed were raised in producing a “map movie” depicting the spread of acquired immune deficiency syndrome (AIDS) over time. Jenks' data model concept is used as the basis for a typology of data models representing phenomena typically depicted by enumeration unit data. The typology is then used to evaluate symbolization decisions for AIDS incidence maps. Implications for symbol selection imposed by dynamic rather than static maps are considered, as are technical issues involved in producing the animation on a microcomputer platform. A hybrid symbolization method that we have termed the “chorodot” is suggested as a way to meet the constraints on symbolization imposed by animation and to represent the appropriate data model for AIDS incidence.     

Extending F‐Perceptory to model fuzzy objects with composite geometries for GIS

When analyzing spatial issues, geographers are often confronted with many problems with regard to the imprecision of the available information. It is necessary to develop representation and design methods which are suited to imprecise spatiotemporal data. This led to the recent proposal of the F‐Perceptory approach. F‐Perceptory models fuzzy primitive geometries that are appropriate in representing homogeneous regions. However, the real world often contains cases that are much more complex, describing geographic features with composite structures such as a geometry aggregation or combination. From a conceptual point of view, these cases have not yet been managed with F‐Perceptory. This article proposes modeling fuzzy geographic objects with composite geometries, by extending the pictographic language of F‐Perceptory and its mapping to the Unified Modeling Language (UML) necessary to manage them in object/relational databases. Until now, the most commonly used object modeling tools have not considered imprecise data. The extended F‐Perceptory is implemented under a UML‐based modeling tool in order to support users in fuzzy conceptual data modeling. In addition, in order to properly define the related database design, an automatic derivation process is implemented to generate the fuzzy database model.     

Consistency grammar for 3D indoor model checking

Indoor 3D models are digital representations of building interiors reconstructed from scanned data acquired by laser scanners, digital depth (RGBD) cameras, and CAD drawings. Consequently, there is noise in the source data and a notable variety in the methods used to treat the noise and to process these data into reconstructed models. Alas, the correctness of these reconstructions and thus their suitability for a given application are uncertain. There is a lack of a robust base logic that would allow for controlling the consistency of these (automatically) generated models. Fortunately, correctness criteria are well‐defined through existing international standards. Hence, we propose a conceptual framework based on formal grammars to check the semantic, geometric, and topological consistency of a reconstructed 3D model. The proposed method proceeds in three steps to validate the model: (1) correctness checking of individual components; (2) consistency verification of instances’ interactions; and (3) model consistency check for targeted applications. Our method identifies the components in the model that violate the given rules derived from the current standards and expert knowledge. Ultimately, we propose a quantified formulation of our method that may be straightforwardly integrated into industrial‐level model checkers. The approach is independent of level of details and reconstruction method.     

Geons – domain-specific regionalization of space

The design of methods and tools to build adequate representations of complex geographical phenomena in a way that spatial patterns are emphasized is one of the core objectives of GIScience. In this paper, we build on the concept of geons as a strategy to represent and analyze latent spatial phenomena across different geographical scales (local, national, regional) incorporating domain-specific expert knowledge. Focusing on two types, we illustrate and exemplify how geons are generated and explored. So-called composite geons represent functional land-use classes, required for regional planning purposes. They are created via class modeling to translate interpretation schemes from mapping keys. Integrated geons, on the other hand, address abstract, yet policy-relevant phenomena such as societal vulnerability to hazards. They are delineated by regionalizing continuous geospatial data sets representing relevant indicators in a multidimensional variable space. Using the geon approach, we create spatially exhaustive sets of units, scalable to the level of policy intervention, homogenous in their domain-specific response, and independent from any predefined boundaries. From a GIScience perspective, we discuss either type of geons in a semantic hierarchy of geographic information constructs. Despite its validity for decision-making and its transferability across scales and application fields, the delineation of geons requires further methodological research to assess their statistical and conceptual robustness.     

Predictive mapping with small field sample data using semi‐supervised machine learning

Existing predictive mapping methods usually require a large number of field samples with good representativeness as input to build reliable predictive models. In mapping practice, however, we often face situations when only small sample data are available. In this article, we present a semi‐supervised machine learning approach for predictive mapping in which the natural aggregation (clustering) patterns of environmental covariate data are used to supplement limited samples in prediction. This approach was applied to two soil mapping case studies. Compared with field sample only approaches (decision trees, logistic regression, and support vector machines), maps using the proposed approach can better capture the spatial variation of soil types and achieve higher accuracy with limited samples. A cross validation shows further that the proposed approach is less sensitive to the specific field sample set used and thus more robust when field sample data are small.     

Towards an automated approach to map flooded areas from Sentinel-2 MSI data and soft integration of water spectral features

In this work we propose an approach for mapping flooded areas from Sentinel-2 MSI (Multispectral Instrument) data based on soft fuzzy integration of evidence scores derived from both band combinations (i.e. Spectral Indices - SIs) and components of the Hue, Saturation and Value (HSV) colour transformation. Evidence scores are integrated with Ordered Weighted Averaging (OWA) operators, which model user’s decision attitude varying smoothly between optimistic and pessimistic approach. Output is a map of global evidence degree showing the plausibility of being flooded for each pixel of the input Sentinel-2 (S2) image. Algorithm set up and validation were carried out with data over three sites in Italy where water surfaces are extracted from stable water bodies (lakes and rivers), natural hazard flooding, and irrigated paddy rice fields. Validation showed more than satisfactory accuracy for the OR-like OWA operators (F-score > 0.90) with performance slightly decreased (F-score < 0.75) over heterogeneous conditions (e.g. rice fields). The algorithm was applied with no changes and/or tuning to independent sites from the Copernicus Emergency Management Service (EMS) activations to simulate operational conditions. Over these sites, the proposed approach achieved greater, more consistent and robust mapping accuracy compared to traditional approaches based on the segmentation of single input features. Moreover, OWA operators offer an appealing way of combining and aggregating multiple information in decision making by modelling uncertainty in decision process.     

MASTER: A multiple aspect view on trajectories

For many years trajectory data have been treated as sequences of space‐time points or stops and moves. However, with the explosion of the Internet of Things and the flood of big data generated on the Internet, such as weather channels and social network interactions, which can be used to enrich mobility data, trajectories become more and more complex, with multiple and heterogeneous data dimensions. The main challenge is how to integrate all this information with trajectories. In this article we introduce a new concept of trajectory, called multiple aspect trajectory, propose a robust conceptual and logical data model that supports a vast range of applications, and, differently from state‐of‐the‐art methods, we propose a storage solution for efficient multiple aspect trajectory queries. The main strength of our data model is the combination of simplicity and expressive power to represent heterogeneous aspects, ranging from simple labels to complex objects. We evaluate the proposed model in a tourism scenario and compare its query performance against the state‐of‐the‐art spatio‐temporal database SECONDO extension for symbolic trajectories.     

SCOPED‐W: SCalable Online Platform for extracting Environmental Data and Water‐related model outputs

This article presents SCOPED, an innovative approach for extracting environmental data using OGC services. In the field of water resource management, SCOPED‐W (‘W’ for ‘Water’) is a method that was developed in the framework of EU/FP7 IASON and EOPOWER projects. This platform supports the collection of data required to build a Soil and Water Assessment Tool (SWAT) model and the uptake, spatialization and dissemination of raw data generated from the outputs of different SWAT models for the Black Sea region. Scientists are documenting the data served by the platform in ISO standardized metadata to support informed use. SCOPED‐W primarily targets the community of SWAT users in the Black Sea region but it can easily be replicated in other geographical areas. Additionally, the SCOPED approach is based on data interoperability that makes it fully compatible with other domains of application as demonstrated here with three original use cases. The article also highlights the benefits of the approach for the GEO community and discusses future improvements for supporting integration with other platforms such as UNEP Live.     

FY-2卫星S-VISSR数据几何纠正研究

提出了一种简单高效的FY-2卫星S-VISSR数据的几何纠正方法。该方法以FY-2标称投影图像（NOM）经纬度对照表作为参考图像,FY-2卫星S-VISSR数据作为输入图像,首先利用S-VISSR数据提供的简化格网数据在两幅图像间获取同名点,然后根据同名点寻找两幅图像间的几何变换模型,最后对S-VISSR数据进行几何纠正。实验表明,利用该方法能够快速地完成对FY-2E和FY-2D卫星S-VISSR数据的几何纠正,其精度达到了1个像素左右。     

Application of fuzzy AHP method to IOCG prospectivity mapping: A case study in Taherabad prospecting area,eastern Iran

Using fuzzy analytical hierarchy process (AHP) technique, we propose a method for mineral prospectivity mapping (MPM) which is commonly used for exploration of mineral deposits. The fuzzy AHP is a popular technique which has been applied for multi-criteria decision-making (MCDM) problems. In this paper we used fuzzy AHP and geospatial information system (GIS) to generate prospectivity model for Iron Oxide Copper-Gold (IOCG) mineralization on the basis of its conceptual model and geo-evidence layers derived from geological, geochemical, and geophysical data in Taherabad area, eastern Iran. The FuzzyAHP was used to determine the weights belonging to each criterion. Three geoscientists knowledge on exploration of IOCG-type mineralization have been applied to assign weights to evidence layers in fuzzy AHP MPM approach. After assigning normalized weights to all evidential layers, fuzzy operator was applied to integrate weighted evidence layers. Finally for evaluating the ability of the applied approach to delineate reliable target areas, locations of known mineral deposits in the study area were used. The results demonstrate the acceptable outcomes for IOCG exploration.     

新疆巴里坤ETM数据遥感地质填图的探索

 对新疆巴里坤县八墙子一带ETM数据进行主成分分析、彩色，空间变换及假彩色合成等图像处理，同时，依据野外踏勘、实测 剖面等资料不断调整图像处理方法； 以最大程度突出已知岩性单元间影像区别为目的，通过全色谱段融合方式将图像比例尺提高到1 ︰5万； 在ArcView等平台上进行综合分析、解译和填图，并经过实地查验进一步修改填图方法与结果，最后编辑形成地质图。     

VGDI – Advancing the Concept: Volunteered Geo‐Dynamic Information and its Benefits for Population Dynamics Modeling

The concept of Volunteered Geographic Information (VGI) has progressed from being an exotic prospect to making a profound impact on GIScience and geography in general, as initially anticipated. However, while massive and manifold data is continuously produced voluntarily and applications are built for information and knowledge extraction, the initially introduced concept of VGI lacks certain methodological perspectives in this regard which have not been fully elaborated. In this article we highlight and discuss an important gap in this concept, i.e. the lack of formal acknowledgment of temporal aspects. By coining the proposed advanced framework ‘Volunteered Geo‐Dynamic Information’ (VGDI), we attempt to lay the ground for full conceptual and applied spatio‐temporal integration. To illustrate that integrative approach of VGDI and its benefits, we describe the potential impact on the field of dynamic population distribution modeling. While traditional approaches in that domain rely on survey‐based data and statistics as well as static geographic information, the use of VGDI enables a dynamic setup. Foursquare venue and user check‐in data are presented for a test site in Lisbon, Portugal. Two core modules of spatio‐temporal population assessment are thereby addressed, namely time use profiling and target zone characterization, motivated by the potential integration in existing population dynamics frameworks such as the DynaPop model.     

适用于机载三维遥感的动态GPS定位技术及其数据处理

机载三维遥感采用动态ＧＰＳ定位技术提供遥感器的空中精确位置,能快速高效获得遥感地学编码图像和ＤＥＭ,雇地中国自行研制、具有独创性的机载三维遥感影像制图系统中的动态ＧＰＳ定位技术特点和要求进行了分析。论述了应用三维遥感的ＧＳＰ定位数据处理和算流程。法     

利用农村地籍调查成果更新地理信息公共平台居民地方法研究

省级地理信息公共服务平台数据的快速更新是困扰测绘生产单位的难题,通过试验利用同期完成的大比例尺农村地籍调查成果具有现势性强、精度高的优势,找准该数据用于DLG更新的切入点,对农村地籍要素进行分类与提取,基于自动综合更新技术模式,完成同期城乡数据的衔接及整合,实现行政区划单元范围1∶10 000DLG居民地要素快速更新,为以后省级地理信息公共服务平台数据的快速更新提供新思路。     

A novel approach to leveraging social media for rapid flood mapping: a case study of the 2015 South Carolina floods

Rapid flood mapping is critical for local authorities and emergency responders to identify areas in need of immediate attention. However, traditional data collection practices such as remote sensing and field surveying often fail to offer timely information during or right after a flooding event. Social media such as Twitter have emerged as a new data source for disaster management and flood mapping. Using the 2015 South Carolina floods as the study case, this paper introduces a novel approach to mapping the flood in near real time by leveraging Twitter data in geospatial processes. Specifically, in this study, we first analyzed the spatiotemporal patterns of flood-related tweets using quantitative methods to better understand how Twitter activity is related to flood phenomena. Then, a kernel-based flood mapping model was developed to map the flooding possibility for the study area based on the water height points derived from tweets and stream gauges. The identified patterns of Twitter activity were used to assign the weights of flood model parameters. The feasibility and accuracy of the model was evaluated by comparing the model output with official inundation maps. Results show that the proposed approach could provide a consistent and comparable estimation of the flood situation in near real time, which is essential for improving the situational awareness during a flooding event to support decision-making.     

淤泥质潮滩水边线提取的遥感研究及DEM构建——以长江口九段沙为例

淤泥质潮滩通常是测绘"盲区"。本文讨论采用多时相陆地卫星提取潮滩水边线以此构建潮滩数字高程模型(DEM)的方法。探讨在不同潮情条件下,各光谱波段对淤泥质潮滩水边线判断的敏感性,分析表明沙质海岸与淤泥质海岸水边线的确定方法有较大差别。采用了GIS技术对提取的水边线赋予相应的高程值,该值采用研究区附近潮位站理论潮位推算卫星过境的瞬时潮位值,以此构建潮滩DEM,与近期实测资料进行对比:在106.2 cm-358.6 cm高程范围内,二者相对误差<0.5 m的区域占总面积约70%,0.5～1.0 m为20%,>1.0 m占10%。遥感构建DEM作为一种手段对实测资料的欠缺是一种补充,随着遥感技术的发展精度有望提高。     

Fuzzy Modelling of African Ecoregions and Ecotones Using AVHRR NDVI Temporal Imagery

Abstract

Conventional methods of deriving global or continental vegetation maps from the National Oceanic and Atmospheric Administration's (NOAA) Advanced Very High Resolution Radiometer (AVHRR) time series data are based on two‐value Boolean logic, which cannot properly model the so‐called ecotone, the transition zone between adjacent ecosystems. New methods and data models that have been developed on the basis of fuzzy logic to address the “mixed pixel” issue in multi‐spectral imagery can also be used with multi‐temporal imagery to handle the mixture of vegetation types within an ecotone. This study introduces the concept of semantic space and its transformation from spectral feature space, which utilizes a fuzzy logic approach to characterize the continuum of vegetation communities in the African continent from AVHRR multi‐temporal (12 months for three years from 1986 to 1988) NDVI data. The fuzzy procedure was based on the Fuzzy c‐Means (FCM) algorithm with significant modifications to improve processing speed for handling large volumes of data. A second‐order mapping approach was also devised to explicitly represent subdominant vegetative coverage in ecotones and other heterogeneous regions. Comparisons between a Sub‐Saharan African Vegetation Map compiled by the International Union for Conservation of Nature (IUCN) in 1986 and the maps derived from this study demonstrated that fuzzy modeling and classification might provide a better and more realistic representation of the vegetative characteristics of the region.     

Automated lithological mapping by integrating spectral enhancement techniques and machine learning algorithms using AVIRIS-NG hyperspectral data in Gold-bearing granite-greenstone rocks in Hutti,India

In this study, we proposed an automated lithological mapping approach by using spectral enhancement techniques and Machine Learning Algorithms (MLAs) using Airborne Visible Infrared Imaging Spectroradiometer-Next Generation (AVIRIS-NG) hyperspectral data in the greenstone belt of the Hutti area, India. We integrated spectral enhancement techniques such as Principal Component Analysis (PCA) and Independent Component Analysis (ICA) transformation and different MLAs for an accurate mapping of rock types. A conjugate utilization of conventional geological map and spectral enhancement products derived from ASTER data were used for the preparation of a high-resolution reference lithology map. Feature selection and extraction methods were applied on the AVIRIS-NG data to derive different input dataset such as (a) all spectral bands, (b) shortwave infrared bands, (c) Joint Mutual Information Maximization (JMIM) based optimum bands, and (d) optimum bands using PCA, to choose optimum input dataset for automated lithological mapping. The comparative analysis of different MLAs shows that the Support Vector Machine (SVM) outperforms other Machine Learning (ML) models. The SVM achieved an Overall Accuracy (OA) and Kappa Coefficient (k) of 85.48% and 0.83, respectively, using JMIM based optimum bands. The JMIM based optimum bands were more suitable than other input datasets to classify most of the lithological units (i.e. metabasalt, amphibolite, granite, acidic intrusive and migmatite) within the study area . The sensitivity analysis performed in this study illustrates that the SVM is less sensitive to the number of samples and mislabeling in the model training than other MLAs. The obtained high-resolution classified map with accurate litho-contacts of amphibolite, metabasalt, and granite can be coupled with an alteration map of the area for targeting the potential zone of gold mineralization.