3D Maps Representation Using GNG

Current RGB-D sensors provide a big amount of valuable information for mobile robotics tasks like 3D map reconstruction, but the storage and processing of the incremental data provided by the different sensors through time quickly become unmanageable. In this work, we focus on 3D maps representation and propose the use of the Growing Neural Gas (GNG) network as a model to represent 3D input data. GNG method is able to represent the input data with a desired amount of neurons or resolution while preserving the topology of the input space. Experiments show how GNG method yields a better input space adaptation than other state-of-the-art 3D map representation methods.

Feature selection by multi-objective optimisation: Application to network anomaly detection by hierarchical self-organising maps

Feature selection is an important and active issue in clustering and classification problems. By choosing an adequate feature subset, a dataset dimensionality reduction is allowed, thus contributing to decreasing the classification computational complexity, and to improving the classifier performance by avoiding redundant or irrelevant features. Although feature selection can be formally defined as an optimisation problem with only one objective, that is, the classification accuracy obtained by using the selected feature subset, in recent years, some multi-objective approaches to this problem have been proposed. These either select features that not only improve the classification accuracy, but also the generalisation capability in case of supervised classifiers, or counterbalance the bias toward lower or higher numbers of features that present some methods used to validate the clustering/classification in case of unsupervised classifiers. The main contribution of this paper is a multi-objective approach for feature selection and its application to an unsupervised clustering procedure based on Growing Hierarchical Self-Organising Maps (GHSOMs) that includes a new method for unit labelling and efficient determination of the winning unit. In the network anomaly detection problem here considered, this multi-objective approach makes it possible not only to differentiate between normal and anomalous traffic but also among different anomalies. The efficiency of our proposals has been evaluated by using the well-known DARPA/NSL-KDD datasets that contain extracted features and labelled attacks from around 2 million connections. The selected feature sets computed in our experiments provide detection rates up to 99.8% with normal traffic and up to 99.6% with anomalous traffic, as well as accuracy values up to 99.12%.

Subsidence activity maps derived from DInSAR data: Orihuela case study

A new methodology is proposed to produce subsidence activity maps based on the geostatistical analysis of persistent scatterer interferometry (PSI) data. PSI displacement measurements are interpolated based on conditional Sequential Gaussian Simulation (SGS) to calculate multiple equiprobable realizations of subsidence. The result from this process is a series of interpolated subsidence values, with an estimation of the spatial variability and a confidence level on the interpolation. These maps complement the PSI displacement map, improving the identification of wide subsiding areas at a regional scale. At a local scale, they can be used to identify buildings susceptible to suffer subsidence related damages. In order to do so, it is necessary to calculate the maximum differential settlement and the maximum angular distortion for each building of the study area. Based on PSI-derived parameters those buildings in which the serviceability limit state has been exceeded, and where in situ forensic analysis should be made, can be automatically identified. This methodology has been tested in the city of Orihuela (SE Spain) for the study of historical buildings damaged during the last two decades by subsidence due to aquifer overexploitation. The qualitative evaluation of the results from the methodology carried out in buildings where damages have been reported shows a success rate of 100%.

Using causal maps to support ex-post assessment of social impacts of dams

This paper presents the results of an ex-post assessment of two important dams in Brazil. The study follows the principles of Social Impact Management, which offer a suitable framework for analyzing the complex social transformations triggered by hydroelectric dams. In the implementation of this approach, participative causal maps were used to identify the ex-post social impacts of the Porto Primavera and Rosana dams on the community of Porto Rico, located along the High Paraná River. We found that in the operation of dams there are intermediate causes of a political nature, stemming from decisions based on values and interests not determined by neutral, exclusively technical reasons; and this insight opens up an area of action for managing the negative impacts of dams.

Causal Maps and Indirect Influences Analysis in the Diagnosis of Second-Home Tourism Impacts

This paper proposes a method for diagnosing the impacts of second-home tourism and illustrates it for a Mediterranean Spanish destination. This method proposes the application of network analysis software to the analysis of causal maps in order to create a causal network model based on stakeholder-identified impacts. The main innovation is the analysis of indirect relations in causal maps for the identification of the most influential nodes in the model. The results show that the most influential nodes are of a political nature, which contradicts previous diagnoses identifying technical planning as the ultimate cause of problems.

Accounts related to maps and pamphlets, 1809-1823

This folder contains eight handwritten account statements and notes primarily related to the collection of subscriptions for Croswell's maps and pamphlets, as well as the disbursement and storage of his printed maps and pamphlets.

Red Sea Region, North Africa, ca. 1730 (Raster Image)

This layer is a georeferenced raster image of the historic paper map entitled: Carte de l'Egypte, de la Nubie, de l'Abyssinie &c., par Guillaume de l'Isle, de l'Academie Royal a Paris. It was published by Chez Henri de Leth, a l'enseigne du Pecheur ca. 1730. Scale [ca. 1:9,250,000]. Covers the Red Sea region, North Africa including portions of the Middle East and Europe. Map in French.The image inside the map neatline is georeferenced to the surface of the earth and fit to the Africa Sinusoidal projected coordinate system. All map collar and inset information is also available as part of the raster image, including any inset maps, profiles, statistical tables, directories, text, illustrations, index maps, legends, or other information associated with the principal map. This map shows features such as drainage, major roads, cities and other human settlements, territorial boundaries, shoreline features, and more. Relief shown pictorially. This layer is part of a selection of digitally scanned and georeferenced historic maps from the Harvard Map Collection. These maps typically portray both natural and manmade features. The selection represents a range of originators, ground condition dates, scales, and map purposes.

Mediterranean Sea Region, East, 1690-1699 (Raster Image)

This layer is a georeferenced raster image of the historic paper map entitled: Accuratissima orientalioris districtus maris Mediterranei tabula, authore Iusto Danckerts. It was published by Iusto Danckerts, between 1690 and 1699. Scale [ca. 1:5,300,000]. Covers the eastern Mediterranean Sea region. Map in Latin. The image inside the map neatline is georeferenced to the surface of the earth and fit to the World Miller Cylindrical projected coordinate system. All map collar and inset information is also available as part of the raster image, including any inset maps, profiles, statistical tables, directories, text, illustrations, index maps, legends, or other information associated with the principal map. This map shows features such as drainage, cities and other human settlements, roads, shoreline features, and more. Relief shown pictorially.This layer is part of a selection of digitally scanned and georeferenced historic maps from the Harvard Map Collection. These maps typically portray both natural and manmade features. The selection represents a range of originators, ground condition dates, scales, and map purposes.

Mediterranean Sea Region, 1690-1699 (Raster Image)

This layer is a georeferenced raster image of the untitled historic paper map: [Mediterranean sea], authore Iusto Danckerts. It was published by Iusto Danckerts, between 1690 and 1699. Scale [ca. 1:5,300,000]. Covers the Mediterranean Sea region. Map in Latin. Source map issued on two sheets, now pasted together. The image inside the map neatline is georeferenced to the surface of the earth and fit to the World Miller Cylindrical projected coordinate system. All map collar and inset information is also available as part of the raster image, including any inset maps, profiles, statistical tables, directories, text, illustrations, index maps, legends, or other information associated with the principal map. This map shows features such as drainage, cities and other human settlements, roads, territorial features, shoreline features, and more. Relief shown pictorially.This layer is part of a selection of digitally scanned and georeferenced historic maps from the Harvard Map Collection. These maps typically portray both natural and manmade features. The selection represents a range of originators, ground condition dates, scales, and map purposes.

Mediterranean Sea Region, 1700-1710 (Raster Image)

This layer is a georeferenced raster image of the historic paper map entitled: Carte nouvelle de la mer Mediterranée : divisée en mer de Levant et de Ponant, subdivisés en leurs principales parties ou mers : avec les observations des Mrs. de l'Académie, dressée par ... Sanson. It was published by chez Pierre Mortier, between 1700 and 1710. Scale [ca. 1:4,375,000]. Covers the Mediterranean Sea and Black Sea regions. Map in French. The image inside the map neatline is georeferenced to the surface of the earth and fit to the World Miller Cylindrical projected coordinate system. All map collar and inset information is also available as part of the raster image, including any inset maps, profiles, statistical tables, directories, text, illustrations, index maps, legends, or other information associated with the principal map. This map shows features such as drainage, cities and other human settlements, roads, territorial boundaries, shoreline features, and more. Relief shown pictorially.This layer is part of a selection of digitally scanned and georeferenced historic maps from the Harvard Map Collection. These maps typically portray both natural and manmade features. The selection represents a range of originators, ground condition dates, scales, and map purposes.

Europe & Mediterranean Sea Region, 1705 (Image 2 of 2) (Raster Image)

This layer is a georeferenced raster image of the historic paper map entitled: Toonneel des oorlogs in't zuider deel van Europa, door Carel Allard = Theatre de la guerre dans l'Europe meridionale, par Charles Allard. It was published by C. Allard in 1705. Scale [ca. 1:6,800,000]. Covers a portion of Europe and the Mediterranean Sea region. This layer is image 2 of 2 total images of the two sheet source map, representing the eastern portion of the map. Map in Dutch and French. The image inside the map neatline is georeferenced to the surface of the earth and fit to the World Miller Cylindrical projected coordinate system. All map collar and inset information is also available as part of the raster image, including any inset maps, profiles, statistical tables, directories, text, illustrations, index maps, legends, or other information associated with the principal map. This map shows features such as drainage, cities and other human settlements, territorial boundaries, shoreline features, and more. Relief shown pictorially.This layer is part of a selection of digitally scanned and georeferenced historic maps from the Harvard Map Collection. These maps typically portray both natural and manmade features. The selection represents a range of originators, ground condition dates, scales, and map purposes.

Indian Ocean Region, ca. 1690 (Raster Image)

This layer is a georeferenced raster image of the historic paper map entitled: Nova tabula Indiae Orientalis. It was published by Carolus Allard excudit, between 1690 and 1710. Scale [ca. 1:5,500,000]. Covers the Indian Ocean Region. Map in Latin. The image inside the map neatline is georeferenced to the surface of the earth and fit to the World Miller Cylindrical projected coordinate system. All map collar and inset information is also available as part of the raster image, including any inset maps, profiles, statistical tables, directories, text, illustrations, index maps, legends, or other information associated with the principal map. This map shows features such as drainage, roads, cities and other human settlements, territorial boundaries, shoreline features, and more. Relief shown pictorially.This layer is part of a selection of digitally scanned and georeferenced historic maps from the Harvard Map Collection. These maps typically portray both natural and manmade features. The selection represents a range of originators, ground condition dates, scales, and map purposes.