GIS Colloquium – Talks (Summer Term 2018)

Micro Diagrams: A Multi-Scale Approach for Geovisual Analysis of Categorised Point Datasets

Mathias Gröbe
Mon, April 23, 2.15 pm (Venue: INF 348, Room 015)

Location-based social media from different platforms such as Twitter and Flickr increasingly serve as data source for many diverse research projects with their point-geocoded content. For analyses and visualisation, it is necessary to show distributions of categories in different scales and resolutions. The Micro Diagrams were developed as solution to map such large geospatial point datasets. For example, a pie chart shows the numerical proportion, and the size or transparency of the chart symbolises the number of records. Therefor an aggregation is necessary to create the diagrams and to map the number of values in one cluster to a visual variable like size. Depending on the aggregation type, the resulting patterns differ. It is possible to choose a convenient method that allows to work with multiple scales with a separate content zoom interaction and to carry out scale-dependent pattern analysis of multivariate point datasets. As visualisation constraint, the area that is used for the representation of the values scales with the numbers of aggregated values.

Smart Point Clouds – extended intelligence of point clouds due to hypertemporal data for realization of the digital shadow

Evelyn Schmitz
Mon, April 30, 2.15 pm (Venue: INF 348, Room 015)

Raw point clouds are unstructured aggregations of measured xyz-coordinates. While it is easy for humans to detect and interpret parts of these aggregations, algorithms struggle with the correct detection and identification of objects. A solution is the selection of information given by the points of hypertemporal data acquisitions to enlarge the smartness of point clouds and their application fields, using the advantages of a fourth dimension, i.e. time. The digital shadow aims at the creation of a permanent, actual and accurate image of relevant data in the field of production. Simple and fast algorithms in combination with data from the past and present are required to develop agile, self-optimizing factories, decreasing costs by increasing production efficiency at high quality. An approach for the identification of the changed geo-location of single objects, e.g. robots, racks and trolleys, in a fabric coordinate system between several time steps is presented. Hypertemporal data were acquired at the research campus ARENA2036 with a FARO Focus S 350 laser scanner. After the application of an automated rough filtering of stable objects, a voxel-based change detection algorithm compares properties of corresponding voxels based on their constituting points. The method delivers a first step for the realization of the digital shadow in a factory hall.

Recent Advances in Remote Sensing Image Search and Retrieval from Large Archives

Prof. Dr. Begum Demir
Mon, May 14, 2.15 pm (Venue: INF 348, Room 015)

During the last decade, a huge number of earth observation (EO) satellites with optical and Synthetic Aperture Radar sensors onboard have been launched and advances in satellite systems have increased the amount and variety of EO data. This has led to massive EO data archives with huge amount of remote sensing (RS) images, from which retrieving useful information is challenging. In view of that, content based image retrieval (CBIR) has attracted great attention in the RS community. In this talk, a general overview on scientific and practical problems related to RS image characterization, indexing and search from massive archives will be initially discussed. Then, recent developments that can overcome the considered problems will be introduced by focusing on semantic-sensitive hashing based scalable and accurate RS CBIR systems.

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