GML-Based Data Management and Semantic World Modelling for a 4D Forest Simulation and Information System

2014 ◽  
Vol 3 (3) ◽  
pp. 50-67 ◽  
Author(s):  
Jürgen Roßmann ◽  
Martin Hoppen ◽  
Arno Bücken
Keyword(s):  
Information System ◽  
Data Management ◽  
Data Extraction ◽  
Remote Sensing Data ◽  
Schema Family ◽  
Common Basis ◽  
Simulation Techniques ◽  
Crown Volume ◽  
Forest Models ◽  
Forest Simulation

Various types of 3D simulation applications benefit from realistic forest models. They range from flight simulators for entertainment to harvester simulators for training and tree growth simulations for research and planning. This paper's 4D forest simulation and information system integrates the necessary methods for data extraction, modelling and management. Using modern methods of semantic world modelling, tree data can efficiently be extracted from remote sensing data. The derived forest models contain position, height, crown volume, type and diameter of each tree. This data is modelled using GML-based data models to assure compatibility and exchangeability. ForestGML is the name of a new schema family developed to provide a common basis for forestry data. A flexible approach for database synchronization is used to manage the data and provide caching, persistence, a central communication hub for change distribution, and a versioning mechanism. Combining various simulation techniques and data versioning, the 4D forest simulation and information system can provide applications with “both directions” of the fourth dimension. This paper outlines the current state, new developments, and integration of tree extraction, data modelling, and data management. It also shows several applications realized with the system.

GML-Based Data Management and Semantic World Modelling for a 4D Forest Simulation and Information System

2019 ◽  
pp. 423-442
Author(s):  
Jürgen Roßmann ◽  
Martin Hoppen ◽  
Arno Bücken
Keyword(s):  
Information System ◽  
Data Management ◽  
Data Extraction ◽  
Remote Sensing Data ◽  
Schema Family ◽  
Common Basis ◽  
Simulation Techniques ◽  
Crown Volume ◽  
Forest Models ◽  
Forest Simulation

Various types of 3D simulation applications benefit from realistic forest models. They range from flight simulators for entertainment to harvester simulators for training and tree growth simulations for research and planning. This paper's 4D forest simulation and information system integrates the necessary methods for data extraction, modelling and management. Using modern methods of semantic world modelling, tree data can efficiently be extracted from remote sensing data. The derived forest models contain position, height, crown volume, type and diameter of each tree. This data is modelled using GML-based data models to assure compatibility and exchangeability. ForestGML is the name of a new schema family developed to provide a common basis for forestry data. A flexible approach for database synchronization is used to manage the data and provide caching, persistence, a central communication hub for change distribution, and a versioning mechanism. Combining various simulation techniques and data versioning, the 4D forest simulation and information system can provide applications with “both directions” of the fourth dimension. This paper outlines the current state, new developments, and integration of tree extraction, data modelling, and data management. It also shows several applications realized with the system.

GML-Based nD Data Management With a Big Geo Data Semantic World Modeling Approach

2018 ◽  
pp. 191-223
Author(s):  
Juergen Rossmann ◽  
Martin Hoppen ◽  
Arno Buecken
Keyword(s):  
Information System ◽  
Data Management ◽  
Data Extraction ◽  
Remote Sensing Data ◽  
Management Approach ◽  
Multiple Time ◽  
Simulation Techniques ◽  
3D Data ◽  
World Modeling ◽  
Forest Simulation

3D simulation applications benefit from realistic and exact forest models. They range from training simulators like flight or harvester simulators to economic and ecological simulations for tree growth or succession. The nD forest simulation and information system integrates the necessary methods for data extraction, modeling, and management of highly realistic models. Using semantic world modeling, tree data can efficiently be extracted from remote sensing data – even for very large areas. Data is modeled using a GML-based modeling language and a flexible data management approach is integrated to provide caching, persistence, a central communication hub, and a versioning mechanism. Combining various simulation techniques and data versioning, the nD forest simulation and information system can provide applications with historic 3D data in multiple time dimensions (hence nD) as well as with predicted data based on simulations.

scholarly journals DBE2 – Management of experimental data for the VANTED system

2011 ◽  
Vol 8 (2) ◽  
pp. 85-94
Author(s):  
Hendrik Mehlhorn ◽  
Falk Schreiber
Keyword(s):  
Experimental Data ◽  
Information System ◽  
Data Integration ◽  
Data Management ◽  
Data Storage ◽  
Controlled Vocabulary ◽  
Biological Experiment ◽  
Experiment Data ◽  
Measurement Units ◽  
Persistent Data

Summary DBE2 is an information system for the management of biological experiment data from different data domains in a unified and simple way. It provides persistent data storage, worldwide accessibility of the data and the opportunity to load, save, modify, and annotate the data. It is seamlessly integrated in the VANTED system as an add-on, thereby extending the VANTED platform towards data management. DBE2 also utilizes controlled vocabulary from the Ontology Lookup Service to allow the management of terms such as substance names, species names, and measurement units, aiming at an eased data integration.

Capturing sexual assault data: An information system designed by forensic clinicians and healthcare researchers

2017 ◽  
Vol 47 (1) ◽  
pp. 46-55 ◽  
Author(s):  
S Aqif Mukhtar ◽  
Debbie A Smith ◽  
Maureen A Phillips ◽  
Maire C Kelly ◽  
Renate R Zilkens ◽  
...  
Keyword(s):  
Information System ◽  
Sexual Assault ◽  
Data Management ◽  
Sexual Violence ◽  
Western Australia ◽  
Management System ◽  
Data Management System ◽  
Quality Data ◽  
High Quality ◽  
High Quality Data

Background: The Sexual Assault Resource Center (SARC) in Perth, Western Australia provides free 24-hour medical, forensic, and counseling services to persons aged over 13 years following sexual assault. Objective: The aim of this research was to design a data management system that maintains accurate quality information on all sexual assault cases referred to SARC, facilitating audit and peer-reviewed research. Methods: The work to develop SARC Medical Services Clinical Information System (SARC-MSCIS) took place during 2007–2009 as a collaboration between SARC and Curtin University, Perth, Western Australia. Patient demographics, assault details, including injury documentation, and counseling sessions were identified as core data sections. A user authentication system was set up for data security. Data quality checks were incorporated to ensure high-quality data. Results: An SARC-MSCIS was developed containing three core data sections having 427 data elements to capture patient’s data. Development of the SARC-MSCIS has resulted in comprehensive capacity to support sexual assault research. Four additional projects are underway to explore both the public health and criminal justice considerations in responding to sexual violence. The data showed that 1,933 sexual assault episodes had occurred among 1881 patients between January 1, 2009 and December 31, 2015. Sexual assault patients knew the assailant as a friend, carer, acquaintance, relative, partner, or ex-partner in 70% of cases, with 16% assailants being a stranger to the patient. Conclusion: This project has resulted in the development of a high-quality data management system to maintain information for medical and forensic services offered by SARC. This system has also proven to be a reliable resource enabling research in the area of sexual violence.

scholarly journals Fine-grained, spatio-temporal datasets measuring 200 years of land development in the United States

2020 ◽  
Author(s):  
Johannes H. Uhl ◽  
Stefan Leyk ◽  
Caitlin M. McShane ◽  
Anna E. Braswell ◽  
Dylan S. Connor ◽  
...  
Keyword(s):  
United States ◽  
Temporal Resolution ◽  
Data Extraction ◽  
Historical Analysis ◽  
Land Development ◽  
Remote Sensing Data ◽  
The United States ◽  
Building Stock ◽  
Fine Grained ◽  
Spatio Temporal

Abstract. The collection, processing and analysis of remote sensing data since the early 1970s has rapidly improved our understanding of change on the Earth’s surface. While satellite-based earth observation has proven to be of vast scientific value, these data are typically confined to recent decades of observation and often lack important thematic detail. Here, we advance in this arena by constructing new spatially-explicit settlement data for the United States that extend back to the early nineteenth century, and is consistently enumerated at fine spatial and temporal granularity (i.e., 250 m spatial, and 5 a temporal resolution). We create these time series using a large, novel building stock database to extract and map retrospective, fine-grained spatial distributions of built-up properties in the conterminous United States from 1810 to 2015. From our data extraction, we analyse and publish a series of gridded geospatial datasets that enable novel retrospective historical analysis of the built environment at unprecedented spatial and temporal resolution. The datasets are available at https://dataverse.harvard.edu/dataverse/hisdacus (Uhl and Leyk, 2020a, b, c, d).

Sign in / Sign up

Export Citation Format

Share Document