The 3rd ACM SIGSPATIAL International Workshop on Geospatial Simulation

2021 ◽  
Vol 12 (3) ◽  
pp. 11-14
Author(s):  
Joon-Seok Kim ◽  
Taylor Anderson ◽  
Ashwin Shashidharan ◽  
Andreas Züfle
Keyword(s):  
Spatial Data ◽  
International Workshop ◽  
Data Sources ◽  
Relative Location ◽  
Technological Changes ◽  
Research Opportunities ◽  
New Methodologies ◽  
New Research

Space has long been acknowledged by researchers as a fundamental constraint which shapes our world. As technological changes have transformed the very concept of distance, the relative location and connectivity of geospatial phenomena have remained stubbornly significant in how systems function. At the same time, however, technology has advanced the science of geospatial simulation to bear on our understanding of how such systems work. While previous generations of scientists and practitioners were unable to gather spatial data or to incorporate it into models at any meaningful scale, new methodologies and data sources are becoming increasingly available to researchers, developers, users, and practitioners. These developments present new research opportunities for geospatial simulation.

The 2nd ACM SIGSPATIAL International Workshop on Spatial Gems

2021 ◽  
Vol 12 (3) ◽  
pp. 32-34
Author(s):  
John Krumm ◽  
Cyrus Shahabi ◽  
Andreas Züfle
Keyword(s):  
Spatial Data ◽  
International Workshop ◽  
New Techniques ◽  
Research Results ◽  
New Research

Researchers and practitioners working with spatial data often develop fundamental new techniques they would like to share with their community. These are not necessarily new research results, not yet in any textbook, but they are interesting, self-contained techniques for doing something useful in the domain of spatial data. We call these techniques "spatial gems".

scholarly journals Cropland Abandonment in Slovakia: Analysis and Comparison of Different Data Sources

Land ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 334
Author(s):  
Juraj Lieskovský ◽  
Dana Lieskovská
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Spatial Data ◽  
Data Sources ◽  
Communist Regime ◽  
Corine Land Cover ◽  
Cropland Area ◽  
Cropland Abandonment ◽  
Multi Temporal

This study compares different nationwide multi-temporal spatial data sources and analyzes the cropland area, cropland abandonment rates and transformation of cropland to other land cover/land use categories in Slovakia. Four multi-temporal land cover/land use data sources were used: The Historic Land Dynamics Assessment (HILDA), the Carpathian Historical Land Use Dataset (CHLUD), CORINE Land Cover (CLC) data and Landsat images classification. We hypothesized that because of the different spatial, temporal and thematic resolution of the datasets, there would be differences in the resulting cropland abandonment rates. We validated the datasets, compared the differences, interpreted the results and combined the information from the different datasets to form an overall picture of long-term cropland abandonment in Slovakia. The cropland area increased until the Second World War, but then decreased after transition to the communist regime and sharply declined following the 1989 transition to an open market economy. A total of 49% of cropland area has been transformed to grassland, 34% to forest and 15% to urban areas. The Historical Carpathian dataset is the more reliable long-term dataset, and it records 19.65 km2/year average cropland abandonment for 1836–1937, 154.44 km2/year for 1938–1955 and 140.21 km2/year for 1956–2012. In comparison, the Landsat, as a recent data source, records 142.02 km2/year abandonment for 1985–2000 and 89.42 km2/year for 2000–2010. These rates, however, would be higher if the dataset contained urbanisation data and more precise information on afforestation. The CORINE Land Cover reflects changes larger than 5 ha, and therefore the reported cropland abandonment rates are lower.

Modeling and Implementation of Inter-Campuses Equipment Optimized Management Based on WebGIS

2013 ◽  
Vol 680 ◽  
pp. 534-539
Author(s):  
Wei Feng Ma
Keyword(s):  
Information Management ◽  
Spatial Data ◽  
Large Scale ◽  
New Technology ◽  
Rapid Expansion ◽  
Mathematics Model ◽  
Data Mapping ◽  
Geographically Dispersed ◽  
New Research ◽  
Research Challenge

With the rapid expansion of the campus scale and the increasing of the geographically dispersed campus, how to adopt new theory, new method and new technology to realize the equipment optimized assignment and the information management is a new research challenge. It is the key to safeguard the national fund to use reasonably, and to speed up the development of education healthily. Through analyzing the domestic and foreign related research works, the paper proposed that it can take use of the spatial data expression and analysis with Geographic Information System (GIS) to realize the large-scale and inter-campuses equipment optimized assignment and information management. It discussed the mathematics model and the system architecture. Moreover, the paper described the key implementation technology in great detail such as spatial data mapping with MapInfo professional 9 and the development of WebGIS functions with MapXtreme. The results show that the solution is feasible and effective.

First Results from the VULCAN Diffractometer at the SNS

2010 ◽  
Vol 652 ◽  
pp. 105-110 ◽  
Author(s):  
X.L. Wang ◽  
Thomas Holden ◽  
A.D. Stoica ◽  
K. An ◽  
H.D. Skorpenske ◽  
...  
Keyword(s):  
Neutron Beam ◽  
Research Opportunities ◽  
Instrument Performance ◽  
Measurement Results ◽  
First Results ◽  
Design Calculations ◽  
New Research ◽  
First Time

On Friday June 26, 2009, the neutron beam shutter for the VULCAN diffractometer at the SNS was opened for the first time. Initial measurements to characterize the instrument performance are reported. It is shown that the measurement results are by and large in agreement with design calculations. New research opportunities with VULCAN are discussed.

Web Scraping for Hospitality Research: Overview, Opportunities, and Implications

2020 ◽  
pp. 193896552097358
Author(s):  
Saram Han ◽  
Christopher K. Anderson
Keyword(s):  
Data Sources ◽  
Analytical Models ◽  
Online Data ◽  
Travel Agents ◽  
Web Scraping ◽  
Travel Services ◽  
New Research ◽  
Online Travel ◽  
Online Travel Agents ◽  
Tools And Methods

As consumers increasingly research and purchase hospitality and travel services online, new research opportunities have become available to hospitality academics. There is a growing interest in understanding the online travel marketplace among hospitality researchers. Although many researchers have attempted to better understand the online travel market through the use of analytical models, experiments, or survey collection, these studies often fail to capture the full complexity of the market. Academics often rely upon survey data or experiments owing to their ease of collection or potentially to the difficulty in assembling online data. In this study, we hope to equip hospitality researchers with the tools and methods to augment their traditional data sources with the readily available data that consumers use to make their travel choices. In this article, we provide a guideline (and Python code) for how to best collect/scrape publicly available online hotel data. We focus on the collection of online data across numerous platforms, including online travel agents, review sites, and hotel brand sites. We outline some exciting possibilities regarding how these data sources might be utilized, as well as discuss some of the caveats that have to be considered when analyzing online data.

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