M a y / J u n e 1 9 9 8 I E E E S o f t w a r e 3 1 uery and analysis lie at the heart of a geographic information system.1 The ability to analyze geographical patterns and relationships differentiates GISs from computer cartography, computer-aided design, remote sensing, and database management. Computer scientists have researched relational database query languages for more than a decade, but...

Emerging technologies will change the future use of geographic information systems (GISs), moving GISs from the office desktops into the users’ hands. Current GIS architectures focus on a static environment in which a user sits at a workstation to perform spatial analysis. With the advent of ubiquitous computing, this setting will change dramatically. Devices that combine a hand-held computer w...

BACKGROUND Analyzing and visualizing health-related databases using Geographic Information Systems (GISs) becomes essential in controlling many public health problems. OBJECTIVES To explore the perception and preferences of public health professionals (PHPs) about the usability of GISs in public health field. METHODS For this scoping review, the investigators searched Medline Ovid, PubMed, ...

Introduction This book presents methods for spatial data modeling, algorithms, access methods, and query processing. The main focus is on extending DBMS technology to accommodate spatial data. The book also includes spatial methods used in Geographic Information Systems (GISs). Historically, GISs developed separately from Database systems. GISs are specialized in all aspects of spatial data han...

Due to the vast variety of geo-scientific tasks it is hardly imaginable that all of them could be solved within a single GIS. There will be always a need for special-purpose applications which could solve tasks not good enough covered by established GISs. It is natural for such application to benefit from general geoscientific data already accumulated in standard GISs. However, these data are n...

Simulations of the CMIP6 historical period 1850–2014, characterized by emergence anthropogenic climate drivers like greenhouse gases, are presented for different configurations NASA Goddard Institute Space Studies (GISS) Earth System ModelE2.1. The GISS-E2.1 ensembles more sensitive to gas forcing than their CMIP5 predecessors (GISS-E2) but warm less during recent decades due a reduction that i...

Simulations of preindustrial, present-day, and 2100 conditions in the NASA GISS composition and climate model G-PUCCINI D. T. Shindell, G. Faluvegi, N. Unger, E. Aguilar, G. A. Schmidt, D. M. Koch, S. E. Bauer, and R. L. Miller NASA Goddard Institute for Space Studies, New York, NY, USA Center for Climate Systems Research, Columbia University, NY, USA Dept. of Geophysics, Yale University, New H...

As geospatial data grows explosively, needs for the incorporation of data mining techniques into Geographic Information Systems (GISs) are in great demand. Association rules mining is a core technique in data mining and is a solid candidate for the cause-effect analysis of large geospatial databases. It efficiently detects frequent asymmetric causal patterns in large databases. In this paper, w...

Mixed probabilistic and deterministic graphical models are ubiquitous in real-world applications. Unfortunately, Gibbs sampling, a popular MCMC technique, does not converge to the correct answers in presence of determinism and therefore cannot be used for inference in such models. In this paper, we propose to remedy this problem by combining Gibbs sampling with SampleSearch, an advanced importa...