Mathematical and GIS-Modeling of Landslides in Kharkiv Region of Ukraine

2013 ◽  
pp. 347-352 ◽  
Author(s):  
Oleksandr Trofymchuk ◽  
Yuriy Kalyukh ◽  
Hanna Hlebchuk
Keyword(s):  
Gis Modeling

Economical exposition to drought events (1980-2001)

2017 ◽  
Author(s):  
Chloé Meyer
Keyword(s):  
World Bank ◽  
Standardized Precipitation Index ◽  
Research Unit ◽  
Precipitation Index ◽  
Climatic Research Unit ◽  
Columbia University ◽  
East Anglia ◽  
Gis Modeling ◽  
The World Bank ◽  
Year 2000

Estimation of the annual economical exposition to drought based on Standardized Precipitation Index. It is based on three sources: 1) A global monthly gridded precipitation dataset obtained from the Climatic Research Unit (University of East Anglia). 2) A GIS modeling of global Standardized Precipitation Index based on Brad Lyon (IRI, Columbia University) methodology. 3) A Global Domestic Product grid for the year 2010, provided by the World Bank. Unit is expected average annual GDP (2007 as the year of reference) exposed in (US $, year 2000 equivalent). For more information, visit: http://preview.grid.unep.ch/ Cost Drought Exposure Risk

Comparative analysis of the distribution and habitats of two Eremias species (Reptilia, Lacertidae) using niche-based GIS modeling

2019 ◽  
Vol 26 (5) ◽  
pp. 281
Author(s):  
Tatjana N. Dujsebayeva ◽  
Dmitry V Malakhov ◽  
Nikolay N. Berezovikov ◽  
Xianguang Guo ◽  
Jinlong Liu ◽  
...  
Keyword(s):  
Comparative Analysis ◽  
Gis Modeling

GIS modeling of lithic procurement in highlands: Archaeological and actualistic approach in the Andes

2021 ◽  
Vol 38 ◽  
pp. 103026
Author(s):  
Gustavo F. Lucero ◽  
Silvina C. Castro ◽  
Valeria Cortegoso
Keyword(s):  
Gis Modeling ◽  
Lithic Procurement ◽  
The Andes

Relocation selection for poverty alleviation: Factor analysis and GIS modeling

2011 ◽  
Vol 8 (3) ◽  
pp. 466-475 ◽  
Author(s):  
Yimin Li ◽  
Haihong Yin ◽  
Suhong Liu
Keyword(s):  
Factor Analysis ◽  
Poverty Alleviation ◽  
Gis Modeling ◽  
Selection For

Integrating economic, environmental and GIS modeling to target cost effective land retirement in multiple watersheds

2003 ◽  
Vol 46 (2) ◽  
pp. 249-267 ◽  
Author(s):  
Wanhong Yang ◽  
Madhu Khanna ◽  
Richard Farnsworth ◽  
Hayri Önal
Keyword(s):  
Cost Effective ◽  
Gis Modeling ◽  
Target Cost ◽  
Land Retirement

scholarly journals A Spatial Analysis Approach to Understanding Caddoan Mounds in the Arkansas River Drainage

2004 ◽  
Author(s):  
Gregory Vogel
Keyword(s):  
Spatial Analysis ◽  
Spatial Data ◽  
Large Scale ◽  
Theoretical Background ◽  
Gis Analysis ◽  
Arkansas River ◽  
Gis Modeling ◽  
River Drainage ◽  
The People ◽  
Computationally Intensive

In this article I present a theoretical framework for understanding Caddoan mounds in the central Arkansas River drainage and the implications they may hold for the social structure and environmental adaptations of the people who made them. The power and efficiency of Geographic Information Systems (GIS) modeling now allows for large-scale, computationally intensive spatial analysis simply not possible before. Questions of landscape organization or spatial relationships that previously would have taken months or even years to answer can now be solved in a matter of minutes with GIS and related technologies, given the appropriate datasets. Quite importantly, though, such analyses must first be placed in context and theory if they are to be meaningful additions to our understanding of the past. While it is conventional to refer to “GIS analysis” (and I use the term in this article), it is important to keep in mind that data manipulations alone are not analysis. GIS, along with statistical software and related computer technologies, are tools of spatial analysis just as shovels and trowels are tools of excavation. Such tools can organize and reveal information if they are employed carefully, but the tools themselves have no agency and cannot interpret anything on their own. The terms “GIS analysis” or “GIS interpretation” are therefore somewhat misnomers, just as “trowel analysis” or “trowel interpretation” would be. It is not the GIS, or any component of it, that does the analysis or interpretation; it simply manipulates spatial data. We interpret these manipulations based upon theoretical background, previous research, and the questions we wish to answer.

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