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.

GIS and Spatial Analysis

2011 ◽  
pp. 146-173
Author(s):  
Andrew Curtis ◽  
Michael Leitner
Keyword(s):  
Spatial Analysis ◽  
Spatial Data ◽  
Birth Outcome ◽  
Academic Training ◽  
Academic Environment ◽  
Gis Analysis ◽  
Community Programs ◽  
Analysis Techniques ◽  
Statistical Approaches ◽  
Insight Into

n the opening chapters, GIS was broken into four general components, one of which was the spatial analysis of data. This is probably the least utilized of all GIS functions outside of an academic environment. A point that is often missed when discussing GIS is that the technology often exceeds the capabilities of the user. This is especially true if the user has not received any academic training in spatial data and GIS use. In Chapter VI a more sophisticated overview will be presented of the latest spatial analysis techniques along with examples of their implementation. Although the number of “spatially” trained scientists continues to grow, there is still a gap between the number of available skilled GIS modelers and the community programs needing GIS analysis. This chapter is designed to provide a stopgap approach, using more simple spatial statistical approaches that can be applied to gain a reasonable first insight into a birth outcome surface.

scholarly journals Adoption the basis of spatial analysis and geographic information systems (GIS) techniques to development oil industry projects

2014 ◽  
Vol 5 (1) ◽  
pp. 92-109
Author(s):  
Fanir Farooq O. Naji
Keyword(s):  
Decision Making ◽  
Spatial Analysis ◽  
Spatial Data ◽  
Information Age ◽  
Oil Industry ◽  
Project Planning ◽  
Digital Maps ◽  
The People ◽  
Calculation Processing ◽  
Analyze Data

It is recognized today that human lives the information age, which ischaracterized by the multiplicity of its data and the complexity of its aspects andthe most important thing is characterized by "information" that will determine theprogress of the people, the more able countries to devise ways to protect theinformation and how to make the best use of them whenever it is an indication ofits progress and its ability to face obstacles to development and the informationsources are diverse and interrelated up to the level of complexity that they can beanalyzed and dealt with the existence of developed computer systems, that storedand processed the information .And because maps are also considered sources ofinformation which use in management and project planning, and being animportant means of connecting ideas and planning them so it necessitated the needfor the emergence of advanced systems have the ability to draw and designschemes and production of digital maps. With possibility of linking information(metadata) with the real location on the Earth's surface, called the (spatial data).The emergence of these systems are scientific leap on the in geographic scienceespecially spatial data that has accumulated over the centuries and resulted in ahuge amount of data and information. These systems added a lot in the field ofbuilding spatial database which can updating and help in treating maps accuratelyand effectively combines the advantages of the two systems (information systemsand systems of digital maps), which was named "GIS" systems which electronic NO.10digital competent to enter, store and retrieve, analyze data . And connect themwith large areas of maps that can not be saved on security on the paper. The data issaved with maps in a coherent manner so as to facilitate the user to display the datawith maps and several methods as well as a calculation processing to extract theresults and reports in a few time and effort and use them in decision-making whichhelps to speed the study and analysis the information and support decision-makersin a number of important decisions concerning projects which requires accuracyand speed.

scholarly journals Segment-Based Spatial Analysis for Assessing Road Infrastructure Performance Using Monitoring Observations and Remote Sensing Data

2018 ◽  
Vol 10 (11) ◽  
pp. 1696 ◽  
Author(s):  
Yongze Song ◽  
Graeme Wright ◽  
Peng Wu ◽  
Dominique Thatcher ◽  
Tom McHugh ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Spatial Analysis ◽  
Spatial Data ◽  
Line Segment ◽  
Large Scale ◽  
Environmental Data ◽  
Road Infrastructure ◽  
Explanatory Variables ◽  
Infrastructure Performance ◽  
Pavement Damage

Road infrastructure is important to the well-being and economic health of all nations. The performance of road pavement infrastructure is sophisticated and affected by numerous factors and varies greatly across different roads. Large scale spatial analysis for assessing road infrastructure performance is increasingly required for road management, therefore multi-source factors, including satellite remotely sensed climate and environmental data, and ground-monitored vehicles observations, are collected as explanatory variables. Different from the traditional point or area based geospatial attributes, the performance of pavement infrastructure is the line segment based spatial data. Thus, a segment-based spatial stratified heterogeneity method is utilized to explore the comprehensive impacts of vehicles, climate, properties of road and socioeconomic conditions on pavement infrastructure performance. Segment-based optimal discretization is applied on discretizing segment-based pavement data, and a segment-based geographical detector is utilized to assess the spatial impacts of variables and their interactions. Results show that the segment-based methods can more reasonably and accurately describe the characteristics of line segment based spatial data and assess the spatial associations. The two major categories of factors associated with pavement damage are the variables of traffic vehicles and heavy vehicles in particular, and climate and environmental conditions. Meanwhile, the interactions between the explanatory variables in these two categories have much more influence than the single explanatory variables, and the interactions can explain more than half of the pavement damage. This study highlights the great potential of remote sensing based large scale spatial analysis of road infrastructures. The approach in this study provides new ideas for spatial analysis for segmented geographical data. The findings indicate that the quantified comprehensive impacts of variables are practical for wise decision-making for road design, construction and maintenance.

Etude de l'aménagement d'une forêt classée au Mali avec la participation des populations riveraines - Données du problème et éléments de méthodologie | A Study of the Management of a State-Owned Forest in Mali with the Participation of the Population Living nearby - Issue under Investigation and Elements of Methodology

2000 ◽  
Vol 151 (3) ◽  
pp. 80-83
Author(s):  
Pascal Schneider ◽  
Jean-Pierre Sorg
Keyword(s):  
Natural Resources ◽  
Research Methodology ◽  
Large Scale ◽  
Environmental Context ◽  
Forest Resources ◽  
The State ◽  
Commercial Use ◽  
Economic Context ◽  
The People

In and around the state-owned forest of Farako in the region of Sikasso, Mali, a large-scale study focused on finding a compromise allowing the existential and legitimate needs of the population to be met and at the same time conserving the forest resources in the long term. The first step in research was to sketch out the rural socio-economic context and determine the needs for natural resources for autoconsumption and commercial use as well as the demand for non-material forest services. Simultaneously, the environmental context of the forest and the resources available were evaluated by means of inventories with regard to quality and quantity. According to an in-depth comparison between demand and potential, there is a differentiated view of the suitability of the forest to meet the needs of the people living nearby. Propositions for a multipurpose management of the forest were drawn up. This contribution deals with some basic elements of research methodology as well as with results of the study.

Popular Resource Sovereignty

2018 ◽  
Author(s):  
Leif Wenar
Keyword(s):  
Human Rights ◽  
Natural Resources ◽  
Large Scale ◽  
Good Reason ◽  
Resource Curse ◽  
Civil Conflict ◽  
Popular Sovereignty ◽  
State Sovereignty ◽  
The People ◽  
Rich Countries

Article 1 of both of the major human rights covenants declares that the people of each country “shall freely dispose of their natural wealth and resources.” This chapter considers what conditions would have to hold for the people of a country to exercise this right—and why public accountability over natural resources is the only realistic solution to the “resource curse,” which makes resource-rich countries more prone to authoritarianism, civil conflict, and large-scale corruption. It also discusses why cosmopolitans, who have often been highly critical of prerogatives of state sovereignty, have good reason to endorse popular sovereignty over natural resources. Those who hope for more cosmopolitan institutions should see strengthening popular resource sovereignty as the most responsible path to achieving their own goals.

scholarly journals Efficient Approximate Range Aggregation over Large-scale Spatial Data Federation

2021 ◽  
pp. 1-1
Author(s):  
Yexuan Shi ◽  
Yongxin Tong ◽  
Yuxiang Zeng ◽  
Zimu Zhou ◽  
Bolin Ding ◽  
...  
Keyword(s):  
Spatial Data ◽  
Large Scale ◽  
Data Federation

scholarly journals Spatial Agglomeration of China’s Forest Products Manufacturing Industry: Measurement, Characteristics and Determinants

Forests ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1006
Author(s):  
Zhenhuan Chen ◽  
Hongge Zhu ◽  
Wencheng Zhao ◽  
Menghan Zhao ◽  
Yutong Zhang
Keyword(s):  
Spatial Distribution ◽  
Spatial Data ◽  
Large Scale ◽  
Manufacturing Industry ◽  
Economies Of Scale ◽  
Forest Products ◽  
Spatial Data Analysis ◽  
Forest Protection ◽  
Spatial Agglomeration ◽  
Continuous Space

China’s forest products manufacturing industry is experiencing the dual pressure of forest protection policies and wood scarcity and, therefore, it is of great significance to reveal the spatial agglomeration characteristics and evolution drivers of this industry to enhance its sustainable development. Based on the perspective of large-scale agglomeration in a continuous space, in this study, we used the spatial Gini coefficient and standard deviation ellipse method to investigate the spatial agglomeration degree and location distribution characteristics of China’s forest products manufacturing industry, and we used exploratory spatial data analysis to investigate its spatial agglomeration pattern. The results show that: (1) From 1988 to 2018, the degree of spatial agglomeration of China’s forest products manufacturing industry was relatively low, and the industry was characterized by a very pronounced imbalance in its spatial distribution. (2) The industry has a very clear core–periphery structure, the spatial distribution exhibits a “northeast-southwest” pattern, and the barycenter of the industrial distribution has tended to move south. (3) The industry mainly has a high–high and low–low spatial agglomeration pattern. The provinces with high–high agglomeration are few and concentrated in the southeast coastal area. (4) The spatial agglomeration and evolution characteristics of China’s forest products manufacturing industry may be simultaneously affected by forest protection policies, sources of raw materials, international trade and the degree of marketization. In the future, China’s forest products manufacturing industry should further increase the level of spatial agglomeration to fully realize the economies of scale.

scholarly journals TreeMerge: a new method for improving the scalability of species tree estimation methods

2019 ◽  
Vol 35 (14) ◽  
pp. i417-i426 ◽  
Author(s):  
Erin K Molloy ◽  
Tandy Warnow
Keyword(s):  
Large Scale ◽  
Species Tree ◽  
New Method ◽  
Divide And Conquer ◽  
Supplementary Information ◽  
Estimation Methods ◽  
Running Time ◽  
Tree Estimation ◽  
Computationally Intensive ◽  
A Minor

Abstract Motivation At RECOMB-CG 2018, we presented NJMerge and showed that it could be used within a divide-and-conquer framework to scale computationally intensive methods for species tree estimation to larger datasets. However, NJMerge has two significant limitations: it can fail to return a tree and, when used within the proposed divide-and-conquer framework, has O(n5) running time for datasets with n species. Results Here we present a new method called ‘TreeMerge’ that improves on NJMerge in two ways: it is guaranteed to return a tree and it has dramatically faster running time within the same divide-and-conquer framework—only O(n2) time. We use a simulation study to evaluate TreeMerge in the context of multi-locus species tree estimation with two leading methods, ASTRAL-III and RAxML. We find that the divide-and-conquer framework using TreeMerge has a minor impact on species tree accuracy, dramatically reduces running time, and enables both ASTRAL-III and RAxML to complete on datasets (that they would otherwise fail on), when given 64 GB of memory and 48 h maximum running time. Thus, TreeMerge is a step toward a larger vision of enabling researchers with limited computational resources to perform large-scale species tree estimation, which we call Phylogenomics for All. Availability and implementation TreeMerge is publicly available on Github (http://github.com/ekmolloy/treemerge). Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Potential Energy Implications of Connected and Automated Vehicles: Exploring Key Leverage Points through Scenario Screening and Analysis

2019 ◽  
Vol 2673 (5) ◽  
pp. 84-94 ◽  
Author(s):  
Brian Bush ◽  
Laura Vimmerstedt ◽  
Jeff Gonder
Keyword(s):  
Systems Engineering ◽  
Large Scale ◽  
Operating Cost ◽  
Dynamics Model ◽  
Transportation Service ◽  
Service Outcomes ◽  
Behavioral Parameters ◽  
Computationally Intensive ◽  
Different Levels ◽  
Selection Of

Connected and automated vehicle (CAV) technologies could transform the transportation system over the coming decades, but face vehicle and systems engineering challenges, as well as technological, economic, demographic, and regulatory issues. The authors have developed a system dynamics model for generating, analyzing, and screening self-consistent CAV adoption scenarios. Results can support selection of scenarios for subsequent computationally intensive study using higher-resolution models. The potential for and barriers to large-scale adoption of CAVs have been analyzed using preliminary quantitative data and qualitative understandings of system relationships among stakeholders across the breadth of these issues. Although they are based on preliminary data, the results map possibilities for achieving different levels of CAV adoption and system-wide fuel use and demonstrate the interplay of behavioral parameters such as how consumers value their time versus financial parameters such as operating cost. By identifying the range of possibilities, estimating the associated energy and transportation service outcomes, and facilitating screening of scenarios for more detailed analysis, this work could inform transportation planners, researchers, and regulators.

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