Land Cover, Tenure Characteristics, and Rural Well-Being in a Black Belt County

2013 ◽  
Vol 4 (3) ◽  
pp. 19-38
Author(s):  
Janice F. Dyer ◽  
Luke Marzen ◽  
Diane Hite
Keyword(s):  
Land Cover ◽  
Land Tenure ◽  
Census Data ◽  
Well Being ◽  
Black Belt ◽  
Significant Relationships ◽  
Land Cover Data ◽  
Research Findings ◽  
Cultural Ecological ◽  
Property Tax Assessment

Landownership is an important form of wealth, especially in a natural-resource dependent region such as the Black Belt of Alabama. We examine the connection between property ownership, land cover, and the well-being of communities in Macon County, Alabama. This study is an exploratory application of geographic information systems to integrate information from property tax assessment records, land cover data, and a well-being index based on census data. Research questions regarding the relationships between socioeconomic well-being, land tenure, and land cover were tested on rural parcels 50 acres or larger (N=1418). Test results reveal statistically significant relationships between socioeconomic conditions and absentee ownership (both out-of-state and out-of-county) and land cover type (in particular, evergreen forestland). Analyses of research findings offer insight to the cultural-ecological connections within the Black Belt and prompts exploration of the notion of space as political.

scholarly journals Regionalisation of asset values for risk analyses

2006 ◽  
Vol 6 (2) ◽  
pp. 167-178 ◽  
Author(s):  
A. H. Thieken ◽  
M. Müller ◽  
L. Kleist ◽  
I. Seifert ◽  
D. Borst ◽  
...  
Keyword(s):  
Land Cover ◽  
Urban Areas ◽  
Large Scale ◽  
Census Data ◽  
Population Data ◽  
Dasymetric Mapping ◽  
Unit Value ◽  
Land Cover Data ◽  
Mapping Techniques ◽  
Asset Data

Abstract. In risk analysis there is a spatial mismatch of hazard data that are commonly modelled on an explicit raster level and exposure data that are often only available for aggregated units, e.g. communities. Dasymetric mapping techniques that use ancillary information to disaggregate data within a spatial unit help to bridge this gap. This paper presents dasymetric maps showing the population density and a unit value of residential assets for whole Germany. A dasymetric mapping approach, which uses land cover data (CORINE Land Cover) as ancillary variable, was adapted and applied to regionalize aggregated census data that are provided for all communities in Germany. The results were validated by two approaches. First, it was ascertained whether population data disaggregated at the community level can be used to estimate population in postcodes. Secondly, disaggregated population and asset data were used for a loss evaluation of two flood events that occurred in 1999 and 2002, respectively. It must be concluded that the algorithm tends to underestimate the population in urban areas and to overestimate population in other land cover classes. Nevertheless, flood loss evaluations demonstrate that the approach is capable of providing realistic estimates of the number of exposed people and assets. Thus, the maps are sufficient for applications in large-scale risk assessments such as the estimation of population and assets exposed to natural and man-made hazards.

scholarly journals AN AREA MERGING METHOD IN MAP GENERALIZATION CONSIDERING THE BOUNDARY CHARACTERISTICS OF STRUCTURED GEOGRAPHIC OBJECTS

2019 ◽  
Vol XLII-4/W16 ◽  
pp. 671-678
Author(s):  
P. D. Wu ◽  
Y. Yin ◽  
C. M. Li
Keyword(s):  
Land Cover ◽  
Experimental Validation ◽  
Census Data ◽  
Southern China ◽  
Global Perspective ◽  
Map Generalization ◽  
Land Cover Data ◽  
Geographic Object ◽  
Boundary Characteristics ◽  
Merging Method

Abstract. Merging is an important operation for the generalization of land-cover data. However, current research often entails merging on a global perspective, which is not conducive to capturing the spatial characteristics of geographic objects with significant spatial structures, i.e., structured geographic objects. As such, this paper proposes an area merging method that can maintain the boundary characteristics of the structured geographic objects. First, we identify the structured geographic objects based on the description parameters of the spatial structure. Second, a Miter-type buffer transformation is introduced to extract the boundary of each structured geographic object, and area elements inside the boundary are processed with corresponding merging operations. Finally, the boundary of the structured geographic objects and the merging result of the area elements are inserted back into the aggregated result of the original land-cover data using the NOT operation. The proposed approach is experimentally validated using geographical condition census data for a city in southern China. The experimental validation indicates that the proposed approach not only reasonably identify the typical characteristics of structured geographic objects but also effectively maintains the boundary characteristics of these objects.

scholarly journals AGGREGATION IN LAND-COVER DATA GENERALIZATION CONSIDERING SPATIAL STRUCTURE CHARACTERISTICS

2019 ◽  
Vol IV-4/W9 ◽  
pp. 111-118
Author(s):  
P. D. Wu ◽  
Y. Yin ◽  
C. M. Li ◽  
X. L. Liu
Keyword(s):  
Land Cover ◽  
Spatial Structure ◽  
Census Data ◽  
Southern China ◽  
Global Perspective ◽  
Experimental Result ◽  
Land Cover Data ◽  
Geographic Object ◽  
Boundary Characteristics ◽  
Data Generalization

Abstract. Aggregation is an important operation for the generalization of land-cover data. However, current research often entails aggregation on a global perspective, which is not conducive to capturing the spatial characteristics of geographic objects with significant spatial structures, i.e., structured geographic objects. Hence this paper proposes an area aggregation method that can maintain the boundary characteristics of the structured geographic objects. First, we identify the structured geographic objects based on the description parameters of the spatial structure. Second, a Miter-type buffer transformation is introduced to extract the boundary of each structured geographic object, and area elements inside the boundary are processed with corresponding aggregation operations. Finally, the boundary of the structured geographic objects and the aggregation result of the area elements are inserted back into the aggregated result of the original land-cover data using the NOT operation. The proposed approach is experimentally validated using geographical condition census data for a city in southern China. The experimental result indicates that the proposed approach not only reasonably identify the typical characteristics of structured geographic objects but also effectively maintains the boundary characteristics of these objects.

From Help Giving to Helping Relations

2018 ◽  
pp. 464-488
Author(s):  
Arie Nadler
Keyword(s):  
Well Being ◽  
Psychological Research ◽  
Psychological Needs ◽  
Social Psychological ◽  
Significant Relationships ◽  
Long Run ◽  
Help Giving ◽  
Social Psychological Research ◽  
Practical Implications

This chapter reviews social psychological research on help giving and helping relations from the 1950s until today. The first section considers the conditions under which people are likely to help others, personality dispositions that characterize helpful individuals, and motivational and attributional antecedents of helpfulness. The second section looks at long-term consequences of help and examines help in the context of enduring and emotionally significant relationships. Research has shown that in the long run help can increase psychological and physical well-being for helpers but discourage self-reliance for recipients. The third section analyzes helping from intra- and intergroup perspectives, considering how its provision can contribute to helpers’ reputations within a group or promote the positive social identity of in-groups relative to out-groups. Help is thus conceptualized as a negotiation between the fundamental psychological needs for belongingness and independence. Theoretical and practical implications are discussed.

scholarly journals “How Do We Actually Do Convergence” for Disaster Resilience? Cases from Australia and the United States

2021 ◽  
Author(s):  
Shefali Juneja Lakhina ◽  
Elaina J. Sutley ◽  
Jay Wilson
Keyword(s):  
United States ◽  
Research Policy ◽  
Well Being ◽  
The United States ◽  
First Century ◽  
Urban Resilience ◽  
South Wales ◽  
Systemic Risks ◽  
Work Community ◽  
Research Findings

AbstractIn recent years there has been an increasing emphasis on achieving convergence in disaster research, policy, and programs to reduce disaster losses and enhance social well-being. However, there remain considerable gaps in understanding “how do we actually do convergence?” In this article, we present three case studies from across geographies—New South Wales in Australia, and North Carolina and Oregon in the United States; and sectors of work—community, environmental, and urban resilience, to critically examine what convergence entails and how it can enable diverse disciplines, people, and institutions to reduce vulnerability to systemic risks in the twenty-first century. We identify key successes, challenges, and barriers to convergence. We build on current discussions around the need for convergence research to be problem-focused and solutions-based, by also considering the need to approach convergence as ethic, method, and outcome. We reflect on how convergence can be approached as an ethic that motivates a higher order alignment on “why” we come together; as a method that foregrounds “how” we come together in inclusive ways; and as an outcome that highlights “what” must be done to successfully translate research findings into the policy and public domains.

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