scholarly journals The Importance of Scale in Using Hierarchical Census Data to Identify the Wildland–Urban Interface

2007 ◽  
Vol 31 (3) ◽  
pp. 138-147 ◽  
Author(s):  
Yangjian Zhang ◽  
Michael C. Wimberly
Keyword(s):  
Spatial Pattern ◽  
Census Data ◽  
Urban Expansion ◽  
Multiple Scale ◽  
County Level ◽  
Census Block ◽  
Wildland Urban Interface ◽  
Small Unit ◽  
Block Level ◽  
Block Area

Abstract Census data in combination with GIS are increasingly being used to analyze urban expansion and develop models for identifying landscape change in the urban fringe. Census data are aggregated along the large-to-small-unit gradient of county, tract, census block group (CBG), and census block. The multiple scale availability often confounds the selection of an appropriate level of data in research pertinent to using census data. This study addressed the modifiable areal unit problem of census data through comparing spatial pattern and area of wildland-urban interface (WUI) determined at different levels of census aggregation (county, census tract, CBG, and census block). Total WUI area in each single year decreased along the shrinking census unit gradient from county to census block. Area converted from wildland to WUI between 1990 and 2000 decreased along the census gradient of the tract, CBG, census block, county level. The number of WUI patches decreased, and area of WUI patches increased along the decreasing census gradient of county, tract, CBG, block. In contrast to 60% of WUI blocks falling inside WUI CBGs or tracts, more than 80% of WUI tracts fell inside WUI counties, and 76.8% of WUI CBGs fell inside WUI tracts. WUI at the block level showed a different spatial pattern from those at the tract and CBG levels in that it represented more spatial detail. County-level data tended to overestimate WUI area while underestimating area converted to WUI. The study concluded that coarse sale data, such as those at the county level, were suitable for detecting a regional pattern. Fine-scale data, such as those at the census block level, need to be used in addressing issues at a landscape pattern.

scholarly journals Spatial Pattern and Driving Mechanism of Urban–Rural Income Gap in Gansu Province of China

Land ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1002
Author(s):  
Ping Zhang ◽  
Weiwei Li ◽  
Kaixu Zhao ◽  
Sidong Zhao
Keyword(s):  
Spatial Pattern ◽  
Development Planning ◽  
Gansu Province ◽  
Floating Population ◽  
Driving Mechanism ◽  
County Level ◽  
Income Gap ◽  
Rural Income ◽  
Group Matrix ◽  
Urban Rural

The urban–rural income gap is a principal indicator for evaluating the sustainable development of a region, and even the comprehensive strength of a country. The study of the urban–rural income gap and its changing spatial patterns and influence factors is an important basis for the formulation of integrated urban–rural development planning. In this paper, we conduct an empirical study on 84 county-level cities in Gansu Province by using various analysis tools, such as GIS, GeoDetector and Boston Consulting Group Matrix. The findings show that: (1) The urban–rural income gap in Gansu province is at a high level in spatial correlation and agglomeration, leading to the formation of a stepped and solidified spatial pattern. (2) Different factors vary greatly in influence, for example, per capita Gross Domestic Product, alleviating poverty policy and urbanization rate are the most prominent, followed by those such as floating population, added value of secondary industry and number of Internet users. (3) The driving mechanism becomes increasingly complex, with the factor interaction effect of residents’ income dominated by bifactor enhancement, and that of the urban–rural income gap dominated by non-linear enhancement. (4) The 84 county-level cities in Gansu Province are classified into four types of early warning zones, and differentiated policy suggestions are made in this paper.

Census-block-level Property Risk Assessment for Wildfire in Louisiana, U.S.A

2021 ◽  
Author(s):  
Rubayet Bin Mostafiz ◽  
Carol Friedland ◽  
Robert Rohli ◽  
Nazla Bushra
Keyword(s):  
Risk Assessment ◽  
Census Block ◽  
Block Level ◽  
Level Property

scholarly journals SolarView: Georgia Solar Adoption in Context

Data ◽  
2018 ◽  
Vol 3 (4) ◽  
pp. 61
Author(s):  
Jacqueline Tidwell ◽  
Abraham Tidwell ◽  
Steffan Nelson ◽  
Marcus Hill
Keyword(s):  
Census Data ◽  
Local Level ◽  
National Policy ◽  
Ecological Factors ◽  
Energy Transition ◽  
County Level ◽  
Solar Pv ◽  
Multiple Sources ◽  
Policy Goals ◽  
Transition Issues

The local-national gap is a problem currently plaguing the adoption of emerging technologies targeted at resolving energy transition issues that are characterized by disparities in the adoption of innovations and policies on a local level in response to national policy implementation. These disparities reflect a complex system of technical, economic, social, political, and ecological factors linked to the perceptions held by communities and how they see energy development and national/global policy goals. This dataset is an attempt to bridge the local-national gap regarding solar PV adoption in the State of Georgia (U.S.) by aggregating variables from seven different publicly-available sources. The objective of this activity was to design a resource that would help researchers interested in the context underlying solar adoption on the local scale of governance (e.g., the county level). The SolarView database includes information necessary for informing policy-making activities such as solar installation information, a historical county zip code directory, county-level census data, housing value indexes, renewable energy incentive totals, PV rooftop suitability percentages, and utility rates. As this is a database from multiple sources, incomplete data entries are noted.

scholarly journals Using Census Data to Understand County-Level Differences in Overall Drug Mortality and Opioid-Related Mortality by Opioid Type

2019 ◽  
Vol 109 (8) ◽  
pp. 1084-1091 ◽  
Author(s):  
Shannon M. Monnat ◽  
David J. Peters ◽  
Mark T. Berg ◽  
Andrew Hochstetler
Keyword(s):  
Census Data ◽  
County Level ◽  
Related Mortality

Quantifying Urban Expansion Using Landsat Images and Landscape Metrics: A Case Study of the Halton Region, Ontario

GEOMATICA ◽  
2020 ◽  
Author(s):  
Liyuan Qing ◽  
Hasti A. Petrosian ◽  
Sarah N. Fatholahi ◽  
Michael A. Chapman ◽  
Jonathan Li
Keyword(s):  
Landscape Metrics ◽  
Urban Areas ◽  
Census Data ◽  
Urban Expansion ◽  
Landsat Images ◽  
Factors Affecting ◽  
Supervised Learning Algorithms ◽  
Dramatic Rise ◽  
Multi Temporal ◽  
Gis Software

Urbanization is considered as one of the main factors affecting global change. The Halton Region as part of the Great Toronto Area (GTA), is regarded as one of the fastest growing regions in Canada, generating 20% of national GDP. It is also one of the most desirable places for living and thriving business. This research attempts to assess the urban expansion in the Halton Region, Ontario, Canada from 1989 to 2019 using satellite images, analysis approaches and landscape metrics. Multi-temporal Landsat images, and the supervised learning algorithms in GIS software were used to explore the dynamic changes, and to classify the urban and non-urban areas. The temporal urban expansion in the Halton Region experienced a dramatic rise, and mainly occurred from the centre of the area. The analysis of landscape metrics based on different methods, including Land Use in Central Indiana (LUCI) model, Vegetation-Impervious Surface-soil (V-I-S) model, and the census data of Canada was carried out to understand the transition mode of the urbanization in the Halton Region. Also, the population growth in the centre of the Halton Region was considered as one of driven forces affecting urban expansion. The results showed that most of the landscape metrics rose between 1989 and 2019, indicating leapfrog pattern of urbanization occurred over the entire period. The contribution of this research is to evaluate the urbanization in the Halton Region, and give the city managers a clear mind to make appropriate decisions in further urban planning.

scholarly journals Geography of racial coresidence

2021 ◽  
Author(s):  
Anna Dmowska ◽  
Tomasz Stepinski
Keyword(s):  
Metropolitan Areas ◽  
Data Driven ◽  
Racial Groups ◽  
Census Block ◽  
Asian Populations ◽  
Racial Preferences ◽  
Level Data ◽  
Geographical Regions ◽  
Block Level ◽  
Us Cities

Whereas most work on residential race relations in US cities is based on the concept of segregation, our approach studies this issue from a who-lives-with-whom perspective. To this end, we study coresidence profiles – percentages of a given racial subpopulation living in different population zones. Population zones are data-driven divisions of a city based on characteristic racial compositions. We used 1990 and 2010 decennial census block-level data for 61 largest US metropolitan areas to calculate coresidence profiles for four major racial subpopulations in each city at both years. Profiles for each race/year combination were clustered into three archetypes. Cities, where given race profiles belong to the same archetype, have similar coresidence patterns with respect to this race. We present the geographic distributions of co-habitation profiles and show how they changed during the 1990-2010 period. Our results revealed that coresidence profiles depend not only on racial preferences but also on the availability of racial groups; cities in the different geographical regions have different coresidence profiles because they have different shares of White, Black, Hispanic, and Asian subpopulations. Temporal changes in coresidence profiles are linked to the increased share of Hispanic and Asian populations.

scholarly journals CONSISTENCY IN REMOTE SENSING-BASED URBAN MAPPING FOR GROWTH AND MOBILITY ANALYSIS

2019 ◽  
Vol XLII-4/W16 ◽  
pp. 461-462
Author(s):  
L. Møller-Jensen ◽  
A. N. Allotey
Keyword(s):  
Remote Sensing ◽  
Census Data ◽  
Urban Expansion ◽  
Growth Dynamics ◽  
Transport Infrastructure ◽  
Flood Events ◽  
Mobility Analysis ◽  
Digital Road Maps ◽  
Road Maps ◽  
Initial Results

Abstract. This extended abstract presents initial results from a study that focus on the accuracy of satellite-based maps of Accra’s urban expansion as well as their comparability and ability to provide a basis for assessing urban spatial growth dynamics. Within the study we have analysed five different satellite-derived maps of urban development in Accra and compared the results and underlying methods. It is discussed how these maps can be operationalized and, combined with census data and digital road maps, used for calculating how flood events that disable parts of the transport infrastructure impact the overall mobility of the Accra population.

scholarly journals Spatial Pattern of Educational Development at Block Level in Jalore District, Rajasthan

2019 ◽  
Vol 06 (01) ◽  
pp. 160-164
Author(s):  
Shivani Swarnkar ◽  
Siddhartha Kumar Gaurav
Keyword(s):  
Spatial Pattern ◽  
Educational Development ◽  
Block Level
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