Rapid WUI growth in a natural amenity-rich region in central-western Patagonia, Argentina

2019 ◽  
Vol 28 (7) ◽  
pp. 473 ◽  
Author(s):  
Maria Marcela Godoy ◽  
Sebastian Martinuzzi ◽  
H. Anu Kramer ◽  
Guillermo E. Defossé ◽  
Juan Argañaraz ◽  
...  
Keyword(s):  
Census Data ◽  
Developed Countries ◽  
Environmental Conflicts ◽  
Natural Amenities ◽  
Housing Growth ◽  
High Resolution Imagery ◽  
Land Cover Data ◽  
Balance Development ◽  
Natural Amenity ◽  
Fire Ignition

The wildland–urban interface (WUI) is a focal area for human environmental conflicts including wildfires. The WUI grows because new houses are built, and in developed countries, housing growth can be very rapid in areas with natural amenities. However, it is not clear if natural amenity-driven WUI growth is limited to developed countries, or also prevalent in developing countries. Amenity-driven WUI growth may be particularly rapid there, owing to a rapidly growing middle class. Our objectives were to (i) map the current WUI; (ii) quantify recent WUI growth; and (iii) analyse relationships between the WUI and both fire ignition points and wildfire perimeters in the region of El Bolson, in Central Andean Patagonia, Argentina. We mapped the current WUI based on housing information derived from census data, topographic maps, high-resolution imagery and land-cover data. We found that the WUI contained 96.6% of all buildings in 2016 even though the WUI covered only 6.4% of the study area. Between 1981 and 2016, the WUI increased in area by 76%, and the number of houses by 74%. Furthermore, 77% of the recent fires in the region occurred in the WUI, highlighting the need to balance development with wildfire risk and other human–environmental problems.

scholarly journals Monitoring Urban Sprawl Using Time-Series Data: Famagusta Region of Northern Cyprus

SAGE Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 215824402110074
Author(s):  
Kamyar Fuladlu ◽  
Müge Riza ◽  
Mustafa Ilkan
Keyword(s):  
Time Series ◽  
Urban Sprawl ◽  
Census Data ◽  
Time Series Data ◽  
Developed Countries ◽  
Geographical Information ◽  
Series Data ◽  
Great Success ◽  
European Cities ◽  
Northern Cyprus

Monitoring urban sprawl is a controversial topic among scholars. Many studies have tried to employ various methods for monitoring urban sprawl in cases of North American and Northern and Western European cities. Although numerous methods have been applied with great success in various developed countries, they are predominantly impractical for cases of developing Mediterranean European cities that lack reliable census data. Besides, the complexity of the methods made them difficult to perform in underfunded situations. Therefore, this study aims to develop a new multidimensional method that researchers and planners can apply readily in developing Mediterranean European cities. The new method was tested in the Famagusta region of Northern Cyprus, which has been experiencing unplanned growth for the past half-century. In support of this proposal, a detailed review of the existing literature is presented with an emphasis on urban sprawl characteristics. Four characteristics were chosen to monitor urban sprawl’s development in the Famagusta region. The method was structured based on a time-series (2001, 2006, 2011, and 2016) dataset that used remote sensing data and geographical information systems to monitor the urban sprawl. Based on the findings, the Famagusta region experienced rapid growth during the last 15 years. The lack of a masterplan resulted in the uncontrolled expansion of the city in the exurban areas. The development configuration was polycentric and linear in form with single-use composition. Together, the expansion and configuration manifested as more built-up area, scattered development, and increased automobile dependency.

scholarly journals Estimation of Determinants of Farmland Abandonment and Its Data Problems

Land ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 596
Author(s):  
Shinichi Kitano
Keyword(s):  
Census Data ◽  
Evaluation Research ◽  
Developed Countries ◽  
Third Party ◽  
Objective Data ◽  
Farmland Abandonment ◽  
Subjective Data ◽  
Research Attention ◽  
Abandoned Farmland ◽  
The Impact

Abandoned farmland is particularly problematic in developed countries where agriculture has a comparative disadvantage in terms of effective use of land resources invested over time. While many studies have estimated the causes of these problems, few have discussed in detail the impact of data characteristics and accuracy on the estimation results. In this study, issues related to the underlying data and the estimation of the determinants of farmland abandonment were examined. Most previous studies on farmland abandonment in Japan have used census data as the basis of their analyses. However, census data are recorded subjectively by farmers. To address this, surveys of abandoned farmland are being conducted by a third party, and the results are compiled into a geographic information system (GIS) database. Two types of datasets (subjective census data and objective GIS data) were examined for their estimation performance. Although the two sets of data are correlated, there are considerable differences between them. Subjective variables are compatible with subjective data, and objective variables are compatible with objective data (meaning that parameters are easily identified). Original data for analysis, such as policy variables, are compatible with objective data. In policy evaluation research, attention should be paid to objective data collection.

scholarly journals Assessment of land cover on soil erosion in Lam Phra Phloeng watershed by USLE model

2018 ◽  
Vol 192 ◽  
pp. 02017 ◽  
Author(s):  
Jatuwat Wattanasetpong ◽  
Uma Seeboonruang ◽  
Uba Sirikaew ◽  
Walter Chen
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Land Cover ◽  
Soil Loss ◽  
Land Development ◽  
Developed Countries ◽  
Surface Erosion ◽  
Agricultural Field ◽  
Land Cover Data

Soil loss due to surface erosion has been a global problem not just for developing countries but also for developed countries. One of the factors that have greatest impact on soil erosion is land cover. The purpose of this study is to estimate the long-term average annual soil erosion in the Lam Phra Phloeng watershed, Nakhon Ratchasima, Thailand with different source of land cover by using the Universal Soil Loss Equation (USLE) and GIS (30 m grid cells) to calculate the six erosion factors (R, K, L, S, C, and P) of USLE. Land use data are from Land Development Department (LDD) and ESA Climate Change Initiative (ESA/CCI) in 2015. The result of this study show that mean soil erosion by using land cover from ESA/CCI is less than LDD (29.16 and 64.29 ton/ha/year respectively) because soil erosion mostly occurred in the agricultural field and LDD is a local department that survey land use in Thailand thus land cover data from this department have more details than ESA/CCI.

Indicators of Land Degradation Vulnerability due to Anthropic Factors

2013 ◽  
pp. 1400-1413 ◽  
Author(s):  
V. Imbrenda ◽  
M. D’Emilio ◽  
M. Lanfredi ◽  
M. Ragosta ◽  
T. Simoniello
Keyword(s):  
Land Management ◽  
Land Degradation ◽  
Resource Availability ◽  
Census Data ◽  
Vulnerability Index ◽  
Decision Makers ◽  
Accurate Estimation ◽  
Spatial Characterization ◽  
Land Cover Data ◽  
First Time

Land degradation is one of the most impacting phenomena on natural resource availability, both in quantitative and qualitative terms. In order to provide efficient tools for territorial sustainable management in areas affected by land degradation, it is important to define suitable models and indicators able to identify exposed areas and their vulnerability level, so as to provide an effective support for decision makers in identifying intervention priorities and planning mitigation/adaptation strategies. This work is focused on the evaluation at high spatial detail of land degradation vulnerability due to anthropic factors, which is a crucial issue in areas devoted to farming practices. Vulnerability is evaluated by integrating a new indicator of the mechanization level the authors recently developed, with a set of census based indicators of land management. The new indicator is independent of census data being based on land cover data; thus, it can provide a better spatial characterization and a more frequent updating compared to commonly adopted indices that are evaluated at municipal scale. By analyzing data for the whole Southern Italy, such an indicator was integrated for the first time at full spatial resolution to obtain a final vulnerability index of land management. This comprehensive index enabled a more accurate estimation of the land degradation vulnerability due to anthropic factors allowing the discrimination of priority areas within the municipal areas.

Indicators of Land Degradation Vulnerability Due to Anthropic Factors

2013 ◽  
pp. 87-101 ◽  
Author(s):  
V. Imbrenda ◽  
M. D’Emilio ◽  
M. Lanfredi ◽  
M. Ragosta ◽  
T. Simoniello
Keyword(s):  
Land Management ◽  
Land Degradation ◽  
Resource Availability ◽  
Census Data ◽  
Vulnerability Index ◽  
Decision Makers ◽  
Accurate Estimation ◽  
Spatial Characterization ◽  
Land Cover Data ◽  
First Time

Land degradation is one of the most impacting phenomena on natural resource availability, both in quantitative and qualitative terms. In order to provide efficient tools for territorial sustainable management in areas affected by land degradation, it is important to define suitable models and indicators able to identify exposed areas and their vulnerability level, so as to provide an effective support for decision makers in identifying intervention priorities and planning mitigation/adaptation strategies. This work is focused on the evaluation at high spatial detail of land degradation vulnerability due to anthropic factors, which is a crucial issue in areas devoted to farming practices. Vulnerability is evaluated by integrating a new indicator of the mechanization level the authors recently developed, with a set of census based indicators of land management. The new indicator is independent of census data being based on land cover data; thus, it can provide a better spatial characterization and a more frequent updating compared to commonly adopted indices that are evaluated at municipal scale. By analyzing data for the whole Southern Italy, such an indicator was integrated for the first time at full spatial resolution to obtain a final vulnerability index of land management. This comprehensive index enabled a more accurate estimation of the land degradation vulnerability due to anthropic factors allowing the discrimination of priority areas within the municipal areas.

scholarly journals Labor market integration of non-Chinese immigrants in Hong Kong from 1991 to 2011: Structure of global market or White privilege?

2018 ◽  
Vol 4 (1) ◽  
pp. 79-108 ◽  
Author(s):  
Yuying Tong ◽  
Wenyang Su ◽  
Eric Fong
Keyword(s):  
Hong Kong ◽  
Labor Market ◽  
Market Integration ◽  
White Privilege ◽  
Census Data ◽  
Chinese Immigrants ◽  
Developed Countries ◽  
Global Market ◽  
The North ◽  
Dominant Society

Previous studies of Hong Kong immigrants have largely focused on those Chinese from the mainland, and less attention has been paid to non-Chinese immigrants. As exceptions to this, a few studies have focused on the channels of non-Chinese immigrants to Hong Kong, but less research has examined their labor market outcomes. This is partly because theories about immigrants in Asia’s global city are underdeveloped, and the traditional labor market assimilation theory based on the North American and European experience may not easily translate to the case of global cities in Asia. In this research, we examine the employment status, occupational rank, and earnings outcomes of Chinese and non-Chinese immigrants from the perspectives of global economic structure and White privilege. Using 5% Hong Kong census/by-census data from 1991, 1996, 2001, 2006, and 2011, we draw two major conclusions. First, in the Hong Kong labor market, immigrants from more developed countries enjoy a labor market advantage, which demonstrates the advantages of core-nation origin. In contrast, their counterparts from peripheral nations are penalized. The labor market gap between immigrants from core nations and peripheral nations grew at the turn of the 21st century but narrowed in 2006. Second, White immigrants are privileged in the Hong Kong labor market, showing that White privilege has been transmitted to a non-White-dominant society.

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 Age Distribution Model For GCC Countries

2011 ◽  
Vol 8 (11) ◽  
Author(s):  
Shafiqur Rahman
Keyword(s):  
Goodness Of Fit ◽  
Census Data ◽  
Age Distribution ◽  
Developed Countries ◽  
Distribution Model ◽  
School Age Children ◽  
Population Census ◽  
Goodness Of Fit Test ◽  
Chi Square ◽  
Gcc Countries

Efficient and reliable estimates of the proportions of population at different age levels are essential for making quality budget of any developing or developed nation. These estimates are obtained from the best-fitted age distribution model and can be used to find the number of school age children, number of pensioners etc. Past population census data of GCC countries are analyzed to find the best-fitted age distribution model applying chi-square goodness of fit test and model selection criteria and observed that the age distribution of most of the GCC countries is exponential. A comparative study of the age distributions of six GCC countries with some developed countries is also provided.

scholarly journals Classifying settlement types from multi-scale spatial patterns of building footprints

2020 ◽  
pp. 239980832092120 ◽  
Author(s):  
Warren C Jochem ◽  
Douglas R Leasure ◽  
Oliver Pannell ◽  
Heather R Chamberlain ◽  
Patricia Jones ◽  
...  
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
Spatial Patterns ◽  
Gaussian Mixture ◽  
Developed Countries ◽  
Urban Morphology ◽  
Multi Scale ◽  
High Resolution Imagery ◽  
Very High Resolution Imagery ◽  
Very High

Urban settlements and urbanised populations continue to grow rapidly and much of this transition is occurring in less developed countries. Remote sensing techniques are now often applied to monitor urbanisation and changes in settlement patterns. In particular, increasing availability of very high resolution imagery (<1 m spatial resolution) and computing power is enabling complete sets of settlement data in the form of building footprints to be extracted from imagery. These settlement data provide information on the changes occurring in cities, particularly in countries which may lack other data on urbanisation. While spatially detailed, extracted building footprints typically lack other information that identify building types or can be used to differentiate intra-urban land uses or neighbourhood types. This work demonstrates an approach to classifying settlement types through multi-scale spatial patterns of urban morphology visible in building footprint data extracted from very high resolution imagery. The work uses a Gaussian mixture modelling approach to select and hierarchically merge components into clusters. The results are maps classifying settlement types on a high spatial resolution (100 m) grid. The approach is applied in Kaduna, Nigeria; Kinshasa, Democratic Republic of the Congo; and Maputo, Mozambique and demonstrates the potential of computational methods to take advantage of large spatial datasets and extract meaningful information to support monitoring of urban areas. The model-based approach produces a hierarchy of potential clustering solutions, and we suggest that this can be used in partnership with local knowledge of the context when creating settlement typologies.

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