scholarly journals Prediction of Total Imperviousness from Population Density and Land Use Data for Urban Areas (Case Study: South East Queensland, Australia)

2021 ◽  
Vol 11 (21) ◽  
pp. 10044
Author(s):  
Mohammad Reza Ramezani ◽  
Bofu Yu ◽  
Yahui Che
Keyword(s):  
Land Use ◽  
Population Density ◽  
Urban Areas ◽  
Regression Models ◽  
Landsat 8 ◽  
World Population ◽  
Residential Areas ◽  
New Model ◽  
Impervious Area ◽  
The World

Total imperviousness (residential and non-residential) increases with population growth in many regions around the world. Population density has been used to predict the total imperviousness in large areas, although population size was only closely related to residential imperviousness. In this study, population density together with land use data for 154 suburbs in Southeast Queensland (SEQ) of Australia were used to develop a new model for total imperviousness estimation. Total imperviousness was extracted through linear spectral mixing analysis (LSMA) using Landsat 8 OLI/TIRS, and then separated into residential and non-residential areas based on land use data for each suburb. Regression models were developed between population density and total imperviousness, and population density and residential imperviousness. Results show that (1) LSMA approach could retrieve imperviousness accurately (RMSE < 10%), (2) linear regression models could be used to estimate both total imperviousness and residential imperviousness better than nonlinear regression models, and (3) correlation between population density and residential imperviousness was higher (R2 = 0.77) than that between population density and total imperviousness (R2 = 0.52); (4) the new model was used to predict the total imperiousness based on population density projections to 2057 for three potential urban development areas in SEQ. This research allows accurate prediction of the total impervious area from population density and service area per capital for other regions in the world.

scholarly journals MODELING THE DEVELOPMENTS IN URBANISATION AND RELATIONSHIP WITH VEGETATION COVER IN ALANYA

2021 ◽  
Vol XLVI-4/W5-2021 ◽  
pp. 291-297
Author(s):  
B. İşler ◽  
Z. Aslan
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Surface ◽  
Urban Areas ◽  
Vegetation Index ◽  
Landsat 8 ◽  
World Population ◽  
Land Use Land Cover ◽  
Temperature And Precipitation ◽  
Atmospheric Variables

Abstract. The increase in the world population and the migration of people from rural to urban areas causes an increase in artificial surfaces and causes many negative effects on the ecosystem, regional climate variations and global diversity. Nowadays, as the effects of climate change are felt more and more, it has gained importance in researches on this subject. Therefore, the estimation of the change in the vegetation density for the coming years and the determination of the land use / land cover (LULC) change in cities are very essential for urban planning. In this study, the effects of regional urbanization on vegetation are examined by using satellite data and atmospheric variables. In the vegetation analysis, multi-time index values obtained from TERRA-MODIS satellite, EVI (Enhanced Vegetation Index) and LST (Land Surface Temperature) were taken into account between the years of 2005 and 2018 in Alanya, Turkey. Temperature and precipitation were selected as the atmospheric variables and expected variations in EVI value until 2030 were estimated. In the study employed a wavelet-transformed artificial neural network (WANN) model to generate long-term (12-year) EVI forecasts using LST, temperature and precipitation. The relationship between land use / land cover and urbanization is investigated with NDBI (Normalized Difference Built-up Index) data obtained from the Landsat 8 OLI / TIRS satellite sensor. The simulation results show that The EVI value, which was 0.30 in 2018, will decrease to 0.25 in 2030.

scholarly journals Spatial-Temporal Land Use and Land Cover Changes in Urban Areas Using Remote Sensing Images and GIS Analysis: The Case Study of Opole, Poland

Geosciences ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 312
Author(s):  
Barbara Wiatkowska ◽  
Janusz Słodczyk ◽  
Aleksandra Stokowska
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Satellite Imagery ◽  
Urban Areas ◽  
Agricultural Land ◽  
Urban Expansion ◽  
Landsat 8 ◽  
Rate Of Increase ◽  
Management Procedures

Urban expansion is a dynamic and complex phenomenon, often involving adverse changes in land use and land cover (LULC). This paper uses satellite imagery from Landsat-5 TM, Landsat-8 OLI, Sentinel-2 MSI, and GIS technology to analyse LULC changes in 2000, 2005, 2010, 2015, and 2020. The research was carried out in Opole, the capital of the Opole Agglomeration (south-western Poland). Maps produced from supervised spectral classification of remote sensing data revealed that in 20 years, built-up areas have increased about 40%, mainly at the expense of agricultural land. Detection of changes in the spatial pattern of LULC showed that the highest average rate of increase in built-up areas occurred in the zone 3–6 km (11.7%) and above 6 km (10.4%) from the centre of Opole. The analysis of the increase of built-up land in relation to the decreasing population (SDG 11.3.1) has confirmed the ongoing process of demographic suburbanisation. The paper shows that satellite imagery and GIS can be a valuable tool for local authorities and planners to monitor the scale of urbanisation processes for the purpose of adapting space management procedures to the changing environment.

scholarly journals Correlating elements content in mosses collected in 2015 across Germany with spatially associated characteristics of sampling sites and their surroundings

2019 ◽  
Vol 31 (1) ◽  
Author(s):  
Stefan Nickel ◽  
Winfried Schröder
Keyword(s):  
Land Use ◽  
Population Density ◽  
Atmospheric Deposition ◽  
Vegetation Structure ◽  
Urban Areas ◽  
Explanatory Power ◽  
Spatial Density ◽  
Area Index ◽  
Explanatory Variables ◽  
Tree Layer

Abstract Background The aim of the study was a statistical evaluation of the statistical relevance of potentially explanatory variables (atmospheric deposition, meteorology, geology, soil, topography, sampling, vegetation structure, land-use density, population density, potential emission sources) correlated with the content of 12 heavy metals and nitrogen in mosses collected from 400 sites across Germany in 2015. Beyond correlation analysis, regression analysis was performed using two methods: random forest regression and multiple linear regression in connection with commonality analysis. Results The strongest predictor for the content of Cd, Cu, Ni, Pb, Zn and N in mosses was the sampled species. In 2015, the atmospheric deposition showed a lower predictive power compared to earlier campaigns. The mean precipitation (2013–2015) is a significant factor influencing the content of Cd, Pb and Zn in moss samples. Altitude (Cu, Hg and Ni) and slope (Cd) are the strongest topographical predictors. With regard to 14 vegetation structure measures studied, the distance to adjacent tree stands is the strongest predictor (Cd, Cu, Hg, Zn, N), followed by the tree layer height (Cd, Hg, Pb, N), the leaf area index (Cd, N, Zn), and finally the coverage of the tree layer (Ni, Cd, Hg). For forests, the spatial density in radii 100–300 km predominates as significant predictors for Cu, Hg, Ni and N. For the urban areas, there are element-specific different radii between 25 and 300 km (Cd, Cu, Ni, Pb, N) and for agricultural areas usually radii between 50 and 300 km, in which the respective land use is correlated with the element contents. The population density in the 50 and 100 km radius is a variable with high explanatory power for all elements except Hg and N. Conclusions For Europe-wide analyses, the population density and the proportion of different land-use classes up to 300 km around the moss sampling sites are recommended.

scholarly journals Montanhas em um mundo plano: porque a proximidade ainda importa para a localização da atividade econômica

2009 ◽  
Vol 11 (2) ◽  
pp. 9
Author(s):  
Andrés Rodríguez-Pose ◽  
Riccardo Crescenzi
Keyword(s):  
Urban Areas ◽  
New Economic Geography ◽  
World Population ◽  
Capital Social ◽  
Playing Field ◽  
The World ◽  
Tectonic Forces ◽  
The City ◽  
Innovative Capacity ◽  
Backward And Forward Linkages

Thomas Friedman (2005) argumenta que a expansão do comércio, a internacionalização das firmas, o crescimento acelerado do processo de outsourcing e a possibilidade de conexão em redes a custos cada vez mais baixos estão criando um “mundo plano”: um campo competitivo de condições homogêneas de concorrência no qual os indivíduos têm maior poder e melhores condições de vida. Este artigo desafia essa visão do mundo, argumentando que embora a globalização traga mudanças, oportunidades e desafios, nem todos os territórios têm a mesma capacidade de maximizar os benefícios e as oportunidades e de minimizaras ameaças circundantes. Numerosas forças estão se fundindo no sentido de provocar a emergência de “montanhas” urbanas, onde a riqueza, a atividade econômica e a capacidade de inovação se aglomeram. Estas forças “tectônicas” incluem fatores como a inovação, os transbordamentos, os encadeamentos para trás e para frente nas cadeias produtivas, a dinâmica de especialização versus diversificação, o capital social e comunitário e, por último, mas não menos importante, o “buzz” da cidade. As interações destas forças na proximidade geográfica das grandes áreas urbanas dão forma a uma geografia muito mais complexa da economia mundial e permitem a ascensão de novos players econômicos. Mas esta geografia, ao contrário de ser plana, é repleta de montanhas, em que as grandes aglomerações urbanas representam os picos mais altos. A maioria da população mundial, ao contrário de ter maior poder, permanece mal preparada para encarar estes desafios. Palavras-chave: progresso tecnológico; nova geografia econômica; vantagem competitiva. Abstract: Thomas Friedman (2005) argues that the expansion of trade, the internationalization of firms, the galloping process of outsourcing, and the possibility of networking at increasingly low prices is creating a ‘flat world’: a level playing field where individuals are empowered and better off. This paper challenges this view of the world by arguing that although globalization implies changes, opportunities, and threats, not all territories have the same capacity to maximize the benefits and opportunities and minimize the threats at hand. Numerous forces are coalescing in order to provoke the emergence of urban “mountains” where wealth, economic activity, and innovative capacity agglomerate. These “tectonic” forces include factors such as innovation, spill overs, backward and forward linkages, specialisation vs. diversification dynamics, community and social capital, and, last but not least, the buzz of the city. The interactions of these forces in the close geographical proximity of large urban areas give shape to a much more complex geography of the world economy and allows for new economic players to emerge. But this geography, rather than flat, is full of mountains, with large urban agglomerations representing the highest peaks. The majority of the world population, far from being empowered, remains ill-prepared to face these challenges. Keywords: technological progress; new economic geography; competitive advantage.

scholarly journals Use of Low-cost Sensors to Develop Land Use Regression Models for PM2.5 of 6 Urban Areas in the US

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
T. Lu ◽  
M.J. Bechle ◽  
Y. Wan ◽  
A.A. Presto ◽  
S. Hankey
Keyword(s):  
Land Use ◽  
Urban Areas ◽  
Regression Models ◽  
Low Cost ◽  
Land Use Regression ◽  
The Us ◽  
Develop Land

scholarly journals Global Variation in Climate, Human Development, and Population Density Has Implications for Urban Ecosystem Services

2019 ◽  
Vol 11 (22) ◽  
pp. 6200 ◽  
Author(s):  
Daniel Richards ◽  
Mahyar Masoudi ◽  
Rachel R. Y. Oh ◽  
Erik S. Yando ◽  
Jingyuan Zhang ◽  
...  
Keyword(s):  
Ecosystem Services ◽  
Population Density ◽  
Human Development ◽  
Urban Areas ◽  
Urban Ecosystem ◽  
Urban Ecosystem Services ◽  
Global Variation ◽  
The World ◽  
Tropical Cities ◽  
Future Work

Humans rely upon ecosystem services to regulate their environment and to provide resources and cultural benefits. As the world’s urban population grows, it becomes increasingly important to find ways of improving the provision of ecosystem services in urban areas. However, the kinds of ecosystem services that are most needed or demanded by urban populations, and the opportunities to provide these, vary widely in cities around the world. Here we explore variation in climate, Human Development Index (HDI), and population density, and discuss their implications for providing and managing urban ecosystem services. Using 221 published studies of urban ecosystem services, we analyse the extent to which existing research adequately covers global variation in climatic and social conditions. Our results reveal an under-representation of studies from tropical cities and from lower HDI countries, with implications for how we conceptualize and quantify urban ecosystem services, and how we transfer benefits across case studies. Future work should be aimed at correcting these deficits and determining the extent to which conclusions about urban ecosystem services are transferable from one city to another.

The Role of Road Infrastructure and Air Pollution in the Recent Suburbanization of India’s Cities

2017 ◽  
Vol 8 (2) ◽  
pp. 151-169 ◽  
Author(s):  
Matthew J. Holian ◽  
Kala Seetharam Sridhar
Keyword(s):  
Air Pollution ◽  
Population Density ◽  
Urban Areas ◽  
Regression Models ◽  
Central City ◽  
Road Transport ◽  
Transport Infrastructure ◽  
Multiple Regression Models ◽  
Indian Cities

This article re-examines the suburbanization of Indian cities by calculating population density gradients, for a large number of urban agglomerations, using recent data and Mills’ two-point method. In the next step, we estimate multiple regression models to explore the determinants of suburbanization. This study presents several methodological advances over previous research, by incorporating new measures of transport infrastructure, air pollution and city–suburb income ratios as determinants of suburbanization of Indian cities. Our results clearly show that suburbanization is higher in urban areas with higher population and lower central city–suburban literacy ratios. We find some evidence that suburbanization is higher in urban areas with more road transport infrastructure, consistent with our expectations, though results concerning air pollution run counter to expectations. However, these could relate to caveats regarding the data and methods.

scholarly journals Land-use change and quality of life in residential neighbourhoods: Evidence from Tehran, Iran

GeoScape ◽  
2021 ◽  
Vol 15 (2) ◽  
pp. 104-119
Author(s):  
Navid Forouhar ◽  
Amir Forouhar ◽  
Mahnoosh Hasankhani
Keyword(s):  
Quality Of Life ◽  
Land Use ◽  
Land Use Change ◽  
Land Use Planning ◽  
Urban Areas ◽  
Structured Interview ◽  
Structural Defects ◽  
Residential Areas ◽  
Commercial Development

Abstract Land-use planning generally aims to manage the development of urban areas to address the needs of the communities. In this regard, the multiple and often competing environmental, economic and social conflicts complicate the process of land-use planning. Commercial development in residential neighbourhoods is a common type of land-use conflict that can dramatically exacerbate these potential conflicts. Over the recent decades, many affluent neighbourhoods of Tehran Metropolis (the capital of Iran) have been confronted with an unbridled development of commercial activities within the residential areas. This paper seeks to understand the process of land-use change and its impacts on the residents’ quality of life in an affluent neighbourhood of Tehran Metropolis (Gisha Neighbourhood) by adopting a combination of quantitative and qualitative methods of impact assessment including semi-structured interview, purposeful field survey, and traffic survey. The results yield that incompatible land-use policies of the Tehran Comprehensive Plan and structural defects in the land-use change regulations led to an unbridled process of commercialisation which intensified non-local activities with city/regional service coverage along the main streets of Gisha Neighbourhood. The analysis demonstrates that despite improving the accessibility of residents to urban facilities and reducing their travel time/cost, the process of land-use changes in Gisha Neighbourhood declined the residents’ quality of life by its considerable negative effects on socio-cultural structures, landuse patterns, traffic flow, and human health in the residential areas of the neighbourhood.

scholarly journals NDVI Based Assessment of Land Cover Changes Using Remote Sensing and GIS (A case study of Srinagar district, Kashmir)

2020 ◽  
Author(s):  
Perminder Singh ◽  
Ovais Javeed
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Urban Areas ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Satellite Image ◽  
Spectral Signature ◽  
Landsat 8 ◽  
Thematic Mapping

Normalized Difference Vegetation Index (NDVI) is an index of greenness or photosynthetic activity in a plant. It is a technique of obtaining  various features based upon their spectral signature  such as vegetation index, land cover classification, urban areas and remaining areas presented in the image. The NDVI differencing method using Landsat thematic mapping images and Landsat oli  was implemented to assess the chane in vegetation cover from 2001to 2017. In the present study, Landsat TM images of 2001 and landsat 8 of 2017 were used to extract NDVI values. The NDVI values calculated from the satellite image of the year 2001 ranges from 0.62 to -0.41 and that of the year 2017 shows a significant change across the whole region and its value ranges from 0.53 to -0.10 based upon their spectral signature .This technique is also  used for the mapping of changes in land use  and land cover.  NDVI method is applied according to its characteristic like vegetation at different NDVI threshold values such as -0.1, -0.09, 0.14, 0.06, 0.28, 0.35, and 0.5. The NDVI values were initially computed using the Natural Breaks (Jenks) method to classify NDVI map. Results confirmed that the area without vegetation, such as water bodies, as well as built up areas and barren lands, increased from 35 % in 2001 to 39.67 % in 2017.Key words: Normalized Difference Vegetation Index,land use/landcover, spectral signature 

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