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 Análise da Variação Espaço-Temporal das Áreas Verdes e da Qualidade Ambiental em Áreas Urbanas, Recife-PE (Analysis of the Time-Space Variation of Green Areas and the Environmental Quality in Urban Areas, Recife-PE)

2015 ◽  
Vol 7 (6) ◽  
pp. 1196
Author(s):  
Tiago Henrique de Oliveira ◽  
José Gleidson Dantas ◽  
Josiclêda Domiciano Galvíncio ◽  
Rejane Magalhães de Mendonça Pimentel ◽  
Milton Botler
Keyword(s):  
Land Use ◽  
Environmental Quality ◽  
Urban Areas ◽  
Rapid Change ◽  
Large Temperature ◽  
Natural Soil ◽  
Area Index ◽  
Time Space ◽  
Green Areas ◽  
Spatio Temporal

As rápidas mudanças do uso e cobertura do solo em ambiente urbano apresentam grande impacto nas relações entre os ciclos energéticos e hidrológicos sobre a superfície. O município do Recife, através da Lei de Uso e Ocupação do Solo de 1996 (Lei nº 16.176/96) define área verde como “toda área de domínio público ou privado, em solo natural,onde predomina qualquer forma de vegetação, distribuída em seus diferentes estratos: Arbóreo, Arbustivo e Herbáceo /Forrageira, nativa ou exótica”. O objetivo deste artigo é analisar a variação espacial das áreas verdes disponíveis no município do Recife e a evolução espaço-temporal da qualidade ambiental na RPA 4 através do computo do Índice de umidade (NDWI), Índice de Área Foliar (IAF) e Temperatura da superfície em imagens TM Landsat. Foi realizada uma classificação supervisionada na ortofotocarta Recife onde as áreas verdes foram exportadas para polígonos, permitindo a sua quantificação. Para as imagens TM foi aplicada parte da metodologia SEBAL. As áreas verdes ocupam 45,58% do Recife. Os transectos lineares e perfis permitiram visualizar mais facilmente as mudanças espaço-temporais ocorridos na RPA-4. Foi visualizada grande diferença de temperatura entre as áreas vegetadas e as áreas mais urbanizadas. Palavras-chave: Uso e ocupação do solo; área urbana, áreas vegetadas, sensoriamento remoto; MAXVER. A B S T R A C T The rapid change of use and land cover in urban environment poses great impact on relations between energy and hydrological cycles on the surface. The municipality of Recife, through the Land Use Legislation from 1996 (Law No. 16.176/96) defines green area as ";;;;;;any public or private domain area, in natural soil, where overcrows any form of vegetation, distributed in its different layers: Arboreal, shrubby and Herbaceous Forage, native or exotic";;;;;;. The goal of this paper is to analyze the spatial variation of available green areas in the city of Recife and the spatio-temporal evolution of environmental quality in the Political Administrative Region 4, known as RPA-4, through the calculation of moisture content (NDWI), leaf area index (LAI) and the surface temperature from Landsat TM images. Supervised classification was performed on orthophoto Reef where the green areas were exported to polygons, allowing its quantification. For the TM images, it has been applied the methodology SEBAL. The green areas occupy 45.58% of Recife. The linear transects and profiles allowed to show more easily space-time changes occurring in the RPA-4. Large temperature differences have been displayed between the most vegetated areas and more urbanized areas. Key-words: Land use; urban areas; vegetated area, remote sensing; MAXVER.

scholarly journals Contribution of Greening and High-Albedo Coatings to Improvements in the Thermal Environment in Complex Urban Areas

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Bonggeun Song ◽  
Kyunghun Park
Keyword(s):  
Land Use ◽  
Urban Areas ◽  
Thermal Environment ◽  
Explanatory Power ◽  
Ground Cover ◽  
Residential Areas ◽  
Coating Materials ◽  
Land Use Types ◽  
Green Areas ◽  
Field Temperature

The aim was to identify microclimate characteristics in relation to ground cover in green areas and the reflectivity of building coating materials. Furthermore, microclimate modeling of temperatures was conducted using ENVI-met, to analyze the effects of improved thermal environments based on increased green areas and increased reflectivity of exterior coatings. The accuracy of ENVI-met was validated through comparisons with field temperature measurements. The RMSE deviation of the predicted and actual field temperature values was 3–6°C; however, the explanatory power was as high as 60%. ENVI-met was performed for commercial and single residential areas that have high densities of artificial cover materials, before and after changes related to development of green areas and to increase in the reflectivity of coating materials. The results indicated that both areas exhibited distinct temperature reductions due to the creation of green spaces. When the reflectivity of the coating material was increased, a temperature increase was observed in all land-use types. Therefore, in order to improve the thermal environment of complex urban areas, it is necessary to improve green-area development and to use high-reflectivity ground and building cover materials, while taking into account the spatial characteristics of land-use types and their surrounding areas.

scholarly journals The effect of satellite derived leaf area index and roughness length information on modelled reactive nitrogen deposition in north-western Europe

2019 ◽  
Author(s):  
Shelley C. van der Graaf ◽  
Richard Kranenburg ◽  
Arjo J. Segers ◽  
Martijn Schaap ◽  
Jan Willem Erisman
Keyword(s):  
Land Use ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Urban Areas ◽  
Forest Canopy ◽  
Roughness Length ◽  
Arable Land ◽  
Reactive Nitrogen ◽  
Past Century ◽  
Area Index

Abstract. The nitrogen cycle has been continuously disrupted by human activity over the past century, resulting in almost a tripling of the total reactive nitrogen fixation in Europe. Consequently, excessive amounts of reactive nitrogen (Nr) have manifested in the environment, leading to a cascade of adverse effects, such as acidification and eutrophication of terrestrial and aquatic ecosystems, and particulate matter formation. Chemistry transport models (CTM) are frequently used as tools to simulate the complex chain of processes that determine atmospheric Nr flows. In these models, the parameterization of the atmosphere-biosphere exchange of Nr is largely based on few surface exchange measurement and is therefore known to be highly uncertain. In addition to this, the input parameters that are used here are often fixed values, only linked to specific land use classes. In an attempt to improve this, a combination of multiple satellite products is used to derive updated, time-variant leaf area index (LAI) and roughness length (z0) input maps. As LAI, we use the MODIS MCD15A2H product. The monthly z0 input maps presented in this paper are a function of satellite-derived NDVI values (MYD13A3 product) for short vegetation types (such as grass and arable land) and a combination of satellite-derived forest canopy height and LAI for forests. The use of these growth-dependent satellite products allows us to represent the growing season more realistically. For urban areas, the z0 values are updated, too, and linked to a population density map. The approach to derive these dynamic z0 estimates can be linked to any land use map and is as such transferable to other models. We evaluated the resulting changes in modelled deposition of Nr components using the LOTOS-EUROS CTM, focusing on Germany, the Netherlands and Belgium. The implementation of these updated LAI and z0 input maps led to local changes in the total Nr deposition of up to ~ 30 % and a general shift from wet to dry deposition. The most distinct changes are observed in land use specific deposition fluxes. These fluxes may show relatively large deviations, locally affecting estimated critical load exceedances for specific natural ecosystems.

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 ANALYSING RELATIONSHIPS BETWEEN URBAN LAND USE FRAGMENTATION METRICS AND SOCIO-ECONOMIC VARIABLES

2016 ◽  
Vol XLI-B8 ◽  
pp. 1029-1036 ◽  
Author(s):  
M. Sapena ◽  
L. A. Ruiz ◽  
F. J. Goerlich
Keyword(s):  
Land Use ◽  
Urban Areas ◽  
Structural Changes ◽  
Principal Component ◽  
Urban Land ◽  
Growth Patterns ◽  
Urban Land Use ◽  
Economic Variables ◽  
Explanatory Variables ◽  
Socio Economic Variables

Analysing urban regions is essential for their correct monitoring and planning. This is mainly accounted for the sharp increase of people living in urban areas, and consequently, the need to manage them. At the same time there has been a rise in the use of spatial and statistical datasets, such as the Urban Atlas, which offers high-resolution urban land use maps obtained from satellite imagery, and the Urban Audit, which provides statistics of European cities and their surroundings. In this study, we analyse the relations between urban fragmentation metrics derived from Land Use and Land Cover (LULC) data from the Urban Atlas dataset, and socio-economic data from the Urban Audit for the reference years 2006 and 2012. We conducted the analysis on a sample of sixty-eight Functional Urban Areas (FUAs). One-date and two-date based fragmentation indices were computed for each FUA, land use class and date. Correlation tests and principal component analysis were then applied to select the most representative indices. Finally, multiple regression models were tested to explore the prediction of socio-economic variables, using different combinations of land use metrics as explanatory variables, both at a given date and in a dynamic context. The outcomes show that demography, living conditions, labour, and transportation variables have a clear relation with the morphology of the FUAs. This methodology allows us to compare European FUAs in terms of the spatial distribution of the land use classes, their complexity, and their structural changes, as well as to preview and model different growth patterns and socio-economic indicators.

scholarly journals Satellite-derived leaf area index and roughness length information for surface–atmosphere exchange modelling: a case study for reactive nitrogen deposition in north-western Europe using LOTOS-EUROS v2.0

2020 ◽  
Vol 13 (5) ◽  
pp. 2451-2474
Author(s):  
Shelley C. van der Graaf ◽  
Richard Kranenburg ◽  
Arjo J. Segers ◽  
Martijn Schaap ◽  
Jan Willem Erisman
Keyword(s):  
Land Use ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Urban Areas ◽  
Forest Canopy ◽  
Roughness Length ◽  
Arable Land ◽  
Reactive Nitrogen ◽  
Past Century ◽  
Area Index

Abstract. The nitrogen cycle has been continuously disrupted by human activity over the past century, resulting in almost a tripling of the total reactive nitrogen fixation in Europe. Consequently, excessive amounts of reactive nitrogen (Nr) have manifested in the environment, leading to a cascade of adverse effects, such as acidification and eutrophication of terrestrial and aquatic ecosystems, and particulate matter formation. Chemistry transport models (CTMs) are frequently used as tools to simulate the complex chain of processes that determine atmospheric Nr flows. In these models, the parameterization of the atmosphere–biosphere exchange of Nr is largely based on few surface exchange measurement and is therefore known to be highly uncertain. In addition to this, the input parameters that are used here are often fixed values, only linked to specific land use classes. In an attempt to improve this, a combination of multiple satellite products is used to derive updated, time-variant leaf area index (LAI) and roughness length (z0) input maps. As LAI, we use the Moderate Resolution Imaging Spectroradiometer (MODIS) MCD15A2H product. The monthly z0 input maps presented in this paper are a function of satellite-derived normalized difference vegetation index (NDVI) values (MYD13A3 product) for short vegetation types (such as grass and arable land) and a combination of satellite-derived forest canopy height and LAI for forests. The use of these growth-dependent satellite products allows us to represent the growing season more realistically. For urban areas, the z0 values are updated, too, and linked to a population density map. The approach to derive these dynamic z0 estimates can be linked to any land use map and is as such transferable to other models. We evaluated the sensitivity of the modelled Nr deposition fields in LOng Term Ozone Simulation – EURopean Operational Smog (LOTOS-EUROS) v2.0 to the abovementioned changes in LAI and z0 inputs, focusing on Germany, the Netherlands and Belgium. We computed z0 values from FLUXNET sites and compared these to the default and updated z0 values in LOTOS-EUROS. The root mean square difference (RMSD) for both short vegetation and forest sites improved. Comparing all sites, the RMSD decreased from 0.76 (default z0) to 0.60 (updated z0). The implementation of these updated LAI and z0 input maps led to local changes in the total Nr deposition of up to ∼30 % and a general shift from wet to dry deposition. The most distinct changes are observed in land-use-specific deposition fluxes. These fluxes may show relatively large deviations, locally affecting estimated critical load exceedances for specific natural ecosystems.

scholarly journals Urban Vitality, Urban Form, and Land Use: Their Relations within a Geographical Boundary for Walkers

2020 ◽  
Vol 12 (24) ◽  
pp. 10633
Author(s):  
Suji Kim
Keyword(s):  
Land Use ◽  
Urban Form ◽  
Urban Areas ◽  
Spatial Regression ◽  
Built Environments ◽  
Daily Lives ◽  
Explanatory Variables ◽  
Functional Forms ◽  
Geographical Boundary ◽  
The Right

The aim of this study was to exmine the influence of combined urban form and land use on the vibrancy in urban areas within a geographical boundary for walkers. A geographical boundary is defined as a block group surrounded by expressways and arterials, based on findings in previous studies. Spatial regression was performed with mobile signal data representing the degree of vitality within the defined areal unit as a dependent variable, and explanatory variables measured by urban form hierarchy were used to consider both natural and built environments. The outcome helps comprehend the physical and functional forms of vibrant neighborhood environments. The result implies the importance of highly desirable features for walking- or transit-friendly neighborhoods. It also indicates the right combination of land uses needed to support the daily lives of local residents: little lost space, short blocks, well-connected streets, short distances to transit stations, and proximity to essential facilities. This study suggests a new way of defining a spatial unit for vitality analysis and shows the critical roles of both natural and built environments in activating local vitality. These findings establish the groundwork for designing better neighborhoods, especially for an area composed of local streets and collector roads.

scholarly journals How does the built environment affect transit use by train, tram and bus?

2020 ◽  
Vol 13 (1) ◽  
pp. 625-650
Author(s):  
Chris De Gruyter ◽  
Tayebeh Saghapour ◽  
Liang Ma ◽  
Jago Dodson
Keyword(s):  
Land Use ◽  
Built Environment ◽  
Public Transport ◽  
Demand Management ◽  
Explanatory Power ◽  
Demand Forecasting ◽  
Explanatory Variables ◽  
Transport Services ◽  
Transit Ridership ◽  
Transit Use

While much research has explored the influence of the built environment on public transport use, little focus has been given to how this influence varies by public transport mode. Using a case study of Melbourne, this study assesses the influence of the built environment and other characteristics (transit service quality, demand management and socio-demographics) on commuting by train, tram and bus. Key findings indicate that the built environment has a significant influence, but with notable differences between individual public transport modes. Commuting by tram was found to have the strongest association with the explanatory variables, while bus had the weakest explanatory power. Differences in the geographical coverage of public transport services in Melbourne play a key role in explaining the influence of the built environment. Population density is positively associated with tram use, which operates in older, higher density environments, but is negatively associated with train and bus use. Furthermore, the association with land-use mix is only significant for train and tram use, as buses tend to operate in areas with greater land-use homogeneity. When focused on inner Melbourne only, the influence of the built environment is diluted, while distance to public transport becomes more significant. The findings have important implications for practice, not only in terms of improving transit demand forecasting but also in targeting changes to the built environment to leverage higher transit ridership by mode.

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