scholarly journals Urban perimeters issues in low-density areas

2021 ◽  
Vol 1203 (3) ◽  
pp. 032065
Author(s):  
Olga Gonçalves ◽  
Ana Virtudes
Keyword(s):  
Land Use ◽  
Urban Areas ◽  
Spatial Planning ◽  
Polygonal Line ◽  
Urban Land ◽  
Urban Land Use ◽  
Urban Spaces ◽  
Low Density ◽  
Master Plans ◽  
Topographic Features

Abstract In the domain of spatial planning, there is a concern to preserve the territory whilst ensuring a proper expansion of urban perimeters. Cities, towns and villages should be contained within urban perimeters for building and urbanization purposes. The concept of urban perimeter is defined as the closed polygonal line demarcating the continuous territory of urban land-use. The spatial planning instruments should define the urban land-use referring to areas totally or partially urbanized or built. Regarding low-density territories with a greater propensity to urban sprawl and population ageing, the previously mentioned rules are not always met. Thus, this study focuses on the case of the Interior region of Portugal classified as low-density territory. Here the number of inhabitants is decreasing with low demand for urban spaces. However, the urban perimeters were mainly defined without being based on territorial features, topographic mapping or ecological sensitive areas. Thus, for a diversity of aspects, there are inappropriate areas to build that were wrongly included as part of urban areas, creating as a result urban void. One main reason for this problem are the topographic conditions that don’t fit with the urbanization and building requirements in urban perimeters. In this sense, this research aims to describe the articulation between the urbanization and building processes, under the rules of the Municipal Master Plans, regarding the topographic features of urban perimeters. The conclusion shows that the most sloped areas are those that were less sought after for urbanization, however these zones comprise a significant part of the urban perimeters. Finally, there is the need to stress that in low-density territories, many urban voids will never be urbanized.

IMPACTS OF URBAN LAND USE ON CRIME PATTERNS THROUGH GIS APPLICATION

2013 ◽  
Vol 11 (2) ◽  
Author(s):  
Ahmad Nazri Muhamad Ludin ◽  
Norsiah Abd. Aziz ◽  
Nooraini Hj Yusoff ◽  
Wan Juliyana Wan Abd Razak
Keyword(s):  
Land Use ◽  
Drug Abuse ◽  
Land Use Planning ◽  
Urban Areas ◽  
Spatial Relationship ◽  
Police Department ◽  
Strong Relationship ◽  
Urban Land ◽  
Urban Land Use ◽  
Land Use Patterns

Land use planning plays a crucial role in creating a balance between the needs of society, physical development and the ecosystem. However, most often poor planning and displacement of land uses particularly in urban areas contribute to social ills such as drug abuse and criminal activities. This research explains the spatial relationship of drug abuse and other criminal activities on urban land use planning and their implications on the society at large. Spatial statistics was used to show patterns, trends and spatial relationships of crimes and land use planning. Data on crime incidents were obtained from the Royal Malaysia Police Department whilst cases of drug abuse were collected from the National Anti-Drug Agency (AADK). Analysis of the data together with digital land use maps produced by Arnpang Jaya Municipal Council, showed the distribution of crime incidents and drug abuse in the area. Findings of the study also indicated that, there was a strong relationship between petty crimes, drng abuse and land use patterns. These criminal activities tend to concentrate in residential and commercial areas of the study area.

A hydraulic invariance-based methodology for the implementation of storm-water release restrictions in urban land use master plans

2017 ◽  
Vol 31 (23) ◽  
pp. 4046-4055 ◽  
Author(s):  
Viviana Pappalardo ◽  
Alberto Campisano ◽  
Francesco Martinico ◽  
Carlo Modica ◽  
Luca Barbarossa
Keyword(s):  
Land Use ◽  
Urban Land ◽  
Urban Land Use ◽  
Storm Water ◽  
Water Release ◽  
Master Plans

scholarly journals Exploring the Spatial and Temporal Relationship between Air Quality and Urban Land-Use Patterns Based on an Integrated Method

2020 ◽  
Vol 12 (7) ◽  
pp. 2964 ◽  
Author(s):  
Chia-An Ku
Keyword(s):  
Land Use ◽  
Air Quality ◽  
Urban Areas ◽  
Temporal Relationship ◽  
Urban Land ◽  
Urban Land Use ◽  
Air Pollutant ◽  
Land Use Patterns ◽  
Use Patterns ◽  
Mitigation Planning

The deterioration of air quality in urban areas is often closely related to urbanization, as this has led to a significant increase in energy consumption and the massive emission of air pollutants, thereby exacerbating the current state of air pollution. However, the relationship between urban development and air quality is complex, thus making it difficult to be analyzed using traditional methods. In this paper, a framework integrating spatial analysis and statistical methods (based on 170 regression models) is developed to explore the spatial and temporal relationship between urban land use patterns and air quality, aiming to provide solid information for mitigation planning. The thresholds for the influence of urban patterns are examined using different buffer zones. In addition, the differences in the effects of various types of land use pattern on air quality were also explored. The results show that there were significant differences between 1999 and 2013 with regards to the correlations between land use patterns and air pollutant concentrations. Among all land uses, forest, water and built-up areas were proved to influence concentrations the most. It is suggested that the developed framework should be applied further in the real-world mitigation planning decision-making process

scholarly journals Study on Land-use Changes and Their Impacts on Air Pollution in Chengdu

Atmosphere ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 42 ◽  
Author(s):  
Wei Sun ◽  
Zhihong Liu ◽  
Yang Zhang ◽  
Weixin Xu ◽  
Xiaotong Lv ◽  
...  
Keyword(s):  
Land Use ◽  
Wind Speed ◽  
Correlation Coefficient ◽  
Urban Areas ◽  
Land Use Changes ◽  
Urban Land ◽  
Urban Land Use ◽  
Simulation Results ◽  
The City ◽  
Better Than

The expansion of urban areas and the increase in the number of buildings and urbanization characteristics, such as roads, affect the meteorological environment in urban areas, resulting in weakened pollutant dispersion. First, this paper uses GIS (geographic information system) spatial analysis technology and landscape ecology analysis methods to analyze the dynamic changes in land cover and landscape patterns in Chengdu as a result of urban development. Second, the most appropriate WRF (Weather Research and Forecasting) model parameterization scheme is selected and screened. Land-use data from different development stages in the city are included in the model, and the wind speed and temperature results simulated using new and old land-use data (1980 and 2015) are evaluated and compared. Finally, the results of the numerical simulations by the WRF-Chem air quality model using new and old land-use data are coupled with 0.25° × 0.25°-resolution MEIC (Multi-resolution Emission Inventory for China) emission source data from Tsinghua University. The results of the sensitivity experiments using the WRF-Chem model for the city under different development conditions and during different periods are discussed. The meteorological conditions and pollution sources remained unchanged as the land-use data changed, which revealed the impact of urban land-use changes on the simulation results of PM2.5 atmospheric pollutants. The results show the following. (1) From 1980 to 2015, the land-use changes in Chengdu were obvious, and cultivated land exhibited the greatest changes, followed by forestland. Under the influence of urban land-use dynamics and human activities, both the richness and evenness of the landscape in Chengdu increased. (2) The microphysical scheme WSM3 (WRF Single–Moment 3 class) and land-surface scheme SLAB (5-layer diffusion scheme) were the most suitable for simulating temperatures and wind speeds in the WRF model. The wind speed and temperature simulation results using the 2015 land-use data were better than those using the 1980 land-use data when assessed according to the coincidence index and correlation coefficient. (3) The WRF-Chem simulation results obtained for PM2.5 using the 2015 land-use data were better than those obtained using the 1980 land-use data in terms of the correlation coefficient and standard deviation. The concentration of PM2.5 in urban areas was higher than that in the suburbs, and the concentration of PM2.5 was lower on Longquan Mountain in Chengdu than in the surrounding areas.

Urban Land Use Changes by the Integration of Remote Sensing, GIS, and Dynamics Modeling

2013 ◽  
Vol 726-731 ◽  
pp. 4645-4649
Author(s):  
Jia Hua Zhang ◽  
Cui Hao ◽  
Feng Mei Yao
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Urban Areas ◽  
Logistic Model ◽  
Land Use Changes ◽  
Urban Land ◽  
Urban Land Use ◽  
Ratio Test ◽  
Multinomial Logistic Model ◽  
The Impact

We developed an approach to assess urban land use changes that incorporates socio-economic and environmental factors with multinomial logistic model, remote sensing data and GIS, and to quantify the impact of macro variables on land use of urban areas for the years 1990, 2000 and 2010 in Binhai New Area, China. The Markov transition matrix was designed to integrate with multinomial logistic model to illustrate and visualize the predicted land use surface. The multinomial logistic model was evaluated by means of Likelihood ratio test and Pseudo R-Square and showed a relatively good simulation. The prediction map of 2010 showed accurate rates 78.54%, 57.25% and 70.38%, respectively.

Land Use Conversion Probabilities in a Peri-Urban District of Ghana

2015 ◽  
Vol 03 (03) ◽  
pp. 1550026 ◽  
Author(s):  
Divine Odame APPIAH ◽  
Eric Kwabena FORKUO ◽  
John Tiah BUGRI
Keyword(s):  
Land Use ◽  
Urban Areas ◽  
Urban Land ◽  
Agent Based Modeling ◽  
Urban Land Use ◽  
Urban District ◽  
Agent Based ◽  
Land Use Conversion ◽  
Theory Application ◽  
Space Economy

This paper is a critical review, which synthesizes the theory-application linkage of peri-urban land use and land cover changes (LULCC) using the Bosomtwe District in the Ashanti Region of Ghana as the case. From abstractive thinking to empirical possibility, we conjecture human decisions within agent-based modeling (ABM) perspective. The key question the paper has tried to answer is: what are the probable future land use conversion and modification potentials in the district? LULCC in peri-urban areas respond to social and biophysical dynamics. These control spatial distribution of populations, infrastructure, and the space economy. Under systemic laxity of controls, peri-urban land uses deviate from effective land use plans.

scholarly journals Patterns of Land Use Activities in Ghana’s Secondary Cities

2020 ◽  
Vol 12 (2) ◽  
pp. 84-107
Author(s):  
Bismark Mensah ◽  
Isaac Obeng Darkwa ◽  
Esther Yamoaba Bonful ◽  
Moses Bangfunourteru Tuu ◽  
Mohammed Sanda ◽  
...  
Keyword(s):  
Land Use ◽  
Internal Structure ◽  
Urban Areas ◽  
Urban Land ◽  
Urban Land Use ◽  
Middle Income ◽  
Classical Models ◽  
Land Use Models ◽  
The Common ◽  
Industrial Zones

Ghana is rapidly urbanizing. This urbanization has resulted in villages growing into towns and towns into urbanized areas. Theories and models have been employed to explain the internal structure of urban areas, especially, with respect to land use variations. These models started with the classical urban land use models in America. Urban scholars in Africa have struggled to fit the development of the African cities into these classical models. They have therefore called for African scholars to develop models for urban land use in Africa. This paper sought to identify the common patterns of land use activities which shape the internal structure of Ghana’s secondary cities. The study employed Geographic Information System (GIS) as a major tool of analysis in explaining the patterns in urban areas. This is augmented with in-depth ground observations of the study areas. The findings of the study showed the absence of homogeneity in most of the sectors and undefined industrial zones as contradictions to the classical models. The study further revealed that residential zones were not fully occupied by either lower income, middle income, or higher income residence. The income groups may only dominate in a given sector. Based on the findings, a common pattern is proposed to represent the land uses within the selected secondary cities in Ghana.

scholarly journals A 30-meter resolution national urban land-cover dataset of China, 2000–2015

2019 ◽  
Author(s):  
Wenhui Kuang ◽  
Shu Zhang ◽  
Xiaoyong Li ◽  
Dengsheng Lu
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Urban Areas ◽  
Vegetation Index ◽  
Urban Land ◽  
Google Earth ◽  
Urban Environments ◽  
Urban Land Use ◽  
Environmental Research ◽  
Urban Land Cover

Abstract. Accurate urban land-cover datasets are essential for mapping urban environments. However, a series of national urban land-cover data covering more than 15 years that characterizes urban environments is relatively rare. Here we propose a hierarchical principle on remotely sensed urban land-use/cover classification for mapping intra-urban structure/component dynamics. China's Land Use/cover Dataset (CLUD) is updated, delineating the imperviousness, green surface, waterbody and bare land conditions in cities. A new data subset called CLUD-Urban is created from 2000 to 2015 at five-year intervals with a medium spatial resolution (30 m). The first step is a prerequisite to extract the vector boundaries covered with urban areas from CLUD. A new method is then proposed using logistic regression between urban impervious surface area (ISA) and the annual maximum Normalized Difference Vegetation Index (NDVI) value retrieved from Landsat images based on a big-data platform with Google Earth Engine. National ISA and urban green space (UGS) fraction datasets for China are generated at 30-meter resolution with five-year intervals from 2000 to 2015. The overall classification accuracy of national urban areas is 92 %. The root mean square error values of ISA and UGS fractions are 0.10 and 0.14, respectively. The datasets indicate that the total urban area of China was 6.28 × 104 km2 in 2015, with average fractions of 70.70 % and 26.54 % for ISA and UGS, respectively. The ISA and UGS increased between 2000 and 2015 with unprecedented annual rates of 1,311.13 km2/yr and 405.30 km2/yr, respectively. CLUD-Urban can be used to enhance our understanding of urbanization impacts on ecological and regional climatic conditions and urban dwellers' environments. CLUD-Urban can be applied in future researches on urban environmental research and practices in the future. The datasets can be downloaded from https://doi.org/10.5281/zenodo.2644932.

Reviewing the Pertinence of Sentinel-1 SAR for Urban Land Use Land Cover Classification

2020 ◽  
Vol 11 (5) ◽  
pp. 529-535
Author(s):  
Dan Abudu ◽  
Nigar Sultana Parvin ◽  
Geoffrey Andogah
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Urban Areas ◽  
Land Use Changes ◽  
Land Cover Classification ◽  
Urban Land ◽  
Urban Land Use ◽  
Land Use Land Cover ◽  
Sensing Technology

Conventional approaches for urban land use land cover classification and quantification of land use changes have often relied on the ground surveys and urban censuses of urban surface properties. Advent of Remote Sensing technology supporting metric to centimetric spatial resolutions with simultaneous wide coverage, significantly reduced huge operational costs previously encountered using ground surveys. Weather, sensor’s spatial resolution and the complex compositions of urban areas comprising concrete, metallic, water, bare- and vegetation-covers, limits Remote Sensing ability to accurately discriminate urban features. The launch of Sentinel-1 Synthetic Aperture Radar, which operates at metric resolution and microwave frequencies evades the weather limitations and has been reported to accurately quantify urban compositions. This paper assessed the feasibility of Sentinel-1 SAR data for urban land use land cover classification by reviewing research papers that utilised these data. The review found that since 2014, 11 studies have specifically utilised the datasets.

scholarly journals LAND USE CLASSIFICATION USING DEEP MULTITASK NETWORKS

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 17-21
Author(s):  
J. R. Bergado ◽  
C. Persello ◽  
A. Stein
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Urban Areas ◽  
Large Scale ◽  
Urban Land ◽  
Urban Land Use ◽  
The Other ◽  
Classification Task ◽  
Land Use Classification ◽  
Convolutional Network

Abstract. Updated information on urban land use allows city planners and decision makers to conduct large scale monitoring of urban areas for sustainable urban growth. Remote sensing data and classification methods offer an efficient and reliable way to update such land use maps. Features extracted from land cover maps are helpful on performing a land use classification task. Such prior information can be embedded in the design of a deep learning based land use classifier by applying a multitask learning setup—simultaneously solving a land use and a land cover classification task. In this study, we explore a fully convolutional multitask network to classify urban land use from very high resolution (VHR) imagery. We experimented with three different setups of the fully convolutional network and compared it against a baseline random forest classifier. The first setup is a standard network only predicting the land use class of each pixel in the image. The second setup is a multitask network that concatenates the land use and land cover class labels in the same output layer of the network while the other setup accept as an input the land cover predictions, predicted by a subpart of the network, concatenated to the original input image patches. The two deep multitask networks outperforms the other two classifiers by at least 30% in average F1-score.

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