scholarly journals Monitoring Urban Expansion and Urban Green Spaces Change in Addis Ababa: Directional and Zonal Analysis Integrated with Landscape Expansion Index

Forests ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 389
Author(s):  
Eyasu Markos Woldesemayat ◽  
Paolo Vincenzo Genovese
Keyword(s):  
Urban Area ◽  
Urban Growth ◽  
Growth Pattern ◽  
Addis Ababa ◽  
Urban Expansion ◽  
Outer Zone ◽  
Green Spaces ◽  
Urban Green Spaces ◽  
The Third ◽  
Expansion Pattern

Addis Ababa, the capital of Ethiopia, is urbanizing very fast. This study aimed to assess urban expansion and Urban Green Spaces (UGS) change in the city from 1989 to 2019. Remote Sensing and Geographical Information System (GIS) and Landscape Expansion Index (LEI) were used to extract Land Use Land Cover (LULC) data, measure urban expansion and UGS change and analyze urban growth pattern in inner zone, outer zone and eight quadrants. The results showed that urban area in the inner zone increased from 3712 ha to 3716 ha (0.1%), and from 3716 ha to 3874 ha (4.2%) and in the first (1989–1999) and second periods (1999–2009), while it decreased from 3874 ha to 3733 ha (3.6%) in the third period (2009–2019), portraying a non-unidirectional trend of change. Conversely, the UGS in the inner zone decreased from 60 ha to 54 ha (10%), and from 54 ha to 38 ha (29.6%) in the first and second periods, while it increased from 38 ha to 53 ha (39.4%) in the third period, reporting spatial tradeoff between the two land cover types. Meanwhile, urban areas in the outer zone increased from 10,729 ha to 15,112 ha (40%), from 15,112 ha to 21,377 ha (41.4%) and from 21,377 ha to 28,176 ha (31.8%) in the first, second and third periods, respectively, representing frontiers of suburbanization. On the other hand, the UGS in the outer zone decreased from 3624 ha to 3171 ha, from 3127 ha to 2555 ha and from 2555 ha to 1879 ha, with an annual rate of decline of 1.25%, 1.8% and 2.6%, respectively, showing increasing trend of UGS destruction for urban construction. Furthermore, the LEI analysis result showed that urban expansion pattern demonstrated largely an outlying growth characterized by differentiation and isolation of patches, whereas the infill and edge expansion pattern were insignificant and fluctuated over 30 years. Furthermore, the directional analysis showed that urban area predominately expanded in SEE,> SSE,> SSW,> SWW,> and NEE directions with varying magnitude in the first, second and third period, but decreased in third period in NWW, < NNW< and NNE directions. In response to such urban growth pattern, the center of gravity of urban area shifted from north to south during the study period, displaying main direction urbanization in recent years. Conclusively, zonal and directional studies are more effective in characterizing the Spatio-temporal dynamics variabilities of urban expansion and UGS change for informed urban planning towards sustainable urban development.

scholarly journals Dynamic Changes in Community Deprivation of Access to Urban Green Spaces by Multiple Transport Modes

2021 ◽  
Vol 9 ◽  
Author(s):  
Shunqi Cheng ◽  
Zhiqiang Liao ◽  
Yu Zhu
Keyword(s):  
Growth Rate ◽  
Spatial Pattern ◽  
Urban Area ◽  
Public Transport ◽  
Green Spaces ◽  
Dynamic Changes ◽  
Urban Green ◽  
Urban Green Spaces ◽  
The Core ◽  
Transport Modes

Urban green spaces (UGSs) improve the quality of life of urban inhabitants. With the acceleration of urbanization and changes in traffic networks, it remains unclear whether changes in the distribution of UGSs can satisfy the needs of all inhabitants and offer equal services to inhabitants from different socioeconomic backgrounds. This study addresses this issue by analyzing dynamic changes in UGS accessibility in 2012, 2016, and 2020 for inhabitants of the central urban area of Fuzhou in China at the community level. The study introduces multiple transportation modes for an accessibility estimation based on a framework using the two-step floating catchment area method and examines the dynamic changes in community deprivation of UGS accessibility using Kernel regularized least squares, a machine learning algorithm. The results demonstrate that spatial disparities of UGS accessibility exist among the multi-transport modes and vary with time. Communities with high accessibility to UGSs by walking are scattered around the urban area; for accessibility by cycling, the high accessibility regions expand and surround the regions with low accessibility in the core urban areas, forming a semi-enclosed spatial pattern. However, the core urban spatial orientation of UGS accessibility by public transit demonstrates a reverse trend to the above two modes. The spatial pattern of UGS accessibility also varies over time, and the growth rate of accessibility slightly declined during the study period. Furthermore, the increase in UGS accessibility tended to slow from 2016–2020 compared with 2012–2016, and the trend toward equality was also erratic. The degree of deprivation for communities first weakened and was then aggravated, corresponding to the slowdown in the growth rate of accessibility, leading to the persistence existence of social inequality. Moreover, significant deprivation mainly exists among less educated people or those using the cycling and integrated travel modes. Although public transport is developing, deprived communities, such as communities with large proportion of older people, have experienced a decline in access to UGSs by public transport. Based on these findings, the study proposes a policy framework for the balanced distribution of UGSs as part of urbanization.

scholarly journals Rapid Mapping and Annual Dynamic Evaluation of Quality of Urban Green Spaces on Google Earth Engine

2021 ◽  
Vol 10 (10) ◽  
pp. 670
Author(s):  
Qiang Chen ◽  
Cuiping Zhong ◽  
Changfeng Jing ◽  
Yuanyuan Li ◽  
Beilei Cao ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Urban Area ◽  
Google Earth ◽  
Green Spaces ◽  
Dynamic Evaluation ◽  
Urban Green ◽  
Urban Green Spaces ◽  
Rapid Mapping ◽  
Google Earth Engine

In order to achieve the United Nations 2030 Sustainable Development Goals (SDGs) related to green spaces, monitoring dynamic urban green spaces (UGSs) in cities around the world is crucial. Continuous dynamic UGS mapping is challenged by large computation, time consumption, and energy consumption requirements. Therefore, a fast and automated workflow is needed to produce a high-precision UGS map. In this study, we proposed an automatic workflow to produce up-to-date UGS maps using Otsu’s algorithm, a Random Forest (RF) classifier, and the migrating training samples method in the Google Earth Engine (GEE) platform. We took the central urban area of Beijing, China, as the study area to validate this method, and we rapidly obtained an annual UGS map of the central urban area of Beijing from 2016 to 2020. The accuracy assessment results showed that the average overall accuracy (OA) and kappa coefficient (KC) were 96.47% and 94.25%, respectively. Additionally, we used six indicators to measure quality and temporal changes in the UGS spatial distribution between 2016 and 2020. In particular, we evaluated the quality of UGS using the urban greenness index (UGI) and Shannon’s diversity index (SHDI) at the pixel level. The experimental results indicate the following: (1) The UGSs in the center of Beijing increased by 48.62 km2 from 2016 to 2020, and the increase was mainly focused in Chaoyang, Fengtai, and Shijingshan Districts. (2) The average proportion of relatively high and above levels (UGI > 0.5) in six districts increased by 2.71% in the study area from 2016 to 2020, and this proportion peaked at 36.04% in 2018. However, our result revealed that the increase was non-linear during this assessment period. (3) Although there was no significant increase or decrease in SHDI values in the study area, the distribution of the SHDI displayed a noticeable fluctuation in the northwest, southwest, and northeast regions of the study area between 2016 and 2020. Furthermore, we discussed and analyzed the influence of population on the spatial distribution of UGSs. We found that three of the five cold spots were located in the east and southeast of Haidian District. Therefore, the proposed workflow could provide rapid mapping and dynamic evaluation of the quality of UGS.

scholarly journals Quantifying Rapid Urbanization and its impact on Urban Green Spaces: Directional and Zonal Analysis integrated with Landscape Expansion Index

2020 ◽  
Author(s):  
Eyasu markos woldesemayat
Keyword(s):  
Urban Areas ◽  
Temporal Dynamics ◽  
Addis Ababa ◽  
Growth Patterns ◽  
Green Spaces ◽  
Geographical Information ◽  
Rapid Urbanization ◽  
Urban Green ◽  
Urban Green Spaces ◽  
Urban Zone

Addis Ababa, the capital of Ethiopia, is urbanizing rapidly in recent years mainly through the destruction of environmental resources. This study aimed at the dynamics of urban green spaces (UGS). Remote Sensing and Geographical Information System (GIS) was used to extract land use and land cover data. The Landscape Expansion Index (LEI) was employed to measure urban growth patterns. The result showed that a more noticeable growth was observed in the peri-urban zone (40.1km2 to 176.1km2), followed by the inner urban zone (from 67.1km2 to 105km2). The expansion in the urban core zone was marginal and followed a non-unidirectional trend i.e. increased in the first period (1989-1999) and second period (1999-2009) by (0.11% and 4.2%), while decreased in the third period (2009-2019) by 3.6%. The result for LEI dynamics showed that the city experienced a pronounced outlying growth (98%) pattern, while edge expansion and infilling growth were insignificant. Conversely, the UGS declined in the inner urban zone by (18.03%), (28.61%) and (18.97%) in the first, second, and third periods. Similarly, in the peri-urban zone, the UGS persistently declined by (11.5%), (17.1%) and, (28.03%). The directional analysis showed that urban areas significantly expanded in SEE, SSE, SSW, and NEE with a net increase of 5.35, 4.4 km, 2.83, and 2.3 km2/year, respectively. Conventional large-scale /citywide/ dynamics investigations are not robust enough to represent the actual magnitude and directions of change, while the zonal and directional study is more effective in characterizing the Spatio-temporal dynamics for better urban planning towards.

scholarly journals Spatio-Temporal Evaluation of Urban Growth of Zuru Metropolis, Nigeria

2021 ◽  
Vol 5 (2) ◽  
pp. 456-467
Author(s):  
Y.A. Maleeks ◽  
A.O. Aliyu ◽  
A. Bala ◽  
A.U. Isiaka ◽  
K.Z. Atta
Keyword(s):  
Population Growth ◽  
Urban Area ◽  
Urban Growth ◽  
Water Body ◽  
Anthropogenic Activities ◽  
Landsat Imagery ◽  
Urban Expansion ◽  
Population Increase ◽  
Urban Dynamics ◽  
Spatio Temporal

The pattern of development in a city is mostly governed by urban dynamics, with population increase being the primary driving force. Built-up cover is the most important predictor of urban expansion. Zuru metropolis in Kebbi State has witnessed remarkable developmental activities caused by human influences such as buildings, road constructions, and population growth for over decades. Urban growth was ascertained for a period of 30 years through the analysis of Landsat imagery of 1988, 1998, 2008 and 2018. The datasets were classified into five (5) land covers, namely, built-up, water body, rocky surface, vegetation, and others. Quantitative assessment of the urban growth was ascertained by computing post-classification LC dynamics and Land Consumption Rate/Land Absorption Coefficient (LCR/LAC). The results showed that the built-up cover (urban area) conspicuously increased with area of 693.35 ha, 728.74 ha, 5210.5 ha and 6845.75 ha respectively for the period of study (1988 – 2018). The increment in built-up area was indicative of population growth from 1988 to 2018. The study revealed that between 1988 to 2018 showed that built-up increased by 11.78%, while rocky surface and water body have shrunk by 16.44% and 0.02% respectively, which can be attributed to anthropogenic activities in which rocky surface and waterbody have been transformed into built-up cover. It further revealed that the urban area experienced crowdedness in the years 2008 and 2018 respectively due to high LCR values of 2.71% compared to LCR values of 0.0714% and 0.0558% in 1988 and 1998. Land transformation into urban area and spread of the population to the outskirts of the study area was prominent between 1998 and 2008 due to high LAC value of 0.0998. The study concluded that there was transformation of rocky surface and waterbody into urban area, which was caused by population growth, human and agricultural activities in Zuru metropolis.

scholarly journals Analyzing Urban Growth Pattern and Driving Factors Using Remote Sensing and GIS: A Case Study of Banepa Municipality, Nepal

2020 ◽  
Vol 20 (1) ◽  
pp. 9-18
Author(s):  
Rabina Twayana ◽  
Sijan Bhandari ◽  
Reshma Shrestha
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Urban Growth ◽  
Growth Pattern ◽  
Agricultural Land ◽  
Urban Expansion ◽  
Urban Land ◽  
Driving Factors ◽  
Rapid Urbanization ◽  
The Impact

Nepal is considered one of the rapidly urbanizing countries in south Asia. Most of the urbanization is dominated in large and medium cities i.e., metropolitan, sub-metropolitan, and municipalities. Remote Sensing and Geographic Information System (GIS) technologies in the sector of urban land governance are growing day by day due to their capability of mapping, analyzing, detecting changes, etc. The main aim of this paper is to analyze the urban growth pattern in Banepa Municipality during three decades (1992-2020) using freely available Landsat imageries and explore driving factors for change in the urban landscape using the AHP model. The Banepa municipality is taken as a study area as it is one of the growing urban municipalities in the context of Nepal. The supervised image classification was applied to classify the acquired satellite image data. The generated results from this study illustrate that urbanization is gradually increasing from 1992 to 2012 while, majority of the urban expansion happened during 2012-2020, and it is still growing rapidly along the major roads in a concentric pattern. This study also demonstrates the responsible driving factors for continuous urban growth during the study period. Analytical Hierarchy Process (AHP) was adopted to analyze the impact of drivers which reveals that, Internal migration (57%) is major drivers for change in urban dynamics whereas, commercialization (25%), population density (16%), and real estate business (5%) are other respective drivers for alteration of urban land inside the municipality. To prevent rapid urbanization in this municipality, the concerned authorities must take initiative for proper land use planning and its implementation on time. Recently, Nepal Government has endorsed Land Use Act 2019 for preventing the conversion of agricultural land into haphazard urban growth.

scholarly journals Quantifying the Speed, Landscape Pattern Changes and Its Driving Factors of Shenzhen China

2021 ◽  
Vol 308 ◽  
pp. 02004
Author(s):  
Qinxue He ◽  
Yuhong Chen ◽  
Yunlei Su
Keyword(s):  
Land Use ◽  
Urban Area ◽  
Urban Growth ◽  
Urban Expansion ◽  
Urban Land ◽  
Driving Factors ◽  
Cultivated Land ◽  
Land Use Types ◽  
University Enrolment ◽  
Main Factors

Urban expansion has always been a topic of great concern. The purpose of this study is to explore land use change and the types of urban expansion in Shenzhen from 1995 to 2015, and to indicate the driving factors of this change, so as to provide a paradigm for other similar studies. By analysing the landscape expansion index and the correlation coefficient between urban area and various factors in Shenzhen, the following conclusions are obtained: 1) The main changes of land use types are the decrease of cultivated land and the increase of urban land. The land cover type changed most dramatically from 2000 to 2005, and the urban land transformed from cultivated land and grassland occupied most of the area. 2) Analysis shows that during the 20 years from 1995 to 2015, the main expansion type is edge-expansion. In detail, during the period from 1995 to 2010, the proportion of infilling has been increasing, while that of the outlying has been decreasing. After 2010, the urban area of Shenzhen increased slightly. Besides, according to the landscape expansion index, Shenzhen experienced dramatic urban expansion from 2000 to 2005. 3) Education and population growth are the main factors of urban growth in Shenzhen, which is reflected in the strongest correlation between university enrolment rate and urban area.

scholarly journals THE CITY OF ADDIS ABABA FROM ‘FOREST CITY’ TO ‘URBAN HEAT ISLAND’: AN ANALYSIS OF URBAN GREEN SPACE DYNAMICS USING REMOTE SENSING AND GEOGRAPHIC INFORMATION SYSTEM

2017 ◽  
Vol 10 (2) ◽  
pp. 254-262
Author(s):  
Mathias Tesfaye Abebe ◽  
Tebarek Lika Megento
Keyword(s):  
Remote Sensing ◽  
Green Space ◽  
Addis Ababa ◽  
Urban Green Space ◽  
Green Spaces ◽  
Urban Green ◽  
Urban Green Spaces ◽  
Gis Tools ◽  
Remote Sensing Techniques ◽  
Space Dynamics

The unprecedented rate of urban growth in developing countries causes various problems such as deficiency in public infrastructure services, lack of green spaces and inadequate service provisions. This study applies GIS tools and remote sensing techniques to assess the effects of urban development on urban green space in Ethiopia’s capital. Spatial and non-spatial datasets were collected from different organizations and processed using GIS tools and remote sensing techniques for land use/ land cover classification and analysis. The analysis demonstrated shrinking of urban green spaces- plantations, forestland, grassland and cultivated land (at annual rates of 5.9%, 3.3%, 5.4% and 3.7 % respectively) by 82.1%, 62.1%, 78.8 and 65.8 % respectively during the past three decades (1986-2015) whereas built-up and transport areas increased at annual rate of 5.7% and 1.3% and consumed 419% and 47% of the city’s total area respectively.

scholarly journals Urban Expansion in Ethiopia from 1987 to 2017: Characteristics, Spatial Patterns, and Driving Forces

2019 ◽  
Vol 11 (10) ◽  
pp. 2973 ◽  
Author(s):  
Berhanu Keno Terfa ◽  
Nengcheng Chen ◽  
Dandan Liu ◽  
Xiang Zhang ◽  
Dev Niyogi
Keyword(s):  
Urban Development ◽  
Spatial Patterns ◽  
Urban Growth ◽  
Driving Forces ◽  
Addis Ababa ◽  
Urban Expansion ◽  
Spatiotemporal Analysis ◽  
Rapid Urbanization ◽  
Master Plans ◽  
Coalescence Theory

Rapid urban growth in major cities of a country poses challenges for sustainable development. Particularly in Africa, the process of rapid urbanization is little understood and research is mostly limited to single cities. Thus, this study provides a comprehensive comparative analysis of the growth and spatial patterns of urban development in the three major cities of Ethiopia (Addis Ababa, Adama, and Hawassa) from 1987 to 2017. Also, the applicability of diffusion and coalescence theory on the evolution of these cities has been tested. Remote sensing and GIS technologies were combined with spatial metrics and morphological analysis was employed to undertake this study. The result revealed that all the studied cities experienced accelerated growth in the urbanized areas, but the cities with a larger initial urbanized size were associated with lower expansion rates. Differences in extent and direction of expansion in each city were mostly related to physical features, urban master plans, and policies, with an increase in the irregularity and dispersion of urban growth, representing strong evidence of urban sprawl. The spatiotemporal analysis confirmed that the urbanization processes of Addis Ababa and Adama were consistent and Hawassa city diverged from expectations based on diffusion and coalescence theory. In general, large cities with strong economic growth in a country fail to effectively control the scattered nature of urban growth, thus requiring aggressive policy intervention. The approach used in this study permits a deeper exploration of urban development patterns and the identification of priority areas for effective urban planning and management.

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