scholarly journals Using Remote Sensing in Monitoring the Urban Green Spaces: A Case Study in Qorveh, Iran

2021 ◽  
Vol 2 (1) ◽  
pp. 11-15
Author(s):  
Aynaz Lotfata
Keyword(s):  
Remote Sensing ◽  
Green Space ◽  
Land Development ◽  
Urban Land ◽  
Urban Land Use ◽  
Green Spaces ◽  
Space Distribution ◽  
Mental Wellbeing ◽  
Urban Green ◽  
Urban Green Spaces

Urban green spaces are important to the physical activity, mental wellbeing, and health of urban residents. In medium-sized cities in Iran, urban green spaces have been ignored during the past decades. In this study, remote sensing and geographic information system was used to investigate the green space distribution in the built-up areas. Accordingly, normalized difference vegetation index (NDVI) and normalized difference built-up index (NDBI) were used to estimate urban green spaces distribution within the urban landscapes to measure the urban land use effect. The geospatial analysis results presented a lack of green spaces in built-up areas. Also, 16.8% of the total area of Qorveh city is considered as a dysfunctional urban fabric that 39.4% of the city’s population live in this area. This study highlighted the usage of green space index with geospatial analyses in illustrating the urban green spaces’ importance for planning. For the future urban land development scenarios, this approach could be used linking with regional planning approaches.

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 Remote Sensing–Based Urban Green Space Detection Using Marine Predators Algorithm Optimized Machine Learning Approach

2021 ◽  
Vol 2021 ◽  
pp. 1-22
Author(s):  
Nhat-Duc Hoang ◽  
Xuan-Linh Tran
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Land Use ◽  
Green Space ◽  
Urban Land ◽  
Urban Green Space ◽  
Urban Land Use ◽  
Urban Green ◽  
Marine Predators ◽  
Sentinel 2

Information regarding the current status of urban green space is crucial for urban land-use planning and management. This study proposes a remote sensing and data-driven solution for urban green space detection at regional scale via employment of state-of-the-art metaheuristic and machine learning approaches. Remotely sensed data obtained from Sentinel 2 satellite in the study area of Da Nang city (Vietnam) are used to construct and verify an intelligent model that hybridizes Marine Predators Algorithm (MPA) and support vector machines (SVM). SVM are employed to generalize a decision boundary that separates features characterizing statistical measurements of remote sensing data into two categories of “green space” and “nongreen space”. The MPA metaheuristic is used to optimize the SVM training phase by identifying an appropriate set of the SVM’s hyperparameters including the penalty coefficient and the kernel function parameter. Experimental results show that the proposed model which processes information provided by all of the Sentinel 2 satellite’s spectral bands can deliver a better performance than those obtained from the model based on vegetation indices. With a good classification accuracy rate of roughly 93%, an F1 score = 0.93, and an area under the receiver operating characteristic = 0.98, the newly developed model is a promising tool to assist local authority to obtain up-to-date information on urban green space and develop plans of sustainable urban land use.

scholarly journals ACCOUNTING OF GREEN SPACES BY REMOTE SENSING MATERIALS

2021 ◽  
Vol 4 (2) ◽  
pp. 50-54
Author(s):  
Darya D. Dajbova
Keyword(s):  
Remote Sensing ◽  
Information Systems ◽  
Geographic Information Systems ◽  
Green Space ◽  
Remote Sensing Data ◽  
Green Spaces ◽  
Urban Green ◽  
Urban Green Spaces ◽  
Sensing Data

The article states the necessity of urban green spaces assessment. The current methods of urban green inventory are described. The necessity of modernization of the methods taking into account the achievements of remote sensing and Geographic Information Systems is stated. The basic outline of using of free-of-charge remote sensing data and ground photography data for green spaces inventory is suggested. A case study of using said data for green space inventory of the selected area in Leninsky district of Novosibirck city, Russia, is described.

scholarly journals The Development Simulation of Urban Green Space System Layout Based on the Land Use Scenario: A Case Study of Xuchang City, China

2019 ◽  
Vol 12 (1) ◽  
pp. 326 ◽  
Author(s):  
Jie Liu ◽  
Lang Zhang ◽  
Qingping Zhang
Keyword(s):  
Land Use ◽  
Urban Planning ◽  
Green Space ◽  
Land Development ◽  
Urban Land ◽  
Urban Green Space ◽  
Urban Land Use ◽  
Space System ◽  
Urban Green ◽  
System Layout

The development and evolution of an urban green space system is affected by both natural effects and human intervention. The simulation and prediction of an urban green space system can enhance the foresight of urban planning. In this study, several land use change scenarios of the main urban area of Xuchang City were simulated from 2014 to 2030 based on high-resolution land use data. The layout of each scenario was evaluated using landscape indexes. A Cellular Automata–based method (i.e., future land use simulation, FLUS) was applied to develop the urban green space system, which we combined with urban land use evolution. Using recent data, the FLUS model effectively dealt with the uncertainty and complexity of various land use types under natural and human effects and solved the dependence and error transmission of multiperiod data in the traditional land use simulation process. The root mean square error (RMSE) of probability of the suitability occurrence module and the Kappa coefficient of the overall model simulation accuracy verification index both met accuracy requirements. It was feasible to combine the evolution of the urban green space system with urban land development. Moreover, under the Baseline Scenario, the urban land use layout was relatively scattered, and the urban green space system showed a disordered development trend. The Master Plan Scenario had a compact urban land use layout, and the green space system was characterized by networking and systematization, but it did not consider the service capacity of the green space. The Planning Guidance Scenario introduced constraint conditions (i.e., a spatial development strategy, green space accessibility, and ecological sensitivity), which provided a more intensive and efficient urban space and improved the service function of the green space system layout. Managers and planners can evaluate the urban future land use development mode under different constraints. Moreover, they would be able to adjust the urban planning in the implementation process. This work has transformed the technical nature of the planning work from “static results” to a “dynamic process”.

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 Analyzing the Level of Accessibility of Public Urban Green Spaces to Different Socially Vulnerable Groups of People

2018 ◽  
Vol 10 (11) ◽  
pp. 3917 ◽  
Author(s):  
K Rahman ◽  
Dunfu Zhang
Keyword(s):  
Green Space ◽  
Public Spaces ◽  
Google Earth ◽  
High Density ◽  
Green Spaces ◽  
Vulnerable Groups ◽  
Geographical Data ◽  
Urban Green ◽  
Urban Green Spaces ◽  
Socially Vulnerable Groups

This study estimates the factors affecting socially vulnerable groups’ demand for and accessibility levels to green public spaces in Dhaka City, Bangladesh. Dhaka is a high-density city with one of the lowest levels of green space per capita in the world. Dhaka has just 8.5% of tree-covered lands, while an ideal city requires at least 20% of green space. Urban public green space provides a healthy environment to city dwellers as well as ecological soundness. This study aims to examine the effects of population density and size of a community area (Thana) on the social demand for and accessibility to green parks. To determine the socially vulnerable group demand index, this study used demographic data from the National Population and Housing Census 2011 conducted by the Bangladesh Bureau of Statistics. This study used geographical data extracted from Google Earth Pro to measure accessibility levels, and additionally analyzed geographical data with ArcGIS 10.0 and Google Earth Pro. We drew radius circles using Free Map Tools to measure time-distance weighted scores from community areas to urban green spaces. The results show that the large population size of socially vulnerable groups creates very high demand at the score of 0.61 for urban green public parks and small-sized, high-density community areas generate very good accessibility at 2.01% to green public spaces. These findings are highly useful to policymakers, urban planners, landscape engineers, and city governments to make a compact city sustainable, inclusive, and resilient. Moreover, the notion of a “smart city” might be a smart solution in order to manage Dhaka Megacity sustainably in this modern technological age.

Noise perception assessment in urban green spaces using soundwalk approach

2021 ◽  
Vol 263 (1) ◽  
pp. 5780-5791
Author(s):  
Omid Samani ◽  
Verena Zapf ◽  
M. Ercan Altinsoy
Keyword(s):  
Green Space ◽  
Traffic Noise ◽  
Urban Green Space ◽  
Green Spaces ◽  
Noise Emission ◽  
Visual Effect ◽  
Technical Noise ◽  
Urban Green ◽  
Urban Green Spaces ◽  
The City

Urban green spaces are intended to provide citizens with calm environments free of annoying city noises. This requires a thorough understanding of noise emission and related exposure to sounds in green spaces. This research investigates noise perception in various spots in an urban green space. For this purpose, the study has been conducted in the grand garden of the city of Dresden. The garden covers 1.8 square kilometers of various landscapes, including water streams, park railways, fountains, bridges, roads for bicycles and pedestrians etc. Noise perception was investigated at eleven spots with emphasis on four noise types: nature noise, human noise, traffic noise, and technical noise. In parallel, audio-visual recordings were conducted for each spot to identify the connection between the perceptual measures and the psychoacoustic parameters. These spots are categorized based on the resulting perception and psychoacoustic parameters. In addition, the visual effect of each spot on final perception is investigated. Eventually, annoyance for each spot is identified based on the corresponding participants' perception and is associated with the relevant psychoacoustic parameters.

scholarly journals Assessing the Coverage of Urban Green Space in Butwal Sub-Metropolitan City, Nepal: A GIS based Approach

2018 ◽  
Vol 15 ◽  
pp. 77-86
Author(s):  
Mahendra Singh Thapa ◽  
Gokul Poudel
Keyword(s):  
Green Space ◽  
Urban Environments ◽  
Green Spaces ◽  
Landsat 8 ◽  
Urban Green ◽  
Urban Green Spaces ◽  
Metropolitan City ◽  
Object Oriented Approach ◽  
Materialistic Values ◽  
Urban Places

Urban green spaces are integral part of urban infrastructure. Green spaces can offer a number of benefits ranging from inner spiritual to outer materialistic values. Available green spaces in particular area especially in urban places need to be identified and located properly with scientific way and means so that we can use those places in emergency caused by natural or human induced hazards. This study has tried to measure the green space available for people dwelling in Butwal Sub-Metropolitan City of Nepal. An attempt was made to quantify green spaces in urban environments from Landsat 8 OLI imageries using object-oriented approach and field verification. The study concluded that the total green space available in Butwal Sub-Metropolitan City is 86.37 km2 i.e., around 86% of total municipal area and per capita green space is around 623 m2.

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