Assessing the accessibility of urban green spaces in the central Wuhan based on geographic information system and remote sensing

2021 ◽  
Author(s):  
Zhicheng Tang ◽  
Yiheng Wang ◽  
Zheng Yang ◽  
Yunxiao Jiang ◽  
Luo Guo
Keyword(s):  
Remote Sensing ◽  
Information System ◽  
Geographic Information System ◽  
Geographic Information ◽  
Green Spaces ◽  
Urban Green ◽  
Urban Green Spaces

scholarly journals Establishment of a Geographic Information System-Based Algorithm to Analyze Suitable Locations for Green Roofs and Roadside Trees

2021 ◽  
Vol 11 (16) ◽  
pp. 7368
Author(s):  
Heeju Kim ◽  
Kyushik Oh ◽  
Dongwoo Lee
Keyword(s):  
Information System ◽  
Ecosystem Services ◽  
Geographic Information System ◽  
Urban Areas ◽  
Green Roofs ◽  
Urban Ecosystem ◽  
Geographic Information ◽  
Green Spaces ◽  
Small Scale ◽  
Urban Green Spaces

Urban green spaces offer various ecosystem services such as those for controlling the urban microclimate, improving water circulation, and providing leisure and recreation opportunities. However, it is almost impossible to create new, large green spaces in cities where urbanization has been long underway. Consequently, small-scale green spaces such as green roofs and roadside trees are gaining attention as features that can increase the effects of ecosystem services. Although the area of individual buildings in urban areas is relatively small, the sum of building rooftop areas account for a large portion of urban areas. Moreover, there are areas widely available throughout cities where street trees could be planted. However, this requires large amounts of accurate databases (DBs) and long-term spatial analyses to identify specific locations suitable for small-scale green facilities on a citywide scale using a geographic information system (GIS). Consequently, in-depth research on this topic has been insufficient. Thus, this study presents an algorithm to analyze locations where green roofs and roadside trees could be introduced based on GIS spatial analysis and verifies the effectiveness of the algorithm built for the city of Seoul. In addition, computational fluid dynamics (CFD) modeling is performed to analyze the temperature reduction effect, the representative function of ecosystem control services that can be brought about by the potential green spaces. The results show that rooftop greening in study areas is possible in 311,793 of 742,770 buildings. The rooftop floor area of buildings that can apply rooftop greening is 33,288,745 m2, which is about 50% of the total area of the rooftop in Seoul. It was found that roadside trees could be planted on a sidewalk with an extension length of 872,725 m and an area of 838,864 m2. A total of 145,366 trees can be planted in the study area. In addition, it was shown that the introduction of green roofs reduced temperatures by 0.13 °C to 0.14 °C and roadside trees reduced temperatures by 0.14 °C to 0.6 °C. With the growing need to improve urban ecosystem services as a result of rapid climate change, the algorithm developed in this study can be utilized to create spatial policies that expand and manage urban green spaces and thereby contribute to the improvement of urban ecosystem services.

scholarly journals Mapping Kabul’s Private Urban Green Spaces Using Geographic Information System-Supervised Classification

2020 ◽  
Vol 13 (1) ◽  
pp. 42-60
Author(s):  
Emal Ahmad Hussainzad ◽  
Mohd Johari Mohd Yusof ◽  
Sreetheran Maruthaveeran
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Informal Settlements ◽  
Geographic Information ◽  
Green Spaces ◽  
Urban Green Spaces ◽  
Urban Greenery ◽  
Training Samples ◽  
The Face ◽  
Supervised Image Classification

AbstractPrivate green spaces are considered an important part of urban greenery. However, the extent of private green spaces in an informal city like Kabul is unknown. To this end, this study has mapped out the private green spaces in the informal settlements of Kabul city. A Geographic Information System (GIS)-supervised image classification technique was used to identify these private green spaces in three of the 22 police districts (PDs) in the city. Briefly, the classification consisted of defining training samples, extraction of signature and classification of the imagery. As a result, 330.3 hectares were identified as private green spaces, which made up 12.3 % of the total area of informal settlements in these three districts. With 217.1 hectares, PD7 had the largest area of private green spaces among the three police districts, contributing to 65.7 % of the overall area of private green spaces, followed by PD8 (21.3 %) and PD16 (13 %). In future, the map generated in this study could be used to monitor, manage and conserve the existing urban greenery in the face of private green spaces. The results could also be utilised by the Kabul Municipality and other relevant departments to implement an upgrading programme in the informal settlements of Kabul city, which would lead to fulfilling the environmental needs of the residents.

scholarly journals A Survey of Remote Sensing and Geographic Information System Applications for Flash Floods

2021 ◽  
Vol 13 (9) ◽  
pp. 1818
Author(s):  
Lisha Ding ◽  
Lei Ma ◽  
Longguo Li ◽  
Chao Liu ◽  
Naiwen Li ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Information System ◽  
Geographic Information System ◽  
Flash Flood ◽  
Flash Floods ◽  
Geographic Information ◽  
Flood Disaster ◽  
Future Research ◽  
Time Zone ◽  
Gis Technologies

Flash floods are among the most dangerous natural disasters. As climate change and urbanization advance, an increasing number of people are at risk of flash floods. The application of remote sensing and geographic information system (GIS) technologies in the study of flash floods has increased significantly over the last 20 years. In this paper, more than 200 articles published in the last 20 years are summarized and analyzed. First, a visualization analysis of the literature is performed, including a keyword co-occurrence analysis, time zone chart analysis, keyword burst analysis, and literature co-citation analysis. Then, the application of remote sensing and GIS technologies to flash flood disasters is analyzed in terms of aspects such as flash flood forecasting, flash flood disaster impact assessments, flash flood susceptibility analyses, flash flood risk assessments, and the identification of flash flood disaster risk areas. Finally, the current research status is summarized, and the orientation of future research is also discussed.

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