Optical Remote Sensing Method for Detecting Urban Green Space as Indicator Serving City Sustainable Development

Abstract

Urban green space, discovered by optical remote sensors, is the area covered by terrestrial vegetation in urban areas, and is considered an important factor in urban sustainability. Two sensors ALOS/AVNIR-2 and Landsat/OLI&TIR were used in this study to determine green space by Maximum Likelihood Classification method. The investigated area was Nha Trang city, located in the central Vietnam. This was found that the impervious surfaces were rapidly increased leading to significantly reduce urban green space within 10 years from 2007-2017. In urban areas, the green index was very low compared to the TCXDVN 9257: 2012. Based on the Markov chain, it is projected that over the next 10 years, the total vegetation cover of the city will continue to decline compared to that of today. This is likely to lead to increase catastrophe and environmental risks, especially floods and erosion in the coastal city of Nha Trang. The process could be very useful in mapping urban green space as indicator serving city sustainable development.

Assessing Vegetation Cover Change Using Remote Sensing: Case Study at Binh Duong Province, Vietnam

“…The suburb areas such as Long Bien had the green space per capita higher than the national standard of TCVN 9257:2012 with 134.2 m 2 person -1 in 2016. Meanwhile, the center such as Dong Da had a very low green area per capita with only 2.5 m 2 person -1 in 2016 [52]. Another study was conducted in HCMC showed similar results.…”

“…Thus, the ratio of vegetation per capita in industrial areas such as Di An and Thuan An City reduces from 2010 to 2020. Urbanization has been the important factor causing the decrease of green spaces in cities which was mentioned in the previous studies in Vietnam and over the world [52,57,[60][61]. As the consequence, the loss of green space causes negative impacts on the ecosystem and the quality of human life.…”

The Importance of Connected and Interspersed Urban Green and Blue Space for Biodiversity: A Case Study in Cork City, Ireland

“…These habitats have been found to be vitally important for urban biodiversity [33], and when considered together can form corridors and networks through the often-inhospitable matrix. To overcome this within urban ecosystems, remote sensing is the predominant method used for the identification and classification of UGBS [34][35][36][37][38][39][40][41] and has been identified as a powerful method for uncovering these 'invisible' green spaces in the urban framework. Sentinel-2 is the primary sensor utilized in Europe in recent years due to its wide swatch, frequent revisit time, fine spatial resolution (10 m) and zero cost [42][43][44].…”

Synergetic Use of Sentinel-1 and Sentinel-2 Data for Extraction of Built-Up Area in a Rocky Desert Oasis, Example for Draa Tafilalt, South-East of Morocco

“…Novel Sentinel satellites of the Earth observation missions provided by European Space Agency raised a new wave of discussions on synergism of multiple sensor data application for urban extraction in general and radar and optical sensors in particular (Kozlova, 2018;Strozzi et al, 2018 andVan et al, 2018). Although challenged by spatial and spectral heterogeneity of urban environments, optical and synthetic aperture radar (SAR) imagery seem to be suitable sources of reliable information about the multiple facets of urban environments (Corbane, 2008).…”