Using SPOT Data and FRAGSTAS to Analyze the Relationship between Plant Diversity and Green Space Landscape Patterns in the Tropical Coastal City of Zhanjiang, China

Cheng, Xuhua; Nizamani, Mir Muhammad; Jim, Chi Yung; Balfour, Kelly; Liu, Da; Qureshi, Salman; Zhu, Zhi‐Xin; Wang, Hua-Feng

doi:10.3390/rs12213477

Cited by 20 publications

(8 citation statements)

References 59 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This finding is consistent with previous studies, concluding that even areas that are highly urbanized are often dynamic in land-cover change [50,52,[81][82][83]. In addition, we found that greenspace turned out to be more fragmented, which is often considered to have a negative impact on biodiversity conservation [84][85] and the regulation of ecosystem service, such as heat mitigation [37]. However, the increased accessibility is largely benefited from the more dispersed greenspace distribution.…”

Section: Fragmented Greenspace Increased Accessibilitysupporting

confidence: 91%

Greenspace to Meet People’s Demand: A Case Study of Beijing in 2005 and 2015

Chen

Huang

2021

Remote Sensing

View full text Add to dashboard Cite

Urban greenspace provides essential benefits and often depends on its distribution and spatial relationship with residents. Many cities set ambitious goals to increase the coverage of greenspace. In addition, to increase the total amount of greenspace, spatial patterns of greenspace supply and demand also need to be taken into account to make sure its ecosystem services can reach the residents. While previous research has examined greenspace distribution, its association with various ecosystem services, and its spatial relationship with residents’ socioeconomic characteristics, relatively few studies have considered the spatial pattern of greenspace demand to assess its supply change over time. To fill this gap, we evaluated the greenspace change of Beijing between 2005 and 2015 using 2.5 m and 0.5 m high resolution remote sensing images. We first identified all of the greenspace changes, then evaluated the improvement of greenspace that was accessible to residents, and finally, we examined whether such improvement met different levels of demand estimated by neighborhood population, age structure, and economic status. The results showed a net increase of 1472 ha (7.8%) from 2005 to 2015. On average, percent greenspace within 500 m of the neighborhood boundary increased from 21% to 24%. Areas with low greenspace supply had a significantly higher increase. The standard deviation reduced from 8% to 7%, which indicated a smaller disparity of accessible greenspace. However, results showed that greenspace increase had little variation among neighborhoods with different demand levels. Our findings indicated that the greening efforts improved spatial distribution and reduced inequality in accessibility but failed to address different demand levels among neighborhoods. Furthermore, we identified neighborhoods with low supply/high demand and that lost greenspace between 2005–2015. These neighborhoods need to be given attention in future greening projects.

show abstract

Section: Fragmented Greenspace Increased Accessibilitysupporting

confidence: 91%

Greenspace to Meet People’s Demand: A Case Study of Beijing in 2005 and 2015

Chen

Huang

2021

Remote Sensing

View full text Add to dashboard Cite

show abstract

“…Due to the high aesthetic quality of the urban green spaces, Zhanjiang was declared a “National Garden City” by the Chinese Ministry of Construction in 2005 [ 37 ]. In 2020, the gross domestic product (GDP) was about 6.46 trillion yuan (RMB) [ 38 ]. With rapid economic development and population growth, Zhanjiang has experienced rapid urban expansion and large areas of agricultural land have been converted to nonagricultural and urban land [ 39 ].…”

Section: Methodsmentioning

confidence: 99%

Investigating the Association between Streetscapes and Mental Health in Zhanjiang, China: Using Baidu Street View Images and Deep Learning

Zhang

Zhai

Liu

et al. 2022

IJERPH

View full text Add to dashboard Cite

Mental health is one of the main factors that significantly affect one’s life. Previous studies suggest that streets are the main activity space for urban residents and have important impacts on human mental health. Existing studies, however, have not fully examined the relationships between streetscape characteristics and people’s mental health on a street level. This study thus aims to explore the spatial patterns of urban streetscape features and their associations with residents’ mental health by age and sex in Zhanjiang, China. Using Baidu Street View (BSV) images and deep learning, we extracted the Green View Index (GVI) and the street enclosure to represent two physical features of the streetscapes. Global Moran’s I and hotspot analysis methods were used to examine the spatial distributions of streetscape features. We find that both GVI and street enclosure tend to cluster, but show almost opposite spatial distributions. The Results of Pearson’s correlation analysis show that residents’ mental health does not correlate with GVI, but it has a significant positive correlation with the street enclosure, especially for men aged 31 to 70 and women over 70-year-old. These findings emphasize the important effects of streetscapes on human health and provide useful information for urban planning.

show abstract

“…Utilizing a 30-meter spatial resolution remote sensing imagery dated June 23, 2020, sourced from Landsat 8, we implemented a supervised classification within the Environment for Visualizing Images 5.3 (ENVI 5.3; L3Harris Geospatial, Colorado, United States) to categorize Haikou's land cover into distinct classes: built-up area, herbaceous (herb) area, tree and shrub area, water area, and undeveloped land (i.e., barren or open land), achieving an overall classification accuracy of 81%. Upon completion of this process, the classified map was utilized as input for FRAGSTATS 4.2.1, adhering to the methodology delineated by Cheng and Nizamani (2020), to compute nine pattern indicators of landscape organization, which are detailed in Table 2. Subsequently, we delved into examining the impact of these indices on broader vegetational patterns of the landscape, particularly in association with spontaneous, cultivated, native, and exotic species.…”

Section: Landscape Indicesmentioning

confidence: 99%

Interplay of socio-economic and environmental factors in shaping urban plant biodiversity: a comprehensive analysis

Zhang,

Nizamani,

Guo

et al. 2024

Front. Ecol. Evol.

Self Cite

View full text Add to dashboard Cite

Urban environments are dynamic landscapes shaped by a multitude of factors, including environmental conditions and socio-economic influences. This study systematically investigates how various factors shape urban plant diversity in Haikou City, Hainan Province, China, focusing on 30 key drivers including socio-economic aspects, biophysical conditions, landscape elements, and management practices. Our research methodology involved a comprehensive analysis of these factors’ impact on six types of urban plant species: spontaneous, native spontaneous, exotic spontaneous, cultivated, native cultivated, and exotic cultivated. Conducted in urban areas with varying population densities and landscape features, our sampling approach aimed to understand the species’ distribution patterns. We discovered significant correlations between plant species diversity and specific environmental and socio-economic variables. Our results indicate that spontaneous species are prevalent in densely populated areas with strong social ties, whereas areas rich in tree and shrub cover see fewer such species. Native cultivated species favor more serene, less urbanized landscapes, while exotic cultivated species are predominantly found in economically affluent areas with diverse vegetation. These findings offer valuable insights for urban planning and biodiversity conservation, emphasizing the need for customized greening strategies that align with local environmental and social contexts. By adopting such tailored approaches, urban planners can more effectively manage landscapes, enrich green spaces, and foster biodiverse, sustainable ecosystems. This research not only enhances our understanding of urban plant biodiversity but also lays the groundwork for future studies and policy-making, promoting harmonious integration of diverse plant life within urban settings.

show abstract

Using SPOT Data and FRAGSTAS to Analyze the Relationship between Plant Diversity and Green Space Landscape Patterns in the Tropical Coastal City of Zhanjiang, China

Cited by 20 publications

References 59 publications

Greenspace to Meet People’s Demand: A Case Study of Beijing in 2005 and 2015

Greenspace to Meet People’s Demand: A Case Study of Beijing in 2005 and 2015

Investigating the Association between Streetscapes and Mental Health in Zhanjiang, China: Using Baidu Street View Images and Deep Learning

Interplay of socio-economic and environmental factors in shaping urban plant biodiversity: a comprehensive analysis

Contact Info

Product

Resources

About