Quantifying the relationship between landscape patterns and ecosystem services along the Urban–rural gradient

Abdollahi, Sedighe; Ildoromi, Alireza; Salmanmahini, Abdolrassoul; Fakheran, Sima; Woźniak, Edyta

doi:10.1007/s11355-023-00561-x

Cited by 3 publications

(1 citation statement)

References 59 publications

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“…Landscape is a mosaic, consisting of various land use type or heterogeneous regions composed of multifarious ecosystems (Turner, 1989;Liu et al, 2020). Therefore, many ecological economists use the number, proportion, area, shape, and spatial distribution that make up ecosystems or land use/cover types to estimate landscape pattern (Liu et al, 2020;Abdollahi et al, 2023). In the process of rapid urban expansion, land use/cover types are constantly undergoing significant changes, which in turn affect the landscape pattern (Dadashpoor et al, 2019;Guo et al, 2021).…”

Section: Open Access Edited Bymentioning

confidence: 99%

Impact of landscape patterns on ecosystem services in China: a case study of the central plains urban agglomeration

Zhong

2024

Front. Environ. Sci.

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Urban agglomeration is the highest stage of urban development, which reasonable planning will be conducive to the rapid and healthy development of the regional economy. However, in recent years, unreasonable urban agglomeration planning has changed landscape patterns and brought huge challenges to ecosystem services. Moreover, there is currently a lack of understanding of the relationship between landscape patterns and ecosystem services, especially in the process of urban agglomeration construction. In this study, we attempt to reveal the impact of landscape patterns on ecosystem services value (ESV) based on many years of remote sensing data in the Central Plains Urban Agglomeration (CPUA). The results show that landscape patterns have significant spatiotemporal evolution characteristics, and there are significant differences between different landscape patterns in the CPUA. Moreover, most of landscape patterns show significant east-west differences. Total ESV has decreased from USD 838.53 million in 2000 to USD 792.32 million in 2018. From a spatial perspective, the areas with high ESV are mostly distributed in the western mountainous and southern hilly areas, but low ESV area are mainly concentrated in the central and northern plains. In addition, the results of model analysis reveal that there is a remarkable positive correlation between ESV and patch density, interspersion juxtaposition index, cohesion index, and splitting index, but a remarkable negative correlation between ESV and total edge. These results provide critical guidance and suggestions for the improvement of future urban agglomeration construction.

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Section: Open Access Edited Bymentioning

confidence: 99%

Impact of landscape patterns on ecosystem services in China: a case study of the central plains urban agglomeration

Zhong

2024

Front. Environ. Sci.

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The marginal effect of landscapes on urban land surface temperature within local climate zones based on optimal landscape scale

Yu,

Zhang,

2024

Urban Climate

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Assessment of Temporal Aggregation of Sentinel-2 Images on Seasonal Land Cover Mapping and Its Impact on Landscape Metrics

Nolasco,

Balzarini

2024

Preprint

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Landscape metrics (LM) play a crucial role in fields such as urban planning, ecology, and environmental research, providing insights into the ecological and functional dynamics of ecosystems. However, in dynamic systems, generating thematic maps for LM analysis poses challenges due to the substantial data volume required and issues such as cloud cover interruptions. The aim of this study was to compare the accuracy of land cover maps produced by three temporal aggregation methods: median reflectance, maximum normalised difference vegetation index (NDVI) and a two-date image stack using Sentinel-2 (S2), and then to analyse their implications for LM calculation. The Google Earth Engine platform facilitated data filtering, image selection, and aggregation while mitigating cloud cover effects. A random forest algorithm was employed to classify five land cover classes across ten sites, with classification accuracy assessed using global measurements and Kappa index. LM were then quantified. The analysis revealed that S2 data provided a high-quality, cloud-free dataset suitable for analysis, ensuring a minimum of 25 cloud-free pixels over the study period. The two-date and median methods exhibited superior land cover classification accuracy compared to the max NDVI method. In particular, the two-date method resulted in lower fragmentation-heterogeneity and complexity metrics in resulting maps compared to the median and max NDVI methods. Nevertheless, median method holds promise for integration into operational land cover mapping programs, particularly for larger study areas exceeding the width of S2 swath coverage. These results highlight the importance of appropriate temporal aggregation techniques when using satellite data for landscape analysis and monitoring.

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Quantifying the relationship between landscape patterns and ecosystem services along the Urban–rural gradient

Cited by 3 publications

References 59 publications

Impact of landscape patterns on ecosystem services in China: a case study of the central plains urban agglomeration

Impact of landscape patterns on ecosystem services in China: a case study of the central plains urban agglomeration

The marginal effect of landscapes on urban land surface temperature within local climate zones based on optimal landscape scale

Assessment of Temporal Aggregation of Sentinel-2 Images on Seasonal Land Cover Mapping and Its Impact on Landscape Metrics

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