Exploring the interaction mechanism of natural conditions and human activities on wetland ecosystem services value

Xiao, Junzhu; Song, Fei; Su, Fangli; Song, Shuang; Wei, Chao

doi:10.1016/j.jclepro.2023.139161

Cited by 5 publications

(3 citation statements)

References 54 publications

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“…Pan et al, 2014;Seidl et al, 2019). And the increase in land use intensity brought about by urban expansion and other factors inevitably compresses the area of the natural landscape and inhibits RESV growth (Xiao et al, 2023).…”

Section: Factors Driving Changes In Resv and Their Influence Pathwaymentioning

confidence: 99%

Spatio-temporal evolution and driving factors of regulating ecosystem service value: a case study of Poyang Lake Area, China

Liu,

Huang,

Liu

et al. 2024

Front. Ecol. Evol.

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Clarifying the driving mechanisms of spatial and temporal changes in the regulating ecosystem service value (RESV) is an important part of realizing the goal of sustainable development. Existing studies have focused on specific factors, ignoring the complex interactions between factors and their regional differences. In this regard, the spatial and temporal changes of RESV and its driving mechanisms in the different zones (core area, fringe area, and peripheral area) were explored in the Poyang Lake Area, China. The results showed that RESV spatially showed the distribution characteristics of fringe area > core area > peripheral area, while the lakes influenced the provision of regulating ecosystem services, showing that RESV per unit area was higher in the core area, and gradually declined with the increase of distance from the lakes, presenting the decreasing trend of fringe area > peripheral area. From 2000 to 2020, the study area lost 70.5988 billion CNY for RESV, in which the core area was the most affected. Further analysis of the driving mechanism of RESV in different areas found that there are regional differences in the paths of the driving factors: Population density mainly affects the core area, precipitation mainly affects the fringe area, and GDP per land mainly affects the peripheral area.

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Section: Factors Driving Changes In Resv and Their Influence Pathwaymentioning

confidence: 99%

Spatio-temporal evolution and driving factors of regulating ecosystem service value: a case study of Poyang Lake Area, China

Liu,

Huang,

Liu

et al. 2024

Front. Ecol. Evol.

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“…The value of ecosystem services is the benefit that human beings receive directly or indirectly from ecosystems, which is important for maintaining ecological balance and protecting biodiversity (Ran Xiao et al, 2023). From 1990 to 2020, the value of ecosystem services in the central Yunnan urban agglomeration showed a general decreasing trend, with a decreasing rate of 61.23%.…”

Section: Upgrading Development In "Barren" Areas Of Ecosystem Service...mentioning

confidence: 99%

“…It mainly includes the input of useful materials and energy into the economic and social system, the acceptance and transformation of waste from the economic and social system, and the direct provision of services to human society. It involves four categories: provisioning, regulating, supporting, and cultural services (Ran et al, 2023;Vacǩaŕǒváet al, 2023;Xiao et al, 2023;Xu et al, 2023). The level of ecosystem services plays a crucial role in ensuring human production and development (Willemen et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Discriminating the non-coordination between ecosystem service value and economic development and its spatial characteristics in central Yunnan urban agglomeration in the recent 30 years

Li,

Yang,

Niu

et al. 2024

Front. Ecol. Evol.

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Environmental issues have become one of the important topics affecting China and the world. As the world’s most populous country and the second-largest economy, China’s environmental conditions have significant impacts on global ecosystems and sustainable development. To accurately determine the relationship between economic development and the environment, explore the non-coordination and spatial characteristics between the two, and promote regional sustainable development. This study is based on land-use data from four periods: 1990, 2000, 2010, and 2020. It uses the dynamic measurement and value equivalent method to explore the characteristics of land-use changes and measure the value of ecosystem services in the Central Yunnan Urban Agglomeration. At the same time, the study uses the non-coordination degree model and hotspot analysis tools to identify the non-coordination between Ecosystem Service Value and economic development (Gross Domestic Product), and explore the spatial characteristics between them. The research results show that: (1) The main land-use types include cultivated land, forest land, and grassland, which account for more than 90% of the total proportion. The land types with a small proportion in the region are water areas, construction land, and unused land. (2) The development level of ecosystem service value presents four types of changes: fluctuating increase, fluctuating decrease, continuous increase, and continuous decrease. The regional spatial distribution shows obvious regional heterogeneity, overall presenting a spatial distribution pattern of “low in the middle, high around.” (3) The average index of non-coordination degree from 1990 to 2020 is 0.591, 0.635, 0.584, and 0.565, showing a coordinated non-coordination coupling type. The regional space presents a spatial pattern of “high in the central and western regions, low in the northeastern and southern regions.” (4) The hotspots of non-coordination are mainly concentrated in the central and northwest regions of the Central Yunnan Urban Agglomeration, while the coldspots of non-coordination are mainly distributed in the northeastern, western, and southern regions of the Central Yunnan Urban Agglomeration, showing a regular agglomeration distribution. This study suggests that it is necessary to balance and coordinate the relationship between regional economic development and the environment.

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Remote sensing image recognition and monitoring methods for wetland resources in lake areas

Chenjing

2024

Fifth International Conference on Geology, Mapping, and Remote Sensing (ICGMRS 2024)

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The types of wetland resources in lake areas are diverse and complex, and the differences in spectral characteristics of different features can easily lead to a decrease in recognition and monitoring capabilities when extracting wetland remote sensing image information. This article is based on Landsat remote sensing image data. Through image preprocessing and enhancement, spectral and texture features are extracted. Artificial neural networks, maximum likelihood method, random forest and other algorithms are used to extract and classify wetland information, and the classification accuracy and effectiveness of the three methods are compared. The experimental results show that the random forest method reaches 85.18% overall recognition accuracy and 0.8149 Kappa coefficient, which is the most effective in extracting and classifying the features in the lake area. Further extracting the multivariate features of remote sensing data such as spectral features and texture features, the experimental results show that the overall classification accuracy reaches 91.45% and the Kappa coefficient reaches 0.8927, and the classification accuracy is effectively improved.

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Exploring the interaction mechanism of natural conditions and human activities on wetland ecosystem services value

Cited by 5 publications

References 54 publications

Spatio-temporal evolution and driving factors of regulating ecosystem service value: a case study of Poyang Lake Area, China

Spatio-temporal evolution and driving factors of regulating ecosystem service value: a case study of Poyang Lake Area, China

Discriminating the non-coordination between ecosystem service value and economic development and its spatial characteristics in central Yunnan urban agglomeration in the recent 30 years

Remote sensing image recognition and monitoring methods for wetland resources in lake areas

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