Journal of the Indian Society of Remote Sensing, Journal Year: 2024, Volume and Issue: unknown
Published: Dec. 21, 2024
Language: Английский
Journal of the Indian Society of Remote Sensing, Journal Year: 2024, Volume and Issue: unknown
Published: Dec. 21, 2024
Language: Английский
Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)
Published: Feb. 24, 2025
Carbon sink service (CSS) is crucial in addressing global warming and provides theoretical support for research on human‒system coupling. CSS generation, flow, utilization the composite ecosystem of mountains, rivers, forests, farmlands, lakes, grasslands (CEMRFFLG) sustainable development. Quantifying coupled supply‒flow‒demand processes mechanisms CEMRFFLG remains a pressing issue study carbon flows (CSSFs). First, quantify supply demand situation Chongqing. Second, coupling process CSSF among water, forest, farmland, grassland subsystems explored via breakpoint model combined with metacoupling framework. Finally, multiscenario simulation was performed to reveal its flow mechanism. The results show that: (1) Net primary productivity (NPP) mainly comes from emissions (CEs) come farmland. (2) During telecoupling, forest subsystem has highest total value outflow inflow plots, accounting 35.51% 61.24% total, respectively. (3) moves areas human activities. This paper proposes optimization suggestions essential achieving complex ecosystem's
Language: Английский
Citations
0Frontiers in Earth Science, Journal Year: 2025, Volume and Issue: 13
Published: March 10, 2025
Forest ecosystems provide many ecosystem services, and payment for these services has recently become a policy-relevant issue. This paper puts forward multi-function quantitative standard (MQECS) forest based on the Human Development Index six distinct service values. Using MQECS method, i total ecological compensation amount (TECA ) in Guangdong Liaoning provinces 2012 were calculated. The MQECSi of 663.02 225.27 RMB·hm −2 , TECAi 66.82 × 10 8 13.67 RMB, respectively. is approximately three times that Liaoning, government needs to increase investment per unit area by 176.25% 50.20% current achieve target standards. Additionally, method was also applied calculate different cities Liaoning. not only considers local government's ability pay but incorporates factors influencing human wellbeing valuation services. It suitable application management China.
Language: Английский
Citations
0Environment Development and Sustainability, Journal Year: 2025, Volume and Issue: unknown
Published: April 17, 2025
Language: Английский
Citations
0Land, Journal Year: 2024, Volume and Issue: 13(11), P. 1876 - 1876
Published: Nov. 10, 2024
The InVEST model, with its ability to perform spatial visualization and quantification, is an important tool for mapping ecosystem services. However, the accuracy simulating performance of model are deeply influenced by land use parameter, which often relies on use/cover data. To address this issue, we propose a novel method optimizing parameter based vegetation–impervious surface–soil (V–I–S) machine learning algorithm. optimized called Sub-InVEST, it improves assessing services sub-pixel scale. conceptual steps (i) extracting V–I–S fraction remote sensing images spectral unmixing method; (ii) determining relationship between type using algorithm field observation data; (iii) inputting into original instead model. evaluate Sub-InVEST employed habitat quality module multi-source data, were applied acquire estimate central Guangzhou city from 2000 2020 help LSMA ISODATA methods. experimental results showed that robust in sets complex ground scenes. distribution both models revealed consistent increasing trend southwest northeast. Meanwhile, linear regression analyses observed correlation trends, R2 values 0.41, 0.35, 0.42, 0.39, 0.47 years 2000, 2005, 2010, 2015, 2020, respectively. Compared had more favorable estimating Guangzhou. depictions numerical Sub-InVSET manifest greater detail better concordance imagery show seamless density curve substantially enhanced probability across interval ranges.
Language: Английский
Citations
0Journal of the Indian Society of Remote Sensing, Journal Year: 2024, Volume and Issue: unknown
Published: Dec. 21, 2024
Language: Английский
Citations
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