Dynamic assessment and prediction of land use alterations influence on ecosystem service value: A pathway to environmental sustainability

Roy, Sujit Kumar; Alam, Md. Tauhidul; Mojumder, Pratik; Mondal, Ismail; Kafy, Abdulla - Al; Dutta, Mithun; Ferdous, Md Nahid; Al Mamun, Md. Abdullah; Mahtab, Sania Binte

doi:10.1016/j.indic.2023.100319

Cited by 11 publications

(4 citation statements)

References 33 publications

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“…This approach, characterized by its intuitive nature, ease of use, and minimal data requirements, is particularly suitable for macro-region and continuous-time ESV assessments [50][51][52]. In 1997, Costanza and other American scholars assigned global value coefficients to diverse ecosystems worldwide [53,54]. Subsequently, the Chinese scholar Xie Gaodi revised these coefficients to suit China's specific circumstances, creating a unit area ecological system service value equivalent table for the country [49].…”

Section: Accounting Methods and Formulas For Ecosystem Service Valuementioning

confidence: 99%

The Temporal and Spatial Evolution Characteristics of the Ecosystem Service Value and Conversion Rate in China’s Key State-Owned Forest Regions

Huang,

Li,

Ren

et al. 2024

Forests

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To achieve a sustainable development path that harmonizes ecological and economic considerations, China has advocated the “two mountains” concept: “lucid waters and lush mountains are invaluable assets”. This idea posits that those who protect the environment can economically benefit by selling pristine landscapes and utilizing rich ecological resources. This paper use “the equivalence factor method” to calculate ecological benefits, introduces a technical measure—the conversion rate of ecosystem service value—and analyzes its temporal and spatial evolution from 2003 to 2020 in the operational areas of 87 state-owned forestry enterprises in Northeast China. The findings show: (1) a significant improvement in ecosystem-service quality, with its value increasing from 404.7 to 850.2 billion CNY between 2003 and 2020. The restoration of the ecological environment in China’s KSFR provides a foundation for economic and social development. (2) A decrease in the economic gains derived by operators from developing protected ecosystems, with the most significant decline observed in economic benefits generated from the supply product, including timber harvesting. However, the industrial structure in KSFR shifted from being dominated by timber production to diversified development, with non-timber forest resources becoming an important part of regional economic growth. (3) Significant potential for realizing the value of ecosystem services, evidenced by an increasing trend in the conversion rates of cultural, regulatory, and supporting services. These findings underscore the effectiveness of China’s natural forest protection and restoration policies in optimizing forest ecology and realizing the “two mountains” concept through appropriate market transactions and ecological compensation mechanisms.

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Section: Accounting Methods and Formulas For Ecosystem Service Valuementioning

confidence: 99%

The Temporal and Spatial Evolution Characteristics of the Ecosystem Service Value and Conversion Rate in China’s Key State-Owned Forest Regions

Huang,

Li,

Ren

et al. 2024

Forests

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“…Numerous urban growth models were developed and extensively utilized to study the patterns of urban expansion also, how this could affect the urban ambient environment (Roy et al, 2023). These models could be affiliated with urban policy-making or evaluation of the different development scenarios (Sadooghi et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Urban Growth Modeling in Kurunegala, Sri Lanka using Cellular Automata/Markov Chain Multi-criteria Analysis and Markov-Markovian Transition Estimator

Hasan

2024

Preprint

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With accelerated global urbanization, the expansion of cities has become a pressing concern for urban planners and researchers. The growth and dynamics of urban encroachment are closely tied to changes in land use, especially in urbanized areas. This study seeks to evaluate the accuracy of the CA-Markov (Cellular Automata) model in predicting land use/land cover changes (LULCC) in the Kurunegala district, Sri Lanka as a result of urban expansion. The investigation employs secondary data, including 2007, 2012, 2017, and 2022 Landsat 05, 07, 08, and 09 images respectively. Using software applications such as ArcGIS 10.8, IDRISI 17.0, and MS-Excel 2019, diverse techniques including supervised classification, Markovian transition estimation, and CA-Markov chain analysis, this study attempts to analyze the Urban Growth Modeling for 2027 and 2037 using CA-Markov Chain Multi-criteria Analysis (MCA) under Markov-Markovian Transition Estimator. The study used 32 spatial variables for determining the LULCC. As per the derived results, from 2022 to 2027, urban areas have increased quite markedly. The vegetation cover area has reduced and the areas of water bodies have increased spatially. From 2027 to 2037, the urban area increment is 72.552%. Also, vegetation cover and water body distribution have reduced by 8.051% and 39.91% respectively.

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“…Numerous urban growth models were developed and extensively utilized to study the patterns of urban expansion also, how this could affect the urban ambient environment [11]. These models could be affiliated with urban policy-making or evaluation of the different development scenarios [12].…”

Section: Introductionmentioning

confidence: 99%

Urban Growth Modeling in Kurunegala, Sri Lanka using Cellular Automata/Markov Chain Multi-criteria Analysis and Markov-Markovian Transition Estimator

2024

Eart & Envi Scie Res & Rev

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With accelerated global urbanization, the expansion of cities has become a pressing concern for urban planners and researchers. The growth and dynamics of urban encroachment are closely tied to changes in land use, especially in urbanized areas. This study seeks to evaluate the accuracy of the CA-Markov (Cellular Automata) model in predicting land use/land cover changes (LULCC) in the Kurunegala district, Sri Lanka as a result of urban expansion. The investigation employs secondary data, including 2007, 2012, 2017, and 2022 Landsat 05, 07, 08, and 09 images respectively. Using software applications such as ArcGIS 10.8, IDRISI 17.0, and MS-Excel 2019, diverse techniques including supervised classification, Markovian transition estimation, and CAMarkov chain analysis, this study attempts to analyze the Urban Growth Modeling for 2027 and 2037 using CA-Markov Chain Multi-criteria Analysis (MCA) under Markov-Markovian Transition Estimator. The study used 32 spatial variables for determining the LULCC. As per the derived results, from 2022 to 2027, urban areas have increased quite markedly. The vegetation cover area has reduced and the areas of water bodies have increased spatially. From 2027 to 2037, the urban area increment is 72.552%. Also, vegetation cover and water body distribution have reduced by 8.051% and 39.91% respectively.

show abstract

Dynamic assessment and prediction of land use alterations influence on ecosystem service value: A pathway to environmental sustainability

Cited by 11 publications

References 33 publications

The Temporal and Spatial Evolution Characteristics of the Ecosystem Service Value and Conversion Rate in China’s Key State-Owned Forest Regions

The Temporal and Spatial Evolution Characteristics of the Ecosystem Service Value and Conversion Rate in China’s Key State-Owned Forest Regions

Urban Growth Modeling in Kurunegala, Sri Lanka using Cellular Automata/Markov Chain Multi-criteria Analysis and Markov-Markovian Transition Estimator

Urban Growth Modeling in Kurunegala, Sri Lanka using Cellular Automata/Markov Chain Multi-criteria Analysis and Markov-Markovian Transition Estimator

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