Spatial differentiation and scenario simulation of cultivated land in mountainous areas of Western Hubei, China: a PLUS model

Han, Peng; Xiang, Jingwei; Zhao, Qinglin

doi:10.1007/s11356-023-26128-9

Cited by 8 publications

(5 citation statements)

References 44 publications

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“…It is also suitable for simulating regions of larger scales with high simulation accuracy [34]. In this study, we compared our results with those of other studies ( [29,[34][35][36]; the specific results are shown in Table 6) and found that our kappa coefficients were 0.92 and 0.89, respectively. This indicates that our simulation accuracy is high, which has certain advantages in accuracy and provides more reference value.…”

Section: The Plus Model Is Suitable For Simulating Land Use-type Data...mentioning

confidence: 75%

“…This module combines the top-down and bottom-up structural mechanisms, connecting random seed generation with the decreasing threshold. Under the constraints of development probability and the number of land uses, it automatically simulates the generation of land use patches with the following calculation formula [29]:…”

Section: The Plus Modelmentioning

confidence: 99%

“…This shows that optimizing land use structure is beneficial to reducing the pollution load. Existing studies by Zhu [42], Lin [30], and Han [29] et al have shown that the ecological protection scenario is conducive to pollution control or the improvement of environmental risk through multi-scenario simulation of point source pollution.…”

Section: Land Use Pattern Optimization Plays An Important Role In The...mentioning

confidence: 99%

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Evolutionary Trend Analysis of Agricultural Non-Point Source Pollution Load in Chongqing Based on Land Use Simulation

Zhu,

Zhang,

Tian

et al. 2024

Agronomy

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Analysis of the relationship between future land use change and agricultural non-point source pollution (ANPSP) evolution is vital to promoting sustainable regional development. By simulating future land use types, we can identify and analyze the evolution trend of ANPSP. This study takes Chongqing as a case study to establish an integrated solution based on the PLUS model, output coefficient model, and GIS technology. The solution can simulate data, identify trends, and identify key control areas under future development scenarios. The results show that the PLUS model can simulate land use types at the provincial scale with high accuracy, with a Kappa coefficient of around 0.9. The land use type changes show that urban expansion has occupied a large amount of cultivated land. From 2000 to 2020, the proportion of high-load areas with TN pollution load levels was 4.93%, 5.02%, and 4.73%, respectively. Under the two scenarios in 2030–2050, the number of high-load areas decreased, and the average load level decreased from west to east. Sensitivity analysis found that risk changes are more sensitive to the increase in fertilizer application. When the TN and TP output coefficients are increased, the number of towns with increased levels is greater than those with decreased levels when the output coefficients are decreased. Sensitivity analysis can better identify key pollution control areas. The areas sensitive to changes in farmers’ behavior are mainly the Hechuan District, Nanchuan District, Qijiang District, Jiangjin District, and Bishan District. This study provides data and decision-making support for rural green development and water environment improvement.

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Section: The Plus Model Is Suitable For Simulating Land Use-type Data...mentioning

confidence: 75%

Section: The Plus Modelmentioning

confidence: 99%

Section: Land Use Pattern Optimization Plays An Important Role In The...mentioning

confidence: 99%

See 1 more Smart Citation

Evolutionary Trend Analysis of Agricultural Non-Point Source Pollution Load in Chongqing Based on Land Use Simulation

Zhu,

Zhang,

Tian

et al. 2024

Agronomy

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“…To explore land-use changes in the YRB under different development goals based on Chinese watershed policy and previous experience [36,37], this paper sets up four different LUCC transformation matrices to predict and simulate land use in the Yangtze River Basin in 2030. Natural development scenario (NDS): the parameters are not adjusted based on the extrapolation of existing trends.…”

Section: Setting Of Future Scenariosmentioning

confidence: 99%

Temporal and Spatial Variations in Landscape Habitat Quality under Multiple Land-Use/Land-Cover Scenarios Based on the PLUS-InVEST Model in the Yangtze River Basin, China

Guo

Wang

et al. 2023

Land

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Despite the Yangtze River Basin (YRB)’s abundant land and forestry resources, there is still a dearth of research on forecasting habitat quality changes resulting from various geographic and environmental factors that drive landscape transformations. Hence, this study concentrates on the YRB as the focal area, with the aim of utilizing the Patch Landscape Upscaling Simulation model (PLUS) and the habitat quality model to scrutinize the spatial distribution of landscape patterns and the evolution of HQ under four scenarios: the natural development scenario (NDS), farmland protection scenario (CPS), urban development scenario (UDS), and ecological protection scenario (EPS), spanning from the past to 2030. Our results show that (1) from 2000 to 2020, the construction land in the YRB expanded at a high dynamic rate of 47.86% per year, leading to a decrease of 32,776 km2 in the cultivated land area; (2) the UDS had the most significant expansion of construction land, followed by the NDS, CPS, and EPS, which had higher proportions of ecologically used land such as forests and grasslands; (3) from 2000 to 2020, the HQ index ranged from 0.211 to 0.215 (low level), showing a slight upward trend, with the most drastic changes occurring in the low-level areas (−0.49%); (4) the EPS had the highest HQ (0.231), followed by the CPS (0.215), with the CPS increasing the HQ proportion of the lower-level areas by 2.64%; (5) and in addition to government policies, NDVI, DEM, GDP, and population were also significant factors affecting landscape pattern and changes in habitat quality.

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“…Furthermore, the advantageous part of the pattern analysis strategy, based on the emergent probability and competition mechanism combined with the seed growth mechanism and a multi-objective algorithm, is that it can more accurately analyze the land use change and reflect a more realistic landscape state. Currently, few studies have applied the model for the quantitative assessment of carbon stocks in national park ecosystems [44].…”

Section: Land Use Change Drivers and Scenario Simulation Analysismentioning

confidence: 99%

China’s National Park Construction Contributes to Carbon Peaking and Neutrality Goals

Wang

Song

Shi

et al. 2023

Land

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The official establishment of China’s national parks marks a new stage in the construction of China’s ecological civilization system. National parks systematically protect the areas with the richest biodiversity and the most complete ecosystem processes in China. This is beneficial not only for China’s natural conservation work, but also for the world’s response to environmental issues, such as climate change. Based on remote sensing images of land use in the four periods 1990, 2000, 2010, and 2020, this study calculated the land use changes in each national park during the corresponding period. Using the Plus model LEAS module, the driving factors of land use change in the national parks were studied and explored. In addition, the study used the InVEST model carbon storage module, using remote sensing images from different periods and the corresponding carbon pools of each national park as the basic data for model operation, to obtain the carbon storage changes in each national park over the past 30 years. Based on the hotspot analysis function, the hotspot areas of carbon storage changes in the national parks in the past 30 years were determined. Consequently, based on the CARS module of the PLUS model, the carbon storage in Northeast Tiger and Leopard National Park in 2030 was estimated under different scenarios. Research suggested that, except for Sanjiangyuan National Park where grassland is the main land use type, the other four national parks are all dominated by forests, and the expansion and changes in the main land use types were due to human activities. In the past 30 years, the carbon storage in China’s national park ecosystem has mainly shown a trend of first increasing and then gradually decreasing. Based on the changes in carbon storage in the national park, restoration scenarios were simulated for the core protected and generally controlled areas of Northeast Tiger and Leopard National Park. Under the ideal scenario, the highest value of carbon storage would be achieved by 2030, which would be 7,468,250 t higher than that in 2020. The present study provides a reference for the regional management of China’s national parks and further confirms that the implementation of the national park system can enhance China’s ability to achieve carbon peaking and neutrality goals.

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Spatial differentiation and scenario simulation of cultivated land in mountainous areas of Western Hubei, China: a PLUS model

Cited by 8 publications

References 44 publications

Evolutionary Trend Analysis of Agricultural Non-Point Source Pollution Load in Chongqing Based on Land Use Simulation

Evolutionary Trend Analysis of Agricultural Non-Point Source Pollution Load in Chongqing Based on Land Use Simulation

Temporal and Spatial Variations in Landscape Habitat Quality under Multiple Land-Use/Land-Cover Scenarios Based on the PLUS-InVEST Model in the Yangtze River Basin, China

China’s National Park Construction Contributes to Carbon Peaking and Neutrality Goals

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