Revealing the Impact of Protected Areas on Land Cover Volatility in China DOI Creative Commons
Yajuan Wang,

Yongheng Rao,

Zhu Hong-bo

et al.

Land, Journal Year: 2022, Volume and Issue: 11(8), P. 1361 - 1361

Published: Aug. 21, 2022

Protected areas are fundamental for maintaining ecosystem functions and have generally been considered to affect land use change. Here, we explored how protected affected cover volatility in China from 2011 2020 with LandTrendr using the Google Earth Engine (GEE) platform by comparing difference of Normalized Difference Vegetation Index (NDVI) unprotected areas. The results show that regions frequent mainly located eastern, central, southwestern China, indicating high NDVI loss values is spatially aggregated most cases. Considering impact areas, relatively consistent inside outside area throughout study period, showing a trend first fluctuating then rising. Approximately 22% detected occurred though average value (0.56) was greater than (0.51). Combined outliers, accompanied larger still primarily distributed years. detection gain shows (average 0.48) 0.47) almost every year, even combined also Elucidating helpful understanding changes formulate an effective policy.

Language: Английский

Dynamic simulation and projection of land use change using system dynamics model in the Chinese Tianshan mountainous region, central Asia DOI
Zhengrong Zhang, Xuemei Li, Xinyu Liu

et al.

Ecological Modelling, Journal Year: 2023, Volume and Issue: 487, P. 110564 - 110564

Published: Nov. 11, 2023

Language: Английский

Citations

17

Predicting Land Use Changes under Shared Socioeconomic Pathway–Representative Concentration Pathway Scenarios to Support Sustainable Planning in High-Density Urban Areas: A Case Study of Hangzhou, Southeastern China DOI Creative Commons
Song Yao, Yonghua Li, Hezhou Jiang

et al.

Buildings, Journal Year: 2024, Volume and Issue: 14(7), P. 2165 - 2165

Published: July 14, 2024

Amidst the challenges posed by global climate change and accelerated urbanization, structure distribution of land use are shifting dramatically, exacerbating ecological land-use conflicts, particularly in China. Effective resource management requires accurate forecasts cover (LUCC). However, future trajectory LUCC, influenced remains uncertain. This study developed an integrated multi-scenario framework combining system dynamics patch-generating simulation models to predict LUCC high-density urban regions under various Shared Socioeconomic Pathway (SSP)–Representative Concentration (RCP) scenarios. The results showed following: (1) From 2020 2050, cultivated land, unused water projected decrease, while construction is expected increase. (2) Future patterns exhibit significant spatial heterogeneity across three Construction will expand all districts Hangzhou, main areas. Under SSP585 scenario, expansion most significant, it least SSP126 scenario. (3) Distinct factors drive different types. digital elevation model predominant factor for forest grassland, contributing 19.25% 30.76%, respectively. Night light contributes at 13.94% 20.35%, (4) average intensity (LUI) central markedly surpasses that surrounding suburban areas, with Xiacheng having highest LUI Chun’an lowest. area increased significantly smaller than SSP245 These findings offer valuable guidance sustainable planning built environment Hangzhou similarly situated centers worldwide.

Language: Английский

Citations

5

An Algorithm of Forest Age Estimation Based on the Forest Disturbance and Recovery Detection DOI
Zihao Huang, Xuejian Li, Huaqiang Du

et al.

IEEE Transactions on Geoscience and Remote Sensing, Journal Year: 2023, Volume and Issue: 61, P. 1 - 18

Published: Jan. 1, 2023

Forest age is a crucial parameter for evaluating the state and potential of carbon sequestration in forest ecosystems. However, lack time-series will lead to an inability capture disturbance restoration history, resulting increased uncertainty estimating sinks. To address this issue, we aimed propose integrated algorithm estimation based on recovery using Zhejiang Province forests as example. Based Google Earth Engine (GEE) platform, first used random (RF) estimate 2004, then LandTrendr with RF detect loss gain year during 2005-2019, finally derived mapped time series distribution from 2004 2019. The results show that: (1) R 2 (≥0.6) xmlns:xlink="http://www.w3.org/1999/xlink">RMSE (≤5 years) revealed that constructed models could high reliability; (2) effectively extracted regions overall accuracies (OAs) above 0.7, while area has net increase 2206.86 km 2005-2019; (3) 2019 was still dominated by young middle-aged forests, shift dominance 20-30 30-40 years old after 2013. This study provided effective methodological idea reliable basic data past future

Language: Английский

Citations

13

Coupling video vision transformer (ViVit) into land change simulation: a comparison with three-dimensional convolutional neural network (3DCNN) DOI

Haiyang Li,

Liang Fan, Yifan Gao

et al.

Journal of Spatial Science, Journal Year: 2024, Volume and Issue: 69(3), P. 873 - 895

Published: Feb. 26, 2024

To enhance land use/cover change (LUCC) simulation accuracy, we introduced ViViT-ANN-CA, blending video vision transformer's spatio-temporal features extraction ability, artificial neural network's (ANN) non-linearity computing and CA's spatial computing. Compared to 3DCNN-ANN-CA, ViViT-ANN-CA showed higher accuracy in simulating water bodies vegetation, with overall improvements Hailing District Wuxi City. ViViT demonstrates comparable feature ability three-dimensional convolutional network (3DCNN), promising for future ynamic LUCC simulations.

Language: Английский

Citations

4

Coupled and Coordinated Relationship between Land-Use Cover Change and Ecosystem Services Value in Horqin Sandy Land DOI Open Access
Zhidan Ba, Huishi Du, Yujie Zhao

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(14), P. 6184 - 6184

Published: July 19, 2024

In this study, an ecosystem service value evaluation method was applied to establish a coupling coordination degree model, quantify the and relationship between land-use cover change changes, examine impacts of different driving factors on changes. The results were as follows. (1) 2020, these two variables peaked at level above 0.9. (2) Their one in 2000, indicating transformative shift entry into new stage during period within study area. This provides valuable information for development ecological compensation restoration strategies Horqin Sandy Land’s civilization construction plan.

Language: Английский

Citations

4

Impacts of land use and crop structure change on the value of ecosystem services in Hetao Irrigation District of China DOI
Lin Yang, Shengwei Zhang, Meng Luo

et al.

Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: unknown, P. 144113 - 144113

Published: Oct. 1, 2024

Language: Английский

Citations

4

Integrating LUCC and forest aging to project and attribute subtropical forest NEP in Zhejiang Province under four SSP-RCP scenarios DOI Creative Commons
Zihao Huang, Xuejian Li, Fangjie Mao

et al.

Agricultural and Forest Meteorology, Journal Year: 2025, Volume and Issue: 365, P. 110462 - 110462

Published: Feb. 27, 2025

Language: Английский

Citations

0

Spatiotemporal Coupling Assessment of Human–Nature Relationships in Ecologically Sensitive Areas Under Intensive Anthropogenic Activities DOI

C. Li,

Weichen Mu,

Fen Qin

et al.

Published: Jan. 1, 2025

Language: Английский

Citations

0

Spatiotemporal Coupling Assessment of Human–Nature Relationships in Ecologically Sensitive Areas Under Intensive Anthropogenic Activities DOI

C. Li,

Weichen Mu,

Fen Qin

et al.

Published: Jan. 1, 2025

Language: Английский

Citations

0

Predicting land use/land cover changes using CA-Markov and LCM models in the metropolitan area of Mashhad, Iran DOI
Hossein Aghajani,

Farnaz Sarkari,

Mehdi Fattahi Moghaddam

et al.

Modeling Earth Systems and Environment, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 24, 2024

Language: Английский

Citations

3