Understanding the Spatiotemporal Dynamics and Influencing Factors of the Rice–Crayfish Field in Jianghan Plain, China DOI Creative Commons

Fang Luo,

Yiqing Zhang, Xiang Zhao

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(9), P. 1541 - 1541

Published: April 26, 2024

The rice–crayfish co-culture system, a representative of Agri-aqua food systems, has emerged worldwide as an effective strategy for enhancing agricultural land use efficiency and boosting sustainability, particularly in China Southeast Asia. Despite its widespread adoption China’s Jianghan Plain, the exact spatiotemporal dynamics factors influencing this practice region are yet to be clarified. Therefore, understanding fields (RCFs) is crucial promoting optimizing policies. In study, we identified spatial distribution RCF using Sentinel-2 images data analyze during period 2016–2020. Additionally, used Multiscale Geographically Weighted Regression model explore key RCF’s changes. Our findings reveal that (1). area Plain expanded from 1216.04 km2 2429.76 between 2016 2020, marking 99.81% increase. (2). evolved toward more contiguous clustered pattern, suggesting clear industrial agglomeration area. (3). expansion RCFs was majorly influenced by landscape local conditions. Significantly, Aggregation Landscape Shape Indexes positively impacted expansion, whereas proximity rural areas towns had negative impact. This study provides solid foundation system sustainably developing related industries. To ensure sustainable development industries recommend governments optimize layout settlements, improve transportation infrastructure, enhance regional water sources irrigation construction, all line with national revitalization village planning. concentration contiguity through consolidation can achieve efficient these

Language: Английский

Spatiotemporal variation in determinants of cropland abandonment across Yangtze River Economic Belt, China DOI
Hang Chen,

Yongzhong Tan,

Wu Xiao

et al.

CATENA, Journal Year: 2024, Volume and Issue: 245, P. 108326 - 108326

Published: Aug. 25, 2024

Language: Английский

Citations

3

Evaluation of the efficiency and drivers of complemented cropland in Southwest China over the past 30 years from the perspective of cropland abandonment DOI
Dan Lu, Zhanpeng Wang, Xinxin Li

et al.

Journal of Environmental Management, Journal Year: 2023, Volume and Issue: 351, P. 119909 - 119909

Published: Dec. 28, 2023

Language: Английский

Citations

9

Patterns and drivers of terrace abandonment in China: Monitoring based on multi-source remote sensing data DOI
Dan Lu, Kangchuan Su, Zhanpeng Wang

et al.

Land Use Policy, Journal Year: 2024, Volume and Issue: 148, P. 107388 - 107388

Published: Oct. 21, 2024

Language: Английский

Citations

2

Multi-scenario comparisons to identify the spatial distribution, land type, and effectiveness of cultivated land restoration in the main grain-producing area DOI

Kunyu Liang,

Xiaobin Jin,

Shilei Wang

et al.

Habitat International, Journal Year: 2024, Volume and Issue: 154, P. 103211 - 103211

Published: Nov. 12, 2024

Language: Английский

Citations

2

Identifying and quantifying local uncertainty and discrepancy in the comparison of global cropland extent through a synergistic approach DOI
Xiaojie Liu, Xiaobin Jin,

Xiuli Luo

et al.

Applied Geography, Journal Year: 2023, Volume and Issue: 162, P. 103164 - 103164

Published: Dec. 2, 2023

Language: Английский

Citations

5

One-third of cropland within protected areas could be retired in China for inferior sustainability and effects DOI
Runjia Yang, Wu Xiao, Yanmei Ye

et al.

The Science of The Total Environment, Journal Year: 2023, Volume and Issue: 905, P. 167084 - 167084

Published: Sept. 19, 2023

Language: Английский

Citations

4

Improved Cropland Abandonment Detection with Deep Learning Vision Transformer (DL-ViT) and Multiple Vegetation Indices DOI Creative Commons
Mannan Karim, Jiqiu Deng, Muhammad Ayoub

et al.

Land, Journal Year: 2023, Volume and Issue: 12(10), P. 1926 - 1926

Published: Oct. 16, 2023

Cropland abandonment is a worldwide problem that threatens food security and has significant consequences for the sustainable growth of economy, society, natural ecosystem. However, detecting mapping abandoned lands challenging due to their diverse characteristics, like varying vegetation cover, spectral reflectance, spatial patterns. To overcome these challenges, we employed Gaofen-6 (GF-6) imagery in conjunction with Vision Transformer (ViT) model, harnessing self-attention multi-scale feature learning significantly enhance our ability accurately efficiently classify land covers. In Mianchi County, China, study reveals approximately 385 hectares cropland (about 2.2% total cropland) were between 2019 2023. The highest annual occurred 2021, 214 hectares, followed by 170 primary reason was transformation into excavation activities, barren lands, roadside greenways. ViT’s performance peaked when multiple indices (VIs) integrated GF-6 bands, resulting achieved results (F1 score = 0.89 OA 0.94). Our represents an innovative approach integrating ViT 8 m multiband composite precise identification analysis short-term patterns, marking distinct contribution compared previous research. Moreover, findings have broader implications effective use management, resource optimization, addressing complex challenges field.

Language: Английский

Citations

4

Responses of soil microbial biomass carbon and microbial entropy to soil properties in typical sloping croplands of China under erosion conditions DOI
Yuan Li, Shengzhao Wei, Hongna Wang

et al.

European Journal of Soil Biology, Journal Year: 2024, Volume and Issue: 122, P. 103660 - 103660

Published: Aug. 12, 2024

Language: Английский

Citations

1

Spatiotemporal nonlinear characteristics and threshold effects of China's water resources DOI
Youzhu Zhao, Luchen Wang, Qiuxiang Jiang

et al.

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 373, P. 123633 - 123633

Published: Dec. 6, 2024

Language: Английский

Citations

1

Understanding the Spatiotemporal Dynamics and Influencing Factors of the Rice–Crayfish Field in Jianghan Plain, China DOI Creative Commons

Fang Luo,

Yiqing Zhang, Xiang Zhao

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(9), P. 1541 - 1541

Published: April 26, 2024

The rice–crayfish co-culture system, a representative of Agri-aqua food systems, has emerged worldwide as an effective strategy for enhancing agricultural land use efficiency and boosting sustainability, particularly in China Southeast Asia. Despite its widespread adoption China’s Jianghan Plain, the exact spatiotemporal dynamics factors influencing this practice region are yet to be clarified. Therefore, understanding fields (RCFs) is crucial promoting optimizing policies. In study, we identified spatial distribution RCF using Sentinel-2 images data analyze during period 2016–2020. Additionally, used Multiscale Geographically Weighted Regression model explore key RCF’s changes. Our findings reveal that (1). area Plain expanded from 1216.04 km2 2429.76 between 2016 2020, marking 99.81% increase. (2). evolved toward more contiguous clustered pattern, suggesting clear industrial agglomeration area. (3). expansion RCFs was majorly influenced by landscape local conditions. Significantly, Aggregation Landscape Shape Indexes positively impacted expansion, whereas proximity rural areas towns had negative impact. This study provides solid foundation system sustainably developing related industries. To ensure sustainable development industries recommend governments optimize layout settlements, improve transportation infrastructure, enhance regional water sources irrigation construction, all line with national revitalization village planning. concentration contiguity through consolidation can achieve efficient these

Language: Английский

Citations

0