Identification and factor analysis of rocky desertification severity levels in large-scale karst areas based on deep learning image segmentation

Wang, Yuhao; Tang, Xianghong; Huang, Yong; Yang, Jing; Lu, Jianguang

doi:10.1016/j.ecolind.2024.112565

Ecological Indicators

2024

DOI: 10.1016/j.ecolind.2024.112565

|View full text |Cite

Identification and factor analysis of rocky desertification severity levels in large-scale karst areas based on deep learning image segmentation

Yuhao Wang,

Xianghong Tang,

Yong Huang

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 62 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

High-Resolution Dynamic Monitoring of Rocky Desertification of Agricultural Land Based on Spatio-Temporal Fusion

Zhao,

Zhou,

et al. 2024

Land

View full text Add to dashboard Cite

The current research on rocky desertification primarily prioritizes large-scale surveillance, with minimal attention given to internal agricultural areas. This study offers a comprehensive framework for bedrock extraction in agricultural areas, employing spatial constraints and spatio-temporal fusion methodologies. Utilizing the high resolution and capabilities of Gaofen-2 imagery, we first delineate agricultural land, use these boundaries as spatial constraints to compute the agricultural land bedrock response Index (ABRI), and apply the spatial and temporal adaptive reflectance fusion model (STARFM) to achieve spatio-temporal fusion of Gaofen-2 imagery and Sentinel-2 imagery from multiple time periods, resulting in a high-spatio-temporal-resolution bedrock discrimination index (ABRI*) for analysis. This work demonstrates the pronounced rocky desertification phenomenon in the agricultural land in the study area. The ABRI* effectively captures this phenomenon, with the classification accuracy for the bedrock, based on the ABRI* derived from Gaofen-2 imagery, reaching 0.86. The bedrock exposure area in the farmland showed a decreasing trend from 2019 to 2021, a significant increase from 2021 to 2022, and a gradual decline from 2022 to 2024. Cultivation activities have a significant impact on rocky desertification within agricultural land. The ABRI significantly enhances the capabilities for the dynamic monitoring of rocky desertification in agricultural areas, providing data support for the management of specialized farmland. For vulnerable areas, timely adjustments to planting schemes and the prioritization of intervention measures such as soil conservation, vegetation restoration, and water resource management could help to improve the resilience and stability of agriculture, particularly in karst regions.

show abstract

High-Resolution Dynamic Monitoring of Rocky Desertification of Agricultural Land Based on Spatio-Temporal Fusion

Zhao,

Zhou,

et al. 2024

Land

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Identification and factor analysis of rocky desertification severity levels in large-scale karst areas based on deep learning image segmentation

Cited by 1 publication

References 62 publications

High-Resolution Dynamic Monitoring of Rocky Desertification of Agricultural Land Based on Spatio-Temporal Fusion

High-Resolution Dynamic Monitoring of Rocky Desertification of Agricultural Land Based on Spatio-Temporal Fusion

Contact Info

Product

Resources

About