High-Resolution Dynamic Monitoring of Rocky Desertification of Agricultural Land Based on Spatio-Temporal Fusion DOI Creative Commons
Xin Zhao, Zhongfa Zhou,

Guijie Wu

et al.

Land, Journal Year: 2024, Volume and Issue: 13(12), P. 2173 - 2173

Published: Dec. 13, 2024

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

Language: Английский

Threshold analysis of the key factors of rocky desertification evolution in the typical karst region of China DOI Creative Commons
Kun Wang, Ling Han, Juan Liao

et al.

All Earth, Journal Year: 2025, Volume and Issue: 37(1), P. 1 - 14

Published: March 7, 2025

Language: Английский

Citations

0
High-Resolution Dynamic Monitoring of Rocky Desertification of Agricultural Land Based on Spatio-Temporal Fusion DOI Creative Commons
Xin Zhao, Zhongfa Zhou,

Guijie Wu

et al.

Land, Journal Year: 2024, Volume and Issue: 13(12), P. 2173 - 2173

Published: Dec. 13, 2024

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

Language: Английский

Citations

0