Data Description: Landslides in the Qinling Mountains, China
This dataset contains vector boundary information of landslides in the Qinling region of China. Landslides are a significant geological hazard, crucial for geological risk assessment, land use planning, and disaster management. This dataset aims to provide a detailed description of the landslide distribution in the Qinling area to facilitate related research and applications.
Data Content:
Quantity: It includes vector boundaries of 169,888 landslides.
Validation Check: In this version of the dataset, 2000 landslide boundaries have undergone validation checks. These boundaries have been meticulously verified to ensure data accuracy and reliability.
Update Plan: Following the completion of validation checks, the remaining landslide boundaries will be validated and uploaded incrementally. This ensures continuous improvement and updates of the dataset to reflect the latest landslide distribution in the Qinling Mountains.
Data Utility:
Scientific Research: Researchers can use this dataset to study the distribution and evolution patterns of landslides in the Qinling Mountains and their correlation with geological and topographical factors.
Geological Risk Assessment: Government agencies and geological experts can use this dataset for geological hazard risk assessment to develop effective response strategies.
Land Use Planning: Based on the landslide distribution, rational land use planning can be carried out to reduce losses caused by geological disasters.
Data Format:
The data is presented in vector boundary format, making it easy to process and analyze in GIS software.
The dataset uses a common geographic information data format, facilitating integration and interaction with other geographic data.
Data Source:
The data is derived from optical image interpretation, combined with extensive literature review and previous research work. This approach ensures comprehensive coverage and accurate identification of landslide boundaries in the Qinling Mountains.
Data Quality Assurance:
The data undergoes strict quality control and validation checks to ensure its accuracy and reliability.
The dataset’s update plan guarantees continuous updates and improvements to meet user needs and application scenarios.
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