Author
Listed:
- Youhai Tang
(School of Architecture, Southwest Jiaotong University, Chengdu 611756, China)
- Jingwen Guo
(School of Architecture, Southwest Jiaotong University, Chengdu 611756, China)
- Linglan Bi
(School of Architecture, Southwest Jiaotong University, Chengdu 611756, China)
Abstract
Tens of thousands of ordinary traditional settlements remain clustered within specific geographic regions of China. Efficient and objective rapid identification of these settlements is crucial for preserving rural cultural heritage. This study takes the traditional settlement Linpan in the Chengdu Plain as a case study, focusing on Pidu District of Chengdu City in Sichuan Province, and proposes an innovative approach for rapid large scale surveys of common traditional settlements using object detection technology. Based on the technical requirements, the spatial characteristics of Linpan settlements in the Chengdu Plain were refined. High-resolution satellite images from 2016 and 2023 of Pidu were processed and cropped, and a diversified training dataset was constructed. After annotation, multiple rounds of training were conducted to develop a detection model based on YOLOv11. The model was then applied to identify thousands of rural settlements across the 438 km 2 area of Pidu, followed by an evaluation of various detection parameters. The results demonstrate that this method can complete the identification of Linpan settlements across the entire Pidu in just 6–7 min, achieving a precision of 96.59% and a recall rate of 94.39%. In terms of efficiency and accuracy, this approach significantly outperforms visual interpretation and remote sensing interpretation methods. Furthermore, based on the detection results, the spatiotemporal distribution characteristics of Linpan settlements during the study period were analyzed. This study aims to improve the surveying methods for traditional villages sand advance their conservation from “static observation” to “dynamic analysis”.
Suggested Citation
Youhai Tang & Jingwen Guo & Linglan Bi, 2025.
"Research on Linpan Identification in Chengdu Plain Based on Object Detection Technology (2016–2023)—A Case Study of PiDu District,"
Land, MDPI, vol. 14(10), pages 1-25, September.
Handle:
RePEc:gam:jlands:v:14:y:2025:i:10:p:1933-:d:1756731
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlands:v:14:y:2025:i:10:p:1933-:d:1756731. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.