Author
Listed:
- Xingsheng Xia
(Academy of Plateau Science and Sustainability, Qinghai Normal University, Xining 810016, China
School of Geographical Sciences, Qinghai Normal University, Xining 810008, China
These authors contributed equally to this work.)
- Wei Liang
(Academy of Plateau Science and Sustainability, Qinghai Normal University, Xining 810016, China
School of Geographical Sciences, Qinghai Normal University, Xining 810008, China
These authors contributed equally to this work.)
- Shenghui Lv
(Academy of Plateau Science and Sustainability, Qinghai Normal University, Xining 810016, China
School of Geographical Sciences, Qinghai Normal University, Xining 810008, China)
- Yaozhong Pan
(Academy of Plateau Science and Sustainability, Qinghai Normal University, Xining 810016, China
State Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing 100875, China)
- Qiong Chen
(Academy of Plateau Science and Sustainability, Qinghai Normal University, Xining 810016, China
School of Geographical Sciences, Qinghai Normal University, Xining 810008, China)
Abstract
Alpine grasslands, a crucial component of the Qinghai–Tibet Plateau, play a vital role in maintaining ecological barriers and facilitating sustainable development, and the exact stability change is also the key to coping with climate change and implementing ecological protection projects. The purpose of this study was to identify the spatial and temporal distribution of multi-stage alpine grassland and explore its inter-annual distribution and growth stability. The Guoluo Tibetan Autonomous Prefecture, China (hereinafter referred to as Guoluo), where alpine grassland is widely distributed, was selected as the research area. Long-term stable grassland samples constructed using the Mann–Kendall–Sneyers mutation test method were analyzed alongside random forest classification to identify multi-stage grassland distribution trends from 1990 to 2020. Based on the Fractional Vegetation Cover (FVC) and coefficient of variation ( C v ), spatial and temporal changes in grassland quality and their driving factors were discussed. The results show the following: (1) Remote sensing grassland extraction, based on the establishment of long-term stable grassland samples and random forest classification, demonstrated high accuracy and reliability, with OA and Kappa coefficients consistently above 0.89 and 0.77, and PA and UA maintained consistently at approximately 0.9. (2) The distribution of grassland in Guoluo corresponded to the spatial patterns determined by the natural geographical environment, showing a gradual trend from high-cover grassland in the southeast to low-cover grassland in the northwest. The proportion of medium and high-cover grasslands slightly increased, indicating an improvement in grassland quality. However, the encroachment and degradation caused by human activities and climate change resulted in a slight decrease in the proportion of grassland area compared with 1990. (3) Despite the overall grassland ecosystem still having relative stability, local grassland quality changes dramatically, mainly in the north of Maduo County. And significant fluctuations in the area of grassland quality were noted over the last two decades, suggesting potential degradation in ecosystem stability. Climate change and human activities were identified as primary drivers of these changes. Climate change is dominant in the alpine region. The low-warming region is dominated by human activities. These findings offer essential insights for the planning and implementation of alpine grassland ecosystem protection and restoration initiatives and also have important value for exploring the evolution law of alpine grassland ecosystems.
Suggested Citation
Xingsheng Xia & Wei Liang & Shenghui Lv & Yaozhong Pan & Qiong Chen, 2024.
"Remote Sensing Identification and Stability Change of Alpine Grasslands in Guoluo Tibetan Autonomous Prefecture, China,"
Sustainability, MDPI, vol. 16(12), pages 1-19, June.
Handle:
RePEc:gam:jsusta:v:16:y:2024:i:12:p:5041-:d:1414042
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:jsusta:v:16:y:2024:i:12:p:5041-:d:1414042. 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.