Article(id=1309574977972691228, tenantId=1146029695717560320, journalId=1308397196074385509, issueId=1309574965775659485, articleNumber=null, orderNo=null, doi=10.11733/j.issn.1007-0435.2026.08.016, pmid=null, cstr=null, oa=null, hot=0, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1761840000000, receivedDateStr=2025-10-31, revisedDate=1764604800000, revisedDateStr=2025-12-02, acceptedDate=null, acceptedDateStr=null, onlineDate=1790156605474, onlineDateStr=2026-09-23, pubDate=null, pubDateStr=null, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1790156605474, onlineIssueDateStr=2026-09-23, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1790156605474, creator=13701087609, updateTime=1790156605474, updator=13701087609, issue=Issue{id=1309574965775659485, tenantId=1146029695717560320, journalId=1308397196074385509, year='2026', volume='34', issue='8', pageStart='2753', pageEnd='3140', issueExtLink='null', onlineDate='null', pubDate='1786723200000', pubDateStr='2026-08-15', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1790156602567, creator='13701087609', updateTime=1790156935415, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1309576361992352087, tenantId=1146029695717560320, journalId=1308397196074385509, issueId=1309574965775659485, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1309576361992352088, tenantId=1146029695717560320, journalId=1308397196074385509, issueId=1309574965775659485, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=2921, endPage=2932, ext={EN=ArticleExt(id=1309574978450841886, articleId=1309574977972691228, tenantId=1146029695717560320, journalId=1308397196074385509, language=EN, title=Evaluation of Degraded Grassland Restoration Effect Based on Multi-source Remote Sensing Data: A Case Study of Alpine Meadow in the Qinghai Section of Qilian Mountain National Park, columnId=null, journalTitle=Acta Agrestia Sinica, columnName=null, runingTitle=null, highlight=null, articleAbstract=Evaluation of the effect of degraded grassland restoration is of crucial for optimizing restoration measures and achieving sustainable utilization of grassland resources. However, current restoration evaluation mainly relies on manual ground surveys, making it difficult to meet the demands of large-scale, long-term dynamic monitoring. This study takes the restoration of degraded alpine grassland in Qilian Mountain National Park as an example. The spatial-temporal adaptive reflectance fusion model and multi-source remote sensing data were used to acquire a high spatial-temporal resolution NDVI dataset. Then the remote sensing estimation models for key grassland parameters were constructed to evaluate the restoration status of degraded grassland. The results show that (1) The models constructed based on high spatiotemporal resolution NDVI exhibited high accuracy, with R values of 0.82 and 0.89 and RMSE values of 12.02% and 32.36 g·m-2 for the coverage and above ground biomass (AGB) models, respectively. (2) The inversion results show that grass growth conditions significantly improved after the implementation of restoration measures (P<0.05), with coverage and AGB reached 1.32-2.17 times and 1.42-3.3 times of the values before the implementation of restoration measures, respectively. (3) Over the past 25 years, coverage and AGB increased at annual rates of 1.24% and 3.23 g·m-2, respectively. The findings of this study provide technical support for evaluating the restoration effects of degraded alpine grasslands and offer a scientific basis for timely adjustments to restoration measures for degraded grasslands., authors=YU Hong-yan1,2, YE Yang-qi3, CHEN Jin3, FENG Shuo3, WANG Zhi-hao3, LUO Shun-hua1, WANG Xian-ying2, HUANG Tao4, QIN Yu4, MENG Bao-ping1, authorsList=YU Hong-yan, YE Yang-qi, CHEN Jin, FENG Shuo, WANG Zhi-hao, LUO Shun-hua, WANG Xian-ying, HUANG Tao, QIN Yu, MENG Bao-ping, authorCompany=1 College of Pratacultural Science, Gansu Agricultural University, Lanzhou, Gansu Province 730070, China; 2 Qinghai Service and Guarantee Center of Qilian Mountain National Park, Xining, Qinghai Province 810001, China; 3 School of Geographic Science, Nantong University, Nantong, Jiangsu Province 226007, China; 4 Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, Gansu Province 730000, China, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1309574978362761501, articleId=1309574977972691228, tenantId=1146029695717560320, journalId=1308397196074385509, language=CN, title=基于多源遥感数据的退化草地修复效果评价研究—以祁连山国家公园青海片区高寒草甸为例, columnId=1309565024058835950, journalTitle=草地学报, columnName=研究论文, runingTitle=null, highlight=null, articleAbstract=退化草地修复效果评价对优化修复措施、实现草地资源可持续利用意义重大。然而,当前修复评价主要依赖人工地面调查,难以满足大范围、长期动态监测需求。本研究以祁连山国家公园退化修复草地为例,基于时空自适应反射率融合模型构建高时空分辨率NDVI数据集,结合地面观测数据构建草地关键参数遥感反演模型并评估草地修复状况。结果表明:(1)基于高分辨率NDVI所构建的模型精度较高,盖度和地上生物量模型R分别为0.82和0.89,RMSE分别为12.02%和32.36 g·m⁻²;(2)模型反演结果表明,修复措施实施后草地生长状况明显好转(P<0.05),草地盖度和地上生物量分别是措施实施前的1.32~2.17倍和1.42~3.3倍;(3)近25年来草地盖度和地上生物量分别以每年1.24%和3.23 g·m⁻²的速度增加。本研究结果可为高寒草地退化修复效果评估提供技术支撑,同时可为及时调整退化草地修复措施提供科学依据。, authors=于红妍1,2, 叶杨琪3, 陈金3, 冯硕3, 王致豪3, 罗顺华1, 王贤颖2, 黄涛4, 秦彧4, 孟宝平1, authorsList=于红妍, 叶杨琪, 陈金, 冯硕, 王致豪, 罗顺华, 王贤颖, 黄涛, 秦彧, 孟宝平, authorCompany=1 甘肃农业大学草业学院, 甘肃 兰州 730070; 2 祁连山国家公园青海服务保障中心, 青海 西宁 810001; 3 南通大学地理科学学院, 江苏 南通 226007; 4 中国科学院西北生态环境资源研究院, 甘肃 兰州 730000, correspAuthors=null, authorNote=于红妍(1978-),女,汉族,山东海阳人,硕士,正高级工程师,主要从事草地生态保护研究,E-mail:qhyuhy@163.com, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=8kI085DFbyt0UA1qQcNuQw==, pdfFileSize=6591768, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=青海省科技计划项目 (2024-ZJ-750); 海北州2022年中央林业草原生态保护恢复资金项目 (北林草[2022]134号); 祁连山国家公园青海片区草地生态系统斑块化格局及其对生态要素影响的研究 (青林保[2025]439号))}, authors=null, keywords=[Keyword(id=1309574978715083039, tenantId=1146029695717560320, journalId=1308397196074385509, articleId=1309574977972691228, language=CN, orderNo=1, keyword=修复效果评价), Keyword(id=1309574978794774816, tenantId=1146029695717560320, journalId=1308397196074385509, articleId=1309574977972691228, language=CN, orderNo=2, keyword=草地盖度), Keyword(id=1309574978866077985, tenantId=1146029695717560320, journalId=1308397196074385509, articleId=1309574977972691228, language=CN, orderNo=3, keyword=地上生物量), Keyword(id=1309574978933186850, tenantId=1146029695717560320, journalId=1308397196074385509, articleId=1309574977972691228, language=CN, orderNo=4, keyword=时空变化), Keyword(id=1309574979134513443, tenantId=1146029695717560320, journalId=1308397196074385509, articleId=1309574977972691228, language=EN, orderNo=1, keyword=Evaluation of restoration effect), Keyword(id=1309574979226788132, 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detailUrlEn=https://castjournals.cast.org.cn/joweb/cdxb/EN/10.11733/j.issn.1007-0435.2026.08.016, pdfUrlCn=https://castjournals.cast.org.cn/joweb/cdxb/CN/PDF/10.11733/j.issn.1007-0435.2026.08.016, pdfUrlEn=https://castjournals.cast.org.cn/joweb/cdxb/EN/PDF/10.11733/j.issn.1007-0435.2026.08.016, aliStartDate=null, aliEndDate=null, collectionFlag=false, citedCount=null, citedUrl=null, previewStatus=0, delFlag=0, hasFullText=0, orderTime=1786723200000, fullTextJson=null, articleText=null, reference=WANG Z W. 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Evaluation of Degraded Grassland Restoration Effect Based on Multi-source Remote Sensing Data: A Case Study of Alpine Meadow in the Qinghai Section of Qilian Mountain National Park
YU Hong-yan1,2, YE Yang-qi3, CHEN Jin3, FENG Shuo3, WANG Zhi-hao3, LUO Shun-hua1, WANG Xian-ying2, HUANG Tao4, QIN Yu4, MENG Bao-ping1
Affiliations
1 College of Pratacultural Science, Gansu Agricultural University, Lanzhou, Gansu Province 730070, China; 2 Qinghai Service and Guarantee Center of Qilian Mountain National Park, Xining, Qinghai Province 810001, China; 3 School of Geographic Science, Nantong University, Nantong, Jiangsu Province 226007, China; 4 Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, Gansu Province 730000, China
Evaluation of the effect of degraded grassland restoration is of crucial for optimizing restoration measures and achieving sustainable utilization of grassland resources. However, current restoration evaluation mainly relies on manual ground surveys, making it difficult to meet the demands of large-scale, long-term dynamic monitoring. This study takes the restoration of degraded alpine grassland in Qilian Mountain National Park as an example. The spatial-temporal adaptive reflectance fusion model and multi-source remote sensing data were used to acquire a high spatial-temporal resolution NDVI dataset. Then the remote sensing estimation models for key grassland parameters were constructed to evaluate the restoration status of degraded grassland. The results show that (1) The models constructed based on high spatiotemporal resolution NDVI exhibited high accuracy, with R values of 0.82 and 0.89 and RMSE values of 12.02% and 32.36 g·m-2 for the coverage and above ground biomass (AGB) models, respectively. (2) The inversion results show that grass growth conditions significantly improved after the implementation of restoration measures (P<0.05), with coverage and AGB reached 1.32-2.17 times and 1.42-3.3 times of the values before the implementation of restoration measures, respectively. (3) Over the past 25 years, coverage and AGB increased at annual rates of 1.24% and 3.23 g·m-2, respectively. The findings of this study provide technical support for evaluating the restoration effects of degraded alpine grasslands and offer a scientific basis for timely adjustments to restoration measures for degraded grasslands.
YU Hong-yan, YE Yang-qi, CHEN Jin, FENG Shuo, WANG Zhi-hao, LUO Shun-hua, WANG Xian-ying, HUANG Tao, QIN Yu, MENG Bao-ping.
Evaluation of Degraded Grassland Restoration Effect Based on Multi-source Remote Sensing Data: A Case Study of Alpine Meadow in the Qinghai Section of Qilian Mountain National Park[J].
Acta Agrestia Sinica,
2026
, 34
(8)
: 2921
-2932
.
DOI: 10.11733/j.issn.1007-0435.2026.08.016
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