Article(id=1309575101687882236, tenantId=1146029695717560320, journalId=1308397196074385509, issueId=1309575072856240766, articleNumber=null, orderNo=null, doi=10.11733/j.issn.1007-0435.2026.06.025, pmid=null, cstr=null, oa=null, hot=0, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1750089600000, receivedDateStr=2025-06-17, revisedDate=1764864000000, revisedDateStr=2025-12-05, acceptedDate=null, acceptedDateStr=null, onlineDate=1790156634970, onlineDateStr=2026-09-23, pubDate=null, pubDateStr=null, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1790156634970, onlineIssueDateStr=2026-09-23, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1790156634970, creator=13701087609, updateTime=1790156634970, updator=13701087609, issue=Issue{id=1309575072856240766, tenantId=1146029695717560320, journalId=1308397196074385509, year='2026', volume='34', issue='6', pageStart='1963', pageEnd='2340', issueExtLink='null', onlineDate='null', pubDate='1781452800000', pubDateStr='2026-06-15', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1790156628097, creator='13701087609', updateTime=1790156954064, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1309576440438419817, tenantId=1146029695717560320, journalId=1308397196074385509, issueId=1309575072856240766, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1309576440438419818, tenantId=1146029695717560320, journalId=1308397196074385509, issueId=1309575072856240766, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=2229, endPage=2241, ext={EN=ArticleExt(id=1309575104112189951, articleId=1309575101687882236, tenantId=1146029695717560320, journalId=1308397196074385509, language=EN, title=Research on the Spatiotemporal Differentiation Characteristics and Prediction of Grassland Degradation in the Upper Reaches of the Yellow River Based on CA-Markov Model, columnId=null, journalTitle=Acta Agrestia Sinica, columnName=null, runingTitle=null, highlight=null, articleAbstract=Taking the grassland in the upper reaches of the Yellow River Basin as the research object, based on multi-source data from 2000 to 2023, the degradation problem was analyzed from the dual perspectives of “grassland coverage type transformation + degradation evaluation index system”, and the CA-Markov model was used to predict the future degradation pattern. The results showed that: (1) The grassland is mainly composed of medium coverage grassland. Over the past 23 years, the total area of grassland has decreased by 2201.60 km2, and the coverage conversion has fluctuated greatly, showing obvious spatial differentiation characteristics. (2) The proportion of un-degradation grassland has decreased from 59.77% to 54.62%, showed an overall “one decrease and three increases” degradation feature. Spatially, it presented a pattern of “low in the southwest and high in the northeast”, and the area of regions with increased degradation grades was larger than that of regions with decreased grades. (3) By 2030, the proportion of un-degradation grassland will further decline, while the proportions of mild, moderate and severe degradation grassland will increase, and the degradation trend will continue to intensify. The research can provide a scientific basis for regional grassland protection and management., authors=ZHANG Yan1,2, ZHANG Jia-qian1,2, authorsList=ZHANG Yan, ZHANG Jia-qian, authorCompany=1 College of Land Engineering, Chang'an University, Xi'an, Shaanxi Province 710054, China; 2 Key Laboratory of Land Consolidation, Xi'an, Shaanxi Province 710054, 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=1309575103764062717, articleId=1309575101687882236, tenantId=1146029695717560320, journalId=1308397196074385509, language=CN, title=基于CA-Markov模型的黄河流域上游草地退化时空分异特征及预测研究, columnId=1309565024058835950, journalTitle=草地学报, columnName=研究论文, runingTitle=null, highlight=null, articleAbstract=以黄河流域上游草地为研究对象,基于2000—2023年多源数据,结合“草地覆盖度类型转化+退化评价指标体系” 双视角解析退化问题,并运用CA-Markov模型预测未来退化格局。结果表明:(1)草地以中覆盖度草地为主,23年间草地总面积减少2201.60 km²,且覆盖度转换波动大,呈现明显的空间分异特征。(2)未退化草地面积占比由59.77%降至54.62%,整体呈“一降三升”退化特征。空间呈“西南低-东北高”格局,且退化等级升高区面积超过降低区。(3)至2030年,未退化草地比例进一步下降,轻、中、重度退化比例上升,退化态势持续加剧。研究可为区域草地保护与管理提供科学依据。, authors=张艳1,2, 张嘉倩1,2, authorsList=张艳, 张嘉倩, authorCompany=1 长安大学土地工程学院, 陕西 西安 710054; 2 陕西省土地整治重点实验室, 陕西 西安 710054, correspAuthors=null, authorNote=张艳(1978-),女,汉族,河北沧州人,副教授,主要从事土地资源管理、生态安全研究,E-mail:zyzhangyan@chd.edu.cn, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=9Jz8tZY8wYNAl8su6E9IKw==, pdfFileSize=6663979, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, 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Research on the Spatiotemporal Differentiation Characteristics and Prediction of Grassland Degradation in the Upper Reaches of the Yellow River Based on CA-Markov Model
ZHANG Yan, ZHANG Jia-qian
Affiliations
1 College of Land Engineering, Chang'an University, Xi'an, Shaanxi Province 710054, China; 2 Key Laboratory of Land Consolidation, Xi'an, Shaanxi Province 710054, China
Taking the grassland in the upper reaches of the Yellow River Basin as the research object, based on multi-source data from 2000 to 2023, the degradation problem was analyzed from the dual perspectives of “grassland coverage type transformation + degradation evaluation index system”, and the CA-Markov model was used to predict the future degradation pattern. The results showed that: (1) The grassland is mainly composed of medium coverage grassland. Over the past 23 years, the total area of grassland has decreased by 2201.60 km2, and the coverage conversion has fluctuated greatly, showing obvious spatial differentiation characteristics. (2) The proportion of un-degradation grassland has decreased from 59.77% to 54.62%, showed an overall “one decrease and three increases” degradation feature. Spatially, it presented a pattern of “low in the southwest and high in the northeast”, and the area of regions with increased degradation grades was larger than that of regions with decreased grades. (3) By 2030, the proportion of un-degradation grassland will further decline, while the proportions of mild, moderate and severe degradation grassland will increase, and the degradation trend will continue to intensify. The research can provide a scientific basis for regional grassland protection and management.
Key words
Grassland utilization dynamic changes
/
Grassland degradation
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CA-Markov model
/
Upper reaches of the Yellow River Basin
ZHANG Yan, ZHANG Jia-qian.
Research on the Spatiotemporal Differentiation Characteristics and Prediction of Grassland Degradation in the Upper Reaches of the Yellow River Based on CA-Markov Model[J].
Acta Agrestia Sinica,
2026
, 34
(6)
: 2229
-2241
.
DOI: 10.11733/j.issn.1007-0435.2026.06.025
基金
收起
国家自然科学基金项目 (41971033); 陕西省重大科技项目 (2022ZDLSF07-05)
参考文献
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文献
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参考文献引证文献
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