{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T00:29:51Z","timestamp":1773707391134,"version":"3.50.1"},"reference-count":46,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2023,10,23]],"date-time":"2023-10-23T00:00:00Z","timestamp":1698019200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Opening Fund of Key Laboratory of Interactive Media Design and Equipment Service Innovation, Ministry of Culture and Tourism","award":["2020 + 11"],"award-info":[{"award-number":["2020 + 11"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>The Yellow River Basin is an important energy base and economic belt in China, but its water resources are scarce, its ecology is fragile, and the task of achieving the goal of carbon peak and carbon neutrality is arduous. Carbon compensation potential can also be used to study the path to achieving carbon neutrality, which can clarify the potential of one region\u2019s carbon sink surplus to be compensated to the other areas. Still, there needs to be more research on the carbon compensation potential of the Yellow River Basin. Therefore, this study calculated the carbon compensation potential using the \u03b2 convergence test and parameter comparison method. With the help of spatial measurement tools such as GIS, GeoDa, Stata, and social network analysis methods, the spatiotemporal pattern and network structure of the carbon compensation potential in the Yellow River Basin were studied from the perspective of urban agglomeration. The results demonstrate the following: (1) The overall carbon compensation rate of the YRB showed a downward trend from 2005 to 2019, falling by 0.94, and the specific pattern was \u201chigh in the northwest and low in the southeast\u201d. The spatial distribution is roughly spread along the east\u2013west axis, and the distribution axis and the center of gravity keep shifting to the northwest. It also showed a weak divergence and a bifurcation trend. (2) The carbon compensation rate in the YRB passed the spatial correlation and \u03b2 convergence tests, demonstrating the existence of spatial correlation and a \u201ccatch-up effect\u201d among cities. (3) The overall distribution pattern of the carbon compensation potential in the YRB is a \u201clow in the west and high in the east\u201d pattern, and its value increased by 8.86% during the sampled period. (4) The network correlation of carbon compensation potential in the YRB has been significantly enhanced, with the downstream region being more connected than the upstream region. (5) The Shandong Peninsula Urban Agglomeration has the largest network center, followed by the Central Plains Urban Agglomeration, and the Ningxia along the Yellow River Urban Agglomeration has the fewest linked conduction paths. According to the research results, accurate and efficient planning and development suggestions are proposed for urban agglomeration in the Yellow River Basin.<\/jats:p>","DOI":"10.3390\/ijgi12100435","type":"journal-article","created":{"date-parts":[[2023,10,23]],"date-time":"2023-10-23T10:32:24Z","timestamp":1698057144000},"page":"435","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Spatiotemporal Pattern of Carbon Compensation Potential and Network Association in Urban Agglomerations in the Yellow River Basin"],"prefix":"10.3390","volume":"12","author":[{"given":"Haihong","family":"Song","sequence":"first","affiliation":[{"name":"Urban and Rural Planning, School of Landscape Architecture, Northeast Forestry University, Harbin 150040, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1471-5878","authenticated-orcid":false,"given":"Yifan","family":"Li","sequence":"additional","affiliation":[{"name":"Urban and Rural Planning, School of Landscape Architecture, Northeast Forestry University, Harbin 150040, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5250-2251","authenticated-orcid":false,"given":"Liyuan","family":"Gu","sequence":"additional","affiliation":[{"name":"Urban and Rural Planning, School of Landscape Architecture, Northeast Forestry University, Harbin 150040, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingnan","family":"Tang","sequence":"additional","affiliation":[{"name":"Urban and Rural Planning, School of Landscape Architecture, Northeast Forestry University, Harbin 150040, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Zhang","sequence":"additional","affiliation":[{"name":"Urban and Rural Planning, School of Landscape Architecture, Northeast Forestry University, Harbin 150040, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,10,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"149352","DOI":"10.1016\/j.scitotenv.2021.149352","article-title":"Synergistic CO2 reduction effects in Chinese urban agglomerations: Perspectives from social network analysis","volume":"798","author":"Shen","year":"2021","journal-title":"Sci. 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