FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4313398132> ?p ?o ?g. }

• W4313398132 endingPage "799" @default.
• W4313398132 startingPage "799" @default.
• W4313398132 abstract "Forests represent the greatest carbon reservoir in terrestrial ecosystems. Climate change drives the changes in forest vegetation growth, which in turn influences carbon sequestration capability. Exploring the dynamic response of forest vegetation to climate change is thus one of the most important scientific questions to be addressed in the precise monitoring of forest resources. This paper explores the relationship between climate factors and vegetation growth in typical forest ecosystems in China from 2007 to 2019 based on long-term meteorological monitoring data from six forest field stations in different subtropical ecological zones in China. The time-varying parameter vector autoregressive model (TVP-VAR) was used to analyze the temporal and spatial differences of the time-lag effects of climate factors, and the impact of climate change on vegetation was predicted. The enhanced vegetation index (EVI) was used to measure vegetation growth. Monthly meteorological observations and solar radiation data, including precipitation, air temperature, relative humidity, and photosynthetic effective radiation, were provided by the resource sharing service platform of the national ecological research data center. It was revealed that the time-lag effect of climate factors on the EVI vanished after a half year, and the lag accumulation tended to be steady over time. The TVP-VAR model was found to be more suitable than the vector autoregressive model (VAR). The predicted EVI values using the TVP-VAR model were close to the true values with the root mean squares error (RMSE) < 0.05. On average, each site improved its prediction accuracy by 14.81%. Therefore, the TVP-VAR model can be used to analyze the relationship of climate factors and forest EVI as well as the time-lag effect of climate factors on vegetation growth in subtropical China. The results can be used to improve the predictability of the EVI for forests and to encourage the development of intensive forest management." @default.
• W4313398132 created "2023-01-06" @default.
• W4313398132 creator A5026528392 @default.
• W4313398132 creator A5058710463 @default.
• W4313398132 creator A5058955724 @default.
• W4313398132 creator A5065168227 @default.
• W4313398132 creator A5067670757 @default.
• W4313398132 creator A5083138275 @default.
• W4313398132 date "2023-01-01" @default.
• W4313398132 modified "2023-09-25" @default.
• W4313398132 title "The Time-Lag Effect of Climate Factors on the Forest Enhanced Vegetation Index for Subtropical Humid Areas in China" @default.
• W4313398132 cites W1969610664 @default.
• W4313398132 cites W2004478864 @default.
• W4313398132 cites W2005840830 @default.
• W4313398132 cites W2019459021 @default.
• W4313398132 cites W2039361154 @default.
• W4313398132 cites W2113410727 @default.
• W4313398132 cites W2115492173 @default.
• W4313398132 cites W2167787089 @default.
• W4313398132 cites W2334695885 @default.
• W4313398132 cites W2750583954 @default.
• W4313398132 cites W2787931125 @default.
• W4313398132 cites W2956365704 @default.
• W4313398132 cites W3002831817 @default.
• W4313398132 cites W3033075976 @default.
• W4313398132 cites W3038212236 @default.
• W4313398132 cites W3039956742 @default.
• W4313398132 cites W3084718445 @default.
• W4313398132 cites W3085762746 @default.
• W4313398132 cites W3123819419 @default.
• W4313398132 cites W3124444187 @default.
• W4313398132 cites W3133662003 @default.
• W4313398132 cites W3138105444 @default.
• W4313398132 cites W3138681513 @default.
• W4313398132 cites W3141197532 @default.
• W4313398132 cites W3161168496 @default.
• W4313398132 cites W3166685400 @default.
• W4313398132 cites W3176161745 @default.
• W4313398132 cites W3178854284 @default.
• W4313398132 cites W3188133710 @default.
• W4313398132 cites W3196708372 @default.
• W4313398132 cites W3198253279 @default.
• W4313398132 cites W3200878966 @default.
• W4313398132 cites W3212443079 @default.
• W4313398132 cites W3212708638 @default.
• W4313398132 cites W4205225306 @default.
• W4313398132 cites W4206332512 @default.
• W4313398132 cites W4307947802 @default.
• W4313398132 cites W4308442046 @default.
• W4313398132 doi "https://doi.org/10.3390/ijerph20010799" @default.
• W4313398132 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36613120" @default.
• W4313398132 hasPublicationYear "2023" @default.
• W4313398132 type Work @default.
• W4313398132 citedByCount "0" @default.
• W4313398132 crossrefType "journal-article" @default.
• W4313398132 hasAuthorship W4313398132A5026528392 @default.
• W4313398132 hasAuthorship W4313398132A5058710463 @default.
• W4313398132 hasAuthorship W4313398132A5058955724 @default.
• W4313398132 hasAuthorship W4313398132A5065168227 @default.
• W4313398132 hasAuthorship W4313398132A5067670757 @default.
• W4313398132 hasAuthorship W4313398132A5083138275 @default.
• W4313398132 hasBestOaLocation W43133981321 @default.
• W4313398132 hasConcept C107054158 @default.
• W4313398132 hasConcept C110872660 @default.
• W4313398132 hasConcept C127313418 @default.
• W4313398132 hasConcept C132651083 @default.
• W4313398132 hasConcept C14168384 @default.
• W4313398132 hasConcept C142724271 @default.
• W4313398132 hasConcept C153294291 @default.
• W4313398132 hasConcept C1549246 @default.
• W4313398132 hasConcept C18903297 @default.
• W4313398132 hasConcept C205649164 @default.
• W4313398132 hasConcept C2776133958 @default.
• W4313398132 hasConcept C2780376076 @default.
• W4313398132 hasConcept C31258907 @default.
• W4313398132 hasConcept C39432304 @default.
• W4313398132 hasConcept C41008148 @default.
• W4313398132 hasConcept C49204034 @default.
• W4313398132 hasConcept C65680412 @default.
• W4313398132 hasConcept C71924100 @default.
• W4313398132 hasConcept C73935091 @default.
• W4313398132 hasConcept C75778745 @default.
• W4313398132 hasConcept C78869512 @default.
• W4313398132 hasConcept C86803240 @default.
• W4313398132 hasConcept C91586092 @default.
• W4313398132 hasConceptScore W4313398132C107054158 @default.
• W4313398132 hasConceptScore W4313398132C110872660 @default.
• W4313398132 hasConceptScore W4313398132C127313418 @default.
• W4313398132 hasConceptScore W4313398132C132651083 @default.
• W4313398132 hasConceptScore W4313398132C14168384 @default.
• W4313398132 hasConceptScore W4313398132C142724271 @default.
• W4313398132 hasConceptScore W4313398132C153294291 @default.
• W4313398132 hasConceptScore W4313398132C1549246 @default.
• W4313398132 hasConceptScore W4313398132C18903297 @default.
• W4313398132 hasConceptScore W4313398132C205649164 @default.
• W4313398132 hasConceptScore W4313398132C2776133958 @default.
• W4313398132 hasConceptScore W4313398132C2780376076 @default.
• W4313398132 hasConceptScore W4313398132C31258907 @default.

• next