FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2972912258> ?p ?o ?g. }

• W2972912258 endingPage "2107" @default.
• W2972912258 startingPage "2107" @default.
• W2972912258 abstract "Land surface phenology is a response of vegetation to local climate and to climate change, leading to crucial impacts on plant growth rhythm and productivity. Differences in vegetation growth activities in earlier and latter parts of the growing season are tightly correlated to phenological changes and the temporal distribution of plant productivity. However, its spatiotemporal pattern and climatic constraints are poorly understood. For Northeast China (NEC), long-term remotely-sensed vegetation greenness records (NDVI) were employed to quantify seasonally asymmetrical characteristics of vegetation growth in detail, which consists of asymmetry in growing rate (AsyR), mean vegetation greenness (AsyV), and growing period length (AsyL) during vegetation green up and senescence stages (simply termed as spring and autumn). Furthermore, the impact of temperature and precipitation on these indices were examined using relative importance analysis. The results indicate these asymmetric metrics present a pronounced interannual variability profile with a potential cycle of ten years (significant in AsyV and AsyR) for the entire NEC. AsyV is changing synchronously with AsyL but asynchronously with AsyR. The geographical distribution of asymmetric indices shows a similar pattern to identified vegetation cover types, especially in distinguishing crops from natural vegetation. Spatial-averaged asymmetric indices indicate spring production is greater than autumn production (reflected by negative AsyV) across most vegetation types in NEC, yet autumn is longer than spring in all vegetation types, which is identified by positive AsyL. Negative AsyR is mainly found in forests implying there is rapid green up and slow senescence in trees. From a temporal perspective, AsyV decreases with time in forested regions but increases in cropland and grassland, which is similar to the pattern for AsyL. AsyR primarily exhibits a positive trend in forest and a negative trend in cropland and grassland. A relative importance analysis indicates that asymmetries of temperature (AsyTemp) and precipitation (AsyPrcp) play an equal role in significantly affecting vegetation asymmetries in greenness and growth rate but are insignificant to growing season length. AsyTemp mainly presents an obvious contribution to changes in AsyR and AsyV over cropland and grassland. AsyPrcp shows a more widespread controlling effect on AsyR and AsyV over the NEC, except in eastern broad-leaved forest. For the entire NEC, asymmetries of temperature and precipitation are negatively correlated with AsyR but are positively correlated with AsyV and AsyL. This finding may imply that a warmer (positive AsyTemp) autumn tends to improve the length and intensity of vegetation activity. Thus, the long-term change in vegetation growth asymmetries may provide insights for the altering functions of ecosystems and provide information to more accurately build plant growth models in the context of global climate change. Additionally, when combined with other information, asymmetric indices can serve as a supporting tool in classification of vegetation types." @default.
• W2972912258 created "2019-09-19" @default.
• W2972912258 creator A5059415772 @default.
• W2972912258 date "2019-09-10" @default.
• W2972912258 modified "2023-09-27" @default.
• W2972912258 title "Asymmetric Behavior of Vegetation Seasonal Growth and the Climatic Cause: Evidence from Long-Term NDVI Dataset in Northeast China" @default.
• W2972912258 cites W1795468129 @default.
• W2972912258 cites W1910947081 @default.
• W2972912258 cites W1970268633 @default.
• W2972912258 cites W1973995336 @default.
• W2972912258 cites W1983101872 @default.
• W2972912258 cites W1988100102 @default.
• W2972912258 cites W1995091554 @default.
• W2972912258 cites W1995407148 @default.
• W2972912258 cites W2007468519 @default.
• W2972912258 cites W2022270279 @default.
• W2972912258 cites W2029411945 @default.
• W2972912258 cites W2029857439 @default.
• W2972912258 cites W2034672914 @default.
• W2972912258 cites W2039388573 @default.
• W2972912258 cites W2057387551 @default.
• W2972912258 cites W2072093516 @default.
• W2972912258 cites W2072413429 @default.
• W2972912258 cites W2083702808 @default.
• W2972912258 cites W2096682311 @default.
• W2972912258 cites W2099428109 @default.
• W2972912258 cites W2103497845 @default.
• W2972912258 cites W2115952782 @default.
• W2972912258 cites W2116167682 @default.
• W2972912258 cites W2117189556 @default.
• W2972912258 cites W2120397678 @default.
• W2972912258 cites W2126401154 @default.
• W2972912258 cites W2128257717 @default.
• W2972912258 cites W2131062081 @default.
• W2972912258 cites W2139429070 @default.
• W2972912258 cites W2140844338 @default.
• W2972912258 cites W2151011640 @default.
• W2972912258 cites W2164876780 @default.
• W2972912258 cites W2173213292 @default.
• W2972912258 cites W2211764928 @default.
• W2972912258 cites W2226447297 @default.
• W2972912258 cites W2238813690 @default.
• W2972912258 cites W2280849556 @default.
• W2972912258 cites W2285422781 @default.
• W2972912258 cites W2318680928 @default.
• W2972912258 cites W2336426693 @default.
• W2972912258 cites W2601281019 @default.
• W2972912258 cites W2610782730 @default.
• W2972912258 cites W2773041315 @default.
• W2972912258 cites W2794396966 @default.
• W2972912258 cites W2794421859 @default.
• W2972912258 cites W2885725149 @default.
• W2972912258 cites W2892606152 @default.
• W2972912258 cites W2898867855 @default.
• W2972912258 cites W2900007188 @default.
• W2972912258 cites W2948123395 @default.
• W2972912258 cites W4205550663 @default.
• W2972912258 cites W4232332215 @default.
• W2972912258 cites W4361755798 @default.
• W2972912258 doi "https://doi.org/10.3390/rs11182107" @default.
• W2972912258 hasPublicationYear "2019" @default.
• W2972912258 type Work @default.
• W2972912258 sameAs 2972912258 @default.
• W2972912258 citedByCount "10" @default.
• W2972912258 countsByYear W29729122582020 @default.
• W2972912258 countsByYear W29729122582021 @default.
• W2972912258 countsByYear W29729122582022 @default.
• W2972912258 countsByYear W29729122582023 @default.
• W2972912258 crossrefType "journal-article" @default.
• W2972912258 hasAuthorship W2972912258A5059415772 @default.
• W2972912258 hasBestOaLocation W29729122581 @default.
• W2972912258 hasConcept C100970517 @default.
• W2972912258 hasConcept C107054158 @default.
• W2972912258 hasConcept C127313418 @default.
• W2972912258 hasConcept C132651083 @default.
• W2972912258 hasConcept C137660486 @default.
• W2972912258 hasConcept C139719470 @default.
• W2972912258 hasConcept C142724271 @default.
• W2972912258 hasConcept C153294291 @default.
• W2972912258 hasConcept C1549246 @default.
• W2972912258 hasConcept C162324750 @default.
• W2972912258 hasConcept C18903297 @default.
• W2972912258 hasConcept C204983608 @default.
• W2972912258 hasConcept C205649164 @default.
• W2972912258 hasConcept C2776133958 @default.
• W2972912258 hasConcept C39432304 @default.
• W2972912258 hasConcept C49204034 @default.
• W2972912258 hasConcept C51417038 @default.
• W2972912258 hasConcept C71924100 @default.
• W2972912258 hasConcept C86803240 @default.
• W2972912258 hasConceptScore W2972912258C100970517 @default.
• W2972912258 hasConceptScore W2972912258C107054158 @default.
• W2972912258 hasConceptScore W2972912258C127313418 @default.
• W2972912258 hasConceptScore W2972912258C132651083 @default.
• W2972912258 hasConceptScore W2972912258C137660486 @default.
• W2972912258 hasConceptScore W2972912258C139719470 @default.
• W2972912258 hasConceptScore W2972912258C142724271 @default.
• W2972912258 hasConceptScore W2972912258C153294291 @default.

• next