04951nam 2201213z- 450 9910619465703321202210253-0365-5326-6(CKB)5670000000391617(oapen)https://directory.doabooks.org/handle/20.500.12854/93215(oapen)doab93215(EXLCZ)99567000000039161720202210d2022 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierRemote Sensing of Land Surface PhenologyMDPI - Multidisciplinary Digital Publishing Institute20221 online resource (276 p.)3-0365-5325-8 Land surface phenology (LSP) uses remote sensing to monitor seasonal dynamics in vegetated land surfaces and retrieve phenological metrics (transition dates, rate of change, annual integrals, etc.). LSP has developed rapidly in the last few decades. Both regional and global LSP products have been routinely generated and play prominent roles in modeling crop yield, ecological surveillance, identifying invasive species, modeling the terrestrial biosphere, and assessing impacts on urban and natural ecosystems. Recent advances in field and spaceborne sensor technologies, as well as data fusion techniques, have enabled novel LSP retrieval algorithms that refine retrievals at even higher spatiotemporal resolutions, providing new insights into ecosystem dynamics. Meanwhile, rigorous assessment of the uncertainties in LSP retrievals is ongoing, and efforts to reduce these uncertainties represent an active research area. Open source software and hardware are in development, and have greatly facilitated the use of LSP metrics by scientists outside the remote sensing community. This reprint covers the latest developments in sensor technologies, LSP retrieval algorithms and validation strategies, and the use of LSP products in a variety of fields. It aims to summarize the ongoing diverse LSP developments and boost discussions on future research prospects.Environmental science, engineering and technologybicsscHistory of engineering and technologybicsscTechnology: general issuesbicsscarcticautumn phenologycarbon cyclecarbon exchangeclimate changeclimate changesclimatic limitationcontributioncrop sowing datedata suitabilitydevelopment stagedifferent driversdigital cameradriving factorsenhanced vegetation indexevapotranspirationGoogle Earth EngineGPPgross primary productionHangzhouhigh elevationhuman activitiesland surface phenologyland surface temperatureMODISMongolian oakn/aNDPINDVINortheast Chinaphenologyphotosynthesisplant phenologyprocess-based modelQilian MountainsQinghai-Tibetan Plateaurandom forest modelremote sensingsap flowsatellite dataseasonally dry tropical forestsnow coversnow phenologysoil moisturesolar-induced chlorophyll fluorescencespatial scaling effectsspatiotemporal dynamicsspatiotemporal patternsspatiotemporal variationsstructural equation modelthe Loess PlateauThree-River Headwaters regionturning pointurban heat island effecturbanizationvegetation dynamicsvegetation indexesvegetation phenologywater use efficiencyyield gapyield potentialEnvironmental science, engineering and technologyHistory of engineering and technologyTechnology: general issuesMa Xuanlongedt1315239Jin JiaxinedtZhu XiaolinedtZhou YukeedtXie QiaoyunedtMa XuanlongothJin JiaxinothZhu XiaolinothZhou YukeothXie QiaoyunothBOOK9910619465703321Remote Sensing of Land Surface Phenology3032286UNINA