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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.

Technology: general issues --- History of engineering & technology --- Environmental science, engineering & technology --- climate change --- digital camera --- MODIS --- Mongolian oak --- phenology --- sap flow --- urbanization --- plant phenology --- spatiotemporal patterns --- structural equation model --- Google Earth Engine --- Three-River Headwaters region --- GPP --- carbon cycle --- arctic --- photosynthesis --- remote sensing --- crop sowing date --- development stage --- yield gap --- yield potential --- process-based model --- land surface temperature --- urban heat island effect --- contribution --- Hangzhou --- land surface phenology --- NDVI --- spatiotemporal dynamics --- different drivers --- random forest model --- data suitability --- satellite data --- spatial scaling effects --- the Loess Plateau --- autumn phenology --- turning point --- climate changes --- human activities --- Qinghai-Tibetan Plateau --- snow phenology --- driving factors --- spatiotemporal variations --- Northeast China --- vegetation indexes --- seasonally dry tropical forest --- vegetation phenology --- climatic limitation --- solar-induced chlorophyll fluorescence --- enhanced vegetation index --- gross primary production --- evapotranspiration --- water use efficiency --- NDPI --- Qilian Mountains --- snow cover --- high elevation --- soil moisture --- vegetation dynamics --- carbon exchange --- n/a

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This book focuses on the up-to-date studies on the sustainability with changing climate and extremes. The main contributors discussed the changing climate and extreme events, as well as their impacts on natural and human dimension sustainability, including the incorporated social–ecologic and socioeconomic processes. Special attention is given to four main sections: natural disasters in agriculture; urban/rural ecosystem, tourism, and ecosystem service; extreme climate indices, and newly created dataset for climate change.

Research & information: general --- Environmental economics --- trade conflict --- carbon emissions --- import and export trade --- cooperative emission reduction --- meteorological hazards --- risk assessment --- spatial pattern --- population exposure --- Qinghai-Tibet Plateau --- climate change --- slope geohazards --- new geohazard clusters --- extreme cooling events --- Arctic Oscillation --- winter in China --- atmospheric circulation --- GPP --- CMIP6 --- ESM --- STA --- China --- warm days --- cold days --- warm nights --- cold nights --- hot days --- frost days --- compound drought and heatwave events --- complex network --- event synchronization --- atmospheric circulation patterns --- urban agglomeration --- drought --- heat wave --- flood --- GM (1, 1) --- Arctic --- universal thermal climate index (UTCI) --- spatial-temporal changes --- 1979–2019 --- ecosystem services trade-offs --- land-use change --- soil conservation --- carbon storage --- water yield --- precipitation gradient --- Loess Plateau --- climate hazards --- geospatial analysis --- urban adaptation --- risk management --- snow disaster --- risk zoning --- Heilongjiang Province --- precipitation --- model resolutions --- cold region of China --- spatiotemporal distribution --- spatiotemporal variation --- 1961–2019 --- high-resolution and high-quality precipitation data --- independent and non-independent test --- the 0.01° multi-source fusion precipitation product --- extreme precipitation event --- forest types --- NDVI --- AVHRR GIMMS --- temperature range --- precipitation range --- snow cover --- black carbon concentration --- radiative forcing --- northeast China --- high temperature --- mobile phone data --- impact factor --- Zhuhai City --- WRF model --- projection --- short-lived heatwave event --- long-lived heatwave event --- Yangtze River Basin --- central and western Pacific --- thermocline --- yellowfin tuna --- CPUE --- El Niño --- La Niña --- GAM model --- spring soil moisture --- impact mechanism --- Songnen Plain --- Sanjiang Plain --- maize --- diurnal temperature range --- fresh air index --- natural microclimate comfort index --- fresh air–natural microclimate comfort index --- scenic spots --- Fujian province --- extreme climate indices --- temporal and spatial dynamics --- linear trend --- climate abrupt change --- central China --- peanut drought --- Shandong Province --- natural disaster risk assessment principles --- dry-hot wind disaster --- Shandong province --- natural disaster risk assessment principle --- summer maize --- inter- and mixed cropping --- flowering period --- yield --- potato climatic productivity potential --- Inner Mongolia --- effect --- human mobility --- rainfall --- taxi GPS data --- community --- Zhuhai central areas --- citrus --- quality --- future projection --- state-owned forest farms --- human resource allocation --- industrial structure --- coordination and adaptation --- personal structure --- contiguous poverty-stricken areas --- rainstorms and droughts --- direct economic losses --- disaster-affected population --- drought and flood --- vulnerability --- risk prediction --- agroecosystem --- heatwaves --- population exposure change --- global warming --- 1.5 °C warming scenario --- 2.0 °C warming scenario --- n/a --- 1979-2019 --- 1961-2019 --- El Niño --- La Niña --- fresh air-natural microclimate comfort index

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Quantitative land remote sensing has recently advanced dramatically, particularly in China. It has been largely driven by vast governmental investment, the availability of a huge amount of Chinese satellite data, geospatial information requirements for addressing pressing environmental issues and other societal benefits. Many individuals have also fostered and made great contributions to its development, and Prof. Xiaowen Li was one of these leading figures. This book is published in memory of Prof. Li. The papers collected in this book cover topics from surface reflectance simulation, inversion algorithm and estimation of variables, to applications in optical, thermal, Lidar and microwave remote sensing. The wide range of variables include directional reflectance, chlorophyll fluorescence, aerosol optical depth, incident solar radiation, albedo, surface temperature, upward longwave radiation, leaf area index, fractional vegetation cover, forest biomass, precipitation, evapotranspiration, freeze/thaw snow cover, vegetation productivity, phenology and biodiversity indicators. They clearly reflect the current level of research in this area. This book constitutes an excellent reference suitable for upper-level undergraduate students, graduate students and professionals in remote sensing.

gross primary production (GPP) --- interference filter --- Visible Infrared Imaging Radiometer Suite (VIIRS) --- cost-efficient --- precipitation --- topographic effects --- land surface temperature --- Land surface emissivity --- scale effects --- spatial-temporal variations --- statistics methods --- inter-annual variation --- spatial representativeness --- FY-3C/MERSI --- sunphotometer --- PROSPECT --- passive microwave --- flux measurements --- urban scale --- vegetation dust-retention --- multiple ecological factors --- leaf age --- standard error of the mean --- LUT method --- spectra --- SURFRAD --- Land surface temperature --- aboveground biomass --- uncertainty --- land surface variables --- copper --- Northeast China --- forest disturbance --- end of growing season (EOS) --- random forest model --- probability density function --- downward shortwave radiation --- machine learning --- MODIS products --- composite slope --- daily average value --- canopy reflectance --- spatiotemporal representative --- light use efficiency --- hybrid method --- disturbance index --- quantitative remote sensing inversion --- SCOPE --- GPP --- South China’s --- anisotropic reflectance --- vertical structure --- snow cover --- land cover change --- start of growing season (SOS) --- MS–PT algorithm --- aerosol --- pixel unmixing --- HiWATER --- algorithmic assessment --- surface radiation budget --- latitudinal pattern --- ICESat GLAS --- vegetation phenology --- SIF --- metric comparison --- Antarctica --- spatial heterogeneity --- comprehensive field experiment --- reflectance model --- sinusoidal method --- NDVI --- BRDF --- cloud fraction --- NPP --- VPM --- China --- dense forest --- vegetation remote sensing --- Cunninghamia --- high resolution --- geometric-optical model --- phenology --- LiDAR --- ZY-3 MUX --- point cloud --- multi-scale validation --- Fraunhofer Line Discrimination (FLD) --- rice --- fractional vegetation cover (FVC) --- interpolation --- high-resolution freeze/thaw --- drought --- Synthetic Aperture Radar (SAR) --- controlling factors --- sampling design --- downscaling --- n/a --- Chinese fir --- MRT-based model --- RADARSAT-2 --- northern China --- leaf area density --- potential evapotranspiration --- black-sky albedo (BSA) --- decision tree --- CMA --- fluorescence quantum efficiency in dark-adapted conditions (FQE) --- surface solar irradiance --- validation --- geographical detector model --- vertical vegetation stratification --- spatiotemporal distribution and variation --- gap fraction --- phenological parameters --- spatio-temporal --- albedometer --- variability --- GLASS --- gross primary productivity (GPP) --- EVI2 --- machine learning algorithms --- latent heat --- GLASS LAI time series --- boreal forest --- leaf --- maize --- heterogeneity --- temperature profiles --- crop-growing regions --- satellite observations --- rugged terrain --- species richness --- voxel --- LAI --- TMI data --- GF-1 WFV --- spectral --- HJ-1 CCD --- leaf area index --- evapotranspiration --- land-surface temperature products (LSTs) --- SPI --- AVHRR --- Tibetan Plateau --- snow-free albedo --- PROSPECT-5B+SAILH (PROSAIL) model --- MCD43A3 C6 --- 3D reconstruction --- photoelectric detector --- multi-data set --- BEPS --- aerosol retrieval --- plant functional type --- multisource data fusion --- remote sensing --- leaf spectral properties --- solo slope --- land surface albedo --- longwave upwelling radiation (LWUP) --- terrestrial LiDAR --- AMSR2 --- geometric optical radiative transfer (GORT) model --- MuSyQ-GPP algorithm --- tree canopy --- FY-3C/MWRI --- meteorological factors --- solar-induced chlorophyll fluorescence --- metric integration --- observations --- polar orbiting satellite --- arid/semiarid --- homogeneous and pure pixel filter --- thermal radiation directionality --- biodiversity --- gradient boosting regression tree --- forest canopy height --- Landsat --- subpixel information --- MODIS --- humidity profiles --- NIR --- geostationary satellite --- South China's --- MS-PT algorithm